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@@ -0,0 +1,1071 @@
+1
+00:00:01,180 --> 00:00:03,500
+بسم الله الرحمن الرحيم الصلاة والسلام على رسول
+
+2
+00:00:03,500 --> 00:00:09,210
+اللهِ أهلاً وسهلاً بكم في محاضرة جديدة من وثائق تقييم
+
+3
+00:00:09,210 --> 00:00:12,350
+البيانات. اليوم، إن شاء الله، هنتكلم على الـ second
+
+4
+00:00:12,350 --> 00:00:16,890
+mining task أو الـ third mining task اللي هي الـ
+
+5
+00:00:16,890 --> 00:00:20,750
+clustering. طبعاً، إحنا كنا بنتكلم سابقاً أن الـ
+
+6
+00:00:20,750 --> 00:00:24,490
+mining task تنقسم من الـ predictive أو الـ
+
+7
+00:00:24,490 --> 00:00:26,870
+descriptive، و الـ predictive اتكلمنا عن الـ
+
+8
+00:00:26,870 --> 00:00:28,990
+classification و الـ regression و الـ recommendation.
+
+9
+00:00:28,990 --> 00:00:31,470
+اليوم، طبعاً، الـ recommendation ما شرحناها عشان
+
+10
+00:00:31,470 --> 00:00:34,170
+اتكلمنا عن classification و regression. واليوم، إن
+
+11
+00:00:34,170 --> 00:00:36,710
+شاء الله تعالى، هنتكلم.. نبدأ في الـ descriptive
+
+12
+00:00:36,710 --> 00:00:41,370
+task. هنتكلم على الـ clustering. طب لما إحنا بنتكلم
+
+13
+00:00:41,370 --> 00:00:43,910
+على الـ clustering، بنتكلم على unsupervised learning.
+
+14
+00:00:43,910 --> 00:00:46,750
+و هذا نوع من الـ machine learning اللي بتعلم من الـ
+
+15
+00:00:46,750 --> 00:00:51,650
+test data. يعني أنا بهمني إنه البيانات تبعتي مايكونش
+
+16
+00:00:51,650 --> 00:00:55,030
+لها label. هذا مفهوم الـ test data، إن الـ test data
+
+17
+00:00:55,030 --> 00:00:59,090
+إنه الـ label مش موجود، that has not been labeled.
+
+18
+00:00:59,090 --> 00:01:04,580
+مالهاش label classified or categorized، ما تمش
+
+19
+00:01:04,580 --> 00:01:09,020
+تصنيفها أو تقسيمها قبل هيك. بالـ unsupervised
+
+20
+00:01:09,020 --> 00:01:14,400
+learning، على خلاف كل الـ machine learning، مافيش
+
+21
+00:01:14,400 --> 00:01:19,420
+عندي output معروف مسبقاً، وبالتالي مافيش عندي
+
+22
+00:01:19,420 --> 00:01:22,320
+teacher أو instruction، مافيش عندي أي structure للـ
+
+23
+00:01:22,320 --> 00:01:25,700
+learning algorithm. ف حين إنه في الـ supervised
+
+24
+00:01:25,700 --> 00:01:28,020
+learning، سواء كان في الـ regression أو كان في الـ
+
+25
+00:01:28,020 --> 00:01:32,840
+classification، كان عندي واضح الـ label، هو الـ
+
+26
+00:01:32,840 --> 00:01:36,180
+guidance تبعي، أو هو المعلم تبعي. إيه الشغلات اللي
+
+27
+00:01:36,180 --> 00:01:39,260
+أنا بدي إياها، وإيه الـ role اللي أنا كنت بحاول أحصل
+
+28
+00:01:39,260 --> 00:01:41,920
+عليها. الـ unsupervised learning، الـ learning
+
+29
+00:01:41,920 --> 00:01:47,880
+algorithm فقط بأعرض عليه البيانات، وبطلب يعمل
+
+30
+00:01:47,880 --> 00:01:50,840
+extract للـ knowledge. طبعاً، extract للـ knowledge، هان
+
+31
+00:01:50,840 --> 00:01:54,500
+إما بتقسيمهم لمجموعات، أو يقول لي إيش الـ frequent
+
+32
+00:01:54,500 --> 00:01:57,720
+pattern فيهم. زي ما في الـ association rules، إلى
+
+33
+00:01:57,720 --> 00:02:02,710
+آخرين. طبعاً، لما اتكلم في الـ unsupervised learning،
+
+34
+00:02:02,710 --> 00:02:06,530
+بدل
+
+35
+00:02:06,530 --> 00:02:11,390
+ما أنا آخذ feedback و
+
+36
+00:02:11,390 --> 00:02:15,070
+أقارب الـ unsupervised learning، بعرف الـ
+
+37
+00:02:15,070 --> 00:02:19,510
+communities، أو الشغلات المشتركة في الـ data، الشغلات
+
+38
+00:02:19,510 --> 00:02:23,230
+الـ common اللي موجودة، اللي بتتشارك فيها معظم
+
+39
+00:02:23,230 --> 00:02:28,960
+الـ instances اللي موجودة عندي. وبتقرر.. وبت.. اللي
+
+40
+00:02:28,960 --> 00:02:32,640
+بعرف.. بعد ما بتقرر على الشغلات الـ common هاي، أو
+
+41
+00:02:32,640 --> 00:02:36,760
+الشغلات المشتركة هاي، بناءً عليها بتتصرف. إما بتقرر
+
+42
+00:02:36,760 --> 00:02:41,420
+.. يعني بتتصرف، وبصير الـ algorithm بناءً على وجود أو
+
+43
+00:02:41,420 --> 00:02:45,940
+عدم وجود الـ properties أو الـ common properties
+
+44
+00:02:45,940 --> 00:02:49,440
+اللي موجودة عنده. يعني، يعني تخيل أنا لو أنا في عندي
+
+45
+00:02:49,440 --> 00:02:53,910
+مجموعة من الصور، وقلنا بدنا نصنفهم، مجموعة من الصور،
+
+46
+00:02:53,910 --> 00:02:56,290
+و أنا بدي أصنفهم، معناته حتى اللي عرف المحتوى الصور،
+
+47
+00:02:56,290 --> 00:03:01,830
+وأصير أقول لك والله إن التصنيف هذا بيتبع كده، أو يتبع كده.
+
+48
+00:03:01,830 --> 00:03:05,230
+الـ unsupervised learning، زي ما قلنا، عبارة عن
+
+49
+00:03:05,230 --> 00:03:09,330
+descriptive model. في أكتر من نوع في الـ
+
+50
+00:03:09,330 --> 00:03:11,590
+unsupervised learning، زي ما بنعرف سابقاً، لـ
+
+51
+00:03:11,590 --> 00:03:14,630
+clustering. طبعاً، شفناها في المقدمة، تابعة للمساق، لـ
+
+52
+00:03:14,630 --> 00:03:18,930
+clustering. معناته أنا بدي أجسم الـ data instances
+
+53
+00:03:18,930 --> 00:03:27,350
+اللي موجودة عندي، لمجموعة من الـ groups. طبعاً، مجموع
+
+54
+00:03:27,350 --> 00:03:32,050
+الـ groups هذه، عددها معروف مسبقاً. طب من هنا، علشان
+
+55
+00:03:32,050 --> 00:03:35,870
+نتم تجميعهم، بدنا ندرس صفات الـ properties هاي،
+
+56
+00:03:35,870 --> 00:03:38,970
+و تجميعهم مع بعضهم. الـ anomaly detection أو الـ
+
+57
+00:03:38,970 --> 00:03:42,030
+outlier detection، أروح أدور على الـ unusual، أو
+
+58
+00:03:42,030 --> 00:03:48,270
+الشغلات النادرة في الـ data set اللي موجودة عندها، و
+
+59
+00:03:48,270 --> 00:03:53,390
+أظهرها. الـ association rules، لما أنا بتكلم على الـ
+
+60
+00:03:53,390 --> 00:03:58,570
+patterns، و بدور على الـ frequent pattern اللي ممكن
+
+61
+00:03:58,570 --> 00:04:02,410
+تكون موجودة عندي، و ارتباط العناصر، وأشوف ارتباط
+
+62
+00:04:02,410 --> 00:04:06,660
+القوانين، أو ارتباط الـ data مع بعضها، عشان أقدر أبني
+
+63
+00:04:06,660 --> 00:04:10,060
+decision. وفي عندي transformation، اللي هي فعلياً أنا
+
+64
+00:04:10,060 --> 00:04:13,760
+أقدر أحول الـ data لـ data set مختلفة، عشان أقدر
+
+65
+00:04:13,760 --> 00:04:18,480
+أرسمها، أو أقدر أتعامل معاها بشكل أبسط. إحنا طبعاً،
+
+66
+00:04:18,480 --> 00:04:22,980
+هنتكلم على الـ course هذا، الـ clustering و الـ
+
+67
+00:04:22,980 --> 00:04:27,600
+association rules. طبعاً، لما نتكلم فعلياً، الـ
+
+68
+00:04:27,600 --> 00:04:31,380
+clustering، معناته الـ clustering algorithm بده يروح
+
+69
+00:04:31,380 --> 00:04:36,680
+يجسم الـ data set اللي عندي، لـ distinct groups. الجروب
+
+70
+00:04:36,680 --> 00:04:42,780
+هذه، معروفة مسبقاً. تخيل
+
+71
+00:04:42,780 --> 00:04:48,320
+إن الـ raw data تبعتي، هي عبارة عن سلة الفواكه رمضان
+
+72
+00:04:48,320 --> 00:04:51,600
+كريم، إن شاء الله، كل عام وأنتم طيبين، إن شاء الله، سلة
+
+73
+00:04:51,600 --> 00:04:54,580
+الفواكه، هي عبارة عن الـ input data، الـ raw data
+
+74
+00:04:54,580 --> 00:05:00,580
+تبعتي، وأنا قلت بدي أجسمها لثلاث مجموعات. طبيعى الـ
+
+75
+00:05:00,580 --> 00:05:05,060
+algorithm هيدرس خصائص العناصر كلياتها، يعرف العناصر
+
+76
+00:05:05,060 --> 00:05:08,260
+المشتركة، ويحدد العناصر المشتركة، وبالتالي هيقول لي
+
+77
+00:05:08,260 --> 00:05:12,700
+في عندك مجموعة التفاح، ومجموعة الموز، ومجموعة
+
+78
+00:05:12,700 --> 00:05:17,360
+المانجو. هذا لما قلت له جسم ليها لثلاث مجموعات.
+
+79
+00:05:17,360 --> 00:05:19,940
+متذكرين الـ definition السابق؟ أنا قلت لها
+
+80
+00:05:19,940 --> 00:05:25,040
+predefined أو predetermined number of groups، لازم
+
+81
+00:05:25,040 --> 00:05:30,110
+أحدده مسبقاً. تمام. طيب، لو أنا روحت قلت له لمجموعتين،
+
+82
+00:05:30,110 --> 00:05:35,970
+روحت قلت له جسم ليّ إياها لمجموعتين، مش ثلاث مجموعات،
+
+83
+00:05:35,970 --> 00:05:42,070
+دراسة العناصر هاي، وهيروح وكأنه هيقول لي إنه هذه
+
+84
+00:05:42,070 --> 00:05:45,990
+أنا بتوقع إنه يكون هذه التفاح والمانجو في مجموعة، و
+
+85
+00:05:45,990 --> 00:05:49,690
+الموز في مجموعة ثانية، لأن الشكل واللون مختلف، بعاد
+
+86
+00:05:49,690 --> 00:05:54,430
+كتير عن بعضهم. وبالتالي، عدد المجموعات هو اللي بيلعب
+
+87
+00:05:54,430 --> 00:05:57,370
+دوراً. طبعاً يا جماعة الخير، كل ما كان عندي عدد
+
+88
+00:05:57,370 --> 00:06:00,950
+المجموعات اللي أنا بديّ إياها، تبعتي، هو الصح، معناته أنا
+
+89
+00:06:00,950 --> 00:06:04,370
+بشتغل عليها بشكل كويس، أو بكون عندي النتيجة تبعتي
+
+90
+00:06:04,370 --> 00:06:09,310
+صح. لما بتكلم في الـ clustering، معناته أنا بتكلم إن
+
+91
+00:06:09,310 --> 00:06:13,250
+الـ method تبعتي، هي الـ.. الـ.. أو الـ clustering هي
+
+92
+00:06:13,250 --> 00:06:17,470
+عبارة عن method بتجسم البيانات اللي بتشارك
+
+93
+00:06:19,620 --> 00:06:26,360
+الصفات المشتركة، أو الـ similar trend and better.
+
+94
+00:06:26,360 --> 00:06:32,520
+يعني إن الـ instances هتتوزع بناءً على محتوى، على
+
+95
+00:06:32,520 --> 00:06:36,820
+احتوائها على مجموعة من الشغلات المشتركة. يعني هيكون
+
+96
+00:06:36,820 --> 00:06:40,140
+في عندي تشابه كبير جداً ما بين العناصر اللي في
+
+97
+00:06:40,140 --> 00:06:45,200
+المجموعة الواحدة. الهدف الأساسي فعلياً من الـ
+
+98
+00:06:45,200 --> 00:06:48,660
+clustering، معناته هو عبارة عن split up، تقسيم الـ
+
+99
+00:06:48,660 --> 00:06:56,200
+data، بطريقة، طبعاً، بتقسمها لـ groups، بطريقة إن النقاط
+
+100
+00:06:56,200 --> 00:06:59,220
+اللي في الـ cluster الواحد، أو في المجموعة الواحدة
+
+101
+00:06:59,220 --> 00:07:03,820
+are very similar، متشابهة جداً. عشان هيك كانت في
+
+102
+00:07:03,820 --> 00:07:08,920
+الرسم السابق، هان لما اتكلمنا، كان التفاح لحال،
+
+103
+00:07:08,920 --> 00:07:12,400
+المانجو لحال، والموز لحال. ولما قلت لك أنا بقسمهم
+
+104
+00:07:12,400 --> 00:07:16,460
+لمجموعتين، مش لثلاث مجموعات، معناته تقول إحنا هنا
+
+105
+00:07:16,460 --> 00:07:21,980
+نضيفهم على بعضهم. لكن الآن، إيش الشغلات المشتركة
+
+106
+00:07:21,980 --> 00:07:25,280
+اللي أنت اعتمدت عليها؟ الحجم مثلاً، واللون. لكن لو
+
+107
+00:07:25,280 --> 00:07:27,640
+واحد يجي يقول لي والله أنا بقسمهم هالنا مجموعتين،
+
+108
+00:07:27,640 --> 00:07:32,400
+بناءً على طبيعة الفاكهة اللي موجودة هاي، وبالتالي،
+
+109
+00:07:32,400 --> 00:07:35,660
+إحنا نتكلم، في عندي فواكه استوائية، الـ mango و الموز،
+
+110
+00:07:35,660 --> 00:07:42,040
+فاكهة استوائية ولا لأ. وبالتالي، ممكن يكون تصنيف في
+
+111
+00:07:42,040 --> 00:07:46,540
+الآخر. ما فيش عندي قرار صحيح مئة في المئة، أن
+
+112
+00:07:46,540 --> 00:07:50,520
+التقسيمة تبعتي هذه صح، أو.. لكن بقدر أقول والله
+
+113
+00:07:50,520 --> 00:07:53,820
+التقسيمة هذه أصح من هذه التقسيمة، بناءً على معرفتي
+
+114
+00:07:53,820 --> 00:07:56,640
+بالبيانات اللي موجودة عندها. طبعاً، الـ similarity،
+
+115
+00:07:56,640 --> 00:08:01,640
+طبعاً، التشابه ما بين الـ algorithm for the
+
+116
+00:08:01,640 --> 00:08:03,600
+unsupervised learning و الـ classification
+
+117
+00:08:03,600 --> 00:08:08,820
+algorithm، إنه الـ cluster algorithm بيخصص، أو بِتنبأ
+
+118
+00:08:08,820 --> 00:08:11,780
+رقم المجموعة
+
+119
+00:08:14,590 --> 00:08:16,970
+للـ point. يعني أنا روحت قلت له والله أنا بدي ثلاث
+
+120
+00:08:16,970 --> 00:08:19,850
+مجموعات، بروح بقول له هذه الـ point في المجموعة رقم
+
+121
+00:08:19,850 --> 00:08:22,830
+واحد، هذه الـ point في المجموعة رقم اثنين، هذه الـ
+
+122
+00:08:22,830 --> 00:08:25,090
+point في المجموعة رقم ثلاثة، هذه الـ point في
+
+123
+00:08:25,090 --> 00:08:29,550
+المجموعة رقم ثلاثة. وبالتالي، هو بيعمل predict لرقم
+
+124
+00:08:29,550 --> 00:08:32,370
+المجموعة اللي أنا قلته من البداية، عشان أنا قلت له
+
+125
+00:08:32,370 --> 00:08:37,550
+بدي ثلاث مجموعات، فهو هيجسم ليّ إياها لثلاث مجموعات. طبعاً، و
+
+126
+00:08:37,550 --> 00:08:39,950
+هذه هي المفهوم، التشابه اللي أنا بتكلم عليه، إنهم
+
+127
+00:08:39,950 --> 00:08:45,040
+بنعمل prediction للـ number، بحيث إنه فعلياً، كما زي
+
+128
+00:08:45,040 --> 00:08:48,480
+ما قلنا، إن هذا الـ number هي عبارة عن رقم المجموعة
+
+129
+00:08:48,480 --> 00:08:51,620
+أو رقم الـ cluster اللي بيحتوي الـ point اللي موجودة
+
+130
+00:08:51,620 --> 00:08:57,000
+عندها. طبعاً،
+
+131
+00:08:57,000 --> 00:08:59,820
+لما بتكلم على الـ clustering، معناته إن أنا بدي آخذ
+
+132
+00:08:59,820 --> 00:09:07,020
+بيانات كلها في نفس الـ space. بتكلم على بيانات كلها
+
+133
+00:09:07,020 --> 00:09:13,040
+في نفس الـ space، في مجموعات معينة. يعني هذا الـ space
+
+134
+00:09:13,040 --> 00:09:17,240
+هو عبارة عن high dimensional، ممكن يكون 2D, 3D, 4D.
+
+135
+00:09:17,240 --> 00:09:23,080
+طبعاً،  أتكلم دي اللي هي عدد الـ attribute، و بروح اللي
+
+136
+00:09:23,080 --> 00:09:28,300
+بجسم ليّ إياها لمجموعات. بجسم الـ rows، الـ instances أو الـ
+
+137
+00:09:28,300 --> 00:09:33,860
+points هاي، بجسم ليّ إياها لمجموعات، عبارة عن مجموعات، أو
+
+138
+00:09:33,860 --> 00:09:46,740
+طبعاً، اللي بـ guess الـ point هذه لمجموعات أصغر، بـ
+
+139
+00:09:46,740 --> 00:09:51,060
+guess similarly. عفواً، اللي قلنا إحنا كمان مرة، إن
+
+140
+00:09:51,060 --> 00:09:56,440
+فكرة الـ algorithm بياخد الـ points اللي موجودة
+
+141
+00:09:56,440 --> 00:10:00,220
+عندها، بغض النظر عن الـ space أو الـ dimensionality
+
+142
+00:10:00,220 --> 00:10:05,440
+تبعتها. لكن كل الـ points أو الـ data set تبعتي على
+
+143
+00:10:05,440 --> 00:10:09,560
+نفس العدد من الـ attributes، ثابتة. بروح بجسم ليّ إياها
+
+144
+00:10:09,560 --> 00:10:12,760
+لمجموعات أصغر. يعني،  بجوز يكون كانت والله عندي الـ
+
+145
+00:10:12,760 --> 00:10:15,780
+data set فيها مئة ألف record، وقلت له جسم ليّ إياها لثلاث
+
+146
+00:10:15,780 --> 00:10:18,980
+مجموعات، المئة ألف هدول بيتجسموا على ثلاث مجموعات،
+
+147
+00:10:18,980 --> 00:10:25,500
+حتماً. Each cluster consists of a point that are near
+
+148
+00:10:25,500 --> 00:10:31,080
+to some in some sense. وهذه النقاط في كل مجموعة
+
+149
+00:10:31,080 --> 00:10:36,460
+متشابهة بشكل أو بآخر. طبعاً، لما نتكلم على الـ similar،
+
+150
+00:10:36,460 --> 00:10:41,660
+أو العلاقة related، similar to another، في نفس
+
+151
+00:10:41,660 --> 00:10:46,640
+المجموعة. عناصر المجموعة الواحدة متشابهة، وعناصر
+
+152
+00:10:46,640 --> 00:10:49,860
+المجموعات المختلفة غير متشابهة.
+
+153
+00:10:52,050 --> 00:10:58,450
+هذا المصطلح أهم، و more professional، أن الـ intra
+
+154
+00:10:58,450 --> 00:11:03,050
+distance أو الـ cluster distance يجب أن يكون قليل،
+
+155
+00:11:06,170 --> 00:11:10,330
+كان المسافة ما بين عناصر الـ in instance أو الـ
+
+156
+00:11:10,330 --> 00:11:14,550
+cluster الواحدة تكون قصيرة جداً، ليس منها in
+
+157
+00:11:14,550 --> 00:11:20,110
+instance، أو الـ distance. لما بتكلم على distance يا
+
+158
+00:11:20,110 --> 00:11:24,310
+جماعة الخير، لو تخيل إن في اثنين متطابقين، أو
+
+159
+00:11:24,310 --> 00:11:30,150
+متشابهين، المسافة بينهم قد ايش؟ صفر. أصبح لكن لما يكون
+
+160
+00:11:30,150 --> 00:11:34,690
+المختلفين، المسافة بينهم أبعد ما يمكن. وبالتالي، أنا
+
+161
+00:11:34,690 --> 00:11:37,670
+بقى اتكلم إنه لازم يكون في عند الـ Inter distance
+
+162
+00:11:37,670 --> 00:11:42,270
+أبعد ما يمكن، والـ intra distance أصغر ما يمكن.
+
+163
+00:11:42,270 --> 00:11:46,830
+وبهيك أنا بكون نجحت في تقسيم المجموعات اللي موجودة
+
+164
+00:11:46,830 --> 00:11:51,940
+عندها. طبعاً، لو أنا بدي أعمل مقارنة فعلياً ما بين الـ
+
+165
+00:11:51,940 --> 00:11:55,440
+Clustering و الـ Classification، بناءً على الـ data
+
+166
+00:11:55,440 --> 00:11:59,220
+اللي موجودة عندي. طبعاً، الرسمة الأولى اللي فوق بتمثل
+
+167
+00:11:59,220 --> 00:12:03,700
+classification، والرسمة اللي تحت بتمثل الـ
+
+168
+00:12:03,700 --> 00:12:05,820
+clustering. طبعاً، اللي بتكلم عن الـ classification،
+
+169
+00:12:05,820 --> 00:12:09,520
+يعني إن في عندي label، لازم يكون label، هي الـ label
+
+170
+00:12:09,520 --> 00:12:13,960
+النقاط اللي باللون الأخضر proteins، واللي باللون
+
+171
+00:12:13,960 --> 00:12:18,120
+البني الغامق هذا، أو البني الداكن، هي عبارة عن الـ
+
+172
+00:12:18,120 --> 00:12:22,870
+genes. ومعناته إن لازم يكون في عندي rule يخصص كل
+
+173
+00:12:22,870 --> 00:12:26,950
+point لـ label واضح. طبعاً، الـ rule هذا، زي ما بنعرف
+
+223
+00:16:22,060 --> 00:16:22,880
+ordered
+
+224
+00:16:25,670 --> 00:16:30,370
+طيب الـ cluster الثاني عبارة عن money prices أو
+
+225
+00:16:30,370 --> 00:16:34,610
+purchase money فهي عندي مجموعة عالية من الـ items
+
+226
+00:16:34,610 --> 00:16:39,530
+عالية، والـ purchases تبعتي high prices كذلك، وهذه
+
+227
+00:16:39,530 --> 00:16:42,370
+اللي باللون الأزرق، كذلك باللون الأخضر لما أنا
+
+228
+00:16:42,370 --> 00:16:47,470
+أتكلم أن الـ customer بيشتري مجموعة قليلة من
+
+229
+00:16:47,470 --> 00:16:52,510
+العناصر بأسعار قليلة أو بأسعار زهيدة نوعاً ما، تمام.
+
+230
+00:16:54,270 --> 00:16:57,630
+طبعاً، أين المجالات أو أين التطبيقات اللي ممكن أنا
+
+231
+00:16:57,630 --> 00:17:01,750
+أشغل فيها، عفواً، أشغل فيها أو أطبق فيها الـ
+
+232
+00:17:01,750 --> 00:17:05,590
+clustering؟ العديد من المجالات في الـ target
+
+233
+00:17:05,590 --> 00:17:11,230
+marketing، في التسويق الموجه، لما أنا حابب أستكشف من
+
+234
+00:17:11,230 --> 00:17:15,950
+الناس اللي ممكن يشتريه الإبداع تبعتي، وأروح أوجه
+
+235
+00:17:15,950 --> 00:17:20,910
+لهم الإعلانات أو أعرض عليهم المنتج تبعي، مثلاً أنا
+
+236
+00:17:20,910 --> 00:17:27,750
+والله لو جئنا سألنا، أنا عمال بعمل تطبيق IOS عشان
+
+237
+00:17:27,750 --> 00:17:32,670
+يتكلم أو بعملي high prediction لضغط الدم وعدد
+
+238
+00:17:32,670 --> 00:17:37,450
+ضربات القلب والأخره، من المعنيين لو أنا بدي أروح
+
+239
+00:17:37,450 --> 00:17:42,950
+أدور في الـ data أو بدي أحاول أستكشف، عندي data set
+
+240
+00:17:42,950 --> 00:17:45,830
+لـ customers اللي بيشتغلوا applications، ممكن أنا
+
+241
+00:17:45,830 --> 00:17:48,430
+أروح أبحث عن فئة الناس اللي ممكن تشتري الـ
+
+242
+00:17:48,430 --> 00:17:51,230
+application هذا، من خلال، إما من خلال الـ similarity
+
+243
+00:17:51,230 --> 00:17:55,390
+أو من خلال الاهتمامات
+
+244
+00:17:55,390 --> 00:17:59,510
+تبعتهم، في الآخر لازم ألاقي بين العناصر هدول شغلات
+
+245
+00:17:59,510 --> 00:18:02,670
+مشتركة، وممكن أنا أتوجه لهم، لأن ممكن أتوجه لهم لكل
+
+246
+00:18:02,670 --> 00:18:05,950
+المجموعات، فلما أنا بروح وأجسمهم لمجموعات ألاقي
+
+247
+00:18:05,950 --> 00:18:13,310
+حتماً مجموعة فيها هذه العناصر، في الـ genomics أو في
+
+248
+00:18:13,310 --> 00:18:17,730
+علم الجينات، ممكن أنا أروح أصنف الجينات كذلك، أو
+
+249
+00:18:17,730 --> 00:18:21,310
+عفواً، أقسم الجينات لمجموعات، في الـ astronomy أو في
+
+250
+00:18:21,310 --> 00:18:26,670
+علم الفضاء، عشان أصنف أو أجسم المجموعات أو أوجد
+
+251
+00:18:26,670 --> 00:18:30,470
+مجموعات لـ similar stars والـ galaxies والمجرات
+
+252
+00:18:30,470 --> 00:18:33,660
+اللي موجودة عندي، في الـ insurance أو في التأمين، عشان
+
+253
+00:18:33,660 --> 00:18:37,460
+أعرف في المجموعات اللي أنا فعلياً كيف ممكن أعرف
+
+254
+00:18:37,460 --> 00:18:44,420
+فيها الـ vehicles أو أن اصدر أو اقسم بوليصات التأمين
+
+255
+00:18:44,420 --> 00:18:48,240
+حسب الـ holder اللي موجود عندها، لو جديش قيمة الـ
+
+256
+00:18:48,240 --> 00:18:51,200
+insurance، في الـ city planning كذلك، في التخطيط
+
+257
+00:18:51,200 --> 00:18:56,200
+الحضري للمدن، كيف يتم جسمها لمجموعة من الـ houses
+
+258
+00:18:56,200 --> 00:19:03,220
+بناءً على أنواعهم وأنواع سفرتهم والـ location أو الـ
+
+259
+00:19:03,220 --> 00:19:07,260
+geographical location تبعتهم، لكن أنا فعلياً جامعة
+
+260
+00:19:07,260 --> 00:19:11,300
+الخير، كل الكلام الجميل عن الـ clustering، في عندي من
+
+261
+00:19:11,300 --> 00:19:13,860
+ضمن الكلام كان في عندي مشكلة واضحة، أو هي الـ
+
+262
+00:19:13,860 --> 00:19:19,560
+challenge الأساسي في موضوع الـ clustering، فعلياً إذا
+
+263
+00:19:19,560 --> 00:19:23,240
+الـ data unlabeled، ما أعطاني عدد الـ clusters الحقيقية
+
+264
+00:19:23,240 --> 00:19:28,380
+اللي موجودة عندي، لو أنا عرضت عليك الـ data هاي كم
+
+265
+00:19:28,380 --> 00:19:34,600
+clusters؟ هذه الـ data set unlabeled data، ما فيش
+
+266
+00:19:34,600 --> 00:19:38,000
+عليها أي علامات مميزة، وسألتك هذه كم مجموعة؟
+
+267
+00:19:47,800 --> 00:19:55,400
+ممكن أكثر؟ اه ممكن، هذه أربعة clusters، هدول مع بعض،
+
+268
+00:19:55,400 --> 00:20:06,910
+هدول لحال، هدول لحال، هذا لحال، أو هذا لحال، ممكن ستة
+
+269
+00:20:06,910 --> 00:20:10,630
+كذلك، طيب أي عدد فيهم الصح؟ طيب الثلاثة ليش مش ثلاثة؟
+
+270
+00:20:10,630 --> 00:20:14,130
+لو أنا قلت له ثلاثة، حاجة اسمهم على ثلاثة، من الصح
+
+271
+00:20:14,130 --> 00:20:19,030
+فيهم؟ اثنين ولا ثلاثة ولا أربعة ولا ستة ولا خمسة؟
+
+272
+00:20:19,030 --> 00:20:23,850
+مين؟ لأن الـ label غايب عندي، معناته أنا في عندي
+
+273
+00:20:23,850 --> 00:20:26,810
+مشكلة، أو إحنا بنقول في عندي challenge حقيقية، لأن
+
+274
+00:20:26,810 --> 00:20:32,480
+أقدر أقيّم الـ Cluster Algorithm أو الـ Behavior تبع
+
+275
+00:20:32,480 --> 00:20:34,340
+الـ Cluster Algorithm، علشان هي بتقول الـ
+
+276
+00:20:34,340 --> 00:20:39,120
+Clustering can be ambiguous، ممكن يكون مضلل، مضلل
+
+277
+00:20:39,120 --> 00:20:42,600
+يعني مش واضح أو ضبابي في التعامل اللي موجود عندها.
+
+278
+00:20:43,850 --> 00:20:46,950
+الـ Clustering Types، لما أتكلم على الـ Clustering
+
+279
+00:20:46,950 --> 00:20:51,630
+Types، المعنى هو .. الـ .. الـ Clustering هي عبارة عن
+
+280
+00:20:51,630 --> 00:20:56,110
+مجموعة من الست في الـ clusters، وهذه تراوح مجموعات
+
+281
+00:20:56,110 --> 00:20:59,010
+الـ clusters هذه إما ما بين الـ hierarchical أو الـ
+
+282
+00:20:59,010 --> 00:21:03,830
+partitional، الـ cluster إما بتكون هرمي أو تجزيئي أو
+
+283
+00:21:03,830 --> 00:21:06,810
+تقطيعي، الـ clusters اللي موجودة، لما أتكلم على
+
+284
+00:21:06,810 --> 00:21:09,250
+partitional الـ clustering، معناته أنا بتكلم على
+
+285
+00:21:09,250 --> 00:21:15,790
+division للـ data على مجموعات غير متقاطعة، أنا بأجسم
+
+286
+00:21:15,790 --> 00:21:20,310
+الـ data objects أو الـ instances اللي موجودة على
+
+287
+00:21:20,310 --> 00:21:25,870
+مجموعات غير متقاطعة، وهذا ما نسميه non overlapping
+
+288
+00:21:25,870 --> 00:21:29,330
+clusters أو non overlapping subsets، أو نسميها إحنا
+
+289
+00:21:29,330 --> 00:21:36,230
+cluster، وبالتالي كل element بيكون موجود فقط في one
+
+290
+00:21:36,230 --> 00:21:40,140
+subset، بينما في الـ Hierarchical Clustering، معناته
+
+291
+00:21:40,140 --> 00:21:45,860
+أنا بتكلم على set of nested clusters organized as
+
+292
+00:21:45,860 --> 00:21:49,720
+hierarchical tree، وبالتالي لأ، أنا في عندي تقاطع ما
+
+293
+00:21:49,720 --> 00:21:53,060
+بين كل cluster والتاني، لما إن في عندي هيكلية أو
+
+294
+00:21:53,060 --> 00:21:56,660
+hierarchy هرمية أو في عندي tree، معناته أنا قاعد
+
+295
+00:21:56,660 --> 00:22:00,420
+في عندي عناصر اللي حتكون عندي ماخدة أشكال مختلفة.
+
+296
+00:22:00,420 --> 00:22:03,660
+لو أنا قلت هذه الـ data اللي عندي هان وبدأت أطبق
+
+297
+00:22:03,660 --> 00:22:07,660
+عليها partitional clustering، معناته ممكن حيكون
+
+298
+00:22:07,660 --> 00:22:10,860
+عبارة عن الـ Partition، Different Partitional
+
+299
+00:22:10,860 --> 00:22:15,140
+Clustering، لو أنا افترضت أنه بالـ Hierarchical
+
+300
+00:22:15,140 --> 00:22:17,660
+data، معناته أنا ممكن أحكي الـ Hierarchical فكرة
+
+301
+00:22:17,660 --> 00:22:24,370
+أنه اثنين وثلاثة هان في one cluster، والـ cluster
+
+302
+00:22:24,370 --> 00:22:27,870
+هذا مع أربعة كونوا cluster جديد، مع واحد كونوا
+
+303
+00:22:27,870 --> 00:22:30,830
+cluster جديد، وهذه طبعاً بسميها traditional
+
+304
+00:22:30,830 --> 00:22:33,710
+hierarchical clustering، بينما هذه بسميها
+
+305
+00:22:33,710 --> 00:22:37,850
+dendrogram، وطبعاً الـ dendrogram بيبين بشكل واضح
+
+306
+00:22:37,850 --> 00:22:41,290
+علاقة الـ instances مع بعض، يعني أنا واضح أن عندي
+
+307
+00:22:41,290 --> 00:22:47,950
+اثنين وثلاثة انجمعوا، بعدين انجمع لهم أربعة، و
+
+308
+00:22:47,950 --> 00:22:54,500
+بعدين انجمع لكل اللي هي واحدة، كذلك هنا، هنا الـ non
+
+309
+00:22:54,500 --> 00:22:56,940
+-traditional الهراريكال .. الهراريكال طبعاً الـ
+
+310
+00:22:56,940 --> 00:22:59,740
+traditional في كل مرة أنا عمالي بضيف point، لكن في
+
+311
+00:22:59,740 --> 00:23:02,220
+الـ non-traditional، لأ، ممكن تكون الأمور شوية مختلفة.
+
+312
+00:23:02,220 --> 00:23:05,500
+ممكن بي واحد وبي اثنين مع بعض، بي اثنين وبي ثلاثة
+
+313
+00:23:05,500 --> 00:23:08,840
+مع بعض، بي ثلاثة وبي أربعة، وهدول كلهم موجودين مع
+
+314
+00:23:08,840 --> 00:23:13,200
+بعض، وهذه هي في الـ dendogram اللي بتظهر عندنا إن
+
+315
+00:23:13,200 --> 00:23:16,840
+شاء الله تعالى، في التسجيل الجاي حأروح باتجاه الـ
+
+316
+00:23:16,840 --> 00:23:20,300
+partitional clustering، أشوفكم على خير إن شاء الله.
+
+317
+00:23:20,300 --> 00:23:21,640
+والسلام عليكم ورحمة الله.
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/0qyAh66hZ2s_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/0qyAh66hZ2s_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..91f0a1c7c6c0884368d0f457a98cb9fbdbcacde4
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/0qyAh66hZ2s_raw.json
@@ -0,0 +1 @@
+{"segments": [{"id": 1, "seek": 368, "start": 1.18, "end": 3.68, "text": "بسم الله الرحمن الرحيم الصلاة والسلام على رسول الله", "tokens": [3555, 38251, 21984, 34892, 5016, 27842, 34892, 5016, 32640, 31767, 15040, 3660, 16070, 3794, 37440, 15844, 12602, 3794, 12610, 21984], "avg_logprob": -0.13876487811406454, "compression_ratio": 1.3623188405797102, "no_speech_prob": 0.0, "words": [{"start": 1.18, "end": 1.46, "word": "بسم", "probability": 0.85693359375}, {"start": 1.46, "end": 1.58, "word": " الله", "probability": 0.962890625}, {"start": 1.58, "end": 1.88, "word": " الرحمن", "probability": 0.7893880208333334}, {"start": 1.88, "end": 2.16, "word": " الرحيم", "probability": 0.97119140625}, {"start": 2.16, "end": 2.52, "word": " الصلاة", "probability": 0.814697265625}, {"start": 2.52, "end": 2.94, "word": " والسلام", "probability": 0.9597981770833334}, {"start": 2.94, "end": 3.12, "word": " على", "probability": 0.70166015625}, {"start": 3.12, "end": 3.5, "word": " رسول", "probability": 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{"start": 605.44, "end": 606.02, "word": " نفس", "probability": 0.930908203125}, {"start": 606.02, "end": 606.36, "word": " العدد", "probability": 0.8592122395833334}, {"start": 606.36, "end": 606.46, "word": " من", "probability": 0.9365234375}, {"start": 606.46, "end": 606.56, "word": " ال", "probability": 0.91748046875}, {"start": 606.56, "end": 607.06, "word": " attributes", "probability": 0.87451171875}, {"start": 607.06, "end": 607.84, "word": " ثابتة", "probability": 0.762908935546875}, {"start": 607.84, "end": 608.74, "word": " بروح", "probability": 0.7447916666666666}, {"start": 608.74, "end": 609.56, "word": " بجسمليها", "probability": 0.88349609375}, {"start": 609.56, "end": 610.42, "word": " لمجموعات", "probability": 0.922265625}, {"start": 610.42, "end": 610.8, "word": " أصغر", "probability": 0.932861328125}, {"start": 610.8, "end": 611.52, "word": " يعني", "probability": 0.72314453125}, {"start": 611.52, "end": 611.7, "word": " بين", "probability": 0.69580078125}, {"start": 611.7, "end": 612.0, "word": " جوسين", "probability": 0.58349609375}, {"start": 612.0, "end": 612.3, "word": " كانت", "probability": 0.913818359375}, {"start": 612.3, "end": 612.46, "word": " والله", "probability": 0.7015380859375}, {"start": 612.46, "end": 612.68, "word": " عندي", "probability": 0.65478515625}, {"start": 612.68, "end": 612.76, "word": " ال", "probability": 0.85546875}, {"start": 612.76, "end": 612.9, "word": " data", "probability": 0.91552734375}, {"start": 612.9, "end": 613.2, "word": " set", "probability": 0.96142578125}, {"start": 613.2, "end": 613.42, "word": " فيها", "probability": 0.905029296875}, {"start": 613.42, "end": 613.64, "word": " مائة", "probability": 0.7576497395833334}, {"start": 613.64, "end": 613.86, "word": " ألف", "probability": 0.896728515625}, {"start": 613.86, "end": 614.24, "word": " record", "probability": 0.9541015625}, {"start": 614.24, "end": 614.82, "word": " وقلتله", "probability": 0.68369140625}, {"start": 614.82, "end": 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" نفس", "probability": 0.99169921875}, {"start": 641.66, "end": 642.48, "word": " المجموعة", "probability": 0.95322265625}, {"start": 642.48, "end": 643.78, "word": " عناصر", "probability": 0.8390299479166666}, {"start": 643.78, "end": 644.34, "word": " المجموعة", "probability": 0.944921875}, {"start": 644.34, "end": 644.98, "word": " الواحدة", "probability": 0.968994140625}, {"start": 644.98, "end": 646.02, "word": " متشابهة", "probability": 0.91884765625}, {"start": 646.02, "end": 646.64, "word": " وعناصر", "probability": 0.8853515625}, {"start": 646.64, "end": 647.2, "word": " المجموعات", "probability": 0.9833984375}, {"start": 647.2, "end": 647.74, "word": " المختلفة", "probability": 0.9842529296875}, {"start": 647.74, "end": 648.56, "word": " غير", "probability": 0.962890625}, {"start": 648.56, "end": 649.86, "word": " متشابهة", "probability": 0.990234375}], "temperature": 1.0}, {"id": 26, "seek": 66305, "start": 652.05, "end": 663.05, "text": "هذا المصطلح أهم و more professional أن الـ intra distance أو ال cluster distance يجب أن يكون قليل", "tokens": [3224, 15730, 9673, 9381, 9566, 1211, 5016, 5551, 16095, 4032, 544, 4843, 14739, 2423, 39184, 43358, 4560, 34051, 2423, 13630, 4560, 7251, 7435, 3555, 14739, 7251, 30544, 12174, 20292, 1211], "avg_logprob": -0.5796370775468888, "compression_ratio": 1.1565217391304348, "no_speech_prob": 0.0, "words": [{"start": 652.05, "end": 652.77, "word": "هذا", "probability": 0.4739990234375}, {"start": 652.77, "end": 653.19, "word": " المصطلح", "probability": 0.92734375}, {"start": 653.19, "end": 653.59, "word": " أهم", "probability": 0.78369140625}, {"start": 653.59, "end": 654.05, "word": " و", "probability": 0.33154296875}, {"start": 654.05, "end": 654.39, "word": " more", "probability": 0.1998291015625}, {"start": 654.39, "end": 654.97, "word": " professional", "probability": 0.9267578125}, {"start": 654.97, "end": 656.03, "word": " أن", "probability": 0.1795654296875}, {"start": 656.03, "end": 657.97, "word": " الـ", 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الواحدة تكون قصيرة جدا ليس منها in instance او ال distance لما بتكلم على distance يا جماعة الخير لو تخيل ان في اتنين متطابقين او متشابهين المسافة بينهم جديش صفر أصبح", "tokens": [41361, 9673, 3794, 31845, 3660, 19446, 49374, 18871, 33546, 2288, 2423, 294, 5197, 34051, 2423, 13630, 2423, 14407, 24401, 3660, 6055, 30544, 12174, 9381, 48923, 10874, 28259, 32239, 3794, 9154, 11296, 294, 5197, 1975, 2407, 2423, 4560, 5296, 15042, 39894, 4117, 19528, 15844, 4560, 35186, 10874, 15042, 27884, 33962, 13546, 45164, 6055, 9778, 26895, 16472, 8978, 1975, 2655, 1863, 9957, 44650, 9566, 16758, 4587, 9957, 1975, 2407, 44650, 8592, 16758, 3224, 9957, 9673, 3794, 31845, 3660, 49374, 16095, 10874, 16254, 8592, 20328, 5172, 2288, 5551, 9381, 49628], "avg_logprob": -0.2521306709809737, "compression_ratio": 1.7184466019417475, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 666.1699999999998, "end": 666.9899999999999, "word": "كان", "probability": 0.376708984375}, {"start": 666.9899999999999, 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"end": 938.28, "word": " على", "probability": 0.356201171875}, {"start": 938.28, "end": 938.56, "word": " 3000", "probability": 0.74462890625}, {"start": 938.56, "end": 939.08, "word": " بتكلم", "probability": 0.7840169270833334}, {"start": 939.08, "end": 939.32, "word": " على", "probability": 0.87158203125}, {"start": 939.32, "end": 941.82, "word": " 660", "probability": 0.646240234375}, {"start": 941.82, "end": 942.46, "word": " تقريبا", "probability": 0.9880859375}], "temperature": 1.0}, {"id": 38, "seek": 96650, "start": 943.68, "end": 966.5, "text": "بنتكلم على 2300 على 4 بينما اللي تحت بنتكلم على أعداد أعداد كبيرة و أسعار قليلة بينما اللي تحت أعداد قليلة و أسعار قليلة، مظبوط؟ لأ لو أنا بدي أجي أجسم، معناته هيكون التقسيم في ال cluster الأول اللي على أسر باللون الأحمر اللي هي few purchases with high prices", "tokens": [3555, 1863, 2655, 4117, 19528, 15844, 6673, 628, 15844, 1017, 49374, 15042, 13672, 1829, 6055, 33753, 4724, 29399, 4117, 19528, 15844, 5551, 22488, 18513, 5551, 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"word": " على", "probability": 0.7431640625}, {"start": 1269.25, "end": 1269.61, "word": " division", "probability": 0.81298828125}, {"start": 1269.61, "end": 1269.87, "word": " لل", "probability": 0.94140625}, {"start": 1269.87, "end": 1270.25, "word": " data", "probability": 0.9453125}], "temperature": 1.0}, {"id": 52, "seek": 129689, "start": 1271.45, "end": 1296.89, "text": "على مجموعات غير متقاطعة انا بجسم ال data objects أو ال instances اللي موجودة على مجموعات غير متقاطعة وهذا ما نسميها non overlapping clusters او non overlapping subsets او نسميها احنا cluster وبالتالي كل element بكون موجود فقط في one subset", "tokens": [3615, 23942, 3714, 7435, 2304, 45367, 9307, 32771, 13546, 44650, 4587, 41193, 27884, 1975, 8315, 4724, 7435, 38251, 2423, 1412, 6565, 34051, 2423, 14519, 13672, 1829, 3714, 29245, 23328, 3660, 15844, 3714, 7435, 2304, 45367, 9307, 32771, 13546, 44650, 4587, 41193, 27884, 37037, 15730, 19446, 8717, 38251, 1829, 11296, 2107, 33535, 23313, 1975, 2407, 2107, 33535, 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لما ان في عندي هيكلية او hierarchy هيرامية او في عندي tree معناته انا قاعد في عندي عناصر اللي هتكون عندي ماخدة أشكال مختلفة لو انا قلت هي ال data اللي عندي هان وبدأ اطبق عليها partitionary clustering", "tokens": [3555, 9957, 15042, 8978, 2423, 39184, 10886, 1178, 804, 2033, 48673, 20449, 8315, 47395, 41850, 39894, 4117, 19528, 15844, 992, 295, 15646, 292, 23313, 9983, 382, 35250, 804, 4230, 46599, 6027, 2655, 6027, 1829, 5296, 10721, 1975, 8315, 8978, 18871, 16254, 6055, 4587, 41193, 3615, 19446, 49374, 28242, 13630, 4032, 16712, 7649, 1829, 5296, 15042, 16472, 8978, 18871, 16254, 39896, 28820, 10632, 1975, 2407, 3296, 13988, 8032, 13546, 10943, 10632, 1975, 2407, 8978, 18871, 16254, 4230, 20449, 8315, 47395, 1975, 8315, 12174, 995, 22488, 8978, 18871, 16254, 18871, 33546, 2288, 13672, 1829, 8032, 2655, 30544, 18871, 16254, 3714, 47283, 41891, 5551, 8592, 4117, 6027, 3714, 46456, 46538, 3660, 45164, 1975, 8315, 12174, 1211, 2655, 39896, 2423, 1412, 13672, 1829, 18871, 16254, 8032, 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Hierarchical data معناته انا ممكن احيي الـ Hierarchical فكرة انه اتنين و تلاتة هان في one cluster", "tokens": [2304, 3615, 8315, 47395, 3714, 43020, 39896, 30544, 6225, 3555, 9640, 3660, 18871, 2423, 39184, 4100, 849, 20825, 4100, 2628, 2033, 48673, 45164, 1975, 8315, 1975, 5172, 2655, 43042, 2655, 16472, 3224, 20666, 39184, 10886, 1178, 804, 1412, 20449, 8315, 47395, 1975, 8315, 3714, 43020, 1975, 5016, 1829, 1829, 2423, 39184, 10886, 1178, 804, 6156, 4117, 25720, 16472, 3224, 1975, 2655, 1863, 9957, 4032, 6055, 1211, 9307, 3660, 8032, 7649, 8978, 472, 13630], "avg_logprob": -0.35895271518745936, "compression_ratio": 1.5555555555555556, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 1326.44, "end": 1326.82, "word": "معناته", "probability": 0.502197265625}, {"start": 1326.82, "end": 1327.1, "word": " ممكن", "probability": 0.625244140625}, {"start": 1327.1, "end": 1327.66, "word": " هيكون", "probability": 0.68408203125}, {"start": 1327.66, "end": 1328.08, "word": " عبارة", 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1382.96, "end": 1383.46, "word": " واحد", "probability": 0.968017578125}, {"start": 1383.46, "end": 1383.78, "word": " و", "probability": 0.70166015625}, {"start": 1383.78, "end": 1383.9, "word": " بي", "probability": 0.78564453125}, {"start": 1383.9, "end": 1384.08, "word": " اتنين", "probability": 0.92822265625}, {"start": 1384.08, "end": 1384.28, "word": " مع", "probability": 0.9560546875}, {"start": 1384.28, "end": 1384.58, "word": " بعض", "probability": 0.994140625}, {"start": 1384.58, "end": 1384.76, "word": " بي", "probability": 0.729248046875}, {"start": 1384.76, "end": 1384.92, "word": " اتنين", "probability": 0.9683837890625}, {"start": 1384.92, "end": 1385.0, "word": " و", "probability": 0.95703125}, {"start": 1385.0, "end": 1385.12, "word": " بي", "probability": 0.96240234375}, {"start": 1385.12, "end": 1385.5, "word": " تلاتة", "probability": 0.949462890625}, {"start": 1385.5, "end": 1385.66, "word": " مع", "probability": 0.91845703125}, {"start": 1385.66, "end": 1386.0, "word": " بعض", "probability": 0.995361328125}, {"start": 1386.0, "end": 1386.4, "word": " بي", "probability": 0.737060546875}, {"start": 1386.4, "end": 1386.62, "word": " تلاتة", "probability": 0.9639892578125}, {"start": 1386.62, "end": 1386.7, "word": " و", "probability": 0.9736328125}, {"start": 1386.7, "end": 1386.82, "word": " بي", "probability": 0.98046875}, {"start": 1386.82, "end": 1387.16, "word": " أربعة", "probability": 0.8346354166666666}, {"start": 1387.16, "end": 1387.62, "word": " و", "probability": 0.65185546875}, {"start": 1387.62, "end": 1387.76, "word": " هدول", "probability": 0.826171875}, {"start": 1387.76, "end": 1388.06, "word": " كلهم", "probability": 0.84765625}, {"start": 1388.06, "end": 1388.62, "word": " موجودين", "probability": 0.979736328125}, {"start": 1388.62, "end": 1388.84, "word": " مع", "probability": 0.99072265625}, {"start": 1388.84, "end": 1389.14, "word": " بعض", "probability": 0.998046875}, {"start": 1389.14, "end": 1389.26, "word": " و", "probability": 0.418701171875}, {"start": 1389.26, "end": 1389.44, "word": " هده", "probability": 0.6475423177083334}, {"start": 1389.44, "end": 1389.54, "word": " هي", "probability": 0.57958984375}, {"start": 1389.54, "end": 1389.66, "word": " في", "probability": 0.7216796875}, {"start": 1389.66, "end": 1389.74, "word": " ال", "probability": 0.9287109375}, {"start": 1389.74, "end": 1390.26, "word": " dendogram", "probability": 0.5797526041666666}, {"start": 1390.26, "end": 1390.56, "word": " اللي", "probability": 0.829345703125}, {"start": 1390.56, "end": 1391.54, "word": " بتظهر", "probability": 0.9632568359375}, {"start": 1391.54, "end": 1392.16, "word": " عندنا", "probability": 0.79052734375}, {"start": 1392.16, "end": 1393.2, "word": " ان", "probability": 0.51171875}, {"start": 1393.2, "end": 1393.42, "word": " شاء", "probability": 0.94482421875}, {"start": 1393.42, "end": 1393.52, "word": " الله", "probability": 0.94287109375}, {"start": 1393.52, "end": 1394.02, "word": " تعالى", "probability": 0.9405924479166666}, {"start": 1394.02, "end": 1394.32, "word": " في", "probability": 0.92822265625}, {"start": 1394.32, "end": 1394.98, "word": " التسجيل", "probability": 0.984619140625}, {"start": 1394.98, "end": 1395.32, "word": " الجاي", "probability": 0.740234375}, {"start": 1395.32, "end": 1395.74, "word": " هروح", "probability": 0.9103190104166666}, {"start": 1395.74, "end": 1396.3, "word": " باتجاه", "probability": 0.8558349609375}, {"start": 1396.3, "end": 1396.84, "word": " ال", "probability": 0.96533203125}, {"start": 1396.84, "end": 1397.84, "word": " partitional", "probability": 0.566162109375}, {"start": 1397.84, "end": 1398.6, "word": " clustering", "probability": 0.776123046875}, {"start": 1398.6, "end": 1399.54, "word": " أشوفكم", "probability": 0.640869140625}, {"start": 1399.54, "end": 1399.72, "word": " على", "probability": 0.97021484375}, {"start": 1399.72, "end": 1399.94, "word": " خير", "probability": 0.992919921875}, {"start": 1399.94, "end": 1400.12, "word": " ان", "probability": 0.64599609375}, {"start": 1400.12, "end": 1400.24, "word": " شاء", "probability": 0.986083984375}, {"start": 1400.24, "end": 1400.3, "word": " الله", "probability": 0.95849609375}, {"start": 1400.3, "end": 1400.4, "word": " و", "probability": 0.57568359375}, {"start": 1400.4, "end": 1400.62, "word": " السلام", "probability": 0.952392578125}, {"start": 1400.62, "end": 1400.96, "word": " عليكم", "probability": 0.937744140625}, {"start": 1400.96, "end": 1401.12, "word": " و", "probability": 0.994140625}, {"start": 1401.12, "end": 1401.3, "word": " مرحبا", "probability": 0.85068359375}, {"start": 1401.3, "end": 1401.64, "word": " لله", "probability": 0.41021728515625}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 1404.2035625, "duration_after_vad": 1359.913124999999}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/3PercFMmDro.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/3PercFMmDro.srt
new file mode 100644
index 0000000000000000000000000000000000000000..25eb7b56ae4d445fe6674acb8c5236344af03171
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+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/3PercFMmDro.srt
@@ -0,0 +1,2598 @@
+1
+00:00:05,250 --> 00:00:07,430
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:07,430 --> 00:00:11,930
+اليوم إن شاء الله شباب، هنبدأ بـ Chapter جديد في الـ
+
+3
+00:00:11,930 --> 00:00:15,070
+data mining، وهنتكلم على أولى الـ data mining tasks
+
+4
+00:00:15,070 --> 00:00:20,630
+وهي الـ classification. الـ classification لكن قبل
+
+5
+00:00:20,630 --> 00:00:24,150
+ما أبدأ بالمحاضرة فعلياً، وبالـ slides، بدي أسأل أنا
+
+6
+00:00:24,150 --> 00:00:26,270
+إيش احنا بنقصد بالـ classification؟
+
+7
+00:00:44,700 --> 00:00:53,400
+أه محمد، شو يعني classification؟
+
+8
+00:00:53,400 --> 00:00:56,580
+بدي
+
+9
+00:00:56,580 --> 00:00:59,060
+أصنف.. شو يعني بدي أصنف؟ أيوة، أنا بدي أقول..
+
+10
+00:00:59,060 --> 00:01:04,700
+بينهم شغلات مشتركة.
+
+11
+00:01:04,700 --> 00:01:09,520
+شو رايك؟ مشتركة؟  مرتّب، عفواً، بجسم الـ data على شكل
+
+12
+00:01:09,520 --> 00:01:14,720
+categories. بجسم الـ data على شكل categories، كريم.
+
+13
+00:01:14,720 --> 00:01:20,040
+بناءً على ترميز معيّنة، بعمل زي لِبْط بمثل الصدر أو كذا.
+
+14
+00:01:20,040 --> 00:01:24,340
+طيب، أنا قاعد بسأل شو يعني تصنيف بالعربي؟ شو يعني
+
+15
+00:01:24,340 --> 00:01:30,220
+تصنيف شغلات بينها أو في عناصر، فيها عناصر مشتركة.
+
+16
+00:01:30,220 --> 00:01:38,040
+عمار، شو يعني تصنيف؟ تقسيم العناصر إلى مجموعات. طيب.
+
+17
+00:01:38,040 --> 00:01:42,200
+شو يعني تصنيف يا راني؟ تصنيف شو يعني؟
+
+18
+00:01:47,010 --> 00:01:54,950
+طيب، لو أنا جيت قلت لك، أه أحمد، تفضل. اعمل sub-class
+
+19
+00:01:54,950 --> 00:02:00,410
+بناءً على role معيّن، أو subset. طيب لو.. لو أنا جيت
+
+20
+00:02:00,410 --> 00:02:09,330
+قلت لكم عندي الآن قرصة كتب، مجموعة كتب، وبدنا نصنّفها.
+
+21
+00:02:15,120 --> 00:02:19,440
+إيش اسمك؟ إبراهيم. إبراهيم، أنا عارف، بعمل تساؤل لك.
+
+22
+00:02:19,440 --> 00:02:26,500
+سنّوار، حسب إيش بدي أصنّفها؟ ليش يا إبراهيم سألتني
+
+23
+00:02:26,500 --> 00:02:32,420
+السؤال هذا؟ عشان أنا أقدر.. طب إيش اللي بدك إياه مني
+
+24
+00:02:32,420 --> 00:02:36,480
+يا إبراهيم، عشان تقدر تصنّفها؟
+
+25
+00:02:36,480 --> 00:02:39,660
+هو هو أنت صرت إبراهيم الآن؟ أيوة، إيش اللي بدك
+
+26
+00:02:39,660 --> 00:02:42,960
+يامني، عشان تقدر تصنّفها؟  حتى تقدر تحصر لي شغلات؟
+
+27
+00:02:45,760 --> 00:02:50,560
+معلومات.. معلومات.. معلومات عن إيش؟ معلومات عن
+
+28
+00:02:50,560 --> 00:02:54,680
+أستراليا.. معلومات عن أستراليا.. معلومات عن
+
+29
+00:02:54,680 --> 00:02:55,440
+أستراليا.. معلومات عن أستراليا.. معلومات عن
+
+30
+00:02:55,440 --> 00:02:56,680
+أستراليا.. معلومات عن أستراليا.. معلومات عن
+
+31
+00:02:56,680 --> 00:02:56,920
+أستراليا.. معلومات عن أستراليا.. معلومات عن
+
+32
+00:02:56,920 --> 00:02:58,800
+أستراليا.. معلومات عن أستراليا.. معلومات عن
+
+33
+00:02:58,800 --> 00:03:00,320
+أستراليا.. معلومات عن أستراليا.. معلومات عن
+
+34
+00:03:00,320 --> 00:03:02,840
+أستراليا.. معلومات عن أستراليا.. معلومات عن
+
+35
+00:03:02,840 --> 00:03:07,340
+أستراليا.. معلومات عن أستراليا.. معلومات عن
+
+36
+00:03:07,340 --> 00:03:10,880
+أستراليا.. معلومات عن أستراليا.. معلومات عن أست
+
+37
+00:03:12,100 --> 00:03:16,820
+تمام؟ كان كله بيتكلم على clustering أو grouping.
+
+38
+00:03:16,820 --> 00:03:21,720
+لأن كلكم بتتكلموا، لمجموعات. أصنفهم لمجموعات، أصنفهم
+
+39
+00:03:21,720 --> 00:03:27,360
+لمجموعات. مش هيك أصنفهم. يعني في عندي predefined
+
+40
+00:03:27,360 --> 00:03:32,220
+sets. في عندي مجموعات معروفة مسبقاً، والمجموعات هذه
+
+41
+00:03:32,220 --> 00:03:38,060
+إلها عناوين، وأنت دورك تشوف هل العنصر هذا بيتوافق مع
+
+42
+00:03:38,060 --> 00:03:41,440
+المجموعة هذه ولا لأ، عشان تحطه تحتها. بينما اللي
+
+43
+00:03:41,440 --> 00:03:44,840
+كنتوا أنتم بتطرحوه، بتقول أنا بدي أدرس الخصائص
+
+44
+00:03:44,840 --> 00:03:50,630
+المشتركة بين الكتب، وأجسّمهم لمجموعات. هذا بيسمّيه
+
+45
+00:03:50,630 --> 00:03:52,510
+احنا في الـ data science أو في الـ data mining
+
+46
+00:03:52,510 --> 00:03:57,230
+clustering. يا تامر، بيسمّيه clustering أو grouping.
+
+47
+00:03:57,230 --> 00:04:04,370
+بينما للتصنيف، أنا بقعد فيه عندي مجموعات معرفة
+
+48
+00:04:04,370 --> 00:04:08,350
+مسبقاً، predefined
+
+49
+00:04:08,350 --> 00:04:14,870
+groups. ممكن
+
+50
+00:04:14,870 --> 00:04:18,680
+يكونوا أقل شيء، لازم يكونوا اثنتين. أجل، لازم يكونوا
+
+51
+00:04:18,680 --> 00:04:23,600
+مجموعتين، وبعدين هي بيجي دوري أنا، بشوف كل object
+
+52
+00:04:23,600 --> 00:04:26,780
+في الـ data set اللي عندي، أو كل object في الكتب
+
+53
+00:04:26,780 --> 00:04:33,440
+اللي عندي، بيندرج تحت أي مصنّف؟ تحت أي عنوان من
+
+54
+00:04:33,440 --> 00:04:37,020
+المجموعات هذه. لو أنا أجيت قلت لك يا همام، الكتب اللي
+
+55
+00:04:37,020 --> 00:04:43,400
+عندي أنا إما science أو politics أو financial أو
+
+56
+00:04:43,400 --> 00:04:45,020
+literature، أدب.
+
+57
+00:04:47,290 --> 00:04:54,550
+اقتصاد، سياسة، علوم، شوف كيف تساوي وعندك مجموعة
+
+58
+00:04:54,550 --> 00:04:59,950
+الكتب مثل ما هي مكدسة قدامي، شو هتعمل؟ كيف؟ ماشي،
+
+59
+00:04:59,950 --> 00:05:09,560
+هتفرزهم الآن، شو هتسوي؟ هتمسك كل كتاب..  كمل، على
+
+60
+00:05:09,560 --> 00:05:12,820
+الأقل أعرف الموضوع اللي بيتكلم فيه الكتاب، يعني
+
+61
+00:05:12,820 --> 00:05:18,400
+مثلاً كتاب بتكلم عن الاحتلال الإنجليزي لشرق آسيا،
+
+62
+00:05:18,400 --> 00:05:26,760
+مثلاً بتصنّفه سياسة ولا تاريخ، literature حسب الكتاب
+
+63
+00:05:26,760 --> 00:05:30,500
+عن إيش بتكلم؟ هل بتكلم مثلاً رؤية سياسية ولا
+
+64
+00:05:30,500 --> 00:05:34,480
+بتكلم مجرد سرد تاريخي للموضوع، الاحتلال على
+
+65
+00:05:34,480 --> 00:05:37,620
+التاريخ. جيت وجيت والله، كتاب بتكلم على الـ second
+
+66
+00:05:37,620 --> 00:05:38,240
+derivative.
+
+67
+00:05:41,020 --> 00:05:45,180
+Science. لجيت كتاب بتكلم عن الـ poems أو الشعر،
+
+68
+00:05:45,180 --> 00:05:48,800
+literature. مظبوط؟ هيك صار في عندي أنا الآن
+
+69
+00:05:48,800 --> 00:05:52,860
+باستخدام الـ knowledge تبعتي، تمام؟ ومعرفتي
+
+70
+00:05:52,860 --> 00:05:58,370
+بالمجموعات السابقة، بالمجموعات السابقة اللي موجودة
+
+71
+00:05:58,370 --> 00:06:02,010
+عندي، وبروح إيش بصير؟ آخذ كل كتاب أو كل object
+
+72
+00:06:02,010 --> 00:06:06,230
+بقرّن الخصائص تبعته، أو بحاول أطلع، أعرف عن إيش بتكلم
+
+73
+00:06:06,230 --> 00:06:10,910
+الكتاب هذا، وبروح بصنّفه لحاله، بحطه تحت مجموعة أو
+
+74
+00:06:10,910 --> 00:06:16,170
+تحت أي مجموعة من العناصر اللي موجودة. عامّة، تمام؟
+
+75
+00:06:16,170 --> 00:06:22,010
+فمعناته الـ classification هي عضوية المجموعات
+
+76
+00:06:22,010 --> 00:06:25,950
+predefined groups، مجموعات معروفة مسبقاً، وبدي أحدّد
+
+77
+00:06:25,950 --> 00:06:31,030
+مين العناصر، تمام، اللي ممكن يكونوا تحت المجموعة
+
+78
+00:06:31,030 --> 00:06:36,970
+اللي عندي الآن. بيفرق عن التقسيم أو الـ clustering.
+
+79
+00:06:36,970 --> 00:06:42,840
+لو قلت للشباب، أنا بدي أجسّمكم لمجموعات، تمام؟ شغلات
+
+80
+00:06:42,840 --> 00:06:45,480
+كتيرة ممكن تكون مشتركة، أو شغلات كتيرة ممكن تكون
+
+81
+00:06:45,480 --> 00:06:49,840
+مختلفة بينكم. عشان لو رحت أنا قلت، بجسّمكم تبع الـ
+
+82
+00:06:49,840 --> 00:06:56,300
+.. سنة الميلاد، تمام؟ لاحظ أنا في كل الكلام اللي
+
+83
+00:06:56,300 --> 00:07:02,620
+أنا بقوله، ما لي أي control على.. على عدد
+
+84
+00:07:02,620 --> 00:07:05,760
+المجموعات. بينما في الـ cluster.. في الـ
+
+85
+00:07:05,760 --> 00:07:11,400
+classification، عدد المجموعات. طبعاً، بدي أجسّمكم تبعاً
+
+86
+00:07:11,400 --> 00:07:16,100
+لتاريخ ميلادكم، لسنة الميلاد. كل ناس مولودين في سنة
+
+87
+00:07:16,100 --> 00:07:20,840
+هذول بيكونوا مجموعة لحالهم. طب لجيت واحد لحاله، أه
+
+88
+00:07:20,840 --> 00:07:28,040
+هذا، بدوني أعمل مجموعة، ما عنديش مشكلة في الموضوع، لأ.
+
+89
+00:07:28,040 --> 00:07:34,940
+ممكن أسخّر الـ clustering لخدمة الـ classification. ممكن
+
+90
+00:07:34,940 --> 00:07:39,240
+أسخّر الـ clustering لخدمة الـ classification، وهذا
+
+91
+00:07:39,240 --> 00:07:43,240
+بنسميه عادةً semi-supervised learning. إن أنا فعلياً
+
+92
+00:07:43,240 --> 00:07:47,480
+عندي بعض الـ data، بعض الـ data labeled، وبعض الـ
+
+93
+00:07:47,480 --> 00:07:51,560
+data.. وكمّ كبير من الـ data unlabeled. فبروح
+
+94
+00:07:51,560 --> 00:07:56,580
+بجسّمهم لأربع مجموعات حسب معرفتي من هنا، وبطلع في كل
+
+95
+00:07:56,580 --> 00:08:00,560
+cluster، كل مجموعة، إيش الأكثر عناصر من الـ الـ هم
+
+96
+00:08:00,560 --> 00:08:03,600
+label، وبسمّيه، بطلق عليه، وبخلي الـ bag كله، ماشي؟
+
+97
+00:08:03,600 --> 00:08:08,260
+يحملوا نفس الصفة. أجيت أقول بدي أصنفكم تبعاً
+
+98
+00:08:08,260 --> 00:08:09,560
+لمعدلاتكم.
+
+99
+00:08:12,460 --> 00:08:15,200
+واحد يقول يا دكتور، ما هو معروف، المعدلات تسعين وفوق
+
+100
+00:08:15,200 --> 00:08:22,200
+من ثمانين لتسعين، okay. بس لاحظ أنا ما اتكلمت على كل
+
+101
+00:08:22,200 --> 00:08:26,000
+اسم مجموعة. المجموعات هذه ما لها أسامي، مش معرفة
+
+102
+00:08:26,000 --> 00:08:31,280
+بالنسبة لي مسبقاً. تبع أوزانكم، أطوالكم، تمام؟ كل
+
+103
+00:08:31,280 --> 00:08:34,740
+الشغلات هذه، عاملة جماعة. بتتكلم على مجموعات، على
+
+104
+00:08:34,740 --> 00:08:38,720
+مجموعات، وبعدين هيك بنصير إما بحدّد الخاصية وبشغل، أو
+
+105
+00:08:38,720 --> 00:08:42,440
+بروح بقول لشبابنا، نجسّم لمجموعتين، لثلاث مجموعات، و
+
+106
+00:08:42,440 --> 00:08:45,860
+بصير أدوّر على الـ common properties اللي تجمعكم مع
+
+107
+00:08:45,860 --> 00:08:51,860
+بعض. لكن إيش الصفة السائدة لكل مجموعة؟ ما نعرفش
+
+108
+00:08:51,860 --> 00:08:55,580
+لاحقاً. بدنا نصير نفكّر، ندوّر بعنوان. بينما بالـ
+
+109
+00:08:55,580 --> 00:08:59,340
+classification، أنا عندي التصنيفات موجودة عندي
+
+110
+00:08:59,340 --> 00:09:05,320
+مستويات الطلاب موجودة: ممتاز، جيد جداً، جيد، مقبول؟ هذه
+
+111
+00:09:05,320 --> 00:09:08,920
+التصنيفات اللي موجودة عندي الآن. درجة الرطوبة إما
+
+112
+00:09:08,920 --> 00:09:13,960
+هتكون عالية أو متوسطة أو منخفضة. الجو إما هيكون
+
+113
+00:09:13,960 --> 00:09:18,860
+غائم أو غائم جزئياً أو صافي، تمام؟ اليوم إما هيكون
+
+114
+00:09:18,860 --> 00:09:22,420
+ماطر أو هيكون غير ماطر. هذه المعلومات أو هذه الـ
+
+115
+00:09:22,420 --> 00:09:22,860
+categories.
+
+116
+00:09:29,580 --> 00:09:33,860
+بتكلم على category كمجموعات إلها صفات مشتركة محددة
+
+117
+00:09:33,860 --> 00:09:38,040
+وواضحة، وإلها اسم. فهنا احنا بنتكلم على تصنيف
+
+118
+00:09:38,040 --> 00:09:43,860
+classification. إيش اللي احنا بنتعلمه في الـ chapter
+
+119
+00:09:43,860 --> 00:09:44,380
+هذا؟
+
+120
+00:10:02,660 --> 00:10:06,840
+إيش بتتوقع إن احنا نتعلم في الـ chapter هذا الآن؟
+
+121
+00:10:06,840 --> 00:10:18,980
+كيف أقدر أعرف المجموعات؟ مش صحيح، أيوة، أتعرف
+
+122
+00:10:18,980 --> 00:10:24,340
+على التقنيات اللي بتستخدم في التصنيف، غيره. طبعاً هذا
+
+123
+00:10:24,340 --> 00:10:29,700
+حتكلم، شغل مكتبات أو شغل ناس شغّالة في المجال. غير،
+
+124
+00:10:29,700 --> 00:10:34,050
+أه حسن، إيش بتتوقع أن أبدأ أتعلم الفصل هذا، أو
+
+125
+00:10:34,050 --> 00:10:38,450
+الشابتر هذا؟
+
+126
+00:10:38,450 --> 00:10:44,170
+كيف المكتبات بتعمل؟ إيش المبدأ اللي بتشتغل عليه؟
+
+127
+00:10:44,170 --> 00:10:48,470
+أه أحمد، إيش ممكن أتوقع أن أتعلم الفصل هذا، الشابتر
+
+128
+00:10:48,470 --> 00:10:52,430
+هذا؟ على أي أساس أصنف؟
+
+129
+00:10:56,620 --> 00:11:00,240
+أديب، الشغلات المشتركة بين الـ instances أو الـ
+
+130
+00:11:00,240 --> 00:11:07,980
+objects، عشان أقدر أصنفها. أقدر أفرّق بين إيش؟ بين الـ
+
+131
+00:11:07,980 --> 00:11:13,180
+objects أو بين جُثتين. أتعرف على الخصائص تبع كل
+
+132
+00:11:13,180 --> 00:11:19,480
+مجموعة، عشان أقدر أحدد لـ new objects أو الـ unseen
+
+133
+00:11:19,480 --> 00:11:23,900
+samples بتنتمي لأي مجموعة. بس فعلياً، مش أنا اللي
+
+134
+00:11:23,900 --> 00:11:29,680
+هشتغل. الـ Machine، الفكرة الآن لما نتكلم على
+
+135
+00:11:29,680 --> 00:11:32,560
+Classification، هنبدأ نتكلم على Machine Learning
+
+136
+00:11:32,560 --> 00:11:37,160
+Algorithm. هنبدأ نتكلم على تعلم الآلة، أو تعلم..
+
+137
+00:11:37,160 --> 00:11:40,840
+تعلم الآلة. كيف الآلة بتدور على الـ characteristics
+
+138
+00:11:40,840 --> 00:11:45,320
+المشتركة لكل مجموعة. الآن بما أن الـ classification
+
+139
+00:11:45,320 --> 00:11:50,380
+هي واحدة من supervised learning methods. احنا كنا
+
+140
+00:11:50,380 --> 00:11:54,300
+حكينا المرة الماضية، الـ data mining tasks نوعين:
+
+141
+00:11:55,310 --> 00:11:59,690
+Predictive و Descriptive. في الـ Predictive، قلت أنا
+
+142
+00:11:59,690 --> 00:12:03,430
+فيه Classification، وبدي أتنبأ بـ category، بدي أتنبأ
+
+143
+00:12:03,430 --> 00:12:07,310
+بالـ target label تبع المجموعة. وفي عندي Regression،
+
+144
+00:12:07,310 --> 00:12:11,490
+بدي أتنبأ بـ continuous value، بـ قيمة، وقلنا في الـ
+
+145
+00:12:11,490 --> 00:12:15,670
+Descriptive، في الوصفية، إما بتكلم على Clustering،
+
+146
+00:12:15,670 --> 00:12:20,770
+تقسيم لمجموعات، أو Outlier Detection، تحديد الشوائب،
+
+147
+00:12:20,770 --> 00:12:27,070
+أو الـ Association Rules، تحديد العلاقات ما بين
+
+148
+00:12:27,070 --> 00:12:34,350
+العناصر اللي موجودة. الآن، ضمن الكلام هذا، أنا هتعرف
+
+149
+00:12:34,350 --> 00:12:37,630
+على مجموعة من الـ algorithms، والخوارزميات اللي
+
+150
+00:12:37,630 --> 00:12:45,450
+بتستخدمها من أجل استنباط خصائص المجموعات المعرفة
+
+151
+00:12:45,450 --> 00:12:51,390
+مسبقاً، اللي موجودة عندي في الـ data. ومن ثم، لما بدي
+
+152
+00:12:51,390 --> 00:12:55,000
+أجي أعمل prediction، بدي تديني الـ prediction، أو بدي
+
+153
+00:12:55,000 --> 00:12:58,740
+تديني الـ category أو الـ group، أو اسم المجموعة اللي
+
+154
+00:12:58,740 --> 00:13:01,540
+بينتمي إليها الـ object الجديد هذا، اللي هو الـ
+
+155
+00:13:01,540 --> 00:13:06,640
+unseen object أو unseen instance. يعني فعلياً أنا
+
+156
+00:13:06,640 --> 00:13:09,840
+بدي أشوف الآلة كيف اللي بتتعلم. طب أنا وين في
+
+157
+00:13:09,840 --> 00:13:14,400
+الموضوع؟ أنت دورك، جهّزت البيانات، بدك تختار algorithm
+
+158
+00:13:14,400 --> 00:13:18,100
+كويس، وتقول للـ algorithm، اقرأ البيانات، وتعلّم منها.
+
+159
+00:13:18,100 --> 00:13:23,160
+تعمل evaluation، قبل ما تقول أنا صار فيه عندي model
+
+160
+00:13:23,160 --> 00:13:26,280
+بيقدر يعمل prediction للـ category أو للـ class اللي
+
+161
+00:13:26,280 --> 00:13:34,320
+موجود عندها. الـ classification
+
+162
+00:13:34,320 --> 00:13:39,020
+هي
+
+163
+00:13:39,020 --> 00:13:41,840
+واحدة من الـ mining tasks أو الـ data mining tasks
+
+164
+00:13:41,840 --> 00:13:46,140
+التقليدية. الـ task يعني من أهم أو من أكثر الـ tasks
+
+165
+00:13:46,140 --> 00:13:52,520
+شهرةً.  لـ classification، وطبعاً ممتدّة أساساً بالـ
+
+166
+00:13:52,520 --> 00:13:55,060
+Machine Learning. عادة الـ Machine Learning
+
+167
+00:13:55,060 --> 00:13:58,880
+Algorithms، الشباب، بشكل عام، أو التقنيات بتشتغل ضمن
+
+168
+00:13:58,880 --> 00:14:04,860
+منهجيات معيّنة. الأولى، أنه فعلياً، هل الـ Machine
+
+169
+00:14:04,860 --> 00:14:08,940
+Learning هذه بتتدرّب أو بتتعلم من خلال الـ Human
+
+170
+00:14:08,940 --> 00:14:15,200
+Supervision، من خلال مراقبة الإنسان، أو إشراف الإنسان.
+
+171
+00:14:15,200 --> 00:14:19,280
+الفكرة كالتالي: ما ينفعش أنا أروح أقول للطلاب في
+
+172
+00:14:19,280 --> 00:14:23,900
+المدرسة هذه، مجموعة الكتب، أروح أدخّلهم في الصف الآن
+
+173
+00:14:23,900 --> 00:14:27,660
+من العاشرة للحادية عشرة، عليكم عربي، ادرسوا كتاب العربي
+
+174
+00:14:27,660 --> 00:14:35,260
+بدون ما يكون عندهم
+
+223
+00:18:05,560 --> 00:18:10,260
+batch learning كذلك في عندي الـ trend في الـ machine
+
+224
+00:18:10,260 --> 00:18:14,240
+learning هل هي model-based ولا instance-based
+
+225
+00:18:14,240 --> 00:18:19,860
+model-based يعني هيروح يبني model، هيروح يبني موديل
+
+226
+00:18:19,860 --> 00:18:24,680
+هو اللي بديه يعمل prediction لاحقاً، بينما بالـ
+
+227
+00:18:24,680 --> 00:18:28,700
+instance-based في كل مرة بديه يعمل prediction بديه
+
+228
+00:18:28,700 --> 00:18:34,620
+يرجع للـ data الأصلية، وطبعاً هدول الشغلتين لكل
+
+229
+00:18:34,620 --> 00:18:39,480
+واحدة فيه إيجابياتها وإليها سلبياتها، كذلك في
+
+230
+00:18:39,480 --> 00:18:43,040
+trend آخر فيه deterministic وفيه probabilistic
+
+231
+00:18:43,040 --> 00:18:47,390
+approach في الـ learning، في الـ deterministic اللي
+
+232
+00:18:47,390 --> 00:18:51,610
+هو الدقيق أو الموحد، أن الـ algorithm هذا مع الـ
+
+233
+00:18:51,610 --> 00:18:56,370
+input هذا لو عدته خمسة آلاف مرة، لو عدته مليون مرة
+
+234
+00:18:56,370 --> 00:19:01,070
+هيديني نفس النتيجة، محدد، بينما في الـ probabilistic
+
+235
+00:19:01,070 --> 00:19:04,310
+طبعاً في الـ deterministic مافيش عندي مجالة
+
+236
+00:19:04,310 --> 00:19:09,240
+randomness، مافيش مجالة عشوائية، كله شغال ضمن قيم
+
+237
+00:19:09,240 --> 00:19:12,580
+حقيقية موجودة بين إيدينا، بينما في الـ
+
+238
+00:19:12,580 --> 00:19:15,720
+probabilistic approach بيعتمد على الـ randomness
+
+239
+00:19:15,720 --> 00:19:18,660
+لأنه بياخد sample من الـ population وبيصير.. ممكن
+
+240
+00:19:18,660 --> 00:19:23,180
+تتغير.. عفواً، النتيجة تتغير ما بين مرة والتانية
+
+241
+00:19:23,180 --> 00:19:26,200
+بشكل
+
+242
+00:19:26,200 --> 00:19:28,880
+عام، احنا بنتكلم على الـ supervised learning و
+
+243
+00:19:28,880 --> 00:19:34,050
+بالتحديد الـ classification، الآن supervision زي ما
+
+244
+00:19:34,050 --> 00:19:37,870
+قلنا سابقاً، training data، الـ data set اللي أنا
+
+245
+00:19:37,870 --> 00:19:49,150
+اخترتها بتتكلم عن الـ heart disease، الـ
+
+246
+00:19:49,150 --> 00:19:55,090
+body mass index، الـ blocked artery، تصلب الشرايين،
+
+247
+00:19:55,090 --> 00:20:04,810
+قلم في الصدر، وفي الآخر التصنيف التبعي، هل هذا heart
+
+248
+00:20:04,810 --> 00:20:11,790
+disease؟ هل هذا مرض قلب؟ مرض قلب ولا لأ؟ yes و no، الـ
+
+249
+00:20:11,790 --> 00:20:18,030
+data set في جو زي اليوم، بتكلم الجو غائم، الـ outlook
+
+250
+00:20:18,030 --> 00:20:24,790
+cloudy، الـ temperature عشرة مثلاً أو اثنا عشر، الـ
+
+251
+00:20:24,790 --> 00:20:32,600
+humidity intermediate، متوسطة، الـ Windy، فيه رياح، بدي
+
+252
+00:20:32,600 --> 00:20:38,720
+أعمل، هل اليوم ماطر أو لأ؟ كـ category، كفئة، لاحظ أنا
+
+253
+00:20:38,720 --> 00:20:43,400
+الآن بتكلم هذه الـ label تبعتي، هي الـ target، هي الـ
+
+254
+00:20:43,400 --> 00:20:47,140
+group، الـ predefined group، إما هدول الـ instances
+
+255
+00:20:47,140 --> 00:20:52,320
+الـ data set مقسمين لمجموعتين، ناس مصابين بأمراض
+
+256
+00:20:52,320 --> 00:20:58,190
+القلب وناس غير مصابة، الجو أيام ماطرة وأيام غير
+
+257
+00:20:58,190 --> 00:21:03,210
+ماطرة، تصنيفات الطلاب جيد جداً أو ممتاز، جيد جداً، جيد،
+
+258
+00:21:03,210 --> 00:21:07,210
+مقبول، هذه التصنيفات الموجودة معروفة مسبقاً، وهذه
+
+259
+00:21:07,210 --> 00:21:11,770
+هتكون موجودة عندنا في الـ training set، هذه لازم تكون
+
+260
+00:21:11,770 --> 00:21:16,530
+عاملة combination ما بين الـ attributes اللي عندي
+
+261
+00:21:16,530 --> 00:21:20,310
+بالإضافة
+
+262
+00:21:21,330 --> 00:21:25,310
+الـ groups أو الـ predefined groups، يعني بين جثتين
+
+263
+00:21:25,310 --> 00:21:34,190
+محدد له بشكل دقيق، كل raw بيتبع أي مجموعة، تمام؟ كل
+
+264
+00:21:34,190 --> 00:21:39,870
+raw بيتبع أي مجموعة، وعادة هذه بنسميها احنا
+
+265
+00:21:39,870 --> 00:21:45,990
+training data، training data، فالـ classification هي
+
+266
+00:21:45,990 --> 00:21:53,400
+مهمتها تعمل predict categorial class label، تتنبأ
+
+267
+00:21:53,400 --> 00:21:59,360
+بالفئة، باسم الفئة تبعتها، تبعت المجموعات، للـ
+
+268
+00:21:59,360 --> 00:22:03,160
+unseen data، طبعاً الـ class label هذا إما بيكون
+
+269
+00:22:03,160 --> 00:22:10,460
+discrete أو بيكون nominal، شو يعني nominal data؟
+
+270
+00:22:10,460 --> 00:22:15,620
+text.. text.. text.. تمام؟ طب شو يعني discrete
+
+271
+00:22:15,620 --> 00:22:20,450
+data؟ قيم منفصلة عن بعضها، هي فعلياً ظاهرها
+
+272
+00:22:20,450 --> 00:22:24,690
+continuous، عشر، عشرين، ثلاثين، تمام؟ ولما بتروح
+
+273
+00:22:24,690 --> 00:22:27,630
+يعمل الـ prediction هو بتقول أما عشرة أو عشرين أو
+
+274
+00:22:27,630 --> 00:22:30,570
+ثلاثين، مالهاش علاقة بالأرقام أو العلاقة بالحساب
+
+275
+00:22:30,570 --> 00:22:36,670
+مطلقاً، الآن في
+
+276
+00:22:36,670 --> 00:22:39,570
+الـ classification هيبني prediction model عشان
+
+277
+00:22:39,570 --> 00:22:43,410
+يتنبأ بالـ discrete values اللي موجودة عندها، تعالى
+
+278
+00:22:43,410 --> 00:22:49,530
+نشوف الصورة هاي، أو بلاش، قبل ما نروح على الصورة هاي
+
+279
+00:22:49,530 --> 00:22:53,010
+عشان أنا بقى أظل أقول Model Model Model Model شو
+
+280
+00:22:53,010 --> 00:23:06,790
+يعني Model؟ نموذج، نموذج، تمام، وشو
+
+281
+00:23:06,790 --> 00:23:11,250
+يعني نموذج؟ تصور، تصور، تصور، تصور، تصور، تصور،
+
+282
+00:23:11,250 --> 00:23:13,250
+تصور، تصور، تصور، تصور، تصور، تصور، تصور، تصور،
+
+283
+00:23:13,250 --> 00:23:13,750
+تصور، تصور، تصور، تصور، تصور، تصور، تصور، تصور،
+
+284
+00:23:13,750 --> 00:23:16,030
+تصور، تصور
+
+285
+00:23:18,130 --> 00:23:22,990
+صورة مصغرة، شوف أحمد من غاد بيقول لك photo
+
+286
+00:23:22,990 --> 00:23:26,770
+description، بس سيبك من الـ photo واتكلم عن الـ
+
+287
+00:23:26,770 --> 00:23:31,290
+description، أنا بقول لك صح، صورة مصغرة أو نموذج، بلاش
+
+288
+00:23:31,290 --> 00:23:38,410
+نقول مصغر، صورة تصف النموذج أو الشكل أو الـ object
+
+289
+00:23:38,410 --> 00:23:41,730
+اللي جاي عندي، الآن بتروح شركة Apple على سبيل.. لأ
+
+290
+00:23:41,730 --> 00:23:43,410
+انتوا أقول لكوا علاقة بما في ناس بتكون interested
+
+291
+00:23:43,410 --> 00:23:48,310
+بالسيارات، تروح شركة BMW بتقول لك والله إحنا في عندنا
+
+292
+00:23:48,310 --> 00:23:53,470
+الـ model تبع 2030 من السيارة جاهز، شو
+
+293
+00:23:53,470 --> 00:23:59,130
+يعني؟ مش.. لأ لأ ما تكلم ال.. ما تكلم على الـ model
+
+294
+00:23:59,130 --> 00:24:05,770
+يعني أن هو في عنده تصور أو وصف دقيق لشكل السيارة،
+
+295
+00:24:05,770 --> 00:24:08,470
+إيش السيارة بدها تكون، اللي في الـ 2030 يا همام،
+
+296
+00:24:08,470 --> 00:24:12,150
+ممكن prototype أو ممكن يكون عاملة prototype، بس في
+
+297
+00:24:12,150 --> 00:24:17,710
+الآخر أهم في الـ prototype هذا مثلاً، معارض
+
+298
+00:24:17,710 --> 00:24:20,990
+السيارات، لما بروح بيعرض في المعارض، إيش بقول لك؟
+
+299
+00:24:20,990 --> 00:24:25,910
+بقول لك، هي model، تمام؟ عن السيارة، هي model عن
+
+300
+00:24:25,910 --> 00:24:26,450
+الجوال
+
+301
+00:24:29,520 --> 00:24:34,720
+sample، إيش بستفيد من الـ sample هاي؟ فعلياً بشوف الـ
+
+302
+00:24:34,720 --> 00:24:39,000
+real description، بشوف وصفه دقيق كيف بيكون، لأ لما
+
+303
+00:24:39,000 --> 00:24:42,700
+بروح بقول لك في عندي الـ model تبعت الجوال مكونة من أو
+
+304
+00:24:42,700 --> 00:24:47,500
+هيك كده، فبديك وصفه، جدش حجمه، جدش الكاميرا، جدش وزنه،
+
+305
+00:24:47,500 --> 00:24:50,020
+جدش الـ processor، جدش الـ memory، جدش الـ storage
+
+306
+00:24:50,020 --> 00:24:53,760
+تبعته، إيش هو التقنية المستخدمة، مع الـ bluetooth، مع
+
+307
+00:24:53,760 --> 00:24:57,300
+الـ land، مع الـ wireless، عفواً، كل الشغلات هذه بتكون
+
+308
+00:24:57,300 --> 00:25:04,310
+موصوفة، وبالتالي الـ model هي عبارة عن طريقة لوصف شيء
+
+309
+00:25:04,310 --> 00:25:07,150
+معين، objects معين، مرة عليكوا تشغلوا اسمها data
+
+310
+00:25:07,150 --> 00:25:11,930
+model في الـ database زمان؟ الفصل الماضي يا إيهاب،
+
+311
+00:25:11,930 --> 00:25:16,970
+لما اتكلمنا على الـ data model وقبلها أنت بتعرف
+
+312
+00:25:16,970 --> 00:25:21,750
+شوية عن الـ relational model، تمام؟ مصبوط؟ ففعلياً
+
+313
+00:25:21,750 --> 00:25:25,450
+ليش بسميها model؟ لأنّه بوصف البيانات، وبالتالي
+
+314
+00:25:25,450 --> 00:25:31,710
+أنا الآن الـ model اللي هتكلم عليه هي عبارة عن آلية
+
+315
+00:25:31,710 --> 00:25:37,370
+لِوصف الـ knowledge، ما تنساش الـ data mining هدفها
+
+316
+00:25:37,370 --> 00:25:42,450
+knowledge
+
+317
+00:25:42,450 --> 00:25:45,870
+extraction
+
+318
+00:25:45,870 --> 00:25:53,930
+ولا لأ؟ هدف الـ mining task استخراج knowledge من الـ
+
+319
+00:25:53,930 --> 00:25:56,970
+data set اللي موجودة، طب الـ knowledge اللي طلعت هاي
+
+320
+00:25:58,780 --> 00:26:04,060
+كيف بدي أوصفها؟ كيف بدي أستخدمها؟ لازم تكون ضمن
+
+321
+00:26:04,060 --> 00:26:10,040
+model معين، عشان نقدر نستخدمها، الآن بالمثال
+
+322
+00:26:10,040 --> 00:26:14,300
+اللي موجود عندي هان في
+
+323
+00:26:14,300 --> 00:26:18,800
+عندي input raw data، مجموعة من التفاح حسب الصورة
+
+324
+00:26:18,800 --> 00:26:26,140
+اللي موجودة عندي هان، ثمان تفاحات، أحجامهم، ألوانهم،
+
+325
+00:26:27,010 --> 00:26:30,190
+الأوراق اللي موجودة عليهم، بالإضافة للريحة والطعم،
+
+326
+00:26:30,190 --> 00:26:33,610
+ريحة
+
+327
+00:26:33,610 --> 00:26:38,890
+تفاح، اللي هو ريحة ولا ما له؟ مش ريحة، ممتاز، لو ضليتكم
+
+328
+00:26:38,890 --> 00:26:41,630
+ساكتين، بقول لكم كيف بندخلها بس، وما أنك أنت سألتني،
+
+329
+00:26:41,630 --> 00:26:46,810
+خلصنا، فالآن هذه الـ characteristics الوصفية تبعت الـ
+
+330
+00:26:46,810 --> 00:26:51,750
+data هي، هم، هروح نديها للـ algorithm، أو أختار
+
+331
+00:26:51,750 --> 00:26:55,290
+algorithm، machine learning algorithm يقرأ الـ data
+
+332
+00:26:55,290 --> 00:27:03,870
+set كلّها، يعملها تحليل، يِوجد علاقة ما بين الحجم و
+
+333
+00:27:03,870 --> 00:27:10,110
+اللون والرائحة والطعم، كل الشغلات هذه، لما تديله
+
+334
+00:27:10,110 --> 00:27:14,570
+الـ data set أو العناصر هذه، يكون قادر على أن يقول
+
+335
+00:27:14,570 --> 00:27:20,590
+لي أن هذه تفاحة، الآن الـ model هذا أنا روحت اختبرته
+
+336
+00:27:20,590 --> 00:27:27,690
+بتفاحة خضراء، تفاحة ولا لأ؟ تمام؟ اللون واحدة من الـ
+
+337
+00:27:27,690 --> 00:27:32,010
+characteristics اللي كانت موجودة، بس مش كل شيء، الآن
+
+338
+00:27:32,010 --> 00:27:37,070
+الـ model تبعي الأصل يقول إنه هذا تفاحة، لو أنا روحت
+
+339
+00:27:37,070 --> 00:27:45,770
+أضفت هان مجموعة
+
+340
+00:27:45,770 --> 00:27:50,750
+من الـ mango أو البرتقال، تمام؟ مجموعة من البرتقال،
+
+341
+00:27:50,750 --> 00:27:57,670
+وصار في عندي two groups، في عندي هذه apple
+
+342
+00:27:57,670 --> 00:28:04,870
+وهذه orange، الـ system اللي يتعرف على خصائص الـ
+
+343
+00:28:04,870 --> 00:28:08,890
+apple هي المفهوم، التصنيف، أن أنا خلاص okay، هدول
+
+344
+00:28:08,890 --> 00:28:13,550
+هي المصنف تبعي apple أو orange، فالـ system هيتعرف
+
+345
+00:28:13,550 --> 00:28:22,190
+على خصائص الـ apple وخصائص التفاح ويبني model قادر
+
+346
+00:28:22,190 --> 00:28:28,050
+على التفريق ما بين التنتين، فلما أنا بديّه تفاحة،
+
+347
+00:28:28,050 --> 00:28:30,750
+هيقول لي تفاحة، أدّيته برتقالة، الأصل يقول لي
+
+348
+00:28:30,750 --> 00:28:37,430
+برتقالة، طب لو أدّيته حبة مانجو، مش هيعرف، غلط، في
+
+349
+00:28:37,430 --> 00:28:41,490
+الـ classification هان لأنه آلة، وما فيش مجال يا
+
+350
+00:28:41,490 --> 00:28:45,270
+هذه يا هذه، ما فيش مجال، ما فيش خيار ثالث، أنت
+
+351
+00:28:45,270 --> 00:28:48,290
+ما تركت له، في موضوع التصنيف، هي اللي أنا بوصلك
+
+352
+00:28:48,290 --> 00:28:53,020
+إياها، في موضوع التصنيف، ما فيش مجال، عندك أربع فئات
+
+353
+00:28:53,020 --> 00:28:55,920
+بدك تحط تحت واحدة من الأربع فئات، عندك two
+
+354
+00:28:55,920 --> 00:29:00,020
+categories، بدك تضيفها لواحدة من الـ categories بس
+
+355
+00:29:00,020 --> 00:29:04,760
+غالباً هيضيفها للأقرب، يعني تخيّل أنّه والله كان في الـ
+
+356
+00:29:04,760 --> 00:29:08,800
+mango اللي بنتكلم عليها هي لونها أحمر مثلاً وما أخذة
+
+357
+00:29:08,800 --> 00:29:16,910
+شكل كروي أكثر، تمام؟ فهتروح باتجاه التفاح، في الآخر
+
+358
+00:29:16,910 --> 00:29:21,570
+هو صح صنّفها غلط في كل الأحوال، بس هو اجتهد.. اجتهد
+
+359
+00:29:21,570 --> 00:29:27,390
+وراح ضافها للأقرب حسب الـ object اللي موجود، لكن في
+
+360
+00:29:27,390 --> 00:29:32,190
+المقابل كان في حبة مانجو أخرى أكبر حجماً ولونها
+
+361
+00:29:32,190 --> 00:29:37,430
+برتقالي، تمام؟ فمش ضروري أروح أصنّف لك إياها تفاح،
+
+362
+00:29:37,430 --> 00:29:42,030
+بروح أصنّف لك إياها إيش؟ Orange، لأنّه فعلياً الـ
+
+363
+00:29:42,030 --> 00:29:49,070
+characteristic تبعتها متشابهة، نعمل، مش ممكن عمرك
+
+364
+00:29:49,070 --> 00:29:54,310
+مرة عليك برنامج أنّه بيبني فئة لوحده، ممكن يتعلّم
+
+365
+00:29:54,310 --> 00:29:57,650
+يبني.. يبني الحالة، يبني الحالة، ده حالة يعني إذا
+
+366
+00:29:57,650 --> 00:30:01,890
+تجي ده أول مرة، أول مرة تصنّفها لحالة، وممكن الـ human
+
+367
+00:30:01,890 --> 00:30:06,970
+يقول لك شوف رجع لوين، بعدين الـ human يقول، الـ human هو
+
+368
+00:30:06,970 --> 00:30:12,520
+صاحب القرار، عمرها ما قال غيرت حال تمام أو أخدت
+
+369
+00:30:12,520 --> 00:30:15,980
+decision لوحدها، حتى كل اللي بنشوفه في الذكاء
+
+370
+00:30:15,980 --> 00:30:23,100
+الاصطناعي مردّه لتخطيط صحيح من الـ human، وتصرف الآلة
+
+371
+00:30:23,100 --> 00:30:27,020
+ما هو إلا من تصرف الـ human ضمن المسار اللي رسمه
+
+372
+00:30:27,020 --> 00:30:30,540
+الآن سيبك من الأفلام اللي احنا بنشوفها أن الـ.. الـ
+
+373
+00:30:30,540 --> 00:30:34,620
+.. اتطورت حتى تقطع.. تقطع.. تجيب البشر وتحتل
+
+374
+00:30:34,620 --> 00:30:39,060
+الكون، ده ما فيش منه، تمام؟
+
+375
+00:30:40,540 --> 00:30:45,060
+طيب، الآن فبالتالي يا محمد احنا بنتكلم، ما فيش مجال، ما فيش
+
+376
+00:30:45,060 --> 00:30:48,280
+مجال أن أروح فئة، أضيف فئة جديدة، لأ، الفئات موجودة
+
+377
+00:30:48,280 --> 00:30:52,340
+مسبقاً، وبناء عليه أنا هشتغل مع الفئات اللي موجودة
+
+378
+00:30:52,340 --> 00:30:56,060
+عندي، فضل
+
+379
+00:30:59,640 --> 00:31:02,160
+مية بالمئة، الفرق بين الـ regression والـ
+
+380
+00:31:02,160 --> 00:31:06,300
+classification أن الـ classification categorical
+
+381
+00:31:06,300 --> 00:31:10,940
+value، discrete values، واحدة من التنتين هدول، بينما
+
+382
+00:31:10,940 --> 00:31:15,960
+بالـ regression بدّه يديني قيمة continuous value،
+
+383
+00:31:15,960 --> 00:31:26,380
+number، بدها تكون موجودة عندي، طيب الآن الـ
+
+384
+00:31:26,380 --> 00:31:32,500
+classification هي عبارة عن تكنيك أو خوارزمية أو تقنية
+
+385
+00:31:32,500 --> 00:31:36,440
+من أجل التنبؤ
+
+386
+00:31:36,440 --> 00:31:43,340
+to predict group membership، شو يعني group
+
+387
+00:31:43,340 --> 00:31:50,640
+membership؟ عضوية المجموعات، هل هذا ملائم لعضوية
+
+388
+00:31:50,640 --> 00:31:54,240
+المجموعة الفلانية ولا لأ؟ في عندي مجموعة اسمها الـ
+
+389
+00:31:54,240 --> 00:32:00,440
+Smart Students في الـ IT، أنت ملائم إلها ولا غير
+
+390
+00:32:00,440 --> 00:32:05,860
+ملائم؟ مش أنت اللي بتقرر، تمام؟ في لجنة هتروح
+
+391
+00:32:05,860 --> 00:32:11,460
+تختبرك وبناء عليها تقول أنت تنصلح ولا ما تصلحش،
+
+392
+00:32:11,460 --> 00:32:14,380
+ليش؟ لأنّه كمان مرة الـ prediction مش أنت صاحب
+
+393
+00:32:14,380 --> 00:32:19,160
+قراره، عفواً، الـ classification أو التصنيف مش أنت
+
+394
+00:32:19,160 --> 00:32:23,980
+صاحب قراره، في عندنا كل صنف إله rule أو خصائص
+
+395
+00:32:23,980 --> 0
+
+445
+00:36:27,350 --> 00:36:32,570
+negative orange, not orange.  ما بنقولش تفاح لأن لو حط
+
+446
+00:36:32,570 --> 00:36:35,410
+المانجا وحط الموز تحت التفاح،  في عندنا خطأ
+
+447
+00:36:35,410 --> 00:36:40,190
+فبنقول إحنا orange و not orange، وهكذا الآن في
+
+448
+00:36:40,190 --> 00:36:46,670
+مرحلة training زي ما قلنا إنه هيأخد كل ال data
+
+449
+00:36:46,670 --> 00:36:51,450
+points اللي موجودة عندها، اللي هي ال samples، مع ال
+
+450
+00:36:51,450 --> 00:36:58,820
+correct label المرتبط فيها، ويحاول يتعلم يصل لـ
+
+451
+00:36:58,820 --> 00:37:03,280
+pattern معين، كيف ال label هذا مرتبط بالـ point، زي
+
+452
+00:37:03,280 --> 00:37:09,020
+ما حكينا قبل لحظات، بمجرد إن ال system هذا تعلم، بدي
+
+453
+00:37:09,020 --> 00:37:13,300
+يبدأ يتصرف الآن، فتصرفه هيكون عبارة عن function
+
+454
+00:37:13,300 --> 00:37:18,900
+prediction function، هتأخد ال input تبع ال sample
+
+455
+00:37:18,900 --> 00:37:23,480
+تبع ال data point بدون ال label، عشان تعمل هي
+
+456
+00:37:23,480 --> 00:37:27,500
+prediction للـ label أو لل category اللي موجودة
+
+457
+00:37:27,500 --> 00:37:33,980
+عندها. فال
+
+458
+00:37:33,980 --> 00:37:37,240
+step الأولى بنسميها إحنا ال model construction
+
+459
+00:37:37,240 --> 00:37:43,040
+بناء ال model في ال regression يا جماعة الخير، وحتى
+
+460
+00:37:43,040 --> 00:37:45,960
+في ال classification، ممكن ال model تبعي يكون عبارة
+
+461
+00:37:45,960 --> 00:37:48,620
+عن  binary classification، يكون عبارة عن linear
+
+462
+00:37:48,620 --> 00:37:53,740
+line، linear equation، ال Y equal M
+
+463
+00:38:07,350 --> 00:38:13,660
+معادلة خط مستقيم. ماهي الخط المستقيم مهمته؟ بيفصل
+
+464
+00:38:13,660 --> 00:38:17,020
+بين شغلتين، اللي فوق الخط category، واللي تحت الخط
+
+465
+00:38:17,020 --> 00:38:20,800
+category تانية. ففي لحظة ال binary classification،
+
+466
+00:38:20,800 --> 00:38:25,840
+إذا قدرت أنا أصل لمعادلة الخط المستقيم اللي بيفصل
+
+467
+00:38:25,840 --> 00:38:31,160
+ما بين ال two categories، خلاص هي ال model تبعي
+
+468
+00:38:31,160 --> 00:38:37,700
+بصير باخد ال instances، تمام؟ وبقارنها، إذا كانت
+
+469
+00:38:37,700 --> 00:38:41,080
+أكبر من كده فهي positive، أقل من كده فهي negative،
+
+470
+00:38:41,080 --> 00:38:44,860
+true أو false، orange أو not orange، فهي ال model
+
+471
+00:38:44,860 --> 00:38:49,480
+اللي أنا بدور عليه. في ال model construction، إحنا
+
+472
+00:38:49,480 --> 00:38:53,500
+عادة بنفترض إن ال data set، كل sample في ال data
+
+473
+00:38:53,500 --> 00:39:00,070
+set بتنتمي ل only one category، لأن لو نفس ال data
+
+474
+00:39:00,070 --> 00:39:03,030
+set، أو عفوا نفس ال instance هذه تكررت مع different
+
+475
+00:39:03,030 --> 00:39:07,250
+category، هيكون في عندي مشكلة. الشغل اللي بتعلمه قبل
+
+476
+00:39:07,250 --> 00:39:10,390
+شوية، بدي أحاول أنفيها أو بدي أراجع عنها وأحط
+
+477
+00:39:10,390 --> 00:39:13,970
+واحدة مضادة لها، وهذا الكلام ما بيصير تماما
+
+478
+00:39:13,970 --> 00:39:18,070
+تماماً، مثل ما آجي أقول، أعلم الولد الصغير، أقول له 2
+
+479
+00:39:18,070 --> 00:39:23,850
+ضرب 3 يساوي 6، وفي نفس الوقت أروح أقول له بعد فترة
+
+480
+00:39:23,850 --> 00:39:26,090
+2 ضرب 3 يساوي 16.
+
+481
+00:39:29,010 --> 00:39:34,810
+يحفظ مين فيهم؟ مين فيهم الصح؟ الأخيرة صح، اه؟
+
+482
+00:39:34,810 --> 00:39:37,850
+ما بيعرفش ال system، ال computer ما بيعرفش، أنت في
+
+483
+00:39:37,850 --> 00:39:42,370
+مرحلة التلقين، الإثنين صح، ولما يصير في عنده معلومة
+
+484
+00:39:42,370 --> 00:39:47,870
+متضاربة، فعلياً مش هيقدر يأخذ decision في أي حالة
+
+485
+00:39:47,870 --> 00:39:52,140
+فيها. اتنين ضرب تلاتة، هذا اللي بيصير، عشان هيك
+
+486
+00:39:52,140 --> 00:39:55,820
+بنفترض إنه في موضوع ال learning، أو في مرحلة
+
+487
+00:39:55,820 --> 00:39:58,180
+training أو ال learning في ال model construction،
+
+488
+00:39:58,180 --> 00:40:04,680
+إن كل instance بتنتمي فقط ل only one category، one
+
+489
+00:40:04,680 --> 00:40:10,620
+label. مجموعة ال data، ال 6 اللي أنا بدي أدرب عليها
+
+490
+00:40:10,620 --> 00:40:14,640
+النظام، أو اللي بدي أحللها النظام، بحيث إنه يأخذ منها
+
+491
+00:40:14,640 --> 00:40:19,910
+يستخلص ال model منها، بسميها ال training set، بسميها
+
+492
+00:40:19,910 --> 00:40:26,410
+ال training set. دكتور، نعم. ال training set، كلمة
+
+493
+00:40:26,410 --> 00:40:30,110
+بتعمل ال model، بنقل عليها، لأن كل واحد مثلاً في واجب
+
+494
+00:40:30,110 --> 00:40:33,350
+مخل، تلقى ال training set من خمسين ألف دورة، مش
+
+495
+00:40:33,350 --> 00:40:36,170
+هتبقى ال model مثلاً زي ما سيكت في سبوك أو أمازون،
+
+496
+00:40:36,170 --> 00:40:38,530
+بتبني، أو ال training set دي ال model. طب ما إحنا
+
+497
+00:40:38,530 --> 00:40:40,970
+قلنا، مين جابلنا هيك، هيقولنا، كل ما كبرت ال
+
+498
+00:40:40,970 --> 00:40:44,610
+training data set تبعتي، بكون فرصة ال prediction
+
+499
+00:40:44,610 --> 00:40:48,570
+تبعتي إنها تكون أدق، أعلى. كيف الاسم يعني؟ مثلاً خمسين
+
+500
+00:40:48,570 --> 00:40:53,690
+ألف raw data. شوف لأ، لأ، شوية. أنت عندك ال data set كلها
+
+501
+00:40:53,690 --> 00:40:57,410
+خمسين ألف raw data، وبدك تعمل training على تلاتين ألف raw data،
+
+502
+00:40:57,410 --> 00:41:01,370
+مثلاً، مش كافي، لأن عادة جماعة الخبرة، ال rows
+
+503
+00:41:01,370 --> 00:41:04,990
+المستخدمة، أو الحجم لل training set بيكون أكبر من
+
+504
+00:41:04,990 --> 00:41:08,320
+ال testing set. يعني الآن، إذا بتقدر تعمل training
+
+505
+00:41:08,320 --> 00:41:11,160
+على كل ال data، وتختبره في data مختلفة، بيكون ممتاز.
+
+506
+00:41:11,160 --> 00:41:15,060
+عشان هيك كنا في ال data preparation، نأكد هل في
+
+507
+00:41:15,060 --> 00:41:19,160
+مصادر أخرى للبيانات عندك، ولا مافيش؟ وجديش حجمها،
+
+508
+00:41:19,160 --> 00:41:22,540
+طبعاً؟ الآن، إذا أنت لاحظت في أخر assignment، أو في
+
+509
+00:41:22,540 --> 00:41:25,720
+ال assignment الأخير، مطلوب منك، آخر بند، اجسم ال
+
+510
+00:41:25,720 --> 00:41:31,500
+data set اللي عندك، 70% لل training set، و 30% لل
+
+511
+00:41:31,500 --> 00:41:35,380
+test set. مصبوط؟ وهذه التسأل ليش؟ لأنه ما بديش إياك
+
+512
+00:41:35,380 --> 00:41:38,980
+تدرب كل... تدربه على نفس... يعني على نفس ال data، و
+
+513
+00:41:38,980 --> 00:41:42,820
+بعدين آجي أحترمه، لأن كيف بدي أختبره أو بدي أفحص
+
+514
+00:41:42,820 --> 00:41:48,280
+مدى دقة العنصر. كمان مرة يا جماعة الخير، بنأكد، كل ما
+
+515
+00:41:48,280 --> 00:41:53,800
+كانت ال data set أكبر، ال training set أكبر، المفروض
+
+516
+00:41:53,800 --> 00:41:56,860
+إن كل ما تكون ال data، أو خلّنا نقول ال knowledge
+
+517
+00:41:56,860 --> 00:42:02,120
+تبعتي أدق، ال classification تبعتي بتصير أدق، لكن
+
+518
+00:42:02,120 --> 00:42:05,220
+برضه مش منطق إن يكون أنا في عندي اتنين مليار
+
+519
+00:42:05,220 --> 00:42:10,800
+record، تمام؟ وأنا بروح بتقبج عليهم كلهم، عملية ال
+
+520
+00:42:10,800 --> 00:42:13,940
+training بحد ذاتها هذه، هتصير تأخذ مني أشهر لما
+
+521
+00:42:13,940 --> 00:42:17,360
+تنتهي. فبتصير ممكن ال task اللي أنا بأشتغل عليها
+
+522
+00:42:17,360 --> 00:42:24,370
+أساساً خلصت، بطلتلها قيمة. فأنت برضه بتوازن ما بين ال
+
+523
+00:42:24,370 --> 00:42:28,310
+accuracy تبع النظام، وعامل الوقت أو ال performance
+
+524
+00:42:28,310 --> 00:42:34,610
+تبع ال training، جديش بيحقق نتائج في
+
+525
+00:42:34,610 --> 00:42:40,110
+ال data set اللي موجود عندنا. هان الآن، هاي عندي ال
+
+526
+00:42:40,110 --> 00:42:44,610
+data set، ال name، ال rank، ال years، نرجع ولا
+
+527
+00:42:44,610 --> 00:42:48,830
+ما نرجعش، نقعد
+
+528
+00:42:48,830 --> 00:42:54,450
+ولا ما نقعدش، نريح ولا ما نريحش، لأن هاي ال class
+
+529
+00:42:54,450 --> 00:42:58,890
+اللي عندي yes و no. فاروح أعمل التحليل لل data set
+
+530
+00:42:58,890 --> 00:43:04,410
+اللي موجودة، وكان مفاده إنه ال algorithm راح أعطاني
+
+531
+00:43:04,410 --> 00:43:09,590
+classifier model، prediction model لل class، لمية
+
+532
+00:43:09,590 --> 00:43:13,910
+ممكن أختار؟ ل yes و no، بحيث إنه أنا لو زدت بال
+
+533
+00:43:13,910 --> 00:43:20,750
+rank وعدد سنوات الخبرة، يدّيني ال label اللي موجود
+
+534
+00:43:20,750 --> 00:43:27,890
+فقال ال model تبعي هو عبارة عن if then rule، لو كان
+
+535
+00:43:27,890 --> 00:43:31,890
+ال rank professor، وال years أكبر أو يساوي 6، أكبر من
+
+536
+00:43:31,890 --> 00:43:42,910
+6، معناته نرجع. تمام. المرحلة الثانية، ال model usage،
+
+537
+00:43:42,910 --> 00:43:48,060
+بالملاحظة يا شباب، ال classification algorithm، أنا
+
+538
+00:43:48,060 --> 00:43:55,280
+هان غالباً... غالباً بيشتغل فعلياً as a black box، يعني
+
+539
+00:43:55,280 --> 00:43:58,980
+بدي ال input، وأخذ منه ال output، اللي هو ال model
+
+540
+00:43:58,980 --> 00:44:03,300
+إيش اللي بيصير... إيش اللي بيصير؟ غالباً مش كل
+
+541
+00:44:03,300 --> 00:44:06,820
+الناس المعنية فيه، بس أنا بالمساق هذا، هدخل بتفاصيل
+
+542
+00:44:06,820 --> 00:44:11,240
+عشان أعرف فعلياً ال classifier كيف اشتغل، تمام؟ لكن
+
+543
+00:44:11,240 --> 00:44:15,730
+في بعض ال classifiers، مش هنكون، أو مش هنتطرق لها
+
+544
+00:44:15,730 --> 00:44:22,230
+بالشغل تبعتها. بمجرد إن ال classifier انبنى، بدّه
+
+545
+00:44:22,230 --> 00:44:25,630
+أروح أطبقه، أو بدّه أروح أستخدمه، ال model هذا الآن
+
+546
+00:44:25,630 --> 00:44:32,150
+بيصير قابل للاستخدام. فيش
+
+547
+00:44:32,150 --> 00:44:38,150
+بدّه أستخدمه؟ يعمل classifying لمين؟ لل feature، لل
+
+548
+00:44:38,150 --> 00:44:41,810
+future، أو ال unknown objects.
+
+549
+00:44:43,140 --> 00:44:46,840
+بالمثال السابق هذا، أنا صار في عندي Jeff
+
+550
+00:44:46,840 --> 00:44:53,200
+professor، و 4 سنوات. الاسم neglected، مش هعتبره، لأن
+
+551
+00:44:53,200 --> 00:44:58,660
+ال role تبعي مبني على ال rank وال years، وبناءً
+
+552
+00:44:58,660 --> 00:45:03,480
+عليه أنا بدي آخذ القرار. كان بيقول لي، if ال rank
+
+553
+00:45:03,480 --> 00:45:07,280
+equal
+
+554
+00:45:07,280 --> 00:45:17,370
+professor، or ال years أكبر من 6، then yes. مظبوط، هاي ال rule
+
+555
+00:45:17,370 --> 00:45:23,110
+تبعي، هاي ال model تبعي. الآن، هاي ال data اللي عندي
+
+556
+00:45:23,110 --> 00:45:26,710
+حققت عليها، بطبقها مباشرة، باخد ال instances وبطبق
+
+557
+00:45:26,710 --> 00:45:30,250
+ال instance value، وبطبق عليها هان، وباخد القرار
+
+558
+00:45:30,250 --> 00:45:37,070
+تبع لل rule اللي موجود عندي. طيب،
+
+559
+00:45:37,070 --> 00:45:40,690
+لو ما كانش professor، كان assistant professor،
+
+560
+00:45:40,690 --> 00:45:47,550
+و 5 سنوات، no، مع ال else مباشرة، مع ال else مباشرة،
+
+561
+00:45:47,550 --> 00:45:54,150
+الارجل مع الخير. معناته أنا بحاجة في مرحلتين عشان
+
+562
+00:45:54,150 --> 00:45:56,690
+أشتغل مع ال classifier، بحاجة أشتغل على مرحلتين،
+
+563
+00:45:56,690 --> 00:46:00,550
+المرحلة الأولى اللي هي ال model construction،
+
+564
+00:46:00,550 --> 00:46:05,770
+وبيلزمني data عشان أدرب ال model عليها، بين جثين
+
+565
+00:46:05,770 --> 00:46:08,710
+بيلزمني data عشان ال system أو ال learning
+
+566
+00:46:08,710 --> 00:46:14,230
+algorithm يحللها ويبني model بناءً عليها. الشغلة
+
+567
+00:46:14,230 --> 00:46:19,450
+الثانية، إنه أنا بدي أفحص ال model، أو بدي أستخدم ال
+
+568
+00:46:19,450 --> 00:46:22,830
+model في ال prediction، وهي بنسميها إحنا المرحلة
+
+569
+00:46:22,830 --> 00:46:26,630
+مرحلة ال testing أو ال test. فأنا بدي اجسم ال data
+
+570
+00:46:26,630 --> 00:46:33,130
+set تبعتي، ل training set، و
+
+571
+00:46:33,130 --> 00:46:40,340
+test set. ليش؟ عشان لما أنا أحصل على model، عشان لما
+
+572
+00:46:40,340 --> 00:46:43,460
+أحصل على model، كيف بدي أتعرف إن ال model هذا شغال
+
+573
+00:46:43,460 --> 00:46:48,200
+كويس ولا لأ؟ بدي إنه النتيجة المطلوبة، ولا بشتغل من
+
+574
+00:46:48,200 --> 00:46:54,880
+رأسه؟ فبدي أعمله evaluation. طيب، evaluation، how did
+
+575
+00:46:54,880 --> 00:47:00,380
+we test that test set؟ هو الأصل هي unseen data، مصبوط؟
+
+576
+00:47:00,380 --> 00:47:05,760
+فعلياً unseen، ما شفهاش، بس دي فيها label، بخبي ال
+
+577
+00:47:05,760 --> 00:47:10,620
+label عنها، عشان أقدر إيش؟ أقارن بين النتيجة اللي هو
+
+578
+00:47:10,620 --> 00:47:16,080
+هيعطيني إياها، والنتيجة اللي هحصل عليها، وأنا بدي أسأل
+
+579
+00:47:16,080 --> 00:47:25,980
+سؤال: هل ال test set labelled set؟ في مرحلة ال
+
+580
+00:47:25,980 --> 00:47:33,160
+evaluation، هل ال test set labelled set؟ طيب، الآن
+
+581
+00:47:33,160 --> 00:47:34,100
+أنا جديد، كتبت
+
+582
+00:47:36,780 --> 00:47:43,060
+الـ body mass index، point تلاتة سبعة، والـ chest
+
+583
+00:47:43,060 --> 00:47:52,020
+pain yes، تصلب شرايين، Blocked Artery yes، قال لي هذا
+
+584
+00:47:52,020 --> 00:47:57,720
+heart disease. هذا الأصل اللي نعملها prediction، صح؟
+
+585
+00:47:57,720 --> 00:48:06,090
+أنا أخدتها على عليتها، هيك قال لي no. بتقدر تقول عن
+
+586
+00:48:06,090 --> 00:48:09,430
+ال prediction بتاعته صح ولا غلط؟ بتقدر تعمل
+
+587
+00:48:09,430 --> 00:48:16,590
+evaluation لإلها؟ بتقارنها بإيش؟ بال label الأصلي.
+
+588
+00:48:16,590 --> 00:48:21,930
+فعشان هيك ال test set must be labelled. عشان هيك، بعد
+
+589
+00:48:21,930 --> 00:48:24,470
+ما أنت خلصت، عملت processing في ال assignment،
+
+590
+00:48:24,470 --> 00:48:29,890
+وقلت لك اجسم، اجسم ال data set لجزئين، جزء ال
+
+591
+00:48:29,890 --> 00:48:35,340
+training، وجزء testing. بس اللي هيصير فعلياً، لما أصل
+
+592
+00:48:35,340 --> 00:48:40,820
+لمرحلة ال evaluation، هخبّي ال test، أو هخبّي ال label
+
+593
+00:48:40,820 --> 00:48:45,780
+تبعت مين؟ تبعت ال test set، عشان أقول، اتفضل، هاي
+
+594
+00:48:45,780 --> 00:48:49,640
+unseen data، اعمل لهم prediction، فبيديني مجموعة ال
+
+595
+00:48:49,640 --> 00:48:53,160
+labels اللي predicted، وعندي ال original أو ال true
+
+596
+00:48:53,160 --> 00:48:58,320
+labelled، بصير أقارن، وبقدر أتكلم إنه جديش هذا ال
+
+597
+00:48:58,320 --> 00:48:59,180
+model تبعي accurate.
+
+598
+00:49:03,990 --> 00:49:08,470
+أه، الآن أحمد بيسأل، بيقول: هل بقدر أروح أرجع ال
+
+599
+00:49:08,470 --> 00:49:11,830
+data test set هذه، وأوديها على ال training، عشان
+
+600
+00:49:11,830 --> 00:49:17,350
+يتعلم من أخطائه؟ أنت already علمته، وكمان لو أنت
+
+601
+00:49:17,350 --> 00:49:21,270
+روحت أخدته، يعني هيك، من وين بدك تختبره بعد هيك؟
+
+602
+00:49:21,270 --> 00:49:25,130
+بدك تجيب له data set جديدة، طب ليش مش من نفس ال
+
+603
+00:49:25,130 --> 00:49:30,450
+data set؟ لأن already هو شافها، تمام. من الشباب،
+
+604
+00:49:30,450 --> 00:49:37,330
+بينفعش أنا آجي أديك الامتحان وأقول لك اتفضل، حلّ، تمام،
+
+605
+00:49:37,330 --> 00:49:42,530
+وبكرا بدي أختبرك فيه، في الأسئلة هاي، ما أصبحش
+
+606
+00:49:42,530 --> 00:49:50,370
+امتحان، ولا أصبح امتحان امتحان مسرّب، اه، فش يعني، عفواً،
+
+607
+00:49:50,370 --> 00:49:53,550
+كلّكم هتنجحوا، مصبوط؟ الأصل كده، واللي ما بدهوش ينجح
+
+608
+00:49:53,550 --> 00:49:58,570
+يتطخّد الساعة بيكون، بس فعلياً، هل النجاح هذا حقيقي؟
+
+609
+00:49:58,570 --> 00:50:04,890
+لأ، الحاجات هذا fake، النجاح هذا fake. أما إحنا قلنا
+
+610
+00:50:04,890 --> 00:50:09,390
+الفكرة وين؟ إن بعد ما أنا جسمت هان، في مرحلة ال
+
+611
+00:50:09,390 --> 00:50:14,890
+evaluation، مش بدّه يشوف... بدّه يشوف ال... بيشوف هو
+
+612
+00:50:14,890 --> 00:50:19,370
+اجتيش... لأ، بدّه يشوف ال... ال... ال... ال... ال
+
+613
+00:50:19,370 --> 00:50:24,670
+result، دي، يقارن فوق، هيو... هذه... هذه... بدّه يقارن
+
+614
+00:50:24,670 --> 00:50:30,690
+هذه. لأ، ومش قارنها مع اللي فوق، هو على ال model بناءً
+
+615
+00:50:30,690 --> 00:50:33,950
+على ال equation اللي ان
+
+667
+00:55:02,060 --> 00:55:06,660
+computational جديش أنا مهتم بسرعة النظام، يعني الآن
+
+668
+00:55:06,660 --> 00:55:12,010
+مثلًا، بدنا نظام الآن.. محتاجين نظام سريع يحاول
+
+669
+00:55:12,010 --> 00:55:15,610
+يتنبأ أن المريض هذا اللي مش.. منضيق في الصدر أو
+
+670
+00:55:15,610 --> 00:55:19,530
+في صعوبة في التنفس، مصاب بـ Corona ولا لأ؟ أنت..
+
+671
+00:55:19,530 --> 00:55:22,550
+أنت.. أنت خبير.. خبير الصين أصلًا.. أنت عشان إيه
+
+672
+00:55:22,550 --> 00:55:27,730
+قلت Corona مباشرة، تمام؟ الآن الفكرة وين؟ أن أنا
+
+673
+00:55:27,730 --> 00:55:31,710
+جديش بأقدر أعمل training لـ model.. a curated
+
+674
+00:55:31,710 --> 00:55:37,450
+model بشكل سريع، بكون كويس إليّ، ليش؟ لأن أنا
+
+675
+00:55:37,450 --> 00:55:42,050
+فعليًا.. الآن أنا محتاجه، يمكن بكرا ما محتاجوش، فالآن
+
+676
+00:55:42,050 --> 00:55:46,410
+هذه بتفرج معايا الـ performance في مرحلة الـ
+
+677
+00:55:46,410 --> 00:55:52,490
+generation، الـ using في الـ prediction، أن لما أزوده
+
+678
+00:55:52,490 --> 00:55:56,230
+بالعينة اللي المفروض يعمل عليها prediction أو يقيم
+
+679
+00:55:56,230 --> 00:56:01,150
+يعملها evaluation، جديش بده وقت؟ بده ثانية،
+
+680
+00:56:01,150 --> 00:56:06,630
+ثنتين، ثلاث، عشر، كل ما كان أسرع يكون أحسن في الـ
+
+681
+00:56:06,630 --> 00:56:10,670
+real-time system، الآن في عندنا جسم بيتحرك في الجو
+
+682
+00:56:10,670 --> 00:56:16,350
+بسرعة 100 كيلومتر في الساعة، طيارة،
+
+683
+00:56:16,350 --> 00:56:23,350
+صاروخ، قذيفة، غراب، مش عارفين، في الأنظمة الدفاعية
+
+684
+00:56:23,350 --> 00:56:26,710
+بتفرج الآن هذا الجسم اللي بيتحرك في الـ real-time
+
+685
+00:56:26,710 --> 00:56:31,630
+system، تمام؟ بناءً على سرعته وحجمه،
+
+686
+00:56:33,360 --> 00:56:36,620
+بدهم ياخدوا قرار، اللي غالبًا ما بيبينش، بدهم ياخدوا
+
+687
+00:56:36,620 --> 00:56:41,160
+قرار، شو هذا؟ بيكون إفعل صفرات الإنذار ولا لأ، الإنذار
+
+688
+00:56:41,160 --> 00:56:51,780
+ولا لأ، إحنا
+
+689
+00:56:51,780 --> 00:56:57,200
+قلنا حمامة، شكله زاد مع البس، خلاص وهي طايرة
+
+690
+00:56:58,620 --> 00:57:02,060
+الفكرة يا جماعة الخير اللي أنا بدي أوصلك إياها هي إذا
+
+691
+00:57:02,060 --> 00:57:06,940
+ما كانتش مرحلة الـ prediction سريعة، تفقدت الأهمية،
+
+692
+00:57:06,940 --> 00:57:11,060
+تبعتها، فضل يا دكتور قبل لما راحيت على المرض، أكيد
+
+693
+00:57:11,060 --> 00:57:16,080
+فعلاً مش هيكون مثلًا، بدنا نتنبأ أن فيه مثلًا.. لو
+
+694
+00:57:16,080 --> 00:57:19,800
+مثلًا افتراض مثلًا، علشان هنا يعني محتمل يكون فيه
+
+695
+00:57:19,800 --> 00:57:23,100
+نسبة خطأ، فإحنا على وجه السرعة مش هيكون بدنا نتنبأ،
+
+696
+00:57:23,100 --> 00:57:28,190
+بدنا يعني.. طب أنت عملك بتقول أنا المرض هذا فعليًا
+
+697
+00:57:28,190 --> 00:57:34,070
+مش قادر أشخصه أو في عندهم صعوبة في تشخيصه فقط،
+
+698
+00:57:34,070 --> 00:57:37,930
+طب المريض العادي أو اللي عنده احتقان في زوره،
+
+699
+00:57:37,930 --> 00:57:41,890
+ابرت في حرارته واحد زي حالتي بيكون قاعد،
+
+700
+00:57:41,890 --> 00:57:44,950
+بيشرح وبيطلع واحد غبي بيقوله، بس طايرة، ابرِتْ فيه
+
+701
+00:57:44,950 --> 00:57:45,450
+حرارته،
+
+702
+00:57:49,260 --> 00:57:53,380
+تمام؟ بالفكرة يا جماعة، okay، أنا بدي.. بدي system
+
+703
+00:57:53,380 --> 00:57:57,500
+يكون سريع، عفواً بدي أصل لـ model بشكل سريع، بعض الـ
+
+704
+00:57:57,500 --> 00:58:02,240
+models بتاخد أيام وأشهر هي بتعمل الـ training، صح؟
+
+705
+00:58:02,240 --> 00:58:06,460
+بيكون هذا دقيق الشغل، صحيح، لكن أنا برضه حسب الحالة
+
+706
+00:58:06,460 --> 00:58:11,480
+اللي أنا بدي أشتغل عليها، نعم لأ،
+
+707
+00:58:11,480 --> 00:58:16,460
+للأسف data preparation، هل تحسب ضمن الـ time cost؟ لأ،
+
+708
+00:58:17,850 --> 00:58:21,290
+لأن هنا بنتكلم إحنا على الـ computational cost، كل
+
+709
+00:58:21,290 --> 00:58:27,670
+اللي أنت سويتّه قبل، مجرد تجهيز لعملية الـ mining،
+
+710
+00:58:27,670 --> 00:58:33,330
+أكيد كل ما زاد حجم الـ data زاد حجم الـ computation،
+
+711
+00:58:33,330 --> 00:58:37,790
+بالـ training والـ testing، الآن الـ data set تبعتي
+
+712
+00:58:37,790 --> 00:58:42,870
+مكونة من عشرة attributes، هل الـ computation تبعتها،
+
+713
+00:58:42,870 --> 00:58:49,260
+زي ما يكون عندي 100 attributes؟ حتماً لأ، يعني عشر،
+
+714
+00:58:49,260 --> 00:58:54,620
+متغيرات، زي مين؟ متغير، أكيد لأ، جديش الـ robustness أو
+
+715
+00:58:54,620 --> 00:58:58,200
+الموثوقية، جديش الـ system هذا بيديني accurate
+
+716
+00:58:58,200 --> 00:59:03,680
+result في حالة الـ noise data، الـ noise instance أو
+
+717
+00:59:03,680 --> 00:59:06,960
+في حالة وجود الـ missing values، الآن إحنا قبل شوية،
+
+718
+00:59:06,960 --> 00:59:10,740
+اتكلمت على ثلاث عناصر عشان الـ heart disease، الـ body
+
+719
+00:59:10,740 --> 00:59:16,000
+mass index، والـ chest pain، وتصلب الشرايين، الآن لو
+
+720
+00:59:16,000 --> 00:59:18,880
+عندي اثنتين منهم فقط، بيقدر الـ system يديني
+
+721
+00:59:18,880 --> 00:59:23,360
+prediction؟ لأ، ما تقوليش لأ، أنت ما تشكشكش، لأ، الـ
+
+722
+00:59:23,360 --> 00:59:26,380
+system هيديكي prediction، هيديكي prediction، بس اللي
+
+723
+00:59:26,380 --> 00:59:29,900
+أنا بدور عليه، هل بيقدر يديني prediction صحيح؟ إذا
+
+724
+00:59:29,900 --> 00:59:33,360
+بيديني prediction صحيح، معناته هذا more robust، أكثر
+
+725
+00:59:33,360 --> 00:59:38,300
+موثوقية، ليش؟ لأن في حالة أن أنا فقدت واحد من الـ
+
+726
+00:59:38,300 --> 00:59:41,440
+attributes اللي موجودة، بضل قادر أعتمد عليه عشان
+
+727
+00:59:41,440 --> 00:59:46,050
+يعمل prediction، تمام؟ الآن في حالة كان في عندي
+
+728
+00:59:46,050 --> 00:59:49,710
+noise data، نفس النظام، بالمناسبة يا حسن، إحنا عادةً
+
+729
+00:59:49,710 --> 00:59:53,490
+اللي بنتكلم فعليًا، هذا المثال اللي ذكرته ثلاث، عشان
+
+730
+00:59:53,490 --> 00:59:57,870
+بس نستوعب الشيء اللي بيصير، ونفهم فعليًا كل الـ
+
+731
+00:59:57,870 --> 01:00:02,730
+concept بشكل واضح، لكن فعليًا لو أنا سألتك، أبسط
+
+732
+01:00:02,730 --> 01:00:05,710
+اختبار ممكن يجريه الإنسان اللي له علاقة بصحته، الـ
+
+733
+01:00:05,710 --> 01:00:13,270
+CBC، كم factor فيه؟ 15 أعتقد أو 14، يعني بتكلم
+
+734
+01:00:13,270 --> 01:00:16,450
+على الأقل 14 attributes، اللي هو الـ test الـ
+
+735
+01:00:16,450 --> 01:00:21,870
+complete blood test، تمام؟ فبتكلم على 14 attributes
+
+736
+01:00:21,870 --> 01:00:25,730
+لكل عينة، الآن لو في واحدة عينة فيها مشكلة في الـ
+
+737
+01:00:25,730 --> 01:00:30,750
+noise أو value معينة، لأ لأ، مش ضروري، فالآن لو جديش
+
+738
+01:00:30,750 --> 01:00:34,630
+الآن الطبيب الحاذق ممكن بيقدر يقارن شغلات مع بعضها،
+
+739
+01:00:34,630 --> 01:00:38,210
+ويقول لك لأ، في مشكلة، يعني واضح من الجهاز أن في مشكلة، هذه
+
+740
+01:00:38,210 --> 01:00:42,450
+الفكرة وين؟ أن الـ system لو غاب في عندي value أو
+
+741
+01:00:42,450 --> 01:00:46,170
+تشوشت value من الأربع عشر، يكون عنده القدرة على
+
+742
+01:00:46,170 --> 01:00:50,410
+التنبؤ الصحيح، أي واحدة من الأربع عشر هذه ما بتعنّاش
+
+743
+01:00:50,410 --> 01:00:54,870
+بس، في اللحظة اللي بيجيني الـ attribute، عفواً بيجيني
+
+744
+01:00:54,870 --> 01:00:58,610
+الـ rows، الـ raw with missing value أو with noisy
+
+745
+01:00:58,610 --> 01:01:02,350
+data، الأصل يعمل prediction، هيعمل prediction في كل
+
+746
+01:01:02,350 --> 01:01:07,320
+الأحوال، كل مكان بيديني accurate الـ prediction في
+
+747
+01:01:07,320 --> 01:01:11,300
+الـ such case هذه، معناته هذا مرة  أقدر أثق فيه
+
+748
+01:01:11,300 --> 01:01:18,880
+أكثر، تمام، الـ scalability، الـ scalability طبعًا دائمًا
+
+749
+01:01:18,880 --> 01:01:23,740
+إحنا مفهوم الـ scalability، بنتكلم على الـ large
+
+750
+01:01:23,740 --> 01:01:29,560
+amount of data، فعليًا هل الـ algorithm هذا تبعه ممكن
+
+751
+01:01:29,560 --> 01:01:35,000
+من السهل أن يتعامل معه مع large data، الـ data set
+
+752
+01:01:35,000 --> 01:01:37,760
+اللي عندي مليون instances، هل الـ algorithm قادر على
+
+753
+01:01:37,760 --> 01:01:40,960
+تحليل مليون instances مع عشر.. مع عشر attributes،
+
+754
+01:01:40,960 --> 01:01:44,100
+أو مع مئة attributes، فهذا أنا بدي أسأله، كل ما كان
+
+755
+01:01:44,100 --> 01:01:48,780
+الـ algorithm اللي هستخدمه more scalable، معناته
+
+756
+01:01:48,780 --> 01:01:54,420
+بكون أفضل، interpretability، تفسير والـ
+
+757
+01:01:54,420 --> 01:02:01,500
+understanding، وفهم محتوى أو ما وراء الـ Model أو
+
+758
+01:02:01,500 --> 01:02:04,840
+الـ Algorithm اللي عندي، The level of understanding
+
+759
+01:02:04,840 --> 01:02:10,000
+and insight، والمفهوم أو التوضيح أو المعنى الخفي من
+
+760
+01:02:10,000 --> 01:02:14,200
+Provided by the classifier، إحنا قبل شوية لما شفنا
+
+761
+01:02:14,200 --> 01:02:18,000
+الـ if then، كان بسهولة أن أفهم عليه، بدور إيش الـ
+
+762
+01:02:18,000 --> 01:02:21,720
+factors الأساسية اللي كانت موجودة؟ لو هذا الـ if
+
+763
+01:02:21,720 --> 01:02:25,040
+then ما كانتش موجودة، بقدر أستوعب ليش هو جداني yes وجداني no؟ أكيد لأ، لكن لما بيكون الـ algorithm قدامي
+
+764
+01:02:25,040 --> 01:02:29,140
+قادر أو بقدر أو قادر على تفسيره، بكون أفضل، لكن
+
+765
+01:02:29,140 --> 01:02:34,820
+الصحيح الموضوع برضه تفسيره هذا subjective للإنسان
+
+766
+01:02:34,820 --> 01:02:39,980
+أو للشخص اللي بيشتغل عليه، لما أنا كتبنا، كتبنا
+
+767
+01:02:39,980 --> 01:02:42,780
+المعادلة الرياضية، Y تساوي M1 في A1 زائد M2 في A2
+
+768
+01:02:42,780 --> 01:02:50,140
+زائد B،
+
+769
+01:02:50,140 --> 01:02:51,440
+زائد B،
+
+770
+01:02:55,220 --> 01:02:59,920
+إيش رتبة.. إيش درجة المعادلة هي يا شباب؟ إيش رتبة
+
+771
+01:02:59,920 --> 01:03:07,980
+المعادلة هي يا شباب؟ معادلة خطية، لأن الدرجة تقاس بأعلى
+
+772
+01:03:07,980 --> 01:03:12,840
+أُس، الدرجة أو رتبة المعادلة تقاس بأعلى أُس،
+
+773
+01:03:12,840 --> 01:03:18,000
+فالمعادلة هي خطية، بس فعليًا هذه multiple variable،
+
+774
+01:03:18,000 --> 01:03:25,480
+متغيرات، اثنين مع الـ Y، يعني بين قوسين الـ 3D equation، مصبوط؟ هي.. هي الفكرة، الآن مش كل الناس
+
+775
+01:03:25,480 --> 01:03:30,840
+قادرة على تفسير.. هذه، أعرضها على واحد خبير رياضيات
+
+776
+01:03:30,840 --> 01:03:35,740
+مباشرة، بيقول لك هذه بتعني كذا، وواحد كذا، بيجي و
+
+777
+01:03:35,740 --> 01:03:38,580
+بيقول لك أن هذا plane مائل، plane، مسطح مائل، الميل
+
+778
+01:03:38,580 --> 01:03:43,860
+تبعه باتجاه X، ومثلًا X و Y كذا، X و Z كذا، هي الأبعاد
+
+779
+01:03:43,860 --> 01:03:51,450
+تبعته، وهذه ارتفاعه أو التقاطع تبعته مع الـ Y axis،
+
+780
+01:03:51,450 --> 01:03:56,990
+لكن أنا مش عارفني بالكلام هذا، فالموضوع الـ
+
+781
+01:04:02,270 --> 01:04:07,130
+interpretability، أو موضوع تفسير الـ algorithm، و
+
+782
+01:04:07,130 --> 01:04:12,550
+فهمه بيختلف من شخص لشخص، من
+
+783
+01:04:12,550 --> 01:04:17,410
+الـ algorithms اللي هنتعرف عليها، K-nearest
+
+784
+01:04:17,410 --> 01:04:21,490
+neighbor algorithm، وهذا البرنامج يعتمد على
+
+785
+01:04:21,490 --> 01:04:22,550
+البرنامج، الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة
+
+786
+01:04:22,550 --> 01:04:30,530
+الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة،
+
+787
+01:04:30,530 --> 01:04:35,310
+الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة،
+
+788
+01:04:35,310 --> 01:04:35,330
+الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة،
+
+789
+01:04:35,330 --> 01:04:41,850
+الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة،
+
+790
+01:04:41,850 --> 01:04:47,070
+وفي عند الـ rule based induction، وفي عند الـ
+
+791
+01:04:47,070 --> 01:04:49,430
+support vector machine، وفي عند الـ logistic
+
+792
+01:04:49,430 --> 01:04:53,610
+regression، كل هذه الـ algorithms تستخدم في الـ
+
+793
+01:04:53,610 --> 01:04:55,990
+classification، وفي عند الـ back propagation، الـ
+
+794
+01:04:55,990 --> 01:04:59,310
+neural network، في الفصل هذا، في الشابتر هذا إن شاء
+
+795
+01:04:59,310 --> 01:05:02,350
+الله تعالى، هشرح لك الـ k-nearest neighbor، والـ naive
+
+796
+01:05:02,350 --> 01:05:05,170
+bayes، والـ decision tree، والـ back propagation، والـ
+
+797
+01:05:05,170 --> 01:05:09,650
+propagation neural network، كـ classifiers خلال الفصل
+
+798
+01:05:09,650 --> 01:05:14,360
+هذا، أنا محاضرة اليوم هي كاد أن تنتهي.
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/3PercFMmDro_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/3PercFMmDro_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..29d337ba50af75dcfe841df4fd76414c4449cd2f
--- /dev/null
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@@ -0,0 +1 @@
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الفواكه التانية التي لم يقدر ان يصنفها ال system على انهاش برتقال و عادة في اللغات بنسميها binary classification", "tokens": [10721, 2407, 6055, 5172, 39319, 4032, 6055, 33753, 16712, 5172, 39319, 3714, 43020, 6055, 5016, 9566, 28242, 18863, 1863, 33546, 2288, 34051, 28242, 27188, 14407, 4117, 3224, 16712, 7649, 10632, 38392, 32767, 7251, 28543, 2288, 16472, 7251, 9381, 1863, 5172, 11296, 2423, 1185, 15844, 16472, 3224, 33599, 4724, 43500, 4587, 6027, 4032, 6225, 18513, 3660, 8978, 13672, 17082, 9307, 44945, 38251, 1829, 11296, 17434, 21538], "avg_logprob": -0.1762547321391828, "compression_ratio": 1.4943181818181819, "no_speech_prob": 3.5762786865234375e-07, "words": [{"start": 2168.05, "end": 2168.33, "word": "أو", "probability": 0.90234375}, {"start": 2168.33, "end": 2168.85, "word": " تفاح", "probability": 0.9200846354166666}, {"start": 2168.85, "end": 2169.53, "word": " و", "probability": 0.1343994140625}, {"start": 2169.53, "end": 2169.77, "word": " تحت", "probability": 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مبني على ال rank و ال years و بناء عليه أنا بدي أخد القرار كان بيقول لي if ال rank equal of or ال years أكبر من 6", "tokens": [3555, 45340, 12984, 6027, 6055, 16758, 3615, 22653, 21136, 16758, 4587, 23758, 41850, 20328, 9640, 8978, 3224, 43242, 7578, 7506, 8304, 4032, 1017, 8608, 1863, 2407, 9307, 2423, 32277, 2304, 32701, 37893, 8032, 34268, 26890, 3224, 5296, 28814, 1863, 2423, 3090, 6055, 3555, 3615, 1829, 3714, 3555, 22653, 15844, 2423, 6181, 4032, 2423, 924, 4032, 44945, 16606, 47356, 41850, 4724, 16254, 5551, 9778, 3215, 25062, 2288, 9640, 25961, 4724, 1829, 39648, 32239, 498, 2423, 6181, 2681, 295, 420, 2423, 924, 5551, 4117, 26890, 9154, 1386], "avg_logprob": -0.2401889557408732, "compression_ratio": 1.5244444444444445, "no_speech_prob": 3.5762786865234375e-07, "words": [{"start": 2683.14, "end": 2683.72, "word": "بالمثال", "probability": 0.9754638671875}, {"start": 2683.72, "end": 2684.1, "word": " تابعني", "probability": 0.60015869140625}, {"start": 2684.1, "end": 2684.68, 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data اللي عندى حقق عليها بطبقها مباشرة باخد ال instances و بطبق ال instance value و بطبق عليها هان و باخد القرار تبع لل role اللي موجود عندى طيب لو ماكانش ماكانش professor كان assistant professor و 5 سنوات", "tokens": [19096, 2086, 3714, 19913, 3555, 2407, 9566, 8032, 47302, 2423, 3090, 6055, 3555, 3615, 1829, 8032, 47302, 2423, 2316, 6055, 3555, 3615, 1829, 6024, 48506, 8032, 47302, 2423, 1412, 13672, 1829, 43242, 7578, 11331, 4587, 4587, 25894, 11296, 4724, 9566, 3555, 4587, 11296, 3714, 3555, 33599, 25720, 4724, 47283, 3215, 2423, 14519, 4032, 4724, 9566, 3555, 4587, 2423, 5197, 2158, 4032, 4724, 9566, 3555, 4587, 25894, 11296, 8032, 7649, 4032, 4724, 47283, 3215, 25062, 2288, 9640, 6055, 3555, 3615, 24976, 3090, 13672, 1829, 3714, 29245, 23328, 43242, 7578, 23032, 1829, 3555, 45164, 19446, 41361, 8592, 19446, 41361, 8592, 8304, 25961, 10994, 8304, 4032, 1025, 8608, 1863, 2407, 9307], "avg_logprob": -0.1887901408956685, "compression_ratio": 1.8888888888888888, "no_speech_prob": 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23758, 8978, 25124, 16758, 2655, 2288, 23758, 16472, 13412, 16606, 21984, 37279, 6027, 7578, 8032, 46309, 5016, 23275, 2423, 350, 12, 716, 17363, 5987, 4032, 2423, 29052, 272, 2770, 4032, 2423, 3537, 4230, 4032, 2423, 646, 493, 4032, 2423, 48256, 18161, 3209, 9122, 1508, 23463, 16490, 1211, 6027, 27188, 36520, 23758], "avg_logprob": -0.3179209280987175, "compression_ratio": 1.9189189189189189, "no_speech_prob": 0.0, "words": [{"start": 3884.03, "end": 3884.33, "word": "وفي", "probability": 0.436279296875}, {"start": 3884.33, "end": 3884.53, "word": " عند", "probability": 0.90771484375}, {"start": 3884.53, "end": 3884.69, "word": " ال", "probability": 0.88330078125}, {"start": 3884.69, "end": 3884.89, "word": " rule", "probability": 0.3388671875}, {"start": 3884.89, "end": 3885.27, "word": " based", "probability": 0.5478515625}, {"start": 3885.27, "end": 3885.85, "word": " induction", "probability": 0.96484375}, {"start": 3885.85, "end": 3886.79, "word": " وفي", "probability": 0.81103515625}, {"start": 3886.79, "end": 3886.95, "word": " عند", "probability": 0.943359375}, {"start": 3886.95, "end": 3887.07, "word": " ال", "probability": 0.80810546875}, {"start": 3887.07, "end": 3887.45, "word": " support", "probability": 0.91748046875}, {"start": 3887.45, "end": 3887.79, "word": " vector", "probability": 0.96142578125}, {"start": 3887.79, "end": 3888.25, "word": " machine", "probability": 0.88720703125}, {"start": 3888.25, "end": 3888.71, "word": " وفي", "probability": 0.758056640625}, {"start": 3888.71, "end": 3888.87, "word": " عند", "probability": 0.96533203125}, {"start": 3888.87, "end": 3888.99, "word": " ال", "probability": 0.662109375}, {"start": 3888.99, "end": 3889.43, "word": " logistic", "probability": 0.8779296875}, {"start": 3889.43, "end": 3891.41, "word": " regression", "probability": 0.79052734375}, {"start": 3891.41, "end": 3892.09, "word": " كل", "probability": 0.70556640625}, {"start": 3892.09, "end": 3892.35, "word": " هذه", "probability": 0.87060546875}, {"start": 3892.35, "end": 3892.43, "word": " ال", "probability": 0.50732421875}, {"start": 3892.43, "end": 3892.75, "word": " algorithm", "probability": 0.288330078125}, {"start": 3892.75, "end": 3893.37, "word": " تستخدم", "probability": 0.95849609375}, {"start": 3893.37, "end": 3893.51, "word": " في", "probability": 0.92919921875}, {"start": 3893.51, "end": 3893.61, "word": " ال", "probability": 0.96484375}, {"start": 3893.61, "end": 3894.21, "word": " classification", "probability": 0.916015625}, {"start": 3894.21, "end": 3894.97, "word": " وفي", "probability": 0.6600341796875}, {"start": 3894.97, "end": 3895.15, "word": " عند", "probability": 0.96728515625}, {"start": 3895.15, "end": 3895.29, "word": " ال", "probability": 0.80126953125}, {"start": 3895.29, "end": 3895.41, "word": " back", "probability": 0.39697265625}, {"start": 3895.41, "end": 3895.55, "word": " up", "probability": 0.287841796875}, {"start": 3895.55, "end": 3895.69, "word": " و", "probability": 0.35302734375}, {"start": 3895.69, "end": 3895.69, "word": " ال", "probability": 0.42822265625}, {"start": 3895.69, "end": 3895.99, "word": " propagate", "probability": 0.8720703125}, {"start": 3895.99, "end": 3896.37, "word": " neural", "probability": 0.76806640625}, {"start": 3896.37, "end": 3896.93, "word": " network", "probability": 0.912109375}, {"start": 3896.93, "end": 3897.57, "word": " في", "probability": 0.65625}, {"start": 3897.57, "end": 3897.91, "word": " الفصل", "probability": 0.907470703125}, {"start": 3897.91, "end": 3898.15, "word": " هذا", "probability": 0.8193359375}, {"start": 3898.15, "end": 3898.25, "word": " في", "probability": 0.44677734375}, {"start": 3898.25, "end": 3898.85, "word": " الشابتر", "probability": 0.608306884765625}, {"start": 3898.85, "end": 3899.07, "word": " هذا", "probability": 0.74560546875}, {"start": 3899.07, "end": 3899.17, "word": " ان", "probability": 0.77001953125}, {"start": 3899.17, "end": 3899.31, "word": " شاء", "probability": 0.978759765625}, {"start": 3899.31, "end": 3899.37, "word": " الله", "probability": 0.93798828125}, {"start": 3899.37, "end": 3899.83, "word": " تعالى", "probability": 0.95556640625}, {"start": 3899.83, "end": 3900.79, "word": " هشرحلك", "probability": 0.7548828125}, {"start": 3900.79, "end": 3901.01, "word": " ال", "probability": 0.82373046875}, {"start": 3901.01, "end": 3901.13, "word": " k", "probability": 0.128173828125}, {"start": 3901.13, "end": 3901.39, "word": "-nearest", "probability": 0.6424153645833334}, {"start": 3901.39, "end": 3901.79, "word": " neighbor", "probability": 0.74365234375}, {"start": 3901.79, "end": 3902.07, "word": " و", "probability": 0.64111328125}, {"start": 3902.07, "end": 3902.13, "word": " ال", "probability": 0.6064453125}, {"start": 3902.13, "end": 3902.35, "word": " naive", "probability": 0.2464599609375}, {"start": 3902.35, "end": 3902.81, "word": " bison", "probability": 0.603515625}, {"start": 3902.81, "end": 3903.13, "word": " و", "probability": 0.9013671875}, {"start": 3903.13, "end": 3903.19, "word": " ال", "probability": 0.6806640625}, {"start": 3903.19, "end": 3903.45, "word": " decision", "probability": 0.97705078125}, {"start": 3903.45, "end": 3903.87, "word": " tree", "probability": 0.92822265625}, {"start": 3903.87, "end": 3904.57, "word": " و", "probability": 0.93603515625}, {"start": 3904.57, "end": 3904.69, "word": " ال", "probability": 0.75830078125}, {"start": 3904.69, "end": 3904.87, "word": " back", "probability": 0.8662109375}, {"start": 3904.87, "end": 3904.99, "word": " up", "probability": 0.9091796875}, {"start": 3904.99, "end": 3905.11, "word": " و", "probability": 0.94189453125}, {"start": 3905.11, "end": 3905.17, "word": " ال", "probability": 0.89453125}, {"start": 3905.17, "end": 3905.59, "word": " propagate", "probability": 0.96875}, {"start": 3905.59, "end": 3906.13, "word": " neural", "probability": 0.94091796875}, {"start": 3906.13, "end": 3907.27, "word": " network", "probability": 0.98828125}, {"start": 3907.27, "end": 3907.49, "word": " ك", "probability": 0.96923828125}, {"start": 3907.49, "end": 3908.15, "word": " classifiers", "probability": 0.76123046875}, {"start": 3908.15, "end": 3908.81, "word": " خلال", "probability": 0.9890950520833334}, {"start": 3908.81, "end": 3909.65, "word": " الفصل", "probability": 0.9814453125}, {"start": 3909.65, "end": 3909.93, "word": " هذا", "probability": 0.97802734375}], "temperature": 1.0}, {"id": 146, "seek": 391436, "start": 3912.06, "end": 3914.36, "text": "أنا محاضرة اليوم هي كاد انتهيت", "tokens": [10721, 8315, 3714, 5016, 46958, 25720, 45595, 20498, 39896, 9122, 18513, 16472, 47395, 36081], "avg_logprob": -0.127929691473643, "compression_ratio": 0.9482758620689655, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 3912.0600000000004, "end": 3912.78, "word": "أنا", "probability": 0.80419921875}, {"start": 3912.78, "end": 3913.24, "word": " محاضرة", "probability": 0.98388671875}, {"start": 3913.24, "end": 3913.5, "word": " اليوم", "probability": 0.958740234375}, {"start": 3913.5, "end": 3913.66, "word": " هي", "probability": 0.84814453125}, {"start": 3913.66, "end": 3913.82, "word": " كاد", "probability": 0.833984375}, {"start": 3913.82, "end": 3914.36, "word": " انتهيت", "probability": 0.8313802083333334}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 3915.0004375, "duration_after_vad": 3730.108749999983}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/3PercFMmDro_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/3PercFMmDro_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..81ce91e1b58f6f97847de40a504433c089299160
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/3PercFMmDro_raw.srt
@@ -0,0 +1,3212 @@
+1
+00:00:05,250 --> 00:00:07,430
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:07,430 --> 00:00:11,930
+اليوم ان شاء الله شباب هنبدأ ب chapter جديد في ال
+
+3
+00:00:11,930 --> 00:00:15,070
+data mining و هنتكلم على أولى ال data mining tasks
+
+4
+00:00:15,070 --> 00:00:20,630
+و هي ال classification ال classification لكن قبل
+
+5
+00:00:20,630 --> 00:00:24,150
+ما أبدأ بالمحاضرة فعليا و بال slides بدي أسأل انا
+
+6
+00:00:24,150 --> 00:00:26,270
+ايش احنا بنيعني بال classification
+
+7
+00:00:44,700 --> 00:00:53,400
+أه محمد شو يعني classification؟
+
+8
+00:00:53,400 --> 00:00:56,580
+بدي
+
+9
+00:00:56,580 --> 00:00:59,060
+أصنف .. شو يعني بدي أصنف؟ أيوة أنا بدي أقول ..
+
+10
+00:00:59,060 --> 00:01:04,700
+بينهم شغلات مشتركة
+
+11
+00:01:04,700 --> 00:01:09,520
+شو رايك مشتركة؟ مرتجع عفوا بجسم ال data على شكل
+
+12
+00:01:09,520 --> 00:01:14,720
+categories بجسم ال data على شكل categoriesكريم
+
+13
+00:01:14,720 --> 00:01:20,040
+بناء على ترميز معينة بعمل زي لبط بمثل الصدر او كذا
+
+14
+00:01:20,040 --> 00:01:24,340
+طيب انا قاعد باسأل شو يعني تصنيف بالعربي شو يعني
+
+15
+00:01:24,340 --> 00:01:30,220
+تصنيف شغلات بينها او في عناصر مش علها عناصر مشتركة
+
+16
+00:01:30,220 --> 00:01:38,040
+اعمر شو يعني تصنيف تقسيم العناصر الى مجموعات طيب
+
+17
+00:01:38,040 --> 00:01:42,200
+شو يعني تصنيف يا راني تصنيف شو يعني
+
+18
+00:01:47,010 --> 00:01:54,950
+طيب لو انا جيت قلتلك اه احمد تفضل اعمل subclass
+
+19
+00:01:54,950 --> 00:02:00,410
+بناء على role معين او subset طيب لو .. لو انا جيت
+
+20
+00:02:00,410 --> 00:02:09,330
+قلتلكوا عند الان قرصة كتب مجموعة كتب و بدنا نصنفها
+
+21
+00:02:15,120 --> 00:02:19,440
+إيش اسمك؟ إبراهيم إبراهيم أنا عارف تعمل تسألك
+
+22
+00:02:19,440 --> 00:02:26,500
+سنوار حسب إيش بدي أصنفها؟ ليش يا إبراهيم سألتي
+
+23
+00:02:26,500 --> 00:02:32,420
+السؤال هذا؟ عشان أنا أقدر؟ طب إيش اللي بدك يامني
+
+24
+00:02:32,420 --> 00:02:36,480
+يا إبراهيم عشان تقدر تصنفها؟
+
+25
+00:02:36,480 --> 00:02:39,660
+هو هو إنت صرت إبراهيم الآن؟ أيوة إيش اللي بدك
+
+26
+00:02:39,660 --> 00:02:42,960
+يامني عشان تقدر تصنفها؟ حق تقدر تحصرلي شغلات؟
+
+27
+00:02:45,760 --> 00:02:50,560
+معلومات .. معلومات .. معلومات عن إيش؟ معلومات عن
+
+28
+00:02:50,560 --> 00:02:54,680
+أستراليا .. معلومات عن أستراليا .. معلومات عن
+
+29
+00:02:54,680 --> 00:02:55,440
+أستراليا .. معلومات عن أستراليا .. معلومات عن
+
+30
+00:02:55,440 --> 00:02:56,680
+أستراليا .. معلومات عن أستراليا .. معلومات عن
+
+31
+00:02:56,680 --> 00:02:56,920
+أستراليا .. معلومات عن أستراليا .. معلومات عن
+
+32
+00:02:56,920 --> 00:02:58,800
+أستراليا .. معلومات عن أستراليا .. معلومات عن
+
+33
+00:02:58,800 --> 00:03:00,320
+أستراليا .. معلومات عن أستراليا .. معلومات عن
+
+34
+00:03:00,320 --> 00:03:02,840
+أستراليا .. معلومات عن أستراليا .. معلومات عن
+
+35
+00:03:02,840 --> 00:03:07,340
+أستراليا .. معلومات عن أستراليا .. معلومات عن
+
+36
+00:03:07,340 --> 00:03:10,880
+أستراليا .. معلومات عن أستراليا .. معلومات عن أست
+
+37
+00:03:12,100 --> 00:03:16,820
+تمام؟ كان كله بيتكلم على clustering أو grouping
+
+38
+00:03:16,820 --> 00:03:21,720
+لأن كلكوا بتتكلموا لمجموعات أصنفهم لمجموعات أصنفهم
+
+39
+00:03:21,720 --> 00:03:27,360
+لمجموعات مش هيك اصنفهم يعني في عندي predefined
+
+40
+00:03:27,360 --> 00:03:32,220
+setsفي عندي مجموعات معروفة مسبقًا والمجموعات هذه
+
+41
+00:03:32,220 --> 00:03:38,060
+إلها عنوين وانت دورك تشوف هل العنصر هذا بيتواءم مع
+
+42
+00:03:38,060 --> 00:03:41,440
+المجموعة هذه ولا لأ عشان تحطه تحتها بينما اللي
+
+43
+00:03:41,440 --> 00:03:44,840
+كنتوا أنتوا بتطرحوا بتقول أنا بدي أدرس الخصائص
+
+44
+00:03:44,840 --> 00:03:50,630
+المشتركة بين الكتب و أجسمهم لمجموعاتهذا بيسميه
+
+45
+00:03:50,630 --> 00:03:52,510
+احنا في ال data science أو في ال data mining
+
+46
+00:03:52,510 --> 00:03:57,230
+clustering يا تامر بيسميه clustering أو grouping
+
+47
+00:03:57,230 --> 00:04:04,370
+بينما للتصنيف انا بقاعد فيه عندي مجموعات معرفة
+
+48
+00:04:04,370 --> 00:04:08,350
+مسبقا predefined
+
+49
+00:04:08,350 --> 00:04:14,870
+groups ممكن
+
+50
+00:04:14,870 --> 00:04:18,680
+يكونوا أقل شيء لازم يكونوا تنتينأجلش لازم يكونوا
+
+51
+00:04:18,680 --> 00:04:23,600
+مجموعتين و بعد هي كان بيجي دوري أنا بشوف كل object
+
+52
+00:04:23,600 --> 00:04:26,780
+في ال data set اللي عندي أو كل object في الكتب
+
+53
+00:04:26,780 --> 00:04:33,440
+اللي عندي بيندرج تحت أي مصنف تحت أي عنوان من
+
+54
+00:04:33,440 --> 00:04:37,020
+المجموعات هذه لو أنا اجيت قلتلك يا همام الكتب اللي
+
+55
+00:04:37,020 --> 00:04:43,400
+عندي انا اما science او politics او financial او
+
+56
+00:04:43,400 --> 00:04:45,020
+literature أدب
+
+57
+00:04:47,290 --> 00:04:54,550
+اقتصاد، سياسة، علوم، شوبك تساوي وعندك مزالة مجموعة
+
+58
+00:04:54,550 --> 00:04:59,950
+الكتب مثل ما هي مكدسة قدامي، شو هتعمل؟ كيف؟ ماشي،
+
+59
+00:04:59,950 --> 00:05:09,560
+هتفرزهم الآن، شو هتساوي؟ هتمسك كل كتاب؟ كملعلى
+
+60
+00:05:09,560 --> 00:05:12,820
+الأقل أعرف الموضوع اللي بيتكلم فيه الكتاب يعني
+
+61
+00:05:12,820 --> 00:05:18,400
+مثلا كتاب بتتكلم عن الاحتلال الانجليزي لشرق آسيا
+
+62
+00:05:18,400 --> 00:05:26,760
+مثلا بتصنف سياسة ولا تاريخ literature حسب الكتاب
+
+63
+00:05:26,760 --> 00:05:30,500
+عن إيش بتتكلم هل بتتكلم مثلا رؤية سياسية ولا
+
+64
+00:05:30,500 --> 00:05:34,480
+بتتكلم مجرد سرد تاريخي للموضوع الاحتلال على
+
+65
+00:05:34,480 --> 00:05:37,620
+التاريخ جيت وجيت والله كتاب بتتكلم على ال second
+
+66
+00:05:37,620 --> 00:05:38,240
+derivative
+
+67
+00:05:41,020 --> 00:05:45,180
+Science، لجيت كتاب بتتكلم عن الـ poems أو الشعر،
+
+68
+00:05:45,180 --> 00:05:48,800
+literature، مظبوط؟ هيك صار في عندي أنا الآن
+
+69
+00:05:48,800 --> 00:05:52,860
+باستخدم الـ knowledge تبعتي، تمام؟ و معرفتي
+
+70
+00:05:52,860 --> 00:05:58,370
+بالمجموعات السابقةبالمجموعات السابقة اللى موجودة
+
+71
+00:05:58,370 --> 00:06:02,010
+عندى و بروح ايش بصير اخد كل كتاب او كل object
+
+72
+00:06:02,010 --> 00:06:06,230
+بقارن الخصائص طبعته او بحاول اطلع اعرف عناش بتكلم
+
+73
+00:06:06,230 --> 00:06:10,910
+الكتاب هذا و بروح بصنفه لوحده بحطه تحت مجموعة او
+
+74
+00:06:10,910 --> 00:06:16,170
+تحت اي مجموعة من العناصر اللى موجودةعامة تمام
+
+75
+00:06:16,170 --> 00:06:22,010
+فمعناته ال classification هي عضوية المجموعات
+
+76
+00:06:22,010 --> 00:06:25,950
+predefined group مجموعات معروفة مسبقا و بدي احدد
+
+77
+00:06:25,950 --> 00:06:31,030
+مين العناصر تمام اللي ممكن يكونوا تحت المجموعة
+
+78
+00:06:31,030 --> 00:06:36,970
+اللي عندها الان بيفرج عن التقسيم او ال clustering
+
+79
+00:06:36,970 --> 00:06:42,840
+لو قلت الشباب انا بدي اجسمكوا لمجموعات تمامشغلات
+
+80
+00:06:42,840 --> 00:06:45,480
+كتيرة ممكن تكون مشتركة أو شغلات كتيرة ممكن تكون
+
+81
+00:06:45,480 --> 00:06:49,840
+مختلفة بينكوا عشان لو روحت أنا قلت بتجسمكوا تبع ال
+
+82
+00:06:49,840 --> 00:06:56,300
+.. سنة الميلاد تمام؟ لاحظ أنا في كل الكلام اللي
+
+83
+00:06:56,300 --> 00:07:02,620
+أنا بقوله ماليش أي control على .. على عدد
+
+84
+00:07:02,620 --> 00:07:05,760
+المجموعات بينما في ال cluster .. في ال
+
+85
+00:07:05,760 --> 00:07:11,400
+classification عدد المجموعاتطبعا بدي أجسمكوا تبعا
+
+86
+00:07:11,400 --> 00:07:16,100
+لتاريخ ميلادكوا لسنة الميلاد كل ناس مولودين في سنة
+
+87
+00:07:16,100 --> 00:07:20,840
+هدولة بيكونوا مجموعة لحالهم طب لجيت واحد بحاله أه
+
+88
+00:07:20,840 --> 00:07:28,040
+هدا بدوني أعمل مجموعة ماعنديش مشكلة في الموضوع لأ
+
+89
+00:07:28,040 --> 00:07:34,940
+ممكن أسخر ال cluster لخدمة ال classificationممكن
+
+90
+00:07:34,940 --> 00:07:39,240
+أسخر ال clustering لخدمة ال classification وهذا
+
+91
+00:07:39,240 --> 00:07:43,240
+نسميه عادة semi supervised learning ان انا فعليا
+
+92
+00:07:43,240 --> 00:07:47,480
+عندي بعض ال data بعض ال data labelled و بعض ال
+
+93
+00:07:47,480 --> 00:07:51,560
+data .. و كم كبير من ال data unlabeled فبروح
+
+94
+00:07:51,560 --> 00:07:56,580
+بجسمهم لاربع مجموعات حسب معرفتي من هناو بطلع في كل
+
+95
+00:07:56,580 --> 00:08:00,560
+cluster كل مجموعة ايش الاكثر عناصر من ال الهم
+
+96
+00:08:00,560 --> 00:08:03,600
+label و بسميه بطلق عليه و بخلي ال bag كله ماشي
+
+97
+00:08:03,600 --> 00:08:08,260
+يحملوا نفس الصفة اجيت اقول بدي اصنفكوا تبعا
+
+98
+00:08:08,260 --> 00:08:09,560
+لمعدلاتكوا
+
+99
+00:08:12,460 --> 00:08:15,200
+واحد يقول يا دكتور ما هو معروف المعدلات تسعين وفوق
+
+100
+00:08:15,200 --> 00:08:22,200
+من تمانين لتسعين okay بس لاحظ أنا ما اتكلمت على كل
+
+101
+00:08:22,200 --> 00:08:26,000
+اسم مجموعة المجموعات هذه مالهاش أسامي مش معرفة
+
+102
+00:08:26,000 --> 00:08:31,280
+بالنسبة لي مسبقا تبع الأوزانكوا الأطوالكوا تمام كل
+
+103
+00:08:31,280 --> 00:08:34,740
+الشغلات هذه عاملا جاعة بتتكلم على مجموعاتعلى
+
+104
+00:08:34,740 --> 00:08:38,720
+مجموعات و بعد هيك بنصير اما بحدد الخاصية و بشغل او
+
+105
+00:08:38,720 --> 00:08:42,440
+بروح بقول لشبابنا نجسم لمجموعتين لتلت مجموعات و
+
+106
+00:08:42,440 --> 00:08:45,860
+بصير ادور على ال common properties اللي تجمعكم مع
+
+107
+00:08:45,860 --> 00:08:51,860
+بعض لكن ايش الصفر السمة السائدة لكل مجموعة نعرفش
+
+108
+00:08:51,860 --> 00:08:55,580
+لاحقا بدنا نصير نفكر ندور بعنوان بينما بال
+
+109
+00:08:55,580 --> 00:08:59,340
+classification انا عندى التصنيفات موجودة عندى
+
+110
+00:08:59,340 --> 00:09:05,320
+مستويات الطلاب موجودة ممتاز جيد جدا جيدمقبول؟ هذه
+
+111
+00:09:05,320 --> 00:09:08,920
+التصنيفات اللي موجودة في عند الآن درجة الرطوبة إما
+
+112
+00:09:08,920 --> 00:09:13,960
+هتكون عالية أو متوسطة أو منخفضة الجو إما هيكون
+
+113
+00:09:13,960 --> 00:09:18,860
+غائم أو غائم جزئيا أو صافي تمام؟ اليوم إما هيكون
+
+114
+00:09:18,860 --> 00:09:22,420
+ماطر أو هيكون غير ماطر هذه المعلومات أو هذه ال
+
+115
+00:09:22,420 --> 00:09:22,860
+categories
+
+116
+00:09:29,580 --> 00:09:33,860
+بتكلم على category كمجموعات إلها صفات مشتركة محددة
+
+117
+00:09:33,860 --> 00:09:38,040
+وواضحة وإلها اسم فهنا احنا بنتكلم على تصنيف
+
+118
+00:09:38,040 --> 00:09:43,860
+classification إيش اللي احنا بنتعلمه في ال chapter
+
+119
+00:09:43,860 --> 00:09:44,380
+هذا؟
+
+120
+00:10:02,660 --> 00:10:06,840
+إيش بتتوجه إن احنا نتعلم في ال chapter هذا الآن؟
+
+121
+00:10:06,840 --> 00:10:18,980
+كيف أقدر أعرف المجموعات؟ مش صحيح، أيوة أتعرف
+
+122
+00:10:18,980 --> 00:10:24,340
+على التقنيات اللي تستخدم في التصنيف غيره، طبعا هذا
+
+123
+00:10:24,340 --> 00:10:29,700
+حتكلم شغل مكتبات أو شغل ناس شغالة في المجال، غير،
+
+124
+00:10:29,700 --> 00:10:34,050
+أه حسنأيش بتتوقع أن ابدا أتعلم الفصل هذا أو
+
+125
+00:10:34,050 --> 00:10:38,450
+الشابتر هذا؟
+
+126
+00:10:38,450 --> 00:10:44,170
+كيف المكتبات بتعمل؟ ايش المبدأ اللي بتشتغل عليه؟
+
+127
+00:10:44,170 --> 00:10:48,470
+اه أحمد ايش ممكن أتوقع أن أتعلم الفصل هذا الشابتر
+
+128
+00:10:48,470 --> 00:10:52,430
+هذا؟ على أي أساس أصنف؟
+
+129
+00:10:56,620 --> 00:11:00,240
+أديب الشغلات المشتركة بين الـ instances أو الـ
+
+130
+00:11:00,240 --> 00:11:07,980
+object عشان أقدر أصنفها أقدر أفرج بين إيش؟ بين ال
+
+131
+00:11:07,980 --> 00:11:13,180
+objects أو بين جثين أتعرف على الخصائص تبعت كل
+
+132
+00:11:13,180 --> 00:11:19,480
+مجموعة عشان أقدر أحدد لـ new objects أو الـ unseen
+
+133
+00:11:19,480 --> 00:11:23,900
+samples بتنتمي لأي مجموعة بس فعليا مش أنا اللي
+
+134
+00:11:23,900 --> 00:11:29,680
+هشتغلالـ Machine الفكرة الآن لما نتكلم على
+
+135
+00:11:29,680 --> 00:11:32,560
+Classification هنبدأ نتكلم على Machine Learning
+
+136
+00:11:32,560 --> 00:11:37,160
+Algorithm هنبدأ نتكلم على تعلم الآلة أو تعلم ..
+
+137
+00:11:37,160 --> 00:11:40,840
+تعلم الآلة كيف الآلة بتدور على ال characteristics
+
+138
+00:11:40,840 --> 00:11:45,320
+المشتركة لكل مجموعة الآن بما أن ال classification
+
+139
+00:11:45,320 --> 00:11:50,380
+هي واحدة من supervised learning method احنا كنا
+
+140
+00:11:50,380 --> 00:11:54,300
+حكينا المرة الماضية ال data mining tasks نوعين
+
+141
+00:11:55,310 --> 00:11:59,690
+Predictive وDescriptive في الـ Predictive قلت أنا
+
+142
+00:11:59,690 --> 00:12:03,430
+فيه Classification وبدى اتنبأ بكاتجورى بدى اتنبأ
+
+143
+00:12:03,430 --> 00:12:07,310
+بال Target Label تبع المجموعة وفي عند Regression
+
+144
+00:12:07,310 --> 00:12:11,490
+بدى اتنبأ بcontinuous value بصبح وقلنا في ال
+
+145
+00:12:11,490 --> 00:12:15,670
+Descriptive في الوصفية اما بتكلم على Clustering
+
+146
+00:12:15,670 --> 00:12:20,770
+تقسيم لمجموعات او Outlayer Detection تحديد الشوان
+
+147
+00:12:20,770 --> 00:12:27,070
+او ال Association Rulesتحديد الإطباع ما بين
+
+148
+00:12:27,070 --> 00:12:34,350
+العناصر اللي موجودة الآن ضمن الكلام هذا أنا هتعرف
+
+149
+00:12:34,350 --> 00:12:37,630
+على مجموعة من الـ algorithms والقاليات اللي
+
+150
+00:12:37,630 --> 00:12:45,450
+بتستخدمها من أجل استنباط خصائص المجموعات المعرفة
+
+151
+00:12:45,450 --> 00:12:51,390
+مسبقا اللي موجودة عندى في ال data ومن ثم لما بدي
+
+152
+00:12:51,390 --> 00:12:55,000
+أجي أعمل predictionبدي تديني ال prediction أو بدي
+
+153
+00:12:55,000 --> 00:12:58,740
+تديني ال category أو ال group أو اسم المجموعة اللي
+
+154
+00:12:58,740 --> 00:13:01,540
+بينتمي إليها ال object الجديد هذا اللي هو ال
+
+155
+00:13:01,540 --> 00:13:06,640
+unseen object أو unseen instance يعني فعليا أنا
+
+156
+00:13:06,640 --> 00:13:09,840
+بدي أشوف الآلة كيف اللي بتتعلم طب أنا وين في
+
+157
+00:13:09,840 --> 00:13:14,400
+الموضوع انت دورك جهزت البيانات بدك تختار algorithm
+
+158
+00:13:14,400 --> 00:13:18,100
+كويس وتقول لل algorithm اقرأ البيانات وتعلم منها
+
+159
+00:13:18,100 --> 00:13:23,160
+تعمله evaluation قبل ما تقول أنا صار فيه عندىموديل
+
+160
+00:13:23,160 --> 00:13:26,280
+بيقدر يعمل prediction لل category أو لل class اللي
+
+161
+00:13:26,280 --> 00:13:34,320
+موجود عندها ال classification
+
+162
+00:13:34,320 --> 00:13:39,020
+هي
+
+163
+00:13:39,020 --> 00:13:41,840
+واحدة من ال mining task او ال data mining task
+
+164
+00:13:41,840 --> 00:13:46,140
+التقليدية ال task يعني من اهم او من اكثر ال task
+
+165
+00:13:46,140 --> 00:13:52,520
+شهرة ل classification وطبعاممتدة أساسا بالـ
+
+166
+00:13:52,520 --> 00:13:55,060
+Machine Learning عادة الـ Machine Learning
+
+167
+00:13:55,060 --> 00:13:58,880
+Algorithm الشباب بشكل عام أو التقنيات بتشتغل ضمن
+
+168
+00:13:58,880 --> 00:14:04,860
+منهجيات معينة الأولى أنه فعليا هل الـ Machine
+
+169
+00:14:04,860 --> 00:14:08,940
+Learning هذه تتدرب أو تعلم من خلال الـ Human
+
+170
+00:14:08,940 --> 00:14:15,200
+Supervision من خلال مراقبة الإنسانأو إشراف الإنسان
+
+171
+00:14:15,200 --> 00:14:19,280
+الفكرة كالتالي بينفعش أنا أروح أقول للطلاب في
+
+172
+00:14:19,280 --> 00:14:23,900
+المدرسة هذه مجموعة الكتب بروح أدخله في الصف الآن
+
+173
+00:14:23,900 --> 00:14:27,660
+من العشرة للاحد عشر عليكوا عربي أدرس كتاب العربي
+
+174
+00:14:27,660 --> 00:14:35,260
+بدون ما يكون عندهم مدرس، بينفع؟ ليش؟ طبيعي الإنسان
+
+175
+00:14:35,260 --> 00:14:38,140
+إنه هيميل إنه إيش؟ مدونش يدرس، هيقعد يلعب يتحدث
+
+176
+00:14:38,140 --> 00:14:41,080
+ويجار وكذا أثناء إحتياجات بيكون المدرس موجود
+
+177
+00:14:41,080 --> 00:14:45,750
+والتاني يحطي الرسم في بعض ويتحدثوافالآن المراقبة
+
+178
+00:14:45,750 --> 00:14:49,370
+هي ضرورية من أجل ضبط عملية التعلم بس الآلة ما
+
+179
+00:14:49,370 --> 00:14:54,270
+عندهاش شعور وبتملش يعني مش شغلة وبالتالي هتدرس لأ
+
+180
+00:14:54,270 --> 00:14:58,450
+المفهوم الـ Supervision هان شو علاقة الإنسان في
+
+181
+00:14:58,450 --> 00:15:02,350
+تحديد البيانات اللي موجودة إذا أنا كانت ال data
+
+182
+00:15:02,350 --> 00:15:07,410
+اللي موجودة عندى عبق .. حطيتلها target وحطيتلها
+
+183
+00:15:07,410 --> 00:15:13,430
+label حددت الفئات تبع كل instance معاه شو بتكلم
+
+184
+00:15:13,430 --> 00:15:19,480
+عليه؟supervised learning في عندي الـ unsupervised
+
+185
+00:15:19,480 --> 00:15:22,900
+غير مراقب و أنا بقوله جسم لمجموعات تلاتة اربعة
+
+186
+00:15:22,900 --> 00:15:26,780
+خمسة عشرة عشرين بس ال system لحاله بيشتغل semi
+
+187
+00:15:26,780 --> 00:15:29,780
+supervised و هو عبارة عن combination بين التنين
+
+188
+00:15:29,780 --> 00:15:35,400
+هدول reinforcement learning اللي هو إعادة التعلم
+
+189
+00:15:35,400 --> 00:15:41,000
+بالضغط أو بالقوة و هنا بيقبل زي مبدأ الثواب و
+
+190
+00:15:41,000 --> 00:15:45,610
+العقابعلى ال algorithm اللي شغال في حد فيكوا لعب
+
+191
+00:15:45,610 --> 00:15:51,450
+سوبر ماريو كلكوا لعبتوها كويس عمرك اتفرجت على ال
+
+192
+00:15:51,450 --> 00:15:55,930
+system هو بيلعب يعني تخليه تفتح ال super mario
+
+193
+00:15:55,930 --> 00:15:58,470
+تقوله tutorial و تخلي ال system هو اللي يلعب مش
+
+194
+00:15:58,470 --> 00:16:03,550
+video نفس النفس حكاية لعبك بس ممكن هو يشتغلك تشطر
+
+195
+00:16:03,550 --> 00:16:07,550
+منكالفكرة وين؟ كانت في ال .. ليش جبتيلك ال super
+
+196
+00:16:07,550 --> 00:16:10,150
+mario بالتحديد يا جماعة الخير؟ لأن ال concept بسيط
+
+197
+00:16:10,150 --> 00:16:12,930
+جدا ممكن تستوعبهان، الآن لما كانوا في لعبة ال
+
+198
+00:16:12,930 --> 00:16:16,410
+super mario بياكلوا الفطر، إيش بيصير في ال
+
+199
+00:16:16,410 --> 00:16:21,150
+character تبعك؟بتطور، بيكبر، بيتضخم، مظبوط؟ وكل
+
+200
+00:16:21,150 --> 00:16:25,890
+تطور أو كل مشروم أو كل فطر بياكله تمام؟ كان بنجيه
+
+201
+00:16:25,890 --> 00:16:30,290
+من موت محقق عند وين؟ عندما .. لما بدرب في .. في
+
+202
+00:16:30,290 --> 00:16:34,510
+سلحفة أو بجع في جورة أو بدرب في صبار، مظبوط؟ الآن
+
+203
+00:16:34,510 --> 00:16:38,170
+هذه الحالات، كل هذه الحالات مميتةفكان كل ما هو
+
+204
+00:16:38,170 --> 00:16:42,470
+بيحصل فطر أكبر كان بيحصل عدد مرات من النجاة أكبر
+
+205
+00:16:42,470 --> 00:16:47,150
+وكل ما بيصطدم في سلحفا أو بيقعد .. بيسقط في جورة
+
+206
+00:16:47,150 --> 00:16:56,570
+أو بخبط في صبار بغلت وبالتالي إذا أنت اشتغلت بزيد
+
+207
+00:16:56,570 --> 00:17:01,470
+ال rank بزيد الفرصة تبعتك وإذا أنت اشتغلت بالعكس
+
+208
+00:17:01,470 --> 00:17:06,590
+وماتصرفتش بلباقة أو بطريقة جيدةهتصل لمرحلة نقول لك
+
+209
+00:17:06,590 --> 00:17:11,150
+خلاص مضال الكاش فرصة عيد اللعبة من تاني، مظبوط؟
+
+210
+00:17:11,150 --> 00:17:14,090
+هذا مبدأ ال reinforcement learning اللي فعليا احنا
+
+211
+00:17:14,090 --> 00:17:18,590
+ممكن نطبقه بس مش اختصاصنا احنا فعليا الفصل هذا في
+
+212
+00:17:18,590 --> 00:17:23,410
+ال data mining بس شغالين شويهان و شويهان كذلك ال
+
+213
+00:17:23,410 --> 00:17:28,590
+machine learning تقسمالـ Algorithm تبعتها هل عملية
+
+214
+00:17:28,590 --> 00:17:32,550
+التعليم هتصير incrementally on a fly؟ يعني بين
+
+215
+00:17:32,550 --> 00:17:37,330
+قصين وانا قاعد بأتمرن أو عفوا وانا قاعد بأشتغل
+
+216
+00:17:37,330 --> 00:17:41,450
+فعليا هل هكتسب تجارب جديدة أضيفها لل knowledge
+
+217
+00:17:41,450 --> 00:17:45,770
+تبعتي؟ إذا هذا الكلام كان يطبق في موضوع ال machine
+
+218
+00:17:45,770 --> 00:17:51,080
+learning فاحنا بنتكلم على online learningبينما اذا
+
+219
+00:17:51,080 --> 00:17:53,520
+كنت انا و هذا اللي احنا هنشتغل عليه عنhand في ال
+
+220
+00:17:53,520 --> 00:17:58,360
+batch ال data set انا قرأتها لمرة واحدة و بنيت
+
+221
+00:17:58,360 --> 00:18:02,180
+عليها model و ال model هذا وضلت اطبق فيه بدون
+
+222
+00:18:02,180 --> 00:18:05,560
+الاستفادة من ال prediction الجديدة فده بنسمي احنا
+
+223
+00:18:05,560 --> 00:18:10,260
+batch learning كذلك في عندي ال trend في ال machine
+
+224
+00:18:10,260 --> 00:18:14,240
+learning هل هي model based ولا instance based
+
+225
+00:18:14,240 --> 00:18:19,860
+model based يعني هيروح يبني model هيروح يبنيموديل
+
+226
+00:18:19,860 --> 00:18:24,680
+هو اللي بديه يعمل prediction لاحقا بينما بال
+
+227
+00:18:24,680 --> 00:18:28,700
+instance based في كل مرة بديه يعمل prediction بديه
+
+228
+00:18:28,700 --> 00:18:34,620
+يرجع لل data 6 الأصلية و طبعا هدول الشغلتين لكل
+
+229
+00:18:34,620 --> 00:18:39,480
+واحدة فيه إيجابياتها و إليها سليبياتها كذلك في
+
+230
+00:18:39,480 --> 00:18:43,040
+trend آخر فيه deterministic و فيه probabilistic
+
+231
+00:18:43,040 --> 00:18:47,390
+approachفي الـ learning في الـ deterministic اللي
+
+232
+00:18:47,390 --> 00:18:51,610
+هو الدقيق أو الموحد انه ال algorithm هذا مع ال
+
+233
+00:18:51,610 --> 00:18:56,370
+input هذا لو عدته خمس تلاف مرة لو عدته مليون مرة
+
+234
+00:18:56,370 --> 00:19:01,070
+هيديني نفس النتيجة محدد بينما في ال probabilistic
+
+235
+00:19:01,070 --> 00:19:04,310
+طبعا في ال deterministic مافيش عندي مجلة
+
+236
+00:19:04,310 --> 00:19:09,240
+randomness مافيش مجلة عشوائية كله شغال ضمنقيم
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+237
+00:19:09,240 --> 00:19:12,580
+حقيقية موجودة بين إيدينا بينما في الـ
+
+238
+00:19:12,580 --> 00:19:15,720
+Probabilistic Approach بيعتمد على الـ Randomness
+
+239
+00:19:15,720 --> 00:19:18,660
+لأنه بياخد Sample من ال population و بيصير .. ممكن
+
+240
+00:19:18,660 --> 00:19:23,180
+نزقر .. عفوا النتيجة تتغير ما بين كرن و التاني
+
+241
+00:19:23,180 --> 00:19:26,200
+بشكل
+
+242
+00:19:26,200 --> 00:19:28,880
+عام احنا بنتكلم على ال supervised learning و
+
+243
+00:19:28,880 --> 00:19:34,050
+بالتحديد ال classificationالان super vision زي ما
+
+244
+00:19:34,050 --> 00:19:37,870
+قلنا سابقا training data ال data set اللي انا
+
+245
+00:19:37,870 --> 00:19:49,150
+اخترتها بتتكلم عن ال heart disease ال
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+246
+00:19:49,150 --> 00:19:55,090
+body mass index ال blocked artery تصلب الشرايين
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+247
+00:19:55,090 --> 00:20:04,810
+قلم في الصدر و في الآخرالتصنيع التبعي هل هذا heart
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+248
+00:20:04,810 --> 00:20:11,790
+disease هل هذا مرض قلب مرض قلب ولا لأ yes و no ال
+
+249
+00:20:11,790 --> 00:20:18,030
+data set في جو زي اليوم بتكلم الجو غائم ال outlook
+
+250
+00:20:18,030 --> 00:20:24,790
+cloudy ال temperature عشرة مثلا او اتناشر ال
+
+251
+00:20:24,790 --> 00:20:32,600
+humidityIntermediate متوسطة الـ Windy فيه رياح بدي
+
+252
+00:20:32,600 --> 00:20:38,720
+أعمل هل اليوم ماطر أو لأ ك category كفئة لاحظ أنا
+
+253
+00:20:38,720 --> 00:20:43,400
+الآن بتكلم هذه ال label تبعتي هي ال target هي ال
+
+254
+00:20:43,400 --> 00:20:47,140
+group الـ predefined group إما هدول ال instances
+
+255
+00:20:47,140 --> 00:20:52,320
+ال data set مقسمين لمجموعتين ناس مصابين أمراض
+
+256
+00:20:52,320 --> 00:20:58,190
+القلب و ناس غير مصابةالجو أيام ماطرة و أيام غير
+
+257
+00:20:58,190 --> 00:21:03,210
+ماطرة تصنيفات الطلاب جيد جدا او ممتاز جيد جدا جيد
+
+258
+00:21:03,210 --> 00:21:07,210
+مقبولة هذه التصنيفات الموجودة معروفة مسبقا وهذه
+
+259
+00:21:07,210 --> 00:21:11,770
+هتكون موجودة عندهان فلل training set هذه لازم تكون
+
+260
+00:21:11,770 --> 00:21:16,530
+عاملة combination ما بين ال attributes اللي عندي
+
+261
+00:21:16,530 --> 00:21:20,310
+بالاضافة
+
+262
+00:21:21,330 --> 00:21:25,310
+الـ groups او الـ predefined groups يعني بين جثين
+
+263
+00:21:25,310 --> 00:21:34,190
+محددله بشكل دقيق كل raw بيتبع اي مجموعة تمام؟ كل
+
+264
+00:21:34,190 --> 00:21:39,870
+raw بيتبع اي مجموعة و عادة هذه بنسميها احنا
+
+265
+00:21:39,870 --> 00:21:45,990
+training data training data فال classification هي
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+266
+00:21:45,990 --> 00:21:53,400
+مهمتها تعمل predict categorialclass label تتنبأ
+
+267
+00:21:53,400 --> 00:21:59,360
+بالفئة باسم الفئة تبعتنين؟ تبعت المجموعات لل
+
+268
+00:21:59,360 --> 00:22:03,160
+unseen data طبعا ال class label هذا إما بيكون
+
+269
+00:22:03,160 --> 00:22:10,460
+discrete أو بيكون nominal شو يعني nominal data؟
+
+270
+00:22:10,460 --> 00:22:15,620
+text .. text .. text .. تمام؟ طب شو يعني discrete
+
+271
+00:22:15,620 --> 00:22:20,450
+data؟قيم منفصل عن بعضها هي فعلياً وظاهرها
+
+272
+00:22:20,450 --> 00:22:24,690
+continuous عشر، عشرين، تلاتين تمام؟ ولمّا بتروح
+
+273
+00:22:24,690 --> 00:22:27,630
+يعمل ال prediction هو بتقول أما عشرة أو عشرين أو
+
+274
+00:22:27,630 --> 00:22:30,570
+تلاتين مالهاش علاقة بالأرقام أو العلاقة بالحساب
+
+275
+00:22:30,570 --> 00:22:36,670
+مطلقاً الآن ففي
+
+276
+00:22:36,670 --> 00:22:39,570
+ال classification هيبني prediction model عشان
+
+277
+00:22:39,570 --> 00:22:43,410
+يتنبأ بال discrete values اللي موجودة عندها تعالى
+
+278
+00:22:43,410 --> 00:22:49,530
+نشوف الصورة هايأو بلاش، قبل ما نروح على الصورة هاي
+
+279
+00:22:49,530 --> 00:22:53,010
+عشان انا بقى أظل أقول Model Model Model Model شو
+
+280
+00:22:53,010 --> 00:23:06,790
+يعني Model؟ نموذج نموذج، تمام وشو
+
+281
+00:23:06,790 --> 00:23:11,250
+يعني نموذج؟ تصور، تصور، تصور، تصور، تصور، تصور،
+
+282
+00:23:11,250 --> 00:23:13,250
+تصور، تصور، تصور، تصور، تصور، تصور، تصور، تصور،
+
+283
+00:23:13,250 --> 00:23:13,250
+تصور، تصور، تصور، تصور، تصور، تصور، تصور، تصور،
+
+284
+00:23:13,250 --> 00:23:13,250
+تصور، تصور، تصور، تصور، تصور، تصور، تصور، تصور،
+
+285
+00:23:13,250 --> 00:23:13,750
+تصور، تصور، تصور، تصور، تصور، تصور، تصور، تصور،
+
+286
+00:23:13,750 --> 00:23:16,030
+تصور، تصور
+
+287
+00:23:18,130 --> 00:23:22,990
+صورة مصغرة شوف أحمد من غاد بيقولك photo
+
+288
+00:23:22,990 --> 00:23:26,770
+description بس سيبك من ال photo و اتكلم عن ال
+
+289
+00:23:26,770 --> 00:23:31,290
+description انا بقولك صح صورة مصغرة او نموذج بلاش
+
+290
+00:23:31,290 --> 00:23:38,410
+نقول مصغر صورة توصفالنموذج أو الشكل أو ال object
+
+291
+00:23:38,410 --> 00:23:41,730
+اللي جاي عندي الآن بتروح شركة Apple على سبيل .. لأ
+
+292
+00:23:41,730 --> 00:23:43,410
+انتوا أقولكوا علاقة بما في ناس بتكون interested
+
+293
+00:23:43,410 --> 00:23:48,310
+بالسيارات تروح شركة BMW بتقولك والله إحنا في عندنا
+
+294
+00:23:48,310 --> 00:23:53,470
+ال model تبع ألفين و تلاتين من السيارة جاهز شو
+
+295
+00:23:53,470 --> 00:23:59,130
+يعني؟ مش .. لأ لأ ماتكلم ال .. ماتكلم على ال model
+
+296
+00:23:59,130 --> 00:24:05,770
+يعني ان هو في عنده تصور أو وصف دقيقلشكل السيارة،
+
+297
+00:24:05,770 --> 00:24:08,470
+إيش السيارة بديها تكون، اللي في الـ 2030 يا همام
+
+298
+00:24:08,470 --> 00:24:12,150
+ممكن prototype أو ممكن يكون عاملة prototype، بس في
+
+299
+00:24:12,150 --> 00:24:17,710
+الآخر أهم في ال prototype هذا مثلا، معارض
+
+300
+00:24:17,710 --> 00:24:20,990
+السيارات، لما بروح بيعرض في المعارض، إيش بقولك؟
+
+301
+00:24:20,990 --> 00:24:25,910
+بقولك، هي model، تمام؟ عن السيارة، هي model عن
+
+302
+00:24:25,910 --> 00:24:26,450
+الجوال
+
+303
+00:24:29,520 --> 00:24:34,720
+sample ايش بستفيد من الـ sample هاي فعليا بشوف الـ
+
+304
+00:24:34,720 --> 00:24:39,000
+real description بشوف وصفه دقيق كيف بيكون لأ لما
+
+305
+00:24:39,000 --> 00:24:42,700
+بروح بقولك في عند ال model تبعت الجوال مكونا من او
+
+306
+00:24:42,700 --> 00:24:47,500
+هيو كده فبديك وصفه جدش حجمه جدش الكاميرا جدش وزنه
+
+307
+00:24:47,500 --> 00:24:50,020
+جدش ال processor جدش ال memory جدش ال storage
+
+308
+00:24:50,020 --> 00:24:53,760
+تبعته ايش هو التقنية المستخدمة مع ال bluetooth مع
+
+309
+00:24:53,760 --> 00:24:57,300
+ال land مع ال wireless عفوا كل الشغلات هذه بتكون
+
+310
+00:24:57,300 --> 00:25:04,310
+موصوفة وبالتالي ال modelهي عبارة عن طريقة لوصف شيء
+
+311
+00:25:04,310 --> 00:25:07,150
+معين، objects معين مرة عليكوا تشغلوا اسمها data
+
+312
+00:25:07,150 --> 00:25:11,930
+model في ال database زمان؟ الفصل الماضي يا إيهاب
+
+313
+00:25:11,930 --> 00:25:16,970
+لما اتكلمنا على ال data model و قبلها انت بتعرف
+
+314
+00:25:16,970 --> 00:25:21,750
+شوية عن ال relational model تمام؟ مصبوط؟ ففعليا
+
+315
+00:25:21,750 --> 00:25:25,450
+ليش بسميها model؟ لأنه بوصف البيانات كنت وبالتالي
+
+316
+00:25:25,450 --> 00:25:31,710
+أنا الآن ال model اللي هتكلم عليههي عبارة عن آلية
+
+317
+00:25:31,710 --> 00:25:37,370
+لوصف الـ knowledge ما تنساش ال data mining هدفها
+
+318
+00:25:37,370 --> 00:25:42,450
+knowledge
+
+319
+00:25:42,450 --> 00:25:45,870
+extraction
+
+320
+00:25:45,870 --> 00:25:53,930
+ولا لأ؟ هدف ال mining task استخراج knowledge من ال
+
+321
+00:25:53,930 --> 00:25:56,970
+data set اللي موجودة طب ال knowledge اللي طلعت هاي
+
+322
+00:25:58,780 --> 00:26:04,060
+كيف بدي أوصفها؟ كيف بدي استخدمها؟ لازم تكون ضمن
+
+323
+00:26:04,060 --> 00:26:10,040
+model معين عشان نقدراش نتكلم عليه الآن بالمثال
+
+324
+00:26:10,040 --> 00:26:14,300
+اللي موجود عندي هان في
+
+325
+00:26:14,300 --> 00:26:18,800
+عندي input raw data مجموعة من التفاح حسب الصورة
+
+326
+00:26:18,800 --> 00:26:26,140
+اللي موجودة عندي هان تمان تفاحات أحجامهم ألوانهم
+
+327
+00:26:27,010 --> 00:26:30,190
+الأوراق اللي موجودة عليهم بالإضافة للريحة والطعم
+
+328
+00:26:30,190 --> 00:26:33,610
+ريحة
+
+329
+00:26:33,610 --> 00:26:38,890
+طفاح اللي هو ريحة ولا ماله مش ريحة ممتاز لو ضليتك
+
+330
+00:26:38,890 --> 00:26:41,630
+ساكتكم بقولك كيف بندخلها بس وما أنك انت سألني
+
+331
+00:26:41,630 --> 00:26:46,810
+خلصنا فالآن هذه ال characteristics الوصفية تبعت ال
+
+332
+00:26:46,810 --> 00:26:51,750
+data هي هم هروح نديها لل algorithm او اختار
+
+333
+00:26:51,750 --> 00:26:55,290
+algorithm machine learning algorithmيقرأ ال data
+
+334
+00:26:55,290 --> 00:27:03,870
+set كلتها يعملها تحليل يوجد علاقة ما بين الحجم و
+
+335
+00:27:03,870 --> 00:27:10,110
+اللون و الرائحة و الطعم كل الشغلات هذه لما تديله
+
+336
+00:27:10,110 --> 00:27:14,570
+ال data set او العناصر هذه يكون قادر على ان يقول
+
+337
+00:27:14,570 --> 00:27:20,590
+لي ان هذه تفاحة الان ال model هذا انا روحت اختبرته
+
+338
+00:27:20,590 --> 00:27:27,690
+بتفاحة خضرةتفاحة ولا لأ؟ تمام؟ اللون واحدة من ال
+
+339
+00:27:27,690 --> 00:27:32,010
+characteristics اللي كانت موجودة بس مش كل شيء الان
+
+340
+00:27:32,010 --> 00:27:37,070
+ال model تبعي الأصل يقول إنه هذا تفاحة لو أنا روحت
+
+341
+00:27:37,070 --> 00:27:45,770
+أضف تهان مجموعة
+
+342
+00:27:45,770 --> 00:27:50,750
+من ال manga أو البرتقال تمام؟ مجموعة من البرتقال
+
+343
+00:27:50,750 --> 00:27:57,670
+وصار في اندي two groupsفي عندي هذه apple
+
+344
+00:27:57,670 --> 00:28:04,870
+و هذه orange ال system اللي يتعرف على خصائص ال
+
+345
+00:28:04,870 --> 00:28:08,890
+apple هي المفهوم التصنيف انه انا خلاص okay هدولة
+
+346
+00:28:08,890 --> 00:28:13,550
+هي المصنف تبعي apple او orange فال system هيتعرف
+
+347
+00:28:13,550 --> 00:28:22,190
+على خصائص ال apple و خصائص التفاح و يبني modelقادر
+
+348
+00:28:22,190 --> 00:28:28,050
+على التفريق ما بين التنتين فلما أنا بديه تفاحة،
+
+349
+00:28:28,050 --> 00:28:30,750
+هيقوللي تفاحة، اديته برتقالة، الاصلي يقوللي
+
+350
+00:28:30,750 --> 00:28:37,430
+برتقالة، طب لو اديته حبة مانجا، مش هيعرف، غلط، في
+
+351
+00:28:37,430 --> 00:28:41,490
+ال classification هان، لأنه آلة، وفيش مجال، يا
+
+352
+00:28:41,490 --> 00:28:45,270
+هذه، يا هذه، فيش مجال، مافيش خيار تالت، انت
+
+353
+00:28:45,270 --> 00:28:48,290
+ماتركتلهوش، في موضوع التصنيف، هي اللي أنا بوصلك
+
+354
+00:28:48,290 --> 00:28:53,020
+إياها، في موضوع التصنيف، فيش مجال،عندك أربع فئات
+
+355
+00:28:53,020 --> 00:28:55,920
+بدك تحط تحت واحدة من الأربع فئات عندك two
+
+356
+00:28:55,920 --> 00:29:00,020
+categories بدك تضيفه لواحدة من ال categories بس
+
+357
+00:29:00,020 --> 00:29:04,760
+غالبا هيضيفه للأقرب يعني تخيل أنه والله كان في ال
+
+358
+00:29:04,760 --> 00:29:08,800
+manga اللي بنتكلم عليها هي لونها أحمر مثلا وماخدة
+
+359
+00:29:08,800 --> 00:29:16,910
+شكل كراوي أكثر تمام فهتروح باتجاه الطفاحففي الآخر
+
+360
+00:29:16,910 --> 00:29:21,570
+هو صح صنفها غلط في كل الأحوال بس هو اجتهد .. اجتهد
+
+361
+00:29:21,570 --> 00:29:27,390
+و راح ضافها للأقرب حسب ال object اللي موجود لكن في
+
+362
+00:29:27,390 --> 00:29:32,190
+المقابل كان في حبة manga أخرى أكبر حجما و لونها
+
+363
+00:29:32,190 --> 00:29:37,430
+برتقالي تمام؟ فمش ضروري أروح أصنفلك إياها تفاح
+
+364
+00:29:37,430 --> 00:29:42,030
+بروح أصنفلك إياها إيش؟ Orange لأنه فعليا ال
+
+365
+00:29:42,030 --> 00:29:49,070
+characteristic تبعتها متشابهة نعملأ مش ممكن عمرك
+
+366
+00:29:49,070 --> 00:29:54,310
+مرة عليك برنامج انه بيبني فئة لوحده ممكن اتعلم
+
+367
+00:29:54,310 --> 00:29:57,650
+تبني .. تبني الحالة تبني الحالة ده حالة يعني اذا
+
+368
+00:29:57,650 --> 00:30:01,890
+تيجي ده اولشه اول مرة تصنفها لحالة و ممكن ال human
+
+369
+00:30:01,890 --> 00:30:06,970
+يقولش شوف رجع لوين بعدين ال human يقول ال human هو
+
+370
+00:30:06,970 --> 00:30:12,520
+صاحب القرار عمرها مالقالةغيرت حال تمام أو أخدت
+
+371
+00:30:12,520 --> 00:30:15,980
+decision لوحدها حتى كل اللي بنشوفه في الذكاء
+
+372
+00:30:15,980 --> 00:30:23,100
+الاصطناعي مرده لتخطيط صحيح من ال human وتصرف الآلة
+
+373
+00:30:23,100 --> 00:30:27,020
+ما هو إلا من تصرف ال human ضمن المسار اللي رسمه
+
+374
+00:30:27,020 --> 00:30:30,540
+الآن سيبك من الأفلام اللي احنا بنشوفها ان ال .. ال
+
+375
+00:30:30,540 --> 00:30:34,620
+.. اتطورته حتى تقطع .. تقطع .. تجيب البشر وتحتل
+
+376
+00:30:34,620 --> 00:30:39,060
+الكون ده مافيش منه تمام؟
+
+377
+00:30:40,540 --> 00:30:45,060
+طيب، الآن فبالتالي يا محمد احنا بنتكلم فش مجال فش
+
+378
+00:30:45,060 --> 00:30:48,280
+مجال ان اروح فئة اضيف فئة جديدة لأ الفئات موجودة
+
+379
+00:30:48,280 --> 00:30:52,340
+مسبقا و بناء عليه انا هشتغل مع الفئات اللي موجودة
+
+380
+00:30:52,340 --> 00:30:56,060
+عندى فضل
+
+381
+00:30:59,640 --> 00:31:02,160
+مية لمية الفرق بين ال regression و ال
+
+382
+00:31:02,160 --> 00:31:06,300
+classification ان ال classification categorical
+
+383
+00:31:06,300 --> 00:31:10,940
+value discrete values واحدة من التنتين هدول بينما
+
+384
+00:31:10,940 --> 00:31:15,960
+بال regression بده يديني قيمة continuous value
+
+385
+00:31:15,960 --> 00:31:26,380
+number بده تكون موجودة عندى طيب الآن ال
+
+386
+00:31:26,380 --> 00:31:32,500
+classificationهي عبارة عن تكنيك أو قالية أو تقنية
+
+387
+00:31:32,500 --> 00:31:36,440
+من أجل التنبؤ
+
+388
+00:31:36,440 --> 00:31:43,340
+to predict group membership شو يعني group
+
+389
+00:31:43,340 --> 00:31:50,640
+membership؟ عضوية المجموعات، هل هذا ملائم لعضوية
+
+390
+00:31:50,640 --> 00:31:54,240
+المجموعة الفلانية ولا لأ؟ في عندي مجموعة اسمها الـ
+
+391
+00:31:54,240 --> 00:32:00,440
+Smart Students في الـ ITأنت ملائم إلها ولا غير
+
+392
+00:32:00,440 --> 00:32:05,860
+ملائم؟ مش أنت اللي بتقرر، تمام؟ في لجنة هتروح
+
+393
+00:32:05,860 --> 00:32:11,460
+تختبرك وبناء عليها تقول أنت تنصلح ولا ما تصلحش،
+
+394
+00:32:11,460 --> 00:32:14,380
+ليش؟ لأنه كمان مرة ال prediction مش أنت صاحب
+
+395
+00:32:14,380 --> 00:32:19,160
+قراره، عفوا ال classification أو التصطيف مش أنت
+
+396
+00:32:19,160 --> 00:32:23,980
+صاحب قراره، في عندنا كل صنف إله rule أو خصائص
+
+397
+00:32:23,980 --> 00:32:29,960
+معينةكل صنف له خصائص معينة وبالتالي .. بالتالي انت
+
+398
+00:32:29,960 --> 00:32:33,760
+بدك تخضع للخصائص اللي موجودة ان طبقت عليك الخصائص
+
+399
+00:32:33,760 --> 00:32:39,560
+فانت بتنتمي للمجموعة ما انطبقتش لأ ممكن تنتمي
+
+400
+00:32:39,560 --> 00:32:43,880
+للمجموعة الثاني او التالتة حسب العناصر اللي موجودة
+
+401
+00:32:43,880 --> 00:32:47,980
+عندها نعم decision
+
+402
+00:32:47,980 --> 00:32:51,340
+واحد
+
+403
+00:32:51,340 --> 00:32:56,570
+فقط هينتمي لواحدة فقط مانتميش للتنتينفي عندك مشكلة
+
+404
+00:32:56,570 --> 00:33:00,150
+في الـ model تبعتك في ال prediction model تبعتك
+
+405
+00:33:00,150 --> 00:33:04,310
+الآن كريم بيطرح بيقول كالتالي لو كان في عندي
+
+406
+00:33:04,310 --> 00:33:11,070
+instance أو عندي object يمكن أن يصنف تحت شغلتين
+
+407
+00:33:11,070 --> 00:33:17,090
+حسب القلة هذا الكلام مرفوض يتصنف تحت قلة تحت عنصر
+
+408
+00:33:17,090 --> 00:33:22,590
+واحد نظبط يا كريم؟ الآن في الشيء الآن إذا أنا
+
+409
+00:33:22,590 --> 00:33:28,260
+قلتله ifالـ Condition هذا، لو تحقق الشرط هذا، وين
+
+410
+00:33:28,260 --> 00:33:33,640
+هيروح؟ على الـ Block تبعتها، لو ما تحققش، مافيش
+
+411
+00:33:33,640 --> 00:33:37,080
+اللي غير الـ Else، وبالتالي مافيش مجال، يا هن يا
+
+412
+00:33:37,080 --> 00:33:40,740
+هن، لأن طبيعة الـ System اللي احنا بنشتغل معاه،
+
+413
+00:33:40,740 --> 00:33:47,240
+لكن هل ممكن الـ System يخطأ ويديني نفس الـ Input
+
+414
+00:33:47,240 --> 00:33:51,080
+أو نفس الـ Object هذا في two categories مختلفات،
+
+415
+00:33:51,080 --> 00:33:55,370
+يعني لو جربت عليه مرتين،في حالة الـ Deterministic
+
+416
+00:33:55,370 --> 00:34:01,570
+مستحيل في حالة الـ Deterministic مستحيل خلاص،
+
+417
+00:34:01,570 --> 00:34:04,290
+ادّاك النتيجة، النتيجة هتحطل تطلعلك بالسمرار لكن
+
+418
+00:34:04,290 --> 00:34:07,830
+في حالة الـ Probabilistic ممكن، ليش؟ لأنه هصير
+
+419
+00:34:07,830 --> 00:34:11,190
+يعتمد على Random Sample من الـ Data Set ويشغل
+
+420
+00:34:11,190 --> 00:34:15,650
+عليها ويديك على الأقرب منهم Anyway، الآن الفكرة
+
+421
+00:34:15,650 --> 00:34:18,450
+كالتالي إنه أنا بدي أعمل Prediction للـ Group
+
+422
+00:34:18,450 --> 00:34:22,290
+Membership أو أتنبأ بعضوية المجموعات اللي عنديها
+
+423
+00:34:23,410 --> 00:34:27,310
+مثل اللي انا بدأت نبق بالطقس هل هو sunny ولا rainy
+
+424
+00:34:27,310 --> 00:34:32,030
+ولا cloudy بينفعش اروح اقول والله انا في عندي ..
+
+425
+00:34:32,030 --> 00:34:35,190
+بدأ أضيف كمان category جديدة مغبر من عندي أو ال
+
+426
+00:34:35,190 --> 00:34:39,530
+system يقترح علي لأ هذه ال category هي اللي موجودة
+
+427
+00:34:39,530 --> 00:34:48,790
+وانت بدك تصنف كل الأيام لواحد من التلاتة هدول في
+
+428
+00:34:48,790 --> 00:34:54,470
+ال machine learning بشكل عام ال classifierعبارة عن
+
+429
+00:34:54,470 --> 00:35:01,970
+computational object أو computational model حساب
+
+430
+00:35:01,970 --> 00:35:08,370
+على مرحلتين المرحلة
+
+431
+00:35:08,370 --> 00:35:12,410
+الأولى بنسميها ال training مرحلة
+
+432
+00:35:13,190 --> 00:35:15,970
+للـ training مفهوم مرحلة الـ training يا جماعة
+
+433
+00:35:15,970 --> 00:35:21,250
+الخير انه انا فعليا اعمل analysis لكل العناصر اللي
+
+434
+00:35:21,250 --> 00:35:24,530
+موجودة التمن الطفاحات اللي شوفناهم بالشكل السابق
+
+435
+00:35:24,530 --> 00:35:27,290
+والست بورتقالات اللي انتصرت sentimani بشكل وهمي
+
+436
+00:35:27,290 --> 00:35:32,490
+انا هان بدي اخد كل instance و اربط العلاقة و احاول
+
+437
+00:35:32,490 --> 00:35:36,130
+اوجد علاقة بين خصائص ال object هذا مع ال label
+
+438
+00:35:36,130 --> 00:35:43,440
+عشان اقدر اخد generalknowledge أو general rules لـ
+
+439
+00:35:43,440 --> 00:35:48,260
+classification عشان لما يجيني أي object أقول لو
+
+440
+00:35:48,260 --> 00:35:53,760
+كان وزن ال object هذا كذا ولونه orange تمام؟ وشكله
+
+441
+00:35:53,760 --> 00:36:01,740
+دائري فهذا حتما بورتقالة otherwise else هيكون إيش؟
+
+442
+00:36:01,740 --> 00:36:05,200
+تفاح لأنه ماعنديش خيارات غير التفاح فبصير إما
+
+443
+00:36:05,200 --> 00:36:12,530
+بورتقالأو تفاح و تحت التفاح ممكن تحط كل العناصر أو
+
+444
+00:36:12,530 --> 00:36:16,610
+كل الفواكه التانية التي لم يقدر ان يصنفها ال
+
+445
+00:36:16,610 --> 00:36:20,770
+system على انهاش برتقال و عادة في اللغات بنسميها
+
+446
+00:36:20,770 --> 00:36:27,350
+binary classificationtrue وfalse positive و
+
+447
+00:36:27,350 --> 00:36:32,570
+negative orange not orange مابنقولش تفاح لأن لو حط
+
+448
+00:36:32,570 --> 00:36:35,410
+المانجا وحط الموز تحت التفاح حصير في عنا خطأ
+
+449
+00:36:35,410 --> 00:36:40,190
+فبنقول احنا orange و not orange و هكذا الآن في
+
+450
+00:36:40,190 --> 00:36:46,670
+مرحلة لل training زي ما قلنا انه هياخد كل ال data
+
+451
+00:36:46,670 --> 00:36:51,450
+points اللي موجودة عندها اللي هي ال samples مع ال
+
+452
+00:36:51,450 --> 00:36:58,820
+correct label المرتبط فيهاويحاول يتعلم يصل لـ
+
+453
+00:36:58,820 --> 00:37:03,280
+pattern معين كيف ال label هذا مرتبط بالـ point زي
+
+454
+00:37:03,280 --> 00:37:09,020
+ما حكينا قبل لحظات بمجرد إن ال system هذا تعلم بدي
+
+455
+00:37:09,020 --> 00:37:13,300
+يبدأ يتصرف الآن فتصرفه هيكون عبارة عن function
+
+456
+00:37:13,300 --> 00:37:18,900
+prediction function هتاخد ال input تبع ال sample
+
+457
+00:37:18,900 --> 00:37:23,480
+تبع ال data point بدون ال label عشان تعمل هي
+
+458
+00:37:23,480 --> 00:37:27,500
+predictionللـ label أو لل category اللي موجودة
+
+459
+00:37:27,500 --> 00:37:33,980
+عندها فال
+
+460
+00:37:33,980 --> 00:37:37,240
+step الأولى بنسميها احنا ال model construction
+
+461
+00:37:37,240 --> 00:37:43,040
+بناء ال model في ال regression يا جماعة الخير وحتى
+
+462
+00:37:43,040 --> 00:37:45,960
+في ال classification ممكن ال model تبعي يكون عبارة
+
+463
+00:37:45,960 --> 00:37:48,620
+في ال binary classification يكون عبارة عن linear
+
+464
+00:37:48,620 --> 00:37:53,740
+line linear equation ال Y equal M
+
+465
+00:38:07,350 --> 00:38:13,660
+معادلة خط مستقيم ماهي الخط المستقيم مهمته؟بيفصل
+
+466
+00:38:13,660 --> 00:38:17,020
+بين شغلتين اللي فوق الخط category و اللي تحت الخط
+
+467
+00:38:17,020 --> 00:38:20,800
+category تانية ففي لحظة ال binary classification
+
+468
+00:38:20,800 --> 00:38:25,840
+إذا قدرت أنا أصل لمعادلة الخط المستقيم اللي بيفصل
+
+469
+00:38:25,840 --> 00:38:31,160
+ما بين ال two categories خلاص هي ال model تبعي
+
+470
+00:38:31,160 --> 00:38:37,700
+بصير باخد ال instances تمام؟ و بقى قارنهاإذا كانت
+
+471
+00:38:37,700 --> 00:38:41,080
+أكبر من كده فهي positive أقل من كده فهي negative
+
+472
+00:38:41,080 --> 00:38:44,860
+true أو false orange أو not orange فهي ال model
+
+473
+00:38:44,860 --> 00:38:49,480
+اللي أنا بدور عليه في ال model construction احنا
+
+474
+00:38:49,480 --> 00:38:53,500
+عادة بنفترض ان ال data set كل sample في ال data
+
+475
+00:38:53,500 --> 00:39:00,070
+set بتنتمي ل only one categoryلأن لو نفس ال data
+
+476
+00:39:00,070 --> 00:39:03,030
+set أو عفوا نفس ال instance هذه تكررت مع different
+
+477
+00:39:03,030 --> 00:39:07,250
+category اتوا في عندي مشكلة الشغل اللي بتعلمها قبل
+
+478
+00:39:07,250 --> 00:39:10,390
+شوية بدي احاول انفيها او بدي اتراجع عنها و احط
+
+479
+00:39:10,390 --> 00:39:13,970
+واحدة مضادة لها و هذا الكلام ولا عمره بصير تماما
+
+480
+00:39:13,970 --> 00:39:18,070
+تماما مثل ما اجي اقول اعلم الولد الصغير اقوله 2
+
+481
+00:39:18,070 --> 00:39:23,850
+ضرب 3 يساوي 6 و في نفس الوجهة اروح اقوله بعد فترة
+
+482
+00:39:23,850 --> 00:39:26,090
+2 ضرب 3 يساوي 16
+
+483
+00:39:29,010 --> 00:39:34,810
+يحفظ مين فيهم؟ مين فيهم الصح؟ الأخيرة الصح اه؟
+
+484
+00:39:34,810 --> 00:39:37,850
+مابيعرفش ال system ال computer مابيعرفش انت في
+
+485
+00:39:37,850 --> 00:39:42,370
+مرحلة التلقين التنتين صح و لما تصير في عنده معلومة
+
+486
+00:39:42,370 --> 00:39:47,870
+متضاربة فعليا مش هيقدر ياخد decision في أي حالة
+
+487
+00:39:47,870 --> 00:39:52,140
+فيها اتنين ضرب تلاتةهذا اللي بيصير عشان هي كده
+
+488
+00:39:52,140 --> 00:39:55,820
+نفترض انه في موضوع ال learning أو في مرحلة لل
+
+489
+00:39:55,820 --> 00:39:58,180
+training أو ال learning في ال model construction
+
+490
+00:39:58,180 --> 00:40:04,680
+انه كل instance بتنتمي فقط ل only one category one
+
+491
+00:40:04,680 --> 00:40:10,620
+label مجموعة ال data ال 6 اللي انا بدي ادرب عليها
+
+492
+00:40:10,620 --> 00:40:14,640
+النظام او اللي بدي حللها النظام بحيث انه ياخد منها
+
+493
+00:40:14,640 --> 00:40:19,910
+يستخلص ال model منها بسميها ال trainingset بسميها
+
+494
+00:40:19,910 --> 00:40:26,410
+ال training set دكتور نعم ال training set كلمة
+
+495
+00:40:26,410 --> 00:40:30,110
+بتعمل ال model بنقل عليها لإن كل واحد مثلا فواجب
+
+496
+00:40:30,110 --> 00:40:33,350
+مخل تلقى ال training set من خمسين ألف دورة مش
+
+497
+00:40:33,350 --> 00:40:36,170
+هتبقى ال model مثلا زي ما سيكت في سبوك أو أمازونة
+
+498
+00:40:36,170 --> 00:40:38,530
+بتبني او ال training set دي ال model طب ما احنا
+
+499
+00:40:38,530 --> 00:40:40,970
+جولنا مين جابلنا هيك هيقولنا كل ما كبرت ال
+
+500
+00:40:40,970 --> 00:40:44,610
+training data set تبعتي بكون فرصة ال prediction
+
+501
+00:40:44,610 --> 00:40:48,570
+تبعتي انها تكون أدق أعلىكيف الاسم يعني؟ مثلا خمسين
+
+502
+00:40:48,570 --> 00:40:53,690
+ألف raw شوف لأ لأ شوية انت عندك ال data set كلها
+
+503
+00:40:53,690 --> 00:40:57,410
+خمسين ألف raw و بدك تعمل training ع تلاتين ألف raw
+
+504
+00:40:57,410 --> 00:41:01,370
+مثلا مش كافي لإن عادة جماعة التلخير ال rows
+
+505
+00:41:01,370 --> 00:41:04,990
+المستخدمة أو الحجم لل training set بيكون أكبر من
+
+506
+00:41:04,990 --> 00:41:08,320
+ال testing setيعني الآن إذا بتقدر تعمل training
+
+507
+00:41:08,320 --> 00:41:11,160
+على كل ال data و تختبره في data مختلفة بيكون ممتاز
+
+508
+00:41:11,160 --> 00:41:15,060
+عشان هيك كنا في ال data preparation نأكد هل في
+
+509
+00:41:15,060 --> 00:41:19,160
+مصادر أخرى للبيانات عندك ولا مافيش و جديش حجمها،
+
+510
+00:41:19,160 --> 00:41:22,540
+طبعا؟ الآن إذا أنت لاحظت في أخر assignment أو في
+
+511
+00:41:22,540 --> 00:41:25,720
+ال assignment الأخير مطلوب منك، أخر band اجسم ال
+
+512
+00:41:25,720 --> 00:41:31,500
+data set اللي عندك 70% لل training set و 30% لل
+
+513
+00:41:31,500 --> 00:41:35,380
+test setمصبوط وهذه التسأل ليش؟ لأنه مابديش إياك
+
+514
+00:41:35,380 --> 00:41:38,980
+تدرب كل .. تدربه على نفس .. يعني على نفس ال data و
+
+515
+00:41:38,980 --> 00:41:42,820
+بعدين أجي أحترمه لإن كيف بدي أختبره أو بدي أفحص
+
+516
+00:41:42,820 --> 00:41:48,280
+مدى دقة العنصر كمان مرة يا جماعة الخير بنأكد كل ما
+
+517
+00:41:48,280 --> 00:41:53,800
+كانت ال data set أكبر ال training set أكبر المفروض
+
+518
+00:41:53,800 --> 00:41:56,860
+أن كل ما تكون ال data أو خلنا نقول ال knowledge
+
+519
+00:41:56,860 --> 00:42:02,120
+تبعتي أدقالـ classification تبعتي بتصير أداء لكن
+
+520
+00:42:02,120 --> 00:42:05,220
+برضه مش منطق أن يكون انا في عندى اتنين مليار
+
+521
+00:42:05,220 --> 00:42:10,800
+record تمام؟ وانا بتروح بتقبج عليهم كلهم عملية ال
+
+522
+00:42:10,800 --> 00:42:13,940
+training بحد ذاتها هذه هتصير تاخد مني أشهر لما
+
+523
+00:42:13,940 --> 00:42:17,360
+تنتهي فبتصير ممكن ال task اللي أنا بأشتغل عليها
+
+524
+00:42:17,360 --> 00:42:24,370
+أساسا خلصت بطللها قيمة فانت برضه بتوازن ما بينالـ
+
+525
+00:42:24,370 --> 00:42:28,310
+accuracy تبع النظام و عامل الوقت أو ال performance
+
+526
+00:42:28,310 --> 00:42:34,610
+تبع ال training جدّيش بيحقق نتائج في
+
+527
+00:42:34,610 --> 00:42:40,110
+ال data set اللي موجود عندنا هان الان هاي عندى ال
+
+528
+00:42:40,110 --> 00:42:44,610
+data set ال name ال rank ال years اترجى ولا
+
+529
+00:42:44,610 --> 00:42:48,830
+مايترجاش اتقعد
+
+530
+00:42:48,830 --> 00:42:54,450
+ولا مايتقعدشنريح ولا ما نريحوش لأن هاي ال class
+
+531
+00:42:54,450 --> 00:42:58,890
+اللي عندي yes و no فاروح أعمل التحليل لل data set
+
+532
+00:42:58,890 --> 00:43:04,410
+اللي موجودة وكان مفاده إنه ال algorithm راح أداني
+
+533
+00:43:04,410 --> 00:43:09,590
+classifier model prediction model لل class لميه
+
+534
+00:43:09,590 --> 00:43:13,910
+ممكن أختار؟ ل yes و no بحيث إنه أنا لو زودت بال
+
+535
+00:43:13,910 --> 00:43:20,750
+rank وعدد سنوات الخبرةيدّين ال label اللي موجود
+
+536
+00:43:20,750 --> 00:43:27,890
+فجال ال model تبعي هو عبارة عن if then rule لو كان
+
+537
+00:43:27,890 --> 00:43:31,890
+ال rank professor وال year أكبر أو يساوي 6 أكبر من
+
+538
+00:43:31,890 --> 00:43:42,910
+6 معناته نرجّي تمام المرحلة التانية ال model usage
+
+539
+00:43:42,910 --> 00:43:48,060
+بالملاحظة يا شبابالـ classification algorithm أنا
+
+540
+00:43:48,060 --> 00:43:55,280
+هان غالبا .. غالبا يشتغل فعليا as a black box يعني
+
+541
+00:43:55,280 --> 00:43:58,980
+هدي ال input و أخد منه ال output اللي هو ال model
+
+542
+00:43:58,980 --> 00:44:03,300
+إيش اللي بيصير .. إيش اللي بيصير؟ غالبا مش كل
+
+543
+00:44:03,300 --> 00:44:06,820
+الناس المعنية فيهم بس أنا بالمساك هذا هدخل بتفاصيل
+
+544
+00:44:06,820 --> 00:44:11,240
+عشان أعرف فعليا ال classifier كيف اشتغل تمام؟ لكن
+
+545
+00:44:11,240 --> 00:44:15,730
+في بعض ال classifiersمش هنكون او مش هنتطرق لها
+
+546
+00:44:15,730 --> 00:44:22,230
+بالشغل تبعتها بمجرد ان ال classifier انبنى بده
+
+547
+00:44:22,230 --> 00:44:25,630
+اروح اطبقه او بده اروح استخدمه ال model هذا الآن
+
+548
+00:44:25,630 --> 00:44:32,150
+بيصير قابل للاستخدام فيش
+
+549
+00:44:32,150 --> 00:44:38,150
+بده استخدمه؟ يعمل classifying لمين؟ لل feature، ل
+
+550
+00:44:38,150 --> 00:44:41,810
+future او ال unknown objects
+
+551
+00:44:43,140 --> 00:44:46,840
+بالمثال تابعني السابق هذا أنا صار فيه عندى Jeff
+
+552
+00:44:46,840 --> 00:44:53,200
+professor و 4 سنوات الاسم neglected مش هعتبره لإن
+
+553
+00:44:53,200 --> 00:44:58,660
+ال role تبعي مبني على ال rank و ال years و بناء
+
+554
+00:44:58,660 --> 00:45:03,480
+عليه أنا بدي أخد القرار كان بيقول لي if ال rank
+
+555
+00:45:03,480 --> 00:45:07,280
+equal
+
+556
+00:45:07,280 --> 00:45:17,370
+of or ال years أكبر من 6then yes مظبوط هاي ال role
+
+557
+00:45:17,370 --> 00:45:23,110
+تبعي هاي ال model تبعي الآن هاي ال data اللي عندى
+
+558
+00:45:23,110 --> 00:45:26,710
+حقق عليها بطبقها مباشرة باخد ال instances و بطبق
+
+559
+00:45:26,710 --> 00:45:30,250
+ال instance value و بطبق عليها هان و باخد القرار
+
+560
+00:45:30,250 --> 00:45:37,070
+تبع لل role اللي موجود عندى طيب
+
+561
+00:45:37,070 --> 00:45:40,690
+لو ماكانش ماكانش professor كان assistant professor
+
+562
+00:45:40,690 --> 00:45:47,550
+و 5 سنواتNo مع ال else مباشرة مع ال else مباشرة
+
+563
+00:45:47,550 --> 00:45:54,150
+الارجل مع الخير معناته انا بحاجة في مرحلتين عشان
+
+564
+00:45:54,150 --> 00:45:56,690
+اشتغل مع ال classifier بحاجة اشتغل على مرحلتين
+
+565
+00:45:56,690 --> 00:46:00,550
+المرحلة الأولى اللي هي ال model construction
+
+566
+00:46:00,550 --> 00:46:05,770
+وبيلزمني data عشان ادرب ال model عليها بين جثين
+
+567
+00:46:05,770 --> 00:46:08,710
+بلزمني data عشان ال system او ال learning
+
+568
+00:46:08,710 --> 00:46:14,230
+algorithm يحللها ويبني model بناء عليهاالشغلة
+
+569
+00:46:14,230 --> 00:46:19,450
+التانية انه انا بدي افحص ال model او بدي استخدم ال
+
+570
+00:46:19,450 --> 00:46:22,830
+model في ال prediction وهي بنسميها احنا المرحلة
+
+571
+00:46:22,830 --> 00:46:26,630
+مرحلة ال testing او ال test فانا بدي اجسم ال data
+
+572
+00:46:26,630 --> 00:46:33,130
+set تبعتي لل training set و
+
+573
+00:46:33,130 --> 00:46:40,340
+test set ليش؟ عشان لما انا احصل على modelعشان لما
+
+574
+00:46:40,340 --> 00:46:43,460
+أحصل على model كيف بدي أتعرف إن ال model هذا شغال
+
+575
+00:46:43,460 --> 00:46:48,200
+كويس ولا لأ؟ بدي إنه النتيجة المطلوبة ولا بشتغل من
+
+576
+00:46:48,200 --> 00:46:54,880
+رأسه؟ فبدي أعمله evaluation طيب evaluation how did
+
+577
+00:46:54,880 --> 00:47:00,380
+that test set؟ هو الأصل هي unseen data، مصبوط؟
+
+578
+00:47:00,380 --> 00:47:05,760
+فعليا unseen، ماشفهاش، بس دي فيها label، حخف ال
+
+579
+00:47:05,760 --> 00:47:10,620
+label عنه، عشان أقدر إيش؟أقارن بين النتيجة اللي هو
+
+580
+00:47:10,620 --> 00:47:16,080
+هيقين إياها والنتيجة اللي هحصل عليها وانا بدي أسأل
+
+581
+00:47:16,080 --> 00:47:25,980
+سؤال هل ال test set labelled set؟ في مرحلة ال
+
+582
+00:47:25,980 --> 00:47:33,160
+evaluation هل ال test set labelled set؟ طيب، الآن
+
+583
+00:47:33,160 --> 00:47:34,100
+أنا جديد كتبت
+
+584
+00:47:36,780 --> 00:47:43,060
+الـ body mass index point تلاتة سبعة والـ chest
+
+585
+00:47:43,060 --> 00:47:52,020
+pain yes تصلب شرايين Blocked Artery yes قال لي هذا
+
+586
+00:47:52,020 --> 00:47:57,720
+heart disease هذا الأصل اللي نعملها prediction صح؟
+
+587
+00:47:57,720 --> 00:48:06,090
+أنا أخدتها على عليتها هيك قال لي noبتقدر تقول عن
+
+588
+00:48:06,090 --> 00:48:09,430
+ال prediction بتاعته صح ولا غلط؟ بتقدر تعمل
+
+589
+00:48:09,430 --> 00:48:16,590
+evaluation لإلها؟ بتقارنها بإيش؟ بال level الأصلي
+
+590
+00:48:16,590 --> 00:48:21,930
+فعشان هيك ال test set must be label عشان هيك بعد
+
+591
+00:48:21,930 --> 00:48:24,470
+ما انت خلصت عملت processing في ال assignment
+
+592
+00:48:24,470 --> 00:48:29,890
+وقلتلك اجسم اجسم ال data set لجزءين جزء ال
+
+593
+00:48:29,890 --> 00:48:35,340
+trainingوجزء Testing بس اللي هيصير فعلياً لما أصل
+
+594
+00:48:35,340 --> 00:48:40,820
+مرحلة ال evaluation هخب ال test او هخب ال label
+
+595
+00:48:40,820 --> 00:48:45,780
+تبعت مين تبعت ال test set عشان اقول اتفضل هاي
+
+596
+00:48:45,780 --> 00:48:49,640
+unseen ده تعملهم prediction فبديني مجموعة ال
+
+597
+00:48:49,640 --> 00:48:53,160
+labels اللي predicted وعندي ال original او ال true
+
+598
+00:48:53,160 --> 00:48:58,320
+labelled بصير اقارن و بقدر اتكلم انه جديش هذا ال
+
+599
+00:48:58,320 --> 00:48:59,180
+model تبعي accurate
+
+600
+00:49:03,990 --> 00:49:08,470
+أه، الآن أحمد بيسأل، بيقول هل بقدر أروح أرجع ال
+
+601
+00:49:08,470 --> 00:49:11,830
+data test set هذه و أوديها على ال training عشان
+
+602
+00:49:11,830 --> 00:49:17,350
+يتعلم من أخطائه؟ انت already علمته و كمان لو انت
+
+603
+00:49:17,350 --> 00:49:21,270
+روحت أخدته، يعني هيك، من وين بدك تختبره بعد هيك؟
+
+604
+00:49:21,270 --> 00:49:25,130
+بدك تجيبله data set شديدة، طب ليش مش من نفس ال
+
+605
+00:49:25,130 --> 00:49:30,450
+data set؟ لأن already هو شافها، تمام من الشباب،
+
+606
+00:49:30,450 --> 00:49:37,330
+بينفعش أنا آجيأديك الامتحان و اقولك اتفضل حلو تمام
+
+607
+00:49:37,330 --> 00:49:42,530
+و بكرا بدي اختبرك فيها في الأسئلة هاي ما أصبحاش
+
+608
+00:49:42,530 --> 00:49:50,370
+امتحان ولا أصبح امتحان امتحان مسرب اه فش يعني عفوا
+
+609
+00:49:50,370 --> 00:49:53,550
+كلكوا هتنجحوا مصبوط الأصل كده و اللي بديهوش ينجح
+
+610
+00:49:53,550 --> 00:49:58,570
+يتطخدك الساعة بيكون بس فعليا هل النجاح هذا حقيقي؟
+
+611
+00:49:58,570 --> 00:50:04,890
+لأ الحاجات هذا fake النجاح هذا fakeأما احنا قلنا
+
+612
+00:50:04,890 --> 00:50:09,390
+الفكرة وين ان بعد ما انا جسمت هان في مرحلة ال
+
+613
+00:50:09,390 --> 00:50:14,890
+evaluation مش بده يشوف .. بده يشوف ال .. بيشوف هو
+
+614
+00:50:14,890 --> 00:50:19,370
+اجتيش .. لأ بده يشوف ال .. ال .. ال .. ال .. ال
+
+615
+00:50:19,370 --> 00:50:24,670
+rock دي قارن فوق هيو .. هذه .. هذه .. بده يقارن
+
+616
+00:50:24,670 --> 00:50:30,690
+هذهلأ ومش قارنها مع اللي فوق هو على ال model بناء
+
+617
+00:50:30,690 --> 00:50:33,950
+على ال equation اللي انكتبت يعني مثلا هدولة أربع
+
+618
+00:50:33,950 --> 00:50:37,470
+attributes أو three attributes A1, A2, A3 ومع ال
+
+619
+00:50:37,470 --> 00:50:41,670
+label بدي أفترض أنا جدلا ان ال model تبعي هو عبارة
+
+620
+00:50:41,670 --> 00:50:52,330
+عن ال Y بيذهب تساوي M1 في A1 زائد M2 في A2 زائد M3
+
+621
+00:50:52,330 --> 00:51:03,080
+في A3زائد الـ B مش هذا AI الموديل اللي بتعالج
+
+622
+00:51:03,080 --> 00:51:06,480
+أولادي؟ اه هي جزء من ال AI ال machine learning جزء
+
+623
+00:51:06,480 --> 00:51:11,100
+من ال AI يعني اذا ما بنعملش كود بسيط انا ماقلتش
+
+624
+00:51:11,100 --> 00:51:15,140
+كود بسيط انا حاول توصلك صورة ال model كيه بده يكون
+
+625
+00:51:15,140 --> 00:51:19,580
+بس الآن ال model اللي بتكلم عليه يا راني هيهالـ
+
+626
+00:51:19,580 --> 00:51:24,160
+system فعليا بعد ما درس كل ال training data راح
+
+627
+00:51:24,160 --> 00:51:30,260
+قال لي M1 هذه قيمتها point 17 من 100 زائد هذه
+
+628
+00:51:30,260 --> 00:51:41,360
+قيمتها 73 و هذه قيمتها point 0.5 و ال B point 882
+
+629
+00:51:41,360 --> 00:51:46,380
+مثلا ايش بيظل عندي قيمة ال attributes هيها موجودة
+
+630
+00:51:47,610 --> 00:51:50,150
+مصبوط؟ فباخد قيمة الـ attributes و بضربها في القيم
+
+631
+00:51:50,150 --> 00:51:53,530
+اللي موجودة و بجمعهم بناءً على ال Y اللي أنا حصلت
+
+632
+00:51:53,530 --> 00:51:58,870
+عليها ال Y الأصل تكون مين؟ ال class فبدي أقارن ال
+
+633
+00:51:58,870 --> 00:52:04,950
+predicted class ال predicted Y مع ال actual Y ال
+
+634
+00:52:04,950 --> 00:52:08,070
+actual label اللي موجودة عندي اللي أنا خفيتها في
+
+635
+00:52:08,070 --> 00:52:12,670
+مرحلة ال evaluation يعني انتجيها بعد .. اه بعد ما
+
+636
+00:52:12,670 --> 00:52:15,530
+يقيم يعني انت الآن بتشوف .. حل الأسئلة بتاعة
+
+637
+00:52:15,530 --> 00:52:24,940
+الامتحان قبل ولا بعد؟بعد؟ goal طب كيف و بطل ليش؟
+
+638
+00:52:24,940 --> 00:52:29,760
+ايه
+
+639
+00:52:29,760 --> 00:52:33,180
+كانت بتتعلم، ماتجلجش حضرت ال data set اللي عليك
+
+640
+00:52:33,180 --> 00:52:39,400
+المهم؟ أكيد و عملت pre processing تمام؟
+
+641
+00:52:39,400 --> 00:52:43,880
+لأ انت هتستخدم ال AI يعني هتستخدم ال machine
+
+642
+00:52:43,880 --> 00:52:48,520
+learning بس هتفهم ال model كيف بيشتغلتمام؟ انت مش
+
+643
+00:52:48,520 --> 00:52:53,500
+مجرد .. انت مش طالب طب ولا طالب جيغرافيا ان علمك
+
+644
+00:52:53,500 --> 00:52:57,140
+هى ال algorithm هى ال input هى ال output و بتستخدم
+
+645
+00:52:57,140 --> 00:53:00,120
+ال output بتخدمه بالشكل هذا لأ ال algorithm نفسه
+
+646
+00:53:00,120 --> 00:53:03,100
+كيف يشتغل بالتحليل لإنك انت طالب computer science
+
+647
+00:53:03,100 --> 00:53:08,280
+أو تطوير برمجيات سنة تالتة ولا رابعة؟ واش دخل؟ حد
+
+648
+00:53:08,280 --> 00:53:14,740
+قالك تسجل المساق ال accuracyلحظة أنا ما زلت بتكلم
+
+649
+00:53:14,740 --> 00:53:17,940
+في ال basic components أو في ال basic concept تبع
+
+650
+00:53:17,940 --> 00:53:21,440
+ال classification ال accuracy لما بتكلم على ال
+
+651
+00:53:21,440 --> 00:53:27,480
+accuracy بتكلم على دقة النظام بتكلم على قدرة
+
+652
+00:53:27,480 --> 00:53:32,700
+النظام على ال prediction الصحيح وبالتحديد ال
+
+653
+00:53:32,700 --> 00:53:38,900
+accuracy هي عبارة عن ratio بين ال prediction
+
+654
+00:53:38,900 --> 00:53:44,200
+الصحيحة على كل predictionsعدد ال prediction المرات
+
+655
+00:53:44,200 --> 00:53:49,800
+التنبؤ الصحيح على كل حالات التنبؤ اللي تمت عندى
+
+656
+00:53:49,800 --> 00:53:53,460
+كيف يعنى؟ أنا عندى ال test set كان فيها عشرة
+
+657
+00:53:53,460 --> 00:53:59,620
+instances لما قلت للموضل اعمل ال prediction لهدول
+
+658
+00:53:59,620 --> 00:54:06,720
+جاب سبعة منهم صح معناته ال Accuracy سبعة على عشرة
+
+659
+00:54:06,720 --> 00:54:11,590
+اللي هي 70% من النظام اللي موجود عندى هناكمان مرة
+
+660
+00:54:11,590 --> 00:54:16,510
+الـ Accuracy هي قدرة الـ Classifier على التنبؤ
+
+661
+00:54:16,510 --> 00:54:22,030
+بشكل صحيح للـ Unseen Data لو الـ Data Scene هدى و
+
+662
+00:54:22,030 --> 00:54:28,550
+هدى مابتنعدلوش الـ Speed لما أتكلم عن الـ Speed
+
+663
+00:54:28,550 --> 00:54:32,650
+بتتكلم على الـ Computational Cost اللي بده يكلفني
+
+664
+00:54:32,650 --> 00:54:39,570
+إياها الـ Algorithm في مرحلة الـ Generation إنشاء
+
+665
+00:54:39,570 --> 00:54:46,580
+الموديلتمام؟ ومرحلة استخدام ال classifier يعني أنا
+
+666
+00:54:46,580 --> 00:54:50,140
+عندي مرحلتين في عندي مش كله ال model construction
+
+667
+00:54:50,140 --> 00:54:57,620
+وعندي ال model usage الآن كل واحدة منهم في لها
+
+668
+00:54:57,620 --> 00:55:02,060
+تكلفة تكلفة لل training و تكلفة لل prediction جديش
+
+669
+00:55:02,060 --> 00:55:06,660
+computational جديش أنا مهتم بسرعة النظام يعني الآن
+
+670
+00:55:06,660 --> 00:55:12,010
+مثلابدنا نظام الآن .. محتاجين نظام سريع يحاول
+
+671
+00:55:12,010 --> 00:55:15,610
+يتنبأ ان المريض هذا اللي مش .. منضيق في الصدر أو
+
+672
+00:55:15,610 --> 00:55:19,530
+في صعوبة في التنفس مصاب بـ Corona ولا لأ؟ انت ..
+
+673
+00:55:19,530 --> 00:55:22,550
+انت .. انت خبير .. خبير الصين أصلا .. انت عشان ايه
+
+674
+00:55:22,550 --> 00:55:27,730
+قولت Corona مباشرة، تمام؟ الآن الفكرة وين؟ انه أنا
+
+675
+00:55:27,730 --> 00:55:31,710
+جداش بأقدر أعمل training ل model .. a curated
+
+676
+00:55:31,710 --> 00:55:37,450
+model بشكل سريع، بكوني كويس إليهليش؟ لأنه أنا
+
+677
+00:55:37,450 --> 00:55:42,050
+فعليا .. الآن أنا محتاجه يمكن بكرا محتاجوش فالآن
+
+678
+00:55:42,050 --> 00:55:46,410
+هذي بتفرج معايا ال performance في مرحلة ال
+
+679
+00:55:46,410 --> 00:55:52,490
+generation ال using في ال prediction أنه لما أزوده
+
+680
+00:55:52,490 --> 00:55:56,230
+بالعينة اللي المفروض يعمل عليها prediction أو يقيم
+
+681
+00:55:56,230 --> 00:56:01,150
+يعملها evaluation جداش بده وقت في بده ثانية،
+
+682
+00:56:01,150 --> 00:56:06,630
+تنتين، تلاتة، عشرة، كل مكان أسرعيكون أحسن في الـ
+
+683
+00:56:06,630 --> 00:56:10,670
+real-time system الآن في عندنا جسم بتحرك في الجو
+
+684
+00:56:10,670 --> 00:56:16,350
+بسرعة 100 كيلومتر في الساعة طيارة،
+
+685
+00:56:16,350 --> 00:56:23,350
+صاروخ، قذيفة، غراب، مش عارفين في الأنظمة الدفاعية
+
+686
+00:56:23,350 --> 00:56:26,710
+بتفرج الآن هذا الجسم اللي بتحرك في الـ real-time
+
+687
+00:56:26,710 --> 00:56:31,630
+system تمام؟ بناء على سرعته وحجمه
+
+688
+00:56:33,360 --> 00:56:36,620
+بدهم ياخدوا قرار اللي غالبا ما ببينش بدهم ياخدوا
+
+689
+00:56:36,620 --> 00:56:41,160
+قرار شو ده بيكون افعل صفرات الإنذار ولا لأ الإنذار
+
+690
+00:56:41,160 --> 00:56:51,780
+ولا لأ احنا
+
+691
+00:56:51,780 --> 00:56:57,200
+قولنا حمامة شكله زادة مع البس خلاص و هي طايرة
+
+692
+00:56:58,620 --> 00:57:02,060
+الفكرة يا جماعة الخير اللي انا بده اوصلك هي إذا
+
+693
+00:57:02,060 --> 00:57:06,940
+ماكنتش مرحلة ل prediction سريعة تفقدت الأهمية
+
+694
+00:57:06,940 --> 00:57:11,060
+تبعتها فضل يا دكتور قبل لما راحيت على المرض أكيد
+
+695
+00:57:11,060 --> 00:57:16,080
+فعلا مش هيكون مثلا بدنا نتنبأ أنه فيه مثلا .. لو
+
+696
+00:57:16,080 --> 00:57:19,800
+مثلا افتراض مثلا علشان هنا يعني محتمال يكون فيه
+
+697
+00:57:19,800 --> 00:57:23,100
+نسبة خطأ فاحنا على وجه السرعة مش هيكون بدنا نتنبأ
+
+698
+00:57:23,100 --> 00:57:28,190
+بدنا يعني ..طب انت عملك بتقول انا المرض هذا فعليا
+
+699
+00:57:28,190 --> 00:57:34,070
+مش جادر اشخصه او في عندهم صعوبة في تشخيصه فقط
+
+700
+00:57:34,070 --> 00:57:37,930
+طب المفلوز العادي او اللي عنده احتقان في زوره
+
+701
+00:57:37,930 --> 00:57:41,890
+ابترت فيه درجة حرارته واحد زي حالتي بيكون قاعد
+
+702
+00:57:41,890 --> 00:57:44,950
+بيشرح و بيطلع واحد غد بيقوله بسة طايرة ابترت فيه
+
+703
+00:57:44,950 --> 00:57:45,450
+حرارته
+
+704
+00:57:49,260 --> 00:57:53,380
+تمام؟ بالفكرة يا هاب لأ okay أنا بدي .. بدي system
+
+705
+00:57:53,380 --> 00:57:57,500
+يكون سريع عفوا بدي أصل ل model بشكل سريع بعض ال
+
+706
+00:57:57,500 --> 00:58:02,240
+models بتاخد أيام و أشهر هى بتعمل ال training صح
+
+707
+00:58:02,240 --> 00:58:06,460
+بيكون هذا دقيق الشغل صحيح لكن أنا برضه حسب الحالة
+
+708
+00:58:06,460 --> 00:58:11,480
+اللى أنا بدي أشتغل عليها نعم لأ
+
+709
+00:58:11,480 --> 00:58:16,460
+للأسف data preparation هل تحسب ضمن ال time cost لأ
+
+710
+00:58:17,850 --> 00:58:21,290
+لأن هنا بنتكلم احنا على الـ computational cost كل
+
+711
+00:58:21,290 --> 00:58:27,670
+اللي انت سويته قبل مجرد تجهيز لعملية ال mining
+
+712
+00:58:27,670 --> 00:58:33,330
+أكيد كل ما زاد حجم ال data زاد حجم ال computation
+
+713
+00:58:33,330 --> 00:58:37,790
+بال training وال testing الآن ال data set تبعتي
+
+714
+00:58:37,790 --> 00:58:42,870
+مكونة من عشرة attributes هل ال computation تبعتها
+
+715
+00:58:42,870 --> 00:58:49,260
+زي ما يكون عندي 100 attributesحتما لأ يعني عشر
+
+716
+00:58:49,260 --> 00:58:54,620
+متغيرات زي مين متغير اكيد لأ جداش ال robustness او
+
+717
+00:58:54,620 --> 00:58:58,200
+الموثوقية جداش ال system هذا بتديني accurate
+
+718
+00:58:58,200 --> 00:59:03,680
+result في حالة ال noise data ال noise instance او
+
+719
+00:59:03,680 --> 00:59:06,960
+في حالة وجود ال missing values الان احنا قبل شوية
+
+720
+00:59:06,960 --> 00:59:10,740
+اتكلمت على تلت عناصر عشان ال heart disease ال body
+
+721
+00:59:10,740 --> 00:59:16,000
+mass index وال chest pain وتصلب الشراينالآن لو
+
+722
+00:59:16,000 --> 00:59:18,880
+عندي تنتين منهم فقط بيقدر الـ system يديني
+
+723
+00:59:18,880 --> 00:59:23,360
+prediction؟ لأ، ما تقوليش لأ، انت ما تشكشكش لأ ال
+
+724
+00:59:23,360 --> 00:59:26,380
+system هيديكي prediction هيديكي prediction بس اللي
+
+725
+00:59:26,380 --> 00:59:29,900
+أنا بدور عليه هل بيقدر يديني prediction صحيح؟ إذا
+
+726
+00:59:29,900 --> 00:59:33,360
+بيديني prediction صحيح معناته هذا more robust أكتر
+
+727
+00:59:33,360 --> 00:59:38,300
+موثوقية ليش؟ لأن في حالة إن أنا فقدت واحد من ال
+
+728
+00:59:38,300 --> 00:59:41,440
+attributes اللي موجودة بضل جادر أعتمد عليه عشان
+
+729
+00:59:41,440 --> 00:59:46,050
+يعمل prediction تمام؟الآن في حالة كان في عندي
+
+730
+00:59:46,050 --> 00:59:49,710
+noise data نفس النظام بالمناسبة يا حسن احنا عادة
+
+731
+00:59:49,710 --> 00:59:53,490
+اللي بنتكلم فعليا هذا المثال اللي بدكره تلاتة عشان
+
+732
+00:59:53,490 --> 00:59:57,870
+بس نستوعب الاشي اللي بيصير و نفهم فعليا كل ال
+
+733
+00:59:57,870 --> 01:00:02,730
+concept بشكل واضح لكن فعليا لو أنا سألتك أبسط
+
+734
+01:00:02,730 --> 01:00:05,710
+اختبار ممكن يجري الإنسان اللي له علاقة بصحته ال
+
+735
+01:00:05,710 --> 01:00:13,270
+CBC كام factor فيه؟ 15 أنصر أعتقد أو 14يعني بتكلم
+
+736
+01:00:13,270 --> 01:00:16,450
+على الأقل 14 attributes اللي هو ال test ال
+
+737
+01:00:16,450 --> 01:00:21,870
+complete blood test تمام؟ فبتكلم على 14 attributes
+
+738
+01:00:21,870 --> 01:00:25,730
+لكل عينة الآن لو في واحدة عينة فيها مشكلة في ال
+
+739
+01:00:25,730 --> 01:00:30,750
+noise أو value معينة لأ لأ مش ضروري فالآن لو جديش
+
+740
+01:00:30,750 --> 01:00:34,630
+الآن الطبيب الحاذق ممكن بيقدر يقارن شغلات مع بعضها
+
+741
+01:00:34,630 --> 01:00:38,210
+ويقولك لأ في مشكلة يعني واضح الجهاز ان في مشكلةهذه
+
+742
+01:00:38,210 --> 01:00:42,450
+الفكرة وين إن الـ system لو غاب في عندي value أو
+
+743
+01:00:42,450 --> 01:00:46,170
+تشوشت value من الأربع عشر يكون عنده القدرة على
+
+744
+01:00:46,170 --> 01:00:50,410
+التنبؤ الصحيح أي واحدة من الأربع عشر ده مابتعنناش
+
+745
+01:00:50,410 --> 01:00:54,870
+بس في اللحظة اللي بيجيني ال attribute عفوا بيجيني
+
+746
+01:00:54,870 --> 01:00:58,610
+ال rows ال raw with missing value أو with noisy
+
+747
+01:00:58,610 --> 01:01:02,350
+data الأصل يعمل prediction هيعمل prediction في كل
+
+748
+01:01:02,350 --> 01:01:07,320
+الأحوال كل مكان بديني accurateالـ prediction في
+
+749
+01:01:07,320 --> 01:01:11,300
+الـ such case هذه معناته هذا مرة بسط بقدر أثق فيه
+
+750
+01:01:11,300 --> 01:01:18,880
+أكتر تمام ال scalability ال scalability طبعا دائما
+
+751
+01:01:18,880 --> 01:01:23,740
+احنا مفهوم ال scalability بنتكلم على ال large
+
+752
+01:01:23,740 --> 01:01:29,560
+amount of data فعليا هل ال algorithm هذا تبع ممكن
+
+753
+01:01:29,560 --> 01:01:35,000
+من السهل ان يتعامل معاه مع large dataالـ data set
+
+754
+01:01:35,000 --> 01:01:37,760
+اللي عندى مليون instances هل ال algorithm قادر على
+
+755
+01:01:37,760 --> 01:01:40,960
+تحليل مليون instances مع عشر .. مع عشر attributes
+
+756
+01:01:40,960 --> 01:01:44,100
+أو مع مائة attributes فهذا أنا بدي أسأله كل ما كان
+
+757
+01:01:44,100 --> 01:01:48,780
+ال algorithm اللي هستخدمه more scalable معناته
+
+758
+01:01:48,780 --> 01:01:54,420
+بكون أفضل interpretability تفسير و ال
+
+759
+01:01:54,420 --> 01:02:01,500
+understanding و فهم محتوى او ما وراهالـ Model أو
+
+760
+01:02:01,500 --> 01:02:04,840
+الـ Algorithm اللي عندي The level of understanding
+
+761
+01:02:04,840 --> 01:02:10,000
+and insight والمفهوم أو التوضيح أو المعنى الخفي من
+
+762
+01:02:10,000 --> 01:02:14,200
+Provided by the classifier احنا قبل شوية لما شوفنا
+
+763
+01:02:14,200 --> 01:02:18,000
+ال if then كان بسهولة ان افهم عليهش بدور ايش ال
+
+764
+01:02:18,000 --> 01:02:21,720
+factors الأساسية اللي كانت مصبوط؟ لو هذا ال if
+
+765
+01:02:21,720 --> 01:02:25,040
+then ماكنتش موجودة بقدر استوعب ليش هو جداني yes و
+
+766
+01:02:25,040 --> 01:02:29,140
+جداني no؟أكيد لأ لكن لما بكون ال algorithm قدامي
+
+767
+01:02:29,140 --> 01:02:34,820
+قادر أو بقدر او قادر على تفسيره بكون افضل لكن
+
+768
+01:02:34,820 --> 01:02:39,980
+الصحيح الموضوع برضه تفسيره هذي subjective للإنسان
+
+769
+01:02:39,980 --> 01:02:42,780
+او للشخص اللي بشتغل عليه لما أنا كتبنا كتبنا
+
+770
+01:02:42,780 --> 01:02:50,140
+المعادلة الرياضية Y تساوي M1 في A1 زائد M2 في A2
+
+771
+01:02:50,140 --> 01:02:51,440
+زائد B
+
+772
+01:02:55,220 --> 01:02:59,920
+إيش رتبة .. إيش درجة المعادلة هي شباب؟ إيش رتبة
+
+773
+01:02:59,920 --> 01:03:07,980
+المعادلة هي شباب؟ معادلة خطية لأنه الدرجة تقاسب
+
+774
+01:03:07,980 --> 01:03:12,840
+أعلى أُس الدرجة أو رتبة المعادلة تقاسب أعلى أُس
+
+775
+01:03:12,840 --> 01:03:18,000
+فالمعادلة هي خطية بس فعليا هذه multiple variable
+
+776
+01:03:18,000 --> 01:03:25,480
+متغيرات اتنين مع ال Y يعني بين قسين الـ3D3D
+
+777
+01:03:25,480 --> 01:03:30,840
+equation، مصبوط؟ هي .. هي الفكرة، الآن مش كل الناس
+
+778
+01:03:30,840 --> 01:03:35,740
+قادرة على تفسير .. هد يعرضها على واحد خبير رياضيات
+
+779
+01:03:35,740 --> 01:03:38,580
+مباشرة، بيقولك هد بتعني كده و واحد كده، بيجي و
+
+780
+01:03:38,580 --> 01:03:43,860
+بيقولك إن هذا plane مائل، plane، مسطح مائل، الميل
+
+781
+01:03:43,860 --> 01:03:51,450
+تبعه باتجاه X ومثلاًX و Y كذا X و Z كذا هي الأبعاد
+
+782
+01:03:51,450 --> 01:03:56,990
+تبعته و هذه ارتفاعه أو التقاطع تبعته مع ال Y axis
+
+783
+01:03:56,990 --> 01:04:02,270
+لكن أنا مش بعرفني بالكلام هذا فالموضوع ال
+
+784
+01:04:02,270 --> 01:04:07,130
+interpretability أو موضوع تفسير ال algorithm و
+
+785
+01:04:07,130 --> 01:04:12,550
+فهمه بيختلف من شخص لشخص من
+
+786
+01:04:12,550 --> 01:04:17,410
+ال algorithms اللي هنتعرف عليهاKey nearest
+
+787
+01:04:17,410 --> 01:04:21,490
+neighbor algorithm وهذا البرنامج يعتمد على
+
+788
+01:04:21,490 --> 01:04:22,550
+البرنامج الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة
+
+789
+01:04:22,550 --> 01:04:30,530
+الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة
+
+790
+01:04:30,530 --> 01:04:35,310
+الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة
+
+791
+01:04:35,310 --> 01:04:35,330
+الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة
+
+792
+01:04:35,330 --> 01:04:35,330
+الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة
+
+793
+01:04:35,330 --> 01:04:35,330
+الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة
+
+794
+01:04:35,330 --> 01:04:41,850
+الوثيقة الوثيقة الوثيقة الوثيقة الوثيقة
+
+795
+01:04:41,850 --> 01:04:47,070
+الووفي عند ال rule based induction وفي عند ال
+
+796
+01:04:47,070 --> 01:04:49,430
+support vector machine وفي عند ال logistic
+
+797
+01:04:49,430 --> 01:04:53,610
+regression كل هذه ال algorithm تستخدم في ال
+
+798
+01:04:53,610 --> 01:04:55,990
+classification وفي عند ال back up و ال propagate
+
+799
+01:04:55,990 --> 01:04:59,310
+neural network في الفصل هذا في الشابتر هذا ان شاء
+
+800
+01:04:59,310 --> 01:05:02,350
+الله تعالى هشرحلك ال k-nearest neighbor و ال naive
+
+801
+01:05:02,350 --> 01:05:05,170
+bison و ال decision tree و ال back up و ال
+
+802
+01:05:05,170 --> 01:05:09,650
+propagate neural network ك classifiers خلال الفصل
+
+803
+01:05:09,650 --> 01:05:14,360
+هذاأنا محاضرة اليوم هي كاد انتهيت
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/4I0vSe-ObqM_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/4I0vSe-ObqM_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..b14af1ed74713ce05d679f8bc032bac3a5f4a86b
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/4I0vSe-ObqM_raw.srt
@@ -0,0 +1,1724 @@
+1
+00:00:00,000 --> 00:00:02,260
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:02,260 --> 00:00:06,120
+أهلا وسهلا بكم في تكملة chapter الـ Protective
+
+3
+00:00:06,120 --> 00:00:09,040
+Modelling أو الـ Frequent Pattern كنا تكلمنا سابقا
+
+4
+00:00:09,040 --> 00:00:12,880
+على مفهوم الـ Quote للتسجيلات السابقة على مفهوم
+
+5
+00:00:12,880 --> 00:00:15,440
+الـ Frequent Pattern وشو ال association role
+
+6
+00:00:15,440 --> 00:00:17,440
+وتكلمنا على ال support و ال confidence as
+
+7
+00:00:17,440 --> 00:00:17,860
+measurement
+
+8
+00:00:20,590 --> 00:00:24,210
+تحديد قوة الـ association role الـ frequent better
+
+9
+00:00:24,210 --> 00:00:27,710
+واتكلمنا على الابريريو algorithm كواحد من أهم ال
+
+10
+00:00:27,710 --> 00:00:32,830
+algorithm في وجود ال .. أو في الوصول ل ال
+
+11
+00:00:32,830 --> 00:00:37,490
+association roles و لكن قلنا ان في عندنا مجموعة من
+
+12
+00:00:37,490 --> 00:00:42,280
+ال drawbacks على مستوى ال ..الـ Algorithm اللي
+
+13
+00:00:42,280 --> 00:00:45,140
+عندنا منها انه انا فعليا في عندى multiple scan
+
+14
+00:00:45,140 --> 00:00:47,200
+طبعا من ال drawbacks دي اللي علاقة كلها بال
+
+15
+00:00:47,200 --> 00:00:51,160
+computation انه بتزيد من التكلفة الزمنية او
+
+16
+00:00:51,160 --> 00:00:55,680
+الحسابية لل algorithm اللي موجود عندنا ال multiple
+
+17
+00:00:55,680 --> 00:00:59,680
+scan او عدد ال number of candidates و ببدأ من
+
+18
+00:00:59,680 --> 00:01:03,600
+candidate واحد و ببدأ يجمعهم وبالتالي كان العدد
+
+19
+00:01:03,600 --> 00:01:07,680
+كبير العمل الممل و تكراره في موضوع العدل حسبة ال
+
+20
+00:01:07,680 --> 00:01:17,030
+support اللي موجود عندناممكن نقل
+
+21
+00:01:17,030 --> 00:01:22,330
+العدد مرات القراءة لل database أو نقل العدد ال
+
+22
+00:01:22,330 --> 00:01:24,230
+candidates اللي موجودين عندنا
+
+23
+00:01:27,160 --> 00:01:32,420
+بنتكلم عن طريقة كيف نسرع فيها أو نحسن فيها موضوع
+
+24
+00:01:32,420 --> 00:01:36,760
+العدل ال candidates نحسب ال support ال candidates
+
+25
+00:01:36,760 --> 00:01:40,120
+اللي موجودة عندنا وبشكل عام ممكن يعتمد ال parallel
+
+26
+00:01:40,120 --> 00:01:48,700
+computing من أجل تسريع الدأ العملية بشكل عام الان
+
+27
+00:01:48,700 --> 00:01:53,340
+ان شاء الله تعالى هنتكلم عن الوقولنا واحدة من
+
+28
+00:01:53,340 --> 00:01:56,160
+الحلول المتاحة عندي انه انا بحاول اوشد اوجد ال
+
+29
+00:01:56,160 --> 00:01:59,640
+frequent pattern بدون ما يكون في عندي ال candidate
+
+30
+00:01:59,640 --> 00:02:03,540
+generation طبعا احنا الآن بس من باب التأكيد انه ال
+
+31
+00:02:03,540 --> 00:02:07,280
+bottleneck او الحلق اللي .. خلنا نقول نقطة الازحام
+
+32
+00:02:07,280 --> 00:02:10,580
+او الحلق الأضعف في ال a priori approach ان هو ال
+
+33
+00:02:10,580 --> 00:02:14,500
+bred first search ال bred first search عشان يا
+
+34
+00:02:14,500 --> 00:02:16,660
+معنى الخير هي مصطلحات مسمة موجودة في ال data
+
+35
+00:02:16,660 --> 00:02:20,520
+structure اذا كنا بنتذكرها ومقصود فيها انه انا
+
+36
+00:02:20,520 --> 00:02:24,220
+البحث بتم في ال level wiseأيش يعني في الـ Level
+
+37
+00:02:24,220 --> 00:02:30,340
+-wise؟ المبدأ هذا جاي من أن في عندي موضوع Tree بغض
+
+38
+00:02:30,340 --> 00:02:35,120
+النظر الـ Structure تبعت الـ Tree فلاحية أو ربعية
+
+39
+00:02:35,120 --> 00:02:39,480
+و الاخرين فمفهوم ال bred first ان انا باخد level
+
+40
+00:02:39,480 --> 00:02:42,820
+level و بنتقل على كل عناصر ال level بعدين بروح على
+
+41
+00:02:42,820 --> 00:02:46,060
+ال level التاني و بمشي فيه طبعا هذه ال approach
+
+42
+00:02:46,060 --> 00:02:49,060
+لأنه فعليا كان بيبني كل ال candidates اللي من C1
+
+43
+00:02:49,980 --> 00:02:53,420
+وبعد ذلك ننتقل لـ Candidate C2 من الـ two elements
+
+44
+00:02:53,420 --> 00:02:58,480
+و Candidate C3 و هكذا وهذا طبعا اللي فعليا اللي
+
+45
+00:02:58,480 --> 00:03:03,980
+بياخد مني وجه طويل جدا بينما ال .. ال .. ال F
+
+46
+00:03:03,980 --> 00:03:08,340
+growth أو ال frequent pattern growth approach اللي
+
+47
+00:03:08,340 --> 00:03:11,260
+انا بدي اشتغل بدون ما ادور على ال candidates بشتغل
+
+48
+00:03:11,260 --> 00:03:17,440
+على مبدأ ال depth first search انه دائما انزل أعمق
+
+49
+00:03:17,440 --> 00:03:23,200
+نقطة في ال tree تمام؟وبعدها تشوف النقطة الأعمق
+
+50
+00:03:23,200 --> 00:03:29,820
+ومساوية لها و هكذا لما حد تخلص لقريتك وبالتالي هان
+
+51
+00:03:29,820 --> 00:03:35,660
+احنا بيصير في عندي اكسب list of avoidance لموضوع
+
+52
+00:03:35,660 --> 00:03:38,660
+ال candidate generation يعني بيصير في عندي بشكل
+
+53
+00:03:38,660 --> 00:03:40,640
+تلقائي انه التجنب او
+
+54
+00:03:50,810 --> 00:03:55,110
+الاساسي المصطلح أو الفلسفة الأساسية اللى بنى عليها
+
+55
+00:03:55,110 --> 00:03:59,430
+ال candidate او ال FB Growth ان الـ long patterns
+
+56
+00:03:59,430 --> 00:04:05,200
+ممكن تبنى من short patternsاللي كانت الـ frequent
+
+57
+00:04:05,200 --> 00:04:10,500
+items only وعشان كل كلام هذا يعني بكل بساطة بقولك
+
+58
+00:04:10,500 --> 00:04:14,120
+انا لو كان في عندي مجموعة من ال short ال frequent
+
+59
+00:04:14,120 --> 00:04:17,200
+peters اللي هدول المجموعة ال short ممكن يكونوا
+
+60
+00:04:17,200 --> 00:04:20,780
+لواحد اكبر منهم long peters على سبيل المثال لو كان
+
+61
+00:04:20,780 --> 00:04:24,600
+في عندي ال ABC is a frequent peter في ال data set
+
+62
+00:04:24,600 --> 00:04:30,420
+اللي عندي معناه انت ممكن تروح تجيب كل ال peters او
+
+63
+00:04:30,420 --> 00:04:35,720
+ال transaction اللي بتحتوي علىالـ ADC مثلا لو كان
+
+64
+00:04:35,720 --> 00:04:39,800
+frequent يعني ان كل ال patterns اللي بتحتوي على ال
+
+65
+00:04:39,800 --> 00:04:44,000
+ADC هن بيقول ان لو كان في عندي كمان frequent كمان
+
+66
+00:04:44,000 --> 00:04:46,680
+في عندي local frequent pattern اخر D وليكن على
+
+67
+00:04:46,680 --> 00:04:51,800
+سبيل المثال يعني لو اضفت ال D على كل frequent
+
+68
+00:04:51,800 --> 00:04:56,940
+patterns اللي موجودين عندي هن على اللي موجودة من
+
+69
+00:04:56,940 --> 00:05:03,250
+ال database هيكون عنديالـ A,B,C,D عبارة عن
+
+70
+00:05:03,250 --> 00:05:07,510
+frequent pattern يعني انا عندي A,B,C عبارة عن
+
+71
+00:05:07,510 --> 00:05:10,430
+frequent pattern وعندي ال D كمان frequent pattern
+
+72
+00:05:10,430 --> 00:05:15,730
+فحتما هيكون عندي A,B,C,D frequent pattern حتى لو
+
+73
+00:05:15,730 --> 00:05:18,770
+جل السببورت تبعته بس مش هنزل عن ال minimum support
+
+74
+00:05:18,770 --> 00:05:24,830
+ليش؟ لأنه بما انه ال support لهذه أكبر أو تساوي ال
+
+75
+00:05:24,830 --> 00:05:32,140
+minimum supportوديها دي ال support تبعتها أقل أو
+
+76
+00:05:32,140 --> 00:05:36,280
+تساوي ال minimum support فحتما هذا التنين هيكون
+
+77
+00:05:36,280 --> 00:05:39,220
+أكبر أو يساوي ال minimum support مش هيقل عنه بأي
+
+78
+00:05:39,220 --> 00:05:44,630
+حالة من الأحوال لأن التنين frequentالفكرة كمان مرة
+
+79
+00:05:44,630 --> 00:05:49,570
+ان انا فعليا احاول اعمل ركيز ركيرسيفلي growing لل
+
+80
+00:05:49,570 --> 00:05:53,130
+frequent pattern انشئ ال pattern بشكل ركيرسيفي
+
+81
+00:05:53,130 --> 00:05:56,510
+بشكل تلقائي يعني كل pattern يدور او يحاول يضيف ال
+
+82
+00:05:56,510 --> 00:06:03,210
+patterns اللي موجود عندها pattern and by pattern
+
+83
+00:06:03,210 --> 00:06:07,330
+frequent pattern by pattern andالـ Database
+
+84
+00:06:07,330 --> 00:06:10,230
+Partitioning وبالتالي انا بجسم ال database و ممكن
+
+85
+00:06:10,230 --> 00:06:13,650
+انا اشتغل عليها يعني يقولولنا ان ال FP Growth ك
+
+86
+00:06:13,650 --> 00:06:17,210
+algorithm او ك method هتكون افضل نتيجة او اسرع من
+
+87
+00:06:17,210 --> 00:06:23,670
+الابريري للوصول ل ال frequent pattern اللي موجودة
+
+88
+00:06:23,670 --> 00:06:28,970
+لانها for each frequent item لكل frequent item set
+
+89
+00:06:28,970 --> 00:06:33,530
+construct its conditional pattern انشئ لل
+
+90
+00:06:33,530 --> 00:06:37,580
+conditional pattern تبعتها بناء على ايش انتجتThen
+
+91
+00:06:37,580 --> 00:06:41,180
+it's conditional FB tree وروح انشأ الـ Tree اللي
+
+92
+00:06:41,180 --> 00:06:45,620
+بعد هيك الخاصة فيها هنشوف ال FB tree ونفهم إيش ال
+
+93
+00:06:45,620 --> 00:06:48,300
+conditional pattern اللي تم إنشاءها عليه ال
+
+94
+00:06:48,300 --> 00:06:50,740
+conditional pattern يعني كيف تم الوصول تبعتها، إيش
+
+95
+00:06:50,740 --> 00:06:55,160
+الشروط تبعت إنها صارت Teddy frequent؟repeat the
+
+96
+00:06:55,160 --> 00:06:59,980
+process on each newly created pattern conditional
+
+97
+00:06:59,980 --> 00:07:05,560
+FB3 until resulting FB3 is empty مايكونش فيها ولا
+
+98
+00:07:05,560 --> 00:07:09,600
+حاجة وضلك كره العملية لما ماظلش فيها انك في ال FB3
+
+99
+00:07:09,600 --> 00:07:16,660
+and or it contains only one path single path طبعا
+
+100
+00:07:16,660 --> 00:07:19,740
+وهذا بيكون generation all combination وهكذا انا
+
+101
+00:07:19,740 --> 00:07:25,150
+بكون جمعت كل ال sub paths اللي موجودة يعنيالخطوات
+
+102
+00:07:25,150 --> 00:07:28,290
+الخاصة بالألغوريثم انا بروح بعمل database scan
+
+103
+00:07:28,290 --> 00:07:33,410
+once وهي أول عملية قراءة لل database مثل الابريوري
+
+104
+00:07:33,410 --> 00:07:37,390
+و روحت و جبت ال first frequent pattern تمام احنا
+
+105
+00:07:37,390 --> 00:07:42,350
+بيقول depth صحيح breadth دبث عفوا وهيك ان انا روحت
+
+106
+00:07:42,350 --> 00:07:45,810
+في ال pattern الأول مش قضية كتير sort ال frequent
+
+107
+00:07:45,810 --> 00:07:49,940
+pattern وهنا دي شغلة جديدة انه رتبالـ Frequent
+
+108
+00:07:49,940 --> 00:07:53,400
+Patterns بناء على الـ Support بترتيب تنازلي
+
+109
+00:07:53,400 --> 00:07:56,820
+Descending Support Counting Making a Less than
+
+110
+00:07:56,820 --> 00:08:00,160
+Millihell اعمل Scan كمان مرة للـ Tree و اعمل
+
+111
+00:08:00,160 --> 00:08:05,000
+Construction للـ FB Tree اللي موجود اللي هنشوفها
+
+112
+00:08:05,000 --> 00:08:11,800
+Mining the B-Tree By Creating Conditional أو Sub
+
+113
+00:08:11,800 --> 00:08:16,460
+Patterns اللي موجودة تعالى نشوف ايش ممكن احنا
+
+114
+00:08:16,460 --> 00:08:20,360
+نساويممكن نرجع للـ benefits أو نخلصها الآن
+
+115
+00:08:20,360 --> 00:08:24,560
+completeness متكاملة preserve complete information
+
+116
+00:08:24,560 --> 00:08:28,080
+بيحتوي معلومات كاملة عن ال frequent pattern اللي
+
+117
+00:08:28,080 --> 00:08:30,900
+انا عملت لها extraction يعني دائما هو محتفظ بال
+
+118
+00:08:30,900 --> 00:08:33,440
+support تبعيتها هذه المعلومة اللي بتهمني ال
+
+119
+00:08:33,440 --> 00:08:37,120
+frequent pattern كم مرة ظهر never break long
+
+120
+00:08:37,120 --> 00:08:41,240
+patterns of any transaction ممكن تبعش لترانزاكش
+
+121
+00:08:41,240 --> 00:08:44,480
+مطلقا وهو المشكلة احنا مش فعاليا ماحسنهاش مع ال a
+
+122
+00:08:44,480 --> 00:08:48,080
+priori لكن بيتكلموا انه ممكنعندما تكون عند الـ
+
+123
+00:08:48,080 --> 00:08:52,080
+Data Set التعاملات الكبيرة والعناصر الموجودة فيها
+
+124
+00:08:52,080 --> 00:08:55,480
+كتير ممكن تصير فيها عندها comebackness أو الضغط أو
+
+125
+00:08:55,480 --> 00:09:03,020
+التكاملية أو تقليل المعلومات المعلومات المعلومات
+
+126
+00:09:03,020 --> 00:09:03,680
+المعلومات المعلومات المعلومات المعلومات المعلومات
+
+127
+00:09:03,680 --> 00:09:05,080
+المعلومات المعلومات المعلومات المعلومات المعلومات
+
+128
+00:09:05,080 --> 00:09:05,180
+المعلومات المعلومات المعلومات المعلومات المعلومات
+
+129
+00:09:05,180 --> 00:09:05,180
+المعلومات المعلومات المعلومات المعلومات المعلومات
+
+130
+00:09:05,180 --> 00:09:05,180
+المعلومات المعلومات المعلومات المعلومات المعلومات
+
+131
+00:09:05,180 --> 00:09:05,180
+المعلومات المعلومات المعلومات المعلومات المعلومات
+
+132
+00:09:05,180 --> 00:09:05,180
+المعلومات المعلومات المعلومات المعلومات المعلومات
+
+133
+00:09:05,180 --> 00:09:05,780
+المعلومات المعلومات المعلومات الم
+
+134
+00:09:17,640 --> 00:09:24,900
+العناصر الترتيب الترتيب التنازلي
+
+135
+00:09:24,900 --> 00:09:30,580
+الكثير ممكن أن يحدث الكثير ممكن أن يتم شرحالموجود
+
+136
+00:09:30,580 --> 00:09:33,100
+في الأعلى في أعلى القائمة هو غالبا هو المتكرر
+
+137
+00:09:33,100 --> 00:09:36,120
+الموجود عندها Never be larger than the original
+
+138
+00:09:36,120 --> 00:09:38,820
+database مستحيل يطلع عندي بتم أكبر من الموجود
+
+139
+00:09:38,820 --> 00:09:44,060
+عندها Not count node links and count field أنا
+
+140
+00:09:44,060 --> 00:09:50,240
+بعدش ال link بعد فقط عدد مرات الظهر بالمقال كما
+
+141
+00:09:50,240 --> 00:09:55,470
+العادة بالمثال يتضح المقالخلّينا الآن نشوف بالمثال
+
+142
+00:09:55,470 --> 00:09:58,070
+اللي موجود عندنا هناش بيساوي بقول افترض ان انا في
+
+143
+00:09:58,070 --> 00:10:01,090
+عندى هذا ال data ال transactional data set اللي
+
+144
+00:10:01,090 --> 00:10:06,710
+بتحتوي فيها خمس عناصر I1, I2, I3, I4, I5 وفي عندي
+
+145
+00:10:06,710 --> 00:10:12,690
+تسعة عفوان مش ..
+
+146
+00:10:12,690 --> 00:10:20,880
+I discard I transaction رقم تسعةكمان للأقل الخطأ
+
+147
+00:10:20,880 --> 00:10:24,360
+يصير يعني وهذا طبعا كررته هان لأن copy و paste
+
+148
+00:10:24,360 --> 00:10:29,540
+اشتغلت هنا في المثال لما عدلت عليه و لما هان كذلك
+
+149
+00:10:29,540 --> 00:10:38,620
+ان شاء الله كده تمام الان افترض ان ال minimum
+
+150
+00:10:38,620 --> 00:10:41,620
+support تبعتي هي عبارة عن اتنين ال minimum support
+
+151
+00:10:41,620 --> 00:10:47,500
+المطلوبة عبارة عن اتنين2 على 9 يعني 22% تقريبا الـ
+
+152
+00:10:47,500 --> 00:10:52,340
+step الأولى بقرر ال database مع ال first او one
+
+153
+00:10:52,340 --> 00:10:56,380
+item set كل المجموعات التي هي عنصر واحد و بحسب ال
+
+154
+00:10:56,380 --> 00:11:00,000
+support تبعتهم بعد هيك الخبرة التانية بروح برتبهم
+
+155
+00:11:00,000 --> 00:11:05,880
+الآن بكل بساطة لو أنا جيت و قلت لك هاي I واحدالـ
+
+156
+00:11:05,880 --> 00:11:14,540
+support هي 1,2,3,4,5,6 من ضمن العناصر الموجودة الـ
+
+157
+00:11:14,540 --> 00:11:20,220
+frequent هي 6 موجودة أكتر عنصر موجود عندي more
+
+158
+00:11:20,220 --> 00:11:23,800
+frequent هو I2 هو عدد مرات تكراره 7 مرات
+
+159
+00:11:27,740 --> 00:11:33,440
+التلاتة واربعة وخمسة مع بعض اتنين واحد وستة جايين
+
+160
+00:11:33,440 --> 00:11:36,740
+نفس ال frequent طب مين اقدم فيهم اللي بيظهر معاك
+
+161
+00:11:36,740 --> 00:11:40,540
+اولا في ال data set ما تلخمش حالك دائما او ما
+
+162
+00:11:40,540 --> 00:11:43,860
+تلخميش حالك دائما انا باخد اول عنصر بيظهر في ال
+
+163
+00:11:43,860 --> 00:11:47,320
+frequent set او في ال item set هو اللي انا بقدمه
+
+164
+00:11:47,320 --> 00:11:52,880
+في حالة تساوي عنصرين من ناحية عدد ال supportالان
+
+165
+00:11:52,880 --> 00:11:56,640
+بعد ذلك ابدأ ببناء الـ FB tree وهي بتتكلم عن خطوات
+
+166
+00:11:56,640 --> 00:12:03,820
+بناءها ابدا من null label تمام وبناء عليه اعمل ال
+
+167
+00:12:03,820 --> 00:12:07,040
+second time ال second scan لل database المرة
+
+168
+00:12:07,040 --> 00:12:12,140
+التانية في كل transaction اتعامل are processed in
+
+169
+00:12:12,140 --> 00:12:15,900
+ال L order بناء على ال sort order اللي موجود عندها
+
+170
+00:12:16,960 --> 00:12:22,320
+والجزء يتم صنعه لكل تجارب مع أشياء تدعمها تدعمها
+
+171
+00:12:22,320 --> 00:12:23,820
+تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها
+
+172
+00:12:23,820 --> 00:12:25,400
+تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها
+
+173
+00:12:25,400 --> 00:12:28,480
+تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها
+
+174
+00:12:28,480 --> 00:12:29,060
+تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها
+
+175
+00:12:29,060 --> 00:12:29,420
+تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها
+
+176
+00:12:29,420 --> 00:12:32,820
+تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها
+
+177
+00:12:32,820 --> 00:12:41,200
+تدعمها تدعمها تدعمها تدعمها تدعمها تدعمها تد
+
+178
+00:12:42,500 --> 00:12:46,200
+الـ Data Set اللي موجودة عندى بقولي رتبليه هين
+
+179
+00:12:46,200 --> 00:12:49,880
+رتبتهم الآن يا جماعة الخير هى ال ال Transactional
+
+180
+00:12:49,880 --> 00:12:54,560
+Data Set تبعتي و هى ال ال اللي موجودة عندى الان
+
+181
+00:12:54,560 --> 00:12:59,640
+بما أن الترتيب هذا لازم يكون عندى حاضر دائما فأسهل
+
+182
+00:12:59,640 --> 00:13:03,740
+اليك هاي خطوة اليكم انه انا اروح اعيد ترتيب ل
+
+183
+00:13:03,740 --> 00:13:07,660
+Transaction Element في كل ترتيب ال items في كل
+
+184
+00:13:07,660 --> 00:13:10,640
+Transaction بناء على هاي و انا اقترحت ان اعمل هذا
+
+185
+00:13:10,640 --> 00:13:16,580
+الجدولإن أبدأ بـ I2 I1 I5 لأن فعليا هدول موجودين
+
+186
+00:13:16,580 --> 00:13:20,300
+بس I2 هو الـ most frequent element فانا حطيته في
+
+187
+00:13:20,300 --> 00:13:23,960
+الأول هذا بريحني في بناء ال tree لاحقا خليني نبدأ
+
+188
+00:13:23,960 --> 00:13:27,220
+نبني ال tree الآن يا جماعة الخير بعد ما انا حطيت
+
+189
+00:13:27,220 --> 00:13:30,420
+الجدول قال لي ابدأ من null هاي null مش عندى مشكلة
+
+190
+00:13:30,420 --> 00:13:34,560
+في الموضوع هاي ال null ممتاز الآن ال transaction
+
+191
+00:13:34,560 --> 00:13:38,680
+الأول I2 I2
+
+192
+00:13:38,680 --> 00:13:47,150
+I2 وعدد تكرارها واحدلأن وراها I1 I1
+
+193
+00:13:47,150 --> 00:13:52,650
+و هاي كمان مرة و وراهم I5 ليش هدول جايين ورا بعض
+
+194
+00:13:52,650 --> 00:13:55,490
+جمعة الخير في one branch لأن هو عبارة عن نفس ال
+
+195
+00:13:55,490 --> 00:13:58,890
+transaction وبالتالي أنا لازم احطه بنفس النمرة
+
+196
+00:13:58,890 --> 00:14:03,810
+تمام نمتقل لترانزاكشن التاني I2 هي موجودة بغير ال
+
+197
+00:14:03,810 --> 00:14:08,750
+counter تبعتها هاي صارت اتنين I4 مش موجودة بحط
+
+198
+00:14:08,750 --> 00:14:11,550
+branch وهاي I4
+
+199
+00:14:14,290 --> 00:14:18,850
+خلصت الترانزاكشن وانتقل لترانزاكشن التالف I2 هذه
+
+200
+00:14:18,850 --> 00:14:28,470
+تارة تلاتة وراها I3 هذه تلاتة مش موجودة بحط branch
+
+201
+00:14:28,470 --> 00:14:38,630
+جديد و بسميه I3 و لمرة واحدة الترانزاكشن التالف I2
+
+202
+00:14:38,630 --> 00:14:42,990
+تارة اربعة خلنا بس نحاول نشوف ال options نجيب
+
+203
+00:14:42,990 --> 00:14:43,670
+المساحة
+
+204
+00:14:46,390 --> 00:14:51,310
+Eraser انا بدي امسح هذا تمام هذه صارت اربعة الآن
+
+205
+00:14:51,310 --> 00:14:57,310
+هذه
+
+206
+00:14:57,310 --> 00:15:02,590
+صارت اربعة لان انا في ال transaction الرابع I1
+
+207
+00:15:02,590 --> 00:15:08,390
+صارت اتنين الآن بقول I4 I4 مش موجودة فبروح بضيفها
+
+208
+00:15:08,390 --> 00:15:18,410
+هنا I اعفوا I4 وهي كمان مرةبرجع الـ I1 I1 مش
+
+209
+00:15:18,410 --> 00:15:24,790
+موجودة لأنها بادية من الـ NULL فبجب أضعها I1 وهي
+
+210
+00:15:24,790 --> 00:15:36,330
+كمان مرة و وراها I3 وهي مرة I2 I3 معناته هذه ستصبح
+
+211
+00:15:36,330 --> 00:15:42,900
+خمسة وهذه ستصبح اتنين لأن هذه ال branch موجودةالان
+
+212
+00:15:42,900 --> 00:15:46,360
+في اللي بقى احنا خلصنا هان خلصنا هان اي واحد اي
+
+213
+00:15:46,360 --> 00:15:50,680
+تلاتة هذه صارت اتنين لانه موجود ل branch اي اتنين
+
+214
+00:15:50,680 --> 00:15:56,340
+خلصناها الان هذا اي تلاتة اي اتنين عفوا صارت هذه
+
+215
+00:15:56,340 --> 00:16:00,960
+ستة ستة
+
+216
+00:16:00,960 --> 00:16:06,800
+اي واحد صارت تلاتة خلينا
+
+217
+00:16:06,800 --> 00:16:11,100
+اي خمسة وراهم هتصير هان اتنين خلينا بس اجيب ال
+
+218
+00:16:11,100 --> 00:16:11,440
+eraser
+
+219
+00:16:29,840 --> 00:16:38,140
+هنا صارت ستة وهنا صارت خمسة
+
+220
+00:16:38,140 --> 00:16:47,920
+وهذه صارت اتنين هذه صارت خمسة هي المفروض لأ
+
+221
+00:16:47,920 --> 00:16:53,660
+واحد اتنين
+
+222
+00:16:53,660 --> 00:16:56,620
+تلاتة هذه تلاتة المفروض مش خمسة
+
+223
+00:17:01,730 --> 00:17:07,970
+هذه ثلاثة تمام الآن الترانزاكشن اللي بعده I2 I1 I3
+
+224
+00:17:07,970 --> 00:17:15,450
+هذه تصبح سبعة وهذه أربعة وهذه اتنين الآن يا جماعة
+
+225
+00:17:15,450 --> 00:17:18,810
+الخير لو انا فكرت ان احسب ال support لكل واحد من
+
+226
+00:17:18,810 --> 00:17:22,330
+ال elements اللي موجود عندي I2 ال support تبعتها
+
+227
+00:17:22,330 --> 00:17:25,810
+سبعة تمام دعوني أغير بالسلون
+
+228
+00:17:30,540 --> 00:17:37,780
+سبعة صحيحة الان I واحد المفروض ستة I واحد هي عندي
+
+229
+00:17:37,780 --> 00:17:42,860
+هنا اربعة وعندي هنا اتنين فالكلام صحيح مية المية
+
+230
+00:17:42,860 --> 00:17:47,860
+مجموعهم ستة الان I تلاتة ستة كذلك I تلاتة عندي
+
+231
+00:17:47,860 --> 00:17:57,800
+موجود I تلاتة ست مرات اين I تلاتة هاي
+
+232
+00:17:57,800 --> 00:18:10,100
+مرتين هناهي مرتين هان هى
+
+233
+00:18:10,100 --> 00:18:14,320
+مرة هى تانية اتينية اتينية اتينية اتينية اتينية
+
+234
+00:18:14,320 --> 00:18:15,840
+اتينية اتينية اتينية اتينية اتينية اتينية اتينية
+
+235
+00:18:15,840 --> 00:18:15,920
+اتينية اتينية اتينية اتينية اتينية اتينية اتينية
+
+236
+00:18:15,920 --> 00:18:16,160
+اتينية اتينية اتينية اتينية اتينية اتينية اتينية
+
+237
+00:18:16,160 --> 00:18:17,620
+اتينية اتنية اتنية اتنية اتنية اتنية اتنية اتنية
+
+238
+00:18:17,620 --> 00:18:18,540
+اتنية اتنية اتنية اتنية اتنية اتنية اتنية اتنية
+
+239
+00:18:18,540 --> 00:18:19,600
+اتنية اتنية اتنية اتنية اتنية اتنية اتنية اتنية
+
+240
+00:18:19,600 --> 00:18:28,940
+اتنية اتنية
+
+241
+00:18:29,930 --> 00:18:38,930
+طيب اي تلاتة تمام اي اربعة مرتين هيهم لأ
+
+242
+00:18:38,930 --> 00:18:43,330
+هن مرة واحدة مش اربعة هن المفروض ما عدلناهاش مرة
+
+243
+00:18:43,330 --> 00:18:50,850
+واحدة وهي مرة واحدة مرتين تمامهذه الـ I5 مرتين
+
+244
+00:18:50,850 --> 00:18:55,570
+يعني الـ tree تبعتنا هيك بتكون سليمة و العنصر
+
+245
+00:18:55,570 --> 00:19:00,290
+تبعتها موجودة فهذه الـ tree فعليا اللي احنا عاملا
+
+246
+00:19:00,290 --> 00:19:07,870
+كنا بنحاول مرسومها I2 I4 I5 بمشي مع العناصر اعفوا
+
+247
+00:19:07,870 --> 00:19:19,280
+I1 I5 مع ال transaction I2 I4 هيها I2 I3 هيها في
+
+248
+00:19:19,280 --> 00:19:22,540
+كل مرة بمر على I2 انا بزيد ال counter تبعها لحد ما
+
+249
+00:19:22,540 --> 00:19:26,100
+تتحقق العناصر و دائما القصها بالمقطة هذه جمعت خير
+
+250
+00:19:26,100 --> 00:19:29,160
+بس عشان وارجيني هم وين النقاط اللي انا عمله جمعتهم
+
+251
+00:19:29,160 --> 00:19:34,440
+يعني هي Han و Han هدول مع بعض بتمثل الستة طيب تمام
+
+252
+00:19:34,440 --> 00:19:39,540
+انا هيك انا حصلت على ال tree اللي موجودة عندي الان
+
+253
+00:19:39,540 --> 00:19:43,680
+بدي اروح اشوف انشئ ال conditional pattern تبعتي او
+
+254
+00:19:43,680 --> 00:19:47,680
+ال conditional pattern نعممن الـ tree اللي موجودة
+
+255
+00:19:47,680 --> 00:19:52,540
+عندها فممكن انا ابدأ امر على او اعمل traversing لل
+
+256
+00:19:52,540 --> 00:19:57,880
+tree اللي موجودة عندها عشان اشوف ال occurrence تبع
+
+257
+00:19:57,880 --> 00:20:01,700
+ال pattern اللي عندها الان المشكلة تبعتي كيف انا
+
+258
+00:20:01,700 --> 00:20:04,880
+بدي احصل على ال frequent pattern من ال database
+
+259
+00:20:04,880 --> 00:20:11,580
+تمام ال database is transferred ل ال tree وهذا
+
+260
+00:20:11,580 --> 00:20:18,220
+الان بدي اجيب من ال tree اللي عندهاعشان تقدر تنقب
+
+261
+00:20:18,220 --> 00:20:22,540
+أو تطلع او تعمل extraction military وتبني او تعتمد
+
+262
+00:20:22,540 --> 00:20:26,020
+على ال conditional pattern اللي موجود عندك هنا
+
+263
+00:20:26,020 --> 00:20:29,300
+ابدا مع ال frequent pattern اللي من واحد as
+
+264
+00:20:29,300 --> 00:20:33,120
+initial suffix suffix يعني من البداية بدك تشتغل
+
+265
+00:20:34,590 --> 00:20:39,090
+Construct Conditional Pattern Based Which Consists
+
+266
+00:20:39,090 --> 00:20:43,630
+Of The Prefix Paths
+
+267
+00:20:43,630 --> 00:20:46,670
+In Every Tree Co-occurring With The Suffix In The
+
+268
+00:20:46,670 --> 00:20:49,050
+Motion ابدا مع الـ Tree اللي بتبدأ بالـ Suffix
+
+269
+00:20:49,050 --> 00:20:53,910
+اللي موجود عندك Construct Conditional Pattern Tree
+
+270
+00:20:53,910 --> 00:21:01,030
+And Perform Mining On Such Treeاللي عندك هان هيبدأ
+
+271
+00:21:01,030 --> 00:21:06,230
+يزيد معايا growth is achieved by concatenation the
+
+272
+00:21:06,230 --> 00:21:11,690
+suffix مع ال frequent pattern اللي ظهر عندي و عيدك
+
+273
+00:21:11,690 --> 00:21:14,350
+دلك كتر في خطوة أربعة لحد ما تخلص ال tree تعالى
+
+274
+00:21:14,350 --> 00:21:19,150
+نشوف عندي هان ايش اللي بيصير هان او خليني احتفظ
+
+275
+00:21:19,150 --> 00:21:23,210
+بفقط ال tree و اشوف ال header ايش هذا بده عشان
+
+276
+00:21:23,210 --> 00:21:25,930
+بعدين بنشوفه خليني بس اوقف هان
+
+277
+00:21:31,640 --> 00:21:35,040
+الان عشان انا انشئ ال tree او انا بدأ انشئ ال
+
+278
+00:21:35,040 --> 00:21:38,780
+conditional ال pattern base و ال tree تبعتي بناء
+
+279
+00:21:38,780 --> 00:21:41,580
+على ال tree اللي موجودة عندنا .. اللي انشأناها
+
+280
+00:21:41,580 --> 00:21:45,480
+سابقا الان يا جماعة الخير كان بيقوللي في المثال
+
+281
+00:21:45,480 --> 00:21:50,120
+السابق ان اول حاجة ابدأ مع ال frequent pattern
+
+282
+00:21:50,120 --> 00:21:56,200
+length واحد تمام؟ as initial suffix pattern طيب
+
+283
+00:21:56,200 --> 00:22:06,660
+الفكرةهل انا بدي اخد اي
+
+284
+00:22:06,660 --> 00:22:10,460
+اتنين او اي واحد او اي اتنين او اي اتنين او اي
+
+285
+00:22:10,460 --> 00:22:12,640
+اتنين او اي اتنين او اي اتنين او اي اتنين او اي
+
+286
+00:22:12,640 --> 00:22:12,640
+اتنين او اي اتنين او اي اتنين او اي اتنين او اي
+
+287
+00:22:12,640 --> 00:22:13,100
+اتنين او اي اتنين او اتنين او اتنين او اتنين او
+
+288
+00:22:13,100 --> 00:22:13,440
+اتنين او اتنين او اتنين او اتنين او اتنين او اتنين
+
+289
+00:22:13,440 --> 00:22:14,560
+او اتنين او اتنين او اتنين او اتنين او اتنين او
+
+290
+00:22:14,560 --> 00:22:21,320
+اتنين او اتنين او اتنين او اتنDepth Search مظبوط
+
+291
+00:22:21,320 --> 00:22:26,160
+جالك Depth Search Tree الـ Traversing وبالتالي هو
+
+292
+00:22:26,160 --> 00:22:28,540
+بدوش اشتغل Bread بدوش اشتغل Depth معناته Depth
+
+293
+00:22:28,540 --> 00:22:31,640
+بدروح على أعمق نقطة مين أعمق نقطة ده هي النقاط
+
+294
+00:22:31,640 --> 00:22:35,960
+تبعتي و اشتغل عليها مين النقاط اللي موجودة عندى في
+
+295
+00:22:35,960 --> 00:22:44,090
+ال leaves يا جماعة الخير I5 I4 I3 مظبوططيب و بعد
+
+296
+00:22:44,090 --> 00:22:47,470
+هي كنت بدي أطلع لحد ما هي في عندي نوت وبالتالي
+
+297
+00:22:47,470 --> 00:22:52,510
+النقاط تبعتهم كل العناصر معدمين معدم قطين هدول
+
+298
+00:22:52,510 --> 00:22:55,650
+اللي موجودات فوق خالص اللي هم جايات النل لأن هدول
+
+299
+00:22:55,650 --> 00:23:07,650
+هم بمثلوا عندي بمثلوا المفتاح الأساس في الشغل تمام
+
+300
+00:23:09,130 --> 00:23:15,130
+الان بما ان انا هشتغل هشتغل كتالي من خلال ال tree
+
+301
+00:23:15,130 --> 00:23:21,710
+اللي موجودة عندى و زى ما قولنا حبدة من ال I خمسة
+
+302
+00:23:21,710 --> 00:23:25,870
+ايه ال I خمسة لأ انا باصللها من خلال مين يا جماعة
+
+303
+00:23:25,870 --> 00:23:31,910
+الخير ال I خمسة انا باصللها من خلال I اتنين و I
+
+304
+00:23:31,910 --> 00:23:38,380
+اربعةعفوا I2 و I1 كم مرة مريت عليهم عشان اصل لل
+
+305
+00:23:38,380 --> 00:23:41,900
+element هذا خليني برضه احنا قولنا المعلومات تبعتنا
+
+306
+00:23:41,900 --> 00:23:49,780
+بدها تكون دائما موجودة عندى خليني بس اجيب ال data
+
+307
+00:23:49,780 --> 00:23:54,820
+set عشان تظل حاضرة عندنا هي هذه
+
+308
+00:24:03,760 --> 00:24:20,280
+و بدي أجيبها هنا على الآخر لماذا
+
+309
+00:24:20,280 --> 00:24:28,200
+لا أشوف ال animation حقيقية animation
+
+310
+00:24:28,200 --> 00:24:32,980
+team group لا أريد animation حقيقية
+
+311
+00:24:37,210 --> 00:24:42,550
+كل هاي ال element اللى انا بدى اشتغل عليهم طيب ال
+
+312
+00:24:42,550 --> 00:24:55,190
+I الآن
+
+313
+00:24:55,190 --> 00:24:58,190
+جمعت الخيار فهذا الجدول هيلزمني عشان انا اقدر
+
+314
+00:24:58,190 --> 00:25:01,570
+اتذكر انا فعليا ال conditional better base انا
+
+315
+00:25:01,570 --> 00:25:06,330
+وصلت لل I خمس خلال Iالـ I5 أنا وصلت لها من خلال
+
+316
+00:25:06,330 --> 00:25:16,990
+وصلت لها مرتين مرة من خلال I2 و I1 لحالهم هذه كانت
+
+317
+00:25:16,990 --> 00:25:32,710
+مرة مصبوط و مرة كانت من خلال I1 و I3 I2 I1 I3 هذه
+
+318
+00:25:32,710 --> 00:25:37,400
+كمان مرةمعناته انا هي ال path او هي المسارات اللي
+
+319
+00:25:37,400 --> 00:25:46,440
+ودتني لمين ل I5 اللي موجودة هنا وبناء عليه أنا ال
+
+320
+00:25:46,440 --> 00:25:52,320
+nodes اللي فعليا بتهمني في عدد تكرارها المين اللي
+
+321
+00:25:52,320 --> 00:25:59,280
+ظهرت مرتين عندها في ال conditional I2 ظهرت مرتين و
+
+322
+00:25:59,280 --> 00:26:05,790
+I1 ظهرت مرتينI3 مابتلزمش لأنها ظهرت لمرة واحدة طب
+
+323
+00:26:05,790 --> 00:26:09,150
+ايش ال frequent pattern اللي بنعملها generation؟
+
+324
+00:26:09,150 --> 00:26:13,830
+معناته انا بقدر اجي اقول I2 I5 هذا frequent
+
+325
+00:26:13,830 --> 00:26:21,510
+pattern وعدد مرات ظهره اتنين في عند I1 I5 وهذا عدد
+
+326
+00:26:21,510 --> 00:26:26,070
+مراته برضه عدد مرات ظهره اتنين وفي عند ال pattern
+
+327
+00:26:26,070 --> 00:26:32,410
+التالت اللي هو I2 I1I5 اللي هو الـ combination
+
+328
+00:26:32,410 --> 00:26:36,010
+عفوًا لهم كلهم لأن هذه frequent وهذه frequent فلما
+
+329
+00:26:36,010 --> 00:26:39,170
+نضفهم مع بعض هيكون في عندي frequent وهي ال pattern
+
+330
+00:26:39,170 --> 00:26:43,190
+تبعتهم وبالتالي هذه هي ال generated frequent
+
+331
+00:26:43,190 --> 00:26:49,310
+pattern اللي طلعت عندي كمان مرة نشوفها مع I4 I4
+
+332
+00:26:49,310 --> 00:26:53,630
+إيش عمليات الوصول اللي كانت إلها كانت من خلال 2
+
+333
+00:26:53,630 --> 00:27:03,280
+هذه البسارات I2 مباشرة لحالهاأي اتنين كم مرة وصلت
+
+334
+00:27:03,280 --> 00:27:10,260
+لها اللي عفوا عندها اي اتنين اي اربعة كان عندى عدد
+
+335
+00:27:10,260 --> 00:27:15,120
+مرات الظهور مرة عبر اي واحد ومرة عبر اي اتنين يعني
+
+336
+00:27:15,120 --> 00:27:21,580
+اي اتنين مرة واحدة مظبوط ومرة من خلال اي اتنين اي
+
+337
+00:27:21,580 --> 00:27:23,100
+واحد كذلك مرة
+
+338
+00:27:25,920 --> 00:27:31,760
+الان من يلزمني من هؤلاء اللي اظهر مرتين على الأقل
+
+339
+00:27:31,760 --> 00:27:34,700
+الـ I2 المعنى الـ Conditional Pattern Tree تبعتي
+
+340
+00:27:34,700 --> 00:27:40,600
+ال I2 مرتين وبالتالي باجي ال frequent pattern
+
+341
+00:27:40,600 --> 00:27:46,140
+تبعتي هتكون I2 I4 وهي ال support تبعته ال minimum
+
+342
+00:27:46,140 --> 00:27:51,740
+support تبعته 2 باجي لل I3 بنفس الكلام I3 كيف وصلت
+
+343
+00:27:51,740 --> 00:27:58,860
+لهاأيش المسارات تبعت I3 I3 I3 I3 I3 I3 I3 I3 I3 I3
+
+344
+00:27:58,860 --> 00:28:00,700
+I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3
+
+345
+00:28:00,700 --> 00:28:00,700
+I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3
+
+346
+00:28:00,700 --> 00:28:00,820
+I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3
+
+347
+00:28:00,820 --> 00:28:04,540
+I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3
+
+348
+00:28:04,540 --> 00:28:05,400
+I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3
+
+349
+00:28:05,400 --> 00:28:10,580
+I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3 I3
+
+350
+00:28:24,850 --> 00:28:32,970
+هان برضه مرتين عبر I2 I1 I2 I1 برضه مرتين مين ال
+
+351
+00:28:32,970 --> 00:28:36,850
+frequent pattern عند هان؟ كلهم frequent لأن I1 و
+
+352
+00:28:36,850 --> 00:28:41,330
+I2 عبارة عن frequent patterns وبالتالي ال
+
+353
+00:28:41,330 --> 00:28:52,610
+conditional tree تبعتي I2 ظهرت أربع مرات و I1 ظهرت
+
+354
+00:28:52,610 --> 00:28:59,940
+مرتينعفوًا اي واحد ظهرت مرتين كذلك في عندى اي واحد
+
+355
+00:28:59,940 --> 00:29:02,880
+ظهرت لحالها طبعا انا جمعت هدول التنتين مع بعض ان
+
+356
+00:29:02,880 --> 00:29:07,120
+هدى و هدى في بينهم intersection او جايات مع بعضهم
+
+357
+00:29:07,120 --> 00:29:11,180
+صحيح اللي هم في pattern واحد فإذا انا باعتبر ان
+
+358
+00:29:11,180 --> 00:29:14,140
+هدى pattern واحد معناته ان هى ال pattern اللى عندى
+
+359
+00:29:14,140 --> 00:29:18,340
+او ال condition اللى تريه وعندى هنا اي واحد ظهرت
+
+360
+00:29:18,340 --> 00:29:22,930
+لحالهامرتين ايش ال frequent pattern اللي عندي
+
+361
+00:29:22,930 --> 00:29:38,670
+هتكلم على combination I2 I3 مرتين كذلك عندي I1 I3
+
+362
+00:29:38,670 --> 00:29:43,590
+عفوا ليش مرتين اربع مرات لان I2 اربع مرات ظهرت هي
+
+363
+00:29:43,590 --> 00:29:46,050
+اربعة وهنا I3
+
+364
+00:29:49,070 --> 00:29:54,870
+أي اي اتنين مرتين هنا و مرتين هنا يعني اربعة مرتين
+
+365
+00:29:54,870 --> 00:30:03,370
+و مرتين يعني اربعة و هنا في عندي اي اتنين اي واحد
+
+366
+00:30:03,370 --> 00:30:12,210
+اي تلاتة وهذا كذلك ظهر مرتين وبالتالي
+
+367
+00:30:12,210 --> 00:30:15,710
+انا هاي ال pattern اللي موجود عندي وهكذا بتظهر
+
+368
+00:30:15,710 --> 00:30:21,580
+عندى بجهة ال letterبالتالي هذه الـ pre كل ال
+
+369
+00:30:21,580 --> 00:30:24,040
+patterns هذه مجموعة الـ generated frequent
+
+370
+00:30:24,040 --> 00:30:28,080
+patterns اللي انا اشتغلت عليهم اعمل ما بين ال
+
+371
+00:30:28,080 --> 00:30:31,440
+patterns هدول عبارة عن ال association rules اللي
+
+372
+00:30:31,440 --> 00:30:36,500
+موجودة عندها ال FP growth method transform the
+
+373
+00:30:36,500 --> 00:30:40,710
+problem of finding long frequent patternsبحولت
+
+374
+00:30:40,710 --> 00:30:44,230
+ليها من البحث عن long frequent patterns searching
+
+375
+00:30:44,230 --> 00:30:48,330
+for shorter ones recursively and concatenating the
+
+376
+00:30:48,330 --> 00:30:52,510
+suffix و دائما أجمع ليه ال suffix اللي بتكون
+
+377
+00:30:52,510 --> 00:30:57,610
+موجودة it uses the least frequent items as suffix
+
+378
+00:30:58,530 --> 00:31:02,870
+ليش؟ لأن هم هدول الموجودين تحت خالص تمام offering
+
+379
+00:31:02,870 --> 00:31:07,270
+good selectivity وتوفر عليها الموضوع وهذا اختيار
+
+380
+00:31:07,270 --> 00:31:09,810
+مكون مناسب the method .. the method عفوا
+
+381
+00:31:09,810 --> 00:31:14,630
+substantially .. substantially reduce the search
+
+382
+00:31:14,630 --> 00:31:19,690
+cost لأنها بتشتغلش في ال breadth depth عفوا ال
+
+383
+00:31:19,690 --> 00:31:23,110
+search طيب
+
+384
+00:31:23,110 --> 00:31:26,410
+خلينا بدنا نشوف المثال التالي
+
+385
+00:31:34,890 --> 00:31:39,270
+هذا مثال .. مثال تاني تكملونه لواحدكم ان شاء الله
+
+386
+00:31:39,270 --> 00:31:44,350
+تعالى فرصة لكم تتدربوا و تشوفوا الخطوات لإنشاء ال
+
+387
+00:31:44,350 --> 00:31:47,910
+header tree او ال table السابق و كيف احنا اشتغلنا
+
+388
+00:31:47,910 --> 00:31:52,530
+عليه خطوة خطوة الان بقول لي ان في عندي transaction
+
+389
+00:31:52,530 --> 00:31:55,950
+data set من خمس عناصر فيها ال element اللي انت
+
+390
+00:31:55,950 --> 00:31:59,590
+مشرقها ال minimum support تبعتها minimum support
+
+391
+00:31:59,590 --> 00:32:03,230
+معناته ان جماعة الخيربدي أجي أعد والله ال F واحدة
+
+392
+00:32:03,230 --> 00:32:06,590
+تنتين تلاتة أربعة أكبر من ال minimum support
+
+393
+00:32:06,590 --> 00:32:17,590
+معناته ال F frequent ال A مرة تنتين تلاتة
+
+394
+00:32:17,590 --> 00:32:21,450
+ال A frequent ال C مرة تنتين تلاتة أربعة ال C
+
+395
+00:32:21,450 --> 00:32:27,950
+frequent هنا تلاتة هنا أربعة هنا أربعة ال D مرة is
+
+396
+00:32:27,950 --> 00:32:37,540
+not frequent مش هستخدمهاالـ G مرة مش هستخدمها ال D
+
+397
+00:32:37,540 --> 00:32:44,140
+قولنا مرة ال I مرة مش هستخدمها ال M مرتين تين
+
+398
+00:32:44,140 --> 00:32:50,760
+تلاتة فهي frequent هتفض فيها ال B مرتين تين تلاتة
+
+399
+00:32:50,760 --> 00:32:56,640
+فهتفض فيها على إنها frequent بالتالي ال L تبعتي ال
+
+400
+00:32:56,640 --> 00:33:01,830
+L تبعتيطب ده العناصر اللي مثلا في عند ال L it's
+
+401
+00:33:01,830 --> 00:33:08,270
+not frequent مرتين ال
+
+402
+00:33:08,270 --> 00:33:15,030
+O it's not frequent مرتين ال H it's not frequent
+
+403
+00:33:15,030 --> 00:33:21,030
+مرة واحدة ال W it's not frequently مرة واحدة ال N
+
+404
+00:33:21,030 --> 00:33:30,900
+ال K مرة ال S مرة ال N مرةالـ E مرة وبالتالي أنا
+
+405
+00:33:30,900 --> 00:33:34,520
+هي العناصر ال frequent تبعتها اللي هم الموجودين
+
+406
+00:33:34,520 --> 00:33:43,560
+فوق F,A او F,C,A,M,P تلت او خمس عناصر F,C بالترتيب
+
+407
+00:33:43,560 --> 00:33:48,260
+لأنهم ظهرت ال F أولا وال frequent تبعتها أربعةالـ
+
+408
+00:33:48,260 --> 00:33:50,840
+frequency تبعتها أربعة والـ C كذلك وراها أربعة ولا
+
+409
+00:33:50,840 --> 00:33:56,320
+بدنا نرتبهم ترتيب تنازلي فانا فعليا هي ال order
+
+410
+00:33:56,320 --> 00:34:01,360
+frequent set مع كل data set هي ال frequent item
+
+411
+00:34:01,360 --> 00:34:07,740
+set اللي أنا الموجودة عندي فانا هدول فعليا هيهم
+
+412
+00:34:07,740 --> 00:34:12,600
+وبالتالي هي ال F بدنا نرسم ل 3 و بدنا نرسم ل 3
+
+413
+00:34:12,600 --> 00:34:17,330
+عشان نتمرن على الجدول و نتكمل الجدول للآخر تمامفي
+
+414
+00:34:17,330 --> 00:34:22,670
+مقارنة ما بين الـ Apriori والـ FB Growth من ناحية
+
+415
+00:34:22,670 --> 00:34:26,470
+الـ Scalability على نفس الـ dataset اللي تم
+
+416
+00:34:26,470 --> 00:34:31,450
+استخدامها مع تغيير للـ threshold تبع الـ minimum
+
+417
+00:34:31,450 --> 00:34:36,850
+support تبع ال support والزمن بالثانية اللي موجود
+
+418
+00:34:36,850 --> 00:34:44,330
+هناالـ FB Growth فعليا من 40 أو 45 ثانية تقريبا أو
+
+419
+00:34:44,330 --> 00:34:48,670
+أقل شوية أو 43 ثانية و بدأ ينزل لما كنت أنا يشبه
+
+420
+00:34:48,670 --> 00:34:52,630
+أزيد طبعا لاحظوا أنا مافيش مجال ال support يكون
+
+421
+00:34:52,630 --> 00:34:55,930
+صفر لل threshold تبع ال support طبعا هنبغي أن هي
+
+422
+00:34:55,930 --> 00:34:59,370
+نسبة في المية جامعة الخير في الآخر و بدها تصير
+
+423
+00:34:59,370 --> 00:35:05,270
+فمستحيل تكون صفر عندي فالآن واضح أنه أداء ال FB
+
+424
+00:35:05,270 --> 00:35:11,080
+Growthأفضل تمام خصوصا لما بيصغر ال support لما
+
+425
+00:35:11,080 --> 00:35:14,380
+بيصغر ال support لإن كل ما بيكبر ال support تقريبا
+
+426
+00:35:14,380 --> 00:35:19,220
+أداء التنتين بيصير واحد تقريبا
+
+427
+00:35:22,630 --> 00:35:27,570
+هنكمل كفاية التسديل اللي اتأخرنا حاجة في التسديل
+
+428
+00:35:27,570 --> 00:35:30,370
+هذا لحضان و هكمل في الجزئية اللي ضايلة و هعرض
+
+429
+00:35:30,370 --> 00:35:33,630
+عليكم بقى code بسيط في تطبيق ال association role
+
+430
+00:35:33,630 --> 00:35:39,170
+خلال التسديل ان شاء الله تعالى كنت انا حضرته سابقا
+
+431
+00:35:39,170 --> 00:35:42,670
+و هنمر على ال code مع بعض السلام عليكم و رحمة الله
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/5xZPpqSUrAA.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/5xZPpqSUrAA.srt
new file mode 100644
index 0000000000000000000000000000000000000000..0c10002a1a23b8a07684de28287f462959ca70fa
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/5xZPpqSUrAA.srt
@@ -0,0 +1,1380 @@
+1
+00:00:02,650 --> 00:00:05,590
+باسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:05,590 --> 00:00:11,630
+أهلاً وسهلاً بكم في المحاضرة التالية في مساق تنقيب
+
+3
+00:00:11,630 --> 00:00:15,350
+البيانات، نتكلم على الـ Clustering، كنا غطينا في
+
+4
+00:00:15,350 --> 00:00:17,530
+chapter الـ Clustering، مفهوم الـ Clustering أنه
+
+5
+00:00:17,530 --> 00:00:20,970
+عبارة عن تقسيم الـ Data set اللي موجودة عندي
+
+6
+00:00:20,970 --> 00:00:25,570
+لمجموعات بناءً على الـ Similarities أو التشابه ما
+
+7
+00:00:25,570 --> 00:00:29,680
+بين الـ Instances اللي موجودة فيها، وذكرنا أن الـ
+
+8
+00:00:29,680 --> 00:00:33,140
+Clustering يأخذ واحدة من نوعين: إما Partitional
+
+9
+00:00:33,140 --> 00:00:36,540
+Clustering، وهي عبارة عن مجموعة من الـ Clusters أو
+
+10
+00:00:36,540 --> 00:00:39,980
+نعم، مجموعة من الـ Clusters اللي بيكون الـ Disjoint
+
+11
+00:00:39,980 --> 00:00:42,920
+أو التقاطعات بينهم صفر، ما فيش نقاط مشتركة ما بينهم،
+
+12
+00:00:42,920 --> 00:00:48,440
+وبالتالي كل Element موجود في Cluster واحد فقط، وفي
+
+13
+00:00:48,440 --> 00:00:51,760
+عندنا، حكينا أنه في عندنا... وشوفنا على المثال هذا
+
+14
+00:00:51,760 --> 00:00:56,360
+على مثل Partitional K-means، واتكلمنا عليه بالتفصيل
+
+15
+00:00:57,340 --> 00:01:00,400
+في المحاضرة إن شاء الله تعالى، سنتكلم على
+
+16
+00:01:00,400 --> 00:01:03,960
+النوع الثاني من الـ Clustering اللي هو الـ
+
+17
+00:01:03,960 --> 00:01:08,840
+Hierarchical Clustering، إن شاء الله تعالى، عندما
+
+18
+00:01:08,840 --> 00:01:11,580
+نتكلم عن Hierarchical Clustering، يعني أننا نتكلم
+
+19
+00:01:11,580 --> 00:01:16,640
+عن Clustering تجميعي، الفكرة فيه أنه عندما نتكلم عن
+
+20
+00:01:16,640 --> 00:01:19,560
+Agglomerative، الـ Hierarchical أو الـ Agglomerative
+
+21
+00:01:19,560 --> 00:01:24,220
+مترادفان، لأن كل Hierarchical يتعلق بـ Agglomerative
+
+22
+00:01:24,220 --> 00:01:28,280
+يعني تجميعي، Agglomerative Clustering عادةً
+
+23
+00:01:28,280 --> 00:01:33,440
+نُشير لكل الـ Clustering Algorithms التي تبني على نفس
+
+24
+00:01:33,440 --> 00:01:38,200
+المبدأ، وهو تجميع البيانات اللي موجودة عندنا، فكرة
+
+25
+00:01:38,200 --> 00:01:41,920
+الـ Agglomerative Clustering بشكل عام، بتتركز أنه
+
+26
+00:01:41,920 --> 00:01:47,120
+يبدأ، بيعرف أن كل نقطة كـ Cluster مستقل، وبعد ذلك
+
+27
+00:01:47,120 --> 00:01:54,720
+يعمل Merge أو Combine لكل Two Similar Clusters بناءً
+
+28
+00:01:54,720 --> 00:01:57,080
+على ايش؟ الـ Similarity، Cluster معناته في عندي
+
+29
+00:01:57,080 --> 00:02:00,800
+Similarity Distance أو Similarity Function زي ما
+
+30
+00:02:00,800 --> 00:02:04,180
+شوفناها في الـ Partitional، لازم تُطبق عندنا، وهذا
+
+31
+00:02:04,180 --> 00:02:08,500
+الـ Similarity Function هي اللي هتكون معيار دمج أو
+
+32
+00:02:08,500 --> 00:02:12,660
+قبول، دمج أو رفض دمج الـ Two Clusters اللي
+
+33
+00:02:12,660 --> 00:02:17,680
+موجودين عندي، طبعاً، وهذا الكلام بيستمر لحد ما يتوصل
+
+34
+00:02:17,680 --> 00:02:25,300
+يتحقق عندي شرط توقف معين، شرط التوقف يكون عبارة عن
+
+35
+00:02:25,300 --> 00:02:29,980
+عدد الـ Clusters اللي اتكلمت عليه، أنا بدي أعمل دمج
+
+36
+00:02:29,980 --> 00:02:35,040
+دمج دمج لحد ما أوصل لـ 3 Clusters، فعلياً الـ Data اللي
+
+37
+00:02:35,040 --> 00:02:38,820
+عندي هتبدأ من واحد واحد واحد واحد، بعد هيك هيبدأ
+
+38
+00:02:38,820 --> 00:02:43,900
+يتجمعوا، آخر تجميع اللي ممكن أوصل إليه، هذا مفهوم
+
+39
+00:02:43,900 --> 00:02:46,140
+أن يكون عندي 3 Clusters أو 4 Clusters أو 10
+
+40
+00:02:46,140 --> 00:02:49,300
+Clusters حسب الحاجة، وبهيك أنا فعلياً هذا شرطي
+
+41
+00:02:49,300 --> 00:02:55,280
+التوقف اللي موجود عندي، أو فعلياً أنا ما ضلّ عندي
+
+42
+00:02:55,280 --> 00:02:59,060
+شيء أدمجه، اندمجت كل البيانات لحد ما
+
+43
+00:02:59,060 --> 00:03:02,540
+صارت Only One Cluster بيحتوي كل الـ Sub Clusters
+
+44
+00:03:02,540 --> 00:03:06,020
+اللي جاية بعد هيك، طبعاً أنا في عندي Linkage
+
+45
+00:03:06,020 --> 00:03:10,820
+Criteria أو شرط الدمج، أو سمّيناها Linkage، دلالة على
+
+46
+00:03:10,820 --> 00:03:13,760
+أنه أنا فعلياً عندي Clusterين وبدي أربطهم مع بعض، بدي
+
+47
+00:03:13,760 --> 00:03:18,860
+أحطهم في قالب أو عفواً في ضمن Boundary واحدة، طبعاً
+
+48
+00:03:18,860 --> 00:03:21,420
+عندما أتكلم عن الـ Linkage Criteria أو الـ Linkage
+
+49
+00:03:21,420 --> 00:03:25,800
+Function، نفس المصطلح، الـ Similarity Function للـ
+
+50
+00:03:25,800 --> 00:03:28,660
+Clusters، بس دائماً عندما أتكلم عن الـ Similarity
+
+51
+00:03:28,660 --> 00:03:32,160
+بتكلم عن الـ Distance، عفواً، بتكلم عن الـ Distance
+
+52
+00:03:32,160 --> 00:03:36,160
+لكن عندما أتكلم عن الـ Linkage Criteria، بتكلم عن أن
+
+53
+00:03:36,160 --> 00:03:41,840
+أنا فعلياً بتكلم عن الـ Clustering، بتكلم عن Linkage
+
+54
+00:03:41,840 --> 00:03:45,040
+أو ربط ما بين الـ Clusters، فعلياً أنا بتكلم برضه عن
+
+55
+00:03:45,040 --> 00:03:49,410
+الـ Distance، والـ Distance هذه تُقاس مع كل الـ
+
+56
+00:03:49,410 --> 00:03:52,090
+Observations أو كل الـ Instances اللي موجودة عندنا،
+
+57
+00:03:52,090 --> 00:03:56,390
+وين؟ في داخل الـ Cluster اللي موجود عندنا، فعلياً أنا
+
+58
+00:03:56,390 --> 00:04:03,710
+في عندي مجموعة من الـ Linkage Criteria، وهذه الـ
+
+59
+00:04:03,710 --> 00:04:07,470
+Linkage Criteria بتحدد فعلياً هل هدول الـ Clusters
+
+60
+00:04:07,470 --> 00:04:13,390
+Similar أم لا، وبالتالي، يعني بالخلاصة، فكرة الـ
+
+61
+00:04:13,390 --> 00:04:16,590
+Agglomerative أو الـ Hierarchical Clustering بتبدأ
+
+62
+00:04:16,590 --> 00:04:20,890
+بأن كل نقطة عبارة عن Cluster مستقل، وبعد هيك بيصير
+
+63
+00:04:20,890 --> 00:04:25,810
+ادمج ما بين كل Two Clusters، الشرط للدمج أنه في عندي
+
+64
+00:04:25,810 --> 00:04:28,530
+شيء بنسميه الـ Linkage Criteria أو الـ Linkage
+
+65
+00:04:28,530 --> 00:04:31,610
+Distance أو الـ Linkage Function اللي هي شرط الدمج
+
+66
+00:04:31,610 --> 00:04:36,270
+هنا، وهي عبارة عن Distance Measure، لكن مش مع نقطة، مع
+
+67
+00:04:36,270 --> 00:04:39,250
+Cluster، وبالتالي ممكن أنا آخذ نقطة، نُطبق على
+
+68
+00:04:39,250 --> 00:04:43,350
+Cluster، ممكن آخذ كل Cluster، وحنشوف الـ Different
+
+69
+00:04:43,350 --> 00:04:49,630
+Linkage Criteria اللي موجودة عندنا، نبدأ مع أول الـ
+
+70
+00:04:49,630 --> 00:04:54,590
+Linkage Criteria، الـ Criteria اللي هي الـ Criterion
+
+71
+00:04:54,590 --> 00:04:57,450
+اللي هي الـ Single، ولما أنا بتكلم على Single
+
+72
+00:04:57,450 --> 00:05:04,970
+Linkage، بتكلم أنه أنا فعلياً بدور على أقصر Pair
+
+73
+00:05:04,970 --> 00:05:09,500
+يعني بين جُثتين، بأحسن الـ Point اللي أنا فيه،
+
+74
+00:05:09,500 --> 00:05:13,940
+عندي Two Clusters، زي... زي ما ال... أوكي، خليني مش
+
+75
+00:05:13,940 --> 00:05:17,180
+مشكلة، برجع فيه، عندي أنا هنا Two Clusters، Two
+
+76
+00:05:17,180 --> 00:05:20,600
+Clusters، وفي الـ Two Clusters هدول أنا بروح بدور
+
+77
+00:05:20,600 --> 00:05:25,220
+على كل النقاط، يعني بحسب النقطة هاي مع كل الـ
+
+78
+00:05:25,220 --> 00:05:28,180
+Distances الموجودة، في كل الأحوال يا جماعة الخير الـ
+
+79
+00:05:28,180 --> 00:05:34,420
+Distances هتنحسب ما بين كل عناصر الـ Cluster، وكذلك
+
+80
+00:05:34,420 --> 00:05:38,380
+High، يعني أنت تخيلها Fully Connected Distances أو
+
+81
+00:05:38,380 --> 00:05:41,580
+تخيلوها معايا Fully Connected Area، فبتحسب كل الـ
+
+82
+00:05:41,580 --> 00:05:46,920
+Distances اللي موجودة عندنا، الآن الـ Pair، Pair of
+
+83
+00:05:46,920 --> 00:05:51,820
+Clusters اللي بيحقق أقصر مسافة بين أي Two Pairs من
+
+84
+00:05:51,820 --> 00:05:56,640
+النقاط اللي موجودة عندنا، بأخذه على أنه اللي هو الـ
+
+85
+00:05:56,640 --> 00:06:01,360
+يعني عمل Home Dungeon، يعني لو أنا بدي أُعيد تاني،
+
+86
+00:06:04,190 --> 00:06:06,570
+لو أنا افترضت أن أنا في عندي Three Different
+
+87
+00:06:06,570 --> 00:06:15,230
+Clusters، لو
+
+88
+00:06:15,230 --> 00:06:22,170
+كان أنا في عندي Another Cluster، والـ Cluster ده
+
+89
+00:06:22,170 --> 00:06:28,230
+فيه مجموعة من النقاط، تبدأ
+
+90
+00:06:28,230 --> 00:06:31,170
+المسافات تُحسب ما بين كل النقاط اللي موجودة في كل
+
+91
+00:06:31,170 --> 00:06:37,190
+اتجاه، من كل نقطة، الـ Pair of Clusters اللي بتحقق
+
+92
+00:06:37,190 --> 00:06:41,910
+أقصر مسافة بين أي نقطتين موجودتين فيهم، بنعتمد أن
+
+93
+00:06:41,910 --> 00:06:45,250
+هدول الـ Clusters، في حين أن أنا في عندي هنا في
+
+94
+00:06:45,250 --> 00:06:50,490
+Pair بعيد جداً، وأنا ما بدور هون، بدور على أقصر
+
+95
+00:06:50,490 --> 00:06:54,850
+المسافات، يعني الآن هدول أقرب نقطتين لبعض، هيهم
+
+96
+00:06:54,850 --> 00:07:01,800
+بأقارن المسافة هذه ومسافة هذين، من أقصر المسافة هذه،
+
+97
+00:07:01,800 --> 00:07:05,920
+أقصر، معناته هذين الاثنين بنعمل لهم دمج مع بعضهم،
+
+98
+00:07:05,920 --> 00:07:09,020
+على أنهم هدول ايش؟ بيصيروا الـ Next Level أو الـ
+
+99
+00:07:09,020 --> 00:07:12,940
+Next Cluster، هذه فكرة، كمان مرة، الـ Single Linkage،
+
+100
+00:07:12,940 --> 00:07:17,060
+طبعاً احنا ليش بحاول أوضحها هون أكثر لأن فعلياً احنا
+
+101
+00:07:17,060 --> 00:07:21,660
+محتاجين نفهمها كويس، لأن أنا فعلياً بدي كل النقاط
+
+102
+00:07:21,660 --> 00:07:26,230
+اللي موجودة تكون داخلة في الحسبة، بنرجع كمان مرة في
+
+103
+00:07:26,230 --> 00:07:28,970
+عندي أنا Single Linkage، و Single Linkage بعمل
+
+104
+00:07:28,970 --> 00:07:32,270
+Combine لـ Two Clusters لما بيكون فيهم الـ Shortest
+
+105
+00:07:32,270 --> 00:07:37,610
+Pair، لما يكون في عندي أنا فعلياً ال... هذه البيانات
+
+106
+00:07:37,610 --> 00:07:42,390
+تبعتي، أصغر
+
+107
+00:07:42,390 --> 00:07:46,630
+ما بين الـ Minimum Distance Between Any Pair، بشرط
+
+108
+00:07:46,630 --> 00:07:49,870
+أن هدول الـ Pair ما يكونوش تمدمجهم مسبقاً، طبعاً،
+
+109
+00:07:53,060 --> 00:07:58,420
+كمان مرة، لو أنا افترضت أن هنا في عندي Another
+
+110
+00:07:58,420 --> 00:08:02,020
+Cluster، و
+
+111
+00:08:02,020 --> 00:08:06,580
+الـ Cluster هي وهي النقاط اللي موجودة، دائماً
+
+112
+00:08:06,580 --> 00:08:10,900
+دائماً في عملية، وهنا في كمان واحد، دائماً في عملية
+
+113
+00:08:10,900 --> 00:08:14,620
+الدمج، بروح
+
+114
+00:08:14,620 --> 00:08:18,140
+بدور، لما بتكلم عن الـ Single Linkage، بروح بدور على
+
+115
+00:08:18,140 --> 00:08:20,820
+أقصر مسافة، هدول أقرب نقطتين، بحسب الـ Distance بينهم
+
+116
+00:08:21,540 --> 00:08:24,920
+هو كيف بده يدور على أنه أقرب نقطتين؟ هو فعلياً بتم
+
+117
+00:08:24,920 --> 00:08:28,340
+حسب الـ Distance ما بين كل العناصر اللي في الـ
+
+118
+00:08:28,340 --> 00:08:31,800
+Clusters، يعني النقطة هذه مع كل العناصر اللي موجودة
+
+119
+00:08:31,800 --> 00:08:37,660
+هنا، وبيعتمد أقصر مسافة، النقطة مع كل العناصر، كل النقاط
+
+120
+00:08:37,660 --> 00:08:40,880
+اللي هنا مع كل النقاط اللي هنا، وبيعتمد أقصر مسافة،
+
+121
+00:08:40,880 --> 00:08:46,220
+وبالتالي، لو أنا هذه النقطة هيروح يحسبها مع هذول
+
+122
+00:08:46,220 --> 00:08:50,440
+كمان، وبيعتمد هذه أقصر مسافة، الآن هي مسافة هذين،
+
+123
+00:08:50,440 --> 00:08:54,460
+ثلاثة، هدول أقصر، أقصر واحدة فيهم، هذه، بيروح
+
+124
+00:08:54,460 --> 00:09:00,800
+بعمل دمج لمين؟ لهذول، اصحاب Single Linkage، بتمنى
+
+125
+00:09:00,800 --> 00:09:02,260
+تكون الفكرة وصلت
+
+126
+00:09:12,500 --> 00:09:15,880
+الـ Criterion الثاني اللي موجودة عندي أنا اللي هي
+
+127
+00:09:15,880 --> 00:09:21,140
+الـ Average، والـ Average هنا بتتكلم على أنه أنا
+
+128
+00:09:21,140 --> 00:09:24,500
+بيعمل Merge لـ Two Clusters، اللي بيكون Shortest
+
+129
+00:09:24,500 --> 00:09:28,820
+Average Distance، Shortest Average Distance، يعني
+
+130
+00:09:28,820 --> 00:09:36,200
+ايش اللي حيصير؟ بعد ما راح حسب كل الـ Distances بين
+
+131
+00:09:36,200 --> 00:09:37,060
+كل النقاط،
+
+132
+00:09:58,300 --> 00:10:01,740
+بين كل النقاط، ايش بروح بيساوي؟ بياخد الـ Average
+
+133
+00:10:01,740 --> 00:10:05,660
+تبعت الـ Distance، لاحظوا أنا في كل مرة بيعمل
+
+134
+00:10:05,660 --> 00:10:09,540
+Marriage لـ Two Clusters فقط، تمام؟ بيعمل Marriage لـ
+
+135
+00:10:09,540 --> 00:10:13,680
+Two Clusters فقط، فهو بيروح بيحسب كل الـ Averages أو
+
+136
+00:10:13,680 --> 00:10:17,520
+بيحسب كل الـ Distances وبياخد الـ Average في الـ
+
+137
+00:10:17,520 --> 00:10:20,080
+Simple Linkage، أو عفواً في الـ Single، أنا غلطان هنا
+
+138
+00:10:20,080 --> 00:10:23,260
+في الكتابة، طبعاً Simple Linkage
+
+139
+00:10:38,990 --> 00:10:50,390
+Single، Single Linkage، سامحوني،
+
+140
+00:10:50,390 --> 00:10:54,090
+هذه أسهل حاجة أعملها الآن، لأن أنا حولت لصورة، و
+
+141
+00:10:54,090 --> 00:11:04,190
+ما بدي أرجع أُعيد نفس ال... Okay، Shift
+
+142
+00:11:04,190 --> 00:11:08,490
+F5، بنتكلم هنا إنه أنا بتكلم على الـ Single Linkage،
+
+143
+00:11:08,490 --> 00:11:12,010
+أخذت أقصر، لكن هون حسبت كل النقاط، وبالتالي أخذت الـ
+
+144
+00:11:12,010 --> 00:11:14,570
+Average، عشان إذا حاولت أرسم السهم هون، يمثل للـ
+
+145
+00:11:14,570 --> 00:11:21,990
+Center تبع الـ Clusters اللي موجودين عندنا، هذه
+
+146
+00:11:21,990 --> 00:11:28,730
+الـ Average، بالنسبة للـ... للـ Complete، بياخد الـ
+
+147
+00:11:28,730 --> 00:11:34,150
+Maximum Linkage، بياخد... بيعتمد... من وين؟ أطول...
+
+148
+00:11:34,150 --> 00:11:39,200
+أبعد نقطتين، أقصر مسافة بين أبعد نقطتين، بروح، بروح
+
+149
+00:11:39,200 --> 00:11:42,100
+مالهم، جنب
+
+150
+00:11:43,400 --> 00:11:47,280
+يعني لو أنا أجيت هنا، هذه العناصر اللي موجودة عندنا،
+
+151
+00:11:47,280 --> 00:11:50,480
+بحسب كل الـ Distances اللي موجودة عندنا، بكل
+
+152
+00:11:50,480 --> 00:11:55,060
+الاتجاهات، مع كل الـ Clusters، هذه أقصر... يعني هدول
+
+153
+00:11:55,060 --> 00:11:58,580
+أبعد نقطتين، نعم، لكن هذه الـ Distance اللي بين الـ Two
+
+154
+00:11:58,580 --> 00:12:03,040
+Clusters هدول، هي عبارة عن أقصر مسافة، مماثلة مع
+
+155
+00:12:03,040 --> 00:12:06,200
+Different Clusters، فبقرر أنه يعمل Merge للـ
+
+156
+00:12:06,200 --> 00:12:11,060
+Clusters اللي موجودين عندنا، النوع الثالث اللي هو الـ
+
+157
+00:12:11,060 --> 00:12:15,020
+Ward، الـ Ward، الـ Ward، أو الـ Ward، لما أنا
+
+158
+00:12:15,020 --> 00:12:21,520
+بتكلم هنا، بتكلم عن الـ Ward، القسم هنا، بدور، النوبة هو
+
+159
+00:12:21,520 --> 00:12:27,820
+يعمل Merge لـ Two Clusters، لما يقلل
+
+160
+00:12:27,820 --> 00:12:31,160
+الـ Variance بين الـ Clusters الموجودة، يقلل
+
+161
+00:12:31,160 --> 00:12:35,080
+الاختلافات بين الـ Clusters، يعني هو الآن بيحسب كل
+
+162
+00:12:35,080 --> 00:12:39,460
+النقاط، كل الـ Distances اللي موجودة عنده، بيحسب كل
+
+163
+00:12:39,460 --> 00:12:43,380
+الـ Distances وبيحسب كل الـ Distances وبيحاول يشوف
+
+164
+00:12:43,380 --> 00:12:48,720
+مين أقرب Cluster في الاختلافات، في الـ Elements اللي
+
+165
+00:12:48,720 --> 00:12:53,240
+موجود عنده هون، وبيروح بدمجهم، يعني هو ايش بيروح
+
+166
+00:12:53,240 --> 00:12:54,420
+بساوي؟ بكل بساطة،
+
+167
+00:12:58,220 --> 00:13:01,320
+بعد ما بيروح بيحسب، بيحسب كل الـ Areas، بيحسب الـ Variance
+
+168
+00:13:01,320 --> 00:13:04,540
+هنا، الاختلاف، والـ Variance اللي هنا مع الـ Cluster
+
+169
+00:13:04,540 --> 00:13:09,200
+الثالث، الـ Variance وأقل Clusters في اختلاف الـ
+
+170
+00:13:09,200 --> 00:13:13,340
+Variance اللي بينهم، بيروح بدمجهم، ليش؟ عشان يحافظ على
+
+171
+00:13:13,340 --> 00:13:17,240
+التشابه ما بين الـ Two Different Clusters، يعني أنت
+
+172
+00:13:17,240 --> 00:13:21,220
+تخيل أن في عندك Cluster كبير جداً وعندك Cluster
+
+173
+00:13:21,220 --> 00:13:25,250
+صغير جداً، هدول الـ Two Clusters صعب أنهم يدمجوا، ليش؟
+
+174
+00:13:25,250 --> 00:13:28,690
+مع الـ Ward، لأنهم فعلياً الـ Variance تبعتهم عالية
+
+175
+00:13:28,690 --> 00:13:32,190
+جداً، فهو بيروح بدور على الـ Clusters المشابهة بداخله،
+
+176
+00:13:32,190 --> 00:13:36,730
+By Default، بالمناسبة الـ Ward هي الـ Default Linkage
+
+
+223
+00:17:09,140 --> 00:17:12,320
+Hierarchical Clustering نفس.. نفس الكلام، يعني أنه
+
+224
+00:17:12,320 --> 00:17:18,240
+يحتاج كل point أن تدخل برحلة أن تصبح cluster مستقلة
+
+225
+00:17:18,240 --> 00:17:22,860
+ذاتها، وستنتمي إلى آخر cluster، يعني هذا الفرق الأساسي
+
+226
+00:17:22,860 --> 00:17:26,000
+ما بين الـ agglomerative و الـ hierarchical.
+
+227
+00:17:26,000 --> 00:17:31,160
+الـ agglomerative فعلياً سيُدمجها لي، لكن في المحصلة
+
+228
+00:17:31,160 --> 00:17:34,280
+الأخيرة يا جماعة الخير، أنا حصلت على partitional
+
+229
+00:17:34,280 --> 00:17:37,920
+clustering. ملاحظين هنا، الرسمة الأخيرة في step 9 هي
+
+230
+00:17:37,920 --> 00:17:41,180
+عبارة عن partitional لأن ليس لديّ عناصر
+
+231
+00:17:51,050 --> 00:17:56,350
+لكن في الـ hierarchical، لا، أنا أستطيع أن أحافظ على أن
+
+232
+00:17:56,350 --> 00:18:02,330
+العناصر التابعة تكون disjoint حتى مستوى معين. طيب،
+
+233
+00:18:02,330 --> 00:18:05,870
+الآن، كما قلنا، هذه هي الرسمة التي يمكنني الاعتماد عليها.
+
+234
+00:18:05,870 --> 00:18:09,390
+هو أن أقول أن، والله، هذا ما أفهمه من هذه، أن كل
+
+235
+00:18:09,390 --> 00:18:16,390
+واحدة من هذه كانت بهذا الشكل: 1 و 4 اندمجت معهما 2 و
+
+236
+00:18:16,390 --> 00:18:22,090
+8، اندمجت معهما 3 و 5 مستقلة، 0 و 1 و 2 اندمجت معهما 5
+
+237
+00:18:22,090 --> 00:18:28,190
+و 6 و 9، اندمجت معهما 7 و 10، اندمجت معهما 7 و 10
+
+238
+00:18:28,190 --> 00:18:28,470
+اندماجت معهما 7 و 10 اندمجت معهما 7 و 10 اندمجت
+
+239
+00:18:28,470 --> 00:18:28,830
+معهما 7 و 10 اندمجت معهما 7 و 10 اندمجت معهما 7 و
+
+240
+00:18:28,830 --> 00:18:29,230
+10 اندمجت معهما 7 و 10 اندمجت معهما 7 و 10 اندمجت
+
+241
+00:18:29,230 --> 00:18:29,590
+10 اندمجت معهما 7 و 10 اندمجت معهما 7 و 10 اندمجت
+
+242
+00:18:29,590 --> 00:18:33,470
+معهما 7 و 10 اندمجت معهما 7 و 10 اندمجت معهما 7 و
+
+243
+00:18:33,470 --> 00:18:39,300
+10 اندمجت معهما 7 و 10. ولكن لو أخذت نظرة
+
+244
+00:18:39,300 --> 00:18:44,920
+جانبية، يعني أنني أتعرف على شئ اسمه الـ
+
+245
+00:18:44,920 --> 00:18:49,200
+Dendrogram. الـ Dendrogram عبارة عن رسم تخطيطي يخدمني
+
+246
+00:18:49,200 --> 00:18:55,140
+في فهمي للبيانات الموجودة.  الـ visualization
+
+247
+00:18:55,140 --> 00:18:58,080
+مهم جداً، لكي أستطيع أن أرى وأفهم العناصر التي
+
+248
+00:18:58,080 --> 00:19:03,620
+موجودة في موضوع الـ hierarchical clustering، والـ
+
+249
+00:19:03,620 --> 00:19:09,000
+dendrogram التي أرغب في تمثيلها، وبالتالي، ولما الـ
+
+250
+00:19:09,000 --> 00:19:13,000
+visualization يعطيني detailed view للـ hierarchical
+
+251
+00:19:13,000 --> 00:19:16,380
+clustering، فهذا يعني أنها ما زالت في البعدين
+
+252
+00:19:16,380 --> 00:19:22,180
+الأساسيين الموجودة، وبالتالي، أنا سأبقى أشتغل، و
+
+253
+00:19:22,180 --> 00:19:26,500
+سأبقى أسأل، وسنبقى نحاول أن نرسم الـ Dendrogram. أنتَ
+
+254
+00:19:26,500 --> 00:19:30,140
+تخيل الرسمة معي، لو ظهرت معي بهذا الشكل، طبعاً
+
+255
+00:19:30,140 --> 00:19:33,640
+هذان الرسمتان للـ Dendrogram هما الأساس الموجود
+
+256
+00:19:33,640 --> 00:19:36,640
+عندي هنا. الأولى، كما قلت لك، هي عبارة عن
+
+257
+00:19:36,640 --> 00:19:40,420
+الصورة العمودية من فوق، للـ clusters، ورأيت التجميعات
+
+258
+00:19:40,420 --> 00:19:45,020
+بينما هنا، أنا أتحدث عن أنني أرى البيانات كلها في
+
+259
+00:19:45,020 --> 00:19:49,240
+الـ 2D، أراها من نظرة جانبية، وهذه الرسمة هي عبارة
+
+260
+00:19:49,240 --> 00:19:52,520
+عن الـ Dendrogram. الآن، فكرة الـ Dendrogram أو الـ
+
+261
+00:19:52,520 --> 00:19:56,120
+Hierarchical Clustering الأساسية هي أنني أستطيع أن أحصي
+
+262
+00:19:56,120 --> 00:20:00,680
+على أي عدد من الـ clusters التي أحتاجها، يعني تخيل أنا
+
+263
+00:20:00,680 --> 00:20:04,620
+أحتاج three clusters، وسيبقى كل خط عمودي في الرسمة
+
+264
+00:20:04,620 --> 00:20:10,180
+يمثل cluster. أريد three clusters، ها هي. أريد اثنين،
+
+265
+00:20:10,180 --> 00:20:16,120
+ها هما. لاحظ؟ لماذا؟ لأنها فعلياً هذه كلها مع بعضها
+
+266
+00:20:17,510 --> 00:20:21,190
+عبارة عن cluster، وهذه مع بعضها عبارة عن cluster.
+
+267
+00:20:21,190 --> 00:20:27,750
+ثانياً، رسمت العمود مع العناصر الموجودة.  أريد
+
+268
+00:20:27,750 --> 00:20:34,750
+ثلاثة. هذه الثلاثة ستصبح مع بعضها. إذا
+
+269
+00:20:34,750 --> 00:20:39,770
+أنا أريد أن أتحدث عن three clusters، يعني هذا واحد،
+
+270
+00:20:39,770 --> 00:20:44,030
+العشرة معها طبعاً، اثنان،
+
+271
+00:20:48,010 --> 00:20:55,110
+و هذا ثلاثة. هل أريد أكثر؟ نعم، لكن ماذا أريد؟ أن أزال
+
+272
+00:20:55,110 --> 00:21:01,330
+الـ scale الخاص بعدد الـ clusters إلى الأسفل، إلى أين؟
+
+273
+00:21:01,330 --> 00:21:10,890
+أريد أن يكون مثلاً، لو أنزلت عدد الـ clusters إلى هنا،
+
+274
+00:21:10,890 --> 00:21:14,690
+يعني أنا أتحدث عن single cluster واحد.
+
+275
+00:21:17,600 --> 00:21:25,440
+لا، ليس واحداً. الآن، هذا عندك واحد، هذا
+
+276
+00:21:25,440 --> 00:21:32,020
+اثنان، هذا ثلاثة، عشرة على حالها، هذا أربعة. أنا هنا
+
+277
+00:21:32,020 --> 00:21:37,480
+أتحدث عن four clusters، بناءً على النقطة التي
+
+278
+00:21:37,480 --> 00:21:43,410
+اخترتها. أهم شيء في الموضوع أنه أنا فعلياً لما أحصل
+
+279
+00:21:43,410 --> 00:21:46,690
+على الـ dendrogram، أستطيع أن أحصل على أي عدد من الـ
+
+280
+00:21:46,690 --> 00:21:50,410
+clusters التي أريده. أريد أن أعود مرة أخرى لأقول والله
+
+281
+00:21:50,410 --> 00:21:57,490
+أنا هنا أريد.. لو افترضت أنني هنا، هذا الخط
+
+282
+00:21:57,490 --> 00:22:03,590
+الخاص بي، عفواً،
+
+283
+00:22:03,590 --> 00:22:05,630
+رسمتي غير دقيقة بعض الشيء.
+
+284
+00:22:12,280 --> 00:22:15,960
+لو مشيت هنا، وقلت هذا مع الاثنين هنا، أريد
+
+285
+00:22:15,960 --> 00:22:22,820
+أن أمشي، okay.
+
+286
+00:22:22,820 --> 00:22:26,240
+أفضل من الأول. لو سألتك عند هذا الخط، كم cluster
+
+287
+00:22:26,240 --> 00:22:29,940
+أحصل عليه؟ أستطيع أن أقول أنني أتحدث عن four clusters.
+
+288
+00:22:29,940 --> 00:22:41,220
+four clusters: هذا واحد، يجمع واحد وأربعة. ثانياً، ايوه،
+
+289
+00:22:45,790 --> 00:22:56,350
+الثالث، العشرة وحدها، والرابع، هذه. عفواً، ليس أربعة،
+
+290
+00:22:56,350 --> 00:23:03,050
+هذه خمسة، five clusters، خمسة
+
+291
+00:23:03,050 --> 00:23:07,890
+clusters. طبعاً، هناك فائدة أخرى من الـ dendrogram، أنا
+
+292
+00:23:07,890 --> 00:23:10,810
+أستطيع أن أفهم أنه على الرغم من أن الـ cluster
+
+293
+00:23:10,810 --> 00:23:14,590
+الأخير هذا، الذي فيه 7 و 6 و 9، هذه الـ elements
+
+294
+00:23:14,590 --> 00:23:16,610
+في نفس الـ cluster، إلا أنه من خلال الـ
+
+295
+00:23:16,610 --> 00:23:21,370
+dendrogram، أستطيع أن أفهم أن 6 و 9 instances أقرب
+
+296
+00:23:21,370 --> 00:23:26,150
+لبعض من 7. كذلك، 0 و 11 في الـ cluster
+
+297
+00:23:26,150 --> 00:23:32,370
+الثالث، و 2 و 8 في الـ cluster الثاني. لكي نستطيع
+
+298
+00:23:32,370 --> 00:23:36,790
+أن نطبق هذا المثال، في مثال مشهور جداً أخذته سابقاً من
+
+299
+00:23:36,790 --> 00:23:38,990
+الـ slide الخاصة بالدكتور علاء، جزاه الله خيراً،
+
+300
+00:23:38,990 --> 00:23:42,230
+المثال
+
+301
+00:23:42,230 --> 00:23:49,430
+المشهور أيضاً. أنا لديّ خريطة إيطاليا، وأريد
+
+302
+00:23:49,430 --> 00:23:56,280
+أن أعتبر أن المدن هذه بمثابة Clustering، هو أنا الـ
+
+303
+00:23:56,280 --> 00:23:59,660
+clusters، وأريد أن أذهب لأعمل بينها merge، لأرى
+
+304
+00:23:59,660 --> 00:24:05,020
+أقرب المدن لبعضها، باعتماد على الـ single linkage
+
+305
+00:24:05,020 --> 00:24:15,120
+criterion. single linkage criterion. الآن، عفواً، لما
+
+306
+00:24:15,120 --> 00:24:19,800
+أنا أتحدث، هذه رموز للولايات أو المدن في إيطاليا.
+
+307
+00:24:19,800 --> 00:24:22,980
+طبعاً، من ذهب إلى إيطاليا من بينكم؟ لأن أنتم
+
+308
+00:24:22,980 --> 00:24:30,150
+فرحانين.  لكن، بالطبع، بارما
+
+309
+00:24:30,150 --> 00:24:39,190
+ليست من ضمنها، أو موجودة. هي بارما. طيب، الآن فعلياً، الـ
+
+310
+00:24:39,190 --> 00:24:43,710
+contingency matrix، النتيجة التي ستحصل عليها عبارة عن
+
+311
+00:24:46,160 --> 00:24:50,160
+Symmetric Matrix، وفيها كل العناصر الموجودة
+
+312
+00:24:50,160 --> 00:24:57,900
+عندي هنا. وبناءً عليها، أنا أريد أن أقرر. الآن، بارما، بارما،
+
+313
+00:24:57,900 --> 00:25:04,620
+أقصر distance، أين؟ مع من؟ فأنا فعلياً أذهب لأبحث عن
+
+314
+00:25:04,620 --> 00:25:09,200
+الـ shortest distance. أنا الآن هنا، okay، 250، وأبدأ
+
+315
+00:25:09,200 --> 00:25:13,580
+أن أبحث. لكن، عندما وجدنا أن هناك مسافة أقصر منها موجودة،
+
+316
+00:25:13,580 --> 00:25:13,800
+أين؟
+
+317
+00:25:16,920 --> 00:25:23,360
+تربط Milano و TMI و TO، وبالتالي، هذه أقصر
+
+318
+00:25:23,360 --> 00:25:26,720
+ملاحظين يا جماعة الخير، أنا رأيت الـ distance مع
+
+319
+00:25:26,720 --> 00:25:31,300
+الكل، بين الكل.  لم أعتمد السفر، لأنها مدينة مع
+
+320
+00:25:31,300 --> 00:25:33,460
+نفسها. لا أريدها cluster مع نفسها، أو الـ
+
+321
+00:25:33,460 --> 00:25:38,160
+instance مع نفسها. لكن هنا، ذهبت لأبحث حتى وصلت إلى
+
+322
+00:25:38,160 --> 00:25:42,820
+مسافة أصغر، مسافة في كل المسافات الموجودة لديّ
+
+323
+00:25:42,820 --> 00:25:52,650
+هنا، وبالتالي، فعلياً هذه المسافة هنا، و
+
+324
+00:25:52,650 --> 00:26:01,150
+نفس الكلام، mi مع كل المدن، و fi مع كل المدن، كل الـ
+
+325
+00:26:01,150 --> 00:26:07,630
+possible distances حسبتها. يعني، إذا تكلمت من mi
+
+326
+00:26:07,630 --> 00:26:18,920
+إلى ba، mi إلى ba، هي ثمانمائة وسبعة وسبعون كيلومتراً. ففي النهاية
+
+327
+00:26:18,920 --> 00:26:21,980
+أنا أعتمد فقط على مسافة واحدة فقط، التي هي
+
+328
+00:26:21,980 --> 00:26:26,100
+shortest، لأن هذه الـ minimum distance، حسب الـ
+
+329
+00:26:26,100 --> 00:26:32,240
+linkage criteria.  معناته، أنا سأدمج الـ mi و الـ
+
+330
+00:26:32,240 --> 00:26:33,500
+to، تمام.
+
+331
+00:26:36,100 --> 00:26:41,560
+وهذا أول cluster حصلت عليه، سأسميه marriage رقم
+
+332
+00:26:41,560 --> 00:26:48,520
+1. ممتاز. فلما أنا أدمج MIT و MIT، MIT MIT MIT MIT MIT
+
+333
+00:26:48,520 --> 00:26:49,180
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+334
+00:26:49,180 --> 00:26:49,760
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+335
+00:26:49,760 --> 00:26:51,240
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+336
+00:26:51,240 --> 00:26:51,980
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+337
+00:26:51,980 --> 00:26:52,080
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+338
+00:26:52,080 --> 00:26:52,620
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+339
+00:26:52,620 --> 00:26:52,640
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+340
+00:26:52,640 --> 00:26:53,360
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+341
+00:26:53,360 --> 00:26:53,560
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+342
+00:26:53,560 --> 00:26:53,740
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+343
+00:26:53,740 --> 00:26:56,560
+MIT MIT MIT
+
+344
+00:27:06,430 --> 00:27:09,370
+ماذا عن علاقة الـ cluster الجديد هذا مع الـ
+
+345
+00:27:09,370 --> 00:27:10,950
+elements الأخرى؟
+
+346
+00:27:16,670 --> 00:27:21,730
+إن هذا هو الـ cluster. متفقون؟ الآن، الـ cluster الجديد
+
+347
+00:27:21,730 --> 00:27:25,690
+هذا، أنا سأتعامل معه، سأضع له قيمة تمثله،
+
+348
+00:27:25,690 --> 00:27:32,230
+تمثل علاقته، لأنه هذا عبارة عن cluster جديد. ما
+
+349
+00:27:32,230 --> 00:27:34,290
+هو الـ distance بين هذا الـ cluster وباقي الـ clusters
+
+350
+00:27:34,290 --> 00:27:38,770
+الأخرى؟ سآخذ الـ minimum distance ما بين كل
+
+351
+00:27:38,770 --> 00:27:43,410
+العناصر الموجودة. بمعنى، أقول كالتالي في السطر
+
+352
+00:27:43,410 --> 00:27:53,780
+الأول هنا، لما أريد أن أدمج أي و تي أو مع
+
+353
+00:27:53,780 --> 00:27:57,900
+الـ بي إي، هذه التي ستصبح one cluster. يعني هنا
+
+354
+00:27:57,900 --> 00:28:06,580
+هذا العمود سيبقى فارغاً مثلاً، وسأضع هنا تي أو و
+
+355
+00:28:06,580 --> 00:28:11,120
+مأي. بغض النظر عن من دمجت مع من، ليست قضية كبيرة.
+
+356
+00:28:11,120 --> 00:28:17,000
+تمام. الآن، الـ بي إي، لديّ مسافة، لديّ مسافتان،
+
+357
+00:28:17,000 --> 00:28:19,740
+أي منهما سآخذ؟ بما أنني ما زلت أعتمد على الـ
+
+358
+00:28:19,740 --> 00:28:22,840
+single linkage، معناته أنا سآخذ الـ shortest
+
+359
+00:28:22,840 --> 00:28:33,280
+distance. أي منهما أقصر؟ 877 أم 996؟ لا، 877 مع الـ FI. الآن
+
+360
+00:28:33,280 --> 00:28:41,920
+الـ FI، لديّ 295 و 400، سأعتمد 295. هذه ستبقى
+
+361
+00:28:41,920 --> 00:28:49,960
+صفر، لن تتغير. وحتى التي هي الأقصر. الآن، لديّ 457،
+
+362
+00:28:49,960 --> 00:28:53,100
+طبعاً هذا الخام أيضاً، أنا أحتاج أن أنهي منه. جامعة الخير،
+
+363
+00:28:53,100 --> 00:28:59,660
+لا تنسوا 754، ولدي 869،
+
+364
+00:28:59,660 --> 00:29:06,520
+سأعتمد هذه. ولدي 564،
+
+365
+00:29:06,520 --> 00:29:11,930
+سأعتمدها. وبالتالي، الجدول الجديد سيكون بهذا الشكل.
+
+366
+00:29:11,930 --> 00:29:17,770
+هذا، باقي الأرقام لم تتغير. أنا أنهيت من الصف والعمود
+
+367
+00:29:17,770 --> 00:29:21,890
+الذي كان يمثل الـ TO، واعتمدت على الـ shortest
+
+368
+00:29:21,890 --> 00:29:25,090
+distance الموجودة. إن شاء الله لم أخطئ الحساب.
+
+369
+00:29:25,090 --> 00:29:29,610
+ثمانمائة وسبعة وسبعون، ثنين، تسعة، خمسة، صفر.
+
+370
+00:29:37,510 --> 00:29:41,110
+أول عملية تمت، موجودة عندي، باعتماد على single
+
+371
+00:29:41,110 --> 00:29:41,510
+linkage.
+
+372
+00:29:44,500 --> 00:29:47,860
+أريد أن أكرر نفس العملية، لأعمل دمج، سأبدأ بالبحث عن
+
+373
+00:29:47,860 --> 00:29:52,500
+shortest distance. أي 255 في الصف الأول، هي أقصر
+
+374
+00:29:52,500 --> 00:29:57,600
+مسافة حتى اللحظة. 255،
+
+375
+00:29:57,600 --> 00:30:05,420
+هي الأقصر. 255، 255، 255 هي الأقصر. معناته، الآن أريد
+
+376
+00:30:05,420 --> 00:30:10,920
+أن نعمل دمج ما بين الـ NA و الـ BA. بنفس الكلام
+
+377
+00:30:10,920 --> 00:30:22,700
+السابق، سأنتهي من عمود الـ Na وصف الـ Na. تمام، علاقتهما
+
+378
+00:30:22,700 --> 00:30:28,580
+ستكون، سنضعهما في عمود واحد، أي distance التي احتفظت
+
+379
+00:30:28,580 --> 00:30:33,300
+بهما. الآن، هذه لن تتغير، لأنها ستأتي من العمود الذي
+
+380
+00:30:33,300 --> 00:30:40,140
+عندها بـ A، Na.
+
+381
+00:30:42,020 --> 00:30:46,560
+صفر. تمام، هذه عندها ستمائة واثنين وستين، ولديّ
+
+382
+00:30:46,560 --> 00:30:51,280
+أربعمائة وثمانية وستين. لا، سأعتمد المسافة الأقصر.
+
+383
+00:30:51,280 --> 00:30:59,140
+أربعمائة وثمانية وستين، عندها
+
+384
+00:30:59,140 --> 00:31:07,240
+ثمانمائة وسبعة وسبعون، وعندها سبعمائة وأربعة وخمسون،
+
+385
+00:31:07,240 --> 00:31:15,800
+سأعتمد السبعمائة وأربعة وخمسون. طبعاً، صفها سيلغى عند
+
+386
+00:31:15,800 --> 00:31:19,320
+هنا، أربعمائة واثنا عشر، ولدي اثنين وتسعون، سأعتمد
+
+387
+00:31:19,320 --> 00:31:24,780
+الاثنين وتسعون. لماذا؟ لأنني مرة أخرى أبحث عن
+
+388
+00:31:24,780 --> 00:31:30,300
+الـ single linkage، وبالتالي أنا أخطأت.
+
+389
+00:31:37,670 --> 00:31:45,690
+عفواً، أنا أخطأت هنا عند 219، لأنها أقصر. أنا آسف، ليس
+
+390
+00:31:45,690 --> 00:31:53,250
+كثيراً، يعني أقول أن الخطأ مردود، إن شاء الله، سأصحح. أقصر
+
+391
+00:31:53,250 --> 00:32:04,260
+مسافة لديّ فعلياً هي هذه،
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/5xZPpqSUrAA_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/5xZPpqSUrAA_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..2ded31168aeca22382bbe35d57a2f0569ae8af82
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/5xZPpqSUrAA_raw.json
@@ -0,0 +1 @@
+{"segments": [{"id": 1, "seek": 2797, "start": 2.65, "end": 27.97, "text": "باسم الله و الحمد لله الصلاة والسلام على رسول الله أهلا وسهلا بكم حضرتنا التالية في مساق تنقيب البيانات نتكلم على ال clustering كنا غطينا في chapter ال clustering مفهوم ال clustering أنه عبارة عن تقسيم ال data set اللي موجودة عندى لمجموعات بناء على ال similarities أو التشابه ما بين ال instances اللي موجودة فيها", "tokens": [3555, 32277, 2304, 21984, 4032, 21542, 2304, 3215, 24976, 3224, 31767, 15040, 3660, 16070, 3794, 37440, 15844, 12602, 3794, 12610, 21984, 5551, 3224, 15040, 46952, 3224, 15040, 4724, 24793, 11331, 11242, 43500, 8315, 16712, 6027, 10632, 8978, 47524, 995, 4587, 6055, 1863, 38436, 3555, 2423, 21292, 7649, 9307, 8717, 2655, 4117, 19528, 15844, 2423, 13630, 278, 9122, 8315, 32771, 9566, 1829, 8315, 8978, 7187, 2423, 13630, 278, 3714, 5172, 3224, 20498, 2423, 13630, 278, 14739, 3224, 6225, 3555, 9640, 3660, 18871, 6055, 4587, 3794, 32640, 2423, 1412, 992, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 7578, 32767, 7435, 2304, 45367, 9307, 44945, 16606, 15844, 2423, 24197, 34051, 16712, 8592, 16758, 3224, 19446, 49374, 2423, 14519, 13672, 1829, 3714, 29245, 23328, 3660, 8978, 11296], "avg_logprob": -0.15738407029740273, "compression_ratio": 1.9018867924528302, "no_speech_prob": 1.7881393432617188e-06, "words": [{"start": 2.65, "end": 2.97, "word": "باسم", "probability": 0.7498372395833334}, {"start": 2.97, "end": 3.07, "word": " الله", "probability": 0.96875}, {"start": 3.07, "end": 3.19, "word": " و", "probability": 0.5498046875}, {"start": 3.19, "end": 3.39, "word": " الحمد", "probability": 0.9344075520833334}, {"start": 3.39, "end": 3.71, "word": " لله", "probability": 0.9521484375}, {"start": 3.71, "end": 4.29, "word": " الصلاة", "probability": 0.8287760416666666}, {"start": 4.29, "end": 4.71, "word": " والسلام", "probability": 0.9308268229166666}, {"start": 4.71, "end": 4.93, "word": " على", "probability": 0.473388671875}, {"start": 4.93, "end": 5.27, "word": " رسول", 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تعالى", "probability": 0.9352213541666666}], "temperature": 1.0}, {"id": 4, "seek": 9082, "start": 67.84, "end": 90.82, "text": "عندما نتكلم عن hierarchical clustering يعني أننا نتكلم عن clustering تجميعي الفكرة فيه أنه عندما نتكلم عن agglomerative الهيراريكال أو الـ agglomerative السيان لأن كل الهيراريكال يتعلق بال agglomerative يعني تجميعي agglomerative cross-clustering عادة نشير لكل ال clustering algorithm", "tokens": [3615, 41260, 15042, 8717, 2655, 4117, 19528, 18871, 35250, 804, 596, 48673, 37495, 22653, 14739, 8315, 8717, 2655, 4117, 19528, 18871, 13630, 278, 6055, 7435, 2304, 40228, 1829, 27188, 4117, 25720, 8978, 3224, 14739, 3224, 43242, 15042, 8717, 2655, 4117, 19528, 18871, 623, 7191, 14301, 1166, 2423, 3224, 13546, 9640, 1829, 4117, 6027, 34051, 2423, 39184, 623, 7191, 14301, 1166, 21136, 1829, 7649, 5296, 33456, 28242, 2423, 3224, 13546, 9640, 1829, 4117, 6027, 7251, 2655, 30241, 4587, 20666, 623, 7191, 14301, 1166, 37495, 22653, 6055, 7435, 2304, 40228, 1829, 623, 7191, 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agglomerative", "probability": 0.7696533203125}, {"start": 79.56, "end": 81.84, "word": " السيان", "probability": 0.71435546875}, {"start": 81.84, "end": 82.04, "word": " لأن", "probability": 0.662353515625}, {"start": 82.04, "end": 82.32, "word": " كل", "probability": 0.7841796875}, {"start": 82.32, "end": 82.86, "word": " الهيراريكال", "probability": 0.95849609375}, {"start": 82.86, "end": 83.32, "word": " يتعلق", "probability": 0.72308349609375}, {"start": 83.32, "end": 83.6, "word": " بال", "probability": 0.453125}, {"start": 83.6, "end": 84.22, "word": " agglomerative", "probability": 0.74566650390625}, {"start": 84.22, "end": 85.04, "word": " يعني", "probability": 0.54156494140625}, {"start": 85.04, "end": 85.88, "word": " تجميعي", "probability": 0.9123046875}, {"start": 85.88, "end": 86.5, "word": " agglomerative", "probability": 0.82806396484375}, {"start": 86.5, "end": 86.86, "word": " cross", "probability": 0.5009765625}, {"start": 86.86, "end": 87.46, "word": "-clustering", "probability": 0.81591796875}, {"start": 87.46, "end": 88.28, "word": " عادة", "probability": 0.8751627604166666}, {"start": 88.28, "end": 88.88, "word": " نشير", "probability": 0.8395182291666666}, {"start": 88.88, "end": 89.34, "word": " لكل", "probability": 0.741455078125}, {"start": 89.34, "end": 89.58, "word": " ال", "probability": 0.71337890625}, {"start": 89.58, "end": 90.32, "word": " clustering", "probability": 0.31292724609375}, {"start": 90.32, "end": 90.82, "word": " algorithm", "probability": 0.82373046875}], "temperature": 1.0}, {"id": 5, "seek": 11264, "start": 92.3, "end": 112.64, "text": "التي تبني على نفس المبدأ، وهو تجميع البيانات اللي موجودة عندها فكرة الـ agglomerative clustering بشكل عام بتتركز أنه بيبدأ بعرف أن كل نقطة ك cluster مستقل وبعد ذلك يعمل merge أو combine لكل two similar clusters", "tokens": [6027, 31371, 6055, 3555, 22653, 15844, 8717, 36178, 9673, 44510, 10721, 12399, 37037, 2407, 6055, 7435, 2304, 40228, 2423, 21292, 7649, 9307, 13672, 1829, 3714, 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merge", "probability": 0.841796875}, {"start": 108.32, "end": 109.2, "word": " أو", "probability": 0.82666015625}, {"start": 109.2, "end": 109.78, "word": " combine", "probability": 0.91845703125}, {"start": 109.78, "end": 110.96, "word": " لكل", "probability": 0.943359375}, {"start": 110.96, "end": 111.26, "word": " two", "probability": 0.7197265625}, {"start": 111.26, "end": 111.84, "word": " similar", "probability": 0.93310546875}, {"start": 111.84, "end": 112.64, "word": " clusters", "probability": 0.67822265625}], "temperature": 1.0}, {"id": 6, "seek": 14282, "start": 114.38, "end": 142.82, "text": "بناء على ايش الـ Similarity Cluster معناته في عندي Similarity Distance او Similarity Function زي ما شوفناها في الـ Partitional لازم تطبق عندها وهذا الـ Similarity Function هي اللي هتكون معيار دمج أو رفض القبول دمج او رفض دمج ال two clusters اللي موجودين عندى طبعا و هذا الكلام بيستمر لحد ما يتوصى يتحقق عندي شرط توقف معين", "tokens": [3555, 1863, 16606, 15844, 1975, 1829, 8592, 2423, 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بيستمر", "probability": 0.9849853515625}, {"start": 136.66, "end": 137.04, "word": " لحد", "probability": 0.9384765625}, {"start": 137.04, "end": 137.16, "word": " ما", "probability": 0.9794921875}, {"start": 137.16, "end": 137.68, "word": " يتوصى", "probability": 0.73251953125}, {"start": 137.68, "end": 138.16, "word": " يتحقق", "probability": 0.97939453125}, {"start": 138.16, "end": 138.44, "word": " عندي", "probability": 0.6593017578125}, {"start": 138.44, "end": 140.82, "word": " شرط", "probability": 0.8111979166666666}, {"start": 140.82, "end": 141.46, "word": " توقف", "probability": 0.8732096354166666}, {"start": 141.46, "end": 142.82, "word": " معين", "probability": 0.985595703125}], "temperature": 1.0}, {"id": 7, "seek": 17110, "start": 143.44, "end": 171.1, "text": "شغل التوقف يكون عبارة عن عدد ال clusters اللي اتكلم عليه انا بدي اعمل دمش دمش دمش لحد ما اصل ل 3 clusters فعليا ال data اللي عندى هتبدأ من واحد واحد واحد واحد بعد هيك هيبدأ يتجمعوا اخر تجميع اللي ممكن اجاف عندها 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" هذه", "probability": 0.61767578125}, {"start": 713.32, "end": 714.62, "word": " أقصر", "probability": 0.76483154296875}, {"start": 714.62, "end": 714.8, "word": " يعني", "probability": 0.766357421875}, {"start": 714.8, "end": 715.06, "word": " هدول", "probability": 0.8089192708333334}, {"start": 715.06, "end": 715.4, "word": " أبعد", "probability": 0.8854166666666666}, {"start": 715.4, "end": 715.92, "word": " نقطين", "probability": 0.9013671875}, {"start": 715.92, "end": 716.2, "word": " نعم", "probability": 0.968017578125}, {"start": 716.2, "end": 716.64, "word": " لكن", "probability": 0.796875}, {"start": 716.64, "end": 717.04, "word": " هدى", "probability": 0.4126790364583333}, {"start": 717.04, "end": 717.1, "word": " ال", "probability": 0.95703125}, {"start": 717.1, "end": 717.52, "word": " distance", "probability": 0.95556640625}, {"start": 717.52, "end": 717.74, "word": " اللي", "probability": 0.84130859375}, {"start": 717.74, "end": 718.04, "word": " بين", "probability": 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بدور النوبل", "tokens": [6027, 1863, 45367, 16712, 6027, 2655, 13672, 1829, 31439, 2423, 1349, 2423, 1349, 2423, 1349, 1975, 2407, 2423, 1349, 2423, 1349, 5296, 15042, 1975, 8315, 39894, 4117, 19528, 34105, 39894, 4117, 19528, 18871, 2423, 1349, 25062, 38251, 34105, 47525, 13063, 28239, 2407, 36150], "avg_logprob": -0.2382812544026158, "compression_ratio": 2.043010752688172, "no_speech_prob": 0.0, "words": [{"start": 729.74, "end": 730.16, "word": "النوع", "probability": 0.9772135416666666}, {"start": 730.16, "end": 730.64, "word": " التالت", "probability": 0.9833984375}, {"start": 730.64, "end": 730.8, "word": " اللي", "probability": 0.64208984375}, {"start": 730.8, "end": 730.94, "word": " هو", "probability": 0.990234375}, {"start": 730.94, "end": 731.06, "word": " ال", "probability": 0.8291015625}, {"start": 731.06, "end": 731.32, "word": " word", "probability": 0.90869140625}, {"start": 731.32, "end": 731.94, "word": " ال", "probability": 0.27587890625}, {"start": 731.94, "end": 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يعني انت تخيل ان في عندك cluster كبير جدا و عندك cluster صغير جدا", "tokens": [3555, 22488, 19446, 4724, 32887, 5016, 4724, 5016, 35457, 4724, 5016, 35457, 28242, 2423, 3179, 4724, 5016, 35457, 2423, 21977, 34105, 33688, 46456, 15040, 5172, 4032, 2423, 21977, 13672, 1829, 34105, 20449, 2423, 13630, 16712, 6027, 2655, 2423, 21977, 4032, 5551, 4587, 1211, 23313, 8978, 1975, 46456, 15040, 5172, 2423, 21977, 13672, 1829, 49374, 16095, 4724, 32887, 5016, 47525, 2304, 7435, 16095, 32239, 8592, 6225, 8592, 7649, 7251, 5016, 31845, 19913, 15844, 16712, 8592, 16758, 3224, 19446, 49374, 2423, 732, 819, 23313, 37495, 22653, 16472, 2655, 6055, 9778, 26895, 16472, 8978, 43242, 4117, 13630, 9122, 3555, 13546, 10874, 28259, 4032, 43242, 4117, 13630, 20328, 17082, 13546, 10874, 28259], "avg_logprob": -0.1922305095086404, "compression_ratio": 2.0043103448275863, "no_speech_prob": 0.0, "words": [{"start": 778.22, "end": 778.56, "word": "بعد", "probability": 0.729248046875}, {"start": 778.56, "end": 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بداخله by default بالمناسبة ال word هي ال default linkage cluster المول وعادة لما انا بأتكلم على ال word linkage criteria", "tokens": [3224, 3215, 12610, 2423, 732, 23313, 20328, 3615, 3555, 16472, 16095, 7251, 40448, 7435, 14407, 32239, 8592, 22807, 20449, 2423, 1349, 5296, 33456, 16095, 6156, 3615, 20292, 995, 2423, 21977, 6055, 3555, 34268, 16095, 6225, 6027, 10632, 10874, 28259, 6156, 3224, 2407, 4724, 32887, 5016, 47525, 13063, 15844, 2423, 23313, 9673, 8592, 16758, 3224, 3660, 47525, 47283, 43761, 538, 7576, 20666, 2304, 8315, 35457, 3660, 2423, 1349, 39896, 2423, 7576, 49118, 13630, 9673, 12610, 4032, 3615, 18513, 3660, 5296, 15042, 1975, 8315, 4724, 10721, 2655, 4117, 19528, 15844, 2423, 1349, 49118, 11101], "avg_logprob": -0.24378360022780715, "compression_ratio": 1.669603524229075, "no_speech_prob": 0.0, "words": [{"start": 802.67, "end": 803.07, "word": "هدول", "probability": 0.60589599609375}, {"start": 803.07, "end": 803.19, "word": " ال", "probability": 0.814453125}, 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هدول التلاتة بصيروا مع بعضهم إذا أنا بدي أتكلم على three clusters يعني هاي واحد العشرة معاهم طبعا اتنين", "tokens": [3615, 3555, 9640, 3660, 18871, 13630, 37037, 3215, 12610, 20449, 45030, 11242, 6225, 3555, 9640, 3660, 18871, 13630, 6055, 7649, 1829, 12602, 38251, 2655, 18863, 2304, 23328, 20449, 18863, 1863, 33546, 2288, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 11296, 47525, 4117, 6055, 1211, 9307, 3660, 8032, 3215, 12610, 16712, 1211, 9307, 3660, 4724, 9381, 13546, 14407, 20449, 45030, 11242, 16095, 11933, 15730, 41850, 4724, 16254, 5551, 2655, 4117, 19528, 15844, 1045, 23313, 37495, 22653, 8032, 47302, 36764, 24401, 18863, 8592, 25720, 20449, 995, 16095, 23032, 3555, 3615, 995, 1975, 2655, 1863, 9957], "avg_logprob": -0.22556516559834175, "compression_ratio": 1.7755102040816326, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 1217.51, "end": 1218.01, "word": "عبارة", "probability": 0.819091796875}, {"start": 1218.01, "end": 1218.19, "word": " عن", "probability": 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الرابع هايه هدول عفوا مش أربع هدول خمسة خمسة clusters خمسة clusters", "tokens": [6027, 12984, 6027, 12984, 18863, 8592, 25720, 5296, 5016, 6027, 4032, 34892, 16758, 3615, 8032, 47302, 3224, 8032, 3215, 12610, 6225, 5172, 14407, 37893, 5551, 25513, 3615, 8032, 3215, 12610, 16490, 2304, 3794, 3660, 16490, 2304, 3794, 3660, 23313, 16490, 2304, 3794, 3660, 23313], "avg_logprob": -0.3203125132454766, "compression_ratio": 1.4356435643564356, "no_speech_prob": 0.0, "words": [{"start": 1365.79, "end": 1366.55, "word": "الثالث", "probability": 0.61114501953125}, {"start": 1366.55, "end": 1368.55, "word": " العشرة", "probability": 0.6824544270833334}, {"start": 1368.55, "end": 1369.05, "word": " لحال", "probability": 0.7402750651041666}, {"start": 1369.05, "end": 1371.79, "word": " و", "probability": 0.36865234375}, {"start": 1371.79, "end": 1372.89, "word": " الرابع", "probability": 0.923828125}, {"start": 1372.89, "end": 1373.69, "word": " هايه", "probability": 0.3976236979166667}, {"start": 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2113.53, "word": " راجعوا", "probability": 0.8455810546875}, {"start": 2113.53, "end": 2113.91, "word": " المثال", "probability": 0.9485677083333334}, {"start": 2113.91, "end": 2114.29, "word": " حاولوا", "probability": 0.9278564453125}, {"start": 2114.29, "end": 2114.59, "word": " اقطعوه", "probability": 0.61346435546875}, {"start": 2114.59, "end": 2114.71, "word": " على", "probability": 0.849609375}, {"start": 2114.71, "end": 2115.03, "word": " ورقة", "probability": 0.94921875}, {"start": 2115.03, "end": 2115.17, "word": " من", "probability": 0.98291015625}, {"start": 2115.17, "end": 2115.27, "word": " ال", "probability": 0.79052734375}, {"start": 2115.27, "end": 2115.69, "word": " slides", "probability": 0.86328125}, {"start": 2115.69, "end": 2116.93, "word": " وطبقوه", "probability": 0.820068359375}, {"start": 2116.93, "end": 2117.41, "word": " لوحدكم", "probability": 0.7888997395833334}, {"start": 2117.41, "end": 2117.71, "word": " عشان", "probability": 0.9454752604166666}, {"start": 2117.71, "end": 2118.25, "word": " ترسخ", "probability": 0.9468994140625}, {"start": 2118.25, "end": 2119.05, "word": " الأمور", "probability": 0.9420572916666666}, {"start": 2119.05, "end": 2119.29, "word": " ان", "probability": 0.67431640625}, {"start": 2119.29, "end": 2119.45, "word": " شاء", "probability": 0.981201171875}, {"start": 2119.45, "end": 2119.49, "word": " الله", "probability": 0.87939453125}, {"start": 2119.49, "end": 2119.59, "word": " او", "probability": 0.770263671875}, {"start": 2119.59, "end": 2119.69, "word": " ان", "probability": 0.7880859375}, {"start": 2119.69, "end": 2119.79, "word": " شاء", "probability": 0.977294921875}, {"start": 2119.79, "end": 2119.85, "word": " الله", "probability": 0.93359375}, {"start": 2119.85, "end": 2120.13, "word": " بقدر", "probability": 0.9249674479166666}, {"start": 2120.13, "end": 2120.57, "word": " ازودكم", "probability": 0.8560791015625}, {"start": 2120.57, "end": 2121.03, "word": " مثال", "probability": 0.93115234375}, {"start": 2121.03, "end": 2121.67, "word": " تاني", "probability": 0.8802083333333334}, {"start": 2121.67, "end": 2122.47, "word": " عامة", "probability": 0.7701822916666666}, {"start": 2122.47, "end": 2122.95, "word": " قريب", "probability": 0.96337890625}, {"start": 2122.95, "end": 2123.63, "word": " تظل", "probability": 0.6746419270833334}, {"start": 2123.63, "end": 2123.83, "word": " عندنا", "probability": 0.932861328125}, {"start": 2123.83, "end": 2124.23, "word": " جزئية", "probability": 0.9373779296875}, {"start": 2124.23, "end": 2124.69, "word": " واحدة", "probability": 0.9816080729166666}, {"start": 2124.69, "end": 2124.87, "word": " في", "probability": 0.962890625}, {"start": 2124.87, "end": 2125.05, "word": " ال", "probability": 0.52783203125}, {"start": 2125.05, "end": 2125.37, "word": " chapter", "probability": 0.76171875}, {"start": 2125.37, "end": 2125.73, "word": " هذا", "probability": 0.85498046875}, {"start": 2125.73, "end": 2125.87, "word": " اللي", "probability": 0.835693359375}, {"start": 2125.87, "end": 2126.05, "word": " هي", "probability": 0.90966796875}, {"start": 2126.05, "end": 2126.69, "word": " جزئية", "probability": 0.9658203125}, {"start": 2126.69, "end": 2126.91, "word": " ال", "probability": 0.71240234375}, {"start": 2126.91, "end": 2127.49, "word": " evaluation", "probability": 0.97314453125}, {"start": 2127.49, "end": 2127.83, "word": " لل", "probability": 0.5908203125}, {"start": 2127.83, "end": 2128.49, "word": " clustering", "probability": 0.669921875}, {"start": 2128.49, "end": 2128.95, "word": " طبعا", "probability": 0.9766845703125}, {"start": 2128.95, "end": 2129.55, "word": " مش", "probability": 0.29736328125}, {"start": 2129.55, "end": 2130.13, "word": " مويلة", "probability": 0.8958740234375}, {"start": 2130.13, "end": 2130.53, "word": " هتكون", "probability": 0.85595703125}, {"start": 2130.53, "end": 2130.65, "word": " ان", "probability": 0.8779296875}, {"start": 2130.65, "end": 2130.75, "word": " شاء", "probability": 0.98583984375}, {"start": 2130.75, "end": 2130.81, "word": " الله", "probability": 0.93310546875}, {"start": 2130.81, "end": 2131.19, "word": " تعالى", "probability": 0.9202473958333334}, {"start": 2131.19, "end": 2131.93, "word": " لكن", "probability": 0.837890625}, {"start": 2131.93, "end": 2132.21, "word": " بدنا", "probability": 0.491943359375}, {"start": 2132.21, "end": 2132.55, "word": " نحاول", "probability": 0.983642578125}, {"start": 2132.55, "end": 2133.57, "word": " نركز", "probability": 0.8893229166666666}, {"start": 2133.57, "end": 2133.97, "word": " فيها", "probability": 0.9921875}, {"start": 2133.97, "end": 2134.65, "word": " مع", "probability": 0.8974609375}, {"start": 2134.65, "end": 2134.87, "word": " انه", "probability": 0.71044921875}, {"start": 2134.87, "end": 2135.05, "word": " بدي", "probability": 0.478515625}, {"start": 2135.05, "end": 2135.31, "word": " احاول", "probability": 0.894775390625}, {"start": 2135.31, "end": 2135.67, "word": " اخفف", "probability": 0.871337890625}, {"start": 2135.67, "end": 2135.93, "word": " عليكم", "probability": 0.953369140625}, {"start": 2135.93, "end": 2136.05, "word": " في", "probability": 0.94775390625}, {"start": 2136.05, "end": 2136.23, "word": " بعض", "probability": 0.992919921875}, {"start": 2136.23, "end": 2136.83, "word": " العمليات", "probability": 0.72052001953125}, {"start": 2136.83, "end": 2137.51, "word": " الحسابية", "probability": 0.987548828125}, {"start": 2137.51, "end": 2138.13, "word": " السلام", "probability": 0.866943359375}, {"start": 2138.13, "end": 2138.47, "word": " عليكم", "probability": 0.950927734375}, {"start": 2138.47, "end": 2138.87, "word": " ورحمة", "probability": 0.8975830078125}, {"start": 2138.87, "end": 2139.05, "word": " الله", "probability": 0.96826171875}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 2139.6491875, "duration_after_vad": 1983.126249999995}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/5xZPpqSUrAA_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/5xZPpqSUrAA_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..8550d17c75889b38863e8e8fa8fcae031e1cd86c
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+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/5xZPpqSUrAA_raw.srt
@@ -0,0 +1,1764 @@
+1
+00:00:02,650 --> 00:00:05,590
+باسم الله و الحمد لله الصلاة والسلام على رسول الله
+
+2
+00:00:05,590 --> 00:00:11,630
+أهلا وسهلا بكم حضرتنا التالية في مساق تنقيب
+
+3
+00:00:11,630 --> 00:00:15,350
+البيانات نتكلم على ال clustering كنا غطينا في
+
+4
+00:00:15,350 --> 00:00:17,530
+chapter ال clustering مفهوم ال clustering أنه
+
+5
+00:00:17,530 --> 00:00:20,970
+عبارة عن تقسيم ال data set اللي موجودة عندى
+
+6
+00:00:20,970 --> 00:00:25,570
+لمجموعات بناء على ال similarities أو التشابه ما
+
+7
+00:00:25,570 --> 00:00:29,680
+بين ال instances اللي موجودة فيهاو ذكرنا ان ال
+
+8
+00:00:29,680 --> 00:00:33,140
+clusterings ياخد واحدة من نوعين اما partitional
+
+9
+00:00:33,140 --> 00:00:36,540
+clusterings و هي عبارة عن مجموعة من ال clusters او
+
+10
+00:00:36,540 --> 00:00:39,980
+نعم مجموعة من ال clusters اللي بيكون ال disjoint
+
+11
+00:00:39,980 --> 00:00:42,920
+او التقاطعات بينهم صفر مافيش نقاط مشترك ما بينهم
+
+12
+00:00:42,920 --> 00:00:48,440
+وبالتالي كل element موجود في cluster واحد فقط وفي
+
+13
+00:00:48,440 --> 00:00:51,760
+عندنا حكينا انه في عندنا .. وشوفنا على المثال هذا
+
+14
+00:00:51,760 --> 00:00:56,360
+على مثل partitional k-means واتكلمنا عليه بالتفصيل
+
+15
+00:00:57,340 --> 00:01:00,400
+هو المحاضرة ان شاء الله تبارك وتعالى هنتكلم على
+
+16
+00:01:00,400 --> 00:01:03,960
+النوع التاني من ال clustering اللي هو ال
+
+17
+00:01:03,960 --> 00:01:08,840
+hierarchical clustering ان شاء الله تعالىعندما
+
+18
+00:01:08,840 --> 00:01:11,580
+نتكلم عن hierarchical clustering يعني أننا نتكلم
+
+19
+00:01:11,580 --> 00:01:16,640
+عن clustering تجميعي الفكرة فيه أنه عندما نتكلم عن
+
+20
+00:01:16,640 --> 00:01:19,560
+agglomerative الهيراريكال أو الـ agglomerative
+
+21
+00:01:19,560 --> 00:01:24,220
+السيان لأن كل الهيراريكال يتعلق بال agglomerative
+
+22
+00:01:24,220 --> 00:01:28,280
+يعني تجميعي agglomerative cross-clustering عادة
+
+23
+00:01:28,280 --> 00:01:33,440
+نشير لكل ال clustering algorithmالتي تبني على نفس
+
+24
+00:01:33,440 --> 00:01:38,200
+المبدأ، وهو تجميع البيانات اللي موجودة عندها فكرة
+
+25
+00:01:38,200 --> 00:01:41,920
+الـ agglomerative clustering بشكل عام بتتركز أنه
+
+26
+00:01:41,920 --> 00:01:47,120
+بيبدأ بعرف أن كل نقطة ك cluster مستقل وبعد ذلك
+
+27
+00:01:47,120 --> 00:01:54,720
+يعمل merge أو combine لكل two similar clustersبناء
+
+28
+00:01:54,720 --> 00:01:57,080
+على ايش الـ Similarity Cluster معناته في عندي
+
+29
+00:01:57,080 --> 00:02:00,800
+Similarity Distance او Similarity Function زي ما
+
+30
+00:02:00,800 --> 00:02:04,180
+شوفناها في الـ Partitional لازم تطبق عندها وهذا
+
+31
+00:02:04,180 --> 00:02:08,500
+الـ Similarity Function هي اللي هتكون معيار دمج أو
+
+32
+00:02:08,500 --> 00:02:12,660
+رفض القبول دمج او رفض دمج ال two clusters اللي
+
+33
+00:02:12,660 --> 00:02:17,680
+موجودين عندى طبعا و هذا الكلام بيستمر لحد ما يتوصى
+
+34
+00:02:17,680 --> 00:02:25,300
+يتحقق عندي شرط توقف معينشغل التوقف يكون عبارة عن
+
+35
+00:02:25,300 --> 00:02:29,980
+عدد ال clusters اللي اتكلم عليه انا بدي اعمل دمش
+
+36
+00:02:29,980 --> 00:02:35,040
+دمش دمش لحد ما اصل ل 3 clusters فعليا ال data اللي
+
+37
+00:02:35,040 --> 00:02:38,820
+عندى هتبدأ من واحد واحد واحد واحد بعد هيك هيبدأ
+
+38
+00:02:38,820 --> 00:02:43,900
+يتجمعوا اخر تجميع اللي ممكن اجاف عندها لهي مفهوم
+
+39
+00:02:43,900 --> 00:02:46,140
+ان يكون عندى 3 clusters او 4 clusters او 10
+
+40
+00:02:46,140 --> 00:02:49,300
+clusters حسب الحاجة وبهيك انا فعليا هذا شرطي
+
+41
+00:02:49,300 --> 00:02:55,280
+التوقف اللي موجود عندهاأو فعلياً أنا فعلياً ماضلش
+
+42
+00:02:55,280 --> 00:02:59,060
+عندي شغلة أني أدمجها اندمجت كل البيانات لحد ما
+
+43
+00:02:59,060 --> 00:03:02,540
+صارت only one cluster بيحتوي كل ال sub clusters
+
+44
+00:03:02,540 --> 00:03:06,020
+اللي جاية بعد هيك طبعاً أنا في عندي linkage
+
+45
+00:03:06,020 --> 00:03:10,820
+criteria أو شرط الدمج أو سمينا linkage دلالة على
+
+46
+00:03:10,820 --> 00:03:13,760
+أنه أنا فعلياً ا cluster و بده أربطهم مع بعض بده
+
+47
+00:03:13,760 --> 00:03:18,860
+أحطهم في قالب أو عفوا في ضمن boundary واحدةطبعاً
+
+48
+00:03:18,860 --> 00:03:21,420
+عندما أتكلم عن الـ linkage criteria أو الـ linkage
+
+49
+00:03:21,420 --> 00:03:25,800
+function نفس المصطلح الـ similarity function للـ
+
+50
+00:03:25,800 --> 00:03:28,660
+clusters بس دائما عندما أتكلم عن ال similarity
+
+51
+00:03:28,660 --> 00:03:32,160
+بتكلم عن ال distance عفوا، بتكلم عن ال distance
+
+52
+00:03:32,160 --> 00:03:36,160
+لكن عندما أتكلم عن ال linkage criteria بتكلم عن ان
+
+53
+00:03:36,160 --> 00:03:41,840
+انا فعاليا بتكلم عن ال clustering بتكلم عن linkage
+
+54
+00:03:41,840 --> 00:03:45,040
+أو ربط ما بين ال clusters فعليا أنا بتكلم برضه عن
+
+55
+00:03:45,040 --> 00:03:49,410
+ال distanceوالـ distance هذه بتقاس مع كل ال
+
+56
+00:03:49,410 --> 00:03:52,090
+observations أو كل ال instances اللي موجودة عنده
+
+57
+00:03:52,090 --> 00:03:56,390
+وين في داخل ال cluster اللي موجود عندها فعليا انا
+
+58
+00:03:56,390 --> 00:04:03,710
+في عندي المجموعة من ال linkage criteriaوهذه الـ
+
+59
+00:04:03,710 --> 00:04:07,470
+linkage criteria بتحدد فعليًا هل هدول ال clusters
+
+60
+00:04:07,470 --> 00:04:13,390
+similar أم لا وبالتالي يعني بالخلاصة فكرة ال
+
+61
+00:04:13,390 --> 00:04:16,590
+agglomerative أو ال hierarchical clustering بتبدأ
+
+62
+00:04:16,590 --> 00:04:20,890
+أن كل نقطة عبارة عن cluster مستقل وبعد هيك بصير
+
+63
+00:04:20,890 --> 00:04:25,810
+ادمج ما بين كل two clustersالشرط الدمج أنه في عندى
+
+64
+00:04:25,810 --> 00:04:28,530
+شغل بنسميها ال linkage criteria أو ال linkage
+
+65
+00:04:28,530 --> 00:04:31,610
+distance أو ال linkage function اللي هي شرط الدمج
+
+66
+00:04:31,610 --> 00:04:36,270
+هنا وهي عبارة عن distance major لكن مش مع نقطة مع
+
+67
+00:04:36,270 --> 00:04:39,250
+cluster وبالتالي ممكن انا اخد نقطة نوبة على ال
+
+68
+00:04:39,250 --> 00:04:43,350
+cluster ممكن اخد الكل cluster وحنشوف ال different
+
+69
+00:04:43,350 --> 00:04:49,630
+linkage criterionاللي موجودة عندنا نبدأ مع اول ال
+
+70
+00:04:49,630 --> 00:04:54,590
+linkage criteria ال criteria اللي هي ال criterion
+
+71
+00:04:54,590 --> 00:04:57,450
+اللي هي ال single و لما انا بتكلم على single
+
+72
+00:04:57,450 --> 00:05:04,970
+linkage بتكلم انه انا فعليا بادور على اقصر pair
+
+73
+00:05:04,970 --> 00:05:09,500
+يعني بين جثين عمالي بأحسنالـ point اللي انا فيه
+
+74
+00:05:09,500 --> 00:05:13,940
+عندى two clusters زي .. زي ما ال .. اوكي خليني مش
+
+75
+00:05:13,940 --> 00:05:17,180
+مشكلة برجع فيه عندى انا هنا two clusters two
+
+76
+00:05:17,180 --> 00:05:20,600
+clusters و في ال two clusters هدول انا بروح بادور
+
+77
+00:05:20,600 --> 00:05:25,220
+على كل النقاط يعني بحسب النقطة هاي مع كل ال
+
+78
+00:05:25,220 --> 00:05:28,180
+distances الموجودة في كل الأحوال يا جماعة الخير ال
+
+79
+00:05:28,180 --> 00:05:34,420
+distances هتنحسب ما بين كل عناصرالـ cluster و كذلك
+
+80
+00:05:34,420 --> 00:05:38,380
+high يعني انت تخيلها fully connected distances او
+
+81
+00:05:38,380 --> 00:05:41,580
+تخيلوها معايا fully connected area فبتحسب كل ال
+
+82
+00:05:41,580 --> 00:05:46,920
+distances اللي موجودة عندها الان ال pair pair of
+
+83
+00:05:46,920 --> 00:05:51,820
+clusters اللي بحققه اقصر مسافة بين اي two pair من
+
+84
+00:05:51,820 --> 00:05:56,640
+النقاط اللي موجودة عندها باخده على انه اللي هو ال
+
+85
+00:05:56,640 --> 00:06:01,360
+يعني عمل home dungeon يعني لو انا بدى اعيد تاني
+
+86
+00:06:04,190 --> 00:06:06,570
+لو انا افترض ان انا في عندهان three different
+
+87
+00:06:06,570 --> 00:06:15,230
+clusters لو
+
+88
+00:06:15,230 --> 00:06:22,170
+كان انا في عندهان another cluster و ال cluster ده
+
+89
+00:06:22,170 --> 00:06:28,230
+فيه مجموعة من النقاط تبدأ
+
+90
+00:06:28,230 --> 00:06:31,170
+المسافات تنحسب ما بين كل النقاط اللي موجودة في كل
+
+91
+00:06:31,170 --> 00:06:37,190
+اتجاهات من كل نقطةالـ pair of clusters اللي بتحقق
+
+92
+00:06:37,190 --> 00:06:41,910
+أقصر مسافة بين أي نقطين موجودات فيهم بنعتمد أن
+
+93
+00:06:41,910 --> 00:06:45,250
+هدول ال clusters في حين أن أنا فيها عندي هنا في
+
+94
+00:06:45,250 --> 00:06:50,490
+pair قوي بعيد جدا و أنا مابدورش هنا بدور على أقصر
+
+95
+00:06:50,490 --> 00:06:54,850
+المسافات يعني الآن هدول الأقرب نقطين لبعض هيهم
+
+96
+00:06:54,850 --> 00:07:01,800
+بأقارن المسافة هذه ومسافة هذهمين اقصر المسافة هذه
+
+97
+00:07:01,800 --> 00:07:05,920
+اقصر معناته هذين الاتنين بنعمل لهم دمج مع بعضهم
+
+98
+00:07:05,920 --> 00:07:09,020
+على انهم هدول ايش بدون يصيروا ال next level او ال
+
+99
+00:07:09,020 --> 00:07:12,940
+next cluster هذه فكرة كمان مرة ال single linkage
+
+100
+00:07:12,940 --> 00:07:17,060
+طبعا احنا ليش بحاول اوضحها هان اكتر لان فعليا احنا
+
+101
+00:07:17,060 --> 00:07:21,660
+محتاجين نفهمها كويس لان انا فعليا بدي كل النقاط
+
+102
+00:07:21,660 --> 00:07:26,230
+اللي موجودةتكون داخلة في الحسبة بنرجع كمان مرة في
+
+103
+00:07:26,230 --> 00:07:28,970
+عندي انا single linkage و single linkage بعمل
+
+104
+00:07:28,970 --> 00:07:32,270
+combine ل two clusters لما بيكون فيهم ال shortest
+
+105
+00:07:32,270 --> 00:07:37,610
+pair لما يكون في عندي انا فعليا ال .. ده البيانات
+
+106
+00:07:37,610 --> 00:07:42,390
+تبعتي اصغر
+
+107
+00:07:42,390 --> 00:07:46,630
+مايمكن ال minimum distance between any pair بشرط
+
+108
+00:07:46,630 --> 00:07:49,870
+ان هدول ال pair مايكونوش تمدمجهم مسبقا طبعا
+
+109
+00:07:53,060 --> 00:07:58,420
+كمان مرة لو انا افترضت ان هنا في عندى another
+
+110
+00:07:58,420 --> 00:08:02,020
+cluster و
+
+111
+00:08:02,020 --> 00:08:06,580
+ال cluster هي و هي هي النقاط اللي موجودة دائما
+
+112
+00:08:06,580 --> 00:08:10,900
+دائما في عملية و هنا في كمان واحد دائما في عملية
+
+113
+00:08:10,900 --> 00:08:14,620
+الدمج بروح
+
+114
+00:08:14,620 --> 00:08:18,140
+بدور لما بتكلم عن ال single linkage بروح بدور على
+
+115
+00:08:18,140 --> 00:08:20,820
+أقصر مسافة هدول أقرب نقطين بحسب ال distance بينهم
+
+116
+00:08:21,540 --> 00:08:24,920
+هو كيف بده يدور على أنه أقرب نقطين هو فعليا بتم
+
+117
+00:08:24,920 --> 00:08:28,340
+حسب ال distance ما بين كل العناصر اللي في ال
+
+118
+00:08:28,340 --> 00:08:31,800
+clusters يعني النقطة هذه مع كل العناصر اللي موجودة
+
+119
+00:08:31,800 --> 00:08:37,660
+هنا وبيعتمد أقصر مسافة النقطة كل العناصر كل النقاط
+
+120
+00:08:37,660 --> 00:08:40,880
+اللي هنا مع كل النقاط اللي هنا وبيعتمد أقصر مسافة
+
+121
+00:08:40,880 --> 00:08:46,220
+وبالتاليلو انا هذه النقطة هيروح حسبها المعاليين
+
+122
+00:08:46,220 --> 00:08:50,440
+كمان و بيعتمد هذه اقصر مسافة الان هي مسافة تنتين
+
+123
+00:08:50,440 --> 00:08:54,460
+تلاتة هدولة اقصر اقصر واحدة فيهم هدق هذه بيروح
+
+124
+00:08:54,460 --> 00:09:00,800
+بعملي damage لمين لهدول اصحاب single linkage بتمنى
+
+125
+00:09:00,800 --> 00:09:02,260
+تكون الفكرة وصلت
+
+126
+00:09:12,500 --> 00:09:15,880
+الـ criterion التاني اللي موجودة عندي أنا اللي هي
+
+127
+00:09:15,880 --> 00:09:21,140
+ال average وال average هنا بتتكلم على انه انا
+
+128
+00:09:21,140 --> 00:09:24,500
+بيعمل merge لل two clusters اللي اللهم shortest
+
+129
+00:09:24,500 --> 00:09:28,820
+average distance shortest average distance يعني
+
+130
+00:09:28,820 --> 00:09:36,200
+ايش اللي هيصير بعد ما راح حسب كل ال distances بين
+
+131
+00:09:36,200 --> 00:09:37,060
+كل النقاط
+
+132
+00:09:58,300 --> 00:10:01,740
+بين كل النقاط ايش بروح بيساوي بياخد ال average
+
+133
+00:10:01,740 --> 00:10:05,660
+تبعت ال distance لاحظوا انا في كل مرة بيعمل
+
+134
+00:10:05,660 --> 00:10:09,540
+marriage ل two clusters فقط تمام بيعمل marriage ل
+
+135
+00:10:09,540 --> 00:10:13,680
+two clusters فقط فهو بروح بحسب كل ال averages او
+
+136
+00:10:13,680 --> 00:10:17,520
+بحسب كل ال distances و بياخد ال average في ال
+
+137
+00:10:17,520 --> 00:10:20,080
+simple linkage او عفوا في ال single انا غلطان هنا
+
+138
+00:10:20,080 --> 00:10:23,260
+في الكتابة طبعا simple linkage
+
+139
+00:10:38,990 --> 00:10:50,390
+single single linkage سامحوني
+
+140
+00:10:50,390 --> 00:10:54,090
+هذه أسهل حاجة اعملها الآن لان انا حولت لصورة و
+
+141
+00:10:54,090 --> 00:11:04,190
+بديش ارجع اعيد نفس ال .. okay shift
+
+142
+00:11:04,190 --> 00:11:08,490
+F5بنتكلم هنا إنه أنا بتكلم على ال single linkage
+
+143
+00:11:08,490 --> 00:11:12,010
+أخدت أقصر لكن هان حسبت كل النقاط وبالتالي أخدت ال
+
+144
+00:11:12,010 --> 00:11:14,570
+average عشان اذا حاولت أرسم السهم هان يمثل لل
+
+145
+00:11:14,570 --> 00:11:21,990
+center تبع ال clusters اللي موجودين عندها هذه
+
+146
+00:11:21,990 --> 00:11:28,730
+ال average بالنسبة ل ال ال complete بياخد ال
+
+147
+00:11:28,730 --> 00:11:34,150
+maximum linkage بياخد .. بيعتمد .. من وين أطول ..
+
+148
+00:11:34,150 --> 00:11:39,200
+أبعد نقطينأقصر مسافة بين أبعد مقطين بروحيش بروح
+
+149
+00:11:39,200 --> 00:11:42,100
+مالهم جنج
+
+150
+00:11:43,400 --> 00:11:47,280
+يعني لو انا اتيت هنا هذه العناصر اللي موجودة عندها
+
+151
+00:11:47,280 --> 00:11:50,480
+بحسب كل ال distances اللي موجودة عندها بكل
+
+152
+00:11:50,480 --> 00:11:55,060
+الاتجاهات مع كل ال clusters هذه أقصر يعني هدول
+
+153
+00:11:55,060 --> 00:11:58,580
+أبعد نقطين نعم لكن هدى ال distance اللي بين ال two
+
+154
+00:11:58,580 --> 00:12:03,040
+clusters هدول هي عبارة عن أقصر مسافة مماثلة مع
+
+155
+00:12:03,040 --> 00:12:06,200
+different clusters فبقرر انه يعمل merge لل
+
+156
+00:12:06,200 --> 00:12:11,060
+clusters اللي موجودين عندهاالنوع التالت اللي هو ال
+
+157
+00:12:11,060 --> 00:12:15,020
+word ال word ال word او ال word ال word لما انا
+
+158
+00:12:15,020 --> 00:12:21,520
+بتكلم هنا بتكلم عن ال word القسم هنا بدور النوبلهو
+
+159
+00:12:21,520 --> 00:12:27,820
+يعمل ميرج لـ two clusters لما يقلل
+
+160
+00:12:27,820 --> 00:12:31,160
+الـ variance بين ال clusters الموجودة يقلل
+
+161
+00:12:31,160 --> 00:12:35,080
+الاختلافات بين ال clusters يعني هو الان بيحسب كل
+
+162
+00:12:35,080 --> 00:12:39,460
+النقاط كل ال distances اللي موجودة عنده بيحسب كل
+
+163
+00:12:39,460 --> 00:12:43,380
+ال distances و بيحسب كل ال distances و بيحاول يشوف
+
+164
+00:12:43,380 --> 00:12:48,720
+مين أقرب cluster في الاختلافاتفي ال elements اللي
+
+165
+00:12:48,720 --> 00:12:53,240
+موجود عنده هان و بروح بدمجلي اياهم يعني هو اش مروح
+
+166
+00:12:53,240 --> 00:12:54,420
+بساوي بكل بساطة
+
+167
+00:12:58,220 --> 00:13:01,320
+بعد ما بروح بحسب بحسب كل ال areas بحسب ال variance
+
+168
+00:13:01,320 --> 00:13:04,540
+هنا الإختلاف و ال variance اللي هنا مع ال cluster
+
+169
+00:13:04,540 --> 00:13:09,200
+التالت ال variance و أقل clusters في اختلاف ال
+
+170
+00:13:09,200 --> 00:13:13,340
+variance اللي بينهم بروح بدمجهم ليش عشان يحافظ على
+
+171
+00:13:13,340 --> 00:13:17,240
+التشابه ما بين ال two different clusters يعني انت
+
+172
+00:13:17,240 --> 00:13:21,220
+تخيل ان في عندك cluster كبير جدا و عندك cluster
+
+173
+00:13:21,220 --> 00:13:25,250
+صغير جداهدول ال two clusters صعب انهم يدمجوا ليش؟
+
+174
+00:13:25,250 --> 00:13:28,690
+مع ال word لأنهم فعليا ال variance تبعتهم عالية
+
+175
+00:13:28,690 --> 00:13:32,190
+جدا فهو بروح بدور على ال clusters المشابهة بداخله
+
+176
+00:13:32,190 --> 00:13:36,730
+by default بالمناسبة ال word هي ال default linkage
+
+177
+00:13:36,730 --> 00:13:41,290
+cluster المول وعادة لما انا بأتكلم على ال word
+
+178
+00:13:41,290 --> 00:13:42,930
+linkage criteria
+
+179
+00:13:46,150 --> 00:13:51,110
+الـ Cluster الناتجة عادة بتكون متقاربة في الأحجام
+
+180
+00:13:51,110 --> 00:13:56,210
+يعني بين جثين أنه ال data أو عدد العناصر اللي
+
+181
+00:13:56,210 --> 00:14:01,510
+موجودة في كل ال clusters بتكون متقاربة طيب الفكرة
+
+182
+00:14:01,510 --> 00:14:04,130
+في ال agglomerate بشكل عام هي كل ال data موجودة
+
+183
+00:14:04,130 --> 00:14:07,430
+عندى قلنا ال initial كل واحدة عبارة عن cluster
+
+184
+00:14:07,430 --> 00:14:12,130
+فببدأ يروح يدور على المسافات بين كل النقاط
+
+185
+00:14:16,240 --> 00:14:19,540
+بين كل النقاط و برجع بأكد هذه في كل مرة الحسبة
+
+186
+00:14:19,540 --> 00:14:26,480
+بتتم في كل
+
+187
+00:14:26,480 --> 00:14:30,240
+الاتجاهات و في الآخر هيلاقي ان هدول النقطين أقصر
+
+188
+00:14:30,240 --> 00:14:33,640
+distance موجودة بينهم فإيش هيروح يساوي هيروح يضمهم
+
+189
+00:14:33,640 --> 00:14:38,640
+لو اني cluster تمام في الخطوة التالية هيستثني هذه
+
+190
+00:14:38,640 --> 00:14:43,380
+و يدور في نفس كل clusters اقرب two clusters هيبدأ
+
+191
+00:14:43,380 --> 00:14:44,300
+يجمعهم
+
+192
+00:14:46,800 --> 00:14:53,500
+بعدين هايهم ليش دمج هدول لأن المسافة بين هدول أقصر
+
+193
+00:14:53,500 --> 00:14:57,360
+ما بين النقطة هذه والنقطة هذه وإلا كانش كان راح
+
+194
+00:14:57,360 --> 00:15:00,260
+دمج ليها على أن هذه عبارة عن cluster اللي بيحتوي
+
+195
+00:15:00,260 --> 00:15:03,260
+على نقطة واحدة مع ال single linkage criteria هي
+
+196
+00:15:03,260 --> 00:15:08,380
+shortest distance فراح فعليا دمج النقطة هايوبتبدأ
+
+197
+00:15:08,380 --> 00:15:11,820
+عملية الدمج تتوسع واحدة ورا التانية لحد ما يكون كل
+
+198
+00:15:11,820 --> 00:15:15,540
+النقاط اتوصلت أو او او او على الأقل انا وصلت لعدد
+
+199
+00:15:15,540 --> 00:15:18,260
+ال clusters المطلوب لو كان مثلا تلاتة بكون انا هذه
+
+200
+00:15:18,260 --> 00:15:21,380
+ال destination تبعتي انه حصلت انه على three
+
+201
+00:15:21,380 --> 00:15:25,240
+different clusters ولاحظوا عملية ال merge و ورا
+
+202
+00:15:25,240 --> 00:15:28,500
+التانية كل ما انا بدمج العناصر مع بعضها بتظهر ال
+
+203
+00:15:28,500 --> 00:15:32,980
+MDHالـ agglomerative لكن يا جماعة الخير في الـ
+
+204
+00:15:32,980 --> 00:15:37,000
+agglomerative هان هي الأساس للهيراريكال هي الأساس
+
+205
+00:15:37,000 --> 00:15:39,840
+للهيراريكال لكن مش هي الهيراريكال ليش؟ لأنه
+
+206
+00:15:39,840 --> 00:15:42,800
+بالهيراريكال لاحظوا أو بال .. بال agglomerative
+
+207
+00:15:42,800 --> 00:15:46,680
+أنه أنا في النهاية هان الكل two clusters بعملهم
+
+208
+00:15:46,680 --> 00:15:52,040
+دمج مع بعضهم بتزول الحدود اللي ما بينهم يعني لما
+
+209
+00:15:52,040 --> 00:15:57,700
+أنا كنت هانهذه نقطة و تنتين وهذه نقطة و تنتين و
+
+210
+00:15:57,700 --> 00:16:00,860
+هذه
+
+211
+00:16:00,860 --> 00:16:06,560
+نقطة و تنتين و هذه نقطة و تنتين و هذه نقطة و تنتين
+
+212
+00:16:06,560 --> 00:16:07,980
+و هذه نقطة و تنتين و هذه نقطة و تنتين و هذه نقطة و
+
+213
+00:16:07,980 --> 00:16:08,180
+تنتين و هذه نقطة و تنتين و هذه نقطة و تنتين و هذه
+
+214
+00:16:08,180 --> 00:16:08,180
+نقطة و تنتين و هذه نقطة و تنتين و هذه نقطة و تنتين
+
+215
+00:16:08,180 --> 00:16:08,180
+و هذه نقطة و تنتين و هذه نقطة و تنتين و هذه نقطة و
+
+216
+00:16:08,180 --> 00:16:13,360
+تنتين و هذه نقطة و تنتين و هذه نقطة و تنتين و هذه
+
+217
+00:16:13,360 --> 00:16:18,260
+نقطة و
+
+218
+00:16:18,260 --> 00:16:29,980
+تنتين و هذه نقطة و تنتين و هذه نقطة ووهادي هيك حسب
+
+219
+00:16:29,980 --> 00:16:43,240
+متى مرسمهم سابقا وهادي هيك بعدين هيك وهادي
+
+220
+00:16:43,240 --> 00:16:50,780
+طبعا هنا هيك لأنه تم دمجهم مرة تانية النقطين
+
+221
+00:16:50,780 --> 00:16:52,020
+هدولة كانوا في الأول
+
+222
+00:16:57,340 --> 00:17:00,400
+لو الرسم يبقى معايا بالشكل هذا يعني ان انا عارف من
+
+223
+00:17:00,400 --> 00:17:04,760
+اين بدأت كل اتنين صارت موجودة طبعا لما اتكلم ..
+
+224
+00:17:04,760 --> 00:17:09,140
+لما اروح بالتفصيل بالـ Hierarchical Clustering الـ
+
+225
+00:17:09,140 --> 00:17:12,320
+Hierarchical Clustering نفس .. نفس الكلام يعني انه
+
+226
+00:17:12,320 --> 00:17:18,240
+يحتاج كل pointهي هتدخل برحلة انها cluster مستقلة
+
+227
+00:17:18,240 --> 00:17:22,860
+ذاتها و هتنتمي لآخر cluster يعني هاي الفرق الأساسي
+
+228
+00:17:22,860 --> 00:17:26,000
+ما بين ال agglomerative و ال hierarchical بال
+
+229
+00:17:26,000 --> 00:17:31,160
+agglomerative فعليا راح دمجلي اياهم لكن في المحصلة
+
+230
+00:17:31,160 --> 00:17:34,280
+الأخيرة يا جماعة الخير انا حصلت على partitional
+
+231
+00:17:34,280 --> 00:17:37,920
+clustering ملاحظين هنا الرسمة الأخيرة في step 9 هي
+
+232
+00:17:37,920 --> 00:17:41,180
+عبارة عن partitional لأن مافيش عندى عناصر
+
+233
+00:17:51,050 --> 00:17:56,350
+لكن في الهيراريكال لأ انا ممكن احافظ على ان
+
+234
+00:17:56,350 --> 00:18:02,330
+العناصر التابعة تكون disjoint لحد level معين طيب
+
+235
+00:18:02,330 --> 00:18:05,870
+الآن زي ما قلنا هذه هي الرسمة اللي ممكن اعتمد عليه
+
+236
+00:18:05,870 --> 00:18:09,390
+هو اقول ان والله هذه اش انا بفهم من هدول ان كل
+
+237
+00:18:09,390 --> 00:18:16,390
+واحدة هدولة كانت بالشكل هذا1 و 4 اندمجت معاهم 2 و
+
+238
+00:18:16,390 --> 00:18:22,090
+8 اندمجت معاهم 3 و 5 مستقلة 01 و 12 اندمجت معاهم 5
+
+239
+00:18:22,090 --> 00:18:28,190
+و 6 و 9 اندمجت معاهم 7 و 10 اندمجت معاهم 7 و 10
+
+240
+00:18:28,190 --> 00:18:28,470
+اندمجت معاهم 7 و 10 اندمجت معاهم 7 و 10 اندمجت
+
+241
+00:18:28,470 --> 00:18:28,830
+معاهم 7 و 10 اندمجت معاهم 7 و 10 اندمجت معاهم 7 و
+
+242
+00:18:28,830 --> 00:18:29,230
+10 اندمجت معاهم 7 و 10 اندمجت معاهم 7 و 10 اندمجت
+
+243
+00:18:29,230 --> 00:18:29,230
+معاهم 7 و 10 اندمجت معاهم 7 و 10 اندمجت معاهم 7 و
+
+244
+00:18:29,230 --> 00:18:29,590
+10 اندمجت معاهم 7 و 10 اندمجت معاهم 7 و 10 اندمجت
+
+245
+00:18:29,590 --> 00:18:33,470
+معاهم 7 و 10 اندمجت معاهم 7 و 10 اندمجت معاهم 7 و
+
+246
+00:18:33,470 --> 00:18:39,300
+10 اندمجت معاهم 7 و 10 اندمولكن لو أخدت نظرة
+
+247
+00:18:39,300 --> 00:18:44,920
+جانبية يعني أنني أتعرف على شغلة اسمها الـ
+
+248
+00:18:44,920 --> 00:18:49,200
+Dendogram الـ Dendogram عبارة عن رسم تخطيطي يخدمني
+
+249
+00:18:49,200 --> 00:18:55,140
+في فهمي البيانات الموجودةعندها ال visualization
+
+250
+00:18:55,140 --> 00:18:58,080
+مهم جدًا عشان انا اقدر اشوف و افهم العناصر اللي
+
+251
+00:18:58,080 --> 00:19:03,620
+موجودة في موضوع ال ال hierarchical clustering و ال
+
+252
+00:19:03,620 --> 00:19:09,000
+dendrogram اللي بدها اتمثلها وبالتالي و لما ال
+
+253
+00:19:09,000 --> 00:19:13,000
+visualization بديني detailed view لل hierarchical
+
+254
+00:19:13,000 --> 00:19:16,380
+clustering معناته هي ما زالت في ال two dimensional
+
+255
+00:19:16,380 --> 00:19:22,180
+أساسًا اللي موجودة وبالتالي أنا عماليبقى أشتغل و
+
+256
+00:19:22,180 --> 00:19:26,500
+بقى أسأل و عمّالة بنحاول نرسم الـ Dendrogram انت
+
+257
+00:19:26,500 --> 00:19:30,140
+تخيل الرسمة معايا لو زهرت معايا بالشكل هذا طبعا
+
+258
+00:19:30,140 --> 00:19:33,640
+هدول الرسمتين للـ Dendrogram هم الأساس اللي موجود
+
+259
+00:19:33,640 --> 00:19:36,640
+عندي هان الأولى هذه زي ما قلت لك هي عبارة عن
+
+260
+00:19:36,640 --> 00:19:40,420
+الصورة العمودية من فوق ال clusters وشوفت التجميعات
+
+261
+00:19:40,420 --> 00:19:45,020
+بينما هان انا بأتكلم انه انا بشوف ال data كلها في
+
+262
+00:19:45,020 --> 00:19:49,240
+ال 2D بشوفها من نظرة جانبية وهذا الرسمة هي عبارة
+
+263
+00:19:49,240 --> 00:19:52,520
+عن ال Dendrogramالان فكرة الـ Dendrogram أو الـ
+
+264
+00:19:52,520 --> 00:19:56,120
+Hierarchical Clustering الأساسية ان انا بقدر احصي
+
+265
+00:19:56,120 --> 00:20:00,680
+على اي عدد من ال clusters انا محتاجه يعني تخيل انا
+
+266
+00:20:00,680 --> 00:20:04,620
+محتاج three clusters و بقى كل خط عمودي في الرسمة
+
+267
+00:20:04,620 --> 00:20:10,180
+بمثل cluster بدي three clusters هيهم بدي اتنين
+
+268
+00:20:10,180 --> 00:20:16,120
+هيهم لاحظ؟ ليش؟ لأن انا فعليا هدول كلهم مع بعض
+
+269
+00:20:17,510 --> 00:20:21,190
+عبارة عن cluster وهدول مع بعض عبارة عن cluster
+
+270
+00:20:21,190 --> 00:20:27,750
+تاني رسمت العمود مع العناصر اللي موجودة عندها بدك
+
+271
+00:20:27,750 --> 00:20:34,750
+تلاتة هدول التلاتة بصيروا مع بعضهم إذا
+
+272
+00:20:34,750 --> 00:20:39,770
+أنا بدي أتكلم على three clusters يعني هاي واحد
+
+273
+00:20:39,770 --> 00:20:44,030
+العشرة معاهم طبعا اتنين
+
+274
+00:20:48,010 --> 00:20:55,110
+و هاي تلاتة ممكن بدي أكتر؟ اه ممكن بس ايه بدي ازال
+
+275
+00:20:55,110 --> 00:21:01,330
+ال scale تبع عدد ال cluster لتحت جداش
+
+276
+00:21:01,330 --> 00:21:10,890
+بدي يكون مثلا لو نزلت عدد ال cluster لهيك
+
+277
+00:21:10,890 --> 00:21:14,690
+يعني انا بتكلم على single cluster واحد
+
+278
+00:21:17,600 --> 00:21:25,440
+لأ مش واحد الان هاى عندك انا واحد هذا
+
+279
+00:21:25,440 --> 00:21:32,020
+اتنين هذا تلاتة عشر على حالها هذه اربعة انا هاى
+
+280
+00:21:32,020 --> 00:21:37,480
+بتكلم انا على four clusters بناء على النقطة اللى
+
+281
+00:21:37,480 --> 00:21:43,410
+اخترتهاأهم شغلة في الموضوع أنه أنا فعليا لما بحصل
+
+282
+00:21:43,410 --> 00:21:46,690
+على ال dendrogram بقدر أحصل على أي عدد من ال
+
+283
+00:21:46,690 --> 00:21:50,410
+cluster أنا بدياه بدي أرجع كمان مرة أجي أقول والله
+
+284
+00:21:50,410 --> 00:21:57,490
+أنا هاي بدي .. لو أنا افترضت أنه أنا هنا هذا الخط
+
+285
+00:21:57,490 --> 00:22:03,590
+تبعي عفوا
+
+286
+00:22:03,590 --> 00:22:05,630
+اللي رسمتي مش ظابط كتير
+
+287
+00:22:12,280 --> 00:22:15,960
+لو انا مشيت هنا و قلت انا هايت مع الاتنين هنا بدي
+
+288
+00:22:15,960 --> 00:22:22,820
+امشي okay
+
+289
+00:22:22,820 --> 00:22:26,240
+أحسن من الأول لو أنا سألك عند الخط هذا كام cluster
+
+290
+00:22:26,240 --> 00:22:29,940
+انا بحقق انا بقدر اقول بتكلم على four clusters
+
+291
+00:22:29,940 --> 00:22:41,220
+four clusters هاي واحد بيجمع واحد و أربعة تاني ايو
+
+292
+00:22:45,790 --> 00:22:56,350
+الثالث العشرة لحال و الرابع هايه هدول عفوا مش أربع
+
+293
+00:22:56,350 --> 00:23:03,050
+هدول خمسة خمسة clusters خمسة
+
+294
+00:23:03,050 --> 00:23:07,890
+clustersطبعاً في فايدة تانية من الـ dendrogram أنا
+
+295
+00:23:07,890 --> 00:23:10,810
+بقى أقدر أفهم أنه على الرغم أنه من ال cluster
+
+296
+00:23:10,810 --> 00:23:14,590
+الأخير هذا اللي فيه الـ 7 و 6 و 9 أدول ال element
+
+297
+00:23:14,590 --> 00:23:16,610
+في نفس ال cluster إلا غير أنه من خلال الـ
+
+298
+00:23:16,610 --> 00:23:21,370
+dendrogram بقدر أفهم أنه الـ 6 و 9 instances أقرب
+
+299
+00:23:21,370 --> 00:23:26,150
+لبعض من السبعة كذلك الصفر و ال 11 في ال cluster
+
+300
+00:23:26,150 --> 00:23:32,370
+التالت و ال 2 و 8 في ال cluster التانيعشان نقدر
+
+301
+00:23:32,370 --> 00:23:36,790
+نطبق المثال هذا في مثال مشهور جدا أخدته سابقا من
+
+302
+00:23:36,790 --> 00:23:38,990
+الـ slide الخاصة بالدكتور علاء الله يجزي الخير
+
+303
+00:23:38,990 --> 00:23:42,230
+المثال
+
+304
+00:23:42,230 --> 00:23:49,430
+المشهور برضه، أنا في عندي الخريطة إيطاليا وبدي
+
+305
+00:23:49,430 --> 00:23:56,280
+اعتبر أن المدن هذه بمثابة Clusteringهو انا ال
+
+306
+00:23:56,280 --> 00:23:59,660
+clusters و بدي اروح اعمل ما بينهم merge عشان اشوف
+
+307
+00:23:59,660 --> 00:24:05,020
+اقرب المدن لبعضهم باعتمادني على ال single linkage
+
+308
+00:24:05,020 --> 00:24:15,120
+criterion single linkage criterion الان عفوا لما
+
+309
+00:24:15,120 --> 00:24:19,800
+انا بتكلم هذه رموز للولايات او المدن في ايطاليا
+
+310
+00:24:19,800 --> 00:24:22,980
+طبعا في ناس اللي راحت ايطاليا ما بينكوا لان انتوا
+
+311
+00:24:22,980 --> 00:24:30,150
+فرحانينبس أكيد بارمة
+
+312
+00:24:30,150 --> 00:24:39,190
+مش من ضمنهم و لا موجودة هي بارمة طيب الآن فعليا ال
+
+313
+00:24:39,190 --> 00:24:43,710
+contingency matrix بتجيب اللي بتجيه عبارة عن
+
+314
+00:24:46,160 --> 00:24:50,160
+Symmetric Matrix وفيها كل العناصر اللي موجودة
+
+315
+00:24:50,160 --> 00:24:57,900
+عندهان وبناء عليها انا بدي اقرر الان بارما بارما
+
+316
+00:24:57,900 --> 00:25:04,620
+اقصر distance وين مع مين فانا فعليا بروح بدور على
+
+317
+00:25:04,620 --> 00:25:09,200
+ال shortest distance انا الان هان اوكي 250 و ببدأ
+
+318
+00:25:09,200 --> 00:25:13,580
+بقى ادور لكن لاجينا ان في مسافة اقصر منها موجودة
+
+319
+00:25:13,580 --> 00:25:13,800
+وين
+
+320
+00:25:16,920 --> 00:25:23,360
+بتربط Milano و TMI و TO وبالتالي هدولة أقصر
+
+321
+00:25:23,360 --> 00:25:26,720
+ملاحظين يا جماعة الخير أنا شوفت ال distance مع
+
+322
+00:25:26,720 --> 00:25:31,300
+الكل بين الكل ماعليش ماعتمدتش السفر لأنها مدينة مع
+
+323
+00:25:31,300 --> 00:25:33,460
+نفسها مابديش إياها ال cluster مع نفسه أو ال
+
+324
+00:25:33,460 --> 00:25:38,160
+instance مع نفسها لكن هان دلت أدور لحد ما لجيت
+
+325
+00:25:38,160 --> 00:25:42,820
+مسافة أصغر مسافة في كل المسافات اللي موجودة عندي
+
+326
+00:25:42,820 --> 00:25:52,650
+هان وبالتاليفعليا هذه المسافة هنا و
+
+327
+00:25:52,650 --> 00:26:01,150
+نفس الكلام mi مع كل المدن و fi مع كل المدن كل ال
+
+328
+00:26:01,150 --> 00:26:07,630
+possible distances حسبتها يعني اذا اتكلمت من mi
+
+329
+00:26:07,630 --> 00:26:18,920
+لbaمي بي ا هي تمنية سبعة وسبعين كيلو متر ففي الآخر
+
+330
+00:26:18,920 --> 00:26:21,980
+انا باعتمد فقط على مسافة واحدة فقط اللي هي
+
+331
+00:26:21,980 --> 00:26:26,100
+shortest لان هذه ال minimum distance حسب ال
+
+332
+00:26:26,100 --> 00:26:32,240
+linkage criteria معناته انا بدي اتم دمج ال mi و ال
+
+333
+00:26:32,240 --> 00:26:33,500
+to تمام
+
+334
+00:26:36,100 --> 00:26:41,560
+وهذه اول cluster انا حصلت عليه هسميه marriage رقم
+
+335
+00:26:41,560 --> 00:26:48,520
+1 ممتاز فلما انا اتدمج MIT و MIT MIT MIT MIT MIT
+
+336
+00:26:48,520 --> 00:26:49,180
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+337
+00:26:49,180 --> 00:26:49,760
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+338
+00:26:49,760 --> 00:26:51,240
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+339
+00:26:51,240 --> 00:26:51,980
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+340
+00:26:51,980 --> 00:26:51,980
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+341
+00:26:51,980 --> 00:26:52,080
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+342
+00:26:52,080 --> 00:26:52,620
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+343
+00:26:52,620 --> 00:26:52,640
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+344
+00:26:52,640 --> 00:26:52,640
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+345
+00:26:52,640 --> 00:26:53,360
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+346
+00:26:53,360 --> 00:26:53,560
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+347
+00:26:53,560 --> 00:26:53,560
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+348
+00:26:53,560 --> 00:26:53,560
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+349
+00:26:53,560 --> 00:26:53,560
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+350
+00:26:53,560 --> 00:26:53,740
+MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT MIT
+
+351
+00:26:53,740 --> 00:26:56,560
+MIT MIT MIT
+
+352
+00:27:06,430 --> 00:27:09,370
+ماذا عن علاقة الـ Cluster الجديد هذا مع الـ
+
+353
+00:27:09,370 --> 00:27:10,950
+Element التانيات؟
+
+354
+00:27:16,670 --> 00:27:21,730
+إن هذا هو ال cluster متفقين الآن ال cluster الجديد
+
+355
+00:27:21,730 --> 00:27:25,690
+هذا انا بدي أتعامل معاه بدي أضع له قيمة تمثله
+
+356
+00:27:25,690 --> 00:27:32,230
+يتمثل علاقته معاه لأن هذا عبارة عن cluster جديد شو
+
+357
+00:27:32,230 --> 00:27:34,290
+ال distance بين ال cluster هذا وباقي ال clusters
+
+358
+00:27:34,290 --> 00:27:38,770
+التانيات فهاخد ال minimum distance ما بين كل
+
+359
+00:27:38,770 --> 00:27:43,410
+العناصر اللي موجودة بمعنى حاجة أقول كتالة في السطر
+
+360
+00:27:43,410 --> 00:27:53,780
+الأول هنا لما انا بدي أدمجمأي و تي او مع
+
+361
+00:27:53,780 --> 00:27:57,900
+ال بي اي مش هدول اللي بيصيروا one cluster يعني هنا
+
+362
+00:27:57,900 --> 00:28:06,580
+هذا الأعمود بيبقى شقب مثلا و بدي أحط هنا تي او و
+
+363
+00:28:06,580 --> 00:28:11,120
+مأي بغض النظر مين جدمت على مين أنا مش قضية كتير
+
+364
+00:28:11,120 --> 00:28:17,000
+تمام الآن ال بي اي في عندي مسافةفي عندى مسافتين
+
+365
+00:28:17,000 --> 00:28:19,740
+مين بتاخد فيهم بما انه بعتمد انا مازلت على ال
+
+366
+00:28:19,740 --> 00:28:22,840
+single linkage معناته انا بدي اخد ال shortest
+
+367
+00:28:22,840 --> 00:28:33,280
+distance مين اقصر 877 ولا 996 لأ 877 مع ال FI الان
+
+368
+00:28:33,280 --> 00:28:41,920
+ال FI في عندى 295 و400 هعتمد ال 200595 هذه ستبقى
+
+369
+00:28:41,920 --> 00:28:49,960
+صفر مش هتتغير وحتى اللي هي الأقصر الان في عندي 457
+
+370
+00:28:49,960 --> 00:28:53,100
+طبعا هذا ال raw كمان انا بده أخلص منه جامعة الخير
+
+371
+00:28:53,100 --> 00:28:59,660
+ماتنساش 754 وعندي 869
+
+372
+00:28:59,660 --> 00:29:06,520
+هعتمد هاي وفي عندي 564
+
+373
+00:29:06,520 --> 00:29:11,930
+هعتمدهم وبالتالي الجدول الجديد تبعيهيكون بالشكل
+
+374
+00:29:11,930 --> 00:29:17,770
+هذا باقي الأرقام ما تغيرتش أنا خلصت من صف و عمود
+
+375
+00:29:17,770 --> 00:29:21,890
+اللي كانت ممثل ال TO واعتمدت على ال shortest
+
+376
+00:29:21,890 --> 00:29:25,090
+distance اللي موجودة ان شاء الله ماكنش نجلتها غلط
+
+377
+00:29:25,090 --> 00:29:29,610
+تمانية سبعتين اتنين تسعة خمسة صفر
+
+378
+00:29:37,510 --> 00:29:41,110
+أول عملية تمت موجودة عندى باعتماد على single
+
+379
+00:29:41,110 --> 00:29:41,510
+linkage
+
+380
+00:29:44,500 --> 00:29:47,860
+بدي أعيد نفس الكرة عشان أعمل damage ببدأ بدور على
+
+381
+00:29:47,860 --> 00:29:52,500
+shortest distance أي 255 في الصف الأول هي أقصر
+
+382
+00:29:52,500 --> 00:29:57,600
+مسافة لحتى اللحظة 255
+
+383
+00:29:57,600 --> 00:30:05,420
+هي الأقصر 255 255 255 هي الأقصر معناته الآن بدي
+
+384
+00:30:05,420 --> 00:30:10,920
+نعمل damage ما بين ال NA و ال BA بنفس الكلام
+
+385
+00:30:10,920 --> 00:30:22,700
+السابق هخلصمن عمود الـ Na وصف الـ Na تمام علاقتهم
+
+386
+00:30:22,700 --> 00:30:28,580
+ستكون عملوها في عمود واحد اي distance اللي احتفظ
+
+387
+00:30:28,580 --> 00:30:33,300
+فيها الان هذي مش هتتغير لأنها هتجيل العمود اللي
+
+388
+00:30:33,300 --> 00:30:40,140
+عندها بـ A Na
+
+389
+00:30:42,020 --> 00:30:46,560
+سنة صفر تمام هي عندها ستمية اتنين وستين وعندي
+
+390
+00:30:46,560 --> 00:30:51,280
+اربعمية تمانية وستين لأ هعتمد المسافة الاقصر
+
+391
+00:30:51,280 --> 00:30:59,140
+اربعمية تمانية وستين عندها
+
+392
+00:30:59,140 --> 00:31:07,240
+تمانية سبعة وسبعين وعندها سبعمية اربعة وخمسين
+
+393
+00:31:07,240 --> 00:31:15,800
+هعتمد السبعميةواربعة وخمسين طبعا صفها تلتغى عند
+
+394
+00:31:15,800 --> 00:31:19,320
+هان اربعمية واطنعش وعندى اتنين وتسعة عشر هعتمد
+
+395
+00:31:19,320 --> 00:31:24,780
+الاتنين وتسعة عشر ليش لأنه كمان مرة انا بدور على
+
+396
+00:31:24,780 --> 00:31:30,300
+ال single linkage وبالتالي انا اخطأت
+
+397
+00:31:37,670 --> 00:31:45,690
+عفوا انا خطأت فيه عند 219 عشان هي اقصر انا اسف مش
+
+398
+00:31:45,690 --> 00:31:53,250
+كتير يعني بقول الخطأ مردود ان شاء الله متصحى اقصر
+
+399
+00:31:53,250 --> 00:32:04,260
+مسافة عندي فعليا هيها بين N A و R Mوبالتالي انا
+
+400
+00:32:04,260 --> 00:32:09,620
+هخلص مثلا من عمود الارقام ومن صف الارقام مش قضية و
+
+401
+00:32:09,620 --> 00:32:15,020
+هدمجهم .. هدمج التنين مع بعض هذا الآن هيصير عندي
+
+402
+00:32:15,020 --> 00:32:16,420
+an ar
+
+403
+00:32:21,380 --> 00:32:38,620
+م 256 و لا 412 لأ 255 468 و لا 268 لأ 268 754
+
+404
+00:32:38,620 --> 00:32:49,340
+و لا 564 لأ 564 564 عفوان 64 تمام
+
+405
+00:32:50,340 --> 00:32:54,420
+وبهيك انا بقى حط القيام اللى موجودة عندى وبالتالي
+
+406
+00:32:54,420 --> 00:32:57,700
+هي الجدول الجديد اللى موجود عندى هان
+
+407
+00:33:01,600 --> 00:33:06,400
+تمام وهذه عبارة عن second merge اللي حصلت عند هان
+
+408
+00:33:06,400 --> 00:33:09,560
+وبالتالي هي ال damage التاني الآن بدي أعيد نفس
+
+409
+00:33:09,560 --> 00:33:18,560
+الكرة بدور على ال shortest distance 6 6 2 8 7 7 2
+
+410
+00:33:18,560 --> 00:33:25,820
+هذه أقصر واحدة لحد اللحظة 6 6 2 2 9 لأ هذه أقصر 2
+
+411
+00:33:25,820 --> 00:33:35,780
+6 هي أقصرOkay 255 هي الأقصر وبالتالي بدي تمدمج ال
+
+412
+00:33:35,780 --> 00:33:40,880
+RN العمود الأخير مع ال BA معناته أنا بدي أخلص من
+
+413
+00:33:40,880 --> 00:33:47,700
+الصف الأخير في الجدولة وهذا الصف بدي أضيف له بدي
+
+414
+00:33:47,700 --> 00:33:53,020
+أصير يبنثل ال BA NA
+
+415
+00:33:53,020 --> 00:33:55,660
+R
+
+416
+00:33:57,490 --> 00:34:09,970
+الان هذا الصفر هيكون 268 هتحل هان وهان
+
+417
+00:34:09,970 --> 00:34:10,790
+خمسمية
+
+418
+00:34:14,770 --> 00:34:18,410
+46 و باقي العناصر مش هصير عليها تغيير وبالتالي
+
+419
+00:34:18,410 --> 00:34:22,710
+كمان مرة هعيد نفس الكرة و أدور على أقصر مسافة أقصر
+
+420
+00:34:22,710 --> 00:34:27,530
+مسافة هيها معناته حين عمل دمج ما بين العنصرين هدول
+
+421
+00:34:27,530 --> 00:34:36,810
+وبالتالي انا هخلص من العمود هذا و من الصف هذا
+
+422
+00:34:36,810 --> 00:34:39,150
+لان احتفظ ب 280
+
+423
+00:34:41,500 --> 00:34:48,680
+هذه الصفر هتبقى تماما هن 295 نقل
+
+424
+00:34:48,680 --> 00:34:52,280
+295
+
+425
+00:34:52,280 --> 00:34:57,240
+نقل 295 نقل
+
+426
+00:34:57,240 --> 00:34:59,560
+295 نقل 295 نقل 295 نقل 295 نقل 295 نقل 295 نقل
+
+427
+00:34:59,560 --> 00:34:59,560
+295 نقل 295 نقل 295 نقل 295 نقل 295 نقل 295 نقل
+
+428
+00:34:59,560 --> 00:34:59,660
+295 نقل 295 نقل 295 نقل 295 نقل 295 نقل 295 نقل
+
+429
+00:34:59,660 --> 00:34:59,680
+295 نقل 295 نقل 295 نقل 295 نقل 295 نقل 295 نقل
+
+430
+00:34:59,680 --> 00:34:59,680
+295 نقل 295 نقل 295 نقل 295 نقل 295 نقل 295 نقل
+
+431
+00:34:59,680 --> 00:34:59,680
+295 نقل 295 نقل 295 نقل 295 نقل 295 نقل 295 نقل
+
+432
+00:34:59,680 --> 00:35:09,140
+295 نقل 295 نقل 295
+
+433
+00:35:09,140 --> 00:35:14,290
+نقبتمنى تكون الأمور تمام راجعوا المثال حاولوا
+
+434
+00:35:14,290 --> 00:35:17,710
+اقطعوه على ورقة من ال slides وطبقوه لوحدكم عشان
+
+435
+00:35:17,710 --> 00:35:20,570
+ترسخ الأمور ان شاء الله او ان شاء الله بقدر ازودكم
+
+436
+00:35:20,570 --> 00:35:25,050
+مثال تاني عامة قريب تظل عندنا جزئية واحدة في ال
+
+437
+00:35:25,050 --> 00:35:27,830
+chapter هذا اللي هي جزئية ال evaluation لل
+
+438
+00:35:27,830 --> 00:35:31,190
+clustering طبعا مش مويلة هتكون ان شاء الله تعالى
+
+439
+00:35:31,190 --> 00:35:35,670
+لكن بدنا نحاول نركز فيها مع انه بدي احاول اخفف
+
+440
+00:35:35,670 --> 00:35:38,870
+عليكم في بعض العمليات الحسابية السلام عليكم ورحمة
+
+441
+00:35:38,870 --> 00:35:39,050
+الله
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9DgNoAZTwqg.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9DgNoAZTwqg.srt
new file mode 100644
index 0000000000000000000000000000000000000000..261bd7e567943c567a2cd51d076dacd5bf73c780
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9DgNoAZTwqg.srt
@@ -0,0 +1,1836 @@
+1
+00:00:04,520 --> 00:00:06,480
+بسم الله الرحمن الرحيم الصلاة والسلام على رسول
+
+2
+00:00:06,480 --> 00:00:11,160
+الله أهلا وسهلا بكم في لقاءٍ من جديد من لقاءات
+
+3
+00:00:11,160 --> 00:00:16,280
+مساق تنقيب البيانات، وإن شاء الله اليوم سأتكلم
+
+4
+00:00:16,280 --> 00:00:21,680
+معكم عن .. سأشتغل معكم عمليًا زي ما اشتغلت في الـ
+
+5
+00:00:21,680 --> 00:00:25,520
+preprocessing سأعمل فيديو قصيرًا عن الـ
+
+6
+00:00:25,520 --> 00:00:28,120
+classification وماذا أريد أن أفعل في عمل الـ
+
+7
+00:00:28,120 --> 00:00:32,800
+classification، وشكله على الكاجل كـ Environment ممكن
+
+8
+00:00:32,800 --> 00:00:37,740
+أنتم تستخدموها في موضوع الـ Data Mining أو الـ
+
+9
+00:00:37,740 --> 00:00:41,800
+Data Science وحاجات كتيرة فقط بـ Classifier راح
+
+10
+00:00:41,800 --> 00:00:44,920
+والـ Classifier هذا له خصوصية شوية ضمن كل فيديو
+
+11
+00:00:44,920 --> 00:00:48,040
+هذه تساعدكم في فهم أو في عمل الواجب بشكل صحيح
+
+12
+00:00:48,040 --> 00:00:52,300
+أتممنى في الواجب تستخدموا الـ data set تبعكم
+
+13
+00:00:52,300 --> 00:00:57,290
+وتقارنوا الـ performance تبع الـ three classifiers من
+
+14
+00:00:57,290 --> 00:01:02,050
+الأربعة، أخذنا الـ Canary Sniper والـ Naive Bison
+
+15
+00:01:02,050 --> 00:01:04,890
+والـ Neural Network والـ Decision Tree، هدول
+
+16
+00:01:04,890 --> 00:01:07,650
+الأربعة، أنا شرحتهم في تسجيلات سابقة، المضمون أنكم
+
+17
+00:01:07,650 --> 00:01:10,210
+تختاروا الثلاثة وتطبقوهم على الـ data set اللي
+
+18
+00:01:10,210 --> 00:01:15,770
+موجودة عندكم، الآن إن شاء الله تعالى هبدأ أعمل
+
+19
+00:01:15,770 --> 00:01:19,160
+sharing للشاشة اللي موجودة عندي، أحاول في الفيديو
+
+20
+00:01:19,160 --> 00:01:23,460
+أنتقل لموضوع الـ Sharing وأتكلم على الـ Data Set
+
+21
+00:01:23,460 --> 00:01:29,580
+أو على الـ Element اللي أنا .. البرنامج
+
+22
+00:01:29,580 --> 00:01:35,640
+اللي أنا بدأ أشتغل عليه، بداية خليني أنا أروح أعمل
+
+23
+00:01:35,640 --> 00:01:40,900
+Share للـ Desktop، هي
+
+24
+00:01:40,900 --> 00:01:44,300
+Share للـ Desktop بالكامل، وبعد التسجيل المفروض للـ
+
+25
+00:01:44,300 --> 00:01:45,700
+Desktop وأنا الآن
+
+26
+00:02:07,030 --> 00:02:12,390
+بسم الله، هي kaggle.com، أنا أيه الحساب على الكاجل؟
+
+27
+00:02:12,600 --> 00:02:16,280
+اللي أنشأته، من تبقى الإحساب آخر، لكن هذا أنا أنشأته
+
+28
+00:02:16,280 --> 00:02:25,400
+من فترة، بخصوص الـ الـ الـ الـ الـ
+
+29
+00:02:25,400 --> 00:02:25,680
+الـ الـ الـ الـ الـ الـ الـ الـ الـ
+
+30
+00:02:25,680 --> 00:02:25,740
+الـ الـ الـ الـ الـ الـ الـ الـ الـ
+
+31
+00:02:25,740 --> 00:02:26,100
+الـ الـ الـ الـ الـ الـ الـ الـ الـ
+
+32
+00:02:26,100 --> 00:02:26,620
+الـ الـ الـ الـ الـ الـ الـ الـ الـ
+
+33
+00:02:26,620 --> 00:02:26,900
+الـ الـ الـ الـ الـ الـ الـ الـ الـ
+
+34
+00:02:26,900 --> 00:02:27,000
+الـ الـ الـ الـ الـ الـ الـ الـ الـ
+
+35
+00:02:27,000 --> 00:02:27,040
+الـ الـ الـ الـ الـ الـ الـ الـ الـ
+
+36
+00:02:27,040 --> 00:02:32,220
+الـ الـ الـ الـ الـ
+
+37
+00:02:32,220 --> 00:02:38,740
+الـ الـ الـ الـ
+
+38
+00:02:38,740 --> 00:02:42,760
+الـ الـ، أُحدد الـ database هي Pima Indians Diabetes
+
+39
+00:02:42,760 --> 00:02:46,120
+الـ database هي مشهورة عالميًا، أنا مش هروح أحملها
+
+40
+00:02:46,120 --> 00:02:50,880
+كمان مرة، فاللي already إذا حملتها بكون انتهيت من
+
+41
+00:02:50,880 --> 00:02:55,620
+الملف اللي موجود عندي، وهنتقل للخطوة التالية، هروح
+
+42
+00:02:55,620 --> 00:03:01,840
+أنا أقوله في الـ data set اللي موجودة عندي هي Pima
+
+43
+00:03:01,840 --> 00:03:02,680
+Indians Diabetes
+
+44
+00:03:07,480 --> 00:03:16,400
+وأنا بدي أستخدم الـ Dataset، طبعًا الـ
+
+45
+00:03:16,400 --> 00:03:18,840
+الـ Dataset جميلة جدًا، عشان نفهمها بشكل سريع، الـ
+
+46
+00:03:18,840 --> 00:03:23,280
+Dataset هي ناتجة عن المركز الوطني لأمراض السكري
+
+47
+00:03:23,280 --> 00:03:30,540
+والحمية والأمراض المزمنة، الهدف منها إنه فعليًا
+
+48
+00:03:30,540 --> 00:03:33,860
+يحاولوا يتنبؤوا هل المريض هذا هو مصاب بسكري أو لا
+
+49
+00:03:33,860 --> 00:03:36,980
+بناءً على التشخيصات اللي هي موجودة في الـ database
+
+50
+00:03:36,980 --> 00:03:39,800
+اللي موجودة قدامنا، هي موجودة، مكوّنة من ثمانية
+
+51
+00:03:39,800 --> 00:03:42,780
+attributes زي اللي هنشوفها كمان شوية، "several
+
+52
+00:03:42,780 --> 00:03:44,920
+constraints were placed on the solution of the
+
+53
+00:03:44,920 --> 00:03:50,400
+ice"، وهذه الـ database مكوّنة، بتتناول الـ female
+
+54
+00:03:50,400 --> 00:03:54,220
+patients only، all the patients here are females at
+
+55
+00:03:54,220 --> 00:04:03,460
+least، على الأقل يكونوا 21 سنة، يعني 21 سنة من Pima
+
+56
+00:04:03,460 --> 00:04:07,860
+المنطقة اللي موجودة فيها، طبعًا هذا كل الكلام أنا ما
+
+57
+00:04:07,860 --> 00:04:11,300
+إلا اللي شفته عندما تعرفت على الـ database
+
+58
+00:04:11,300 --> 00:04:16,980
+والآن بدي أروح أقول له New Notebook
+
+59
+00:04:22,650 --> 00:04:26,450
+الآن الـ New Notebook هو Jupyter Notebook، أنشأته
+
+60
+00:04:26,450 --> 00:04:30,910
+على الـ Kaggle، والآن جاب لي هذا الكود عشان يعمل
+
+61
+00:04:30,910 --> 00:04:35,490
+import للـ database اللي موجودة عندي، طبعًا
+
+62
+00:04:35,490 --> 00:04:40,590
+هذا الفرق الوحيد ما بين الـ Online، الـ Python
+
+63
+00:04:40,590 --> 00:04:46,370
+Jupyter Notebook أو الـ Local، اللي في الآخر أنت لما
+
+64
+00:04:46,370 --> 00:04:49,210
+بنعمل import كنا بنضيف له المسار اللي موجود، طب من
+
+65
+00:04:49,210 --> 00:04:53,790
+يحدد المسار؟ هذا موجود على cloud أو على driver
+
+66
+00:04:56,070 --> 00:04:59,490
+فاحنا بنختاره بكل بساطة بدون إيش؟ بدون ما يكون في
+
+67
+00:04:59,490 --> 00:05:02,650
+عندنا الـ .. عفواً، فبتروح بتزوّدنا إياه على Kaggle
+
+68
+00:05:02,650 --> 00:05:05,090
+بدون ما يكون في عندنا مشاكل، الأصل إحنا هذا الـ code
+
+69
+00:05:05,090 --> 00:05:09,710
+إذا بدنا نشتغل Online نرفعه أو نتعلمه أو نحفظه لأنه
+
+70
+00:05:09,710 --> 00:05:12,250
+هذا الـ code هيلزمنا مع الكاجل، وغالباً هو نفسه
+
+71
+00:05:12,250 --> 00:05:16,350
+موجود مع الـ colab، ما علينا، الآن لو أنا طبعًا
+
+72
+00:05:16,350 --> 00:05:19,190
+لاحظت أنه عمل كمان import لأهم two libraries اللي
+
+73
+00:05:19,190 --> 00:05:22,740
+هم على الـ database أو في الـ dataset، الـ numpy
+
+74
+00:05:22,740 --> 00:05:26,320
+والـ pandas، طبعًا إحنا معظم شغلنا من خلال الـ pandas
+
+75
+00:05:26,320 --> 00:05:31,280
+لكن في مثال اليوم هيلزمنا الـ numpy كذلك لمرة واحدة
+
+76
+00:05:31,280 --> 00:05:35,550
+أو لمرتين، خلينا نعمل run للـ code اللي موجود عندي
+
+77
+00:05:35,550 --> 00:05:39,750
+عمل run، طبعًا سرعة الاستجابة بتعتمد على سرعة الـ
+
+78
+00:05:39,750 --> 00:05:42,950
+connection اللي موجود عندك، طبعًا هنا بيقول لك قد ايش
+
+79
+00:05:42,950 --> 00:05:46,050
+أنت استخدمت من الـ hardest، قد ايش عندك CPU أو إشغال
+
+80
+00:05:46,050 --> 00:05:48,930
+للـ CPU، قد ايش إذا كان عندك إشغال للـ رابط ممكن تطفيه
+
+81
+00:05:48,930 --> 00:05:51,210
+ممكن تعمل restart للجهة بتاعت الـ notebook هذا
+
+82
+00:05:51,210 --> 00:05:59,030
+الـ رابط، بعد ما عملت run أداني رابط في diabetes.csv
+
+83
+00:05:59,030 --> 00:06:02,070
+طبعًا خليني أنا أسمي الـ notebook تبعي diabetes
+
+84
+00:06:06,170 --> 00:06:10,510
+عند الـ score specification
+
+85
+00:06:12,560 --> 00:06:15,840
+وأجي آخذ Notebook جديدة، وأروح أنا أقول له الـ
+
+86
+00:06:15,840 --> 00:06:19,240
+DataFrame، طب أنا خلاص بدي أقرأ الـ database بـ pandas
+
+87
+00:06:19,240 --> 00:06:27,080
+.read_csv اللي زي ما إحنا بنقرأ، وهي الـ
+
+88
+00:06:27,080 --> 00:06:31,220
+single quotation، وهي المسار اللي أنا نسخته، هي كده
+
+89
+00:06:31,220 --> 00:06:34,620
+الأمور تمت، عملية المفروض تمت عملية القراءة عشان أنا
+
+90
+00:06:34,620 --> 00:06:38,920
+أتأكد، وراح أقول DataFrame.head، والـ head ممكن أنا
+
+91
+00:06:38,920 --> 00:06:44,470
+أزودها زي ما قلنا سابقاً، بتعرض أول صفوف من الـ
+
+92
+00:06:44,470 --> 00:06:48,450
+DataFrame اللي أنا قريته، الـ DataFrame هذا مكوّن
+
+93
+00:06:48,450 --> 00:06:53,130
+من حوالي الـ 768 صف، الـ By default
+
+94
+00:06:53,130 --> 00:06:56,490
+الـ head بتجيب عشرة، عفواً، بتجيب خمسة، إذا أنا بدي
+
+95
+00:06:56,490 --> 00:06:59,830
+عشرة أو بدي خمسة أو بدي ثلاثة أو بدي خمسة عشر ممكن
+
+96
+00:06:59,830 --> 00:07:05,350
+أنا أروح أغيره مرة ثانية، فهي راح قرأ لي إياها، اللي
+
+97
+00:07:05,350 --> 00:07:08,840
+قال لي هي البيانات اللي موجودة عندك، بس خليني أقول
+
+98
+00:07:08,840 --> 00:07:14,740
+لكم قدرة الـ Pima Indians Classification، الآن تعرفوا
+
+99
+00:07:14,740 --> 00:07:18,900
+على الـ Attributes بشكل سريع اللي موجودة عنهم، بما
+
+100
+00:07:18,900 --> 00:07:23,120
+أن كل الـ Database أو كل الـ Data Sets مكوّنة من
+
+101
+00:07:23,120 --> 00:07:27,680
+الـ، فعلاً بيسألني عن الـ Pregnancy، عدد مرات
+
+102
+00:07:27,680 --> 00:07:34,600
+الحمل، نسبة الجلوكوز في الدم، ضغط الدم، كم كان،
+
+103
+00:07:34,600 --> 00:07:37,420
+سماكة الجلد، طبعًا سماكة الجلد  مهمة جدًا
+
+104
+00:07:37,420 --> 00:07:44,580
+لأنه بيمثل لي طبقة الدهون، كمية نسبة الأنسولين
+
+105
+00:07:44,580 --> 00:07:48,480
+أو كمية الأنسولين الموجودة، الـ Body Mass Index
+
+106
+00:07:48,480 --> 00:07:52,600
+مؤشر كتلة الجسم، قد ايش؟ طبعًا المفروض كل الناس اللي
+
+107
+00:07:52,600 --> 00:07:55,880
+فوق الـ 30 أو فوق الـ 32 أو 35، أعتقد، إذا أنا مش
+
+108
+00:07:55,880 --> 00:08:01,920
+غلطان يعني، بقول عنهم أصحاب سمنة، الـ DiabetesPedigreeFunction
+
+109
+00:08:01,920 --> 00:08:05,260
+و High Function بتقيس ليه؟ هل
+
+110
+00:08:05,260 --> 00:08:09,120
+المرض هذا مرتبط بعامل وراثي من الأبوين أو من أحد
+
+111
+00:08:09,120 --> 00:08:14,080
+من العائلة؟ قد ايش نسبة الناس اللي في العائلة موجودين
+
+112
+00:08:14,080 --> 00:08:19,540
+أو مصابين بالمرض، المرض السكري، والـ Age الأعمار زي
+
+113
+00:08:19,540 --> 00:08:22,320
+ما قلنا، والـ Outcome اللي هو الـ label أو الـ target
+
+114
+00:08:22,320 --> 00:08:25,800
+تبعنا، The binary classification صفر واحد، واحد
+
+115
+00:08:25,800 --> 00:08:29,380
+مصاب، صفر غير مصاب، وإحنا بدنا نعمل prediction
+
+116
+00:08:29,380 --> 00:08:32,660
+نشوف هل فعليًا اللي هو أنا زودته ببيانات معينة
+
+117
+00:08:32,660 --> 00:08:37,530
+هيقول إنه هذا مصاب أو غير مصاب، تمام، الآن عشان
+
+118
+00:08:37,530 --> 00:08:41,590
+أتعرف على الـ Database بشكل كويس بقول ممكن أنا
+
+119
+00:08:41,590 --> 00:08:49,230
+أروح أقول له الـ DataFrame.describe، والـ
+
+120
+00:08:49,230 --> 00:08:51,510
+Describe بقول لنا هذا بتدينا Simple Statistics، لكن
+
+121
+00:08:51,510 --> 00:08:55,330
+المرحلة هذه بدي Transpose، والناس اللي درست
+
+122
+00:08:55,330 --> 00:08:58,590
+رياضيات منفصلة بتعرف إن الـ Transpose أو دراسة
+
+123
+00:08:58,590 --> 00:09:02,630
+مصفوفات بتعرف إن الـ Transpose بعمل تبديل للصفوف
+
+124
+00:09:02,630 --> 00:09:07,570
+والأعمدة، أخيرًا هي راح جاب لي إياها هون، وبحيث إن الـ
+
+125
+00:09:07,570 --> 00:09:11,790
+statistics الـ count بتمثل عدد الصفوف اللي فيها
+
+126
+00:09:11,790 --> 00:09:18,310
+values، طبعًا كله فيه values عندي هون 768 عدد الـ
+
+127
+00:09:18,310 --> 00:09:21,310
+values، الـ mean المتوسط الحسابي، الـ standard
+
+128
+00:09:21,310 --> 00:09:24,330
+deviation، الـ minimum value، طبعًا جماعة الخير الـ
+
+129
+00:09:24,330 --> 00:09:28,920
+minimum value زي الجلوكوز وضغط الدم، الـ skin
+
+130
+00:09:28,920 --> 00:09:33,280
+thickness، والأنسولين، والـ body mass index، هذه
+
+131
+00:09:33,280 --> 00:09:38,320
+كلها بالنسبة لنا المفروض تكون هذه missing values
+
+132
+00:09:38,320 --> 00:09:41,200
+بس بدها معالجة، لأن مستحيل يكون عندي الـ body mass
+
+133
+00:09:41,200 --> 00:09:44,040
+index صفر، مستحيل يكون الجلوكوز في الدم صفر،
+
+134
+00:09:44,040 --> 00:09:48,490
+مستحيل blood pressure يكون صفر، بس أنا الآن مش هشتغل
+
+135
+00:09:48,490 --> 00:09:51,190
+على الـ database، مش هعملها pre-processing، بينما أنت
+
+136
+00:09:51,190 --> 00:09:54,490
+ملزم إنك تعمل pre-processing للـ database، الـ
+
+137
+00:09:54,490 --> 00:09:57,010
+database ده مش مناسب، أقول لك خذ database ثانية إذا
+
+138
+00:09:57,010 --> 00:10:01,260
+في حد مختار قدر الله، طيب، الآن أنا بحاجة زي ما قلنا
+
+139
+00:10:01,260 --> 00:10:06,380
+عن الـ Database هذه، على علاتها وحافظها، أروح أجهز
+
+140
+00:10:06,380 --> 00:10:11,500
+الـ Data Set للـ Classification، وأهم شغلة
+
+141
+00:10:11,500 --> 00:10:14,660
+في الـ Classification إنه أنا أعمل يا جماعة الخير
+
+142
+00:10:14,660 --> 00:10:18,320
+Split ما بين الـ Data Set، Attribute، آخذ الـ
+
+143
+00:10:18,320 --> 00:10:21,040
+Attributes أو الـ Data Attributes لحال، وآخذ الـ
+
+144
+00:10:21,040 --> 00:10:25,480
+Target Attribute لحالي، وهذا الكلام أنا بدي أروح
+
+145
+00:10:25,480 --> 00:10:34,910
+أسميه تحت "Data" أو "Data Set" "Splitting"
+
+146
+00:10:34,910 --> 00:10:41,750
+"Splitting" أو "Splitting"
+
+147
+00:10:41,750 --> 00:10:43,450
+"Splitting" "Splitting" "Splitting" "Splitting"
+
+148
+00:10:43,450 --> 00:10:43,610
+"Splitting" "Splitting" "Splitting" "Splitting"
+
+149
+00:10:43,610 --> 00:10:44,590
+"Splitting" "Splitting" "Splitting" "Splitting"
+
+150
+00:10:44,590 --> 00:10:44,610
+"Splitting" "Splitting" "Splitting" "Splitting"
+
+151
+00:10:44,610 --> 00:10:44,650
+"Splitting" "Splitting" "Splitting" "Splitting"
+
+152
+00:10:44,650 --> 00:10:44,730
+"Splitting" "Splitting" "Splitting" "Splitting"
+
+153
+00:10:44,730 --> 00:10:44,750
+"Splitting" "Splitting" "Splitting" "Splitting"
+
+154
+00:10:44,750 --> 00:10:56,130
+"Splitting" "Splitting" "Splitting" "Spl
+
+155
+00:10:59,800 --> 00:11:05,500
+Target_Attribute، كيف أنا بدي أعمل الـ
+
+156
+00:11:05,500 --> 00:11:08,140
+Splitting الآن؟ عملية الـ Splitting هي عبارة عن
+
+157
+00:11:08,140 --> 00:11:11,180
+آخذ نسخة من الـ Attributes، أنا ما بدي أخرّب في
+
+158
+00:11:11,180 --> 00:11:13,640
+الـ DataFrame الأصلي اللي موجود عندي هنا، فبأخذ
+
+159
+00:11:13,640 --> 00:11:19,760
+نسخة منه، وراح أقول له أنا هنا الـ Data أو ممكن أسميها الـ
+
+160
+00:11:19,760 --> 00:11:25,480
+Attributes مباشرة، Attribute
+
+161
+00:11:25,480 --> 00:11:31,770
+DataFrame.copy()
+
+162
+00:11:31,770 --> 00:11:39,270
+بدي أحدث الـ Outcome
+
+163
+00:11:39,270 --> 00:11:45,570
+وهذا موجود على الـ Axis رقم واحد، فعلياً مش هيحدثه
+
+164
+00:11:45,570 --> 00:11:48,570
+لأنه ما قلت له إنه copy، فبدي آخذ نسخة من الـ
+
+165
+00:11:48,570 --> 00:11:51,470
+DataFrame هذا وأحدث الـ Outcome، وبدي آخذ منه
+
+166
+00:11:51,470 --> 00:11:56,930
+مين؟ اللي هم في الـ Attributes تمام؟ وفي عندي Target
+
+167
+00:11:59,700 --> 00:12:06,340
+"attribute = DataFrame.drop(the outcome)", وهكذا أصبح لدي two arrays تمثل
+
+168
+00:12:06,340 --> 00:12:15,140
+الـ "attributes" من الـ "age" إلى الـ "pregnancy"
+
+169
+00:12:20,390 --> 00:12:24,550
+والأخير بيمثل الـ Outcome، أنا سميته ايش؟ الـ Target
+
+170
+00:12:24,550 --> 00:12:28,690
+هذا الفصل مهم جدًا يا جماعة الخير بالنسبة لنا لأنه
+
+171
+00:12:28,690 --> 00:12:34,710
+من خلاله أنا بقدر أقول والله إن الـ data تبعتي تمت
+
+172
+00:12:34,710 --> 00:12:38,570
+طبعًا أنا الآن البرنامج جاب لي إنه okay، أخذت رقم
+
+173
+00:12:38,570 --> 00:12:43,890
+أربعة، هذه نفذت بدون أي مشاكل، إذا حابب أنت تعمل
+
+174
+00:12:43,890 --> 00:12:48,070
+الـ attribute describe أو تشوف
+
+175
+00:12:56,430 --> 00:12:59,030
+الخطوة التالية اللي أنا بدي أسويها في الـ
+
+176
+00:12:59,030 --> 00:13:01,630
+preparation، برضه من تحت الـ preparation، اللي أنا
+
+177
+
+223
+00:17:11,250 --> 00:17:16,170
+أو لـ train size 70 تمام؟ وبيمشي الحال، الآن الـ Y
+
+224
+00:17:16,170 --> 00:17:21,530
+train هي عبارة عن 70% من الـ target بناء على الـ
+
+225
+00:17:21,530 --> 00:17:25,620
+index اللي تم أخذها، والـ Y-test هي عبارة عن الـ
+
+226
+00:17:25,620 --> 00:17:29,700
+sample اللي موجودة عندنا طبعاً عشان نتأكد أن الأمور
+
+227
+00:17:29,700 --> 00:17:33,620
+تمام، والـ splitting صح تمت، سأروح أنا أقول له X
+
+228
+00:17:33,620 --> 00:17:40,060
+train.
+
+229
+00:17:40,060 --> 00:17:44,760
+head، وبدي أقول له بس يعرض الأول ثلاثة منهم أو مش
+
+230
+00:17:44,760 --> 00:17:47,620
+قضية، هي الأول عشرة بس عشان نشوف الـ indices اللي
+
+231
+00:17:47,620 --> 00:17:53,740
+موجودة فيها، ولاحظوا زي ما حكينا هذا عبارة عن الـ
+
+232
+00:17:53,740 --> 00:18:01,180
+index. الآن في المقابل، لو أنا روحت عرضت الـ Y
+
+233
+00:18:01,180 --> 00:18:06,600
+-Train، وقلت له هي في السلة اللي بعدها، بس عشان
+
+234
+00:18:06,600 --> 00:18:14,000
+أؤكد لكم الـ Ytrain.head
+
+235
+00:18:14,000 --> 00:18:21,550
+وخليني على عشرة كذلك، Run، طلع معي في الـ index
+
+236
+00:18:21,550 --> 00:18:29,230
+و Y train
+
+237
+00:18:29,230 --> 00:18:29,770
+و Y train
+
+238
+00:18:46,050 --> 00:18:50,710
+أنا أخطأت ثانية يا جماعة الخير في التسمية، هي المفروض
+
+239
+00:18:50,710 --> 00:18:57,310
+X test، X test
+
+240
+00:18:57,310 --> 00:19:07,870
+thirty three five green، سيعمل run مرة ثانية.
+
+241
+00:19:07,870 --> 00:19:15,090
+سيعمل run للـ high أه، هيك تمام. أنا اللي أختار في
+
+242
+00:19:15,090 --> 00:19:19,490
+تركيب العناصر اللي فوق، أبدأ بالـ X test، بالـ
+
+243
+00:19:19,490 --> 00:19:24,250
+attributes، وبالـ Y، الـ target طبعاً، هي ميزة أنه
+
+244
+00:19:24,250 --> 00:19:27,990
+أنا فعلياً بضل أتبّع الـ data شو صار فيها، ما بخطئش،
+
+245
+00:19:27,990 --> 00:19:32,690
+لاحظوا 155، 155 هي نفس الـ index اللي موجود يعني،
+
+246
+00:19:32,690 --> 00:19:34,750
+فأنا أموري من ناحية الـ database الآن أو الـ
+
+247
+00:19:34,750 --> 00:19:38,490
+splitting للـ data جاهزة، بحيث أنه أنا جسمت الـ
+
+248
+00:19:38,490 --> 00:19:41,450
+data، فصلت الـ attributes، الـ data attributes
+
+249
+00:19:41,450 --> 00:19:45,030
+والـ target attributes، فصلت كل واحد فيهم في data
+
+250
+00:19:45,030 --> 00:19:48,810
+file، هو روحت للـ data set أو الـ two data frames
+
+251
+00:19:48,810 --> 00:19:55,210
+دول فصلتهم كمان لـ test set وفوقه train set، وهأبدأ
+
+252
+00:19:55,210 --> 00:20:00,370
+أستخدم train set في موضوع الـ classification الآن.
+
+253
+00:20:00,370 --> 00:20:06,830
+سأبدأ أستخدم الـ K nearest neighbor (KNN)
+
+254
+00:20:06,830 --> 00:20:15,070
+أو ما يعرف بالـ K nearest neighbor
+
+255
+00:20:22,150 --> 00:20:25,250
+هنا، جماعة الخير، في الـ K nearest neighbor model
+
+256
+00:20:25,250 --> 00:20:28,950
+يقول إنها أهم شغلة تريد التعرف عليها، من أين تريد
+
+257
+00:20:28,950 --> 00:20:39,370
+أن تعمل الـ import؟ لأن من الـ scikit-learn.
+
+258
+00:20:39,370 --> 00:20:43,530
+طبعاً هنا عندي عائلة اسمها neighbors أو الـ
+
+259
+00:20:43,530 --> 00:20:47,750
+library، عشان ما أحد يقول ليه عائلة neighbors، سأروح
+
+260
+00:20:47,750 --> 00:20:48,590
+أقول له import
+
+261
+00:20:54,790 --> 00:21:06,810
+from sklearn.neighbors import KNeighborsClassifier as KN
+
+262
+00:21:06,810 --> 00:21:10,870
+as KN
+
+263
+00:21:10,870 --> 00:21:17,930
+الآن هذا الموديل أنا ممكن أنشئه مباشرة KNN
+
+264
+00:21:42,660 --> 00:21:46,440
+والخطوة التالية اللي بعد هيك أنا ممكن أحدد له
+
+265
+00:21:50,220 --> 00:21:53,040
+الـ model أو أروح أعمله fit اللي كان المفروض
+
+266
+00:21:53,040 --> 00:21:57,460
+أحدد له الـ dataset اللي بده يعمل عليها training
+
+267
+00:21:57,460 --> 00:22:02,180
+أو مقارنة، هي المفروض الـ train dataset لكن في
+
+268
+00:22:02,180 --> 00:22:07,800
+ملاحظة مهمة جداً قبل ما نكمل، طبعاً بإمكاني أنا أوقف
+
+269
+00:22:07,800 --> 00:22:11,620
+هذه وأعلقها.
+
+270
+00:22:17,090 --> 00:22:21,130
+الأسماء، جماعة الخير، هي من أجل الاختصار، الـ AS من أجل
+
+271
+00:22:21,130 --> 00:22:24,470
+الاختصار عشان ما أضطر أكتب الاسم بالكامل، يعني لو
+
+272
+00:22:24,470 --> 00:22:29,750
+أنا بدي أكتبها، سأروح أقول KN_model
+
+273
+00:22:29,750 --> 00:22:33,670
+equals
+
+274
+00:22:33,670 --> 00:22:43,610
+KNeighborsClassifier، وKN_model equals
+
+275
+00:22:43,610 --> 00:22:48,470
+خمسة، عفواً، خمسة، خليني أعمل نفسي، أمشي على نفس
+
+276
+00:22:48,470 --> 00:22:51,230
+الـ style هذه، واللي فوق نفس المعنى، بس أنا هنا
+
+277
+00:22:51,230 --> 00:22:55,530
+أختصر في الكتابة بناءً على... بعمل alias name
+
+278
+00:22:55,530 --> 00:22:59,210
+وبأستخدم الـ alias name، الآن بضل أقول لهم الـ KNN
+
+279
+00:22:59,210 --> 00:23:06,010
+_model.fit
+
+280
+00:23:06,010 --> 00:23:12,710
+وفي الـ training، شو بياخد؟ بياخد الـ X_train والـ Y
+
+281
+00:23:12,710 --> 00:23:18,620
+train، لأن هذه هي الـ data اللي أنا بعمل عليها أو
+
+282
+00:23:18,620 --> 00:23:22,260
+من خلالها الـ training. لو أنا اشتغلت، عملت له run
+
+283
+00:23:22,260 --> 00:23:35,620
+وشكلي
+
+284
+00:23:35,620 --> 00:23:37,620
+أنا أخطأت في الـ KNeighborsClassifier
+
+285
+00:23:46,470 --> 00:23:51,630
+KNeighborsClassifier، صح الصح، الـ spelling صح
+
+286
+00:23:51,630 --> 00:24:05,130
+"EG", "EI", "GH", "D", "O", "R", "S"
+
+287
+00:24:05,130 --> 00:24:08,190
+ليش؟
+
+288
+00:24:21,090 --> 00:24:35,170
+ممكن عشان أنا حطيت الـ alias name فوق، عشان
+
+289
+00:24:35,170 --> 00:24:40,270
+حطيت الـ alias name، عشان حطيت الـ alias name، لأن
+
+290
+00:24:40,270 --> 00:24:45,710
+الـ alias name بديله، لكن لو أنا صححت هذا وعلّقت
+
+291
+00:24:45,710 --> 00:24:46,030
+هذه
+
+292
+00:24:52,850 --> 00:25:00,330
+مش هيكون في خطأ، فممكن
+
+293
+00:25:00,330 --> 00:25:03,590
+أنا أستخدم هاي أو هاي حسب الحالة اللي موجودة
+
+294
+00:25:03,590 --> 00:25:08,170
+عليها، تمام. فالـ model أصبح جاهز يتعرف على الـ
+
+295
+00:25:08,170 --> 00:25:10,890
+test data أو الـ test set اللي أنا بدي أشتغل
+
+296
+00:25:10,890 --> 00:25:14,950
+عليها، وهي بطبيعة الحال مجسّمة لـ attributes وطبعاً
+
+297
+00:25:14,950 --> 00:25:19,510
+الخطوة التالية، أنا عم بدي أروح أعمل أو بدي أشوف
+
+298
+00:25:19,510 --> 00:25:23,510
+الـ measures، إيش ممكن يسوي لهالـ element اللي موجود
+
+299
+00:25:23,510 --> 00:25:27,050
+أو الـ model اللي أنا أنشأته، لكن عشان أنا أختبر الـ
+
+300
+00:25:27,050 --> 00:25:30,530
+model، جماعة الخير، أو بدي أجرب الـ model، خليني أشوف
+
+301
+00:25:30,530 --> 00:25:35,450
+أو آخذ عينة من الـ data اللي موجودة عندي في موضوع
+
+302
+00:25:35,450 --> 00:25:39,070
+من
+
+303
+00:25:39,070 --> 00:25:42,450
+الـ dataset بشكل عام، أنا بدي أروح وأقول له أنا
+
+304
+00:25:42,450 --> 00:25:46,190
+طبعاً، أول شيء هيكون استخدام الـ numpy اللي
+
+305
+00:25:46,190 --> 00:25:56,740
+موجودة فوق، سأروح أقول له T1، هذه الـ array مكونة من
+
+306
+00:25:56,740 --> 00:26:07,640
+مجموعة أرقام، وليكن
+
+307
+00:26:07,640 --> 00:26:12,940
+على سبيل المثال الصف الأول، وهذه الـ class موجودة
+
+308
+00:26:12,940 --> 00:26:13,320
+هنا.
+
+309
+00:26:17,220 --> 00:26:21,720
+الـ tabs هذه بدي أستبدلها بـ commas.
+
+310
+00:26:31,800 --> 00:26:35,140
+طبعاً، يا عزيزي، في شغل مهم لازم نقوله الآن، أنه
+
+311
+00:26:35,140 --> 00:26:38,300
+مش ضروري الـ prediction دائماً، يعني ما أحد بيقول
+
+312
+00:26:38,300 --> 00:26:40,800
+الـ prediction بيكون صحيح أو بيكون حقيقي 100%،
+
+313
+00:26:40,800 --> 00:26:43,720
+لازم يكون في أخطاء عندي دائماً أو في معظم الأحيان،
+
+314
+00:26:43,720 --> 00:26:47,160
+يكون في عندك أخطاء، وكل ما ارتفع أو كل ما كانت الـ
+
+315
+00:26:47,160 --> 00:26:50,520
+prediction تبعته، الـ score تبعها أعلى بيكون كويسة.
+
+316
+00:26:50,520 --> 00:26:57,720
+Doc reshaping، كل هذا اعتمد المصفوفة هذه على إي واحد
+
+317
+00:26:57,720 --> 00:27:06,120
+سالب واحد، وطبعاً هاي الـ target، سأحط هنا target equals
+
+318
+00:27:06,120 --> 00:27:14,720
+one، وخليني أنا أنسخ هذه، هيك Ctrl V، وابدأ أجي على
+
+319
+00:27:14,720 --> 00:27:20,760
+الـ raw اللي رقمه خمسة، أنسخه، والـ target تبعته صفر،
+
+320
+00:27:20,760 --> 00:27:23,200
+هذا بدي أسميه T5.
+
+321
+00:27:33,150 --> 00:27:38,710
+بنفس الكلام الـ
+
+322
+00:27:38,710 --> 00:27:47,030
+rows اللي عندي، بكمّس عشان تتحول الـ rows اللي عندي لـ
+
+323
+00:27:47,030 --> 00:27:53,370
+مصفوفة، تمام، بنفس العدد.
+
+324
+00:28:01,810 --> 00:28:08,410
+تمام، ليس مشكلة لأن عندما أنا أعمل train للـ model
+
+325
+00:28:08,410 --> 00:28:11,130
+اللي أنا أنشأته، model.kneighbors لديه method
+
+326
+00:28:11,130 --> 00:28:17,070
+اسمها model.kneighbors، أنا هايه الـ model تبعي KNN
+
+327
+00:28:17,070 --> 00:28:24,430
+_model.kneighbors
+
+328
+00:28:25,990 --> 00:28:30,270
+ولا مين؟ وأعطيه مين؟ وأعطيه الـ test element اللي
+
+329
+00:28:30,270 --> 00:28:37,030
+أنا بدي أفحصه، وليكن T1 كمُدخل، ومع عدد عناصر الجوار
+
+330
+00:28:37,030 --> 00:28:42,430
+خمسة، عدد عناصر الجوار خمسة. بتحس في لحظة من اللحظات
+
+331
+00:28:42,430 --> 00:28:47,050
+أن الـ K الخمسة اللي أنا عنها، ما لها علاقة بهذه الـ
+
+332
+00:28:47,050 --> 00:28:50,290
+method اللي موجودة. خليني أشوف، وأروح طبعاً هذه الـ
+
+333
+00:28:50,290 --> 00:28:55,370
+method بترجع لي two vectors، الفكتور الأول يمثل الـ
+
+334
+00:28:55,370 --> 00:28:59,930
+distances، كما
+
+335
+00:28:59,930 --> 00:29:08,790
+والفكتور الثاني الـ indices، تمام؟ الـ indices أو الـ
+
+336
+00:29:08,790 --> 00:29:15,850
+indices، نفس المصطلحات، indices لمن؟
+
+337
+00:29:15,850 --> 00:29:18,550
+لـ indices
+
+338
+00:29:22,020 --> 00:29:27,480
+للـ raw اللي هي صاحبة أقصر مسافة، يعني الـ
+
+339
+00:29:27,480 --> 00:29:31,600
+kneighbors هدول بيروحوا بيجيبوا لي أقرب خمسة للـ element
+
+340
+00:29:31,600 --> 00:29:36,760
+لـ T1، أقرب خمسة لـ T1، وبما أنه المفروض T1 يمثل
+
+341
+00:29:36,760 --> 00:29:39,480
+الـ raw الأول في الـ dataset اللي عندي، فسيروح
+
+342
+00:29:39,480 --> 00:29:43,460
+يقول لي الـ index رقم صفر، أو الـ index رقم صفر، هيكون
+
+343
+00:29:43,460 --> 00:29:47,680
+هذا الـ distance تبعك صفر، وهيجيب لي الـ index في
+
+344
+00:29:47,680 --> 00:29:52,680
+مصفوفة ثانية. أنا الآن سأروح أقول له event، خلينا
+
+345
+00:29:52,680 --> 00:29:58,480
+نشوفها في مجال آخر. هي run، الآن المفروض تم التنفيذ.
+
+346
+00:29:58,480 --> 00:30:04,580
+سآخذ كود جديد، وبدي أروح أطبع الـ distances.
+
+347
+00:30:22,010 --> 00:30:26,970
+لاحظوا يا جماعة الخير، صفر، عشرة، خمسة وخمسين،
+
+348
+00:30:26,970 --> 00:30:34,170
+تسعة وعشرة، تسعة وعشرة، عشرين، عشرة
+
+349
+00:30:34,170 --> 00:30:34,270
+وعشرة، وعشرة وعشرة، وعشرة وعشرة، وعشرة وعشرة،
+
+350
+00:30:34,270 --> 00:30:34,290
+عشرة وعشرة، وعشرة وعشرة، وعشرة وعشرة، وعشرة
+
+351
+00:30:34,290 --> 00:30:34,350
+وعشرة، وعشرة وعشرة، وعشرة وعشرة، وعشرة وعشرة، عشرة
+
+352
+00:30:34,350 --> 00:30:34,570
+وعشرة، وعشرة وعشرة، وعشرة وعشرة، وعشرة وعشرة،
+
+353
+00:30:34,570 --> 00:30:38,390
+عشرة وعشرة، وعشرة وعشرة، وعشرة وعشرة، وعشرة
+
+354
+00:30:38,390 --> 00:30:47,440
+وعشرة، وعشرة وعشرة، وعشرة وعشرة، وعشرة وعشرة. هذه
+
+355
+00:30:47,440 --> 00:30:51,080
+أقرب distances، لأنه بيرتب لي إياها ترتيب تصاعدي حسب
+
+356
+00:30:51,080 --> 00:30:54,960
+الأقرب، فالأقرب. طيب، الآن إذا أنا بدي أشوف الـ
+
+357
+00:30:54,960 --> 00:30:58,900
+indices تبع العناصر اللي موجودة عندي، أو بدي أشوف
+
+358
+00:30:58,900 --> 00:31:02,100
+الـ target تبع الـ indices اللي موجودة عندي، ممكن
+
+359
+00:31:02,100 --> 00:31:09,960
+أنا أروح أقول له target of
+
+360
+00:31:09,960 --> 00:31:14,080
+I from
+
+361
+00:31:15,690 --> 00:31:22,530
+الـ I موجودة أين؟ أو عفواً، for الـ I for
+
+362
+00:31:22,530 --> 00:31:30,390
+I in، الـ indices، أنا
+
+363
+00:31:30,390 --> 00:31:34,810
+هذه مصفوفة برضه من بعدي، سأروح أقول له بعد أيام،
+
+364
+00:31:34,810 --> 00:31:35,310
+فأشرح
+
+365
+00:31:52,280 --> 00:32:00,580
+target غلط طبعاً.
+
+366
+00:32:00,580 --> 00:32:04,760
+هان لما كنت بحاول أن أطبع الـ element، بيقول لي إن
+
+367
+00:32:04,760 --> 00:32:08,140
+هذا عبارة عن object، طب الـ object أنا بدي أجيب الـ
+
+368
+00:32:08,140 --> 00:32:10,920
+contents تبعته، أو محتوى الـ object اللي عندي هان.
+
+369
+00:32:10,920 --> 00:32:15,300
+فهينطبع لي بالشكل اللي موجود عندي هان، جلبناها على
+
+370
+00:32:15,300 --> 00:32:19,570
+السبعة اللي موجودة فوق، الـ indices تبعتهم، أو الـ
+
+371
+00:32:19,570 --> 00:32:22,590
+classes بناءً على الـ indices اللي موجودة عندي.
+
+372
+00:32:22,590 --> 00:32:26,550
+يعني احنا اتفقنا الـ indices هي عبارة عن الـ index
+
+373
+00:32:26,550 --> 00:32:33,910
+تبع الـ train set أو الـ X-train القريبة من، أو
+
+374
+00:32:33,910 --> 00:32:39,450
+الأقرب لـ T1، فكان صفر، وصفر، وهذه الـ labels تبعتهم
+
+375
+00:32:39,450 --> 00:32:43,630
+لأن أنا بدي أعمل voting، سأروح أعدّ أنا هدول، هي واحد،
+
+376
+00:32:43,630 --> 00:32:48,250
+اثنين، ثلاثة، أربعة، خمسة، خمسة من سبعة zero، واثنين
+
+377
+00:32:48,250 --> 00:32:53,530
+من سبعة one، معناته أن الـ class اللي موجود عندي هنا
+
+378
+00:32:53,530 --> 00:32:59,290
+سبعة. طب لو أنا بدي أعيد التجربة هي لخمسة، وهي run
+
+379
+00:32:59,290 --> 00:33:06,780
+السطر اللي بعديها، وهي الـ cell اللي بعديها،
+
+380
+00:33:06,780 --> 00:33:11,760
+فجائني أنه الآن برضه صفر، بس القيم اللي عندي فوق
+
+381
+00:33:11,760 --> 00:33:15,320
+اختلفت، مش قضية لأن هي في الآخر الـ values اللي
+
+382
+00:33:15,320 --> 00:33:18,720
+عندها اختلفت. طب لو أنا فكرت أنه أغير في الـ values
+
+383
+00:33:18,720 --> 00:33:25,840
+اللي عندها، حأروح أعمل run عشان آخذها، okay، هي
+
+384
+00:33:25,840 --> 00:33:32,900
+خليني أقول هنا 30، هي run، لاحظوا الـ distance
+
+385
+00:33:32,900 --> 00:33:38,070
+اختلافها، اختلفت الـ distance كلياً، الآن والأخير هي
+
+386
+00:33:38,070 --> 00:33:44,910
+run، وهيكون في عندي ثلاثة one وأربعة zero، فهو في
+
+387
+00:33:44,910 --> 00:33:47,910
+الآخر هيعمل الـ classification على أنه zero،
+
+388
+00:33:47,910 --> 00:33:51,230
+ممتاز، لكن هذا برضه مش هو الشغل اللي احنا فعلياً
+
+389
+00:33:51,230 --> 00:33:55,450
+محتاجينه، بس نحط بعض الـ comments هنا.
+
+390
+00:34:03,930 --> 00:34:11,170
+print target of
+
+391
+00:34:11,170 --> 00:34:18,030
+the most of
+
+392
+00:34:18,030 --> 00:34:23,630
+the nearest neighbors
+
+393
+00:34:23,630 --> 00:34:24,950
+or
+
+394
+00:34:49,610 --> 00:34:52,410
+"الأزدهار"، "الأزدهار".
+
+395
+00:34:56,600 --> 00:35:01,560
+الآن سأنتقل لجزئية أكثر أهمية عشان نتكلم عنها،
+
+396
+00:35:01,560 --> 00:35:04,920
+classification، عشان أشتغل على classification من
+
+397
+00:35:04,920 --> 00:35:07,640
+نفس الـ library "from sklearn.neighbors import"
+
+398
+00:35:07,640 --> 00:35:13,780
+"import" في عندي الـ "K nearest neighbor" أو الـ
+
+399
+00:3
+
+445
+00:40:00,150 --> 00:40:05,040
+الـ Confusion Matrix الموجودة هنا، في عندي
+
+446
+00:40:05,040 --> 00:40:15,880
+الـ classification model evaluation، هنبدأ
+
+447
+00:40:15,880 --> 00:40:25,940
+الآن، من الـ ASCII layer import matrix
+
+448
+00:40:28,280 --> 00:40:31,460
+الآن بدي أجيب الـ Matrix، إيش الـ Matrix جامعة
+
+449
+00:40:31,460 --> 00:40:34,540
+الخيار؟ تحتوي على أنه من خلالها أنا ممكن أنشأ الـ
+
+450
+00:40:34,540 --> 00:40:37,100
+confusion matrix، أحسب الـ accuracy، أحسب الـ
+
+451
+00:40:37,100 --> 00:40:40,240
+precision، أحسب الـ recall، أحسب الـ F-measure، كل هذه
+
+452
+00:40:40,240 --> 00:40:44,260
+لدى الـ attribute، عفواً، للكلاسيفاير اللي موجود
+
+453
+00:40:44,260 --> 00:40:49,940
+عندها، وخليني أنا أبدأ مع الـ confusion matrix،
+
+454
+00:41:07,520 --> 00:41:13,880
+الـ M، الـ CM،  إيش معنى CM؟
+
+455
+00:41:24,700 --> 00:41:29,180
+هنا كل الـ evaluation functions الموجودة عندنا
+
+456
+00:41:29,180 --> 00:41:33,420
+هتاخد مني شغلتين: هتاخد مني الـ y_test اللي هو الـ
+
+457
+00:41:33,420 --> 00:41:37,260
+label الحقيقي، والـ y_predicted أو الـ predicted
+
+458
+00:41:37,260 --> 00:41:43,800
+الـ y_predict، وهي
+
+459
+00:41:43,800 --> 00:41:48,590
+بدي أروح أقول له اطبع لي الـ matrix اللي عندنا اللي
+
+460
+00:41:48,590 --> 00:41:52,010
+هي الـ Confusion Matrix، الـ Test Set حجمها
+
+461
+00:41:52,010 --> 00:41:57,450
+هي 120, 25، True Positive، True Negative، False Positive، False
+
+462
+00:41:57,450 --> 00:42:02,570
+Negative، False Positive، False Negative، بس إيش الـ
+
+463
+00:42:02,570 --> 00:42:08,250
+classes الموجودة عندي يا جماعة الخير؟ الـ
+
+464
+00:42:08,250 --> 00:42:11,270
+classes يا إخواننا ويا أخواتي بيكونوا  تنتبهوا
+
+465
+00:42:11,270 --> 00:42:13,670
+بشكل كويس، لأنه أنا ما حددت له إيش الـ classes، فإيش
+
+466
+00:42:13,670 --> 00:42:17,770
+هو بياخدهم مباشرةً، بيروح بيعتمد على الآن أول ما قرأت
+
+467
+00:42:17,770 --> 00:42:22,890
+data set، أول ما قرأت data set، إيش أول class واجهه؟
+
+468
+00:42:22,890 --> 00:42:29,870
+طبعاً أنا بتكلم في الـ test set هذا، لأن أول ما
+
+469
+00:42:29,870 --> 00:42:32,730
+زودته، زودته غلط في الـ Y_predict، أول element في
+
+470
+00:42:32,730 --> 00:42:37,250
+الـ Y_test
+
+471
+00:42:37,250 --> 00:42:41,870
+الـ Y_test
+
+472
+00:42:46,220 --> 00:42:49,820
+كان واحد، فخلاص، بيعتبر أنه هذا للـ Class الأول،
+
+473
+00:42:49,820 --> 00:42:53,980
+تمام؟ وهذا للـ Class الثاني، طبعاً هذه العناصر
+
+474
+00:42:53,980 --> 00:42:56,240
+معناته أنها الـ confusion matrix، ومن خلالها أنا
+
+475
+00:42:56,240 --> 00:43:00,000
+بنطلق وبحسب كل حاجة، طب إذا أنا بدي أحسب الـ
+
+476
+00:43:00,000 --> 00:43:05,240
+accuracy الآن،
+
+477
+00:43:05,240 --> 00:43:08,260
+اذكروا، الـ accuracy كانت إيش بتساوي؟ الـ true
+
+478
+00:43:08,260 --> 00:43:12,360
+positive زائد الـ true negative على كل العناصر
+
+479
+00:43:12,360 --> 00:43:13,600
+المجموعة هنا
+
+480
+00:43:19,260 --> 00:43:25,360
+سأقوم بإعادة الـ Accuracy، ACC بتساوي
+
+481
+00:43:25,360 --> 00:43:28,040
+(repeating "تساوي متركز" is removed)
+
+486
+00:43:39,340 --> 00:43:48,690
+بتساوي 72.72، الـ Accuracy للـ Model الموجودة عندنا
+
+487
+00:43:48,690 --> 00:43:55,850
+هان، Matrix.precision  (dot instead of underscore)
+
+488
+00:43:55,850 --> 00:44:01,430
+72.27 ممتاز، بدي أنتقل للخطوة اللي بعدها، لو أنا بدي
+
+489
+00:44:01,430 --> 00:44:05,330
+أحسب الـ F1-score أو الـ precision للـ first
+
+490
+00:44:05,330 --> 00:44:07,690
+class الموجودة عندي هنا
+
+491
+00:44:15,790 --> 00:44:20,710
+بنفس الطريقة الموجودة عندي هنا، بدي أسميها
+
+492
+00:44:20,710 --> 00:44:29,190
+precision = matrix.precision_score (dot instead of underscore)
+
+493
+00:44:29,190 --> 00:44:35,950
+وبدي أعطيه المجموعتين، ولما أنا بدي أقول له
+
+494
+00:44:35,950 --> 00:44:41,010
+(Corrected sentence:  print(precision))
+
+495
+00:44:48,420 --> 00:44:55,240
+بتحملوني، شو رأيكم؟ يعني 65، اللي بعدها أحسن من الـ
+
+496
+00:44:55,240 --> 00:45:01,800
+recall،  الأمور كلها بالشكل هذا اللي هتتجمع، طبعاً
+
+497
+00:45:01,800 --> 00:45:04,560
+لاحظوا الـ classification Model، ككل، الـ Precision، الـ
+
+498
+00:45:04,560 --> 00:45:07,900
+First Class، الـ Recall للـ First Class، هيك هيك هيك (Repeating "هيك" is removed)
+
+499
+00:45:07,900 --> 00:45:11,560
+(Repeating "هيك" is removed)
+
+501
+00:45:29,740 --> 00:45:38,460
+بالنسبة، رأيي صارت بدلعة ودنيا، يا جماعة الخير، No
+
+502
+00:45:38,460 --> 00:45:43,740
+attribute
+
+503
+00:45:43,740 --> 00:45:53,160
+recall_score أو
+
+504
+00:45:53,160 --> 00:45:53,840
+الـ F1-score
+
+505
+00:46:04,040 --> 00:46:10,680
+F1 = matrix.F1_score (dot instead of underscore)
+
+506
+00:46:10,680 --> 00:46:18,160
+(underscore added)
+
+507
+00:46:21,880 --> 00:46:26,800
+آخر شغلة، أنا ممكن أجيب كل الـ values مع بعضها من
+
+508
+00:46:26,800 --> 00:46:31,520
+خلال شغلة نسميها الـ Classification Report
+
+509
+00:46:31,520 --> 00:46:37,800
+الـ Classification Report ممكن يساعدني بشكل كبير
+
+510
+00:46:37,800 --> 00:46:41,520
+بحيث أنه أنا ما احتاجش أن أكتب كل حاجة مع بعضها
+
+511
+00:46:41,520 --> 00:46:45,400
+Classification
+
+512
+00:46:45,400 --> 00:46:45,900
+Report
+
+513
+00:46:50,530 --> 00:46:57,750
+أو الـ cls_report = matrix.classification (underscore added and "dot" instead of "underscore")
+
+514
+00:46:57,750 --> 00:47:01,430
+_report (underscore added)
+
+515
+00:47:01,430 --> 00:47:10,310
+بدي أدّيله الـ method أو عفواً
+
+516
+00:47:10,310 --> 00:47:14,010
+الـ to function أو أزوده بالـ predicted، بالـ true
+
+517
+00:47:14,010 --> 00:47:18,670
+label والـ predicted label، وحروح أقول له هنا، اطبع لي
+
+518
+00:47:18,670 --> 00:47:19,890
+الـ classifier
+
+519
+00:47:23,050 --> 00:47:26,830
+"Classification Report"، وهنا جاب لي الرابورت
+
+520
+00:47:26,830 --> 00:47:32,290
+الكامل، بدأ بالـ "Precision"، والـ "Recall"، والـ "F1
+
+521
+00:47:32,290 --> 00:47:36,090
+Score"،  أي القيم الثلاث اللي موجودة عندها للـ
+
+522
+00:47:36,090 --> 00:47:41,470
+"Class"، طبعاً للـ "Class Zero"، لأن الـ "Report"
+
+523
+00:47:41,470 --> 00:47:45,430
+لازم يبين كل القيم، لازم يبين كل حاجة، الآن الـ
+
+524
+00:47:45,430 --> 00:47:51,210
+"Recall"، الـ "Precision"
+
+525
+00:47:51,210 --> 00:47:55,870
+83، الـ Recall 78، الـ F1-score
+
+526
+00:47:55,870 --> 00:48:07,230
+والـ Accuracy وينها؟ ليش هي كترت داخلات مع بعض؟
+
+527
+00:48:15,290 --> 00:48:21,970
+الـ Accuracy بشكل عام هي 73، لماذا
+
+528
+00:48:21,970 --> 00:48:26,930
+72.72؟ هنا في الـ robot عمل الـ rounding أو
+
+529
+00:48:26,930 --> 00:48:32,090
+القيم الموجودة عندك هنا، فهي فعلياً 72.72، فبعمل
+
+530
+00:48:32,090 --> 00:48:34,950
+الـ rounding، الآن الـ Recall للـ Zero زي ما قلنا
+
+531
+00:48:34,950 --> 00:48:38,090
+83، الـ Precision والـ Recall للـ Class الأول
+
+532
+00:48:43,190 --> 00:48:49,230
+هي الـ Class number one لما
+
+533
+00:48:49,230 --> 00:48:56,040
+قلت له احسب الـ precision، جالي 66، هذه هي تقريباً الـ
+
+534
+00:48:56,040 --> 00:49:03,800
+55.كذا، الـ 56، الـ recall اللي هي 55.8، بعملها
+
+535
+00:49:03,800 --> 00:49:10,240
+تقريباً، الـ F1-score اللي كانت بتمثل الـ 60، تمام؟
+
+536
+00:49:10,240 --> 00:49:13,960
+والـ support  لـ values الموجودة عندها فهي في الـ
+
+537
+00:49:13,960 --> 00:49:16,880
+report هذا، أنا جيبت كل الـ values بالنسبة لي لمرة
+
+538
+00:49:17,890 --> 00:49:23,690
+واحدة، بتمنى يكون الفيديو هذا يوضح لكم فعلياً إيش
+
+539
+00:49:23,690 --> 00:49:27,590
+أنا محتاج في الـ classification، طبعاً هذا الكلام
+
+540
+00:49:27,590 --> 00:49:32,170
+بيطبق مع كل data set أو مع كل classification
+
+541
+00:49:32,170 --> 00:49:36,630
+model، وكل classification model فيه خاصية معينة،
+
+542
+00:49:36,630 --> 00:49:40,210
+يمكن يكون الشغل الوحيد الآن في الاختلاف عندكم اللي
+
+543
+00:49:40,210 --> 00:49:42,770
+هو استدعاء الـ classifier،  باريخ الاستفعال الـ
+
+544
+00:49:42,770 --> 00:49:47,870
+classifier، بينما الـ fit حتظل ثابتة للجميع، الـ
+
+545
+00:49:47,870 --> 00:49:51,270
+predict حتظل ثابتة للجميع، والـ measurement حتظل
+
+546
+00:49:51,270 --> 00:49:56,590
+موجودة لكل العناصر، لكل الـ classifiers بنفس
+
+547
+00:49:56,590 --> 00:50:00,910
+الطريقة، أنا هيك خلصت، بتمنى إن شاء الله تعالى
+
+548
+00:50:04,250 --> 00:50:07,330
+أتمنى من الله تبارك وتعالى أن أكون فعلاً وفقت
+
+549
+00:50:07,330 --> 00:50:10,850
+في أني خلال التسجيل هذا أني أوضح لكم موضوع
+
+550
+00:50:10,850 --> 00:50:16,390
+الـ classification، ومن خلاله استخدمت الـ Canary
+
+551
+00:50:16,390 --> 00:50:20,370
+Snapper واستخدمت الـ Kaggle كـ Tool مختلفة عن الـ
+
+552
+00:50:20,370 --> 00:50:24,770
+IPython في الـ local machine الموجودة عندي، إذا في
+
+553
+00:50:24,770 --> 00:50:29,270
+أي سؤال، احفظوه  لـ next session، الـ online session
+
+554
+00:50:29,270 --> 00:50:33,690
+of the discussion، وعسى أن نكون وفقنا
+
+555
+00:50:33,690 --> 00:50:36,530
+دائماً وأبداً، والسلام عليكم ورحمة الله وبركاته
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9DgNoAZTwqg_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9DgNoAZTwqg_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..e711724308f187a5baf5d36c5bf8902d63efdbf7
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9DgNoAZTwqg_raw.json
@@ -0,0 +1 @@
+{"segments": [{"id": 1, "seek": 2852, "start": 4.52, "end": 28.52, "text": "بسم الله الرحمن الرحيم الصلاة والسلام على رسول الله أهلا وسهلا بكم في لقاءة من جديد من لقاءات مساقة تنقيب البيانات وان شاء الله اليوم سأتكلم معاكم عن .. سأشتغل معاكم عملي زي ما أشتغلت في الـ preprocessing سأعمل فيديو قصير عن ال classification وماذا أريد أن أفعل في عمل ال classification", "tokens": [3555, 38251, 21984, 34892, 5016, 27842, 34892, 5016, 32640, 31767, 15040, 3660, 16070, 3794, 37440, 15844, 12602, 3794, 12610, 21984, 5551, 3224, 15040, 46952, 3224, 15040, 4724, 24793, 8978, 5296, 4587, 16606, 3660, 9154, 10874, 16254, 3215, 9154, 5296, 4587, 16606, 9307, 47524, 995, 4587, 3660, 6055, 1863, 38436, 3555, 2423, 21292, 7649, 9307, 4032, 7649, 13412, 16606, 21984, 45595, 20498, 8608, 10721, 2655, 4117, 19528, 20449, 995, 24793, 18871, 4386, 8608, 10721, 8592, 2655, 17082, 1211, 20449, 995, 24793, 6225, 2304, 20292, 30767, 1829, 19446, 5551, 8592, 2655, 17082, 1211, 2655, 8978, 2423, 39184, 2666, 340, 780, 278, 8608, 10721, 25957, 1211, 8978, 16254, 2407, 12174, 9381, 13546, 18871, 2423, 21538, 4032, 2304, 45636, 995, 5551, 16572, 3215, 14739, 5551, 5172, 30241, 8978, 6225, 42213, 2423, 21538], "avg_logprob": -0.24830426356589147, "compression_ratio": 1.8745098039215686, "no_speech_prob": 8.940696716308594e-07, "words": [{"start": 4.52, "end": 4.82, "word": "بسم", "probability": 0.80126953125}, {"start": 4.82, "end": 4.94, "word": " الله", "probability": 0.962890625}, {"start": 4.94, "end": 5.2, "word": " الرحمن", "probability": 0.8738606770833334}, {"start": 5.2, "end": 5.4, "word": " الرحيم", "probability": 0.9130859375}, {"start": 5.4, "end": 5.72, "word": " الصلاة", "probability": 0.7510579427083334}, {"start": 5.72, "end": 6.04, "word": " والسلام", "probability": 0.96533203125}, {"start": 6.04, "end": 6.2, "word": " على", "probability": 0.4345703125}, {"start": 6.2, "end": 6.48, "word": " رسول", "probability": 0.9853515625}, {"start": 6.48, "end": 6.72, "word": " الله", "probability": 0.94140625}, {"start": 6.72, "end": 7.8, "word": " أهلا", "probability": 0.8846028645833334}, {"start": 7.8, "end": 8.14, "word": " وسهلا", "probability": 0.7942708333333334}, {"start": 8.14, "end": 8.4, "word": " بكم", "probability": 0.6826171875}, {"start": 8.4, "end": 8.54, "word": " في", "probability": 0.939453125}, {"start": 8.54, "end": 8.88, "word": " لقاءة", "probability": 0.67755126953125}, {"start": 8.88, "end": 8.94, "word": " من", "probability": 0.8466796875}, {"start": 8.94, "end": 9.42, "word": " جديد", "probability": 0.9812825520833334}, {"start": 9.42, "end": 10.6, "word": " من", "probability": 0.70849609375}, {"start": 10.6, "end": 11.16, "word": " لقاءات", "probability": 0.957275390625}, {"start": 11.16, "end": 11.74, "word": " مساقة", "probability": 0.55133056640625}, {"start": 11.74, "end": 12.1, "word": " تنقيب", "probability": 0.8873291015625}, {"start": 12.1, "end": 12.64, "word": " البيانات", "probability": 0.932373046875}, {"start": 12.64, "end": 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"probability": 0.96728515625}, {"start": 20.94, "end": 21.32, "word": " أشتغلت", "probability": 0.900146484375}, {"start": 21.32, "end": 21.44, "word": " في", "probability": 0.69091796875}, {"start": 21.44, "end": 21.68, "word": " الـ", "probability": 0.7568359375}, {"start": 21.68, "end": 22.34, "word": " preprocessing", "probability": 0.849853515625}, {"start": 22.34, "end": 22.68, "word": " سأعمل", "probability": 0.83319091796875}, {"start": 22.68, "end": 23.18, "word": " فيديو", "probability": 0.9521484375}, {"start": 23.18, "end": 24.18, "word": " قصير", "probability": 0.9873046875}, {"start": 24.18, "end": 25.1, "word": " عن", "probability": 0.7783203125}, {"start": 25.1, "end": 25.52, "word": " ال", "probability": 0.9208984375}, {"start": 25.52, "end": 26.46, "word": " classification", "probability": 0.54248046875}, {"start": 26.46, "end": 26.94, "word": " وماذا", "probability": 0.68414306640625}, {"start": 26.94, "end": 27.3, "word": " أريد", "probability": 0.7859700520833334}, 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outcome» وهكذا أصبح لدي two arrays تمثل الـ «attributes» من الـ «age» إلى الـ «pregnancy»", "tokens": [36784, 1591, 2024, 1169, 6915, 1412, 40305, 529, 5893, 34051, 1412, 40305, 529, 295, 264, 9700, 5933, 37037, 4117, 15730, 5551, 9381, 49628, 5296, 16254, 732, 41011, 6055, 2304, 12984, 1211, 2423, 39184, 4657, 1591, 2024, 1819, 5933, 9154, 2423, 39184, 4657, 609, 5933, 30731, 2423, 39184, 4657, 79, 3375, 77, 6717, 5933], "avg_logprob": -0.5141782308066333, "compression_ratio": 1.2569444444444444, "no_speech_prob": 0.0, "words": [{"start": 719.7, "end": 720.52, "word": "«attribute", "probability": 0.6597900390625}, {"start": 720.52, "end": 722.06, "word": " equals", "probability": 0.0584716796875}, {"start": 722.06, "end": 723.5, "word": " dataFrame", "probability": 0.7098795572916666}, {"start": 723.5, "end": 724.1, "word": " dot", "probability": 0.2379150390625}, {"start": 724.1, "end": 725.02, "word": " أو", "probability": 0.405517578125}, {"start": 725.02, "end": 725.88, "word": " 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"probability": 0.51416015625}, {"start": 856.49, "end": 857.23, "word": " أستخدمها", "probability": 0.94794921875}, {"start": 857.23, "end": 857.67, "word": " model", "probability": 0.45361328125}, {"start": 857.67, "end": 858.21, "word": " underscore", "probability": 0.026092529296875}, {"start": 858.21, "end": 860.65, "word": " selection", "probability": 0.70166015625}, {"start": 860.65, "end": 863.65, "word": " model", "probability": 0.595703125}, {"start": 863.65, "end": 864.53, "word": " selection", "probability": 0.9248046875}], "temperature": 1.0}, {"id": 37, "seek": 89914, "start": 869.6, "end": 899.14, "text": "ماذا أريد أن أستخدم من الـ Modeling و الـ Selection؟ سأستخدم crane underscore test underscore split function أو ميثود الموجودة في داخلها الميثود هايبتش بتاخد مني argument هذه الميثود بتاخد مني argument أهمها تلقى شغلات الـ attributes ال data set اللي أنا", "tokens": [2304, 45636, 995, 5551, 16572, 3215, 14739, 5551, 14851, 9778, 40448, 9154, 2423, 39184, 6583, 11031, 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"temperature": 1.0}, {"id": 39, "seek": 96154, "start": 932.36, "end": 961.54, "text": "الـ Index اللي موجود في الـ Attribute الأول أو مع الـ Attributes هو نفس الـ Index الموجود على الـ Target بس أنا فصلتهم كأعلى ده عن بعضهم لكن الـ Index بقى نفس الترتيب، ماصارش فيه عليه الشغل طيب، وبالتالي هو هياخد Random Sample نسبة 30% من الـ Indices اللي موجودة هنا ويعمل الـ Reaction 30% هذه هترجع في لمين؟ هترجع لـ X Test", "tokens": [6027, 39184, 33552, 13672, 1829, 3714, 29245, 23328, 8978, 2423, 39184, 7298, 2024, 1169, 16247, 12610, 34051, 20449, 2423, 39184, 7298, 2024, 1819, 31439, 8717, 36178, 2423, 39184, 33552, 9673, 29245, 23328, 15844, 2423, 39184, 24586, 4724, 3794, 41850, 6156, 36520, 2655, 16095, 9122, 10721, 3615, 23942, 11778, 3224, 18871, 45030, 11242, 16095, 44381, 2423, 39184, 33552, 4724, 4587, 7578, 8717, 36178, 16712, 2288, 31371, 3555, 12399, 19446, 9381, 9640, 8592, 8978, 3224, 47356, 25124, 17082, 1211, 23032, 1829, 3555, 12399, 46599, 6027, 2655, 6027, 1829, 31439, 39896, 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2284.19, "word": " method", "probability": 0.3232421875}, {"start": 2284.19, "end": 2284.61, "word": " أو", "probability": 0.81689453125}, {"start": 2284.61, "end": 2285.05, "word": " الـ", "probability": 0.573974609375}, {"start": 2285.05, "end": 2285.27, "word": " model", "probability": 0.93017578125}, {"start": 2285.27, "end": 2285.45, "word": " اللي", "probability": 0.972412109375}, {"start": 2285.45, "end": 2285.87, "word": " عندي", "probability": 0.88916015625}, {"start": 2285.87, "end": 2287.17, "word": " dot", "probability": 0.6669921875}, {"start": 2287.17, "end": 2287.93, "word": " predict", "probability": 0.892578125}], "temperature": 1.0}, {"id": 88, "seek": 230916, "start": 2288.62, "end": 2309.16, "text": "الـ Prediction بتاخد الـ X-Train و Y-Test وبترجعلي الـ Y-Predict", "tokens": [6027, 39184, 430, 24945, 313, 39894, 47283, 3215, 2423, 39184, 1783, 12, 51, 7146, 4032, 398, 12, 51, 377, 46599, 2655, 47341, 3615, 20292, 2423, 39184, 398, 12, 47, 24945], "avg_logprob": 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"no_speech_prob": 5.125999450683594e-06, "words": [{"start": 2311.25, "end": 2311.49, "word": "الـ", "probability": 0.42291259765625}, {"start": 2311.49, "end": 2311.93, "word": " Target", "probability": 0.52734375}, {"start": 2311.93, "end": 2312.15, "word": " اللي", "probability": 0.8544921875}, {"start": 2312.15, "end": 2312.31, "word": " هي", "probability": 0.4404296875}, {"start": 2312.31, "end": 2312.83, "word": " الموجودة", "probability": 0.9345703125}, {"start": 2312.83, "end": 2313.19, "word": " عندها", "probability": 0.968017578125}, {"start": 2313.19, "end": 2314.03, "word": " بمجرد", "probability": 0.45841064453125}, {"start": 2314.03, "end": 2314.53, "word": " ذلك،", "probability": 0.578857421875}, {"start": 2314.53, "end": 2314.95, "word": " دعوني", "probability": 0.5985107421875}, {"start": 2314.95, "end": 2317.29, "word": " أقول", "probability": 0.412109375}, {"start": 2317.29, "end": 2317.59, "word": " له", "probability": 0.4326171875}, {"start": 2317.59, "end": 2318.01, "word": " اطبع", "probability": 0.662353515625}, {"start": 2318.01, "end": 2318.59, "word": " ليها", "probability": 0.794921875}, {"start": 2318.59, "end": 2318.97, "word": " Y", "probability": 0.229736328125}, {"start": 2318.97, "end": 2320.23, "word": "-Predict", "probability": 0.4110107421875}, {"start": 2320.23, "end": 2321.83, "word": " كنت", "probability": 0.3524169921875}, {"start": 2321.83, "end": 2322.29, "word": " أتأكد", "probability": 0.94013671875}, {"start": 2322.29, "end": 2322.41, "word": " أن", "probability": 0.487548828125}, {"start": 2322.41, "end": 2322.73, "word": " الأمور", "probability": 0.9775390625}, {"start": 2322.73, "end": 2323.11, "word": " تمام،", "probability": 0.7764485677083334}, {"start": 2323.11, "end": 2323.33, "word": " وعمل", "probability": 0.6277669270833334}, {"start": 2323.33, "end": 2323.95, "word": " Prediction", "probability": 0.6962890625}, {"start": 2323.95, "end": 2335.23, "word": " تاكس", "probability": 0.287384033203125}, {"start": 2335.23, "end": 2335.61, "word": " تو", "probability": 0.4273681640625}, {"start": 2335.61, "end": 2336.35, "word": " Positional", "probability": 0.55682373046875}, {"start": 2336.35, "end": 2337.11, "word": " Argument", "probability": 0.838134765625}, {"start": 2337.11, "end": 2337.43, "word": " but", "probability": 0.07403564453125}, {"start": 2337.43, "end": 2337.79, "word": " three", "probability": 0.61376953125}, {"start": 2337.79, "end": 2338.05, "word": " were", "probability": 0.87841796875}, {"start": 2338.05, "end": 2338.37, "word": " given", "probability": 0.90625}, {"start": 2338.37, "end": 2340.81, "word": " Space", "probability": 0.400390625}], "temperature": 1.0}, {"id": 90, "seek": 237423, "start": 2362.5, "end": 2374.24, "text": "أنا المفروض أدّي الـ text الـ attributes وهو بده يعمل prediction أنا آسف على الخطأ هذا، الآن هي الـ predicted labels اللي موجودة عندي", "tokens": [10721, 8315, 9673, 5172, 32887, 11242, 5551, 3215, 11703, 1829, 2423, 39184, 2487, 2423, 39184, 17212, 37037, 2407, 47525, 3224, 7251, 25957, 1211, 17630, 41850, 19753, 3794, 5172, 15844, 33962, 9566, 10721, 23758, 12399, 6024, 48506, 39896, 2423, 39184, 19147, 16949, 13672, 1829, 3714, 29245, 23328, 3660, 18871, 16254], "avg_logprob": -0.42343749523162844, "compression_ratio": 1.3333333333333333, "no_speech_prob": 1.1920928955078125e-07, "words": [{"start": 2362.4999999999995, "end": 2363.3599999999997, "word": "أنا", "probability": 0.53955078125}, {"start": 2363.3599999999997, "end": 2364.22, "word": " المفروض", "probability": 0.9119873046875}, {"start": 2364.22, "end": 2364.86, "word": " أدّي", "probability": 0.55535888671875}, {"start": 2364.86, "end": 2365.4, "word": " الـ", "probability": 0.676025390625}, {"start": 2365.4, "end": 2365.66, "word": " text", "probability": 0.330322265625}, {"start": 2365.66, "end": 2366.28, "word": " الـ", "probability": 0.4859619140625}, {"start": 2366.28, "end": 2367.3, "word": " attributes", "probability": 0.66162109375}, {"start": 2367.3, "end": 2367.68, "word": " وهو", "probability": 0.607177734375}, {"start": 2367.68, "end": 2367.96, "word": " بده", "probability": 0.358642578125}, {"start": 2367.96, "end": 2368.24, "word": " يعمل", "probability": 0.9615885416666666}, {"start": 2368.24, "end": 2368.68, "word": " prediction", "probability": 0.74072265625}, {"start": 2368.68, "end": 2369.28, "word": " أنا", "probability": 0.5283203125}, {"start": 2369.28, "end": 2369.56, "word": " آسف", "probability": 0.9309895833333334}, {"start": 2369.56, "end": 2369.7, "word": " على", "probability": 0.8671875}, {"start": 2369.7, "end": 2370.04, "word": " الخطأ", "probability": 0.9949544270833334}, {"start": 2370.04, "end": 2370.94, "word": " هذا،", "probability": 0.793212890625}, {"start": 2370.94, "end": 2371.2, "word": " الآن", "probability": 0.5595703125}, {"start": 2371.2, "end": 2371.68, "word": " هي", "probability": 0.55419921875}, {"start": 2371.68, "end": 2371.86, "word": " الـ", "probability": 0.6485595703125}, {"start": 2371.86, "end": 2372.24, "word": " predicted", "probability": 0.6650390625}, {"start": 2372.24, "end": 2372.74, "word": " labels", "probability": 0.84619140625}, {"start": 2372.74, "end": 2373.1, "word": " اللي", "probability": 0.91259765625}, {"start": 2373.1, "end": 2373.82, "word": " موجودة", "probability": 0.9783935546875}, {"start": 2373.82, "end": 2374.24, "word": " عندي", "probability": 0.60943603515625}], "temperature": 1.0}, {"id": 91, "seek": 240244, "start": 2375.07, "end": 2402.45, "text": "أو كأنا فكرت حالي وصلت لمراحة الـ Evaluation سمحوني، هي العناصر اللي موجودة عندها هذه عبارة عن كلية Predicted Labels Predicted Labels زمين للـ X Test اللي موجودة وين الـ Label الحقيقي تبعها موجود؟ الـ Label الحقيقي موجود في الـ Y Train أو في الـ Y Test هاي طيب، الآن عشان أنا أبدأ أقارن خليني أول حاجة نتعرف على الـ Confusion Matrix اللي موجودة عندها", "tokens": [10721, 2407, 9122, 10721, 8315, 6156, 37983, 2655, 11331, 6027, 1829, 4032, 36520, 2655, 32767, 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"no_speech_prob": 0.0, "words": [{"start": 2403.86, "end": 2404.38, "word": "وهنا", "probability": 0.802734375}, {"start": 2404.38, "end": 2404.7, "word": " في", "probability": 0.13134765625}, {"start": 2404.7, "end": 2405.04, "word": " عندي", "probability": 0.64501953125}, {"start": 2405.04, "end": 2405.74, "word": " الـ", "probability": 0.829833984375}, {"start": 2405.74, "end": 2406.8, "word": " classification", "probability": 0.50927734375}, {"start": 2406.8, "end": 2409.54, "word": " model", "probability": 0.92041015625}, {"start": 2409.54, "end": 2412.18, "word": " evaluation", "probability": 0.96533203125}, {"start": 2412.18, "end": 2415.88, "word": " هنبدأ", "probability": 0.7611083984375}, {"start": 2415.88, "end": 2416.4, "word": " الآن", "probability": 0.725830078125}, {"start": 2416.4, "end": 2417.18, "word": " الان", "probability": 0.43701171875}, {"start": 2417.18, "end": 2417.72, "word": " from", "probability": 0.73046875}, {"start": 2417.72, "end": 2418.64, "word": " ال", "probability": 0.42626953125}, {"start": 2418.64, "end": 2419.24, "word": " ASCII", "probability": 0.6595662434895834}, {"start": 2419.24, "end": 2419.86, "word": " layer", "probability": 0.85693359375}, {"start": 2419.86, "end": 2422.64, "word": " import", "probability": 0.65966796875}, {"start": 2422.64, "end": 2425.94, "word": " matrix", "probability": 0.82861328125}], "temperature": 1.0}, {"id": 93, "seek": 244994, "start": 2428.28, "end": 2449.94, "text": "الآن بدي أجيب الـ Matrix، إيش الـ Matrix جامعة الخيار؟ تحتوي أنه من خلالها أنا ممكن أنشأ الـ confusion matrix، أحسب الـ accuracy، أحسب ال precision، أحسب ال recall، أحسب ال أثمجة، كل هذه لدى ال attribute، عفوا، للكاسيفير اللي موجود عندها، وخليني أنا أبدأ مع ال confusion matrix،", "tokens": [6027, 148, 48506, 4724, 16254, 5551, 7435, 1829, 3555, 2423, 39184, 36274, 12399, 11933, 1829, 8592, 2423, 39184, 36274, 10874, 10943, 27884, 33962, 1829, 9640, 22807, 6055, 33753, 45865, 14739, 3224, 9154, 16490, 1211, 6027, 11296, 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-1.2644230402432954, "compression_ratio": 0.972972972972973, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 2467.52, "end": 2468.92, "word": "الـ", "probability": 0.28570556640625}, {"start": 2468.92, "end": 2469.1, "word": " M", "probability": 0.194091796875}, {"start": 2469.1, "end": 2470.64, "word": " الـ", "probability": 0.4741973876953125}, {"start": 2470.64, "end": 2471.22, "word": " CM", "probability": 0.427978515625}, {"start": 2471.22, "end": 2471.9, "word": " متر", "probability": 0.364593505859375}, {"start": 2471.9, "end": 2473.88, "word": " ايقال", "probability": 0.4678192138671875}], "temperature": 1.0}, {"id": 95, "seek": 250744, "start": 2484.7, "end": 2507.44, "text": "هنا كل الـ evaluation functions اللي موجودة عندنا هتاخد مني شغلتين هتاخد مني الـ y test اللي هو ال label الحقيقي والي predicted أو الـ y predicted الـ y predict وهي بدي أروح أقوله اطبع ليه ال matrix اللي عندنا", "tokens": [3224, 8315, 28242, 2423, 39184, 13344, 6828, 13672, 1829, 3714, 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"end": 2534.43, "text": "اللي هي الـ Confusion Matrix الـ Test Set بيتك حجمها هيهم المجموع العناصر الموجودة 120، 25، True Positive، True Negative، False Positive، False Negative، False Positive، False Negative بس إيش ال classes اللي موجودة عندي يا جماعة الخير؟ ال classes يا أخواننا و يا أخواتي بيكونوا تنتبهوا بشكل كويس", "tokens": [6027, 20292, 39896, 2423, 39184, 11701, 5704, 36274, 2423, 39184, 9279, 8928, 4724, 36081, 4117, 11331, 7435, 2304, 11296, 39896, 16095, 9673, 7435, 2304, 45367, 18863, 1863, 33546, 2288, 9673, 29245, 23328, 3660, 10411, 12399, 3552, 12399, 13587, 46326, 12399, 13587, 43230, 12399, 50040, 46326, 12399, 50040, 43230, 12399, 50040, 46326, 12399, 50040, 43230, 4724, 3794, 11933, 1829, 8592, 2423, 5359, 13672, 1829, 3714, 29245, 23328, 3660, 18871, 16254, 35186, 10874, 15042, 27884, 33962, 13546, 22807, 2423, 5359, 35186, 5551, 9778, 2407, 7649, 8315, 4032, 35186, 5551, 9778, 2407, 9307, 1829, 4724, 1829, 30544, 14407, 6055, 29399, 3555, 3224, 14407, 4724, 8592, 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2512.49, "word": " هيهم", "probability": 0.712646484375}, {"start": 2512.49, "end": 2513.19, "word": " المجموع", "probability": 0.892578125}, {"start": 2513.19, "end": 2513.65, "word": " العناصر", "probability": 0.87841796875}, {"start": 2513.65, "end": 2514.39, "word": " الموجودة", "probability": 0.91064453125}, {"start": 2514.39, "end": 2515.89, "word": " 120،", "probability": 0.2835693359375}, {"start": 2515.89, "end": 2517.31, "word": " 25،", "probability": 0.60498046875}, {"start": 2517.31, "end": 2517.45, "word": " True", "probability": 0.7216796875}, {"start": 2517.45, "end": 2518.53, "word": " Positive،", "probability": 0.8671875}, {"start": 2518.53, "end": 2518.85, "word": " True", "probability": 0.85888671875}, {"start": 2518.85, "end": 2520.35, "word": " Negative،", "probability": 0.93115234375}, {"start": 2520.35, "end": 2520.67, "word": " False", "probability": 0.90234375}, {"start": 2520.67, "end": 2522.23, "word": " Positive،", "probability": 0.966064453125}, {"start": 2522.23, "end": 2522.57, "word": " False", "probability": 0.93798828125}, {"start": 2522.57, "end": 2524.29, "word": " Negative،", "probability": 0.725341796875}, {"start": 2524.29, "end": 2524.39, "word": " False", "probability": 0.79150390625}, {"start": 2524.39, "end": 2525.39, "word": " Positive،", "probability": 0.927490234375}, {"start": 2525.39, "end": 2525.65, "word": " False", "probability": 0.953125}, {"start": 2525.65, "end": 2526.81, "word": " Negative", "probability": 0.9794921875}, {"start": 2526.81, "end": 2527.89, "word": " بس", "probability": 0.583740234375}, {"start": 2527.89, "end": 2528.11, "word": " إيش", "probability": 0.8232421875}, {"start": 2528.11, "end": 2528.25, "word": " ال", "probability": 0.90380859375}, {"start": 2528.25, "end": 2528.53, "word": " classes", "probability": 0.58447265625}, {"start": 2528.53, "end": 2528.81, "word": " اللي", "probability": 0.955322265625}, {"start": 2528.81, "end": 2529.45, "word": " موجودة", "probability": 0.984375}, {"start": 2529.45, "end": 2529.75, "word": " عندي", "probability": 0.636474609375}, {"start": 2529.75, "end": 2530.07, "word": " يا", "probability": 0.77880859375}, {"start": 2530.07, "end": 2530.25, "word": " جماعة", "probability": 0.9296875}, {"start": 2530.25, "end": 2531.17, "word": " الخير؟", "probability": 0.8251953125}, {"start": 2531.17, "end": 2531.27, "word": " ال", "probability": 0.919921875}, {"start": 2531.27, "end": 2531.61, "word": " classes", "probability": 0.84130859375}, {"start": 2531.61, "end": 2531.83, "word": " يا", "probability": 0.7568359375}, {"start": 2531.83, "end": 2532.19, "word": " أخواننا", "probability": 0.775244140625}, {"start": 2532.19, "end": 2532.73, "word": " و", "probability": 0.62255859375}, {"start": 2532.73, "end": 2532.77, "word": " يا", "probability": 0.513671875}, {"start": 2532.77, "end": 2533.11, "word": " أخواتي", "probability": 0.93603515625}, {"start": 2533.11, "end": 2533.41, "word": " بيكونوا", "probability": 0.6285400390625}, {"start": 2533.41, "end": 2533.67, "word": " تنتبهوا", "probability": 0.797265625}, {"start": 2533.67, "end": 2533.91, "word": " بشكل", "probability": 0.8369140625}, {"start": 2533.91, "end": 2534.43, "word": " كويس", "probability": 0.9817708333333334}], "temperature": 1.0}, {"id": 97, "seek": 256187, "start": 2534.93, "end": 2561.87, "text": "لأنه أنا ما حدد لهوش إيش ال classes فإيش هو بياخد مباشرة بيروح بيعتمد على الآن أول ما قرأت data set أول ما قرأت data set إيش أول class واجهه؟ طبعاً أنا بتكلم في ال test set هذا لأن أول ما زودته، زودته غنين في ال Y-predict أول element في ال Y-test", "tokens": [1211, 33456, 3224, 41850, 19446, 11331, 3215, 3215, 46740, 2407, 8592, 11933, 1829, 8592, 2423, 5359, 6156, 28814, 1829, 8592, 31439, 4724, 1829, 47283, 3215, 3714, 3555, 33599, 25720, 4724, 1829, 32887, 5016, 4724, 1829, 34268, 2304, 3215, 15844, 6024, 48506, 5551, 12610, 19446, 12174, 2288, 10721, 2655, 1412, 992, 5551, 12610, 19446, 12174, 2288, 10721, 2655, 1412, 992, 11933, 1829, 8592, 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259360, "start": 2566.22, "end": 2593.6, "text": "كان واحد، فخلاص، بيعتبر أنه هذا للـ Class الأول، تمام؟ وهذا للClass الثاني، طبعاً هذه العناصر معناته أنها الـ confusion matrix ومن خلالها أنا بنطلق و بحسب كل حاجة، طب إذا أنا بدأ أحسب ال accuracy الآن، اذكروا ال accuracy كانت إيش بتساوي؟ ال true positive زائد ال true negative على كل العناصر المجموعة هنا", "tokens": [41361, 36764, 24401, 12399, 6156, 9778, 1211, 33546, 12399, 4724, 1829, 34268, 26890, 14739, 3224, 23758, 24976, 39184, 9471, 16247, 12610, 12399, 46811, 10943, 22807, 37037, 15730, 24976, 44621, 6024, 104, 7649, 1829, 12399, 23032, 3555, 3615, 995, 14111, 29538, 18863, 8315, 9381, 2288, 20449, 8315, 47395, 14739, 11296, 2423, 39184, 15075, 8141, 4032, 27842, 16490, 1211, 6027, 11296, 41850, 44945, 9566, 1211, 4587, 4032, 4724, 5016, 35457, 28242, 11331, 26108, 3660, 12399, 23032, 3555, 11933, 15730, 41850, 47525, 10721, 5551, 5016, 35457, 2423, 14170, 6024, 48506, 12399, 1975, 8848, 37983, 14407, 2423, 14170, 25961, 2655, 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"start": 2599.26, "end": 2620.64, "text": "سأقوم بإعادة الـ Accuracy ACC متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي متركز تساوي مت", "tokens": [3794, 10721, 4587, 20498, 4724, 28814, 3615, 18513, 3660, 2423, 39184, 5725, 374, 2551, 42251, 44650, 2288, 4117, 11622, 6055, 3794, 995, 45865, 44650, 2288, 4117, 11622, 6055, 3794, 995, 45865, 44650, 2288, 4117, 11622, 6055, 3794, 995, 45865, 44650, 2288, 4117, 11622, 6055, 3794, 995, 45865, 44650, 2288, 4117, 11622, 6055, 3794, 995, 45865, 44650, 2288, 4117, 11622, 6055, 3794, 995, 45865, 44650, 2288, 4117, 11622, 6055, 3794, 995, 45865, 44650, 2288, 4117, 11622, 6055, 3794, 995, 45865, 44650, 2288, 4117, 11622, 6055, 3794, 995, 45865, 44650, 2288, 4117, 11622, 6055, 3794, 995, 45865, 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{"start": 2613.26, "end": 2613.4, "word": " تساوي", "probability": 0.9627685546875}, {"start": 2613.4, "end": 2613.48, "word": " متركز", "probability": 0.961669921875}, {"start": 2613.48, "end": 2613.8, "word": " تساوي", "probability": 0.9664306640625}, {"start": 2613.8, "end": 2613.8, "word": " متركز", "probability": 0.961181640625}, {"start": 2613.8, "end": 2613.8, "word": " تساوي", "probability": 0.9691162109375}, {"start": 2613.8, "end": 2613.8, "word": " متركز", "probability": 0.9609375}, {"start": 2613.8, "end": 2613.8, "word": " تساوي", "probability": 0.97021484375}, {"start": 2613.8, "end": 2613.8, "word": " متركز", "probability": 0.9620361328125}, {"start": 2613.8, "end": 2613.8, "word": " تساوي", "probability": 0.9716796875}, {"start": 2613.8, "end": 2613.8, "word": " متركز", "probability": 0.963134765625}, {"start": 2613.8, "end": 2613.8, "word": " تساوي", "probability": 0.9720458984375}, {"start": 2613.8, "end": 2613.8, "word": " متركز", "probability": 0.964599609375}, 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Matrix dot مش underscore جالي 72.27 ممتاز، بدي أنتقل للسلة اللي بعدها لو أنا بدي أحسب ال F major score أو ال precision ال first class اللي موجود عندي هان", "tokens": [3224, 2407, 2423, 39184, 5725, 374, 2551, 24976, 39184, 17105, 13672, 1829, 3714, 29245, 23328, 16472, 4117, 8032, 7649, 36274, 5893, 37893, 37556, 10874, 6027, 1829, 18731, 13, 10076, 3714, 2304, 2655, 31377, 12399, 4724, 16254, 14739, 2655, 4587, 1211, 24976, 3794, 37977, 13672, 1829, 39182, 11296, 45164, 41850, 4724, 16254, 5551, 5016, 35457, 2423, 479, 2563, 6175, 34051, 2423, 18356, 2423, 700, 1508, 13672, 1829, 3714, 29245, 23328, 18871, 16254, 8032, 7649], "avg_logprob": -0.34332771599292755, "compression_ratio": 1.4623115577889447, "no_speech_prob": 1.3113021850585938e-05, "words": [{"start": 2622.61, "end": 2622.91, "word": "هو", "probability": 0.486328125}, {"start": 2622.91, "end": 2623.43, "word": " الـ", "probability": 0.80029296875}, {"start": 2623.43, "end": 2625.49, "word": " Accuracy", "probability": 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"end": 3031.15, "word": " أننا", "probability": 0.5103759765625}, {"start": 3031.15, "end": 3031.61, "word": " نقدر", "probability": 0.8634440104166666}, {"start": 3031.61, "end": 3031.83, "word": " أن", "probability": 0.5556640625}, {"start": 3031.83, "end": 3033.69, "word": " نتوفيك", "probability": 0.64619140625}, {"start": 3033.69, "end": 3033.95, "word": " دائمًا", "probability": 0.62978515625}, {"start": 3033.95, "end": 3034.31, "word": " وأبداً", "probability": 0.61077880859375}, {"start": 3034.31, "end": 3034.55, "word": " والسلام", "probability": 0.763427734375}, {"start": 3034.55, "end": 3034.85, "word": " عليكم", "probability": 0.97314453125}, {"start": 3034.85, "end": 3035.19, "word": " ورحمة", "probability": 0.979248046875}, {"start": 3035.19, "end": 3035.47, "word": " الله", "probability": 0.9755859375}, {"start": 3035.47, "end": 3036.53, "word": " وبركاته", "probability": 0.94736328125}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 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\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9DgNoAZTwqg_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9DgNoAZTwqg_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..b00b1a0c02f34468272c51604ff193f05fe5aa0e
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@@ -0,0 +1,2236 @@
+1
+00:00:04,520 --> 00:00:06,480
+بسم الله الرحمن الرحيم الصلاة والسلام على رسول
+
+2
+00:00:06,480 --> 00:00:11,160
+الله أهلا وسهلا بكم في لقاءة من جديد من لقاءات
+
+3
+00:00:11,160 --> 00:00:16,280
+مساقة تنقيب البيانات وان شاء الله اليوم سأتكلم
+
+4
+00:00:16,280 --> 00:00:21,680
+معاكم عن .. سأشتغل معاكم عملي زي ما أشتغلت في الـ
+
+5
+00:00:21,680 --> 00:00:25,520
+preprocessing سأعمل فيديو قصير عن ال
+
+6
+00:00:25,520 --> 00:00:28,120
+classification وماذا أريد أن أفعل في عمل ال
+
+7
+00:00:28,120 --> 00:00:32,800
+classificationوحشكل على الكجل كـ Environment ممكن
+
+8
+00:00:32,800 --> 00:00:37,740
+أنتم تستخدموها في موضوع الـ Data Mining أو الـ
+
+9
+00:00:37,740 --> 00:00:41,800
+Data Science وحاجات كتفي فقط بـ Classifier راحل
+
+10
+00:00:41,800 --> 00:00:44,920
+والـ Classifier هذا له خصوصية شوية ضمن كل فيديو
+
+11
+00:00:44,920 --> 00:00:48,040
+هذه ساعدكم في فهم أو في عمل الواجب بشكل صحيح
+
+12
+00:00:48,040 --> 00:00:52,300
+تمضبنكم في الواجب تستخدموا ال data set تبعكم
+
+13
+00:00:52,300 --> 00:00:57,290
+وتقارنوا ال performance تبع ال three classifiersمن
+
+14
+00:00:57,290 --> 00:01:02,050
+أربعة احنا خدنا الـ Canary Sniper والـ Naive Bison
+
+15
+00:01:02,050 --> 00:01:04,890
+والـ Neural Network والـ Decision Tree هدول
+
+16
+00:01:04,890 --> 00:01:07,650
+الأربعة انا شرحتهم في تسجيلات السابقة المضمون انكم
+
+17
+00:01:07,650 --> 00:01:10,210
+تختاروا التلاتة و تطبقوهم على ال data set اللي
+
+18
+00:01:10,210 --> 00:01:15,770
+موجودة عندكم، الآن انا شاء الله تعالى هبدأ اعمل
+
+19
+00:01:15,770 --> 00:01:19,160
+sharing للشاشة اللي موجودة عندهاأحاول في الفيديو
+
+20
+00:01:19,160 --> 00:01:23,460
+أنتقل لموضوع الـ Sharing وأتكلم على الـ Data Set
+
+21
+00:01:23,460 --> 00:01:29,580
+أو على الـ Element اللي أنا .. البرنامج
+
+22
+00:01:29,580 --> 00:01:35,640
+اللي أنا بدأ أشتغل عليه بداية خليني أنا أروح أعمل
+
+23
+00:01:35,640 --> 00:01:40,900
+Share للـ Desktop هي
+
+24
+00:01:40,900 --> 00:01:44,300
+Share للـ Desktop بالكامل وبعد التسجيل المفروض للـ
+
+25
+00:01:44,300 --> 00:01:45,700
+Desktop وأنا الآن
+
+26
+00:02:07,030 --> 00:02:12,390
+بسم الله هيالكاجل.com أنا أيه الحساب على الكاجل؟
+
+27
+00:02:12,600 --> 00:02:16,280
+اللي انشأته من تبقى الإحساب آخر لكن هذا أنا أنشأته
+
+28
+00:02:16,280 --> 00:02:25,400
+من فترة بخصوص اللي اللي اللي اللي اللي
+
+29
+00:02:25,400 --> 00:02:25,680
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+30
+00:02:25,680 --> 00:02:25,740
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+31
+00:02:25,740 --> 00:02:26,100
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+32
+00:02:26,100 --> 00:02:26,620
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+33
+00:02:26,620 --> 00:02:26,900
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+34
+00:02:26,900 --> 00:02:27,000
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+35
+00:02:27,000 --> 00:02:27,040
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+36
+00:02:27,040 --> 00:02:32,220
+اللي اللي اللي اللي اللي
+
+37
+00:02:32,220 --> 00:02:32,220
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+38
+00:02:32,220 --> 00:02:38,740
+اللي اللي اللي اللي
+
+39
+00:02:38,740 --> 00:02:42,760
+اللي اللوبحدد ال database هي بيما انديام ديابيتاس
+
+40
+00:02:42,760 --> 00:02:46,120
+ال database هي مشهورة عالمياً أنا مش هروح أحملها
+
+41
+00:02:46,120 --> 00:02:50,880
+كمان مرة فاللي already اذا حملتها بكون انتهيت من
+
+42
+00:02:50,880 --> 00:02:55,620
+الملف اللي موجود عندي و هنتقل الخطوة التالية هروح
+
+43
+00:02:55,620 --> 00:03:01,840
+انا أقوله في ال data set اللي موجودة عندي هي بيما
+
+44
+00:03:01,840 --> 00:03:02,680
+ديابيتاس
+
+45
+00:03:07,480 --> 00:03:16,400
+وأنا بدي أستخدم الـ Dataset Hi طبعا
+
+46
+00:03:16,400 --> 00:03:18,840
+الـ Dataset جمال الغير عشان نفهمها بشكل سريع الـ
+
+47
+00:03:18,840 --> 00:03:23,280
+Dataset هي ناتجة عن المركز الوطني لأمراض السكري
+
+48
+00:03:23,280 --> 00:03:30,540
+والحمية والأمراض الكلةالهدف منها إنه فعليًا
+
+49
+00:03:30,540 --> 00:03:33,860
+يحاولوا يتنبأوا هل المريض هذا هو مؤصاب سكري أو لا
+
+50
+00:03:33,860 --> 00:03:36,980
+بناءً على التشخيصات اللي هي موجودة في ال database
+
+51
+00:03:36,980 --> 00:03:39,800
+اللي موجودة قدامها هي موجودة أعظم مكوّنة من تمانية
+
+52
+00:03:39,800 --> 00:03:42,780
+attributes زي اللي هنشوفها كمان شوية «several
+
+53
+00:03:42,780 --> 00:03:44,920
+constraints were placed on the solution of the
+
+54
+00:03:44,920 --> 00:03:50,400
+ice» وهذه ال database مكوّنة بتتناول ال female
+
+55
+00:03:50,400 --> 00:03:54,220
+patients only all the patients here are females at
+
+56
+00:03:54,220 --> 00:04:03,460
+leastعلى الأقل يكونوا 21 سنة يعني 21 سنة من بيما
+
+57
+00:04:03,460 --> 00:04:07,860
+المنطقة اللي موجودة فيها طبعا هذا كل الكلام انا ما
+
+58
+00:04:07,860 --> 00:04:11,300
+الاصل اللي شفته عندما اتعرفته على ال database
+
+59
+00:04:11,300 --> 00:04:16,980
+والان بده اروح حقوله new notebook
+
+60
+00:04:22,650 --> 00:04:26,450
+الآن الـ New Notebook هو Jupiter Notebook إنشأليه
+
+61
+00:04:26,450 --> 00:04:30,910
+الـ Kaggle، والآن جاب لي هذه كل الكود عشان يعمل
+
+62
+00:04:30,910 --> 00:04:35,490
+import لمين لل database اللي موجودة عنديها، طبعاً
+
+63
+00:04:35,490 --> 00:04:40,590
+هذا الفرق الوحيد ما بين الـ Online، الـ Python
+
+64
+00:04:40,590 --> 00:04:46,370
+Jupiter Notebook أو الـ Localاللي في الآخر انت لما
+
+65
+00:04:46,370 --> 00:04:49,210
+بنعمل import كنا بنزوده بالمسار اللي موجود، طب مين
+
+66
+00:04:49,210 --> 00:04:53,790
+بيحدد المسار؟ هذه موجودة على cloud أو على driver
+
+67
+00:04:56,070 --> 00:04:59,490
+فاحنا بنختارها بكل بساطة بدون إيش بدون ما يكون في
+
+68
+00:04:59,490 --> 00:05:02,650
+عندنا ال .. عفوا فبتروح بتزوّدنا إيه أغلى كاجل
+
+69
+00:05:02,650 --> 00:05:05,090
+بدون ما تكون في عندنا مشاكل الأصل إحنا هذا ال code
+
+70
+00:05:05,090 --> 00:05:09,710
+إذا بدنا نشتغل online نرفعه أو نتعلمه أو نحفظه لأن
+
+71
+00:05:09,710 --> 00:05:12,250
+هذا ال code هيلزمنا مع الكاجل و غالبا هو نفسه
+
+72
+00:05:12,250 --> 00:05:16,350
+موجود مع ال collab ما علينا أن الأن لو أنا طبعا
+
+73
+00:05:16,350 --> 00:05:19,190
+ناحظ أنه عمل كمان import لأهم two libraries اللي
+
+74
+00:05:19,190 --> 00:05:22,740
+هم على ال databaseأو في الـ dataset الـ numpy
+
+75
+00:05:22,740 --> 00:05:26,320
+والبانداز طبعاً أحنا معظم شغلنا من خلال البانداز
+
+76
+00:05:26,320 --> 00:05:31,280
+لكن في مثال اليوم هيلزمنا ال numpy كذلك لمرة واحد
+
+77
+00:05:31,280 --> 00:05:35,550
+أو لمرتين خلينا نعمل runللـ code اللي موجود عندها
+
+78
+00:05:35,550 --> 00:05:39,750
+عمل run طبعاً سرعة الاستجابة بتعتمد على سرعة ال
+
+79
+00:05:39,750 --> 00:05:42,950
+connection اللي موجود عندك طبعاً هنف يقولك جديش
+
+80
+00:05:42,950 --> 00:05:46,050
+انت استخدمت من ال hardest جديش عندك CPU او إشغال
+
+81
+00:05:46,050 --> 00:05:48,930
+للـ CPU جديش إذا كان عندك إشغال للرابط ممكن تطفو
+
+82
+00:05:48,930 --> 00:05:51,210
+ممكن تعمل restart للجهة بتاع ال notebook هذا
+
+83
+00:05:51,210 --> 00:05:59,030
+الرابط بعد ما عملت run أداني رابط في diabetes.csv
+
+84
+00:05:59,030 --> 00:06:02,070
+طبعا خليني أنا أسمي ال notebook تبعي diabetes
+
+85
+00:06:06,170 --> 00:06:10,510
+عند الـ score specification
+
+86
+00:06:12,560 --> 00:06:15,840
+وأجي أخد Notebook جديدة وحروح أنا أقول له الـ
+
+87
+00:06:15,840 --> 00:06:19,240
+DataFrame طب أنا خلاص بدي أقرأ ال database pandas
+
+88
+00:06:19,240 --> 00:06:27,080
+.read underscore csv اللي زي ما أحنا بنقرأ وهي ال
+
+89
+00:06:27,080 --> 00:06:31,220
+single quotation وهي المسار اللي أنا نسخته هي كده
+
+90
+00:06:31,220 --> 00:06:34,620
+الأمور تمت عملية المفروض تم عملية القراءة عشان أنا
+
+91
+00:06:34,620 --> 00:06:38,920
+أتأكد ورح أقول ال DataFrame.head والhead ممكن أنا
+
+92
+00:06:38,920 --> 00:06:44,470
+أزودها زي ما قولنا سابقاًبتعرض الأول صفوف من الـ
+
+93
+00:06:44,470 --> 00:06:48,450
+DataFrame اللي أنا قرأته الـ DataFrame هذا مكوّن
+
+94
+00:06:48,450 --> 00:06:53,130
+من حوالي الـ 708 الـ و سبتين row الـ By default
+
+95
+00:06:53,130 --> 00:06:56,490
+الـ head بتجيب عشرة، عفوا، بتجيب خمسة، إذا أنا بدي
+
+96
+00:06:56,490 --> 00:06:59,830
+عشرة أو بدي خمسة أو بدي تلاتة أو بدي خمستاشر ممكن
+
+97
+00:06:59,830 --> 00:07:05,350
+أنا أروح أغيره مرة تانية، فهي راح قرأليها اللي
+
+98
+00:07:05,350 --> 00:07:08,840
+قاللي هي البيانات اللي موجودة عندكبس خلّيني أقول
+
+99
+00:07:08,840 --> 00:07:14,740
+لكم قدرة الـ Pages Classification 1 الأن تعرفوا
+
+100
+00:07:14,740 --> 00:07:18,900
+على الـ Attributes بشكل سريع اللي موجودة عنهم بما
+
+101
+00:07:18,900 --> 00:07:23,120
+أن كل الـ Database أو كل الـ Data Sets مكوّنة من
+
+102
+00:07:23,120 --> 00:07:27,680
+الـ Gmail فعلا بيسألني عن ال-Pregnancyعدد مرات
+
+103
+00:07:27,680 --> 00:07:34,600
+الحمل، نسبة الجلوكوز في الدم، ضغط الدم، كم كان،
+
+104
+00:07:34,600 --> 00:07:37,420
+سماكة الجلد، طبعاً سماكة الجلد جامعة الخير مهمة
+
+105
+00:07:37,420 --> 00:07:44,580
+لأنه بيمثلها في طبقة الدهون، كمية نسبة الأنسولين
+
+106
+00:07:44,580 --> 00:07:48,480
+أو كمية الأنسولين الموجودة الـ Body Mass Index
+
+107
+00:07:48,480 --> 00:07:52,600
+مؤشر كتلة الجسد الجدش طبعا المفروض كل الناس اللي
+
+108
+00:07:52,600 --> 00:07:55,880
+فوق الـ30 أو فوق الـ32 أو 35، أعتقد إذا أنا مش
+
+109
+00:07:55,880 --> 00:08:01,920
+أوطاني يعنيبقول عنهم أصحاب سمنة، الـ diabetes بـ
+
+110
+00:08:01,920 --> 00:08:05,260
+degree function و high function بتجيس ليه؟ هل
+
+111
+00:08:05,260 --> 00:08:09,120
+المرض هذا مرتبط بالعامل وراتي من الأبوين أو من أحد
+
+112
+00:08:09,120 --> 00:08:14,080
+من العائلة؟ جدش نسبة الناس اللي في العائلةموجودين
+
+113
+00:08:14,080 --> 00:08:19,540
+أو مصابين بالمرض، المرض السكري والـ Age الأعمار زي
+
+114
+00:08:19,540 --> 00:08:22,320
+ما قلنا والـ Outcome اللي هو ال label أو ال target
+
+115
+00:08:22,320 --> 00:08:25,800
+تبعتنا The binary classification صفر واحد، واحد
+
+116
+00:08:25,800 --> 00:08:29,380
+مصاب، صفر غير مصاب، واحنا بدنا نعمل prediction
+
+117
+00:08:29,380 --> 00:08:32,660
+نشوف هل فعليا اللي هو أنا زودته ببيانات معينة
+
+118
+00:08:32,660 --> 00:08:37,530
+هيقول إنه هذا مصاب أو غير مصاب، تمامالآن عشان
+
+119
+00:08:37,530 --> 00:08:41,590
+أتعرف على الـ Database بشكل كويس بقولنا ممكن انا
+
+120
+00:08:41,590 --> 00:08:49,230
+أروح أقوله الـ DataFrame.Describe والـ
+
+121
+00:08:49,230 --> 00:08:51,510
+Describe بقولنا هذا بتدينا Simple Statistics لكن
+
+122
+00:08:51,510 --> 00:08:55,330
+المرحلة ها دي بدي Transpose والناس اللي درست
+
+123
+00:08:55,330 --> 00:08:58,590
+رياضيات منفصلة بتعرف ان ال Transpose أو دراسة
+
+124
+00:08:58,590 --> 00:09:02,630
+مصفوفات بتعرف ان ال Transpose بعمل تبديل للصفوف
+
+125
+00:09:02,630 --> 00:09:07,570
+والأعنيلةأخيرًا هي راح جابليهم هان وبحيث ان ال
+
+126
+00:09:07,570 --> 00:09:11,790
+statistics ال count بتمثل عدد الصفوف اللي فيها
+
+127
+00:09:11,790 --> 00:09:18,310
+values طبعًا كله فيه values عندي هان 678 عدد ال
+
+128
+00:09:18,310 --> 00:09:21,310
+values ال main المتوسط الحسابي ال standard
+
+129
+00:09:21,310 --> 00:09:24,330
+deviation ال minimum value طبعًا جماعة الخير ال
+
+130
+00:09:24,330 --> 00:09:28,920
+minimum value زي الجليكوز وضغط الدمو الـ skin
+
+131
+00:09:28,920 --> 00:09:33,280
+thickness و الانسولين و ال body mass index، هذه
+
+132
+00:09:33,280 --> 00:09:38,320
+كلها بالنسبة لنا المفروض تكون هذه missing values
+
+133
+00:09:38,320 --> 00:09:41,200
+بس بدها معالجة، لأن مستحيل يكون عندي ال body mass
+
+134
+00:09:41,200 --> 00:09:44,040
+index صفر، مستحيل يكون الجليكوز في الدم صفر،
+
+135
+00:09:44,040 --> 00:09:48,490
+مستحيل blood pressure يكون صفربس أنا الان مش هشغل
+
+136
+00:09:48,490 --> 00:09:51,190
+على ال database مش هعملها pre-processing بينما انت
+
+137
+00:09:51,190 --> 00:09:54,490
+ملزم انك تعمل pre-processing لل database ال
+
+138
+00:09:54,490 --> 00:09:57,010
+database ده مش مناسب أقولك خد database تانية إذا
+
+139
+00:09:57,010 --> 00:10:01,260
+في حد مختار قدر اللهطيب، الآن أنا بحاجة زي ما قلنا
+
+140
+00:10:01,260 --> 00:10:06,380
+عن الـ Database هذه على علاتها وحافظة أروح أجهز
+
+141
+00:10:06,380 --> 00:10:11,500
+الـ Data Set للترانسي للـ Classification وأهم شغلة
+
+142
+00:10:11,500 --> 00:10:14,660
+في الـ Classification أنه أنا أعمل يا جماعة الخير
+
+143
+00:10:14,660 --> 00:10:18,320
+Split ما بين الـ Data Set Attribute أخد الـ
+
+144
+00:10:18,320 --> 00:10:21,040
+Attributes أو الـ Data Attributes لحال وأخد الـ
+
+145
+00:10:21,040 --> 00:10:25,480
+Target Attribute لحالي وهذا الكلام أنا بدي أروح
+
+146
+00:10:25,480 --> 00:10:34,910
+أسميها تحت«Data» أو «Data Set» «Splitting»
+
+147
+00:10:34,910 --> 00:10:41,750
+«Splitting» أو «Splitting»
+
+148
+00:10:41,750 --> 00:10:43,450
+«Splitting» «Splitting» «Splitting» «Splitting»
+
+149
+00:10:43,450 --> 00:10:43,610
+«Splitting» «Splitting» «Splitting» «Splitting»
+
+150
+00:10:43,610 --> 00:10:44,590
+«Splitting» «Splitting» «Splitting» «Splitting»
+
+151
+00:10:44,590 --> 00:10:44,590
+«Splitting» «Splitting» «Splitting» «Splitting»
+
+152
+00:10:44,590 --> 00:10:44,610
+«Splitting» «Splitting» «Splitting» «Splitting»
+
+153
+00:10:44,610 --> 00:10:44,650
+«Splitting» «Splitting» «Splitting» «Splitting»
+
+154
+00:10:44,650 --> 00:10:44,730
+«Splitting» «Splitting» «Splitting» «Splitting»
+
+155
+00:10:44,730 --> 00:10:44,750
+«Splitting» «Splitting» «Splitting» «Splitting»
+
+156
+00:10:44,750 --> 00:10:44,750
+«Splitting» «Splitting» «Splitting» «Splitting»
+
+157
+00:10:44,750 --> 00:10:56,130
+«Splitting» «Splitting» «Splitting» «Spl
+
+158
+00:10:59,800 --> 00:11:05,500
+Target Underscore Attribute كيف أنا بدي أعمل الـ
+
+159
+00:11:05,500 --> 00:11:08,140
+Splitting الآن؟ عملية الـ Splitting هي عبارة عن
+
+160
+00:11:08,140 --> 00:11:11,180
+أخد نصخة من الـ Attributes أنا ما بديش أخرّب في
+
+161
+00:11:11,180 --> 00:11:13,640
+الـ Data Frame الأصلي اللي موجود عندي هنا فبتحتقط
+
+162
+00:11:13,640 --> 00:11:19,760
+فيه و هروح أقوله أنا هنا ال Data أو ممكن أسميها ال
+
+163
+00:11:19,760 --> 00:11:25,480
+Attributes مباشرة Attribute
+
+164
+00:11:25,480 --> 00:11:31,770
+Equalالـ DataFrame.prop
+
+165
+00:11:31,770 --> 00:11:39,270
+بدي أحدث الـ Outcome
+
+166
+00:11:39,270 --> 00:11:45,570
+وهذا موجود على الـ Axis أرقم واحد فعليه مش هيحدثه
+
+167
+00:11:45,570 --> 00:11:48,570
+لأنه لم أقول له إنه Blast فبدي أخد نسخة من ال
+
+168
+00:11:48,570 --> 00:11:51,470
+DataFrame هذا و بيحدث ال Outcome وبدي أخذلني فيه
+
+169
+00:11:51,470 --> 00:11:56,930
+مين بحقليهم في ال Attributes تمام؟ وفي عندي Target
+
+170
+00:11:59,700 --> 00:12:06,340
+«attribute equals dataFrame dot أو dataFrame of
+
+171
+00:12:06,340 --> 00:12:15,140
+the outcome» وهكذا أصبح لدي two arrays تمثل
+
+172
+00:12:15,140 --> 00:12:20,140
+الـ «attributes» من الـ «age» إلى الـ «pregnancy»
+
+173
+00:12:20,390 --> 00:12:24,550
+والأخير بيمثل الـ Outcome أنا سميته إيش الـ Target
+
+174
+00:12:24,550 --> 00:12:28,690
+هذا الفصل مهم جدًا يا جماعة الخير بالنسبة لنا لأنه
+
+175
+00:12:28,690 --> 00:12:34,710
+من خلاله أنا بقدر أقول والله أنه ال data تبعتي تمت
+
+176
+00:12:34,710 --> 00:12:38,570
+طبعًا أنا الآن عملي ترنمج جابلي إنه okay أخدت رقم
+
+177
+00:12:38,570 --> 00:12:43,890
+أربعة سل هذه نفذت بدون أي مشاكل إذا حابب أنت تعمل
+
+178
+00:12:43,890 --> 00:12:48,070
+ال attribute describe أو تشوف
+
+179
+00:12:56,430 --> 00:12:59,030
+الخطوة التالية اللي أنا بدي أسويها في الـ
+
+180
+00:12:59,030 --> 00:13:01,630
+preparation، برضه من تحت الـ preparation، اللي أنا
+
+181
+00:13:01,630 --> 00:13:04,870
+بدي أجسم ال data set اللي موجودة عندي الآن، اللي
+
+182
+00:13:04,870 --> 00:13:13,140
+هي ال attributesالـ Data Attributes والـ Target
+
+183
+00:13:13,140 --> 00:13:17,480
+Attributes بدي أجسمهم على مستوى الـ Rows بحيث أنه
+
+184
+00:13:17,480 --> 00:13:20,700
+أجهز الـ Training Set والـ Testing Set زي ما أحنا
+
+185
+00:13:20,700 --> 00:13:29,740
+أبني علىها إيه هان؟ Splitting The
+
+186
+00:13:29,740 --> 00:13:34,080
+Data Set
+
+187
+00:13:34,080 --> 00:13:45,000
+واحنا بين جلسينحكّم الـ Attribute و
+
+188
+00:13:45,000 --> 00:13:59,550
+Target into Training and Test Setعشان أنفذ الكلام
+
+189
+00:13:59,550 --> 00:14:03,850
+هذا أنا بدي أروح من ال AsciiLab.model طبعاً هنا
+
+190
+00:14:03,850 --> 00:14:07,090
+بدي أبدأ أول أستخدم أول مكتبة بعد الـBandas اللي
+
+191
+00:14:07,090 --> 00:14:12,730
+موجودة فوق فهاجله from AsciiLab والـ AsciiLab يا
+
+192
+00:14:12,730 --> 00:14:16,350
+جماعة الخير أهم مكتبة بالنسبة لإلنا موجودة ممكن
+
+193
+00:14:16,350 --> 00:14:23,650
+أنا أستخدمها model underscore selection model
+
+194
+00:14:23,650 --> 00:14:24,530
+selection
+
+195
+00:14:29,600 --> 00:14:31,180
+ماذا أريد أن أستخدم من الـ Modeling و الـ
+
+196
+00:14:31,180 --> 00:14:36,860
+Selection؟ سأستخدم crane underscore test
+
+197
+00:14:36,860 --> 00:14:43,660
+underscore split function أو ميثود الموجودة في
+
+198
+00:14:43,660 --> 00:14:49,100
+داخلها الميثود هايبتش بتاخد مني argument هذه
+
+199
+00:14:49,100 --> 00:14:55,860
+الميثود بتاخد مني argument أهمها تلقى شغلات الـ
+
+200
+00:14:55,860 --> 00:14:59,140
+attributes ال data set اللي أنا
+
+201
+00:15:02,640 --> 00:15:07,240
+أشغل عليها الـ Attributes كأخد مني الـ Target،
+
+202
+00:15:07,240 --> 00:15:14,080
+تمام؟ دعني أتأكد إن كنت بالـ Target صح هما، والـ
+
+203
+00:15:14,080 --> 00:15:19,740
+Test أو الـ Train Size Test underscore Size بدها
+
+204
+00:15:19,740 --> 00:15:26,640
+تساوي 30% الآن شوف بسهولة، فعليًا بروح بجسم الـ
+
+205
+00:15:26,640 --> 00:15:31,340
+Attributes والـ Targets هما as one data frame
+
+206
+00:15:31,340 --> 00:15:36,000
+فعليًاالـ Index اللي موجود في الـ Attribute الأول
+
+207
+00:15:36,000 --> 00:15:39,760
+أو مع الـ Attributes هو نفس الـ Index الموجود على
+
+208
+00:15:39,760 --> 00:15:44,180
+الـ Target بس أنا فصلتهم كأعلى ده عن بعضهم لكن الـ
+
+209
+00:15:44,180 --> 00:15:48,140
+Index بقى نفس الترتيب، ماصارش فيه عليه الشغل طيب،
+
+210
+00:15:48,140 --> 00:15:52,520
+وبالتالي هو هياخد Random Sample نسبة 30% من الـ
+
+211
+00:15:52,520 --> 00:15:57,260
+Indices اللي موجودة هنا ويعمل الـ Reaction 30% هذه
+
+212
+00:15:57,260 --> 00:16:04,240
+هترجع في لمين؟ هترجع لـ X Testوالـ Y-test اللي هي
+
+213
+00:16:04,240 --> 00:16:08,980
+الـ Attributes الخاصة بالتست والـ Target الخاص
+
+214
+00:16:08,980 --> 00:16:14,340
+بالتست خلّيني أسميهم X وY والمصطلحات هذه درجة جداً
+
+215
+00:16:14,340 --> 00:16:18,800
+في التسميات بالإضافة لهيك، أنا فيه عندي الـ X
+
+216
+00:16:18,800 --> 00:16:22,380
+train والـ Y train اللي هم الـ 70% اللي بيظلوا من
+
+217
+00:16:22,380 --> 00:16:26,660
+ال data sets اللي موجودة عندي فأنا فعلياً هكون فيه
+
+218
+00:16:26,660 --> 00:16:32,400
+عندي X train كمان Y train
+
+219
+00:16:35,840 --> 00:16:45,880
+كما X test كما Y test وهذه أربع مجموعات بحيث أن
+
+220
+00:16:45,880 --> 00:16:50,480
+الـ procedure هذا أو الـ function هذه أو الـ
+
+221
+00:16:50,480 --> 00:16:55,180
+constructor هذا بيرجعلي بأربع مجموعات X test X
+
+222
+00:16:55,180 --> 00:16:59,930
+دلالة على الـ attributesتمام فالـ X هي عبارة عن
+
+223
+00:16:59,930 --> 00:17:03,550
+subset من الـ attributes X train و X test X test
+
+224
+00:17:03,550 --> 00:17:08,670
+بتمثل 30% من ال attributes والـ X train بتاخد 70%
+
+225
+00:17:08,670 --> 00:17:11,250
+طبعا ممكن أنا أبدل هنا، أروح أقول له لـ train test
+
+226
+00:17:11,250 --> 00:17:16,170
+أو لـ train size 70 تمام؟ وبيمشي الحال، الآن الـ Y
+
+227
+00:17:16,170 --> 00:17:21,530
+train هي عبارة عن 70% من ال target بناء على ال
+
+228
+00:17:21,530 --> 00:17:25,620
+index اللي تم أخدهاوالـ Y-test هي عبارة عن الـ
+
+229
+00:17:25,620 --> 00:17:29,700
+Sample اللي موجودة عنا طبعاً عشان نتأكد أن الأمور
+
+230
+00:17:29,700 --> 00:17:33,620
+تمام و ال splitting صح تمت، هروح أنا أقول له X
+
+231
+00:17:33,620 --> 00:17:40,060
+train dot
+
+232
+00:17:40,060 --> 00:17:44,760
+head و بدي أقوله بس يعرض الأول تلاتة منهم أو مش
+
+233
+00:17:44,760 --> 00:17:47,620
+قضية، هي الأول عشرة بس عشان نشوف ال indices اللي
+
+234
+00:17:47,620 --> 00:17:53,740
+موجودة فيهمهي، واحظوا زي ما حكينا هذا عبارة عن الـ
+
+235
+00:17:53,740 --> 00:18:01,180
+Index الآن في المقابل، لو أنا روحت عرضة الـ Y
+
+236
+00:18:01,180 --> 00:18:06,600
+-Train وقلت له هي في السلة اللي بعدها، بس عشان
+
+237
+00:18:06,600 --> 00:18:14,000
+أؤكدلكم الـ Ytrain.head
+
+238
+00:18:14,000 --> 00:18:21,550
+وخلّيني على عشرة كذلك، Runطلع معايا في الـ index
+
+239
+00:18:21,550 --> 00:18:29,230
+ويترين
+
+240
+00:18:29,230 --> 00:18:29,770
+ويترين
+
+241
+00:18:46,050 --> 00:18:50,710
+أنا أخطأ تاني يا جماعة الخير في التسمية هي المفروض
+
+242
+00:18:50,710 --> 00:18:57,310
+X test X test
+
+243
+00:18:57,310 --> 00:19:07,870
+thirty three five green هينعمل run مرة تانية
+
+244
+00:19:07,870 --> 00:19:15,090
+هينعمل run للسل high أه، هيك تمامأنا اللي أختار في
+
+245
+00:19:15,090 --> 00:19:19,490
+تركيب العناصر اللي فوق ببدأ بالـ Exit Test بالـ
+
+246
+00:19:19,490 --> 00:19:24,250
+Attributes و بالـ Yالـ Target طبعًا هي ميزة إنه
+
+247
+00:19:24,250 --> 00:19:27,990
+أنا فعليًا بضل بتبع الـ Data شو صار فيها، مابخطيش،
+
+248
+00:19:27,990 --> 00:19:32,690
+لاحظوا 155، 155 هي نفس الـ Index اللي موجود يعني،
+
+249
+00:19:32,690 --> 00:19:34,750
+فأنا أمور من ناحية الـ Database الآن أو الـ
+
+250
+00:19:34,750 --> 00:19:38,490
+Splitting للـ Data جاهزة، بحيث إنه أنا جسمت الـ
+
+251
+00:19:38,490 --> 00:19:41,450
+Data، فصلت الـ Attributes، الـ Data Attributes
+
+252
+00:19:41,450 --> 00:19:45,030
+والـ Target Attributes، فصلت كل واحد فيهم في Data
+
+253
+00:19:45,030 --> 00:19:48,810
+fileهو روحت للـ data set أو الـ two data frames
+
+254
+00:19:48,810 --> 00:19:55,210
+دول فصلتهم كمان ل test set و فوقه train set و هبدأ
+
+255
+00:19:55,210 --> 00:20:00,370
+استخدم train set في موضوع ال classification الان
+
+256
+00:20:00,370 --> 00:20:06,830
+بدأ أستخدم ال K nearest neighbor KNN
+
+257
+00:20:06,830 --> 00:20:15,070
+أو ما يعرف بالـ K nearest neighbor
+
+258
+00:20:22,150 --> 00:20:25,250
+هنا تبعت الخير في الـ Canary's Neighbour Model
+
+259
+00:20:25,250 --> 00:20:28,950
+يقول إنها أهم شغلة تريد التعرف عليها من أين تريد
+
+260
+00:20:28,950 --> 00:20:39,370
+أن تعمل الـ Import؟ لأن من الـ Asciler Dot
+
+261
+00:20:39,370 --> 00:20:43,530
+طبعاً هنا عندني عائلة اسمها Neighbours أو ال
+
+262
+00:20:43,530 --> 00:20:47,750
+library عشان ماحدش يقول ليه عائلة Neighbours هروح
+
+263
+00:20:47,750 --> 00:20:48,590
+أقول له Import
+
+264
+00:20:54,790 --> 00:21:06,810
+«nearest neighbor» «neighbors
+
+265
+00:21:06,810 --> 00:21:10,870
+as KN»
+
+266
+00:21:10,870 --> 00:21:17,930
+الأن هذا الموديل أنا بممكن أنشئه مباشرة «KNN»
+
+267
+00:21:42,660 --> 00:21:46,440
+والخطوة التالية اللي بعد هيك أنا ممكن أحدد له
+
+268
+00:21:50,220 --> 00:21:53,040
+الـ Model أو أروح أعمله Fit اللي كان المفروض
+
+269
+00:21:53,040 --> 00:21:57,460
+أحددله الـ Data Set اللي بده يعمل عليها Training
+
+270
+00:21:57,460 --> 00:22:02,180
+أو مقارنة هي المفروض الـ Train Data Set لكن في
+
+271
+00:22:02,180 --> 00:22:07,800
+ملاحظة مهمة جدا قبل ما نكمل طبعا بإمكاني أنا أوقف
+
+272
+00:22:07,800 --> 00:22:11,620
+هذه وأعلقها
+
+273
+00:22:17,090 --> 00:22:21,130
+الآسي جمعة الخير هي من أجل الاختصار الـ AS من أجل
+
+274
+00:22:21,130 --> 00:22:24,470
+الاختصار عشان مابترضش أكتب الاسم بالكامل يعني لو
+
+275
+00:22:24,470 --> 00:22:29,750
+أنا بدي أكتبها، هروح أقول «KN N underscore model
+
+276
+00:22:29,750 --> 00:22:33,670
+equals
+
+277
+00:22:33,670 --> 00:22:43,610
+nearest neighbors و N underscore neighbor equals
+
+278
+00:22:43,610 --> 00:22:48,470
+ثلاثة»عفواً، خمسة، خلّيني أعمل نفسي، أمشي على نفس
+
+279
+00:22:48,470 --> 00:22:51,230
+الـStyle هذه واللي فوق نفس المعنى، بس أنا هنا
+
+280
+00:22:51,230 --> 00:22:55,530
+بأختصر في الكتابة بناءً على .. بعمل Alias Name
+
+281
+00:22:55,530 --> 00:22:59,210
+وبستخدم الـAlias Name الآن بضل أقولّهم الـKNN
+
+282
+00:22:59,210 --> 00:23:06,010
+underscore model fit
+
+283
+00:23:06,010 --> 00:23:12,710
+وفي ال training، شو بياخد؟ بياخد الـX train والـY
+
+284
+00:23:12,710 --> 00:23:18,620
+trainلأن هذه هي الـ data اللي انا بتعمل عليها أو
+
+285
+00:23:18,620 --> 00:23:22,260
+من خلالها ال training لو انا اشتغلت عملت له run
+
+286
+00:23:22,260 --> 00:23:35,620
+وشكلي
+
+287
+00:23:35,620 --> 00:23:37,620
+أنا أخطأت في ال nearest neighbors
+
+288
+00:23:46,470 --> 00:23:51,630
+«nearest neighbours» صح الصح الـ «spelling» صح
+
+289
+00:23:51,630 --> 00:24:05,130
+«EG» «EI» «GH» «D» «O» «R» «S»
+
+290
+00:24:05,130 --> 00:24:08,190
+ليش؟
+
+291
+00:24:21,090 --> 00:24:35,170
+ممكن عشان أنا حطيت الـ alias name فوق عشان
+
+292
+00:24:35,170 --> 00:24:40,270
+حطيت الـ alias name عشان حطيت الـ alias name لأن
+
+293
+00:24:40,270 --> 00:24:45,710
+الـ alias name بدله لكن لو أنا شهيت هذا وعلّجت
+
+294
+00:24:45,710 --> 00:24:46,030
+هذه
+
+295
+00:24:52,850 --> 00:25:00,330
+مش هيكون في خطأ فممكن
+
+296
+00:25:00,330 --> 00:25:03,590
+أنا أستخدم هاي أو هاي بحسب الحالة اللي موجودة
+
+297
+00:25:03,590 --> 00:25:08,170
+عليها تمام، فالـ mode أصبح جاهز يتعرّف على الـ
+
+298
+00:25:08,170 --> 00:25:10,890
+trend data أو الـ trend set اللي أنا بدي أشتغل
+
+299
+00:25:10,890 --> 00:25:14,950
+عليها وهي بطبيعة الحالة مجسومة للـ tribunes وطبعاً
+
+300
+00:25:14,950 --> 00:25:19,510
+الخطوة التالية أنا عمال بدي أروح أعمل أو بدي أشوف
+
+301
+00:25:19,510 --> 00:25:23,510
+ال majors إيش ممكن يسوي ليهالـ Element اللي موجود
+
+302
+00:25:23,510 --> 00:25:27,050
+أو الـ Model اللي أنا أنشرته لكن عشان أنا أنشق الـ
+
+303
+00:25:27,050 --> 00:25:30,530
+Model جمال الخير أو بدي أجرب الـ Model خليني أشوف
+
+304
+00:25:30,530 --> 00:25:35,450
+أو أخد عينة من الـ Data اللي موجودة عندها في موضوع
+
+305
+00:25:35,450 --> 00:25:39,070
+من
+
+306
+00:25:39,070 --> 00:25:42,450
+الـ Data Set بشكل عام أنا بدي أروح و أقول له أنا
+
+307
+00:25:42,450 --> 00:25:46,190
+طبعاً أول هيكون الأول استخدام للـ Numpy اللي
+
+308
+00:25:46,190 --> 00:25:56,740
+موجودة فوق هروح أقوله T1هذه الـ array مكوّنة من
+
+309
+00:25:56,740 --> 00:26:07,640
+مجموعة أرقام وليكن
+
+310
+00:26:07,640 --> 00:26:12,940
+على سبيل المثال الصف الأول وهذه ال class موجودة
+
+311
+00:26:12,940 --> 00:26:13,320
+هنا
+
+312
+00:26:17,220 --> 00:26:21,720
+الـ Ctrl V التابس هذه بدي استبدلها بـ Comma
+
+313
+00:26:31,800 --> 00:26:35,140
+طبعًا، يا عزيزي، في شغل مهم لازم نقولها الآن إنه
+
+314
+00:26:35,140 --> 00:26:38,300
+مش ضروري الـ Prediction دائمًا يعني ماحدش بيقول
+
+315
+00:26:38,300 --> 00:26:40,800
+الـ Prediction بيكون صحيح أو بيكون حقيقية 100%
+
+316
+00:26:40,800 --> 00:26:43,720
+لازم يكون في أخطاء عندي دائمًا أو في معظم الأحيان
+
+317
+00:26:43,720 --> 00:26:47,160
+يكون في عندك أخطاء وكل ما اكتمل أو كل ما كانت ال
+
+318
+00:26:47,160 --> 00:26:50,520
+Prediction تبعت ال score تبعته أعلى بيكون كويسة
+
+319
+00:26:50,520 --> 00:26:57,720
+Doc Re-Shape كله اعتمد المصفوفة هذه على إيها واحد
+
+320
+00:26:57,720 --> 00:27:06,120
+سالب واحدوطبعاً هاي ال target هحط هنا target equal
+
+321
+00:27:06,120 --> 00:27:14,720
+one وخلّيني أنا أنسخ هذه هيك Ctrl V وبدأ أجي على
+
+322
+00:27:14,720 --> 00:27:20,760
+ال raw اللي رقمه خمسة أنسخه وال target تبعته صفر
+
+323
+00:27:20,760 --> 00:27:23,200
+هذا بدي أسميه T5
+
+324
+00:27:33,150 --> 00:27:38,710
+بنفس الكلام الـ
+
+325
+00:27:38,710 --> 00:27:47,030
+caps اللي عندي بكمس عشان تتحول كيما اللي عندي لاش
+
+326
+00:27:47,030 --> 00:27:53,370
+لمصفوفة تمام ننبغي نفس العدد
+
+327
+00:28:01,810 --> 00:28:08,410
+تمام، ليس مشكلة لان عندما انا اعمل train الـ model
+
+328
+00:28:08,410 --> 00:28:11,130
+اللي انا انشأته model.k-neighbors لديه method
+
+329
+00:28:11,130 --> 00:28:17,070
+اسمها model.k-neighbors انا هايه ال model تبعي KNN
+
+330
+00:28:17,070 --> 00:28:24,430
+underscore model.k-neighbors
+
+331
+00:28:25,990 --> 00:28:30,270
+ولا مين؟ وبديله مين؟ وبديله ال test element اللي
+
+332
+00:28:30,270 --> 00:28:37,030
+انا بدي افحصه وليكن T1 كمه ومع عدد عناصر الجوار
+
+333
+00:28:37,030 --> 00:28:42,430
+خمسة عدد عناصر الجوار خمسة بتحس في لحظة من اللحظات
+
+334
+00:28:42,430 --> 00:28:47,050
+ان ال K الخمسة اللي انا عنها ماالهاش علاقة هذه ال
+
+335
+00:28:47,050 --> 00:28:50,290
+method اللي موجود خليني اشوف و اروح طبعا هذه ال
+
+336
+00:28:50,290 --> 00:28:55,370
+method بترجعلي two vectorsالفكتور الأول يمثل الـ
+
+337
+00:28:55,370 --> 00:28:59,930
+distances كما
+
+338
+00:28:59,930 --> 00:29:08,790
+والفكتور التاني ال index تمام؟ ال index أو ال
+
+339
+00:29:08,790 --> 00:29:15,850
+indices نفس المصطلحات indices لمن؟
+
+340
+00:29:15,850 --> 00:29:18,550
+لـ Indices
+
+341
+00:29:22,020 --> 00:29:27,480
+للـ Raw اللي هي صاحبة أقصر مسافة يعني الـ
+
+342
+00:29:27,480 --> 00:29:31,600
+Cannibals هدول بيروح بيجيبلي أقرب خمسة للـ Element
+
+343
+00:29:31,600 --> 00:29:36,760
+لـ T1 أقرب خمسة لـ T1 وبما أنه المفروض T1 يتمثل
+
+344
+00:29:36,760 --> 00:29:39,480
+الـ Raw الأول في ال data set اللي عندي فهيروح
+
+345
+00:29:39,480 --> 00:29:43,460
+يقوللي ال index رقم Zero او ال index رقم Zero هكون
+
+346
+00:29:43,460 --> 00:29:47,680
+هذا ال distance تبعك صفر وهجيبلي ال index في
+
+347
+00:29:47,680 --> 00:29:52,680
+مصفوفة تانية أنا الآن هروح أقولله eventخلّينا
+
+348
+00:29:52,680 --> 00:29:58,480
+بنشوفها في مجال آخر هيـRun الآن المفروض تم التنفيذ
+
+349
+00:29:58,480 --> 00:30:04,580
+هأخد كود جديد وبدي أروح أقبع الـDistances
+
+350
+00:30:22,010 --> 00:30:26,970
+لاحظوا يا جماعة الخير، صفر، عشرة، خمسة و خمسين،
+
+351
+00:30:26,970 --> 00:30:34,170
+تسعة و عشرة، تسعة و عشرة، عشرين، عشرة
+
+352
+00:30:34,170 --> 00:30:34,270
+و عشرة، عشرة و عشرة، عشرة و عشرة، عشرة و عشرة،
+
+353
+00:30:34,270 --> 00:30:34,290
+عشرة و عشرة، عشرة و عشرة، عشرة و عشرة، عشرة و
+
+354
+00:30:34,290 --> 00:30:34,350
+عشرة، عشرة و عشرة، عشرة و عشرة، عشرة و عشرة، عشرة
+
+355
+00:30:34,350 --> 00:30:34,570
+و عشرة، عشرة و عشرة، عشرة و عشرة، عشرة و عشرة،
+
+356
+00:30:34,570 --> 00:30:38,390
+عشرة و عشرة، عشرة و عشرة، عشرة و عشرة، عشرة و
+
+357
+00:30:38,390 --> 00:30:47,440
+عشرة، عشرة و عشرة، عشرة و عشرة، عشرة و عشرةهذه أو
+
+358
+00:30:47,440 --> 00:30:51,080
+أقرب distance لأنه بيرتب ليهم ترتيب تساعدي حسب
+
+359
+00:30:51,080 --> 00:30:54,960
+الأقرب فالأقرب، طيب، الآن إذا أنا بدي أشوف ال
+
+360
+00:30:54,960 --> 00:30:58,900
+indexes تبع العناصر اللي موجودة عندها أو بدي أشوف
+
+361
+00:30:58,900 --> 00:31:02,100
+ال target تبع ال indices اللي موجودة عندها، ممكن
+
+362
+00:31:02,100 --> 00:31:09,960
+أنا أروح أقول له target of
+
+363
+00:31:09,960 --> 00:31:14,080
+I from
+
+364
+00:31:15,690 --> 00:31:22,530
+الـ I موجودة أين؟ أو عفوًا، for الـ I for
+
+365
+00:31:22,530 --> 00:31:30,390
+I M، ال indices أنا
+
+366
+00:31:30,390 --> 00:31:34,810
+هذه مصفوفة برضه من بعدي، فاروح أقوله بعد أيام،
+
+367
+00:31:34,810 --> 00:31:35,310
+فإشرح
+
+368
+00:31:52,280 --> 00:32:00,580
+Target غلط طبعاً
+
+369
+00:32:00,580 --> 00:32:04,760
+هان لما كنت بحاول أن أطبع الـ Element بقول لي إن
+
+370
+00:32:04,760 --> 00:32:08,140
+هذا عبارة عن object طب ال object أنا بدي أجيب ال
+
+371
+00:32:08,140 --> 00:32:10,920
+contents تبعته أو محتوى ال object اللي عندي هان
+
+372
+00:32:10,920 --> 00:32:15,300
+فهينطبعته بالشكل اللي موجود عندي هان جلبناه على
+
+373
+00:32:15,300 --> 00:32:19,570
+السبعة اللي موجودات فوقالـ Indices تبعتهم أو الـ
+
+374
+00:32:19,570 --> 00:32:22,590
+Classes بناءً على الـ Indexes اللي موجود عندها
+
+375
+00:32:22,590 --> 00:32:26,550
+يعني احنا اتفقنا ال Indices هي عبارة عن ال Index
+
+376
+00:32:26,550 --> 00:32:33,910
+تبعت ال Train Test أو الـ X-Train القريبة من أو
+
+377
+00:32:33,910 --> 00:32:39,450
+الأقرب لـ T1فكان صفر و صفر وهذه الـ Label سبعتهم
+
+378
+00:32:39,450 --> 00:32:43,630
+لان انا بدي اعمل voting هروح اعد انا هدول هي واحد
+
+379
+00:32:43,630 --> 00:32:48,250
+اتنين تلاتة اربعة خمسة خمسة من سبعة Zero و اتنين
+
+380
+00:32:48,250 --> 00:32:53,530
+من سبعة one معناته ان ال class اللي موجود عندي هنا
+
+381
+00:32:53,530 --> 00:32:59,290
+سبعة طب لو انا بدي اعيد التجربة هي لخمسة وهي run
+
+382
+00:32:59,290 --> 00:33:06,780
+السلة البولة اللي بعديهاوهي الـ cell اللي بعديها
+
+383
+00:33:06,780 --> 00:33:11,760
+فجالك إنه الآن برضه 00 بس القيم اللي عندي فوق
+
+384
+00:33:11,760 --> 00:33:15,320
+اختلفت مش قضية لإن هي في الآخر ال values اللي
+
+385
+00:33:15,320 --> 00:33:18,720
+عنديها صارتان طب لو أنا فكرت إنه أغير في ال values
+
+386
+00:33:18,720 --> 00:33:25,840
+اللي عنديها حضر أروح أعمل run عشان أخدها، okay هي
+
+387
+00:33:25,840 --> 00:33:32,900
+خليني أقول هنا 30، هي run، لاحظوا ال distance
+
+388
+00:33:32,900 --> 00:33:38,070
+اختلافها؟تختلفت الـ distance كلياً الآن والأخير هي
+
+389
+00:33:38,070 --> 00:33:44,910
+run وهيصار في عندي تلاتة one وأربعة zero فهو في
+
+390
+00:33:44,910 --> 00:33:47,910
+الآخر هيعمله ال classification على أنه zero،
+
+391
+00:33:47,910 --> 00:33:51,230
+ممتاز، لكن هذا برضه مش هو الشغل اللي احنا فعلياً
+
+392
+00:33:51,230 --> 00:33:55,450
+محتاجينه، بس نحط بعض ال comments هنا
+
+393
+00:34:03,930 --> 00:34:11,170
+Print target of
+
+394
+00:34:11,170 --> 00:34:18,030
+the most of
+
+395
+00:34:18,030 --> 00:34:23,630
+the nearest neighbors
+
+396
+00:34:23,630 --> 00:34:24,950
+or
+
+397
+00:34:49,610 --> 00:34:52,410
+«الأزدهار» «الأزدهار»
+
+398
+00:34:56,600 --> 00:35:01,560
+الآن سأنتقل لجزئية أكتر أهمية عشان تتكلم عنها
+
+399
+00:35:01,560 --> 00:35:04,920
+Classification عشان أتشتغل على Classification من
+
+400
+00:35:04,920 --> 00:35:07,640
+نفس الـ Library «High from Escalar Neighbors»
+
+401
+00:35:07,640 --> 00:35:13,780
+«Import» في عندي الـ «K nearest neighbor» أو الـ
+
+402
+00:35:13,780 --> 00:35:17,540
+«K neighbors classifier»
+
+403
+00:35:17,540 --> 00:35:22,880
+هاجهان from K
+
+404
+00:35:38,630 --> 00:35:43,710
+نفس الكلام السابق بس الأن بدي أسميه KMN underscore
+
+405
+00:35:43,710 --> 00:35:49,210
+classifier equal الـ model اللي موجود عندي هنا
+
+406
+00:35:49,210 --> 00:35:50,610
+number of neighbors
+
+407
+00:35:54,190 --> 00:35:57,350
+يكون الخمسة أو سبعة مش قطيع كتير زي ما حكينا،
+
+408
+00:35:57,350 --> 00:36:00,450
+المهم أنا أختارها بعناية للبرنامج وحين انتوا في
+
+409
+00:36:00,450 --> 00:36:04,310
+الآخر مطلوب منكوا إذا اختارت الـK فتقولي ليش
+
+410
+00:36:04,310 --> 00:36:06,910
+اعتمدت على الـK هذه؟ يعني انت مطلوب تجرب في الواجب
+
+411
+00:36:06,910 --> 00:36:11,730
+مرة و كنتين و تلاتة، K7، K15، K20، إذا اختار K
+
+412
+00:36:11,730 --> 00:36:14,650
+مناسبة بيقولك بحيث أنها تديك أفضل accuracy قدر
+
+413
+00:36:14,650 --> 00:36:19,100
+المستطاع اللي موجودطبعاً في مقلوب منكم تقرير مع
+
+414
+00:36:19,100 --> 00:36:23,580
+الواجب هذا بحيث أنه انتوا تحددوا كل بساطة أو
+
+415
+00:36:23,580 --> 00:36:27,540
+تحددوا بالتفصيل انت ايش سويت و ايش النتائج اللي
+
+416
+00:36:27,540 --> 00:36:32,680
+اشتغلت عليها و النتائج اللي حصلت عليها طيب الآن
+
+417
+00:36:32,680 --> 00:36:38,860
+هذا ال model KMN underscore classifier بيحتاج انه
+
+418
+00:36:38,860 --> 00:36:44,870
+اعمله fit وعملية ال fit زي ما قلنا ال extremeوالـ
+
+419
+00:36:44,870 --> 00:36:51,210
+Y-train بقى زودوا فيهم ممتاز بالنسبة لي هيكاد
+
+420
+00:36:51,210 --> 00:36:57,130
+استدعاء الـ classifier وتجهيزه وهي أنا الـ using
+
+421
+00:36:57,130 --> 00:37:00,450
+the
+
+422
+00:37:00,450 --> 00:37:07,270
+nearest neighbor classifier as classification
+
+423
+00:37:07,270 --> 00:37:10,750
+model تمام
+
+424
+00:37:12,410 --> 00:37:16,570
+من عمل train بشكل صحيح لـ classifier اللي موجود
+
+425
+00:37:16,570 --> 00:37:21,070
+عندي ممتاز، طب لو أنا الآن اذا ال classifier تم
+
+426
+00:37:21,070 --> 00:37:24,490
+إنش أوي بدا انتقل لمرحلة prediction خد بحيث انه
+
+427
+00:37:24,490 --> 00:37:32,730
+بده اعمل test test دي اللي انا سميته knn
+
+428
+00:37:32,730 --> 00:37:39,370
+underscore classifier using
+
+429
+00:37:41,370 --> 00:37:47,370
+الـ X test والـ
+
+430
+00:37:47,370 --> 00:37:54,690
+Y test والآن في عندي مثلًا في الـ KNN underscore
+
+431
+00:37:54,690 --> 00:38:04,610
+model عفوًا الـ classifier dot predict method أو
+
+432
+00:38:04,610 --> 00:38:09,400
+الـ model اللي عندي dot predictالـ Prediction
+
+433
+00:38:09,400 --> 00:38:25,460
+بتاخد الـ X-Train و Y-Test وبترجعلي الـ
+
+434
+00:38:25,460 --> 00:38:29,160
+Y-Predict
+
+435
+00:38:31,250 --> 00:38:34,950
+الـ Target اللي هي الموجودة عندها بمجرد ذلك، دعوني
+
+436
+00:38:34,950 --> 00:38:42,730
+أقول له اطبع ليها Y-Predict كنت أتأكد أن الأمور
+
+437
+00:38:42,730 --> 00:38:55,230
+تمام، وعمل Prediction تاكس
+
+438
+00:38:55,230 --> 00:39:00,810
+تو Positional Argument but three were given Space
+
+439
+00:39:22,500 --> 00:39:27,960
+أنا المفروض أدّي الـ text الـ attributes وهو بده
+
+440
+00:39:27,960 --> 00:39:31,860
+يعمل prediction أنا آسف على الخطأ هذا، الآن هي الـ
+
+441
+00:39:31,860 --> 00:39:36,090
+predicted labels اللي موجودة عنديأو كأنا فكرت حالي
+
+442
+00:39:36,090 --> 00:39:40,710
+وصلت لمراحة الـ Evaluation سمحوني، هي العناصر اللي
+
+443
+00:39:40,710 --> 00:39:43,930
+موجودة عندها هذه عبارة عن كلية Predicted Labels
+
+444
+00:39:43,930 --> 00:39:47,870
+Predicted Labels زمين للـ X Test اللي موجودة وين
+
+445
+00:39:47,870 --> 00:39:50,430
+الـ Label الحقيقي تبعها موجود؟ الـ Label الحقيقي
+
+446
+00:39:50,430 --> 00:39:55,950
+موجود في الـ Y Train أو في الـ Y Test هاي طيب،
+
+447
+00:39:55,950 --> 00:40:00,150
+الآن عشان أنا أبدأ أقارن خليني أول حاجة نتعرف على
+
+448
+00:40:00,150 --> 00:40:05,040
+الـ Confusion Matrix اللي موجودة عندهاوهنا في عندي
+
+449
+00:40:05,040 --> 00:40:15,880
+الـ classification model evaluation هنبدأ
+
+450
+00:40:15,880 --> 00:40:25,940
+الآن الان from ال ASCII layer import matrix
+
+451
+00:40:28,280 --> 00:40:31,460
+الآن بدي أجيب الـ Matrix، إيش الـ Matrix جامعة
+
+452
+00:40:31,460 --> 00:40:34,540
+الخيار؟ تحتوي أنه من خلالها أنا ممكن أنشأ الـ
+
+453
+00:40:34,540 --> 00:40:37,100
+confusion matrix، أحسب الـ accuracy، أحسب ال
+
+454
+00:40:37,100 --> 00:40:40,240
+precision، أحسب ال recall، أحسب ال أثمجة، كل هذه
+
+455
+00:40:40,240 --> 00:40:44,260
+لدى ال attribute، عفوا، للكاسيفير اللي موجود
+
+456
+00:40:44,260 --> 00:40:49,940
+عندها، وخليني أنا أبدأ مع ال confusion matrix،
+
+457
+00:41:07,520 --> 00:41:13,880
+الـ M الـ CM متر ايقال
+
+458
+00:41:24,700 --> 00:41:29,180
+هنا كل الـ evaluation functions اللي موجودة عندنا
+
+459
+00:41:29,180 --> 00:41:33,420
+هتاخد مني شغلتين هتاخد مني الـ y test اللي هو ال
+
+460
+00:41:33,420 --> 00:41:37,260
+label الحقيقي والي predicted أو الـ y predicted
+
+461
+00:41:37,260 --> 00:41:43,800
+الـ y predict وهي
+
+462
+00:41:43,800 --> 00:41:48,590
+بدي أروح أقوله اطبع ليه ال matrix اللي عندنااللي
+
+463
+00:41:48,590 --> 00:41:52,010
+هي الـ Confusion Matrix الـ Test Set بيتك حجمها
+
+464
+00:41:52,010 --> 00:41:57,450
+هيهم المجموع العناصر الموجودة 120، 25، True
+
+465
+00:41:57,450 --> 00:42:02,570
+Positive، True Negative، False Positive، False
+
+466
+00:42:02,570 --> 00:42:08,250
+Negative، False Positive، False Negative بس إيش ال
+
+467
+00:42:08,250 --> 00:42:11,270
+classes اللي موجودة عندي يا جماعة الخير؟ ال
+
+468
+00:42:11,270 --> 00:42:13,670
+classes يا أخواننا و يا أخواتي بيكونوا تنتبهوا
+
+469
+00:42:13,670 --> 00:42:17,770
+بشكل كويسلأنه أنا ما حدد لهوش إيش ال classes فإيش
+
+470
+00:42:17,770 --> 00:42:22,890
+هو بياخد مباشرة بيروح بيعتمد على الآن أول ما قرأت
+
+471
+00:42:22,890 --> 00:42:29,870
+data set أول ما قرأت data set إيش أول class واجهه؟
+
+472
+00:42:29,870 --> 00:42:32,730
+طبعاً أنا بتكلم في ال test set هذا لأن أول ما
+
+473
+00:42:32,730 --> 00:42:37,250
+زودته، زودته غنين في ال Y-predict أول element في
+
+474
+00:42:37,250 --> 00:42:41,870
+ال Y-test
+
+475
+00:42:46,220 --> 00:42:49,820
+كان واحد، فخلاص، بيعتبر أنه هذا للـ Class الأول،
+
+476
+00:42:49,820 --> 00:42:53,980
+تمام؟ وهذا للClass الثاني، طبعاً هذه العناصر
+
+477
+00:42:53,980 --> 00:42:56,240
+معناته أنها الـ confusion matrix ومن خلالها أنا
+
+478
+00:42:56,240 --> 00:43:00,000
+بنطلق و بحسب كل حاجة، طب إذا أنا بدأ أحسب ال
+
+479
+00:43:00,000 --> 00:43:05,240
+accuracy الآن،
+
+480
+00:43:05,240 --> 00:43:08,260
+اذكروا ال accuracy كانت إيش بتساوي؟ ال true
+
+481
+00:43:08,260 --> 00:43:12,360
+positive زائد ال true negative على كل العناصر
+
+482
+00:43:12,360 --> 00:43:13,600
+المجموعة هنا
+
+483
+00:43:19,260 --> 00:43:25,360
+سأقوم بإعادة الـ Accuracy ACC متركز تساوي متركز
+
+484
+00:43:25,360 --> 00:43:28,040
+تساوي متركز تساوي متركز تساوي متركز تساوي متركز
+
+485
+00:43:28,040 --> 00:43:33,260
+تساوي متركز تساوي متركز تساوي متركز تساوي متركز
+
+486
+00:43:33,260 --> 00:43:33,800
+تساوي متركز تساوي متركز تساوي متركز تساوي متركز
+
+487
+00:43:33,800 --> 00:43:33,800
+تساوي متركز تساوي متركز تساوي متركز تساوي متركز
+
+488
+00:43:33,800 --> 00:43:34,360
+تساوي متركز تساوي متركز تساوي متركز تساوي متركز
+
+489
+00:43:34,360 --> 00:43:39,340
+تساوي متركز تساوي متركز تساوي متركز تساوي متركز
+
+490
+00:43:39,340 --> 00:43:48,690
+تساوي متهو الـ Accuracy للـ Model اللي موجود انك
+
+491
+00:43:48,690 --> 00:43:55,850
+هان Matrix dot مش underscore جالي
+
+492
+00:43:55,850 --> 00:44:01,430
+72.27 ممتاز، بدي أنتقل للسلة اللي بعدها لو أنا بدي
+
+493
+00:44:01,430 --> 00:44:05,330
+أحسب ال F major score أو ال precision ال first
+
+494
+00:44:05,330 --> 00:44:07,690
+class اللي موجود عندي هان
+
+495
+00:44:15,790 --> 00:44:20,710
+بنفس الكيفية اللي موجودة عندي هان بدي أسميها
+
+496
+00:44:20,710 --> 00:44:29,190
+precision equal matrix dot precision underscore
+
+497
+00:44:29,190 --> 00:44:35,950
+score وبدي أعطيه المجموعتين ولمّا انا بدي أقوله
+
+498
+00:44:35,950 --> 00:44:41,010
+pre قطعليه لا إله إلا الله
+
+499
+00:44:48,420 --> 00:44:55,240
+بتحملوني شو هساولكم يعني 65 اللي بعدها احسن من ال
+
+500
+00:44:55,240 --> 00:45:01,800
+recallفالأمور كلها بالشكل هذا اللي هتتجمع طبعاً
+
+501
+00:45:01,800 --> 00:45:04,560
+لاحظوا الـ Acrylic Model ككل الـ Precision الـ
+
+502
+00:45:04,560 --> 00:45:07,900
+First Class الـ Recall الـ First Class هيك هيك هيك
+
+503
+00:45:07,900 --> 00:45:11,560
+هيك هيك هيك هيك هيك هيك هيك هيك هيك هيك هيك هيك
+
+504
+00:45:11,560 --> 00:45:18,080
+هيك هيك هيك
+
+505
+00:45:29,740 --> 00:45:38,460
+بارضه، رأيي صارت بدخلعة ودنيا جماعة الخير No
+
+506
+00:45:38,460 --> 00:45:43,740
+attribute
+
+507
+00:45:43,740 --> 00:45:53,160
+recall underscore score أو
+
+508
+00:45:53,160 --> 00:45:53,840
+الـ F major
+
+509
+00:46:04,040 --> 00:46:10,680
+F1 equal matrix F1
+
+510
+00:46:10,680 --> 00:46:18,160
+underscore F1
+
+511
+00:46:21,880 --> 00:46:26,800
+أخر شغلة، أنا ممكن أجيب كل الـValues مع بعضها من
+
+512
+00:46:26,800 --> 00:46:31,520
+خلال شغلة نسميها الـClassification Report
+
+513
+00:46:31,520 --> 00:46:37,800
+الـClassification Report ممكن يساعدني بشكل كتير
+
+514
+00:46:37,800 --> 00:46:41,520
+بحيث أنه أنا محتاجش أن أكتب كل حاجة مع بعضها
+
+515
+00:46:41,520 --> 00:46:45,400
+Classification
+
+516
+00:46:45,400 --> 00:46:45,900
+Report
+
+517
+00:46:50,530 --> 00:46:57,750
+أو الـ CLS underscore report بيساوي matrix dot
+
+518
+00:46:57,750 --> 00:47:01,430
+classification
+
+519
+00:47:01,430 --> 00:47:10,310
+underscore report بدي أدّيله الـ method أو عفوًا
+
+520
+00:47:10,310 --> 00:47:14,010
+الـ to function أو أزوده بالـ predicted بالـ to
+
+521
+00:47:14,010 --> 00:47:18,670
+label والـ predicted label وحروح أقول له هانطبع
+
+522
+00:47:18,670 --> 00:47:19,890
+ليه ال classifier
+
+523
+00:47:23,050 --> 00:47:26,830
+«Reclassification Report» وهنا جاب لي الرابورت
+
+524
+00:47:26,830 --> 00:47:32,290
+الكامل بدأ بالـ «Precision» والـ «Recall» والـ «F
+
+525
+00:47:32,290 --> 00:47:36,090
+Score» أي القيم التلاتة اللي موجودة عندها للـ
+
+526
+00:47:36,090 --> 00:47:41,470
+«Class» طبعاً لل «Class Zero» لأن الـ «Record»
+
+527
+00:47:41,470 --> 00:47:45,430
+لازم يبين كل القيم لازم يبين كل حاجة الآن الـ
+
+528
+00:47:45,430 --> 00:47:51,210
+«Recall» هيالـ Precision
+
+529
+00:47:51,210 --> 00:47:55,870
+تلاتة و تمانين الـ Recall تسعة و سمعين الـ F-score
+
+530
+00:47:55,870 --> 00:48:07,230
+والـ Accuracy وينها؟ ليش هي كتر داخلات مع بعض؟
+
+531
+00:48:15,290 --> 00:48:21,970
+الـ Accuracy بشكل عام هي 73 لماذا
+
+532
+00:48:21,970 --> 00:48:26,930
+72.72؟ هنا في الـ robot عمل الـ Roundation أو
+
+533
+00:48:26,930 --> 00:48:32,090
+القيم اللي موجودة عندك هنا فهي فعليا 72.72 فبعمل
+
+534
+00:48:32,090 --> 00:48:34,950
+الـ Roundation الآن الـ Recall الـ Zero زي ما قلنا
+
+535
+00:48:34,950 --> 00:48:38,090
+6.7 الـ Precision والـ Recall الـ Class الأول
+
+536
+00:48:43,190 --> 00:48:49,230
+هي ال class number one لما
+
+537
+00:48:49,230 --> 00:48:56,040
+قلت له احسب ال precision جالي 66هذه هي تقريبًا الـ
+
+538
+00:48:56,040 --> 00:49:03,800
+55.كذا الـ Z الـ 56 الـ recall اللي هي 55.8 بعملها
+
+539
+00:49:03,800 --> 00:49:10,240
+تقريبًا ال F score اللي كانت بتمثل الـ 60 تمام؟
+
+540
+00:49:10,240 --> 00:49:13,960
+وال support لل values اللي موجودة عندها فهي في ال
+
+541
+00:49:13,960 --> 00:49:16,880
+report هذا أنا جيبت كل ال values بالنسبة لي لمرة
+
+542
+00:49:17,890 --> 00:49:23,690
+واحدة، بتمنى يكون الفيديو هذا يوضحلكم فعليًا إيش
+
+543
+00:49:23,690 --> 00:49:27,590
+أنا محتاج في ال classification طبعًا هذا الكلام
+
+544
+00:49:27,590 --> 00:49:32,170
+بده يتطبق مع كل data set أو مع كل classification
+
+545
+00:49:32,170 --> 00:49:36,630
+model وكل classification model فيه خاصية معينة،
+
+546
+00:49:36,630 --> 00:49:40,210
+يمكن يكون الشغل الوحيد الآن في الاختلاف عندكم اللي
+
+547
+00:49:40,210 --> 00:49:42,770
+هي استدعاء ال classifierباريخ الاستفعال الـ
+
+548
+00:49:42,770 --> 00:49:47,870
+Classifier بينما الـ Fit حتظل ثابت للجميع، الـ
+
+549
+00:49:47,870 --> 00:49:51,270
+Predict حتظل ثابت للجميع، والـ Measurement حتظل
+
+550
+00:49:51,270 --> 00:49:56,590
+موجودة لكل العناع، لكل ال Classifiers بنفس
+
+551
+00:49:56,590 --> 00:50:00,910
+الكيفية، أنا هيك خلصت، بتمنى إن شاء الله تعالى
+
+552
+00:50:04,250 --> 00:50:07,330
+بأتمنى على الله تبارك وتعالى أن أكون فعليًا وفقة
+
+553
+00:50:07,330 --> 00:50:10,850
+اللي لان خلال التسجيل السابق أن أنا أوضحكم موضوع
+
+554
+00:50:10,850 --> 00:50:16,390
+الـ Classification ومن خلاله استخدمت الـ Canary
+
+555
+00:50:16,390 --> 00:50:20,370
+Snapper واستخدمت الـ Kaggle كـ Tool مختلفة عن الـ
+
+556
+00:50:20,370 --> 00:50:24,770
+IPython في الـ Local Machine الموجودة عندي إذا في
+
+557
+00:50:24,770 --> 00:50:29,270
+أي سؤال حضروله لـ Next Sessionالـ Online Session
+
+558
+00:50:29,270 --> 00:50:33,690
+of the Discussion أعلى وعسى أننا نقدر أن نتوفيك
+
+559
+00:50:33,690 --> 00:50:36,530
+دائمًا وأبداً والسلام عليكم ورحمة الله وبركاته
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9N2D6-T56oQ.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9N2D6-T56oQ.srt
new file mode 100644
index 0000000000000000000000000000000000000000..ff10f947aaed07ff4f38c864e5bffb0978cda027
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9N2D6-T56oQ.srt
@@ -0,0 +1,1717 @@
+1
+00:00:00,000 --> 00:00:03,180
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:03,180 --> 00:00:06,300
+أهلا وسهلا بكم في الدرس الثاني من الـ chapter
+
+3
+00:00:06,300 --> 00:00:10,140
+clustering. كنا في التسجيل السابق تكلمنا عن الـ
+
+4
+00:00:10,140 --> 00:00:12,640
+clustering بشكل عام، وقلت إنّ الـ clustering هي عبارة عن
+
+5
+00:00:12,640 --> 00:00:17,820
+تقسيم الـ data set إلى مجموعات محددة عددها مسبقا
+
+6
+00:00:17,820 --> 00:00:22,870
+بناء على تقارب أو تشابه الـ instances الموجودة
+
+7
+00:00:22,870 --> 00:00:27,250
+في الـ data set. يعني، وكنا خلصنا في
+
+8
+00:00:27,250 --> 00:00:29,990
+نهاية المحاضرة أنّنا فعلنا... أو في نهاية التسجيل
+
+9
+00:00:29,990 --> 00:00:35,410
+عفوا، أنّنا فعليًا الـ... الـ clustering واحد من
+
+10
+00:00:35,410 --> 00:00:39,130
+اثنين: إما partition clustering أو hierarchical
+
+11
+00:00:39,130 --> 00:00:42,110
+clustering. فالـ partition clustering يعني أنّ
+
+12
+00:00:42,110 --> 00:00:44,110
+أنا بتكون الـ groups أو المجموعات اللي عندي
+
+13
+00:00:44,110 --> 00:00:47,690
+disjoint، ما فيش بينها overlap، ما فيش
+
+14
+00:00:47,690 --> 00:00:52,660
+بينهم تقاطع في العناصر. يعني كل element موجود في
+
+15
+00:00:52,660 --> 00:00:55,660
+مجموعة واحدة فقط. لكن بالـ hierarchical clustering،
+
+16
+00:00:55,660 --> 00:00:58,540
+لما أنا بيكون عندي hierarchical tree أو عندي
+
+17
+00:00:58,540 --> 00:01:01,000
+hierarchy معينة، بيصير فيه ممكن الـ
+
+18
+00:01:01,000 --> 00:01:05,380
+element ينتمي لأكثر من cluster. تماما مثل
+
+19
+00:01:05,380 --> 00:01:09,620
+علاقة الأعداد أو المجموعات، الأرقام مع بعضها. اليوم
+
+20
+00:01:09,620 --> 00:01:13,100
+إن شاء الله تعالى، زي ما إحنا متفقين، إنّنا هنبلش في
+
+21
+00:01:13,100 --> 00:01:19,190
+موضوع الـ partitional clustering. طبعًا لما أتكلم على
+
+22
+00:01:19,190 --> 00:01:27,050
+الـ partition clustering، يعني أنّني أتكلم على...
+
+23
+00:01:27,050 --> 00:01:31,110
+عفوا، تمام.
+
+24
+00:01:31,110 --> 00:01:32,030
+أنا أريد الـ pointer.
+
+25
+00:01:34,890 --> 00:01:37,510
+عندما أتكلم عن الـ partitional clustering، يعني
+
+26
+00:01:37,510 --> 00:01:42,010
+أنّني أبحث عن الـ natural groups للـ components
+
+27
+00:01:42,010 --> 00:01:45,390
+الموجودة عندي على الـ data الموجودة، بناء على
+
+28
+00:01:45,390 --> 00:01:50,110
+تشابه معين، أو بعض التشابه في العناصر الموجودة
+
+29
+00:01:50,110 --> 00:01:54,890
+عندها. وبالتالي الـ cluster هنا في الـ partitional
+
+30
+00:01:54,890 --> 00:01:58,390
+clustering، أنا بأجمع العناصر زي ما قلنا، مجموعات أو
+
+31
+00:01:58,390 --> 00:02:00,930
+توزيع طبيعي، أو أبحث عن توزيع طبيعي للـ data بحيث
+
+32
+00:02:00,930 --> 00:02:06,420
+أن يكون عند كل element موجود في مجموعة واحدة، وفي
+
+33
+00:02:06,420 --> 00:02:09,900
+نفس
+
+34
+00:02:09,900 --> 00:02:14,960
+الوقت. الـ clustering algorithm بيديني الـ
+
+35
+00:02:14,960 --> 00:02:20,080
+centroid أو النقطة الأساسية التي تمثل مركز الـ
+
+36
+00:02:20,080 --> 00:02:24,860
+cluster، أو بتمثل المركز تبع الـ cluster الموجودة
+
+37
+00:02:24,860 --> 00:02:29,260
+عندها. مركز الـ cluster أو المجموعة الموجودة
+
+38
+00:02:29,260 --> 00:02:35,460
+عندها، عشان أحدد عضوية الـ cluster. هذا يعني أنا زي
+
+39
+00:02:35,460 --> 00:02:40,140
+ما قلنا سابقا، هي عبارة عن مجموعات معروفة مسبقا
+
+40
+00:02:40,140 --> 00:02:51,760
+يعني، واحد، اثنين، ثلاث مجموعات، مجرد ترقيم
+
+41
+00:02:51,760 --> 00:02:58,800
+مجرد اسم للمجموعة. عشان هيك أنا بحدد عضوية
+
+42
+00:02:58,800 --> 00:03:04,840
+المجموعات. الـ algorithm بياخد الـ data points اللي
+
+43
+00:03:04,840 --> 00:03:10,210
+موجودة عندي هنا، وبحسب المسافة بينهم وبين
+
+44
+00:03:10,210 --> 00:03:12,690
+الـ centroid الموجودة عندها. طيب الـ centroid اللي هي
+
+45
+00:03:12,690 --> 00:03:15,110
+الـ centers اللي اتفقنا عليها، مش موجودة عندي أول
+
+46
+00:03:15,110 --> 00:03:18,510
+مرة، بياخدها بشكل عشوائي، وبروح بأجمع يعني بروح
+
+47
+00:03:18,510 --> 00:03:23,190
+بياخد مجموعة. طبعًا الآن في عندي المجموعة بتكون شاغلة
+
+48
+00:03:23,190 --> 00:03:27,010
+لما يكون فيها على الأقل عنصر واحد. فإيش هو بروح
+
+49
+00:03:27,010 --> 00:03:30,690
+بفترض، بروح بفترض أنّ كل مجموعة بتبدأ بعنصر واحد
+
+50
+00:03:30,690 --> 00:03:34,430
+اللي هو بمثل الـ center، وبصير بعد ذلك يدور على
+
+51
+00:03:36,540 --> 00:03:39,920
+عضوية المجموعات، على قرب الـ element من الـ
+
+52
+00:03:39,920 --> 00:03:42,800
+center. هذا كلّ مكان قريب للـ center من التلاتة هدول،
+
+53
+00:03:42,800 --> 00:03:45,880
+فهو بيتمّ إلى المجموعة اللي بتمثلها الـ center اللي
+
+54
+00:03:45,880 --> 00:03:50,500
+موجودة عندها. والـ output طبعًا من الـ algorithm هذا
+
+55
+00:03:50,500 --> 00:03:55,170
+هي عبارة عن عملية description أو statistical
+
+56
+00:03:55,170 --> 00:03:59,670
+description، وصف إحصائي للـ data set الموجودة. مين هو
+
+57
+00:03:59,670 --> 00:04:03,490
+الـ centroid، وإيش هي البيانات اللي موجودة عليه، وإيش
+
+58
+00:04:03,490 --> 00:04:07,890
+هي البيانات اللي موجودة في داخل الـ clusters الـ
+
+59
+00:04:07,890 --> 00:04:11,470
+cluster الموجودة عندها. طبعًا لما أنا بأتكلم إنّه
+
+60
+00:04:11,470 --> 00:04:14,450
+في عندنا الـ k-means clustering algorithm، من أشهر الـ
+
+61
+00:04:14,450 --> 00:04:17,390
+algorithms وأبسطها في الفهم، واللي بيستخدم مع الـ
+
+62
+00:04:17,390 --> 00:04:22,040
+cluster. طبعًا الـ k عدد المجموعات اللي نتكلم عليه، والـ means
+
+63
+00:04:22,040 --> 00:04:25,820
+المقصود فيه المتوسط الحسابي للنقاط الموجودة
+
+64
+00:04:25,820 --> 00:04:33,240
+عندها. الـ... طبعًا قلنا أبسط algorithm وهو الأكثر
+
+65
+00:04:33,240 --> 00:04:36,880
+استخدامًا في عملية الـ clusterings الموجودة، بدور على
+
+66
+00:04:36,880 --> 00:04:40,960
+center. بيجتهد الـ algorithm أو الـ algorithm بيحاول
+
+67
+00:04:40,960 --> 00:04:46,300
+يدور على centers، وبالـ center هذا بمثل نقطة معينة
+
+68
+00:04:46,300 --> 00:04:50,380
+بتمثل الـ cluster، وبضلّ يعيد في العملية الموجودة
+
+69
+00:04:50,380 --> 00:04:54,360
+عندي. هم عبارة عن خطوات، زي ما قلنا، بروح بأخذ
+
+70
+00:04:54,360 --> 00:04:59,260
+center، والـ center هذا بروح بجيب العناصر، بشوف من
+
+71
+00:04:59,260 --> 00:05:02,540
+العناصر القريبة منه، بحسب المسافة. يعني لو أنا قلت له في
+
+72
+00:05:02,540 --> 00:05:06,500
+عندي مثلًا أربع مجموعات، معناته في عندي أربع نقاط
+
+73
+00:05:06,500 --> 00:05:09,900
+رئيسية، أربع نقاط مركزية اللي هي الـ centers تبع الـ
+
+74
+00:05:09,900 --> 00:05:12,860
+clusters، المجموعات اللي عندي، وعليها ببدأ يشتغل
+
+75
+00:05:12,860 --> 00:05:14,660
+الآن الـ algorithm هذا بضلّ
+
+76
+00:05:19,120 --> 00:05:27,820
+يتكرر بتكرر في عمليتين: الأولى، بروح بخصص كل data
+
+77
+00:05:27,820 --> 00:05:33,420
+point للـ cluster center. يعني الآن، المفروض، تبعًا
+
+78
+00:05:33,420 --> 00:05:37,580
+لهذه، بروح بحدد قرب، أو بعض العناصر، أو شبه
+
+79
+00:05:37,580 --> 00:05:43,180
+similarity، بحدد تشابه العناصر، الـ data instances مع
+
+80
+00:05:43,180 --> 00:05:48,220
+الـ centers الموجودة عندها. وبالتالي بروح بخصص لي
+
+81
+00:05:48,220 --> 00:05:52,060
+إيّاه للـ center الأقرب. ومن أجل تحقيق هذا الكلام، في
+
+82
+00:05:52,060 --> 00:05:55,140
+عندي distance function أو similarity function، اللي
+
+83
+00:05:55,140 --> 00:06:02,720
+عادة بنسميها distance. المفهوم distance أكثر في
+
+84
+00:06:02,720 --> 00:06:07,840
+الأرقام. الآن في الـ euclidean distance والـ
+
+85
+00:06:07,840 --> 00:06:10,360
+Manhattan distance، شفناهم سابقًا، وهنشوفهم الآن
+
+86
+00:06:10,360 --> 00:06:13,820
+كأن نذكر بعض فيهم: Jaccard، وSpearman، وSpearman
+
+87
+00:06:13,820 --> 00:06:17,680
+عفوا، والـ Hamming، والكوزاين. بعدين هي كده، لما بروح بدور
+
+88
+00:06:17,680 --> 00:06:21,860
+الـ algorithm بضلّ يكرر في العملية هذه، وبخصص الـ
+
+89
+00:06:21,860 --> 00:06:24,940
+instances للـ cluster، لما يكون في... لما يثبت
+
+90
+00:06:24,940 --> 00:06:28,000
+ويبطل يتغير، أو يصير فيه يعني تغيير على الـ data
+
+91
+00:06:28,000 --> 00:06:34,460
+الموجودة. بنذكر مع بعض الـ distance function أو
+
+92
+00:06:34,460 --> 00:06:39,880
+الـ similarity function، لما تكون الـ instance عبارة
+
+93
+00:06:39,880 --> 00:06:41,480
+عن مجموعة من الأرقام.
+
+94
+00:06:45,320 --> 00:06:47,560
+طبعًا اللي بنتكلم إحنا جالسين إنّ الـ distance
+
+95
+00:06:47,560 --> 00:06:49,860
+function هذه، أو الـ similarity function، سميناها
+
+96
+00:06:49,860 --> 00:06:53,780
+similarity أو distance function، لأنّ الـ... الـ...
+
+97
+00:06:53,780 --> 00:06:58,560
+لما أنا بدي أوصف rows، أو بدي أوصف أرقام قربها أو
+
+98
+00:06:58,560 --> 00:07:02,720
+بعضها من بعضها، أو تشابهها من بعضها، معناه أنّ أنا
+
+99
+00:07:02,720 --> 00:07:05,580
+جالس بأتكلم على نقاط. طبعًا لما أنا برسم الـ object
+
+100
+00:07:05,580 --> 00:07:10,120
+بتكون موجودة عندي في الـ space أو مرسومة عندي، حتماً
+
+101
+00:07:10,120 --> 00:07:13,900
+النقطتين المتقاربتين، المسافة اللي بينهم دليل على
+
+102
+00:07:13,900 --> 00:07:18,680
+تشابه العناصر الموجودة بينهم. طبعًا شوية شوية
+
+103
+00:07:18,680 --> 00:07:23,260
+هتصير الأمور بالنسبة لنا أفضل. لو أنا قلت لك في الـ
+
+104
+00:07:23,260 --> 00:07:25,600
+space هذا، على سبيل المثال، أو قلت لك في الـ space
+
+105
+00:07:25,600 --> 00:07:34,440
+هذا، قلت أنّ في نقطتين، هذه نقطة هنا ونقطة
+
+106
+00:07:34,440 --> 00:07:37,520
+هنا ونقطة هنا.
+
+107
+00:07:41,060 --> 00:07:48,240
+من أكثر نقطتين متشابهتين، أو بلاش، أقرب نقطتين لبعض
+
+108
+00:07:48,240 --> 00:07:53,720
+حتماً
+
+109
+00:07:53,720 --> 00:07:59,940
+النقطتين اللي بينهم الـ distance أصغر ما يمكن. طيب
+
+110
+00:07:59,940 --> 00:08:08,520
+لو أنا جدًّا قلت إنّ في عندي نقطة هنا (غير اللون بس)، لو
+
+111
+00:08:08,520 --> 00:08:09,820
+قلت إنّ في عندي نقطة هنا.
+
+112
+00:08:16,490 --> 00:08:19,670
+النقطة هذه أقرب لمين؟ لو أنا قلت لك هذه النقطة
+
+113
+00:08:19,670 --> 00:08:24,570
+تشبه مين؟ تشبه مين؟ ما فيش شبه. هذه نقطة موجودة في
+
+114
+00:08:24,570 --> 00:08:29,690
+الـ space، معناته أنا هروح أحسب مسافتها ومسافتها
+
+115
+00:08:29,690 --> 00:08:35,250
+والمسافة الأقصر هي بتمثل... هي بتكون أقرب لمين
+
+116
+00:08:35,250 --> 00:08:39,730
+للنقطة الموجودة عندها. طبعًا إحنا كلّنا بنعرف سابقًا
+
+117
+00:08:39,730 --> 00:08:44,770
+زي ما قلنا، الـ Manhattan والـ distance الموجودة عندنا. لو
+
+118
+00:08:44,770 --> 00:08:50,090
+أنا افترضت إنّ في عندي نقطتين، الـ X والـ Y، كانت 2
+
+119
+00:08:50,090 --> 00:08:54,410
+points، والـ 2 points هدول أنا بدي أحسب الـ distance
+
+120
+00:08:54,410 --> 00:08:57,510
+بينهم. لما أتكلم عن الـ Euclidean، أنا بأتكلم عن الجذر
+
+121
+00:08:57,510 --> 00:09:03,550
+التربيعي لمجموع مربعات الفروق ما بين مكونات
+
+122
+00:09:03,550 --> 00:09:06,450
+النقطتين اللي موجودة عندي.
+
+123
+00:09:09,550 --> 00:09:16,450
+وطبعًا كذلك الآن، مع الـ... بينما الـ Manhattan distance
+
+124
+00:09:16,450 --> 00:09:20,970
+هي عبارة عن مجموع القيم المطلقة للفروق ما بين
+
+125
+00:09:20,970 --> 00:09:24,270
+مكونات النقاط اللي موجودة عندنا.
+
+126
+00:09:26,900 --> 00:09:31,120
+وطبعًا، هي قلنا إحنا سابقًا إنّ أنا لما بأتكلم على
+
+127
+00:09:31,120 --> 00:09:36,820
+Manhattan، بأتكلم على الـ Euclidean، معناته بأتكلم على الخط
+
+128
+00:09:36,820 --> 00:09:40,200
+المستقيم اللي باللون الأخضر هذا، اللي هو بتطبيق
+
+129
+00:09:40,200 --> 00:09:43,840
+نظرية في الـ course، بين أي نقطتين. ولما بأتكلم على
+
+130
+00:09:43,840 --> 00:09:47,960
+الـ Manhattan ثاني، معناته بأتكلم على الأضلاع الموجودة
+
+131
+00:09:47,960 --> 00:09:53,860
+عندها. شكلي لما أخدت العناصر
+
+132
+00:09:57,090 --> 00:10:12,650
+ما عدّلتش الرسمة بتاعتي كده.
+
+133
+00:10:12,650 --> 00:10:13,030
+صح.
+
+134
+00:10:19,600 --> 00:10:26,360
+الآن لو أنا بدأت آخذ نظرة في gif file، الـ gif picture
+
+135
+00:10:26,360 --> 00:10:30,800
+اللي موجودة قدامي اللحظة، أنا بأتكلم على عشرة
+
+136
+00:10:30,800 --> 00:10:34,180
+iterations. أنا بدأت من iteration رقم واحد، اثنين،
+
+137
+00:10:34,180 --> 00:10:38,160
+ثلاثة، أربعة، ولاحظوا معايا إنّ المربعات هذه هي الـ
+
+138
+00:10:38,160 --> 00:10:41,920
+centers أو الـ centroids للـ clusters. أنا بأقول أجمع الـ
+
+139
+00:10:41,920 --> 00:10:45,200
+data لأربع مجموعات، والـ data هذه كلّها مختلطة مع
+
+140
+00:10:45,200 --> 00:10:49,420
+بعضها. بدأت الآن، بناء على الـ centers، الألوان تتوجه
+
+141
+00:10:49,420 --> 00:10:53,700
+مع بعض مع كل iteration. وهذا فعليًا اللي بيسويه الـ k-
+
+142
+00:10:53,700 --> 00:10:59,170
+means، إنّه بياخد random center في الأول، وبعدها بيحسب
+
+143
+00:10:59,170 --> 00:11:02,210
+الـ distance بين الـ centers هذه وكل النقاط اللي
+
+144
+00:11:02,210 --> 00:11:06,950
+موجودة، وكل نقطة بتصنف مع الـ center بناء على
+
+145
+00:11:06,950 --> 00:11:10,610
+shortest distance أو الـ similarity function اللي
+
+146
+00:11:10,610 --> 00:11:15,350
+إحنا بنعرفها. كصورة ثابتة، هي الـ data set، روحت قلت له
+
+147
+00:11:15,350 --> 00:11:18,990
+أجمع لي إيّاهم لمجموعات، فراح أخذ ثلاث مجموعات طبعًا
+
+148
+00:11:18,990 --> 00:11:23,270
+هنا، اللي هي أخذت المثلثات، هتمثل three different
+
+149
+00:11:23,270 --> 00:11:27,970
+centers. أيّهم، حتى لو كان، لأنّ الـ selection الأولى للـ
+
+150
+00:11:27,970 --> 00:11:31,170
+centers الأولية by random، حتى لو كانوا كلّهم
+
+151
+00:11:31,170 --> 00:11:35,210
+موجودين مع بعض، ما فيش غير إنّه بيشتغل في الـ... لو اجوا
+
+152
+00:11:35,210 --> 00:11:38,220
+كلّهم في نفس الـ center، ما عندي مشكلة، لأنّه بعد ذلك
+
+153
+00:11:38,220 --> 00:11:44,220
+سيقوم باختيار الـ average أو الـ mean تبعتهم. فقال
+
+154
+00:11:44,220 --> 00:11:47,440
+ليّ، هذه الـ data. افترض في الـ initialization زي ما
+
+155
+00:11:47,440 --> 00:11:50,820
+قلنا، هي بياخد الـ random centers، three centers، حسب
+
+156
+00:11:50,820 --> 00:11:55,980
+المطلوب by random، وراح يبدأ يخصص المجموعات، فراح يبدأ
+
+157
+00:11:55,980 --> 00:11:56,440
+يحسب.
+
+158
+00:12:01,830 --> 00:12:04,830
+اللي قلنا أنّنا هنعمل initialization، حدّد الـ three
+
+159
+00:12:04,830 --> 00:12:09,710
+centroids أو الـ three centers by random، وبعد هيك
+
+160
+00:12:09,710 --> 00:12:13,130
+بدأ يخصص النقاط بناء على الـ distance. طبعًا يا جماعة،
+
+161
+00:12:13,130 --> 00:12:16,210
+الخير، لما أنا بدي آجي أتكلم، النقطة high، أو النقطة
+
+162
+00:12:16,210 --> 00:12:22,490
+high distance هنا، وهأحسبها مع هنا، وهأحسبها مع
+
+163
+00:12:22,490 --> 00:12:31,520
+هنا، وهأصنفها لأقرب center، لأقصر مسافة. وبالتالي،
+
+164
+00:12:31,520 --> 00:12:35,000
+الأحمر هنا، صارت هذه كل النقاط، طبعًا هذه النقاط هي
+
+165
+00:12:35,000 --> 00:12:37,680
+أقرب للأخضر، وهذه للأزرق. فضلًا في الـ iteration
+
+166
+00:12:37,680 --> 00:12:43,670
+الثانية. الآن في الخطوة التالية، هنسوي، هيتحدد
+
+167
+00:12:43,670 --> 00:12:48,470
+الأحمر كله، الأزرق. فرح يحسب المتوسط لكل النقاط
+
+168
+00:12:48,470 --> 00:12:51,770
+اللي باللون الأخضر، المتوسط لكل النقاط اللي بالأحمر،
+
+169
+00:12:51,770 --> 00:12:55,830
+المتوسط لكل النقاط اللي بالأزرق الداكن. بينحسب
+
+170
+00:12:55,830 --> 00:12:58,870
+يعني، بيحسب الـ mean لكل الـ cluster بشكل مستقلّ،
+
+171
+00:12:58,870 --> 00:13:02,610
+والمتوسط هذا هو، بياخده centroid للـ next
+
+172
+00:13:02,610 --> 00:13:06,750
+iteration. recompute الـ center، هي حسب الـ center من
+
+173
+00:13:06,750 --> 00:13:12,020
+جديد. وراح إيش؟ بدأ reassigning، بدأ يروح يعمل الـ
+
+174
+00:13:12,020 --> 00:13:15,780
+center ثاني، وبعدها بيحسب، بعد ما يخلص بيحسب الـ
+
+175
+00:13:15,780 --> 00:13:19,640
+center كمان مرة، وبروح بخصص النقاط، وبحسب الـ
+
+176
+00:13:19,640 --> 00:
+
+223
+00:17:24,250 --> 00:17:30,690
+أربعة ل .. أربعة
+
+224
+00:17:30,690 --> 00:17:33,830
+ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل ..
+
+225
+00:17:33,830 --> 00:17:33,990
+ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل ..
+
+226
+00:17:33,990 --> 00:17:34,930
+أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة
+
+227
+00:17:34,930 --> 00:17:35,370
+ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل ..
+
+228
+00:17:35,370 --> 00:17:35,430
+أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة
+
+229
+00:17:35,430 --> 00:17:36,570
+ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل ..
+
+230
+00:17:36,570 --> 00:17:38,710
+أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة
+
+231
+00:17:38,710 --> 00:17:39,850
+ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل ..
+
+232
+00:17:39,850 --> 00:17:44,650
+أربعة ل .. أربعة ل ..
+
+233
+00:17:44,650 --> 00:17:49,210
+أربعة
+
+234
+00:17:49,210 --> 00:17:55,680
+لبأوقف و ببطل الشغل لما فعليا الـ cluster أو الـ
+
+235
+00:17:55,680 --> 00:18:01,100
+center بعد هيك تثبت لماذا؟ إذا ثبتت الـ cluster أو الـ
+
+236
+00:18:01,100 --> 00:18:03,640
+الـ center اللي موجودة عندي هنا معناته أنا ما فيش
+
+237
+00:18:03,640 --> 00:18:08,180
+عندي تليير بعد هيك بنجوسينت صار فيه ثبات و هيك صار
+
+238
+00:18:08,180 --> 00:18:11,340
+في عندي كل نقطة موجودة في الـ cluster الحقيقي اللي
+
+239
+00:18:11,340 --> 00:18:14,660
+موجود عندك وبعد هيك ستكون كل iteration على الفاضي
+
+240
+00:18:15,590 --> 00:18:17,970
+لماذا؟ لأن الـ Center لم يتغير بمعنى التوزيع كما
+
+241
+00:18:17,970 --> 00:18:22,910
+هو و هذه هي آخر توزيع أحصل عليها طيب، تعالى نطبق
+
+242
+00:18:22,910 --> 00:18:26,990
+نفس المثال لكن مع more dimensions في الـ 2D بقول أنا
+
+243
+00:18:26,990 --> 00:18:31,710
+فيه عندي data set مكونة من تمام نقاط اللي بتجسمهم
+
+244
+00:18:31,710 --> 00:18:35,730
+لـ three clusters باعتماد على الـ manhattan distance
+
+245
+00:18:35,730 --> 00:18:42,570
+هذه النقاط اللي موجودة عندها طيب،
+
+246
+00:18:42,570 --> 00:18:49,280
+by random؟ لازم أختار center أخذنا اتنين و عشرة و
+
+247
+00:18:49,280 --> 00:18:53,580
+أخذنا خمسة و ثمانية و أخذنا واحد و اتنين بينفع
+
+248
+00:18:53,580 --> 00:18:56,600
+الثلاثه تكون ورا بعض بينفع random الكلام random
+
+249
+00:18:56,600 --> 00:19:02,320
+جماعة الخير و بدك تشتغل و تشتغل الـ distance زي ما
+
+250
+00:19:02,320 --> 00:19:05,640
+قلنا هي بتقعد تتكلم و تقول أنت ما تستخدم الـ manhattan
+
+251
+00:19:05,640 --> 00:19:13,370
+الـ manhattan distance، المعرفة=المجموع .. المجموع القيم
+
+252
+00:19:13,370 --> 00:19:19,270
+المطلقة للفرقات بين عناصر النقاط اللي موجودة عندي
+
+253
+00:19:19,270 --> 00:19:24,330
+أسهل حاجة هيك أن أنا أروح أنشئ جدول بالشكل هذا هي
+
+254
+00:19:24,330 --> 00:19:28,230
+الـ data point اللي عندي و هي الـ initial centers
+
+255
+00:19:28,230 --> 00:19:36,450
+centers C1 وC2 وC3 طيب الآن بدي أروح أحسب الـ distance
+
+256
+00:19:36,450 --> 00:19:43,430
+صفر ناقص اثنين، ناقص اثنين، صفر زائد عشرة ناقص عشرة، صفر صفر
+
+257
+00:19:43,430 --> 00:19:51,230
+اثنين ناقص خمسة، ثلاثة زائد عشرة ناقص اثنين، عشرة ناقص
+
+258
+00:19:51,230 --> 00:19:58,990
+ثمانية، اثنين يعني مجموع خمسة، اثنين ناقص واحد، واحد
+
+259
+00:19:58,990 --> 00:20:02,530
+زائد عشرة ناقص اثنين، ثمانية
+
+260
+00:20:05,340 --> 00:20:11,700
+الآن مباشرة بقدر أقرر أن هذا أقصر distance موجودة
+
+261
+00:20:11,700 --> 00:20:15,460
+اللي هي الصفر معناته هذا أقرب ما يكون من الـ
+
+262
+00:20:15,460 --> 00:20:19,420
+cluster الرقم واحد من الـ center الأول فهو ينتمي لـ
+
+263
+00:20:19,420 --> 00:20:23,980
+الـ cluster الأول، نرجع الكرة مرة ثانية، اثنين ناقص
+
+264
+00:20:23,980 --> 00:20:30,000
+اثنين، صفر، خمسة ناقص عشرة، خمسة هي خمسة الآن اثنين
+
+265
+00:20:30,000 --> 00:20:37,850
+ناقص خمسة، ثلاثة، خمسة ناقص ثمانية، ثلاثة معناته ستة
+
+266
+00:20:37,850 --> 00:20:45,330
+2 -1 1 5-2 3 1 3 4 يعني الـ distance الأقصر هي عبارة
+
+267
+00:20:45,330 --> 00:20:48,630
+عن الأربعة فهذا أقرب ما يكون للـ cluster رقم
+
+268
+00:20:48,630 --> 00:20:56,310
+ثلاثة، مع كذلك هنا 8-2 6 4-10 6 طبعاً ليش أربعة ناقص
+
+269
+00:20:56,310 --> 00:20:58,870
+عشرة ستة لما نتكلم بالـ absolute value من هاتين
+
+270
+00:20:58,870 --> 00:21:03,640
+distance، ما تنسوا الـ distance الثانية سبعة، الـ
+
+271
+00:21:03,640 --> 00:21:07,900
+distance الثالثة تسعة، معناته أنا أقصر مسافة
+
+272
+00:21:07,900 --> 00:21:13,640
+تسعة، معناته في الـ cluster الثاني، خمسة صفر، لاحظوا
+
+273
+00:21:13,640 --> 00:21:16,620
+لأن الـ data set أو الـ centers أخذتها معي فلازم
+
+274
+00:21:16,620 --> 00:21:20,080
+تطلع معي صفر بشكل أو بآخر لأ في أي حسب الـ
+
+275
+00:21:20,080 --> 00:21:23,920
+center اللي موجود عندها، فلما حسبنا، تمام تمام، حسبنا
+
+276
+00:21:23,920 --> 00:21:31,360
+كل الـ distances، وزعنا الثمانية عناصر على الـ classes
+
+277
+00:21:31,360 --> 00:21:37,460
+اللي موجودة، يعني a1 في c1 من الـ cluster الأول، a2 و
+
+278
+00:21:37,460 --> 00:21:44,240
+a7 في الـ cluster الثالث، a3 و a4 و a5 و 6 و 8 في الـ
+
+279
+00:21:44,240 --> 00:21:50,120
+cluster الثاني، تمام، هذه التوزيع اللي عندي بناءً على
+
+280
+00:21:50,120 --> 00:21:55,100
+الـ clusters اللي موجودة عندها، إيش المطلوب مني الآن؟
+
+281
+00:21:55,100 --> 00:21:59,960
+المطلوب مني الآن أحسب الـ mean لكل cluster
+
+282
+00:22:03,450 --> 00:22:06,670
+يعني متوسط النقاط اللي في اللون الأسود في الـ
+
+283
+00:22:06,670 --> 00:22:10,530
+cluster الأول، هيهم بروح بجمع النقاط اللي بتاخد
+
+284
+00:22:10,530 --> 00:22:14,050
+واحد اللي في الـ cluster الأول و بحسب المتوسط
+
+285
+00:22:14,050 --> 00:22:17,730
+تبعها، ما فيش غير النقطة، معناته المتوسط تبعها مثل
+
+286
+00:22:17,730 --> 00:22:21,070
+ما هو، هذا الـ center ما تغيرش، اللي باللون الأزرق، هيهم
+
+287
+00:22:21,070 --> 00:22:28,650
+اثنين زائد اثنين زائد واحد، ثلاثة يعني واحد ونصف، خمسة، سبعة و
+
+288
+00:22:28,650 --> 00:22:32,550
+اثنين عفواً، سبعة يعني ثلاثة ونصف، هذا الـ center
+
+289
+00:22:32,550 --> 00:22:36,570
+الثالث، الـ center الثاني هيكون عبارة عن ثمانية
+
+290
+00:22:36,570 --> 00:22:41,930
+زائد خمسة، زائد سبعة، هي عشرين، وهي ستة، ستة و
+
+291
+00:22:41,930 --> 00:22:45,870
+عشرين هي ثلاثين، ثلاثين على واحد، اثنين، ثلاثة، أربعة
+
+292
+00:22:45,870 --> 00:22:53,500
+خمسة يعني ستة وثلاثين على خمسة، ستة و ايه في  ،  اندي هان
+
+293
+00:22:53,500 --> 00:23:03,800
+اثنا عشر، سبعة عشر، اثنين وعشرون، اثنا عشر
+
+294
+00:23:03,800 --> 00:23:08,200
+سبعة عشر، واحد وعشرون، ثلاثون برضه ستة وستة معناته
+
+295
+00:23:08,200 --> 00:23:12,260
+الـ new centers تبعتي أنا هتكون بعد الحسبة تبعتي
+
+296
+00:23:12,260 --> 00:23:19,780
+اثنين وعشرة، بالمتوسطات 6 6 1.5 3.5
+
+297
+00:23:22,880 --> 00:23:26,580
+centers لاحظوا أنا ما زلت ما تكلم من الـ first
+
+298
+00:23:26,580 --> 00:23:30,280
+iteration اللي موجودة عندي، الآن هاخد الـ new
+
+299
+00:23:30,280 --> 00:23:34,600
+centers هدول و أروح فيهم على الـ next iteration أو
+
+300
+00:23:34,600 --> 00:23:37,680
+الـ second iteration، هاي حطيت الـ centers اللي جديدة
+
+301
+00:23:37,680 --> 00:23:41,080
+اللي موجودة عندي هنا و بديت أحسب المسافة من جديد
+
+302
+00:23:41,080 --> 00:23:46,520
+بديت أحسب المسافة من جديد، وبنفس الكلام الآن بحسب
+
+303
+00:23:46,520 --> 00:23:49,720
+على الـ centers الجديدة مع كل row اللي موجود عندي
+
+304
+00:23:49,720 --> 00:23:54,400
+هنا و بأخذ،  لأ، مع نهاية العملية بروح بحسب الـ centers
+
+305
+00:23:54,400 --> 00:23:58,180
+بحسب الـ mean للـ centers اللي موجودة، هيصير في عندي
+
+306
+00:23:58,180 --> 00:23:59,340
+واحد و واحد
+
+307
+00:24:02,460 --> 00:24:07,000
+الآن صار في عندي واحد و واحد، هي اثنين، وأربعة، ستة
+
+308
+00:24:07,000 --> 00:24:12,380
+على اثنين، ثلاثة، عشرة أو تسعة، تسعة عشر، ثمانية و عفواً
+
+309
+00:24:12,380 --> 00:24:15,960
+تسعة ونصف، هذا الـ center الجديدة اللي هشتغل عليها
+
+310
+00:24:15,960 --> 00:24:19,160
+وبالتالي أنا هروح في iteration ثالثة لأن الـ
+
+311
+00:24:19,160 --> 00:24:22,060
+centers مختلفة تماماً عن الـ centers اللي موجودة
+
+312
+00:24:22,060 --> 00:24:26,040
+هترجع تعمل نفس الحسبة بنفس الكيفية لحد ما تثبت معك
+
+313
+00:24:26,270 --> 00:24:29,230
+للـ clusters اللي موجود عندك هنا، طبعاً في كل الـ
+
+314
+00:24:29,230 --> 00:24:32,430
+slide هذه تكتبها على ورقة أو تطبق عليها، وتطبقها، و
+
+315
+00:24:32,430 --> 00:24:34,970
+تجرب الـ center الثاني والثالث والرابع والـ
+
+316
+00:24:34,970 --> 00:24:41,310
+iteration، طبعاً متى بده يوقف؟ بده يوقف لما فعلياً يبطل
+
+317
+00:24:41,310 --> 00:24:47,950
+الـ center عندي يتغير، تمام، okay، طبعاً لأنه في مشكلة
+
+318
+00:24:47,950 --> 00:24:52,390
+أحياناً بالـ mean بتظهر معي لو كان في عندي الـ data
+
+319
+00:24:52,390 --> 00:24:57,440
+مش معمولة pre-processing صح، يعني في عندي outlier
+
+320
+00:24:57,440 --> 00:25:03,040
+زي هي، دي الآن لو أنا جيت قلت لك المتوسط الحسابي
+
+321
+00:25:03,040 --> 00:25:06,120
+اللي هدول، واحد وثلاثة وخمسة وسبعة وتسعة
+
+322
+00:25:06,120 --> 00:25:10,780
+هتقول لي okay، خمسة، لكن لو أنا قلت لك بدل التسعة
+
+323
+00:25:10,780 --> 00:25:16,660
+عندي ألف وتسعة، هيكون المتوسط الحسابي جدّيش؟ متسع و
+
+324
+00:25:16,660 --> 00:25:21,060
+خمسة، معناته الـ center تبعه هيكون بعيد جداً، الـ center
+
+325
+00:25:21,060 --> 00:25:25,100
+تبعي بعيد جداً، معناته يبعد عن نقطة الـ convergence
+
+326
+00:25:25,100 --> 00:25:33,440
+ممكن فعلياً يدينا نتيجة خطأ، أنت تخيّل أن الـ data
+
+327
+00:25:33,440 --> 00:25:39,480
+set  عبارة عن عشر مجموعات
+
+328
+00:25:39,480 --> 00:25:40,400
+عن مجموعات
+
+329
+00:25:53,650 --> 00:25:59,290
+هذه النقطة هي الـ 250، لما تكون هذه الـ center
+
+330
+00:25:59,290 --> 00:26:01,830
+فتأخذ هذه العناصر معها
+
+331
+00:26:04,130 --> 00:26:09,170
+لأنها الأقرب، لما تختار المتوسط سيصبح هنا وهنا و
+
+332
+00:26:09,170 --> 00:26:11,250
+هنا وهنا وهنا وهنا وهنا وهنا وهنا وهنا و
+
+333
+00:26:11,250 --> 00:26:13,170
+هنا وهنا وهنا وهنا وهنا وهنا وهنا وهنا و
+
+334
+00:26:13,170 --> 00:26:13,430
+هنا وهنا وهنا وهنا وهنا وهنا وهنا وهنا و
+
+335
+00:26:13,430 --> 00:26:14,550
+هنا وهنا وهنا وهنا وهنا وهنا وهنا وهنا و
+
+336
+00:26:14,550 --> 00:26:14,930
+هنا وهنا وهنا وهنا وهنا وهنا وهنا وهنا و
+
+337
+00:26:14,930 --> 00:26:15,310
+هنا وهنا وهنا وهنا وهنا وهنا وهنا وهنا و
+
+338
+00:26:15,310 --> 00:26:17,490
+هنا وهنا وهنا وهنا وهنا وهنا وهنا وهنا و
+
+339
+00:26:17,490 --> 00:26:20,790
+هنا وهنا وهنا وهنا وهنا وهنا وهنا و
+
+340
+00:26:20,790 --> 00:26:21,690
+هنا وهنا وهنا وهنا وهنا وهنا وهنا وهنا و
+
+341
+00:26:21,690 --> 00:26:21,710
+هنا وهنا وهنا وهنا وهنا وهنا وهنا وهنا و
+
+342
+00:26:21,710 --> 00:26:21,730
+هنا وهنا وهنا وهنا وهنا وهنا وهنا وهنا و
+
+343
+00:26:21,730 --> 00:26:32,670
+هنا وهنا وهنا وهنا و
+
+344
+00:26:32,670 --> 00:26:36,780
+هنا وهنا، الـ median زي ما احنا بنعرف سابقاً، ونفس
+
+345
+00:26:36,780 --> 00:26:40,720
+الخطوات السابقة بتظل عندها لكن بدل ما أحسب زي ما
+
+346
+00:26:40,720 --> 00:26:46,180
+قلت لك المتوسط أو المتوسط بحسب أو باخد القيمة الوسطية
+
+347
+00:26:46,180 --> 00:26:50,010
+اللي موجودة عندها أو الوسطية الحسابية، الـ mean
+
+348
+00:26:50,010 --> 00:26:52,950
+advantage تبع الـ median زي ما قلنا أنه
+
+349
+00:26:52,950 --> 00:26:55,930
+لا يتأثر بالـ extreme value أو بالـ outlier value
+
+350
+00:26:55,930 --> 00:27:00,650
+اللي موجودة هنا، السؤال اللي بيطرح نفسه الآن،  هل كل
+
+351
+00:27:00,650 --> 00:27:04,090
+شغلنا سابقاً كان مع أرقام،  ماذا لو كانت الـ data
+
+352
+00:27:04,090 --> 00:27:09,430
+اللي عندي عبارة عن binary، 0 و 1، 0 و 1، ده الـ data binary
+
+353
+00:27:09,430 --> 00:27:13,450
+يعني الآن عندي قيم 0 و 1، 0 و 1، معناته ممكن تكون في عند
+
+354
+00:27:13,450 --> 00:27:17,410
+القيم متشابهة ما بين الـ clusters، عشان هيك جالك لما
+
+355
+00:27:17,410 --> 00:27:19,930
+تكون الـ data binary اللي عندي أو الـ variable
+
+356
+00:27:19,930 --> 00:27:24,170
+اللي عندي كلها binary، ما أنفعش أروح أطبق عليها الـ
+
+357
+00:27:24,170 --> 00:27:28,310
+Euclidean أو الـ manhattan، لأ بيصير في عندي similarity
+
+358
+00:27:28,310 --> 00:27:32,610
+function أخرى لازم أتعامل معاها، وطبعاً هنا فعلياً
+
+359
+00:27:32,610 --> 00:27:36,350
+أنا بصير أبدأ أدوّر على الـ dissimilarity، احنا سابقاً
+
+360
+00:27:36,350 --> 00:27:39,150
+ذكرنا أن في عندي الـ Euclidean والـ Jacquard والـ
+
+361
+00:27:39,150 --> 00:27:44,770
+Sparsman والـ Hoffman code إلى آخره، لكن خليني
+
+362
+00:27:44,770 --> 00:27:50,390
+أتكلم احنا على الـ binary data، بصير أحسب الـ
+
+363
+00:27:50,390 --> 00:27:55,990
+dissimilarity، عدم التشابه، يعني أنا بعد ما أدوّر لكل
+
+364
+00:27:55,990 --> 00:28:04,310
+مكان، عدم التشابه، تمام، معناته التشابه عندها
+
+365
+00:28:04,310 --> 00:28:08,510
+صغير، وبالتالي أنا نفس الفكرة أن أنا بدوّر على الـ
+
+366
+00:28:08,510 --> 00:28:12,920
+smaller value دائماً عشان اتكلم عن أنه في شبه أو
+
+367
+00:28:12,920 --> 00:28:18,300
+ما فيش شبه، لكن زي ما قلنا أن أنا بتكلم على عدم
+
+368
+00:28:18,300 --> 00:28:25,620
+التشابه بشكل عام، لما بكون في عندي الـ data set أو
+
+369
+00:28:25,620 --> 00:28:31,540
+الـ point تبعتي فيها عبارة عن value من صفر لواحد، الـ
+
+370
+00:28:31,540 --> 00:28:34,840
+dissimilarity تبعتنا عبارة عن non-negative number
+
+371
+00:28:35,710 --> 00:28:42,510
+لما بيكون close to zero، معناته نقطتين قريبين جداً من
+
+372
+00:28:42,510 --> 00:28:46,710
+بعض أو متشابهات، والعكس كل ما زاد الرقم كل ما كبر
+
+373
+00:28:46,710 --> 00:28:52,450
+الرقم، معناته الرقمين هدول مختلفين عن بعض، يعني
+
+374
+00:28:52,450 --> 00:28:55,490
+هنلاحظ أني بقييس الاختلاف، الآن هنلاحظ أني بقييس
+
+375
+00:28:55,490 --> 00:28:58,650
+الاختلاف، كنت بقييس التشابه، والآن بدي أقييس
+
+376
+00:28:58,650 --> 00:29:04,560
+الاختلاف، اللي الآن من الـ matrix اللي ذكرناها
+
+377
+00:29:04,560 --> 00:29:07,260
+سابقاً اللي هي الـ Jaccard، بدك تفترض أنه أنا
+
+378
+00:29:07,260 --> 00:29:13,340
+فعلياً عندي data set مكونة من الـ object الأول
+
+379
+00:29:13,340 --> 00:29:19,060
+والـ object الثاني، عشان أنا آخد قيم الـ value الـ
+
+380
+00:29:19,060 --> 00:29:23,900
+binary value اللي موجودة، الآن بدأت أوزّع 0 و 1، الـ I و
+
+381
+00:29:23,900 --> 00:29:29,380
+الـ J، الـ I والـ J، A و B و C و D هذه العناصر اللي
+
+382
+00:29:29,380 --> 00:29:35,240
+بتمثل المصفوفة اللي عندي، لاحظوا أنا جمعت الـ B والـ
+
+383
+00:29:35,240 --> 00:29:35,660
+C
+
+384
+00:29:50,030 --> 00:29:54,350
+عشان نفهم الصورة صح ونشوف بالمثال يتضح المقال زي
+
+385
+00:29:54,350 --> 00:29:59,050
+ما بقول المثل، تعالى نروح نشتغل hand ونشوف إيش
+
+386
+00:29:59,050 --> 00:30:04,150
+العناصر اللي موجودة عندها، بيجي بقول، افترض أن هي
+
+387
+00:30:04,150 --> 00:30:08,790
+في عندي أنا الـ binary data، بدي أعملها partitioning
+
+388
+00:30:08,790 --> 00:30:12,930
+clusters، هذه بتمثل patient records، الـ records أو
+
+389
+00:30:12,930 --> 00:30:17,530
+الموجودين عندها، ما بين الـ positive والـ yes طبعاً
+
+390
+00:30:17,530 --> 00:30:22,610
+بتكلم على اسم الشخص، مش هدخل معايا حتماً في الحسبة
+
+391
+00:30:22,610 --> 00:
+
+445
+00:35:55,420 --> 00:35:59,840
+dissimilarity معناته أعلى تشابه، كلما كبرت ال
+
+446
+00:35:59,840 --> 00:36:02,540
+dissimilarity معناته الاختلاف بينهم كبير جداً
+
+447
+00:36:02,540 --> 00:36:07,540
+معناته أنا أكثر اتنين متشابهين أو أقرب اتنين لبعض
+
+448
+00:36:07,540 --> 00:36:14,380
+اللي هي من، جاك و ماري حسب الـ Jacquard computation
+
+449
+00:36:14,380 --> 00:36:17,180
+أو الـ Jacquard metric function اللي احنا بنتكلم
+
+450
+00:36:17,180 --> 00:36:22,180
+عليها، لإيه الدلالة؟ لاحظوا سابقاً كنت
+
+451
+00:36:22,180 --> 00:36:25,520
+أتكلم عن الـ distance أو الـ similarity distance أو
+
+452
+00:36:25,520 --> 00:36:29,240
+الـ distance function كنت أتَكلم عن الـ shortest
+
+453
+00:36:29,240 --> 00:36:31,780
+distance، بس الآن أتَكلم عن الـ shortest
+
+454
+00:36:31,780 --> 00:36:37,160
+dissimilarity طبعاً، و السيميلارتي لما أنا بدي الـ...
+
+455
+00:36:37,160 --> 00:36:40,320
+الـ...
+
+456
+00:36:40,320 --> 00:36:45,760
+...الـ... الآن هذه أكثر تشابه أو أقل اختلاف
+
+457
+00:36:45,760 --> 00:36:50,650
+بين Jack و Mary، لو أنا بدي أتَكلم عن التشابه، خذ واحد
+
+458
+00:36:50,650 --> 00:36:54,390
+ناقص، معناته كل ما بدي أزيد التشابه عنده، ما بدي
+
+459
+00:36:54,390 --> 00:36:59,930
+أصير فيه، وبالتالي بيصير فيني عند جاك وماري أكثر
+
+460
+00:36:59,930 --> 00:37:03,390
+اتنين متشابهين، المحتمل أنهم ياخدوا نفس المرض بناءً
+
+461
+00:37:03,390 --> 00:37:06,310
+على الـ data set يكون عندهم نفس المرض، لأن هذول أكثر
+
+462
+00:37:06,310 --> 00:37:10,210
+اتنين متقاربين في المحوصات وفي الأعراض اللي موجودة
+
+463
+00:37:10,210 --> 00:37:18,290
+عندنا، بينما جيم وماري أكثر اتنين مختلفين، وبالتالي
+
+464
+00:37:18,290 --> 00:37:22,510
+لا نعتقد أو ما فيش اعتقاد أنهم يكونوا من نفس المرض
+
+465
+00:37:22,510 --> 00:37:28,090
+أو منهم نفس المشكلة المرضية اللي عندهم، من اللي لو
+
+466
+00:37:28,090 --> 00:37:35,870
+بدنا نتكلم على المزايا وعيوب الـ K-Means، المزايا
+
+467
+00:37:35,870 --> 00:37:43,030
+simple، سهل أن أنا أفهمه، الـ item يتخصص بشكل تلقائي
+
+468
+00:37:43,030 --> 00:37:51,680
+لـ cluster، الـ disadvantages لازم تَتصنف، لازم تَتصنف
+
+469
+00:37:51,680 --> 00:37:54,720
+لازم
+
+470
+00:37:54,720 --> 00:37:57,060
+تَتصنف، لازم تَتصنف، لازم تَتصنف
+
+471
+00:38:00,680 --> 00:38:03,960
+الـ sensitive to outlier زي ما شفنا أن الـ
+
+472
+00:38:03,960 --> 00:38:08,060
+outlier بتغير الـ center، sensitive to initial seed
+
+473
+00:38:08,060 --> 00:38:11,780
+اللي هي الـ random center اللي في الأول، لو كانت
+
+474
+00:38:11,780 --> 00:38:14,520
+قريبة عندي، لو كانت في نص الـ... لو كانت هي الـ
+
+475
+00:38:14,520 --> 00:38:17,980
+center ممكن أوصل من أول iteration أو الثانية، لكن
+
+476
+00:38:17,980 --> 00:38:20,380
+لو كانت بعيدة، معناته هيأخد منه وقت في الـ
+
+477
+00:38:20,380 --> 00:38:26,660
+convergence لما يوصل لنهاية الحل، طبعاً صعبة، غير
+
+478
+00:38:26,660 --> 00:38:33,280
+مناسبة للي بيشوف الـ cluster من الـ hyper ellipsoid
+
+479
+00:38:33,280 --> 00:38:37,400
+أو الـ hyper shapers اللي راح يكون، لو ما كانتش الـ data
+
+480
+00:38:37,400 --> 00:38:41,680
+أو الـ data متواجدة بأشكال صعبة، مش هيشتغل عليها
+
+481
+00:38:41,680 --> 00:38:45,740
+طبعاً هنا بنتكلم أش... طبعاً الشغلة الأخيرة اللي هي
+
+482
+00:38:45,740 --> 00:38:49,040
+علاقة بالـ failure، فعلياً مش نقصيه، طب هو فعلاً بيفشل
+
+483
+00:38:49,040 --> 00:38:53,740
+تماماً، اللي
+
+484
+00:38:53,740 --> 00:38:58,300
+بيفشل إذا أنا فعلياً ما أديتوش رقم الـ cluster الحقيقي
+
+485
+00:38:58,300 --> 00:39:04,980
+أو المناسب للـ data set اللي موجود عندها، كذلك بيفشل
+
+486
+00:39:04,980 --> 00:39:06,140
+الـ...
+
+487
+00:39:11,460 --> 00:39:16,520
+أن كل cluster أو التعرف تبقى على الـ center لما
+
+488
+00:39:16,520 --> 00:39:19,300
+يكون عندك الـ center، يعني أنك تتكلم عن دائرة أو
+
+489
+00:39:19,300 --> 00:39:24,640
+مربع، طيب لو كان في عندك ghost أو curve أو أي shape
+
+490
+00:39:24,640 --> 00:39:30,080
+مختلف، إيش الـ center بدنا نفهمه؟ مش هيظبط، لأن لو
+
+491
+00:39:30,080 --> 00:39:35,120
+قلت لك في عندك شكل هلال، إيش الـ center تبعته؟ مش
+
+492
+00:39:35,120 --> 00:39:40,200
+هتظبط، لو أنا جيت قلت لك أن في عندي منحنى، إيش الـ
+
+493
+00:39:40,200 --> 00:39:43,620
+center تبع المنحنى؟ مش هتظبط، لكن ممكن أفهمها في
+
+494
+00:39:43,620 --> 00:39:48,640
+مثلث، أفهمها في دائرة، أفهمها في مستطيل، مستطيل أو
+
+495
+00:39:48,640 --> 00:39:53,700
+مربع، ممكن أفهمها في أشكال اللي موجودة عندك، تعالى
+
+496
+00:39:53,700 --> 00:39:59,160
+شوف هنا الآن، لما أنا روحت قلت له الـ... الـ... الـ...
+
+497
+00:40:01,580 --> 00:40:04,200
+لما تكون الـ data اللي عندها لها different
+
+498
+00:40:04,200 --> 00:40:12,340
+densities أو
+
+499
+00:40:12,340 --> 00:40:17,720
+كتابة مختلفة، الـ chemistry بيفشل، ليش؟ لأنه بيعتمد
+
+500
+00:40:17,720 --> 00:40:21,000
+على المسافة، فالآن هذا فعلياً الـ data، هذا الـ cluster
+
+501
+00:40:21,000 --> 00:40:24,980
+الحقيقي، هذا التوزيع، لكن لو أنا أجيت وقلت لك هذه
+
+502
+00:40:24,980 --> 00:40:27,920
+النقطة، هتصنفها مع أي cluster؟ لو أنا افترضت أن الـ
+
+503
+00:40:27,920 --> 00:40:28,440
+center هنا
+
+504
+00:40:31,160 --> 00:40:40,700
+و الـ center هنا، و الـ center هنا، فممكن
+
+505
+00:40:40,700 --> 00:40:47,480
+النقطة high تكون أقرب من هنا، فالنقطة
+
+506
+00:40:47,480 --> 00:40:53,040
+high هي أقرب لهذه، وبالتالي
+
+507
+00:40:53,040 --> 00:40:55,660
+لما يكون في عندي different densities، معناته أن في
+
+508
+00:40:55,660 --> 00:40:59,960
+عندي مشكلة مع الكيميا، كذلك عندما يكون لدي non
+
+509
+00:40:59,960 --> 00:41:04,820
+spherical cluster، تخيل أنه سيجلب لي cluster عندي، و
+
+510
+00:41:04,820 --> 00:41:10,780
+هاي الـ centers، أشتغل على three centers، هذول أريهم
+
+511
+00:41:10,780 --> 00:41:15,580
+كيف
+
+512
+00:41:15,580 --> 00:41:18,860
+بده يجيب لي إياها، أو عندما يكون لدي الـ complex shape
+
+513
+00:41:18,860 --> 00:41:22,120
+بالشكل هذا، سيقول هاي center عندي هنا، وهي center
+
+514
+00:41:22,120 --> 00:41:30,890
+هنا، أو هذا الـ distance صحيح، أو هنا، هل هذه النقطة
+
+515
+00:41:30,890 --> 00:41:34,530
+هي الأقرب لها؟ فهو الـ shape تبع الـ complex، فهذه
+
+516
+00:41:34,530 --> 00:41:37,910
+الحلقات كلها بيفشل فيها الـ K-means، طبعاً احنا فعلياً
+
+517
+00:41:37,910 --> 00:41:42,590
+في عندنا algorithm ثاني زي الـ DB scan، وهذا الـ
+
+518
+00:41:42,590 --> 00:41:48,370
+algorithm فعال جداً في التعامل مع الـ... ما بطلبش مني
+
+519
+00:41:48,370 --> 00:41:50,970
+عدد الـ K، وبيشتغل، وبحاول يتعرف على الـ complex
+
+520
+00:41:50,970 --> 00:41:56,230
+shape، لأنه بيعتمد على الـ density وبحاول يجد لها
+
+521
+00:41:57,020 --> 00:41:59,780
+يتعرف على الـ clusters بناءً على الـ density اللي
+
+522
+00:41:59,780 --> 00:42:03,560
+موجودة، لكن تبقى زي ما قلنا، هل الـ evaluation أو
+
+523
+00:42:03,560 --> 00:42:06,620
+التقييم تبعي تبع أداء الـ cluster صحيح أم لا بناءً
+
+524
+00:42:06,620 --> 00:42:09,680
+على أداء الـ clusters ومعرفة عدد الـ clusters
+
+525
+00:42:09,680 --> 00:42:13,230
+الحقيقية للـ data اللي موجودة، نشوفكم على خير إن شاء
+
+526
+00:42:13,230 --> 00:42:17,130
+الله تعالى، في المحاضرة هذه اتعرفنا على الـ K-means
+
+527
+00:42:17,130 --> 00:42:21,130
+وشفنا كيف نحسبه، واتعرفنا على مزاياه وعيوبه
+
+528
+00:42:21,130 --> 00:42:23,990
+التسجيل اللي جاي إن شاء الله تعالى، هنتقل للـ
+
+529
+00:42:23,990 --> 00:42:27,510
+Hierarchical Clustering، السلام عليكم ورحمة الله
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9N2D6-T56oQ_postprocess.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9N2D6-T56oQ_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..5151effacb08884ebecd6f510cf4de979a2a5352
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/9N2D6-T56oQ_postprocess.srt
@@ -0,0 +1,2116 @@
+1
+00:00:00,000 --> 00:00:03,180
+بسم الله والحمد لله و الصلاة والسلام علي رسول الله
+
+2
+00:00:03,180 --> 00:00:06,300
+أهلا وسهلا بكم في الدوس التاني من chapter ال
+
+3
+00:00:06,300 --> 00:00:10,140
+clustering كنا في التسجيل السابق تكلمنا عن ال
+
+4
+00:00:10,140 --> 00:00:12,640
+clustering بشكل عام وقلت ال clustering هي عبارة عن
+
+5
+00:00:12,640 --> 00:00:17,820
+تقسيم ال data set إلى مجموعات محددة عددها مسبقا
+
+6
+00:00:17,820 --> 00:00:22,870
+بناء على تقارب أو تشابهالـ instances اللي موجودة
+
+7
+00:00:22,870 --> 00:00:27,250
+في ال data set اللي موجودة يعنى وكنا خلصنا في
+
+8
+00:00:27,250 --> 00:00:29,990
+نهاية المحاضرة انه احنا فعل .. او في نهاية التسجيل
+
+9
+00:00:29,990 --> 00:00:35,410
+عفوا ان احنا فعليا ال .. ال clustering واحد من
+
+10
+00:00:35,410 --> 00:00:39,130
+اتنين اما partition ال clustering او hierarchical
+
+11
+00:00:39,130 --> 00:00:42,110
+clustering فال partition ال clustering معناته ان
+
+12
+00:00:42,110 --> 00:00:44,110
+انا بتكون ال groups او المجموعات اللي عندي
+
+13
+00:00:44,110 --> 00:00:47,690
+disjoint مافيش بينها او non overlapped مافيش في
+
+14
+00:00:47,690 --> 00:00:52,660
+بينهم تقاطعفي الاناصر يعني كل element موجود في
+
+15
+00:00:52,660 --> 00:00:55,660
+مجموعة واحدة فقط لكن بالـ Hierarchical Clustering
+
+16
+00:00:55,660 --> 00:00:58,540
+لما انا بكون في عنده Hierarchical Tree أو في عنده
+
+17
+00:00:58,540 --> 00:01:01,000
+Hierarchical معينة لأ بيصير في عنده ممكن ال
+
+18
+00:01:01,000 --> 00:01:05,380
+element اللي بينتمي لأكثر من cluster تماما مثل
+
+19
+00:01:05,380 --> 00:01:09,620
+علاقة الأعداد أو المجموعات الأرقام مع بعضها اليوم
+
+20
+00:01:09,620 --> 00:01:13,100
+ان شاء الله تعالى زي ما احنا متفقين انه هنبلش في
+
+21
+00:01:13,100 --> 00:01:19,190
+موضوع ال Partitional Clusteringطبعاً لما أتكلم على
+
+22
+00:01:19,190 --> 00:01:27,050
+الـ Partition & Clustering يعني أنني أتكلم على ..
+
+23
+00:01:27,050 --> 00:01:31,110
+عفوا تمام
+
+24
+00:01:31,110 --> 00:01:32,030
+أنا أريد الـ pointer
+
+25
+00:01:34,890 --> 00:01:37,510
+عندما أتكلم عن الـ Partitional Clustering يعني
+
+26
+00:01:37,510 --> 00:01:42,010
+أنني أبحث عن الـ Natural Groups للـ Components
+
+27
+00:01:42,010 --> 00:01:45,390
+اللي موجودة عندي على ال data اللي موجودة بناء على
+
+28
+00:01:45,390 --> 00:01:50,110
+تشابه معين أو بعض التشابه في العناصر اللي موجودة
+
+29
+00:01:50,110 --> 00:01:54,890
+عندها وبالتالي ال cluster هنا في ال Partitional
+
+30
+00:01:54,890 --> 00:01:58,390
+Clustering أنا أجسم العناصر زي ما قلنا مجموعات أو
+
+31
+00:01:58,390 --> 00:02:00,930
+توزيع طبيعي أو أبحث عن توزيع طبيعي لل data بحيث
+
+32
+00:02:00,930 --> 00:02:06,420
+أنه يكون عند كل element موجود في مجموعة واحدةوفي
+
+33
+00:02:06,420 --> 00:02:09,900
+نفس
+
+34
+00:02:09,900 --> 00:02:14,960
+الوقت، الـ Clustering Algorithm يدّيني الـ
+
+35
+00:02:14,960 --> 00:02:20,080
+Centroid أو النقطة الأساسية التي تتمثل مركز الـ
+
+36
+00:02:20,080 --> 00:02:24,860
+Centerأو بتمثل المركز تبعت ال cluster اللي موجود
+
+37
+00:02:24,860 --> 00:02:29,260
+عندها المركز ال cluster أو المجموعة اللي موجودة
+
+38
+00:02:29,260 --> 00:02:35,460
+عندها عشان أحدد العضوية ال cluster هذا يعني انا زي
+
+39
+00:02:35,460 --> 00:02:40,140
+ما قلنا سابقا هي عبارة عن مجموعات معروفة مسبقا
+
+40
+00:02:40,140 --> 00:02:51,760
+يعني واحدتلت مجموعات ترقيم
+
+41
+00:02:51,760 --> 00:02:58,800
+مجرد اسم للمجموعة عشان هيك انا بحدد عضوية
+
+42
+00:02:58,800 --> 00:03:04,840
+المجموعات ال algorithm بياخد ال data points اللي
+
+43
+00:03:04,840 --> 00:03:10,210
+موجودة عندى هنا وبحسب ال instances ما بينهموبين
+
+44
+00:03:10,210 --> 00:03:12,690
+الـ Centroid اللي موجودة عندها طب ال Centroid اللي
+
+45
+00:03:12,690 --> 00:03:15,110
+هي ال centers اللي اتفقنا عليها مش موجودة عندى اول
+
+46
+00:03:15,110 --> 00:03:18,510
+مرة بياخدها بشكل عشوائي و بروح بجسم يعنى بروح
+
+47
+00:03:18,510 --> 00:03:23,190
+بياخد مجموعة طبعا الان في عندى المجموعة بتكون شفاي
+
+48
+00:03:23,190 --> 00:03:27,010
+لما يكون فيها على الأقل عنصر واحد فإيش هو بروح
+
+49
+00:03:27,010 --> 00:03:30,690
+بفترض بروح بفترض ان كل مجموعة بتبدأ بعنصر واحد
+
+50
+00:03:30,690 --> 00:03:34,430
+اللي هو بمثل ال center و بصير بعد ذلك يدور على
+
+51
+00:03:36,540 --> 00:03:39,920
+العضوية المجموعات على قرب الـ element من الـ
+
+52
+00:03:39,920 --> 00:03:42,800
+center هذا كل مكان قريب ل center من التلاتة هدول
+
+53
+00:03:42,800 --> 00:03:45,880
+فهو بيتم ال مجموعة اللي بتمثلها ال center اللي
+
+54
+00:03:45,880 --> 00:03:50,500
+موجود عندها و ال output طبعا من ال algorithm هذا
+
+55
+00:03:50,500 --> 00:03:55,170
+هي عبارة عن عمليةdescription أو statistical
+
+56
+00:03:55,170 --> 00:03:59,670
+description وصف إحصائي لل data set الموجودة مين هو
+
+57
+00:03:59,670 --> 00:04:03,490
+ال centroid وإيش هي البيانات اللي موجودة عليه وإيش
+
+58
+00:04:03,490 --> 00:04:07,890
+هي البيانات اللي موجودة في داخل ال clusters ال
+
+59
+00:04:07,890 --> 00:04:11,470
+cluster اللي موجود عندها طبعاً لما أنا بتكلم انه
+
+60
+00:04:11,470 --> 00:04:14,450
+كي عند الكيمين ال cluster algorithm من أشهر ال
+
+61
+00:04:14,450 --> 00:04:17,390
+algorithm وأبسطها في الفهم في اللي استخدم مع ال
+
+62
+00:04:17,390 --> 00:04:22,040
+cluster طبعاً كي العددالذي نتكلم عليه و الـ means
+
+63
+00:04:22,040 --> 00:04:25,820
+المقصود فيه المتوسط الحسابي للنقاط اللي موجود
+
+64
+00:04:25,820 --> 00:04:33,240
+عندها ال .. طبعاً قلنا أبسط algorithm وهو الأكثر
+
+65
+00:04:33,240 --> 00:04:36,880
+استخدامه في عملية ال clusterings الموجودة بدور على
+
+66
+00:04:36,880 --> 00:04:40,960
+center يجتهد ال algorithm أو ال algorithm بحاول
+
+67
+00:04:40,960 --> 00:04:46,300
+يدور على centers و بال center هذا بمثلمطبقة معينة
+
+68
+00:04:46,300 --> 00:04:50,380
+بتمثل ال cluster و بضل يعيد في العملية اللى موجودة
+
+69
+00:04:50,380 --> 00:04:54,360
+عندى هن هم عبارة عن قطبتين زى ما قولنا بروح باخد
+
+70
+00:04:54,360 --> 00:04:59,260
+center و ال center هذا بروح بجيب العناص بشوف من
+
+71
+00:04:59,260 --> 00:05:02,540
+العناص القريبة منه لحسب عنه يعني لو انا قلتله في
+
+72
+00:05:02,540 --> 00:05:06,500
+عندي مثلا اربع مجموعات معناته في عندي اربع نقاط
+
+73
+00:05:06,500 --> 00:05:09,900
+رئيسية اربع نقاط مركزية اللى هى ال centers تبع ال
+
+74
+00:05:09,900 --> 00:05:12,860
+clusters المجموعات اللى عندي و عليها ببدأ يشتغل
+
+75
+00:05:12,860 --> 00:05:14,660
+الآن ال algorithm هذا بضل
+
+76
+00:05:19,120 --> 00:05:27,820
+يتكرر بتكرر في عمليتين الأولى بروح بخصص كل data
+
+77
+00:05:27,820 --> 00:05:33,420
+point لل cluster center يعني الآن المفروض تبعا
+
+78
+00:05:33,420 --> 00:05:37,580
+لهذه بروح بحدد قرب أو بعض العناصر أو شبه
+
+79
+00:05:37,580 --> 00:05:43,180
+similarity بحدد تشابه العناصر ال data instances مع
+
+80
+00:05:43,180 --> 00:05:48,220
+ال centers اللي موجودين عندهاوبالتالي بروح بخصصلي
+
+81
+00:05:48,220 --> 00:05:52,060
+إياها لل center الأقرب ومن أجل تحقيق هذا الكلام في
+
+82
+00:05:52,060 --> 00:05:55,140
+عندي distance function أو similarity function اللي
+
+83
+00:05:55,140 --> 00:06:02,720
+عادة بنسميها distance المفهوم distance أكثر في
+
+84
+00:06:02,720 --> 00:06:07,840
+الأرقامالان في الـ Included Distance و الـ
+
+85
+00:06:07,840 --> 00:06:10,360
+Manhattan Distance شوفناهم سابقاً و هنشوفهم الآن
+
+86
+00:06:10,360 --> 00:06:13,820
+كأن نذكر بعض فيهم جاكارد و Spearsman و Spearman
+
+87
+00:06:13,820 --> 00:06:17,680
+عفوا و الهامينج و الكوزاين بعد هي كد لما بروح بدور
+
+88
+00:06:17,680 --> 00:06:21,860
+ال algorithm بظل يكرر في العملية هذه و بخصص ال
+
+89
+00:06:21,860 --> 00:06:24,940
+instances اللي ال cluster لما يكون في .. لما يثبت
+
+90
+00:06:24,940 --> 00:06:28,000
+و يبطل تتغير أو يصير فيه يعني تغيير على ال data
+
+91
+00:06:28,000 --> 00:06:34,460
+اللي موجودةبنذكر مع بعض الـ distance function أو
+
+92
+00:06:34,460 --> 00:06:39,880
+الـ similarity function لما تكون ال instance عبارة
+
+93
+00:06:39,880 --> 00:06:41,480
+عن مجموعة من الأرقام
+
+94
+00:06:45,320 --> 00:06:47,560
+طبعا اللي بنتكلم احنا جاعدين ان ال distance
+
+95
+00:06:47,560 --> 00:06:49,860
+function هذه او ال similarity function سمناها
+
+96
+00:06:49,860 --> 00:06:53,780
+similarity او distance function لانه ال .. ال ..
+
+97
+00:06:53,780 --> 00:06:58,560
+لما انا بده اوصف rows او بده اوصف ارقام قربها او
+
+98
+00:06:58,560 --> 00:07:02,720
+بعضها من بعضها او تشابهها من بعضها معناه ان انا
+
+99
+00:07:02,720 --> 00:07:05,580
+جاعل بتكلم على نقاط طبعا لما انا برثم ال object
+
+100
+00:07:05,580 --> 00:07:10,120
+تكون موجود عندى في ال space او مرسومة عندىحتما
+
+101
+00:07:10,120 --> 00:07:13,900
+النقطين المتقاربات المسافة اللي بينهم بالدليل على
+
+102
+00:07:13,900 --> 00:07:18,680
+تشابه العناصر اللي موجودة بينهم طبعا شوية شوية
+
+103
+00:07:18,680 --> 00:07:23,260
+هتصير الأمور بالنسبة لنا أفضل لو أنا قلت لك في ال
+
+104
+00:07:23,260 --> 00:07:25,600
+space هذا على سبيل المثال أو قلت لك في ال space
+
+105
+00:07:25,600 --> 00:07:34,440
+هذا قلت ان في نقطين هذول نقطة هنا ونقطة
+
+106
+00:07:34,440 --> 00:07:37,520
+هنا ونقطة هنا
+
+107
+00:07:41,060 --> 00:07:48,240
+من اكثر نقطين متشابهتين او بلاش اقرب نقطين لبعض
+
+108
+00:07:48,240 --> 00:07:53,720
+حتم
+
+109
+00:07:53,720 --> 00:07:59,940
+النقطين اللي بينهم ال distance اصغر ما يمكن طيب
+
+110
+00:07:59,940 --> 00:08:08,520
+لو انا جدي قلت ان في عندى نقطة هنا غير اللون بس لو
+
+111
+00:08:08,520 --> 00:08:09,820
+قلت ان في عندى نقطة هنا
+
+112
+00:08:16,490 --> 00:08:19,670
+النقطة هذه أقرب لمين؟ لو انا قلت لك هذه النقطة
+
+113
+00:08:19,670 --> 00:08:24,570
+تشبه مين؟ تشبه مين؟ مافيش شبه هذه نقطة موجودة في
+
+114
+00:08:24,570 --> 00:08:29,690
+ال space معناته انا هروح أحسب مسافتها ومسافتها
+
+115
+00:08:29,690 --> 00:08:35,250
+والمسافة الأقصر هي بتمثل .. هي بتكون أقرب لمين
+
+116
+00:08:35,250 --> 00:08:39,730
+للنقطة اللي موجودة عندها طبعا احنا كلنا نعرف سابقا
+
+117
+00:08:39,730 --> 00:08:44,770
+زي ما قلنا المنهات و ال distance اللي موجودةعنا لو
+
+118
+00:08:44,770 --> 00:08:50,090
+انا افترض ان في عندى 2 نقطين ال X و ال Y كانت 2
+
+119
+00:08:50,090 --> 00:08:54,410
+points و ال 2 points هدول انا بدى احسب ال distance
+
+120
+00:08:54,410 --> 00:08:57,510
+بينهم لما اتكلم عن ال Euclidean انا بتكلم عن الجدر
+
+121
+00:08:57,510 --> 00:09:03,550
+الترديعي لمجموع مربعات الفروق ما بين مكونات
+
+122
+00:09:03,550 --> 00:09:06,450
+النقطين اللى موجودة عندى
+
+123
+00:09:09,550 --> 00:09:16,450
+وطبعاً كذلك الان مع الان بينما المنهات ال distance
+
+124
+00:09:16,450 --> 00:09:20,970
+هي عبارة عن مجموع القيم المطلقة للفروق ما بين
+
+125
+00:09:20,970 --> 00:09:24,270
+مكونات النقاط اللي موجودة عنا
+
+126
+00:09:26,900 --> 00:09:31,120
+و طبعا هاي قولنا احنا سابقا انه انا لما بتكلم على
+
+127
+00:09:31,120 --> 00:09:36,820
+منهار بتكلم على ال Euclidean معناته بتكلم على الخط
+
+128
+00:09:36,820 --> 00:09:40,200
+المستقيم اللي باللون الأخضر هذا اللي هو بتطبق
+
+129
+00:09:40,200 --> 00:09:43,840
+نظرية في ال course بين اي نقطين و لما بتكلم على
+
+130
+00:09:43,840 --> 00:09:47,960
+المنهار تاني معناته بتكلم على الدقاق اللي موجودة
+
+131
+00:09:47,960 --> 00:09:53,860
+عندها شكلي لما خدت العناصر
+
+132
+00:09:57,090 --> 00:10:12,650
+ماعدلتش الرسم تبعتي كده
+
+133
+00:10:12,650 --> 00:10:13,030
+صح
+
+134
+00:10:19,600 --> 00:10:26,360
+الان لو انا بدأ اخد نظرة في جيف الفايل الجيف بكتشر
+
+135
+00:10:26,360 --> 00:10:30,800
+اللي موجودة قدامي اللحظه انا بتكلم على عشرة
+
+136
+00:10:30,800 --> 00:10:34,180
+iterationأنا بدأت من iteration رقم واحد اتنين
+
+137
+00:10:34,180 --> 00:10:38,160
+تلاتة اربعة و لاحظوا معايا ان المربعات هذه هي ال
+
+138
+00:10:38,160 --> 00:10:41,920
+center او ال centroid لل clusters انا بقول جسم ال
+
+139
+00:10:41,920 --> 00:10:45,200
+data لاربع مجموعات و ال data هاي كلها مختلطة مع
+
+140
+00:10:45,200 --> 00:10:49,420
+بعضها بدأت الانس بناء على ال centers الألوان تتوجه
+
+141
+00:10:49,420 --> 00:10:53,700
+مع بعض مع كل iteration وهذا فعليا اللي بسوي ال K
+
+142
+00:10:53,700 --> 00:10:59,170
+meanانه بياخد random center في الأول و بعدها بيحسب
+
+143
+00:10:59,170 --> 00:11:02,210
+ال distance بين ال centers هاي و كل النقاط اللي
+
+144
+00:11:02,210 --> 00:11:06,950
+موجودة و كل النقطة بتصنف مع ال center بناء على
+
+145
+00:11:06,950 --> 00:11:10,610
+shortest distance أو ال similarity function اللي
+
+146
+00:11:10,610 --> 00:11:15,350
+احنا بنعرفهاكصورة ثابتة هي ال data set روحت قولتله
+
+147
+00:11:15,350 --> 00:11:18,990
+جسملي اياهم لمجموعات فراح اخدت تلات مجموعات طبعا
+
+148
+00:11:18,990 --> 00:11:23,270
+هان اللي هي اخدت المثلثات هتمثلت three different
+
+149
+00:11:23,270 --> 00:11:27,970
+centers ايهم حتى لو كان لان ال selection الاولى لل
+
+150
+00:11:27,970 --> 00:11:31,170
+centers الاولية by random حتى لو كانوا كلهم
+
+151
+00:11:31,170 --> 00:11:35,210
+موجودين مع بعض الا غير انه بيشتغل في ال .. لو اجوا
+
+152
+00:11:35,210 --> 00:11:38,220
+كلهم في نفس ال center ماعندي مشكلةلأنه بعد ذلك
+
+153
+00:11:38,220 --> 00:11:44,220
+سيقوم باختيار الـ average أو الـ main تبعتهم فقال
+
+154
+00:11:44,220 --> 00:11:47,440
+لي هاي ال data افترض في ال initialization زي ما
+
+155
+00:11:47,440 --> 00:11:50,820
+قلنا هى ياخذ ال random centers three centers حسب
+
+156
+00:11:50,820 --> 00:11:55,980
+المطلوب by random وراح بدأ يخصص المجموعات فراح بدأ
+
+157
+00:11:55,980 --> 00:11:56,440
+يحسب
+
+158
+00:12:01,830 --> 00:12:04,830
+اللي قلنا أننا هنعمل initialization حطّد الـ three
+
+159
+00:12:04,830 --> 00:12:09,710
+-centroid أو الـ three-center by random و بعد هيك
+
+160
+00:12:09,710 --> 00:12:13,130
+بدأ يخصص النقاط بناء على ال distance طبعا يا جماعة
+
+161
+00:12:13,130 --> 00:12:16,210
+الخير لما انا بدي اجي اتكلم النقطة high أو النقطة
+
+162
+00:12:16,210 --> 00:12:22,490
+high high distance هان و هحسبها مع هان و هحسبها مع
+
+163
+00:12:22,490 --> 00:12:31,520
+هان و هصنفها لأقرب center لأقصر مسافةوبالتالي
+
+164
+00:12:31,520 --> 00:12:35,000
+الأحمر هنا صارت هذه كل النقاط طبعا هذه النقاط هي
+
+165
+00:12:35,000 --> 00:12:37,680
+أقرب للأخضر وهذه الأزرق فضلك في ال iteration
+
+166
+00:12:37,680 --> 00:12:43,670
+التانية الآن في الخطوة التاليةأسرح سواهي يتحدد
+
+167
+00:12:43,670 --> 00:12:48,470
+الأحمر كلياته الأزرق فرح حسب المتوسط لكل النقاط
+
+168
+00:12:48,470 --> 00:12:51,770
+اللي باللون الأخضر المتوسط لكل النقاط اللي بالأحمر
+
+169
+00:12:51,770 --> 00:12:55,830
+المتوسط لكل النقاط اللي بالأزرق الداكن بينجوسين
+
+170
+00:12:55,830 --> 00:12:58,870
+يعني حسب ال main لكل ال cluster بشكل مستقل
+
+171
+00:12:58,870 --> 00:13:02,610
+والمتوسط هذا هو أخدوا ال centroid لل next
+
+172
+00:13:02,610 --> 00:13:06,750
+iteration recompute ال center هي حسب ال center من
+
+173
+00:13:06,750 --> 00:13:12,020
+جديدو راح ايش بدأ reassigning بدا يروح يعمل ال
+
+174
+00:13:12,020 --> 00:13:15,780
+center التاني و بعدها بحسب بعد ما بخلص بحسب ال
+
+175
+00:13:15,780 --> 00:13:19,640
+center كمان مرة و بروح بخصص النقاط و بحسب ال
+
+176
+00:13:19,640 --> 00:13:24,700
+center كمان مرة و بخصص النقاط لحد ما يصير بعد هيك
+
+177
+00:13:24,700 --> 00:13:27,940
+ان ال center مايصيرش فيه عليه تغيير او بينجوسين
+
+178
+00:13:27,940 --> 00:13:32,140
+تبطل النقاط تتنقل تتنقل ما بين ال cluster و التاني
+
+179
+00:13:32,140 --> 00:13:35,080
+طبعا هذا هو لكن
+
+180
+00:13:38,840 --> 00:13:43,860
+النجاح الكيميي بيعتمد على عدد ال clusters اللي انا
+
+181
+00:13:43,860 --> 00:13:49,080
+بطلبه يعني كل ما قلتله ديني عدد cluster صح بكون
+
+182
+00:13:49,080 --> 00:13:53,140
+انا بشتغل صح طبعا انا لو قلتلكوا ال data هاي و قلت
+
+183
+00:13:53,140 --> 00:13:56,640
+له two clusters هيديني اياهم اتنين لكن في حين قبل
+
+184
+00:13:56,640 --> 00:14:00,080
+شوية هي نفس ال data اللي موجودة هاد شفناها و انهم
+
+185
+00:14:00,080 --> 00:14:00,980
+منفع يكونوا تلاتة
+
+186
+00:14:09,150 --> 00:14:16,210
+التقسيم يعتمد على عدد ال clusters أو ال k التي
+
+187
+00:14:16,210 --> 00:14:24,470
+أطلبها منه تعالى نشوف بقول في المثال الأول لجسم ال
+
+188
+00:14:24,470 --> 00:14:27,510
+data اللى موجودة عنده ل two clusters
+
+189
+00:14:30,430 --> 00:14:35,150
+الخطوة رقم واحد ان انا هشتغل على random center
+
+190
+00:14:35,150 --> 00:14:44,570
+random center معناته خليني اخد ال C1 equal 3 و C2
+
+191
+00:14:44,570 --> 00:14:48,170
+equal 4 طبعا عادة ان ال random selection بتمن خلال
+
+192
+00:14:48,170 --> 00:14:51,850
+ال data set اللي موجودة الان الخطوة التالية هروح
+
+193
+00:14:51,850 --> 00:14:56,730
+احسب ال distance او المسافة بين كل element و ال
+
+194
+00:14:56,730 --> 00:15:01,460
+two centers اللي موجودينعندي و ال two centers اللي
+
+195
+00:15:01,460 --> 00:15:10,240
+موجودين عندى خليني انا امسحهم بس عشان نوضح ايش
+
+196
+00:15:10,240 --> 00:15:19,940
+اللي هيصير الآن بعد هيك زي ما قلنا هيكون هياخد ال
+
+197
+00:15:19,940 --> 00:15:22,960
+element هذا كل element و يحسبه مع ال center الأول
+
+198
+00:15:24,010 --> 00:15:28,910
+ويحسب الـ distance مع الـ center التاني ويخصصه أو
+
+199
+00:15:28,910 --> 00:15:31,550
+يحطه في المجموع يعني بين قصين هو الآن أنشأ
+
+200
+00:15:31,550 --> 00:15:38,550
+مجموعتين فارغات أنشأ مجموعتين فارغات تمام فيهم في
+
+201
+00:15:38,550 --> 00:15:42,930
+centers فقط مثلتهم تلاتة أو أربعة وراح هيضيف
+
+202
+00:15:42,930 --> 00:15:47,490
+العناصر في المجموعتين هدول بناء على بعض أو قرب أو
+
+203
+00:15:47,490 --> 00:15:51,090
+تشابه ال element لما لل centers اللي موجودين هنا
+
+204
+00:15:52,930 --> 00:15:58,970
+تنين ناقص تلاتة واحد تنين ناقص اربعة اتنين فال
+
+205
+00:15:58,970 --> 00:16:04,450
+distance ل C واحد اكثر فصنّف ليها هان اربعة ل واحد
+
+206
+00:16:04,450 --> 00:16:08,250
+اربعة مع تلاتة واحد اربعة مع اربعة صفر اللي هي ال
+
+207
+00:16:08,250 --> 00:16:11,150
+distance الفرق اللي ما بينهم راحظوا أنا كنت بتكلم
+
+208
+00:16:11,150 --> 00:16:12,050
+عن absolute value
+
+209
+00:16:18,660 --> 00:16:23,420
+عشرة لتلاتة سبعة عشرة لاربعة ستة معناته مع ال
+
+210
+00:16:23,420 --> 00:16:29,040
+cluster التاني اتناشر لتلاتة تسعة اتناشر لاربعة
+
+211
+00:16:29,040 --> 00:16:32,120
+تمانية معناته مع ال cluster التاني تلاتة تلاتة
+
+212
+00:16:32,120 --> 00:16:36,040
+لتلاتة صفر تلاتة لاربعة واحد معناته مع ال cluster
+
+213
+00:16:36,040 --> 00:16:41,400
+الأولشوفت كيف لا حد ما تخلص ال data set ممتاز خلصت
+
+214
+00:16:41,400 --> 00:16:44,840
+ال data set الآن بروح باخد المتوسط تبع ال cluster
+
+215
+00:16:44,840 --> 00:16:50,320
+الأول وهذه ال center الجديد و باخد المتوسط تبع ال
+
+216
+00:16:50,320 --> 00:16:54,640
+cluster التاني وهذه ال center الجديد تبعتها و بعيد
+
+217
+00:16:54,640 --> 00:16:59,980
+الكرة تبع اللمين لل center الجديدة تمام الآن من
+
+218
+00:16:59,980 --> 00:17:03,940
+وين الكرة مع ال data set الأصلية تنين مع اتنين و
+
+219
+00:17:03,940 --> 00:17:10,760
+نص نص لل cluster الأولأربعة في المقارنة مع ستة عشر
+
+220
+00:17:10,760 --> 00:17:14,220
+طبعاً انا بتكلم اربعة لاتنين و نص واحد و نص اربعة
+
+221
+00:17:14,220 --> 00:17:21,120
+على ستة عشر معناته بتكلم احد عشر اتن عشر احد عشر و
+
+222
+00:17:21,120 --> 00:17:21,360
+نص
+
+223
+00:17:24,250 --> 00:17:30,690
+أربعة ل .. أربعة
+
+224
+00:17:30,690 --> 00:17:33,830
+ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل ..
+
+225
+00:17:33,830 --> 00:17:33,990
+ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل ..
+
+226
+00:17:33,990 --> 00:17:34,930
+أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة
+
+227
+00:17:34,930 --> 00:17:35,370
+ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل ..
+
+228
+00:17:35,370 --> 00:17:35,430
+أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة
+
+229
+00:17:35,430 --> 00:17:36,570
+ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل ..
+
+230
+00:17:36,570 --> 00:17:38,710
+أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة
+
+231
+00:17:38,710 --> 00:17:39,850
+ل .. أربعة ل .. أربعة ل .. أربعة ل .. أربعة ل ..
+
+232
+00:17:39,850 --> 00:17:44,650
+أربعة ل .. أربعة ل ..
+
+233
+00:17:44,650 --> 00:17:49,210
+أربعة
+
+234
+00:17:49,210 --> 00:17:55,680
+لبأوقف و ببطل الشغل لما فعليا ال cluster أو ال
+
+235
+00:17:55,680 --> 00:18:01,100
+center بعد هيك تثبت لماذا؟ إذا ثبتت ال cluster أو
+
+236
+00:18:01,100 --> 00:18:03,640
+ال center اللي موجودة عندي هنا معناته أنا مافيش
+
+237
+00:18:03,640 --> 00:18:08,180
+عندي تليير بعد هيك بنجوسينت صار فيه ثبات و هيك صار
+
+238
+00:18:08,180 --> 00:18:11,340
+في عندي كل نقطة موجودة في ال cluster الحقيقي اللي
+
+239
+00:18:11,340 --> 00:18:14,660
+موجود عندك وبعد هيك ستكون كل iteration على الفاضي
+
+240
+00:18:15,590 --> 00:18:17,970
+لماذا؟ لأن الـ Center لم يتغير بمعنى التوزيع كما
+
+241
+00:18:17,970 --> 00:18:22,910
+هي و هذه هي أخر توزيع أحصل عليها طيب، تعالى نطبق
+
+242
+00:18:22,910 --> 00:18:26,990
+نفس المثال لكن مع more dimension في الـ2D بقول أنا
+
+243
+00:18:26,990 --> 00:18:31,710
+فيه عندي data set مكونة من تمام نقاط اللي بتجسمهم
+
+244
+00:18:31,710 --> 00:18:35,730
+ل three clusters باعتماد على المنهاتين distance
+
+245
+00:18:35,730 --> 00:18:42,570
+هذه النقاط اللي موجودة عندها طيب،
+
+246
+00:18:42,570 --> 00:18:49,280
+by random؟لازم اختار center اخدنا اتنين و عشرة و
+
+247
+00:18:49,280 --> 00:18:53,580
+اخدنا خمسة و تمانية و اخدنا واحد و اتنين بينفع
+
+248
+00:18:53,580 --> 00:18:56,600
+التلاتة تكون ورا بعض بينفع random الكلام random
+
+249
+00:18:56,600 --> 00:19:02,320
+جماعة الخير و بدك تشتغل و تشتغل ال distance زى ما
+
+250
+00:19:02,320 --> 00:19:05,640
+قولنا هي بتقعد تتكلم و تقول انت ماتستخدم المنهاتن
+
+251
+00:19:05,640 --> 00:19:13,370
+المنهاتن distance المعرفةالمجموع .. المجموع القيم
+
+252
+00:19:13,370 --> 00:19:19,270
+المطلقة للفرقات بين عناصر النقاط اللى موجودة عندى
+
+253
+00:19:19,270 --> 00:19:24,330
+أسهل حاجة هيك ان انا اروح انش جدول بالشكل هذا هى
+
+254
+00:19:24,330 --> 00:19:28,230
+ال data point اللى عندى وهى ال centers ال initial
+
+255
+00:19:28,230 --> 00:19:36,450
+centers C1 وC2 وC3طيب الآن بدروح أحسب ال distance
+
+256
+00:19:36,450 --> 00:19:43,430
+صفر اتنين نقص اتنين صفر زائد عشرة نقص عشرة صفر صفر
+
+257
+00:19:43,430 --> 00:19:51,230
+اتنين نقص خمسة تلاتة زائد عشرة نقص اتنين عشرة نقص
+
+258
+00:19:51,230 --> 00:19:58,990
+تمانية اتنين يعني مجموعة خمسة اتنين نقص واحد واحد
+
+259
+00:19:58,990 --> 00:20:02,530
+زائد عشرة نقص اتنين تمانية
+
+260
+00:20:05,340 --> 00:20:11,700
+الان مباشرة بقدر اقرر ان هذا اقصرDistance موجودة
+
+261
+00:20:11,700 --> 00:20:15,460
+اللي هي الصفر معناته هذا أقرب ما يكون من ال
+
+262
+00:20:15,460 --> 00:20:19,420
+cluster الرقم واحد من ال center الأول فهو بينتمل
+
+263
+00:20:19,420 --> 00:20:23,980
+ال cluster الأول بعيد الكرة مرة تانية اتنين ناقص
+
+264
+00:20:23,980 --> 00:20:30,000
+اتنين صفر خمسة ناقص عشرة خمسة هي خمسة الآن اتنين
+
+265
+00:20:30,000 --> 00:20:37,850
+ناقص خمسة تلاتة خمسة ناقص تمانية تلاتة معناته ستة2
+
+266
+00:20:37,850 --> 00:20:45,330
+-1 1 5-2 3 1 3 4 يعني الـ distance الأقصر هي عبارة
+
+267
+00:20:45,330 --> 00:20:48,630
+عن الأربعة فهذا أقرب ما يكون لك لل cluster رقم
+
+268
+00:20:48,630 --> 00:20:56,310
+تلاتة مع كذلك هنا 8-2 6 4-10 6 طبعا ليش أربعة نقص
+
+269
+00:20:56,310 --> 00:20:58,870
+عشرة ستة لما نتكلم بال absolute value من هاتين
+
+270
+00:20:58,870 --> 00:21:03,640
+distance ما تنسوشالـ distance التانية سبعة الـ
+
+271
+00:21:03,640 --> 00:21:07,900
+distance التالتة التاسعة معناته أنا أقصر مسافة
+
+272
+00:21:07,900 --> 00:21:13,640
+تسعة معناته في ال cluster التاني خمسة صفر لاحظوا
+
+273
+00:21:13,640 --> 00:21:16,620
+لأن ال data set أو ال centers أخدتها معايا فلازم
+
+274
+00:21:16,620 --> 00:21:20,080
+تطلع معايا أصفر بشكل أو بأخر لأ في أي حسب ال
+
+275
+00:21:20,080 --> 00:21:23,920
+center اللي موجود عندها فلما حسبنا تمام تمام حسبنا
+
+276
+00:21:23,920 --> 00:21:31,360
+كل ال distances وزعنا التمن عناصرعلى ال classes
+
+277
+00:21:31,360 --> 00:21:37,460
+اللي موجودة يعني a1 في c1 من ال cluster الأول a2 و
+
+278
+00:21:37,460 --> 00:21:44,240
+a7 في ال cluster التالت a3 و a4 و a5 و 6 و 8 في ال
+
+279
+00:21:44,240 --> 00:21:50,120
+cluster التاني تمام هذه التوزيع اللي عندى بناء على
+
+280
+00:21:50,120 --> 00:21:55,100
+ال clusters اللي موجودة عندها إيش المطلوب مني الآن
+
+281
+00:21:55,100 --> 00:21:59,960
+المطلوب مني الآن أحسب ال main لكل cluster
+
+282
+00:22:03,450 --> 00:22:06,670
+يعني متوسط النقاط اللي في اللون الأسود في ال
+
+283
+00:22:06,670 --> 00:22:10,530
+cluster الأول هيهم بروح بجمع النقاط اللي بتاخد
+
+284
+00:22:10,530 --> 00:22:14,050
+واحد اللي في ال cluster الأول و بحسب المتوسط
+
+285
+00:22:14,050 --> 00:22:17,730
+تبعتها مافيش غير النقطة مانا في المتوسط تبعتها مثل
+
+286
+00:22:17,730 --> 00:22:21,070
+مغير هذا ال center ماتغيرش اللي باللون الأزرق هيهم
+
+287
+00:22:21,070 --> 00:22:28,650
+تنتين نين زائد واحد تلاتة يعني واحد ونص خمسةسبعة و
+
+288
+00:22:28,650 --> 00:22:32,550
+أثنين عفوا سبعة يعني تلاتة و نص هذا ال center
+
+289
+00:22:32,550 --> 00:22:36,570
+التالت ال center التاني هيكون عبارة عن تمانية
+
+290
+00:22:36,570 --> 00:22:41,930
+زيادة خمسة زيادة سبعتاش هي عشرين وهي ستة ستة و
+
+291
+00:22:41,930 --> 00:22:45,870
+عشرين هي تلاتين تلاتين على واحد اتنين تلاتة اربع
+
+292
+00:22:45,870 --> 00:22:53,500
+خمسة يعني ستةثلاثين على خمسة ستة و ايه في اندي هان
+
+293
+00:22:53,500 --> 00:23:03,800
+اتناش سبعتاش اتنين و عشرين اتناش
+
+294
+00:23:03,800 --> 00:23:08,200
+سبعتاش واحد و عشرين تلاتين برضه ستة و ستة معلنات
+
+295
+00:23:08,200 --> 00:23:12,260
+ال news centers تبعتي انا هتكون بعد الحسبة تبعتي
+
+296
+00:23:12,260 --> 00:23:19,780
+اتنين و عشرةبالمتوسطات 6 6 1.5 3.5
+
+297
+00:23:22,880 --> 00:23:26,580
+سينترز لاحظوا أنا ما زلت ماتكلم من ال first
+
+298
+00:23:26,580 --> 00:23:30,280
+iteration اللي موجودة عندي الآن هاخد ال new
+
+299
+00:23:30,280 --> 00:23:34,600
+centers هدول و اروح فيهم على ال next iteration او
+
+300
+00:23:34,600 --> 00:23:37,680
+ال second iteration هاي حطيت ال centers اللي جديدة
+
+301
+00:23:37,680 --> 00:23:41,080
+اللي موجودة عندي هان و بديت احسب المسافة من جديد
+
+302
+00:23:41,080 --> 00:23:46,520
+بديت احسب المسافة من جديد و بنفس الكلام الآن بحسب
+
+303
+00:23:46,520 --> 00:23:49,720
+على ال centers الجديدة مع كل raw اللي موجود عندي
+
+304
+00:23:49,720 --> 00:23:54,400
+هان و باخدلأ مع نهاية العملية بروح بحسب ال centers
+
+305
+00:23:54,400 --> 00:23:58,180
+بحسب ال main لل centers اللي موجودة هيصار في عندي
+
+306
+00:23:58,180 --> 00:23:59,340
+واحد و واحد
+
+307
+00:24:02,460 --> 00:24:07,000
+الان سار في عندي واحد و واحد هي اتنين و اربعة ستة
+
+308
+00:24:07,000 --> 00:24:12,380
+على اتنين تلاتة عشرة او تسعة تسعتاش تمانية و عفوا
+
+309
+00:24:12,380 --> 00:24:15,960
+تسعة و نص هذا ال center الجديدة اللي هشتغل عليها
+
+310
+00:24:15,960 --> 00:24:19,160
+وبالتالي انا هروح في iteration تالتة لان ال
+
+311
+00:24:19,160 --> 00:24:22,060
+centers مختلفة تماما عن ال centers اللي موجودة
+
+312
+00:24:22,060 --> 00:24:26,040
+هتركي كمالية الحسبة نفس الكيفية لحد ما تثبت معاك
+
+313
+00:24:26,270 --> 00:24:29,230
+للـ clusters اللي موجود عندك هنا طبعا فى كل ال
+
+314
+00:24:29,230 --> 00:24:32,430
+slide هذه تكتبها على ورقة أو تطبق عليها و تطبقها و
+
+315
+00:24:32,430 --> 00:24:34,970
+تجرب ال center التاني و التالتة و الرابعة و ال
+
+316
+00:24:34,970 --> 00:24:41,310
+iteration طبعا متى بده يجف بده يجف لما فعليا يبطل
+
+317
+00:24:41,310 --> 00:24:47,950
+ال center عندي يتغير تمام okay طبعا لأنه فى مشكلة
+
+318
+00:24:47,950 --> 00:24:52,390
+أحيانا بالمين بتظهر معايا لو كان فى عندي ال data
+
+319
+00:24:52,390 --> 00:24:57,440
+مش معمولةpre processing صح يعني فى عندي out layer
+
+320
+00:24:57,440 --> 00:25:03,040
+زى هى دى الان لو أنا جيت قولتلك المتوسط الحسابى
+
+321
+00:25:03,040 --> 00:25:06,120
+اللى هدول واحد و تلاتة و خمسة و سبعة و تسعة
+
+322
+00:25:06,120 --> 00:25:10,780
+هتقولليها okay cancer لكن لو أنا قولتلك بدل التسعة
+
+323
+00:25:10,780 --> 00:25:16,660
+عندي الف وتسعة هيكون متوسط الحسابى جديش متسعة و
+
+324
+00:25:16,660 --> 00:25:21,060
+خمسة معناته ال center تبع هيكون بعيد جداالـ Center
+
+325
+00:25:21,060 --> 00:25:25,100
+تبعي بعيد جداً معناته يزيد من نقطة الـ convergence
+
+326
+00:25:25,100 --> 00:25:33,440
+وممكن فعليا يدينا نتيجة خطأ انت تخيل ان ال data
+
+327
+00:25:33,440 --> 00:25:39,480
+set 10 عبارة
+
+328
+00:25:39,480 --> 00:25:40,400
+عن مجموعات
+
+329
+00:25:53,650 --> 00:25:59,290
+هذه النقطة هي الـ 250 لما تكون هذه الـ Center
+
+330
+00:25:59,290 --> 00:26:01,830
+فتأخذ هذه العناصر معاها
+
+331
+00:26:04,130 --> 00:26:09,170
+لأنها الأقرب لما تختار المتوسط سيصبح هنا و هنا و
+
+332
+00:26:09,170 --> 00:26:11,250
+هنا و هنا و هنا و هنا و هنا و هنا و هنا و هنا و
+
+333
+00:26:11,250 --> 00:26:13,170
+هنا و هنا و هنا و هنا و هنا و هنا و هنا و هنا و
+
+334
+00:26:13,170 --> 00:26:13,430
+هنا و هنا و هنا و هنا و هنا و هنا و هنا و هنا و
+
+335
+00:26:13,430 --> 00:26:14,550
+هنا و هنا و هنا و هنا و هنا و هنا و هنا و هنا و
+
+336
+00:26:14,550 --> 00:26:14,930
+هنا و هنا و هنا و هنا و هنا و هنا و هنا و هنا و
+
+337
+00:26:14,930 --> 00:26:15,310
+هنا و هنا و هنا و هنا و هنا و هنا و هنا و هنا و
+
+338
+00:26:15,310 --> 00:26:17,490
+هنا و هنا و هنا و هنا و هنا و هنا و هنا و هنا و
+
+339
+00:26:17,490 --> 00:26:20,790
+هنا و هنا و هنا و هنا و هنا و هنا و هنا و
+
+340
+00:26:20,790 --> 00:26:21,690
+هنا و هنا و هنا و هنا و هنا و هنا و هنا و هنا و
+
+341
+00:26:21,690 --> 00:26:21,710
+هنا و هنا و هنا و هنا و هنا و هنا و هنا و هنا و
+
+342
+00:26:21,710 --> 00:26:21,730
+هنا و هنا و هنا و هنا و هنا و هنا و هنا و هنا و
+
+343
+00:26:21,730 --> 00:26:32,670
+هنا و هنا و هنا و هنا و
+
+344
+00:26:32,670 --> 00:26:36,780
+هنا و هناالـ median زي ما احنا بنعرف سابقا و نفس
+
+345
+00:26:36,780 --> 00:26:40,720
+الخطوات السابقة بتظل عندها لكن بدل ما بحسب زي ما
+
+346
+00:26:40,720 --> 00:26:46,180
+قلتلك المتوسط او متوسط بحسب او باخد القيمة الوسطى
+
+347
+00:26:46,180 --> 00:26:50,010
+اللى موجودة عندها او الوسطى الحسابىالـ Main
+
+348
+00:26:50,010 --> 00:26:52,950
+advantage تبع تلميذ الـ Medium زي ما قلنا أنه
+
+349
+00:26:52,950 --> 00:26:55,930
+لايتأثر بالـ Extreme Value أو بالـ Outlier Value
+
+350
+00:26:55,930 --> 00:27:00,650
+اللي موجودة هنا السؤال اللي بيدرح نفسه الآن هدد كل
+
+351
+00:27:00,650 --> 00:27:04,090
+شغلنا سابقا كان مع أرقام مشهور لو كانت ال data
+
+352
+00:27:04,090 --> 00:27:09,430
+اللي عندي عبارة عن binary 01 01 ده ال data binary
+
+353
+00:27:09,430 --> 00:27:13,450
+يعني الآن عند قيم 01 01 معناته ممكن تكون في عند
+
+354
+00:27:13,450 --> 00:27:17,410
+القيم متشابه ما بين ال clustersعشان هيك جالك لما
+
+355
+00:27:17,410 --> 00:27:19,930
+تكون ال data ال binary اللي عندي أو ال variable
+
+356
+00:27:19,930 --> 00:27:24,170
+اللي عندي كلها binary بنفعش أروح أطبق عليها ال
+
+357
+00:27:24,170 --> 00:27:28,310
+Euclidean أو المنهاتين لأ بصير في عندي similarity
+
+358
+00:27:28,310 --> 00:27:32,610
+function أخرى لازم أتعامل معاها و طبعا هنا فعليا
+
+359
+00:27:32,610 --> 00:27:36,350
+أنا بصير بدأ أدور على ال dissimilarity احنا سابقا
+
+360
+00:27:36,350 --> 00:27:39,150
+ذكرنا ان في عندي ال Euclidean و ال Jacquard و ال
+
+361
+00:27:39,150 --> 00:27:44,770
+Sparsman و ال Hoffman code إلى أخره لكن خلّيني
+
+362
+00:27:44,770 --> 00:27:50,390
+أتكلم احنا علىالـ binary data بصير احسب الـ
+
+363
+00:27:50,390 --> 00:27:55,990
+dissimilarity عدم التشابه يعني انا بعد ما أدوّق كل
+
+364
+00:27:55,990 --> 00:28:04,310
+مكان عدم التشابه peer تمام معناته التشابه عندها
+
+365
+00:28:04,310 --> 00:28:08,510
+صغير وبالتالي انا نفس الفكرة ان انا بدور على ال
+
+366
+00:28:08,510 --> 00:28:12,920
+smaller value دائماعشان اتكلم عن انه في شبه او
+
+367
+00:28:12,920 --> 00:28:18,300
+مافيش شبه لكن زي ما قلنا ان انا بتكلم على عدم
+
+368
+00:28:18,300 --> 00:28:25,620
+التشابه بشكل عام لما بكون في عندى ال data set او
+
+369
+00:28:25,620 --> 00:28:31,540
+ال point تبعتى فيه عبارة عن value من صفر واحد ال
+
+370
+00:28:31,540 --> 00:28:34,840
+dissimilarity تبعتنا عبارة عن non negative number
+
+371
+00:28:35,710 --> 00:28:42,510
+لما بيكون closed to zero معناته نغطي نقراب جدا من
+
+372
+00:28:42,510 --> 00:28:46,710
+بعض أو متشابهات و العكس كل ما زاد الرقم كل ما كبل
+
+373
+00:28:46,710 --> 00:28:52,450
+الرقم معناته الرقامين هدول مختلفين عن بعض يعني
+
+374
+00:28:52,450 --> 00:28:55,490
+هنوجه اني بجيس الاختلاف الآن هنوجه اني بجيس
+
+375
+00:28:55,490 --> 00:28:58,650
+الاختلاف قعد كنت بجيس التشابه و الأن بدي أجيس
+
+376
+00:28:58,650 --> 00:29:04,560
+الاختلافاللي الأن من الـ matrix اللي ذكرناها
+
+377
+00:29:04,560 --> 00:29:07,260
+سابقاً اللي هي الـ jacquard بدك تفترض أنه أنا
+
+378
+00:29:07,260 --> 00:29:13,340
+فعلياً عندي data 6 باعتي مكونة من ال object الأول
+
+379
+00:29:13,340 --> 00:29:19,060
+وال object التاني عشان أنا أخد قيم ال value ال
+
+380
+00:29:19,060 --> 00:29:23,900
+binary value اللي موجودةالان بدأت توزع 01 الـ I و
+
+381
+00:29:23,900 --> 00:29:29,380
+الـ J الـ I و الـ J A و B و C و D هذه العناصر اللي
+
+382
+00:29:29,380 --> 00:29:35,240
+بتمثل المصفوفة اللي عندي اللاحظوا أنا جمعت الـ B و
+
+383
+00:29:35,240 --> 00:29:35,660
+الـ C
+
+384
+00:29:50,030 --> 00:29:54,350
+عشان نفهم الصورة صح و نشوف بالمثال يتضح المقال زي
+
+385
+00:29:54,350 --> 00:29:59,050
+ما بقول المثل تعالى نروح نشتغل handو نشوف ايش
+
+386
+00:29:59,050 --> 00:30:04,150
+العناصر اللي موجودة عندها بيجي بقول افترض ان هاي
+
+387
+00:30:04,150 --> 00:30:08,790
+في عندى انا ال binary data بدي اعملها partitioning
+
+388
+00:30:08,790 --> 00:30:12,930
+cluster هذه بتمثل patient record ال records او
+
+389
+00:30:12,930 --> 00:30:17,530
+الموجودين عندها ما بين ال positive و ال yes طبعا
+
+390
+00:30:17,530 --> 00:30:22,610
+بتكلم على اسم الشخص مش هدخل معايا حتما في الحسبة
+
+391
+00:30:22,610 --> 00:30:29,890
+اللي في عنديالـ fever عفوا الدرجة الحرارة الكف
+
+392
+00:30:29,890 --> 00:30:34,250
+اللي هي السعال الفحص الأول التاني التالت الرابع و
+
+393
+00:30:34,250 --> 00:30:39,050
+positive بواحد و ال yes بواحد و ال no ايه بصفر و
+
+394
+00:30:39,050 --> 00:30:43,890
+ال negative ايه بصفر الان بدأ انا ارجع معاك لهان
+
+395
+00:30:43,890 --> 00:30:48,910
+لما انا جينا من هنا نتكلم هنا ال a ايش ال a بتمثل
+
+396
+00:30:48,910 --> 00:30:51,830
+ال a بتمثل هي عبارة عن مجموع
+
+397
+00:30:54,440 --> 00:30:59,140
+النقاط اللي التقت فيها الـ two objects I و J كانت
+
+398
+00:30:59,140 --> 00:31:02,980
+النقاط الواحد بقى بالـ B أو الـ D مجموع النقاط
+
+399
+00:31:02,980 --> 00:31:06,720
+اللي كانوا فيها زي بعض لكن بالصفر C هي النقاط اللي
+
+400
+00:31:06,720 --> 00:31:13,320
+كانت ل ال object J واحد و ال object I صفر و هكذا
+
+401
+00:31:13,320 --> 00:31:19,100
+تعالوا نجي على المثالاللي موجود عندنا هان طيب إذا
+
+402
+00:31:19,100 --> 00:31:22,380
+احنا قلنا هذه بواحد معناته انا بده اروح اخد two
+
+403
+00:31:22,380 --> 00:31:26,820
+rows موجودين عندي هان بالمثال اللي موجود عندنا هان
+
+404
+00:31:26,820 --> 00:31:31,480
+بدنا نشتغل مع جاك و ماري مع بعض انا بده اشوف مين
+
+405
+00:31:31,480 --> 00:31:34,820
+اقرب اتنين من هدولة لبعضهم معناته انا بده اشوف جاك
+
+406
+00:31:34,820 --> 00:31:38,680
+و ماري و جاك و جيم و ماري و جيم هي الاحتمالات
+
+407
+00:31:38,680 --> 00:31:40,740
+التلاتة اللي موجودة معناته انا بده اشتغل في
+
+408
+00:31:40,740 --> 00:31:41,400
+البداية على
+
+409
+00:31:48,900 --> 00:31:55,780
+الـ two rows اللي موجودين عندها وين التنين كانوا
+
+410
+00:31:55,780 --> 00:31:59,340
+positive وين التنين كانوا فيه عندى واحد كام عمود
+
+411
+00:31:59,340 --> 00:32:05,000
+كان فيهم التنين قيمتهم واحد هذا واحد هذا اتنين
+
+412
+00:32:05,000 --> 00:32:11,540
+خلاص معناته واحد واحد هي اتنين اللي هي ال a تمام
+
+413
+00:32:11,540 --> 00:32:24,840
+طيب جاك واحد وماري صفرJack 1 وماري صفر مافيش Jack
+
+414
+00:32:24,840 --> 00:32:32,160
+0 وماري واحد هيها نقول ال positive واحد هيها واحد
+
+415
+00:32:32,160 --> 00:32:42,920
+الان negative 00000 هي تلاتة هي المصفوفة تبعتي
+
+416
+00:32:42,920 --> 00:32:46,840
+تمام الان احنا قلنا هي عبارة عن
+
+417
+00:32:50,130 --> 00:32:59,190
+abcd نجمع a و b او ناخد المتلت العلوي هذا واحد
+
+418
+00:32:59,190 --> 00:33:04,690
+زائد صفر على واحد زائد صفر زائد واحد زائد اتنين
+
+419
+00:33:04,690 --> 00:33:10,650
+تلاتة و تلاتين لما انا بروح بحسب لماري بحسب لجاك و
+
+420
+00:33:10,650 --> 00:33:17,850
+مق و جيم بنفس الكيفية تمام دعنا نعيدها هنا من ال
+
+421
+00:33:17,850 --> 00:33:18,210
+eraser
+
+422
+00:33:26,820 --> 00:33:33,180
+طبعا القيمة ده هتتغير الان انا هروح اشتغل مع او
+
+423
+00:33:33,180 --> 00:33:36,600
+نحاول نعمل contingency matrix جديدة بلون جديد نغير
+
+424
+00:33:36,600 --> 00:33:42,300
+لون الجلم دعوني
+
+425
+00:33:42,300 --> 00:33:51,780
+اخد blow الان هي contingency matrix ما
+
+426
+00:33:51,780 --> 00:34:02,040
+بين الان بدنا نشتغل marryأو jack و
+
+427
+00:34:02,040 --> 00:34:08,620
+gem طبعا مش فارقة كتير الترتيب اللي ما بينهم قولنا
+
+428
+00:34:08,620 --> 00:34:16,540
+واحد صفر هاي
+
+429
+00:34:16,540 --> 00:34:22,640
+واحد و صفر وهنا فوق الخطوط هادى بدي أضيف الأرقام
+
+430
+00:34:22,640 --> 00:34:28,560
+اللى أنا بدي يعنيطيب نبدأ بواحد و واحد عدد النقاط
+
+431
+00:34:28,560 --> 00:34:35,300
+اللي التقى فيها جاك وجيم مع بعض هي واحد positive
+
+432
+00:34:35,300 --> 00:34:39,460
+هذه negative مافيش
+
+433
+00:34:39,460 --> 00:34:43,480
+واحد ال
+
+434
+00:34:43,480 --> 00:34:53,260
+pointer بين واحد
+
+435
+00:34:53,260 --> 00:35:02,030
+طيبالان جاك واحد وجم صفر جاك واحد وجم صفر جاك واحد
+
+436
+00:35:02,030 --> 00:35:08,330
+هيها وجم صفر هيها معناته واحد تمام
+
+437
+00:35:08,330 --> 00:35:17,570
+بعد هيك جاك صفر وجم واحد جاك صفر مع الكف واحد
+
+438
+00:35:17,570 --> 00:35:20,310
+والان صفر وصفر
+
+439
+00:35:25,620 --> 00:35:31,960
+واحد اتنين ثلاثة معناته
+
+440
+00:35:31,960 --> 00:35:35,520
+الآن العلاقة الـ dissimilarity الـ dissimilarity
+
+441
+00:35:35,520 --> 00:35:40,480
+بين جام جاك و جيم واحد زائد واحد على واحد زائد
+
+442
+00:35:40,480 --> 00:35:45,080
+واحد زائد واحد كمان
+
+443
+00:35:45,080 --> 00:35:49,780
+الان بعمل كمان ما بين ماري و جيم النفس الكيفية
+
+444
+00:35:49,780 --> 00:35:55,420
+لمبادئ بطلع الان بدي اقارن جمهات الخيرأصغر
+
+445
+00:35:55,420 --> 00:35:59,840
+dissimilarity معناته أعلى تشابه كل ما كبرت ال
+
+446
+00:35:59,840 --> 00:36:02,540
+dissimilarity معناته الاختلاف بينهم كبير جدا
+
+447
+00:36:02,540 --> 00:36:07,540
+معناته انا اكتر اتنين متشابهين او اقرب اتنين لبعض
+
+448
+00:36:07,540 --> 00:36:14,380
+اللي هي مين جاك و ماري حسب ال jacquard computation
+
+449
+00:36:14,380 --> 00:36:17,180
+او ال jacquard metric function اللي احنا بنتكلم
+
+450
+00:36:17,180 --> 00:36:22,180
+عليها لإيه الدلال dissimilarityلاحظوا سابقاً كنت
+
+451
+00:36:22,180 --> 00:36:25,520
+بتكلم عن الـ distance أو ال similarity distance أو
+
+452
+00:36:25,520 --> 00:36:29,240
+ال distance function كنت بتكلم عن ال shortest
+
+453
+00:36:29,240 --> 00:36:31,780
+distance بس الآن بتكلم عن ال shortest
+
+454
+00:36:31,780 --> 00:36:37,160
+dissimilarity طبعا و السيميلارتي لما انا بدي ال ..
+
+455
+00:36:37,160 --> 00:36:40,320
+ال
+
+456
+00:36:40,320 --> 00:36:45,760
+.. ال .. الآن هذه اكتر تشابه او اكتر اقل اختلاف
+
+457
+00:36:45,760 --> 00:36:50,650
+بين Jack و Maryلو انا بدي اتكلم عليك تشابه خد واحد
+
+458
+00:36:50,650 --> 00:36:54,390
+ناقص معناته كل ما بدي ازيد التشابه عندهان مابدي
+
+459
+00:36:54,390 --> 00:36:59,930
+اصير فيهان وبالتالي بصير فيني عند جاك وماري اكتر
+
+460
+00:36:59,930 --> 00:37:03,390
+اتنين متشابهين المحتمل انهم ياخدوا نفس المرض بناء
+
+461
+00:37:03,390 --> 00:37:06,310
+على ال data set يكون عندهم نفس المرض لان هذول اكتر
+
+462
+00:37:06,310 --> 00:37:10,210
+اتنين متقاربين في المحوصات وفي الاعراض اللي موجودة
+
+463
+00:37:10,210 --> 00:37:18,290
+عندنا بينما جيم وماري اكتر اتنين مختلفينوبالتالي
+
+464
+00:37:18,290 --> 00:37:22,510
+لا نعتقد أو مافيش اعتقاد انهم يكونوا من نفس المرض
+
+465
+00:37:22,510 --> 00:37:28,090
+أو منهم نفس المشكلة المرضية اللي عندهم من اللي لو
+
+466
+00:37:28,090 --> 00:37:35,870
+بدنا نتكلم على المزايا وعيوب ال K-Means المزايا
+
+467
+00:37:35,870 --> 00:37:43,030
+simple سهل ان انا افهمه ال item يتخصص بشكل تلقائي
+
+468
+00:37:43,030 --> 00:37:51,680
+ل clusterالـ disadvantages لازم تتصنف لازم تتصنف
+
+469
+00:37:51,680 --> 00:37:54,720
+لازم
+
+470
+00:37:54,720 --> 00:37:57,060
+تتصنف لازم تتصنف لازم تتصنف
+
+471
+00:38:00,680 --> 00:38:03,960
+الـ sensitive to outlier زي ما شوفنا ان الـ
+
+472
+00:38:03,960 --> 00:38:08,060
+outlier بتغير الـ center sensitive to initial seed
+
+473
+00:38:08,060 --> 00:38:11,780
+اللي هي ال random center اللي في الأول لو كانت
+
+474
+00:38:11,780 --> 00:38:14,520
+دقيقة عندي لو كانت في نص ال .. لو كانت هي ال
+
+475
+00:38:14,520 --> 00:38:17,980
+center ممكن اوصل من أول iteration أو التانية لكن
+
+476
+00:38:17,980 --> 00:38:20,380
+لو كانت بعيدة معنى انه هياخد منه وجد في ال
+
+477
+00:38:20,380 --> 00:38:26,660
+convergence لما يصل لنهاية الحل طبعا صعبة غير
+
+478
+00:38:26,660 --> 00:38:33,280
+مناسبة للي يشوف ال clusterمن الـ hyper ellipsoid
+
+479
+00:38:33,280 --> 00:38:37,400
+أو الـ hyper shapers اللي حيكون لو كانتش ال data
+
+480
+00:38:37,400 --> 00:38:41,680
+أو ال data متواجدة بأشكال صعبة مش هيشتغل عليها
+
+481
+00:38:41,680 --> 00:38:45,740
+طبعا هنا بنتكلم اش .. طبعا الشغلة الأخيرة اللي هي
+
+482
+00:38:45,740 --> 00:38:49,040
+علاقة بال failure فعليا مش نقصيه طب هو فعلا بيفشل
+
+483
+00:38:49,040 --> 00:38:53,740
+تماما اللي
+
+484
+00:38:53,740 --> 00:38:58,300
+بيفشل اذا انا فعليا مادتهوش رقمالـ cluster الحقيقي
+
+485
+00:38:58,300 --> 00:39:04,980
+أو المناسب لل data set اللي موجود عندها كذلك بيفشل
+
+486
+00:39:04,980 --> 00:39:06,140
+ال
+
+487
+00:39:11,460 --> 00:39:16,520
+إن كل cluster أو التعرف تبقى على ال center لما
+
+488
+00:39:16,520 --> 00:39:19,300
+يكون عندك ال center يعني أنك تتكلم عن دائرة أو
+
+489
+00:39:19,300 --> 00:39:24,640
+مربع طيب لو كان في عندك ghost او care او اي shape
+
+490
+00:39:24,640 --> 00:39:30,080
+مختلف ايش ال center بدنا نفهمه؟ مش هيظبط لأن لو
+
+491
+00:39:30,080 --> 00:39:35,120
+قلت لك في عندك شكل هلال ايش ال center تبعتها؟مش
+
+492
+00:39:35,120 --> 00:39:40,200
+هتظبط لو انا جيل قلتلك ان في عندي المنحنة ايش ال
+
+493
+00:39:40,200 --> 00:39:43,620
+center تبع المنحنة مش هتظبط لكن ممكن افهمها في
+
+494
+00:39:43,620 --> 00:39:48,640
+مثلث افهمها في دائرة افهمها في مستطيل مستطيل او
+
+495
+00:39:48,640 --> 00:39:53,700
+مربع ممكن افهمها في اشكال اللي موجودة عندك تعالى
+
+496
+00:39:53,700 --> 00:39:59,160
+شوف هنا الان لما انا روحي قلتله ال .. ال .. ال ..
+
+497
+00:40:01,580 --> 00:40:04,200
+لما تكون ال data اللي عندها الها different
+
+498
+00:40:04,200 --> 00:40:12,340
+densities او
+
+499
+00:40:12,340 --> 00:40:17,720
+كتابتها مختلفة ال chemistry بيفشل ليش؟ لأنه بيعتمد
+
+500
+00:40:17,720 --> 00:40:21,000
+على المسافة فالان هذا فعليا ال data هذا ال cluster
+
+501
+00:40:21,000 --> 00:40:24,980
+الحقيقي هذه التوزيع لكن لو انا اجيت و قلتلك هذه
+
+502
+00:40:24,980 --> 00:40:27,920
+النقطة هتصنفها مع اي cluster لو انا افترضت انه ال
+
+503
+00:40:27,920 --> 00:40:28,440
+center هنا
+
+504
+00:40:31,160 --> 00:40:40,700
+و الـ center هنا و ال center هنا فممكن
+
+505
+00:40:40,700 --> 00:40:47,480
+النقطة high تكون أقرب من هنا فالنقطة
+
+506
+00:40:47,480 --> 00:40:53,040
+high هي أقرب لهذه وبالتالي
+
+507
+00:40:53,040 --> 00:40:55,660
+لما يكون في عندي different densities معناه ان في
+
+508
+00:40:55,660 --> 00:40:59,960
+عندي مشكلة مع الكيمياكذلك عندما يكون لدي nano
+
+509
+00:40:59,960 --> 00:41:04,820
+spherical cluster تخيل انه سيجلب لي cluster عندي و
+
+510
+00:41:04,820 --> 00:41:10,780
+هاي ال centers اشتغل على three centers هدول اريهم
+
+511
+00:41:10,780 --> 00:41:15,580
+كيف
+
+512
+00:41:15,580 --> 00:41:18,860
+بده يجيبليها او عندما يكون لدي ال complex shape
+
+513
+00:41:18,860 --> 00:41:22,120
+بالشكل هذا سيقول هاي center عندي هنا وهي center
+
+514
+00:41:22,120 --> 00:41:30,890
+هنا او هذا ال distance صحيحة او هناهل هذه النقطة
+
+515
+00:41:30,890 --> 00:41:34,530
+هي الأقرب لها ؟ فهو الـ shape تبع ال complex فهذه
+
+516
+00:41:34,530 --> 00:41:37,910
+الحلقات كلها بيفشل فيها ال K مين طبعا احنا فعليا
+
+517
+00:41:37,910 --> 00:41:42,590
+في عندنا algorithm تاني زي ال DB scan و هذا ال
+
+518
+00:41:42,590 --> 00:41:48,370
+algorithm فعال جدا في التعامل مع ال .. بطلبش مني
+
+519
+00:41:48,370 --> 00:41:50,970
+عدد ال K و بيشتغل و بحاول يتعرف على ال complex
+
+520
+00:41:50,970 --> 00:41:56,230
+shape لأنه بيعتمد على ال density و بحاول يجد لها
+
+521
+00:41:57,020 --> 00:41:59,780
+يتعرف على الـ clusters بناءً على ال density اللي
+
+522
+00:41:59,780 --> 00:42:03,560
+موجودة لكن تبقى زي ما قلنا هل ال evaluation أو
+
+523
+00:42:03,560 --> 00:42:06,620
+التقييم تبعي تبع أداء ال cluster صحيح أم لا بناءً
+
+524
+00:42:06,620 --> 00:42:09,680
+على أداء ال clusters ومعرفة بعدد ال clusters
+
+525
+00:42:09,680 --> 00:42:13,230
+الحقيقية لل data اللي موجودةنشوفكوا على خير ان شاء
+
+526
+00:42:13,230 --> 00:42:17,130
+الله تعالى في المحاضرة هذه اتعرفنا على الكمين
+
+527
+00:42:17,130 --> 00:42:21,130
+وشوفنا كيف نحسبه واتخرفنا على مزاياه وعيوبه
+
+528
+00:42:21,130 --> 00:42:23,990
+التسجيل اللي جاي ان شاء الله تعالى هنتقل للـ
+
+529
+00:42:23,990 --> 00:42:27,510
+Hierarchical Clustering السلام عليكم ورحمة الله
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/CMRo1Sw-HX4_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/CMRo1Sw-HX4_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..95c74138aa8163dacded20ce16365b85f80b9de8
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/CMRo1Sw-HX4_raw.srt
@@ -0,0 +1,3424 @@
+1
+00:00:05,080 --> 00:00:07,260
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:07,260 --> 00:00:10,540
+اليوم ان شاء الله تعالى هنكمل في موضوع ال data
+
+3
+00:00:10,540 --> 00:00:13,800
+cleaning كنا المحاضرة الماضية اللي اشتغلنا في
+
+4
+00:00:13,800 --> 00:00:19,820
+موضوع ال missing لل data و اليوم ان شاء الله تعالى
+
+5
+00:00:19,820 --> 00:00:25,720
+هنشتغل في موضوع ال noisy data الان في ال noisy
+
+6
+00:00:25,720 --> 00:00:29,060
+data قلنا احنا ال noise data مفهومها ان انا في
+
+7
+00:00:29,060 --> 00:00:33,890
+عندى خطأ لسببerror معين الـ error ده ممكن يكون
+
+8
+00:00:33,890 --> 00:00:37,950
+الناتج عنه من human entry أو فيه fault في ال
+
+9
+00:00:37,950 --> 00:00:41,190
+instrument اللي أنا جمعت من خلالها ال data وقولنا
+
+10
+00:00:41,190 --> 00:00:44,430
+من أشهر الأمثلة اللي أنا بتكلم عليها على ال noise
+
+11
+00:00:44,430 --> 00:00:50,130
+data الراتب يكون بالسالب بغض النظر عن كانت إيش
+
+12
+00:00:50,130 --> 00:00:53,890
+الأخطاء إيش الشغلات اللي أنا فعليا محتاجها عشان
+
+13
+00:00:55,040 --> 00:00:59,320
+أعرض أو أتعامل مع ال data set اللي موجودة عندنا
+
+14
+00:00:59,320 --> 00:01:01,900
+كيف بدي أعمل لها handling من أشهر الطرق اللي
+
+15
+00:01:01,900 --> 00:01:05,680
+موجودة عندنا موضوع ال pinning وما المقصود في ال
+
+16
+00:01:05,680 --> 00:01:10,520
+pinning أنه أنا فعليا بدي أروح أجسم ال data set
+
+17
+00:01:10,520 --> 00:01:17,850
+تبعتي لمجموعات وكل مجموعة هتمثل سيبني يا عمركل
+
+18
+00:01:17,850 --> 00:01:21,870
+مجموعة هتتمثل بقيمة معينة القيمة دي ممكن تكون ال
+
+19
+00:01:21,870 --> 00:01:25,050
+main ممكن تكون ال median او ممكن تكون بقيمتين عشان
+
+20
+00:01:25,050 --> 00:01:28,150
+امثل المجموعة لو اعتمدت على ال boundaries لكن في
+
+21
+00:01:28,150 --> 00:01:32,630
+شغل مهم جدا مع ال binning اللي هي الموضوع انه انا
+
+22
+00:01:32,630 --> 00:01:35,810
+فعليا ال partition تبع ال bin ال partition تبعتي
+
+23
+00:01:35,810 --> 00:01:39,770
+هاي او ال bin جداش حجمها بدو يكون هل هتكلم على
+
+24
+00:01:39,770 --> 00:01:44,980
+equal frequencyيعني فعلياً كل ال bins هيكونوا نفس
+
+25
+00:01:44,980 --> 00:01:50,480
+العدد ولا هتكلم على ال equal depth باجب ال equal
+
+26
+00:01:50,480 --> 00:01:54,120
+depth انا باجب فكرتها انه انا اجسم المجموعات تبع
+
+27
+00:01:54,120 --> 00:01:57,800
+ال intervals اجي اقول من عشرة مثلا من واحد لعشرة
+
+28
+00:01:57,800 --> 00:02:02,860
+ال interval الأولى من عشرة عفوا من 11 لعشرين ال
+
+29
+00:02:02,860 --> 00:02:06,260
+interval التانية من واحد وعشرين لتلاتين ال
+
+30
+00:02:06,260 --> 00:02:10,360
+interval التالتةبغض النظر عن الأعداد اللي بدها
+
+31
+00:02:10,360 --> 00:02:14,160
+تكون في كل interval هذي بتسميها احنا ايش؟ equal
+
+32
+00:02:14,160 --> 00:02:18,060
+depth بينها بقى ال equal frequency ان كل partition
+
+33
+00:02:18,060 --> 00:02:23,760
+في نفس العدد من ال elements لكن عشان فعليا اطبق
+
+34
+00:02:23,760 --> 00:02:29,740
+انا ال pinning لازم في البداية اعمل sort لل data
+
+35
+00:02:29,740 --> 00:02:36,350
+لو ماعملتش sort كل شغلك غلط على الفاضيلكن في موضوع
+
+36
+00:02:36,350 --> 00:02:40,370
+الـ Equal Depth ممكن انا اشتغل اذا انا فاهم ال
+
+37
+00:02:40,370 --> 00:02:44,830
+minimum و ال maximum تبعوني قداش بقدر اعمل استخدام
+
+38
+00:02:44,830 --> 00:02:48,210
+و عارف ايش ال range اللي ممكن تخدمني ال intervals
+
+39
+00:02:48,210 --> 00:02:50,430
+ممكن اشتغل لانه في الآخر بدي أصبح ال
+
+40
+00:02:50,430 --> 00:02:53,410
+representation لكل رقم بال interval اللي موجودة
+
+41
+00:02:53,410 --> 00:02:57,890
+عندها تعالوا نشوفمع بعض ال binning الان العملية
+
+42
+00:02:57,890 --> 00:02:59,370
+التانية اللى هتكلم عليها ال regression و ال
+
+43
+00:02:59,370 --> 00:03:02,030
+clustering بعدين كنا احنا بدنا مع ال binning و
+
+44
+00:03:02,030 --> 00:03:05,570
+الرقم واحد كنا بدنا نعمل sort و بالمثال هذا هشتغل
+
+45
+00:03:05,570 --> 00:03:09,510
+على equal frequency equal frequency قاللي انا الان
+
+46
+00:03:09,510 --> 00:03:10,990
+بدي اشتغل على three bins
+
+47
+00:03:19,150 --> 00:03:22,830
+الان يا جماعة الخير لو كان في عندي plus او minus
+
+48
+00:03:22,830 --> 00:03:26,890
+one في ال interval يعني لو كانت ال interval تبعتي
+
+49
+00:03:26,890 --> 00:03:34,150
+هذه 13 رقم 27 مش big deal او مش مشكلة ان الرقم
+
+50
+00:03:34,150 --> 00:03:38,300
+الأخير هذا ينضاف على ال penالاخيرة طيب لو كان في
+
+51
+00:03:38,300 --> 00:03:43,000
+عندي تلت أرقام مخص بن مخص رقم واحد ماعندي مشكلة
+
+52
+00:03:43,000 --> 00:03:47,360
+تكون البن الأخيرة بأقل من digit خصوصا لما احنا
+
+53
+00:03:47,360 --> 00:03:50,720
+بنتكلم انا بدي اعمل handling ل attribute ال
+
+54
+00:03:50,720 --> 00:03:53,740
+attribute مش اتناشر value اللي فيه تلتاشر ممكن
+
+55
+00:03:53,740 --> 00:03:57,100
+يكون فيه تلتاشر الف value فلما فعليا اجي اقول
+
+56
+00:03:57,100 --> 00:04:01,980
+والله بدي خصه عندي مائة قيمةمن الف مش قضية لسه ما
+
+57
+00:04:01,980 --> 00:04:06,200
+زال عندي فيه 900 قيمة موجودات وبقالهم وزلهم
+
+58
+00:04:06,200 --> 00:04:10,160
+وبأثروا بشكل كويس فالخطوة رقم واحد بعد ما انا اعمل
+
+59
+00:04:10,160 --> 00:04:15,140
+sort اجسم المجموعات اعملت sort بدي equal frequency
+
+60
+00:04:15,140 --> 00:04:23,160
+اربعة هاي واحدة تنتين تلاتة الخطوة رقم واحدSort
+
+61
+00:04:23,160 --> 00:04:25,860
+الخطوة الرقم اتنين تجسيمهم او ال partitioning
+
+62
+00:04:25,860 --> 00:04:32,120
+تبعتهم لمجموعات الآن بعد هيك القيام هذه مين فيها
+
+63
+00:04:32,120 --> 00:04:36,700
+ال noise انا فعليا مش عارف هل هي الأربعة هي ال
+
+64
+00:04:36,700 --> 00:04:39,680
+noise ولا الأربعة و تلاتين هي ال noise انا فعليا
+
+65
+00:04:39,680 --> 00:04:43,580
+مش عارفها لكن هذه الأربعة او الأربعة و تلاتين انا
+
+66
+00:04:43,580 --> 00:04:49,120
+فعليا هخلص منها من خلال استبدالها بإيش مع كل بن
+
+67
+00:04:49,120 --> 00:04:53,360
+الآن ممكن استبدلها بالقيامة ال meanأو الـ Median
+
+68
+00:04:53,360 --> 00:04:58,920
+أو الـ Value .. ال .. عفوا القيم ال boundaries لو
+
+69
+00:04:58,920 --> 00:05:03,160
+أنا بدأ اعتمد على ال meme هضطر اجمع تمانية زائد
+
+70
+00:05:03,160 --> 00:05:06,140
+اربعة .. اربعة زائد تمانية زائد تسعة زائد خمستاشع
+
+71
+00:05:06,140 --> 00:05:10,640
+على اربعة واروح استبدلهم قلعت تسعة بتالي المجموعة
+
+72
+00:05:10,640 --> 00:05:15,640
+الاولى كل element فيها بده يصير تسعة كل element
+
+73
+00:05:15,640 --> 00:05:18,900
+فيها بده يصير تسعة المجموعة التانية المتوسطة
+
+74
+00:05:18,900 --> 00:05:22,670
+الحسابة تبعها كانت تلاتة وعشرين ومن ثم ال ..و
+
+75
+00:05:22,670 --> 00:05:26,050
+هتكون تلاتة و عشرين والاخيرة تسعة و عشرين و هكذا
+
+76
+00:05:26,050 --> 00:05:31,470
+لو انا بدي اشتغل على ال boundaries مفهوم ال
+
+77
+00:05:31,470 --> 00:05:36,270
+boundaries هيهم الأربعة والخمستاش هدولة لل بن
+
+78
+00:05:36,270 --> 00:05:41,130
+الأول او لل partition الأول الآن الأربعة والخمستاش
+
+79
+00:05:41,130 --> 00:05:44,550
+هدولة هتكون ثابتات لاحظ في ال main و ال median انا
+
+80
+00:05:44,550 --> 00:05:48,010
+كل ال partitionالـ values تبعت ال partition
+
+81
+00:05:48,010 --> 00:05:51,970
+بستبدلها بقيمة واحدة، مظبوط؟ اللي كانت بال mean أو
+
+82
+00:05:51,970 --> 00:05:56,190
+ال median التسعة استبدلت كل القيم لكن مع ال part
+
+83
+00:05:56,190 --> 00:05:59,570
+.. مع ال boundaries point بصير .. بتكلم على لأ ال
+
+84
+00:05:59,570 --> 00:06:04,830
+partition الواحد في قيمتين ال minimum و ال maximum
+
+85
+00:06:04,830 --> 00:06:10,090
+الآن باجي بدور على القيم اللي في النص تمانية أقرب
+
+86
+00:06:10,090 --> 00:06:14,240
+لأي boundaryوبعملها replacement لل boundary الأقرب
+
+87
+00:06:14,240 --> 00:06:21,660
+8 أقرب لل 4 أكيد ومن ثم replace 4 9 لل 4 لأن الفرق
+
+88
+00:06:21,660 --> 00:06:26,380
+بينها و بين 4 و 5 و 15 و 6 فهي أقرب لل 4 وبالتالي
+
+89
+00:06:26,380 --> 00:06:31,380
+بعملها replacement بال 4 الان نفس ال 21 و 21 و 24
+
+90
+00:06:31,380 --> 00:06:36,120
+يصير 25 هنا أقرب و هكذا تمام؟ هذا مفهوم ال
+
+91
+00:06:36,120 --> 00:06:40,200
+boundaries لكن تعالى نشوف مثالنبدأ فيه من البداية
+
+92
+00:06:40,200 --> 00:06:44,240
+خالص هنشتغل فيه كتالي حاجة أقول أنا في عندي مثلا
+
+93
+00:06:44,240 --> 00:06:58,400
+القيم بسيطة سبعة تلاتة تمانية سالب واحد اتنين خمسة
+
+94
+00:06:58,400 --> 00:07:09,880
+عشرة تسعة ستة اربعة اتناشروهي كمان مرة تلاتة مش
+
+95
+00:07:09,880 --> 00:07:14,420
+هتفرج معايا الان
+
+96
+00:07:14,420 --> 00:07:19,160
+انا بدي اشتغل او بدي اعمل partition او بدي استخدم
+
+97
+00:07:19,160 --> 00:07:23,460
+two partitions الخطوة
+
+98
+00:07:23,460 --> 00:07:26,200
+رقم واحد طبعا كمان مرة بيتكلم عن ال equal
+
+99
+00:07:26,200 --> 00:07:31,700
+frequency equal frequency هشتغل الان اول خطوة رقم
+
+100
+00:07:31,700 --> 00:07:44,830
+واحد sort هي سالب واحدتنين تلاتة كمان تلاتة عندي
+
+101
+00:07:44,830 --> 00:07:57,970
+أربعة خمسة ستة سبعة تمانية تسعة عشرة معاشر هيك ال
+
+102
+00:07:57,970 --> 00:08:01,990
+data صارت sortedأنا بتكلم على equal frequency
+
+103
+00:08:01,990 --> 00:08:04,210
+equal frequency على two partitions يعني أنا بدي
+
+104
+00:08:04,210 --> 00:08:12,630
+أعدهم من النص 1,2,3,4,5,6,7,8,9,10,11,12,6 مافي
+
+105
+00:08:12,630 --> 00:08:17,290
+عندي مشكلة 1,2,3,4,5,6 هي ال partition أو البن
+
+106
+00:08:17,290 --> 00:08:25,930
+الأول وهي البن الثاني الآن بال mean لو أنا بدي
+
+107
+00:08:25,930 --> 00:08:30,610
+أشتغل بال mean بدي .. مافيش عندي مشكلة بدي أجمعبدي
+
+108
+00:08:30,610 --> 00:08:34,850
+أجمع العناصر و أجسمهم على عددهم على 6، مصبوط؟ بقى
+
+109
+00:08:34,850 --> 00:08:38,930
+بالـ Median القيمة اللي بتيجي في النص بما أن
+
+110
+00:08:38,930 --> 00:08:42,570
+الأعداد اللي عندي هان أعداد عدد العناصر أو عدد
+
+111
+00:08:42,570 --> 00:08:46,770
+البن زوجي مافيش قيمة في النص، فهجيب الـ Average
+
+112
+00:08:46,770 --> 00:08:51,410
+تبعت القيمتين اللي في النص تلاتة و تلاتة، بقى أنا
+
+113
+00:08:51,410 --> 00:08:55,490
+هتكلم بالـ Median تلاتة
+
+114
+00:08:55,490 --> 00:09:00,830
+و تلاتة ستة على اتنين، تلاتةمعناته الآن كل البن
+
+115
+00:09:00,830 --> 00:09:05,450
+هذه بدون يعملها replacement بمين؟ بالتلاتة ..
+
+116
+00:09:05,450 --> 00:09:07,710
+تلاتة .. تلاتة .. تلاتة .. تلاتة .. تلاتة .. تلاتة
+
+117
+00:09:07,710 --> 00:09:07,950
+.. تلاتة .. تلاتة .. تلاتة .. تلاتة .. تلاتة ..
+
+118
+00:09:07,950 --> 00:09:08,030
+تلاتة .. تلاتة .. تلاتة .. تلاتة .. تلاتة .. تلاتة
+
+119
+00:09:08,030 --> 00:09:08,990
+.. تلاتة .. تلاتة .. تلاتة .. تلاتة .. تلاتة ..
+
+120
+00:09:08,990 --> 00:09:10,670
+تلاتة .. تلاتة .. تلاتة .. تلاتة .. تلاتة .. تلاتة
+
+121
+00:09:10,670 --> 00:09:11,390
+.. تلاتة .. تلاتة .. تلاتة .. تلاتة .. تلاتة ..
+
+122
+00:09:11,390 --> 00:09:19,130
+تلاتة .. تلاتة .. تلاتة .. تلاتة ..
+
+123
+00:09:19,130 --> 00:09:25,690
+تلاتة .. تلاتة .. تل
+
+124
+00:09:26,510 --> 00:09:30,190
+أقول لك شغلاء حتى لو كانت لو كانت ال value تبعتي
+
+125
+00:09:30,190 --> 00:09:36,070
+هذه مش اتناش بدي أخليها واحد وعشرين عشان يكون في
+
+126
+00:09:36,070 --> 00:09:42,950
+عندي out layer حقيقي وانا بدي ايش اخلص منه الان
+
+127
+00:09:42,950 --> 00:09:46,790
+مين عند ال error او ال error واضح وين يا شباب واضح
+
+128
+00:09:46,790 --> 00:09:51,710
+عندى في السالب لأن القيم كلهم موجبة كل القيم موجبة
+
+129
+00:09:51,710 --> 00:09:56,070
+باستثناء السالب واحدوكلها أقاينها حوالين العشرة
+
+130
+00:09:56,070 --> 00:10:01,770
+باستثناء ال 21 هاي ليش أنا جيبت المثال ده بالتحديد
+
+131
+00:10:01,770 --> 00:10:05,190
+عشان أقولك انتبه مش كل الخيارات ممكن تكون مناسبة
+
+132
+00:10:05,190 --> 00:10:10,310
+لك الآن بال mean وال median أنا خلصت وانحلت التمام
+
+133
+00:10:10,310 --> 00:10:14,070
+وراحت ال error زالت لكن لو أنا بدأ أشغل بال
+
+134
+00:10:14,070 --> 00:10:17,190
+boundary point بدأ أشغل على ال boundaries
+
+135
+00:10:26,090 --> 00:10:29,110
+حيظلوا موجودات في وجهي حيظلوا موجودات في ال data
+
+136
+00:10:29,110 --> 00:10:33,450
+set على الرغم إن هما ال outliers اللي أنا كنت عمال
+
+137
+00:10:33,450 --> 00:10:37,250
+بحاول أخلص منه أو بين جثين ال noise data اللي كنت
+
+138
+00:10:37,250 --> 00:10:42,510
+بحاول أخلص منها، مصبوط؟ فانت بدأت تنتبه، تنتبه إنه
+
+139
+00:10:42,510 --> 00:10:47,130
+أنا مش كل واحدة تسبق معايا، الآن اللي حيصير كتالي
+
+140
+00:10:47,130 --> 00:10:52,230
+سلب واحد، سلب اتنين أقرب لسلب واحد ولا للخمسة؟لأ
+
+141
+00:10:52,230 --> 00:10:56,470
+سالب واحد معناته هي سالب واحد سالب واحد التلاتة
+
+142
+00:10:56,470 --> 00:11:03,870
+لسالب واحد ولا خمسة لأ خمسة خمسة خمسة خمسة هان ستة
+
+143
+00:11:03,870 --> 00:11:12,450
+هان ستة ستة ستة ستة ستة ستة واحد وعشرين لاحظ ال
+
+144
+00:11:12,450 --> 00:11:14,910
+out layer بدل ما اخلص منها او ال noise ده بدل ما
+
+145
+00:11:14,910 --> 00:11:19,960
+اخلص منها عززتها كمان واحدةفانت بقتنطبه مش دائما
+
+146
+00:11:19,960 --> 00:11:25,020
+الخيارات هذه بتكوناش perfect بالنسبة لي فانت بتشوف
+
+147
+00:11:25,020 --> 00:11:29,380
+الخيار الأمثل في التعامل تمام وبالتالي خلصنا من
+
+148
+00:11:29,380 --> 00:11:32,480
+الموضوع ال binning طبعا ال binning زي ما انت شايف
+
+149
+00:11:32,480 --> 00:11:36,360
+موضوع بسيط سهل ممكن انا اسيطر عليه بشوية انتباه
+
+150
+00:11:36,360 --> 00:11:41,480
+وتركيز في التعامل الطريقة التانية ان اتخلص من ال
+
+151
+00:11:41,480 --> 00:11:45,040
+noise data ان انا اعمل regression شو يعني
+
+152
+00:11:45,040 --> 00:11:50,520
+regression؟هي عبارة عن الـ predictive task مصبوط
+
+153
+00:11:50,520 --> 00:11:55,340
+بحيث أن أصل على formula أو model يقدر يتنبأ بالقيم
+
+154
+00:11:55,340 --> 00:11:59,720
+زي ما بقول محمد by value الآن لو أنا أجيت و قلتلك
+
+155
+00:11:59,720 --> 00:12:05,860
+النقاط هذه المرسومة قدامي هي بتمثل ال data set
+
+156
+00:12:05,860 --> 00:12:11,260
+تبعتي لاحظ النقاط كلها جاية تمام حوالين الخط هذا
+
+157
+00:12:11,260 --> 00:12:19,800
+باستثناء النقطة اللي جاية هنابصبت؟ ليش جايها؟ لأن
+
+158
+00:12:19,800 --> 00:12:23,520
+فيها noise القيمة تبعتها فيها outlier أو فيها
+
+159
+00:12:23,520 --> 00:12:28,520
+noise معينة فخلتها بعيدة واحدة من الطرق تبعت ال
+
+160
+00:12:28,520 --> 00:12:32,140
+noise handling أو noise data handling ان انا اعمل
+
+161
+00:12:32,140 --> 00:12:35,000
+estimation او اعمل prediction لل regression
+
+162
+00:12:35,000 --> 00:12:41,300
+function او ال line model تبعتي ال line function
+
+163
+00:12:41,300 --> 00:12:45,200
+تبعتي بحيث ان انا ارسم الخط مستقيم اللي بيمثل كل
+
+164
+00:12:45,200 --> 00:12:51,010
+ال dataأرسم خط مستقيم يمثّل كل ال data والخط
+
+165
+00:12:51,010 --> 00:12:56,230
+المستقيم هذا له معادلة الآن بناء على قيمة X اللي
+
+166
+00:12:56,230 --> 00:13:01,190
+عندي هان اللي هي ثابتة بقدر أعمل estimation لمين
+
+167
+00:13:01,190 --> 00:13:06,250
+لقيمة Y الصحيحة هل هذا أنا بدي أطبقه على كل ال
+
+168
+00:13:06,250 --> 00:13:16,160
+data لأ فقط على ال noise data noisy pointوبالتالي
+
+169
+00:13:16,160 --> 00:13:20,580
+هذه القيمة هتطلع وين؟ معايا على الخط وبالتالي
+
+170
+00:13:20,580 --> 00:13:27,120
+هتاخد Y جديدة الفكرة أن الوصول لل regression model
+
+171
+00:13:27,120 --> 00:13:36,520
+هذا أو معادلة الخط المستقيم هي
+
+172
+00:13:36,520 --> 00:13:41,260
+بحد ذاتها data mining task predictive data mining
+
+173
+00:13:41,260 --> 00:13:45,900
+task عشان أعمل estimation لهلـ Value لـ Numeric
+
+174
+00:13:45,900 --> 00:13:49,180
+Value، مظبوط؟ لكن هذه واحدة من القرق اللي ممكن
+
+175
+00:13:49,180 --> 00:13:52,200
+برضه اطبقها انا عندى وها احنا عادة بنسميها احنا
+
+176
+00:13:52,200 --> 00:13:59,000
+Supervised Handling الشغل التالتة او الطريقة
+
+177
+00:13:59,000 --> 00:14:01,740
+التالتة اللي ممكن اعتمد عليها انا موضوع ال
+
+178
+00:14:01,740 --> 00:14:04,120
+clustering ال clustering اللي هي عبارة عن
+
+179
+00:14:04,120 --> 00:14:07,820
+descriptive task في ال data mining تقسيم ال data
+
+180
+00:14:07,820 --> 00:14:13,090
+set لمجموعة منلمجموعات من العناصر مجموعات عفوا
+
+181
+00:14:13,090 --> 00:14:17,270
+مجموعات من العناصر الآن بالصورة هذه واضح ان ال
+
+182
+00:14:17,270 --> 00:14:19,790
+data set تاني قدرت ان نشكلها في تلت مجموعات او
+
+183
+00:14:19,790 --> 00:14:23,610
+نحطها في تلت مجموعات العناصر اللي برا المجموعات
+
+184
+00:14:23,610 --> 00:14:29,930
+هذه ايش تمثل؟ تمثل noise data ممكن تكون outlier
+
+185
+00:14:29,930 --> 00:14:33,450
+صحيح هي outlier بالنسبة لل cluster لكن لل general
+
+186
+00:14:33,450 --> 00:14:36,030
+trend اللي موجود عندك هي مش outlier مش بعيدة كتير
+
+187
+00:14:36,030 --> 00:14:40,560
+يعني ال point هذه هي أقرب لل cluster هذاالـ
+
+188
+00:14:40,560 --> 00:14:43,580
+Outlier فعلياً يا شباب هي نقطة ممكن تكون موجودة
+
+189
+00:14:43,580 --> 00:14:49,200
+هنا بالنسبة للرسمة Outlier يعني نقطة شاذة، لو كانت
+
+190
+00:14:49,200 --> 00:14:52,860
+هذه نقطة واحدة، هذه النقطة فقط هي الموجودة وباقي
+
+191
+00:14:52,860 --> 00:14:56,780
+النقاط اللي برا هذه مش موجودة، بقول عنها Outlier،
+
+192
+00:14:56,780 --> 00:15:01,300
+لكن الآن بما أنه بمثل noise data، قاعد بأتكلم عليه
+
+193
+00:15:01,300 --> 00:15:08,840
+مجموعة من العناصر، الآن قدامي حل من اتنيناما اعتمد
+
+194
+00:15:08,840 --> 00:15:12,140
+فقط على ال data set أو ال elements أو ال samples
+
+195
+00:15:12,140 --> 00:15:16,380
+اللي في داخل ال clusters التلاتة هدول بعد ما عملت
+
+196
+00:15:16,380 --> 00:15:20,820
+clustering و اتجهل او اعمل delete لكل ال noise
+
+197
+00:15:20,820 --> 00:15:25,280
+data هاي بس فعليا أنا قاعد بدحّب عدد كبير من ال
+
+198
+00:15:25,280 --> 00:15:29,520
+data set ولا لأ؟لأ، الحل التاني إن ممكن أنا أستخدم
+
+199
+00:15:29,520 --> 00:15:33,920
+الـ Common Sense أو أروح أفحص كل واحدة فيهم بشكل
+
+200
+00:15:33,920 --> 00:15:38,660
+مستقل إيش الـ Outlier Value أو إيش الـ Noise
+
+201
+00:15:38,660 --> 00:15:41,260
+عفواً، إيش الـ Noise Value اللي خلتها بعيدة عن ال
+
+202
+00:15:41,260 --> 00:15:45,640
+cluster هذي حتما ال point هذه أقرب ل cluster هذا
+
+203
+00:15:45,640 --> 00:15:49,220
+من هذا، قصده ولا لأ؟ إيش اللي خلاها بعيدة هنا؟
+
+204
+00:15:49,220 --> 00:15:52,160
+هتلاقي في Single Value موجودة في attribute معين
+
+205
+00:15:52,160 --> 00:15:57,110
+ممكن هذه أروح أعملها Adjustment و أضيفها لمين؟للـ
+
+206
+00:15:57,110 --> 00:15:59,890
+cluster اللي موجود عشان مضحيش بال data لكن لو كانت
+
+207
+00:15:59,890 --> 00:16:03,410
+نقطة أو تنتين ومش قادرة تحاول تعملهم handling ضمن
+
+208
+00:16:03,410 --> 00:16:06,990
+العدد الكبير اللي موجود عندي هنا فممكن تحذفهم و
+
+209
+00:16:06,990 --> 00:16:11,130
+تخلص الان في ال clustering و بتحديدا مع ال
+
+210
+00:16:11,130 --> 00:16:15,390
+visualization سواء كنت في ال regression أو بال
+
+211
+00:16:15,390 --> 00:16:19,790
+clustering لاحظ الرسمة كانت بتخدمني بشكل كبير في
+
+212
+00:16:19,790 --> 00:16:23,790
+موضوع كده أفهم ال data اللي موجود عندي وقدرت أحدد
+
+213
+00:16:23,790 --> 00:16:30,640
+من ال outlierبكل بساطة وهيك بتكون خلصنا من معالجة
+
+214
+00:16:30,640 --> 00:16:36,220
+ال noise data خلصنا من معالجة ال noise data في ال
+
+215
+00:16:36,220 --> 00:16:40,580
+inconsistent data inconsistent data غير متناسقة
+
+216
+00:16:40,580 --> 00:16:48,580
+عمره 40 سنة و تاريخ ميلاده 1990 male و pregnant
+
+217
+00:16:48,580 --> 00:16:56,540
+مولود في 1900 وخشبة و طالب سنة أولى ابتدائيفهذه
+
+218
+00:16:56,540 --> 00:17:00,960
+المعلومات هي الـ Inconsistent تتوقع ممكن تلاقي
+
+219
+00:17:00,960 --> 00:17:08,700
+system في الدنيا يحددلك إياها؟
+
+220
+00:17:08,700 --> 00:17:12,540
+أيوة، يعني بدك يكون فعليا Dedicated System تم
+
+221
+00:17:12,540 --> 00:17:16,300
+إنشاء نظام للحالات اللي زي هذه وحط ال rules زي ما
+
+222
+00:17:16,300 --> 00:17:21,400
+عمله بجول كريم بس الآن في موضوع المال و pregnant
+
+223
+00:17:21,400 --> 00:17:26,250
+الحامل للذكور هل هذا وارد؟في عمر واحد عاجل بيفكر
+
+224
+00:17:26,250 --> 00:17:30,070
+يبني rule زي هيك عشان يدور لأنه الأصل لأ، لكن في
+
+225
+00:17:30,070 --> 00:17:34,270
+لحظة من اللحظات ممكن أنا أضطر أكتب rule عشان يحل
+
+226
+00:17:34,270 --> 00:17:37,750
+أو يدورلي على الحالات اللي زي هذه، بس فعليا مش
+
+227
+00:17:37,750 --> 00:17:42,370
+هتلاقيه بسهولة، انت بتعمله development الشغل ال
+
+228
+00:17:42,370 --> 00:17:47,490
+manual أحسن لأن هذه ال cases قليلة جدا، تمام؟
+
+229
+00:17:47,490 --> 00:17:52,880
+وغالبا هتختلف من حالة لحالةلكن احنا بنقول لو فرضا
+
+230
+00:17:52,880 --> 00:17:57,200
+ان الحالة هذه ممكن تتكرر ايش بروح بساوي ممكن
+
+231
+00:17:57,200 --> 00:18:00,440
+ابنيلها system بسيط يعمل ال check تماما زي اللي
+
+232
+00:18:00,440 --> 00:18:05,240
+بتكلم عن ال spelling check programs الان الخطاء
+
+233
+00:18:05,240 --> 00:18:08,720
+الإملئي أثناء الكتابة ايش هو مش هو عبارة عن برنامج
+
+234
+00:18:08,720 --> 00:18:13,780
+عنده موجود الكلمات بين جثين ال rules وبروح بصير
+
+235
+00:18:13,780 --> 00:18:18,760
+يقارنها بعضهم راح يقولك في عندك grammar checkبدي
+
+236
+00:18:18,760 --> 00:18:21,720
+أعرف قوانين الكتابة وصياغة اللغة وهنا نفس الكلام
+
+237
+00:18:21,720 --> 00:18:28,320
+بدي أصير أنا أكون عارف وين ال inconsistency بتصير
+
+238
+00:18:28,320 --> 00:18:30,600
+بين ال attributes وصير أحطها في rules عشان يعملها
+
+239
+00:18:30,600 --> 00:18:34,740
+detection لكن هذا الكلام صعب وصعب جدا احنا بدنا
+
+240
+00:18:34,740 --> 00:18:38,460
+نعمل focus على الشغل لكن ممكن المعنى والهدا مهم
+
+241
+00:18:38,460 --> 00:18:43,440
+جدا عشان هيك عشان هيك أول واحدة في معالج ال
+
+242
+00:18:43,440 --> 00:18:49,580
+inconsistent data ال common senseتستخدم المنطق
+
+243
+00:18:49,580 --> 00:18:53,980
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+كمان مرة يا جماعة الخير ال common sense لازم تكون
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+اتكلم بال hands up
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+حمزة مكسورة، حمزة مفتوحة، حمزة مضمومة والإنجليز
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+259
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+بس هذا الكلام وارد عشان تقدر توافق على سبيل المثال
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+00:20:06,390 --> 00:20:10,210
+في ال integration لما نجيه كمان شوية بدي أجمع two
+
+261
+00:20:10,210 --> 00:20:13,470
+datasets مع بعضهم لجيت رقم واحد، اتنين، تلاتة،
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+أربعة واسمه Dennis، الاسم الأولورقمه في الـ Data 6
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+اللي جاي من وزارة الصحة 1234 والاسم مكتوب Dennis
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+بالـ Spelling التاني هجول لا لا هدول الـ Two
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+غلط بصبت؟ يعني الآن لجيت Two Records نفسه الـ ID
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+1234 و1 خليل و2 حسن
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+طيب
+
+276
+00:21:20,090 --> 00:21:24,030
+كيبك تصلحها؟ كيبك تصلح الـ inconsistent data؟
+
+277
+00:21:24,030 --> 00:21:30,910
+Manual، بعد ما أحددها، بدي أحددها أصلحها إيش؟
+
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+Manual، يعني لازم أرجع لل documents و أقارن ال
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+00:21:34,190 --> 00:21:38,090
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+زبائن بنك معين و لجيت 5% منهم كلهم مولودين في 112
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+فالمية من الطلاب الموجودين بيننا الآن في المحاضرة
+
+284
+00:21:58,570 --> 00:22:01,290
+في ال data mining من موريد الف وتسعمائية وخشبة
+
+285
+00:22:01,290 --> 00:22:04,790
+مستحيل
+
+286
+00:22:06,190 --> 00:22:10,250
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+لل document الحقيقي عشان انا اعمل ال check على ال
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+الـ Consistency تبع الـ Data و تحديد الـ
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+294
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+Inconsistent Values الـ Metadata ليش؟
+
+295
+00:22:46,440 --> 00:22:48,820
+لأن في الـ Metadata باجي أتكلم على الـ Domain و
+
+296
+00:22:48,820 --> 00:22:51,300
+الـ Range و الـ Dependency و الـ Distribution تبع
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+الـ Attributes بيجي يقولني والله عندي ال salary
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+ال inconsistent data بدي أفحص ال field overloading
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+أو ال field overloading شو يعني overloading؟بالـ
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+بعد هيك احنا قلنا للوصول لل knowledge presentation
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+data mining الـ transformation بالمناسبة قبل ال
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+selection مش قضية كتير data mining knowledge
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+knowledge evaluation أو better evaluation و
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+knowledge presentation تمام الآن بدنا ننتقل لل
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+task التانية مباشرة اللي هي ال dataIntegration
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+يعني احنا بفهم بناء على الخطوة هاي إذا كان في عندي
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+two من different resources الأصل .. الأصل أن أعمل
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+cleaning لتنتين جبل ما أعمل integration ليش؟
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+لأنه فعليا احنا مش بحاجة ال null حتصير في عندي
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+السليم يعني في مرحلة ما بعد ال cleaning عشان اضمن
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+يصير في عندي combination صح لل data set الآن
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+346
+00:26:58,000 --> 00:27:00,440
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+كتير كاسمتقدير تحصيل الطالب أو مستوى تحصيل الطالب
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+في المرحلة الابتدائية بناء على الحالة الصحية،
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+00:27:18,730 --> 00:27:23,810
+resources تربية و التعليم و الصحة و بدي اعمل
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+الأول انه انا في عندي smalldata set small
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+00:27:58,220 --> 00:28:05,820
+samples، مظبوط؟ الشغل
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+more information for
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+عليه أنا عنده معلومات خاصة بالمدرسة و بالتعليم سجل
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+لأن هان مش هعمل على ال enlargement لل data set مش
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+00:29:01,940 --> 00:29:05,460
+هزيد عدد ال rows هزيد عدد ال attributes
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+ID
+
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+وزارة التدريب والتعليم في وزارة الصحة مافيش
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+اهم مافيش
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+height illness هل في أمراض ولا لأ هل بتدناول أدوية
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+ولا لأ treatment إلى آخره الأهم أنا بدي أعمل
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+prediction لمستوى تحصيل الطالب بناء على سجله الصحي
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+تمام هذا ال raw أو ال data set بدها تكون هنا وكأني
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+بكل بساطة بدي اعمل inner join بين two tables فهذه
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+ال combination كان هدفها او هذه ال integration
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+هدفها اضافة معلومات جديدةلكل entity لكل sample لأن
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+عشان تتحقق ال task الموجودة لكن لو قلنا والله أن
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+الطالب هذا كان فترة الإبتدائي عايش أو بدرس في
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+مدرسة خاصة أو مدرسة خاصة والمعلومات هذه ماكنتش
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+00:31:46,520 --> 00:31:50,560
+موجودة في وزارة الصحة وقدرنا نحصل المعلومات هذه من
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+المدرسة وين بدها تنضاف؟ بدها تنضاف record 10 بدها
+
+399
+00:31:57,880 --> 00:32:05,910
+تنضافrecord هان تمام وبالتالي مصادر البيانات تبعتي
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+400
+00:32:05,910 --> 00:32:10,750
+انا تصنف على واحد من اتنين اما internal او
+
+401
+00:32:10,750 --> 00:32:14,390
+external internal لما انا بكون as a developer او
+
+402
+00:32:14,390 --> 00:32:19,890
+data scientist شغال والمعلومات هذه ملكي يعني انا
+
+403
+00:32:19,890 --> 00:32:23,530
+شغال في وزارة التربية والتعليم وبدنا نشتغل على كذا
+
+404
+00:32:23,530 --> 00:32:27,790
+هذه المعلومات عندى موجودة في ال database تبعتي
+
+405
+00:32:29,690 --> 00:32:33,650
+تمام؟ هذه بنسميها Internal Source طب و ال External
+
+406
+00:32:33,650 --> 00:32:37,930
+Source أنه أنا فعليا بيانات بدي أحاول أستعيد ..
+
+407
+00:32:37,930 --> 00:32:42,690
+ممكن أدفع حجها أحيانا أحصل عليها من برا الآن
+
+408
+00:32:42,690 --> 00:32:47,870
+بالنسبة إيه للبيانات في وزارة الصحة External ..
+
+409
+00:32:47,870 --> 00:32:54,370
+الآن لما بدك .. روحت الآن ال ..يتكلموا على الشركات
+
+410
+00:32:54,370 --> 00:32:58,270
+الإتصالات والبنوك والـ Credit Cards والمعاملات مش
+
+411
+00:32:58,270 --> 00:33:03,170
+كل المعلومات Local مصبوط؟ بنك فلسطين الآن Local
+
+412
+00:33:03,170 --> 00:33:05,990
+لما أنا بكون جوا فلسطين و بستخدم ال ATM تبعته
+
+413
+00:33:05,990 --> 00:33:09,690
+بأنتقل باستخدام ATM بتاعة البنك الإسلامي الفلسطيني
+
+414
+00:33:09,690 --> 00:33:14,440
+أو العربي بديت فيه عندي Transaction Externalكنت في
+
+415
+00:33:14,440 --> 00:33:17,440
+دولة تانية و استخدمت بطاقة بنك فلسطين برضه فيها
+
+416
+00:33:17,440 --> 00:33:20,800
+عندى external data وإن كان حصير فيه hint أو فيه
+
+417
+00:33:20,800 --> 00:33:25,400
+عندى مقاصة لل value اللى موجودة مش قضية كتير بس
+
+418
+00:33:25,400 --> 00:33:28,320
+احنا بدنا نفهم انه فيه عندى ال data تصنف بناء على
+
+419
+00:33:28,320 --> 00:33:35,540
+مصدرها وعادة التعامل مع ال internalأسهل من ال
+
+420
+00:33:35,540 --> 00:33:39,580
+external لأن عادة ال internal أنا فاهمها كويس عارف
+
+421
+00:33:39,580 --> 00:33:43,540
+إيش محتوياتها عارف إيش عيوبها بالتفصيل و بقدر لكن
+
+422
+00:33:43,540 --> 00:33:47,700
+اللي برا تحتاج مني جهد أكتر و غالبا ما هي مش على
+
+423
+00:33:47,700 --> 00:33:52,420
+مزاجي فحتى عب عليها كويس في موضوع ال integration
+
+424
+00:33:52,420 --> 00:33:58,400
+ضروري تنتبه لل identity identification أنا قبل
+
+425
+00:33:58,400 --> 00:34:03,000
+شوية قلت اسمه واحد اتنين تلاتة أربعة و مرة أحمد
+
+426
+00:34:04,240 --> 00:34:10,340
+ومرة تانية خليل اعمل
+
+427
+00:34:10,340 --> 00:34:14,960
+merge لل two rows هذول يعني اسمه هان واحد اتنين
+
+428
+00:34:14,960 --> 00:34:21,900
+تلاتة اربعة احمد وانا واحد اتنين تلاتة اربعة خليل
+
+429
+00:34:21,900 --> 00:34:27,740
+وانا بقعد بدي اعمل integration بين ال two datasets
+
+430
+00:34:27,740 --> 00:34:35,440
+هذول شو رايكوا اذا انا بدي اعتمد على ال ID هيهال
+
+431
+00:34:35,440 --> 00:34:40,940
+ID بيقوللي ادمج نصبوت؟ ال ID بيقوللي ادمج اذا كنت
+
+432
+00:34:40,940 --> 00:34:43,680
+انا بدي اعتمد فقط على ال primary key بيقوللي ادمج
+
+433
+00:34:43,680 --> 00:34:49,180
+بس في شغل عاملها بتقوللي لا ايجف يعني هذا شخص ممكن
+
+434
+00:34:49,180 --> 00:34:55,240
+يكون غيره شو بيطلب مني هذا الكلام؟ خلصنا من ال
+
+435
+00:34:55,240 --> 00:34:58,300
+noise شو بيطلب مني هذا الكلام؟ انا الآن مش عارف
+
+436
+00:34:58,300 --> 00:35:02,340
+مين فيهم ال noise داتا اذا كانت بتتكلمي تمام؟
+
+437
+00:35:02,340 --> 00:35:04,540
+ignore ال record ممتاز
+
+438
+00:35:06,980 --> 00:35:10,280
+طيب ليش ما تفكر انه ليش ما يكون في وزارة الصحة
+
+439
+00:35:10,280 --> 00:35:15,060
+مجدمين اسم العائلة مثلا يعني احنا هنعتمدنا على ال
+
+440
+00:35:15,060 --> 00:35:17,500
+first name هو اسم العائلة وبالتالي مازالين بس
+
+441
+00:35:17,500 --> 00:35:21,140
+اتحقق شو هو بقى الأسامي اللي موجودة انا أخدتها
+
+442
+00:35:21,140 --> 00:35:25,860
+الان انتبه انا بدي الاسم الأول او بدي ال full name
+
+443
+00:35:25,860 --> 00:35:30,320
+الان في حياة ال full name و ال full name مختلفين و
+
+444
+00:35:30,320 --> 00:35:34,020
+ال ID واحد لسه ما زلت انا بدي احاول اتشبث بال
+
+445
+00:35:34,020 --> 00:35:38,850
+recordو أخلّيه عندى بأكبر قدر ممكن باطلّع على باقي
+
+446
+00:35:38,850 --> 00:35:45,530
+مثلا باطلّع على ال age 17 17 إذا هل في common
+
+447
+00:35:45,530 --> 00:35:49,910
+attributes بين التنين بيأكدولي إن هذا هو نفسه هذا
+
+448
+00:35:49,910 --> 00:35:53,810
+ممكن أصيب أتجوز عن من؟ عن الإسم لأنه فعلا الإسم مش
+
+449
+00:35:53,810 --> 00:35:57,690
+هيخدمني بس أنا حاليا بدي أتأكد إن هذا real entity
+
+450
+00:35:57,690 --> 00:36:01,910
+موجودة عندى في ال data set هذه بنسميها ال entity
+
+451
+00:36:01,910 --> 00:36:03,550
+identification
+
+452
+00:36:05,840 --> 00:36:08,740
+الproblem ال value of conflict او ال value
+
+453
+00:36:08,740 --> 00:36:17,860
+conflict التعارض ما بين القيم لجيت عمره هان 17 و
+
+454
+00:36:17,860 --> 00:36:27,520
+هان لجيته 15 انا في الآخر هحتفظ ب one edge مظبوط؟
+
+455
+00:36:27,520 --> 00:36:32,840
+يعني غالبا ال edge هان مش هجيب ليه طب باس مين فيهم
+
+456
+00:36:32,840 --> 00:36:36,900
+الصح؟الخمسة عشر ولا السبعتاشر؟ ال date of birth
+
+457
+00:36:36,900 --> 00:36:43,760
+هنا موجود قاللي والله انه تاريخ ميلاده هذا الفين
+
+458
+00:36:43,760 --> 00:36:48,180
+وخمسة واحنا الفين وعشرين ميلاده خمسة عشر ميلاده
+
+459
+00:36:48,180 --> 00:36:52,240
+الخطأ عندي هنا وهذا بتطلب برضه مني manual
+
+460
+00:36:52,240 --> 00:36:56,860
+correctness عشان اعدي ال level ممكن يكون عندي
+
+461
+00:36:56,860 --> 00:37:01,120
+indicatorطبعا لكن بيظل فيه احتمال ان هو فعليا ايش
+
+462
+00:37:01,120 --> 00:37:04,600
+يكون مثلا اتأخر سنة او رصب سنة او ما شابه لكن ال
+
+463
+00:37:04,600 --> 00:37:08,140
+date of birth كان بيقول لأ يا اما هو متأكد لان هو
+
+464
+00:37:08,140 --> 00:37:12,420
+بيقطفيه تقابق ما بين ال values ال redundant
+
+465
+00:37:12,420 --> 00:37:21,100
+teachers انا مافيش عندي ال age هنا لكن
+
+466
+00:37:21,100 --> 00:37:26,140
+عنديdate of birth تاريخ الميلاد لما انا اعمل
+
+467
+00:37:26,140 --> 00:37:30,140
+marriage تاريخ الميلاد هيجينيها ك attribute لكن
+
+468
+00:37:30,140 --> 00:37:35,220
+المعلومات اللي فيها موجودة عندى سابقا فبرضه انا
+
+469
+00:37:35,220 --> 00:37:38,820
+بدى أنتبه لها يعني في عندى تلت شغلات أساسية بدى
+
+470
+00:37:38,820 --> 00:37:42,320
+أنتبه لعندي عملية ال integration اتأكد من ال
+
+471
+00:37:42,320 --> 00:37:46,020
+identification لكل entity اللي فعليا ال entity
+
+472
+00:37:46,020 --> 00:37:51,340
+تقابل ال entity المقابلة بتاعتها بشكل صحيحالـ
+
+473
+00:37:51,340 --> 00:37:54,300
+value conflict أو الـ inconsistent اللي ممكن تصير
+
+474
+00:37:54,300 --> 00:37:56,660
+عندي زي ما صار معايا في الاسم أو صار معايا في ال
+
+475
+00:37:56,660 --> 00:38:02,380
+age وفي الآخر في ال redundant features أو في تكرار
+
+476
+00:38:02,380 --> 00:38:08,060
+ال attributes اللي موجودة عندي وبرضه الشغل هيكون
+
+477
+00:38:08,060 --> 00:38:13,740
+manual ممكن اكتب code عشان يعمل integration لو انت
+
+478
+00:38:13,740 --> 00:38:17,820
+طبقت عملت ال inner join بين ال two tables هدول ايش
+
+479
+00:38:17,820 --> 00:38:24,280
+اللي بصير؟بياخد ال rows بناء على ال ID ال ID
+
+480
+00:38:24,280 --> 00:38:29,920
+المختلف بين التنين مابيطلعش يعني تخيل ان هنا واحد
+
+481
+00:38:29,920 --> 00:38:36,660
+اتنين تلاتة تسعة مافيش هنا وهنا عندي واحد اتنين
+
+482
+00:38:36,660 --> 00:38:42,860
+تلاتة تمانية مش موجود هنا هذا ال row مش هيظهر وهذا
+
+483
+00:38:42,860 --> 00:38:47,200
+ال row مش هيظهر ولا لأ؟ ليش؟ لأن فعليا مافيش
+
+484
+00:38:47,200 --> 00:38:51,220
+integration ما بين ال rows اللي موجودةلكن لاحظوا
+
+485
+00:38:51,220 --> 00:38:55,760
+المشكلة دي انا ماعانيت منها مطلقا لما روحت جيبت
+
+486
+00:38:55,760 --> 00:39:00,260
+مصدر تاني للبيانات وصرت اجمعها عشان ازيد مين؟ عدد
+
+487
+00:39:00,260 --> 00:39:04,000
+الروز لان في الآخر انا جيبت من المدرسة الخاصة جيبت
+
+488
+00:39:04,000 --> 00:39:08,180
+ال name و ال age و ال level و ال GPA لمجموع الطلاب
+
+489
+00:39:08,180 --> 00:39:13,120
+عشان ازيد ازيد محصلة الروز اللي موجودة عندها
+
+490
+00:39:19,090 --> 00:39:24,050
+هننتقل الآن لموضوع الـ Data Transformation اللي هي
+
+491
+00:39:24,050 --> 00:39:30,150
+الخطوة الرب العد ايوة أهب تفضل اسأل مثلا زي
+
+492
+00:39:30,150 --> 00:39:33,850
+الميديا اللي جيت العالم الأول بسيط هجيته فعلا فعلا
+
+493
+00:39:33,850 --> 00:39:37,070
+هذا مثلا الإنسان بدري يعمل بحث زي هيك هل فعلا مهتم
+
+494
+00:39:37,070 --> 00:39:41,430
+في ال record زي ما هذا ولا بس انه اتعلم الصحيح؟
+
+495
+00:39:41,430 --> 00:39:45,210
+شوفي أهب كل record بتضيفه على ال data set الأصل
+
+496
+00:39:45,210 --> 00:39:49,450
+بتضيف لك knowledge جديدة و بقوّي ال ruleأو الـ
+
+497
+00:39:49,450 --> 00:39:52,550
+predictors اللي انت بدك تنشئه عشان هيك فعليًا انت
+
+498
+00:39:52,550 --> 00:39:58,150
+محتاجه كل ما كانت عدد ال data set قليلة أو
+
+499
+00:39:58,150 --> 00:40:05,170
+المعلومات اللي عندك قليلة انت بحاجة لأي .. أي شغل
+
+500
+00:40:05,170 --> 00:40:08,730
+بتعزز البيانات اللي موجودة عندك حتى لو one record
+
+501
+00:40:08,730 --> 00:40:13,270
+بدك تضيفه لكن ال data set اللي عندي حجمها 100 ألف
+
+502
+00:40:13,270 --> 00:40:17,950
+recordولا جيت عشرة record أو ميت record أو ألف
+
+503
+00:40:17,950 --> 00:40:23,870
+record في مكان ما مش ضروري أفكر فيهم كتير إذا أنا
+
+504
+00:40:23,870 --> 00:40:26,450
+واثق في البيانات اللي عندي لكن لو كانوا الألف
+
+505
+00:40:26,450 --> 00:40:30,110
+record هدول بمثله حالة خاصة وانا بدي أدرجها في
+
+506
+00:40:30,110 --> 00:40:33,090
+النظام تبعتي لازم أعملها integration للميت ألف
+
+507
+00:40:33,090 --> 00:40:37,890
+اللي عندي وصيروا ميت ألف وواحد تمام؟ أو مية وواحد
+
+508
+00:40:37,890 --> 00:40:42,570
+ألف في موضوع ال transfer .. في أي شباب عنده ..
+
+509
+00:40:42,570 --> 00:40:48,020
+شباب في حد عنده أي سؤال تانيهننتقل لموضوع أو نكمل
+
+510
+00:40:48,020 --> 00:40:51,100
+في ال steps و بنحاول إن شاء الله الأسبوع هذا ننهي
+
+511
+00:40:51,100 --> 00:40:53,540
+ال chapter اللي احنا بنشتغل فيه لأنه صارنا قداشة
+
+512
+00:40:53,540 --> 00:40:55,320
+هذا الأسبوع التالت و احنا بنخد في ال data
+
+513
+00:40:55,320 --> 00:40:58,620
+understanding و ال preparation فبديش ياخد تحسه
+
+514
+00:40:58,620 --> 00:41:03,540
+بالملل فبنروح باتجاه ال mining إن شاء الله الآن في
+
+515
+00:41:03,540 --> 00:41:07,900
+ال data transformation المقصود فيها تحويل أو تحوير
+
+516
+00:41:07,900 --> 00:41:14,330
+البيانات من formمن صورتها الحالية اللى تظهر بصورة
+
+517
+00:41:14,330 --> 00:41:19,910
+تتناسب مع ال mining task عاما اللى احنا بنقول بقول
+
+518
+00:41:19,910 --> 00:41:22,430
+انا في عندى تاريخ الميلاد يا جماعة الخير date of
+
+519
+00:41:22,430 --> 00:41:22,750
+birth
+
+520
+00:41:27,040 --> 00:41:30,680
+القيم اللي موجودة فيه .. القيم اللي موجودة فيه
+
+521
+00:41:30,680 --> 00:41:35,760
+بتقول إذا أنا بدي أبني decision rules هيكون عندي
+
+522
+00:41:35,760 --> 00:41:39,580
+ال values كتيرة لأنه انولد في شهر واحد غير ان
+
+523
+00:41:39,580 --> 00:41:42,320
+انولد في شهر اتنين في عندى تلاتين خيار في شهر واحد
+
+524
+00:41:43,080 --> 00:41:49,060
+و28 في شهر 2 و 31 في شهر 3، مصبوط؟ معناته على مدار
+
+525
+00:41:49,060 --> 00:41:53,500
+السنة، يعني أنا بتكلم هيك وكأنه وكأنه عندي 365
+
+526
+00:41:53,500 --> 00:41:59,420
+variable أو value بدها تدخل في ال decision rules
+
+527
+00:41:59,420 --> 00:42:04,480
+تبعي هذاهذا الكلام مش منطق بينما كل الناس اللي في
+
+528
+00:42:04,480 --> 00:42:08,680
+مستوى أول مثلا أو في فئة الجامعة هدولة فئة واحدة
+
+529
+00:42:08,680 --> 00:42:12,260
+طلاب المدارس في الثانوية فئة تانية اللي من الإعداد
+
+530
+00:42:12,260 --> 00:42:16,880
+يو انزل فئة تالتة الخرجين فئة رابعة فهذه الفئات
+
+531
+00:42:16,880 --> 00:42:22,740
+تاريخ الميلاد هذا مابكفنيش يا راني تاريخ الميلاد
+
+532
+00:42:22,740 --> 00:42:27,460
+هذا مابنفعنيش فانا محتاج ان اغير صورة تاريخ
+
+533
+00:42:27,460 --> 00:42:28,120
+الميلاد
+
+534
+00:42:34,920 --> 00:42:42,620
+الى age بال age بكون انا عملت ايش قللت ال value
+
+535
+00:42:42,620 --> 00:42:46,360
+اللى موجودة قللت ال value اللى موجودة عندى
+
+536
+00:42:46,360 --> 00:42:53,260
+وبالتالي قللت ال decision rules تبعتي لكن لاحظ ان
+
+537
+00:42:53,260 --> 00:42:56,840
+تاريخ الميلاد و ال age اللى كتب معاه نفسه من ال
+
+538
+00:42:56,840 --> 00:43:04,190
+2005 و كتبت ال age 15 مافقدتش المعلومة تبعتيمصبوب؟
+
+539
+00:43:04,190 --> 00:43:07,090
+والأفضل من هيك لو جسمتم لفئات زي ما هنشوف كمان
+
+540
+00:43:07,090 --> 00:43:13,110
+شوية فمن ال data transformation method ل smoothing
+
+541
+00:43:13,110 --> 00:43:19,430
+method لما عملت pinning عبارة عن smoothing method
+
+542
+00:43:19,430 --> 00:43:24,190
+ال regression smoothing method بس هدفها الأساسي
+
+543
+00:43:24,190 --> 00:43:30,110
+تخلص من ال noise واحد يقول ليه ال smoothing
+
+544
+00:43:30,110 --> 00:43:33,650
+حطيناها من ال transformation؟ال data أخدت صور
+
+545
+00:43:33,650 --> 00:43:38,150
+مختلفة البن الأولى أخدت قيمة بدل كل القيم اللي
+
+546
+00:43:38,150 --> 00:43:42,810
+كانت في البن ايش أخدت؟ أخدت ال median او أخدت ال
+
+547
+00:43:42,810 --> 00:43:47,870
+mean أربعة فبالتالي القيم تغيرت كانت شكل وصارت شكل
+
+548
+00:43:47,870 --> 00:43:54,190
+آخر ال values اللي عندي كانت 17 مليون
+
+549
+00:43:57,970 --> 00:44:01,050
+الأرقام هذه كبيرة ما بتتناسبش مع ال computation
+
+550
+00:44:01,050 --> 00:44:06,770
+تبعتي فانا بدي أخليها 1.7 كذلك ال 18 وال 20 مليون
+
+551
+00:44:06,770 --> 00:44:13,410
+ال 20 صارت 2 و ال 1.5 صارت 15 و هكذا فهذا التحوير
+
+552
+00:44:13,410 --> 00:44:18,170
+ال data كانت في صورة وصارت في صورة مختلفة
+
+553
+00:44:22,870 --> 00:44:26,570
+God كان بهدف التخلص من الـ Noise، تمام؟ لكن
+
+554
+00:44:26,570 --> 00:44:30,010
+فعليًا، فعليًا الـ Data اللي صارت موجودة في الـ
+
+555
+00:44:30,010 --> 00:44:35,310
+Attribute هي عبارة عن New Transformation، تحور للـ
+
+556
+00:44:35,310 --> 00:44:38,830
+Data، مصدورة لا لأ؟ ضالت الـ Original Data؟ لأ،
+
+557
+00:44:38,830 --> 00:44:41,750
+فعليًا صار عليها تحور، عشان هيك ذكرناها أول واحدة،
+
+558
+00:44:41,750 --> 00:44:46,370
+لأنها مرت علينا سابقًا الـ Aggregation، أنا فعليًا
+
+559
+00:44:46,370 --> 00:44:50,810
+ممكن أروح أضيف أو أعمل شغلات، يعني الآن بروح بقولي
+
+560
+00:44:50,810 --> 00:44:56,410
+والله بدنا نحسبان نحاول نتنبأ ان الموظف الحكومي
+
+561
+00:44:56,410 --> 00:45:05,490
+بعد كام سنة ممكن يشتري بيت يا
+
+562
+00:45:05,490 --> 00:45:09,940
+عم الله يرزق الجميع من فضله ان شاء اللهأنا عند
+
+563
+00:45:09,940 --> 00:45:14,120
+الراتب الشهري لكن عادة الراتب الشهري مبلغ قليل
+
+564
+00:45:14,120 --> 00:45:17,620
+ماحدش بدور عليه في التعاملات اللي زي هذه بروح بده
+
+565
+00:45:17,620 --> 00:45:21,620
+الراتب السنوي طب أنا ماعنديش الراتب السنوي عند بس
+
+566
+00:45:21,620 --> 00:45:27,000
+الراتب الشهري بأضربه ب12 بأضربه ب12 مظبوط؟ ايش
+
+567
+00:45:27,000 --> 00:45:30,800
+سويت .. كل السنوات و أنا عملية ضرب بس فعليا نقلت
+
+568
+00:45:30,800 --> 00:45:36,070
+ال dataمن Range وحطتليها في Range مختلف وهذه برضه
+
+569
+00:45:36,070 --> 00:45:39,210
+Transformation فنسميها احنا Aggregation
+
+570
+00:45:39,210 --> 00:45:42,450
+Transformation او Aggregate Transformation
+
+571
+00:45:42,450 --> 00:45:46,530
+Generalization لما انا بأتكلم ان ال data ال set
+
+572
+00:45:46,530 --> 00:45:53,330
+تبعت فيه تتبع Hierarchy معينة زي ايش انا في عند ال
+
+573
+00:45:53,330 --> 00:46:00,930
+country وفي عندي ال set ال state وعندي
+
+574
+00:46:02,180 --> 00:46:08,860
+الـ city وعندي ال neighborhood الحي
+
+575
+00:46:08,860 --> 00:46:18,100
+وعندي ال street مثلا شو
+
+576
+00:46:18,100 --> 00:46:24,100
+علقت هدول في بعض الشارع عنوان تفصيل العنوان الشارع
+
+577
+00:46:24,100 --> 00:46:27,040
+موجود في حي و الحي موجود في مدينة و المدينة موجود
+
+578
+00:46:27,040 --> 00:46:32,290
+في ولاية و الولاية بتتبع دولةأنا الآن العنوان اللي
+
+579
+00:46:32,290 --> 00:46:39,890
+موجود عندي مكتوب لحالة مستوى الشارع غزة
+
+580
+00:46:39,890 --> 00:46:45,010
+الرمال شارع عمرو بن عبدالعزيز هذا بس عشان يُنذَكر
+
+581
+00:46:45,010 --> 00:46:52,070
+خلال اليومين الماضيات في الخبار طبعا؟ الآن طب هل
+
+582
+00:46:52,070 --> 00:46:55,150
+التفاصيل هذه بهمني أنا؟ طب ما هي ال redundant
+
+583
+00:46:55,150 --> 00:47:00,180
+value أو عفوا القيم الكتيرة المختلفة هذه؟برضه
+
+584
+00:47:00,180 --> 00:47:03,060
+بتصعب موضوع ال decision تبعتي طبما هي الرمال كلها
+
+585
+00:47:03,060 --> 00:47:09,420
+منطقة واحدة فانا بدي استغني عن ال street واصير
+
+586
+00:47:09,420 --> 00:47:13,760
+اتكلم على ال neighborhood وحتى ال neighborhood مش
+
+587
+00:47:13,760 --> 00:47:19,660
+فارج كبير رمال وشجعية مش فارج كتير تمام فانا هضطر
+
+588
+00:47:21,060 --> 00:47:24,080
+لاحظ انه لما انا بتكلم على transformation يا جماعة
+
+589
+00:47:24,080 --> 00:47:27,020
+الخير لاحظوا يا جماعة الخير انه لما انا بأعمل
+
+590
+00:47:27,020 --> 00:47:33,720
+transformation بحول ال value من street ل
+
+591
+00:47:33,720 --> 00:47:38,340
+neighborhood او ل city فقدت معلوماتش ايه؟ لأ هي
+
+592
+00:47:38,340 --> 00:47:41,220
+نفس المعلومات نفس ال representation بس انا مش
+
+593
+00:47:41,220 --> 00:47:44,200
+بحاجة ل two details هاي هذا برضه بنسميه
+
+594
+00:47:44,200 --> 00:47:48,810
+transformationالـ Normalization الـ Normalization
+
+595
+00:47:48,810 --> 00:47:56,310
+فعليًا أنا بده أروح أعمل Scaling لل Data Scaling
+
+596
+00:47:56,310 --> 00:47:59,710
+زي ما قلنا 17 مليون أو الأرقام اللي عندي كبيرة
+
+597
+00:47:59,710 --> 00:48:03,130
+فبده أروح أقللها أو بده أحطه ضمن Range معين وهنا
+
+598
+00:48:03,130 --> 00:48:07,910
+بدنا عمليات حسابية وهذه هروح لها بتفاصيل الآن الـ
+
+599
+00:48:07,910 --> 00:48:11,330
+Attribute Construction زي ما قلت أنا عندي تاريخ
+
+600
+00:48:11,330 --> 00:48:14,810
+الميلادو تاريخ الميلاد مابديش ايه بديش إياه بدي
+
+601
+00:48:14,810 --> 00:48:20,030
+أحط ال age أو بدي أبني الفئة العمرية و كل التفاصيل
+
+602
+00:48:20,030 --> 00:48:25,450
+هاي كلها عبارة عن different transformation لل data
+
+603
+00:48:25,450 --> 00:48:31,030
+كمان مرة transformation لا يعني إن أنا القيمة
+
+604
+00:48:31,030 --> 00:48:35,150
+تغيرت الجوهر ال value موجود لكن الصورة اللي ظهرت
+
+605
+00:48:35,150 --> 00:48:37,950
+عليها مختلفة
+
+606
+00:48:38,930 --> 00:48:44,390
+طيب، الآن بدنا نروح على الـ Transformation اللي له
+
+607
+00:48:44,390 --> 00:48:47,190
+علاقة بالـ Normalization لأن هنا في عندي
+
+608
+00:48:47,190 --> 00:48:50,770
+Mathematical Forms لازم أفهمها كويس و أفهم النتيجة
+
+609
+00:48:50,770 --> 00:48:53,910
+من كل واحدة فيهم كل الكلام اللي احنا قلناه سابقا
+
+610
+00:48:53,910 --> 00:48:57,380
+جربنا ال smoothingوالـ aggregation بسيطة هي عبارة
+
+611
+00:48:57,380 --> 00:49:00,480
+عن computation بسيطة ممكن تصير موجودة عندي و ال
+
+612
+00:49:00,480 --> 00:49:03,420
+generalization مافيش عليها شغل كتير زي ما احنا
+
+613
+00:49:03,420 --> 00:49:07,080
+شوفناه الآن ال attribute construction برضه عبارة
+
+614
+00:49:07,080 --> 00:49:09,920
+عن attribute جديد بدي انبنى بناء على values موجودة
+
+615
+00:49:09,920 --> 00:49:15,360
+مسبقا الان ال normalization هذه تقريبا أصعبهم و
+
+616
+00:49:15,360 --> 00:49:20,530
+بدنا نشتغل علىبشكل جيد لكن لأ أخفيكوا أنا الصحيح
+
+617
+00:49:20,530 --> 00:49:23,810
+اللي اليوم الصبح غيرت في ال slides فاللي طاب عليه
+
+618
+00:49:23,810 --> 00:49:26,670
+slide بيغينه الله بس ال slides هدول بدهم تعديل
+
+619
+00:49:26,670 --> 00:49:32,910
+ايوة
+
+620
+00:49:32,910 --> 00:49:37,370
+الان كويس عند أحمد فروخي بيسأل سؤال مهم جدا يا
+
+621
+00:49:37,370 --> 00:49:45,030
+شباب الان موضوع ال normalization اللي احنا أخدناه
+
+622
+00:49:45,030 --> 00:49:49,880
+في ال databaseفي database واحد ايش كان الهدف منه
+
+623
+00:49:49,880 --> 00:49:52,960
+انه
+
+624
+00:49:52,960 --> 00:49:55,980
+نقل شويه بس عشان اجيب لكياب تعريفي وطابق الكلام
+
+625
+00:49:55,980 --> 00:49:59,260
+اللي احنا بدنا يهان هو مش بعيد عنه هو عبارة عن كان
+
+626
+00:49:59,260 --> 00:50:05,080
+هدفه نقل ال data analysis تبعتي ال initial data
+
+627
+00:50:05,080 --> 00:50:12,840
+analysis الى other stage بتمنع التكرار، مصبوط؟بس
+
+628
+00:50:12,840 --> 00:50:16,020
+لاحظ في الأول كانت form كانت عبارة عن single
+
+629
+00:50:16,020 --> 00:50:19,760
+entity وفي ال form التاني في ال second normal form
+
+630
+00:50:19,760 --> 00:50:24,020
+اضطرت اعمل partitioning لأكتر من entity عشان اعمل
+
+631
+00:50:24,020 --> 00:50:28,540
+بينهماش أضمن عدم اتكرار ولا لأ مش هذا اللي صار ال
+
+632
+00:50:28,540 --> 00:50:33,200
+transformation اللي صار هذا هو نفسه او ال
+
+633
+00:50:33,200 --> 00:50:35,620
+normalization هو عبارة عن جزء من ال transformation
+
+634
+00:50:35,620 --> 00:50:39,160
+جزء من التحول هل التحول كله مش ضروري هالكلام اللي
+
+635
+00:50:39,160 --> 00:50:41,680
+احنا بيقوله فبالتالي مافيش تعرضات ما بين التانين
+
+636
+00:50:41,680 --> 00:50:46,170
+يا أحمدالأن في الـ Normalization اللي هتتكلم عليها
+
+637
+00:50:46,170 --> 00:50:50,690
+أو في الـ Scaling بالتحديد طبعا Normalization أو
+
+638
+00:50:50,690 --> 00:50:54,090
+Scaling نفس المصطلحات في علم البيانات أو في الـ
+
+639
+00:50:54,090 --> 00:50:59,610
+Data Mining بنتكلم إنه أنا بدي أروح أغير ال data
+
+640
+00:50:59,610 --> 00:51:07,630
+range تبعتي و عادة عادة بقى اتوجه إن أغير ال range
+
+641
+00:51:07,630 --> 00:51:12,730
+ل range أصغريعني بدل ما كانت الأرقام رواتب
+
+642
+00:51:12,730 --> 00:51:23,770
+الموظفين من 17 .. او من .. من 1770 مليون لـ 370
+
+643
+00:51:23,770 --> 00:51:28,430
+مليون اه
+
+644
+00:51:28,430 --> 00:51:33,690
+بالليرة .. هذا الكلام وارد جدا مصبوط؟
+
+645
+00:51:33,690 --> 00:51:37,470
+بدل ما هذا ال range بتروح اخليه يجع في range من
+
+646
+00:51:37,470 --> 00:51:46,730
+واحدلعشرة مثلا أو بدي أخلي من واحد وسبعة من عشرة
+
+647
+00:51:46,730 --> 00:51:55,810
+لتلاتة فاصلة سبعة الان في ال computation مين أسهل
+
+648
+00:51:55,810 --> 00:52:03,890
+الرقم هذا ولا الرقم هذا المفروض
+
+649
+00:52:03,890 --> 00:52:04,930
+الرقم الأصغر أسهل
+
+650
+00:52:08,520 --> 00:52:11,180
+كمان مرة مفهوم الـ Normalization ان انا بدي اعمل
+
+651
+00:52:11,180 --> 00:52:14,780
+scaling لل data او لل attributes اللي عندى هاي
+
+652
+00:52:14,780 --> 00:52:18,840
+بحيث ان احطها في different range و عادة .. عادة
+
+653
+00:52:18,840 --> 00:52:24,140
+اكثر من 95% او 99% من الشغل في ال hand انه انا بحط
+
+654
+00:52:24,140 --> 00:52:28,040
+ال range ل range اصغر لكن هذا لا يمنع .. لا يمنع
+
+655
+00:52:28,040 --> 00:52:32,980
+مطلقا انه افكر احطها في range اكبر منها و عادة يا
+
+656
+00:52:32,980 --> 00:52:37,840
+جماعة الخير تخيل انه انا في عندى two attributes
+
+657
+00:52:46,020 --> 00:52:51,060
+attribute one و attribute two ال values اللي عندي
+
+658
+00:52:51,060 --> 00:52:56,400
+هان بتتراوح
+
+659
+00:52:56,400 --> 00:53:02,320
+من الصفر للواحد و ال attribute التاني هذا من مية
+
+660
+00:53:02,320 --> 00:53:08,300
+إلى الف خليك معاه سيبر
+
+661
+00:53:11,420 --> 00:53:14,460
+عشان تفهم حاجتنا للـ Normalization أو للـ Scaling
+
+662
+00:53:14,460 --> 00:53:19,540
+تخيل إنه أنا في عندي data set فيها two attributes
+
+663
+00:53:19,540 --> 00:53:24,740
+الأول بتراوح القيم المتخلفة اللي في من صفر لواحد
+
+664
+00:53:24,740 --> 00:53:32,160
+والتاني من مية لألف و جيت أنا قلتلك بدي task بسيطة
+
+665
+00:53:32,160 --> 00:53:39,700
+جدا منك ترسمليهم على الـ 2D plane شو
+
+666
+00:53:39,700 --> 00:53:44,680
+رأيك؟كيف ال scale تبعك اللي هتستخدمه في الرسم؟
+
+667
+00:53:44,680 --> 00:53:48,700
+الان
+
+668
+00:53:48,700 --> 00:53:52,420
+كمان مرة شو رايك هاي ال .. هاي ال two attributes و
+
+669
+00:53:52,420 --> 00:53:57,020
+بدك ترسملياهم على two D plane مالهاش علاقة بال
+
+670
+00:53:57,020 --> 00:54:02,560
+mining الآن، تمام؟ شو ال scale اللي بدك تستخدمه؟
+
+671
+00:54:02,560 --> 00:54:07,180
+بدك تستخدم واحد، اتنين، تلاتة، اربعة، خمسة، ستة؟
+
+672
+00:54:07,180 --> 00:54:15,250
+ولا واحد من عشرة؟ولّا مية؟ ممتاز إذا أنت أخدت
+
+673
+00:54:15,250 --> 00:54:18,790
+المية إذا أخدت المية يعني الصحيحة التهان من صفر
+
+674
+00:54:18,790 --> 00:54:24,550
+لمية كل ال values تبعة ال attribute هذا هتيجيك في
+
+675
+00:54:24,550 --> 00:54:27,950
+النقطة هاي هتيجيك وكأنه معمود في النقطة هاي مش
+
+676
+00:54:27,950 --> 00:54:32,970
+هيبينه ليش؟ لأنه ال range تبعك اللي إنت اعتمدت لها
+
+677
+00:54:32,970 --> 00:54:38,250
+يا تناسب وإذا اعتمدت واحد من عشرة المية هتيجي هنا
+
+678
+00:54:40,520 --> 00:54:43,140
+مصبوط؟ وبالتالي مافيش مجال الرسم inconsistent
+
+679
+00:54:43,140 --> 00:54:49,400
+حيكون أو مش هتقدر ترسمهم من الآخر مافيش الحل ان
+
+680
+00:54:49,400 --> 00:54:54,020
+بدي أعمل معيار للرسم بين الاتنين إما بدي أنزل هذا
+
+681
+00:54:54,020 --> 00:54:57,920
+لنفس ال scale أو بدي أرفع هذا لنفس ال scale اللي
+
+682
+00:54:57,920 --> 00:55:05,780
+موجود وعلى الحالتين صح مين الأسهل؟ أنزل قول بدي
+
+683
+00:55:05,780 --> 00:55:12,420
+أجسمه علىعالمية بيصير هذا واحد و هذا عشرة لاحظ ال
+
+684
+00:55:12,420 --> 00:55:20,520
+range لأ بقى يختلف صفر ل واحد و واحدة عشرة نوعا ما
+
+685
+00:55:20,520 --> 00:55:23,840
+قريب لكن برضه ممكن انا ايش راح اساوي احط بنفس ال
+
+686
+00:55:23,840 --> 00:55:26,580
+range بديش اجسم على عالمية انا اجسم على الف
+
+687
+00:55:33,500 --> 00:55:37,500
+صار عند إيش؟ نفس ال scale exactly و أنا مافقدتش من
+
+688
+00:55:37,500 --> 00:55:42,320
+قيمة البيانات ولا حاجة هذا الكلام نفسه .. نفسه
+
+689
+00:55:42,320 --> 00:55:45,440
+بهمني لما يكون ال algorithm تبعي ال machine
+
+690
+00:55:45,440 --> 00:55:47,920
+learning algorithm اللي بيشتغل في ال mining task
+
+691
+00:55:47,920 --> 00:55:51,900
+تكون data set أو attribute ال values تبعته صغيرة
+
+692
+00:55:51,900 --> 00:55:56,480
+جدا و ال attribute التاني ال value تبعته كبيرة جدا
+
+693
+00:55:57,410 --> 00:56:00,830
+تبقى عندي mismatch في التعامل فأفضل حاجة ايش أسوي
+
+694
+00:56:00,830 --> 00:56:04,510
+ان احاول اعمل normalization لكل ال data تكون كلها
+
+695
+00:56:04,510 --> 00:56:10,090
+على range واحد فال scaling هذه او ال normalization
+
+696
+00:56:10,090 --> 00:56:14,810
+هذه مهمة جدا بالنسبالنا ال
+
+697
+00:56:14,810 --> 00:56:18,390
+z score او ال normalization او ال zero score
+
+698
+00:56:18,390 --> 00:56:22,510
+normalization او زي ما بتسميها ال python standard
+
+699
+00:56:22,510 --> 00:56:25,550
+scalar standard scalar
+
+700
+00:56:28,890 --> 00:56:32,550
+في عند الـ Min Max Normalization أو Min Max Scalar
+
+701
+00:56:32,550 --> 00:56:37,450
+وفي عند الـ Decimal Scalar أو Decimal Scaling أو
+
+702
+00:56:37,450 --> 00:56:43,030
+Decimal Normalization نبدأ مع الـ Zero Score أو مع
+
+703
+00:56:43,030 --> 00:56:47,070
+الـ Z Min أو الـ Z Score كلها نفس المصطلحات أو نفس
+
+704
+00:56:47,070 --> 00:56:51,590
+العنصر Standard Scalar بتكلم على الـ Zero Min
+
+705
+00:56:51,590 --> 00:56:57,270
+Normalization Zero Min Normalization مفهومها بكل
+
+706
+00:56:57,270 --> 00:57:03,450
+بساطة يا جماعة الخيرانه احنا فعليا بحاجة طبعا عشان
+
+707
+00:57:03,450 --> 00:57:05,650
+في مثال انا كتبته عند الطالبات المحاضرة الجابه
+
+708
+00:57:05,650 --> 00:57:08,470
+اللي بدي اياه نفسه مافيش داعي ان اختار مثال جديد
+
+709
+00:57:08,470 --> 00:57:15,470
+مفهومها انه بدي احول ال attribute هذا ل attribute
+
+710
+00:57:15,470 --> 00:57:19,110
+او ل value احور ال data اللي فيه ل value مختلفة
+
+711
+00:57:19,110 --> 00:57:24,590
+بحيث ان المتوسط الحسابي تبع ال new form يكون صفر
+
+712
+00:57:24,590 --> 00:57:30,160
+عشان هيك اسمه z من ال zeroأو Z-Mean، Zero-Mean،
+
+713
+00:57:30,160 --> 00:57:34,460
+Zero-Score أو Zero-Mean مفهومها إنه بعد ما أنا
+
+714
+00:57:34,460 --> 00:57:40,100
+أحور الـAttribute أحور الـAttribute، بده يكون
+
+715
+00:57:40,100 --> 00:57:44,460
+الـMean تبعه صفر ليش هذا الكلام مهم؟ لأنه كتير من
+
+716
+00:57:44,460 --> 00:57:47,420
+العمليات الحسابية المرتبطة بالـ Machine Learning
+
+717
+00:57:47,420 --> 00:57:50,700
+Algorithm لها علاقة بالـMean والـStandard
+
+718
+00:57:50,700 --> 00:57:56,610
+Deviation فإذا أنا قدرت أحول الـMean لـ0فبتصير
+
+719
+00:57:56,610 --> 00:58:03,110
+العمليات الحسابية تبعتي أسهل ما يمكن لو أنت بقيت
+
+720
+00:58:03,110 --> 00:58:06,810
+تضرب بصفر خلاص بس ال term اللي أنا جدت فيه term
+
+721
+00:58:06,810 --> 00:58:10,370
+صفر خلصنا لو بدي أجمع صفر مع أن مافيش عندي تغيير
+
+722
+00:58:10,370 --> 00:58:14,770
+وهذا هو الهدف الأساسي من ال normalization هنا إنه
+
+723
+00:58:14,770 --> 00:58:17,970
+أنا عامة في ال transformation عمالي بحاول أبدأ
+
+724
+00:58:17,970 --> 00:58:22,070
+أقلل من ال cost أو ال computational cost اللي ممكن
+
+725
+00:58:22,070 --> 00:58:27,930
+تصير عنديفالـ Zero mean أو الـ Z-score هدفها أنه
+
+726
+00:58:27,930 --> 00:58:31,890
+للـ feature هذا تكون قيمة الـ mean المتوسط الحسابي
+
+727
+00:58:31,890 --> 00:58:38,670
+صفر و ال variance أو الانحراف المعياري تبعته جداش
+
+728
+00:58:38,670 --> 00:58:46,410
+واحد عبر المعادلة اللي موجودة عندنا هنا طبعا ميزة
+
+729
+00:58:46,410 --> 00:58:50,370
+ال scaling هذا انه مافيش minimum و مافيش maximum
+
+730
+00:58:50,370 --> 00:58:54,480
+لكن بتروح تتطبق حسب القانونالقيمة الجديدة اللي هي
+
+731
+00:58:54,480 --> 00:59:00,840
+الـ Z تساوي القيمة السابقة X ناقص المتوسط الحسابي
+
+732
+00:59:00,840 --> 00:59:06,660
+على الانحراف المعياري تبعت ال value اللي موجودة
+
+733
+00:59:06,660 --> 00:59:12,240
+عندها عشان تظهر الصورة الأرقام اللي عندي أنا عشرة
+
+734
+00:59:12,240 --> 00:59:18,000
+خمس طعش عشرة خمس طعش عشرين
+
+735
+00:59:24,250 --> 00:59:27,910
+هذه الـ A original الـ attribute O الـ attribute
+
+736
+00:59:27,910 --> 00:59:33,030
+الأصلي ال values اللي فيه ال values اللي فيه تمام
+
+737
+00:59:33,030 --> 00:59:38,590
+هايهم خمس قيم عشان أقدر أشتغل مع هذا أو أطبق عليه
+
+738
+00:59:38,590 --> 00:59:43,910
+ال Z score شو بدي أساوي؟ بدي أحسب المتوسط الحسابي
+
+739
+00:59:43,910 --> 00:59:50,250
+هاي المتوسط الحسابي يساوي المجموع على العدد عشرة
+
+740
+00:59:50,250 --> 00:59:57,500
+عشرين و بتهيألي فيه كمان واحدةهم خمس قيم خمس طعش
+
+741
+00:59:57,500 --> 01:00:04,980
+عشرين تمام سبعين على خمسة كدهش الشباب سبعين على
+
+742
+01:00:04,980 --> 01:00:12,020
+خمسة يا
+
+743
+01:00:12,020 --> 01:00:17,640
+عيني عليكم عشان هيك يا حبابنا تعمل حسابك تعمل
+
+744
+01:00:17,640 --> 01:00:21,700
+حسابك تجيب ال calculator تبعتك انا بالنسبة لي
+
+745
+01:00:25,870 --> 01:00:29,150
+هيها اه مش هسمحلك تستخدم الجوال ولا في الامتحان
+
+746
+01:00:29,150 --> 01:00:32,830
+هسمحلك تستخدم الجوال فانت ما شاء الله يعني لسه عن
+
+747
+01:00:32,830 --> 01:00:35,470
+بارح طالع من الثانوية العامة او إذا في عندك حدا
+
+748
+01:00:35,470 --> 01:00:41,010
+فهي .. هي فهي إلك إذا في حد أخدها من وراك تلفها
+
+749
+01:00:41,010 --> 01:00:47,710
+منه ضروري من اليوم و طالع في عندنا حساب لأ حساب
+
+750
+01:00:47,710 --> 01:00:51,230
+عشان ما أخوف cashلأن هاي و ما شاء الله عليك انت في
+
+751
+01:00:51,230 --> 01:00:56,110
+القسمة الـ 70 على 5 أثبتتي اللي بالدليل قاطع إنك
+
+752
+01:00:56,110 --> 01:01:05,030
+ناجح ان شاء الله طيب، الآن خلاص حسبت ال main الآن
+
+753
+01:01:05,030 --> 01:01:08,710
+إيش بقول ليه؟ الانحراف المعياري أو ال sigma تساوي
+
+754
+01:01:08,710 --> 01:01:14,110
+الجذر التربيعي للفروقات ما بين ال main على العدد
+
+755
+01:01:26,700 --> 01:01:32,460
+عشرة أربعة عشر ناقص عشرة تربيع أربعة عشر ناقص عشرة
+
+756
+01:01:32,460 --> 01:01:32,460
+تربيع أربعة عشر ناقص عشرة تربيع أربعة عشر ناقص
+
+757
+01:01:32,460 --> 01:01:36,680
+عشرة تربيع أربعة عشر ناقص عشرين تربيع أربعة عشر
+
+758
+01:01:36,680 --> 01:01:42,880
+ناقص عشرين تربيع أربعة عشر ناقص عشرين تربيع أربعة
+
+759
+01:01:42,880 --> 01:01:43,720
+عشر ناقص عشرين تربيع أربعة عشر ناقص عشرين تربيع
+
+760
+01:01:43,720 --> 01:01:44,240
+أربعة عشر ناقص عشرين تربيع أربعة عشر ناقص عشرين
+
+761
+01:01:44,240 --> 01:01:49,650
+تربيع أربعة عشر ناقص عشرين تربيع أربعة عشر ناق16 1
+
+762
+01:01:49,650 --> 01:02:04,310
+16 1 36 مصبوط انا حسبت المربعات الان 16 و 16 32 و
+
+763
+01:02:04,310 --> 01:02:16,360
+32 و 2 34 و 36 70 الان ال sigmaتساوي الجذر
+
+764
+01:02:16,360 --> 01:02:22,900
+التربيعي لـ 70 على 5 اللي هي جذر الـ 14 اللي هي
+
+765
+01:02:22,900 --> 01:02:29,840
+تقريبا قداش تلات
+
+766
+01:02:29,840 --> 01:02:34,060
+أو كسر، صح؟
+
+767
+01:02:34,060 --> 01:02:37,400
+ما هو لما أنت تكتب لتنين جذر مش عارف قداش مش هتحصل
+
+768
+01:02:37,400 --> 01:02:43,020
+لنتيجة تلاتة
+
+769
+01:02:43,020 --> 01:02:50,630
+pointأربعة و سبعين جذر
+
+770
+01:02:50,630 --> 01:02:57,510
+الاربعتاش هذا بنسميه الانحراف المعياري لل data set
+
+771
+01:02:57,510 --> 01:03:03,290
+او لل attribute اللي عندى sigma لسه احنا مخلصناش
+
+772
+01:03:03,290 --> 01:03:08,370
+انا كل اللي بسوته جبت المعاملات بتاعة المعادلة هاي
+
+773
+01:03:08,370 --> 01:03:13,740
+جبت ال mu جبت ال sigmaهلجت بدي أجيب Z زد لمين يا
+
+774
+01:03:13,740 --> 01:03:18,260
+جماعة الخير لكل قيمة من هدول لكل قيمة من هدول احنا
+
+775
+01:03:18,260 --> 01:03:27,880
+خلصنا هذا الان بقدر أمسحه ال
+
+776
+01:03:27,880 --> 01:03:32,420
+attribute new قيمة
+
+777
+01:03:32,420 --> 01:03:40,550
+القيمة الجديدة تساوي X ناقص ميو علىتلاتة يعني بين
+
+778
+01:03:40,550 --> 01:03:45,910
+جثين هتكون عشرة ناقص أربعة تعش على تلاتة فاصلة
+
+779
+01:03:45,910 --> 01:03:52,530
+أربعة وسبعين ولا كيف بده يكون في الآخر المتوسط
+
+780
+01:03:52,530 --> 01:03:57,970
+الحسابي صفر لازم تكون قيم موجبة وقيم سالبة لأنه في
+
+781
+01:03:57,970 --> 01:04:02,390
+الآخر صفر على أي شيء العدد مستحيل يكون صفر فلازم
+
+782
+01:04:02,390 --> 01:04:06,530
+البسطي يطلع معاك صفر مجموع القيم فبتطلع هذه سالب
+
+783
+01:04:06,530 --> 01:04:14,240
+بالنسبة للأولىأربعة تقسيم تلاتة فاصلة أربعة وسبعين
+
+784
+01:04:14,240 --> 01:04:17,340
+سالب
+
+785
+01:04:17,340 --> 01:04:22,440
+واحد point zero سبعة هم ال roundation للرقمين
+
+786
+01:04:22,440 --> 01:04:25,700
+هتكون
+
+787
+01:04:25,700 --> 01:04:31,300
+عندي عشرة ناقص او عفوا خمس طعش ناقص اربعة طعش على
+
+788
+01:04:31,300 --> 01:04:37,040
+تلاتة اربعة وسبعين اعتمد
+
+789
+01:04:37,040 --> 01:04:38,900
+يا أبو حاسم ولا في شك في الكلام
+
+790
+01:04:43,490 --> 01:04:49,430
+26% غلط لأنه بدنا نعمل roundation عندك 6 أو 7 يا
+
+791
+01:04:49,430 --> 01:04:56,250
+باشا عشان أضمن تصفر معايا المسألة الآن عشرة نفس
+
+792
+01:04:56,250 --> 01:05:00,890
+القيمة اللي فوق 1
+
+793
+01:05:00,890 --> 01:05:07,610
+.0715
+
+794
+01:05:07,610 --> 01:05:11,990
+.27 الآن
+
+795
+01:05:14,240 --> 01:05:25,220
+1.6 انا بتذكرها هي صحيحة 1.6 تمام؟ الان متوسط
+
+796
+01:05:25,220 --> 01:05:32,460
+الحساب الجديد يساوي اجمع
+
+797
+01:05:32,460 --> 01:05:40,840
+العناصر هدول على عددهم عددهم خمسة سالب
+
+798
+01:05:40,840 --> 01:05:41,240
+واحد
+
+799
+01:05:44,090 --> 01:05:52,350
+لان انت متراهلش انت بتجمع القمتين هدول وبالتالي
+
+800
+01:05:52,350 --> 01:05:59,410
+ال mean تبعتي قداش صارت صفر لازم يطلع صفر اللي مش
+
+801
+01:05:59,410 --> 01:06:04,250
+مصدق يجمعهم يا شباب مش مشكلة عندي تمام فال mean
+
+802
+01:06:04,250 --> 01:06:10,950
+صفر الانحراف المعياري الجديد يساوي الجذر التربيعي
+
+803
+01:06:10,950 --> 01:06:18,430
+لأالفروقات هدول او القيام هدول تربيع الفروق مع ال
+
+804
+01:06:18,430 --> 01:06:27,890
+mean ال mean صفر فتربيع القيام هذه 1.07 زائد 0.27
+
+805
+01:06:27,890 --> 01:06:40,490
+زائد 1.7 تربيع زائد 0.27 تربيع زائد 1.6 تربيع هدول
+
+806
+01:06:40,490 --> 01:06:43,330
+مجموحهم خمسة على خمسة
+
+807
+01:06:48,310 --> 01:06:51,770
+واحد اه لازم يطلع واحد لو ما طلعش واحد مانتوا في
+
+808
+01:06:51,770 --> 01:06:57,470
+عندك مشكلة لو ما طلعش واحد في عندك مشكلة في الحساب
+
+809
+01:06:57,470 --> 01:07:02,890
+ممكن الأرقام مشكلة لا يا باشا الأرقام إيش ما كانت
+
+810
+01:07:02,890 --> 01:07:07,950
+إذا تطبق عليها ال Z score لازم إنها تجي يطلع ال
+
+811
+01:07:07,950 --> 01:07:11,030
+main صفر و ال standard deviation واحد
+
+812
+01:07:13,890 --> 01:07:18,810
+تمام؟ تمام إيش
+
+813
+01:07:18,810 --> 01:07:27,210
+استفدت؟ الآن أنا عملت scaling .. scaling لمين؟ لل
+
+814
+01:07:27,210 --> 01:07:32,090
+A الأصلية اللي موجودة عندي بقيم جديدة عملت
+
+815
+01:07:32,090 --> 01:07:36,970
+transformation مظبوط؟ القيمة هذه تمثل العشرة وال
+
+816
+01:07:36,970 --> 01:07:41,630
+27 تمثل .. ال 27 من 100 تمثل 15يعني حطيتها في
+
+817
+01:07:41,630 --> 01:07:45,130
+Range جديد الـ Range الجديد هذا ما فقدش قيمته
+
+818
+01:07:45,130 --> 01:07:52,390
+مطلقا لكن كان فيه لميزة قال لي إن المتوسط الحسابي
+
+819
+01:07:52,390 --> 01:07:57,610
+تبع القيم هدول صفر والانحراف المياري واحد كتير من
+
+820
+01:07:57,610 --> 01:08:00,370
+ال machine learning algorithm جامعة الخير بتنبني
+
+821
+01:08:00,370 --> 01:08:05,390
+على حسبة ال main والانحراف المياري فلما أنا بأضمن
+
+822
+01:08:05,390 --> 01:08:09,320
+ال main صفرمعناته كتير من العمليات او من ال terms
+
+823
+01:08:09,320 --> 01:08:12,800
+هعملها neglect هاختصرها في ال computation ولا لأ
+
+824
+01:08:12,800 --> 01:08:16,400
+لما بتكون العمليات ضرب و بحصل على واحد في ال
+
+825
+01:08:16,400 --> 01:08:21,140
+standard deviation هذا الكلام كله بيخدمني في تسريع
+
+826
+01:08:21,140 --> 01:08:23,980
+عملية ال learning اللي هتصير عند ال data mining او
+
+827
+01:08:23,980 --> 01:08:27,940
+في مرحلة ال mining او ال data mining tasks هالكلام
+
+828
+01:08:27,940 --> 01:08:32,920
+هذا مطلوب من ناحية عملي من ناحية عملي ال standard
+
+829
+01:08:32,920 --> 01:08:37,340
+scalar موجودة في ال python as a functionتستدعيها و
+
+830
+01:08:37,340 --> 01:08:39,800
+بتقوله تديها اسم ال attribute و بتعمل generate ل
+
+831
+01:08:39,800 --> 01:08:48,540
+attribute بمباشرة بس لازم تحفظ و تفهم اش اللي بصير
+
+832
+01:08:48,540 --> 01:08:52,240
+لأنه بكل بساطة لاحقا ممكن اديك sequence من خمس
+
+833
+01:08:52,240 --> 01:08:55,960
+عناصر زي هيك و اقولك روح انا بدي نعمل
+
+834
+01:08:55,960 --> 01:08:58,900
+transformation لل data set هذه بحيث انك تتناسب مع
+
+835
+01:08:58,900 --> 01:09:02,500
+ال task الفلانية بتطبيق ال algorithm الفلاني
+
+836
+01:09:06,680 --> 01:09:11,320
+أيوة سؤال مهم أحمد فاروخ بيقول جديش ال scale مافيش
+
+837
+01:09:11,320 --> 01:09:15,160
+scale مافيش range و هذا الكلام قلناه ثابت مافيش
+
+838
+01:09:15,160 --> 01:09:20,740
+عندي minimum و maximum values ما بعرفهمش لكن بما
+
+839
+01:09:20,740 --> 01:09:24,540
+أنه العشرة هي أصغر قيمة عندي و ال data 6 أنا قادر
+
+840
+01:09:24,540 --> 01:09:31,220
+أمسكها أصغر قيمة فهذه كانت ال minimum و ال maximum
+
+841
+01:09:31,220 --> 01:09:40,300
+20 فهذه 61.6%هي ال maximum بس هي ال range تبعتي هي
+
+842
+01:09:40,300 --> 01:09:44,900
+ال range اللي موجودة عندي الآن على غرار الكلام هذا
+
+843
+01:09:44,900 --> 01:09:53,900
+في عند ال min max طبعا ال robust عشان نخلص منها ال
+
+844
+01:09:53,900 --> 01:09:58,440
+robust scalar فكرته بكل بساطة انه بيقولك يا عم إذا
+
+845
+01:09:58,440 --> 01:10:01,580
+أنا كان في عندي outlier point او في عندي noisy
+
+846
+01:10:01,580 --> 01:10:06,000
+pointفضمن ال range هذا و انا اعتمدت على ال mean
+
+847
+01:10:06,000 --> 01:10:11,720
+فهتشد ال mean باتجاه بعيد بمعنى اخر لو كانت
+
+848
+01:10:11,720 --> 01:10:18,740
+العشرين هذه 200 او ناقص 20 شو بيصير في ال mean
+
+849
+01:10:18,740 --> 01:10:24,150
+اللي عندى؟هيتغير وبالتالي صار فيه bias باتجاه الـ
+
+850
+01:10:24,150 --> 01:10:28,330
+outlier باتجاه ال noise data عشان يتجنب ال noise
+
+851
+01:10:28,330 --> 01:10:32,370
+data ال robust scalar هذا بيروح بيعتمد على ال
+
+852
+01:10:32,370 --> 01:10:39,230
+median و ال quartiles ايش ال median؟ ايش ال
+
+853
+01:10:39,230 --> 01:10:44,370
+median؟ الوسيط ال quartiles القيم تبعت الأرباع
+
+854
+01:10:44,370 --> 01:10:48,400
+تبعت العناصر اللي موجودة عندىوبهيك هو بتجنب تأثير
+
+855
+01:10:48,400 --> 01:10:53,580
+ال noise attributes لتظهر أو ال noise value لتظهر
+
+856
+01:10:53,580 --> 01:10:53,860
+عنده
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/GPEcN85s2Oo.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/GPEcN85s2Oo.srt
new file mode 100644
index 0000000000000000000000000000000000000000..deddde60f28a85a4b9b401742c525576e3992701
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/GPEcN85s2Oo.srt
@@ -0,0 +1,698 @@
+1
+00:00:01,140 --> 00:00:03,520
+باسم الله والحمد لله والصلاة والسلام على رسول
+
+2
+00:00:03,520 --> 00:00:08,140
+الله هذا التسجيل الأخير إن شاء الله في الـ chapter
+
+3
+00:00:08,140 --> 00:00:12,840
+clustering عفواً قبل الأخير بيضللنا في تسجيل إن شاء
+
+4
+00:00:12,840 --> 00:00:16,540
+الله سيكون عملي باعتماد الـ python الصحيح فشوف في
+
+5
+00:00:16,540 --> 00:00:24,320
+شغل الـ python بعض الإبداعات منكم وبعضكم .. حلو
+
+6
+00:00:24,320 --> 00:00:25,480
+حلو حلو طبعاً ما شاء الله
+
+7
+00:00:28,370 --> 00:00:31,030
+البداية، الـ chapter إن الـ cluster هي عبارة عن عملية
+
+8
+00:00:31,030 --> 00:00:34,230
+تقسيم الـ instances بناءً على تشابه أو similarities
+
+9
+00:00:34,230 --> 00:00:38,570
+ما بينهم لمجموعات، في عندنا الـ partition cluster والـ
+
+10
+00:00:38,570 --> 00:00:41,070
+partition cluster أنه ما يكونش فيه overlap
+
+11
+00:00:41,070 --> 00:00:44,550
+clusters وفي عندنا hierarchical cluster أنه أنا
+
+12
+00:00:44,550 --> 00:00:48,870
+فعلياً أقدر أشوف كل cluster بينتمي لأي cluster والـ
+
+13
+00:00:48,870 --> 00:00:51,330
+طبعاً هنا بتحكم في عدد الـ clusters اللي أنا بدي
+
+14
+00:00:51,330 --> 00:00:55,310
+إياها، كل cluster ببساطة، اليوم إن شاء الله نتكلم عن
+
+15
+00:00:55,310 --> 00:00:59,990
+جزئية الـ evaluation طبعاً لما نتكلم عن الـ evaluation
+
+16
+00:00:59,990 --> 00:01:07,030
+كتقييم الـ ..
+
+17
+00:01:07,030 --> 00:01:11,390
+نتكلم عن التقييم، هل التقييم وارد في الـ
+
+18
+00:01:11,390 --> 00:01:16,990
+clustering؟ التقييم كتقييم في الـ clustering إذا الـ
+
+19
+00:01:16,990 --> 00:01:21,650
+data  بقى unlabeled أو عمره بيكون صحيح لأن أنا
+
+20
+00:01:21,650 --> 00:01:27,410
+فعلياً لازم أتدخل human عفواً المقصود أن التقييم
+
+21
+00:01:27,410 --> 00:01:35,220
+مستحيل يكون صحيح أو حالياً بدي أقول أنه يكاد يكون من
+
+22
+00:01:35,220 --> 00:01:40,060
+المستحيل تطبيق التقييم إلا من خلال expert قادر
+
+23
+00:01:40,060 --> 00:01:45,460
+فعلياً على دراسة كل instance وفعلياً أنها تنتمي لـ
+
+24
+00:01:45,460 --> 00:01:49,620
+cluster أو متشابه مع العناصر اللي موجودة عندها، لكن
+
+25
+00:01:49,620 --> 00:01:54,920
+إحنا هلأ لما نتكلم عن الـ clustering، أنا لدي
+
+26
+00:01:54,920 --> 00:01:58,140
+algorithm و data set وطبقت على الـ data set، هل في
+
+27
+00:01:58,140 --> 00:02:01,520
+مجال أعمل evaluation للـ algorithm أو للناتج اللي
+
+28
+00:02:01,520 --> 00:02:06,160
+موجود؟ آه في مجال لكن في حالة واحدة فقط، إذا أنا
+
+29
+00:02:06,160 --> 00:02:10,720
+اعتمدت أن في عندي labeled data set، طيب إحنا قلنا
+
+30
+00:02:10,720 --> 00:02:15,020
+من البداية أن
+
+31
+00:02:15,020 --> 00:02:17,800
+الـ cluster بتشتغل على الـ test set يعني الـ label مش
+
+32
+00:02:17,800 --> 00:02:22,580
+موجود، صحيح، الفكرة وين أن أنا بدي أفصل الـ data set
+
+33
+00:02:22,580 --> 00:02:31,250
+بتاعتي، مجموعة الـ attributes لحال والـ target label
+
+34
+00:02:31,250 --> 00:02:40,670
+لحال، وبعد هيك أعمل لها الـ clustering، بدي أعمل هنا
+
+35
+00:02:40,670 --> 00:02:44,590
+clustering للـ data set اللي موجودة عندي هنا وبناءً
+
+36
+00:02:44,590 --> 00:02:48,270
+على الـ clusters، أنا عارف أن كل instance بتتبع أي
+
+37
+00:02:48,270 --> 00:02:54,960
+label، فبيصير أنا بقى بأقارن الـ label اللي عندي مع الـ
+
+38
+00:02:54,960 --> 00:02:57,100
+clusters اللي هو اللي عندي هنا وبناءً على هيك بحصل
+
+39
+00:02:57,100 --> 00:03:02,660
+على تقييم، وبالتالي لما إحنا بنتكلم على الـ الـ الـ الـ
+
+40
+00:03:02,660 --> 00:03:03,400
+(Repeated "ال" - removed)
+
+41
+00:03:03,400 --> 00:03:04,060
+(Repeated "ال" - removed)
+
+42
+00:03:04,060 --> 00:03:05,500
+(Repeated "ال" - removed)
+
+43
+00:03:05,500 --> 00:03:06,460
+(Repeated "ال" - removed)
+
+44
+00:03:06,460 --> 00:03:07,520
+(Repeated "ال" - removed)
+
+45
+00:03:07,520 --> 00:03:07,620
+(Repeated "ال" - removed)
+
+46
+00:03:22,210 --> 00:03:28,550
+لأن النتائج اللي موجودة عندي ما حدش بيقول عنها صح
+
+47
+00:03:28,550 --> 00:03:31,570
+أو خطأ، يعني أنا استخدمت two different algorithms
+
+48
+00:03:31,570 --> 00:03:36,930
+وقلت لهم والله جسمّلت الـ data set كـ partitional لـ
+
+49
+00:03:36,930 --> 00:03:46,770
+three clusters، طلعوا لي three clusters، مش ضروري مش
+
+50
+00:03:46,770 --> 00:03:50,350
+ضروري العناصر اللي في الـ cluster الأول هي نفسها
+
+51
+00:03:50,350 --> 00:03:51,970
+اللي في عناصر الـ cluster الثاني، ناتج الـ
+
+52
+00:03:51,970 --> 00:04:00,600
+algorithm وبالتالي مقارنة الـ output شبه مستحيلة، إذا
+
+53
+00:04:00,600 --> 00:04:02,640
+كنت أقول أن الـ Algorithm أعطاني نفس النتيجة أو
+
+54
+00:04:02,640 --> 00:04:05,880
+نفس الـ الـ فايدة من الثاني، فلا يتميز الثاني عنه
+
+55
+00:04:05,880 --> 00:04:10,360
+تمام، إلا فعلياً لو الـ Data كانت فعلياً الـ Data
+
+56
+00:04:10,360 --> 00:04:13,960
+discriminant، الـ instances ميّالة لـ different tree
+
+57
+00:04:13,960 --> 00:04:18,180
+classes وكل واحدة، كل instance تنتمي لـ class، يعني
+
+58
+00:04:18,180 --> 00:04:22,100
+في عندي discriminant attribute و أقدر أصفّهم
+
+59
+00:04:22,100 --> 00:04:25,100
+أو أودّيهم على الـ certain class أو الـ target
+
+60
+00:04:25,100 --> 00:04:30,020
+cluster، عفواً بشكل كويس، لكن لما أنا فعلياً بأطبق
+
+61
+00:04:30,020 --> 00:04:34,000
+ممكن باعتمادي على الـ training set، الـ training set
+
+62
+00:04:34,000 --> 00:04:39,000
+إذا أنا طبقت الـ cluster algorithm على الـ training
+
+63
+00:04:39,000 --> 00:04:43,020
+set، تلاحظوا معايا يا جماعة الخير؟ لما أنا بدي أعمل
+
+64
+00:04:43,020 --> 00:04:45,720
+evaluation، الآن فعلياً، فعلياً ليه الـ clustering
+
+65
+00:04:45,720 --> 00:04:49,580
+unsupervised learning؟ يعني أنا بتجاهل الـ label أو
+
+66
+00:04:49,580 --> 00:04:53,560
+الـ label مش موجود في الـ data set، هذه واحدة، لما أنا
+
+67
+00:04:53,560 --> 00:04:59,370
+بدي أعمل له evaluation للـ algorithm، تمام؟ بقدر أعمل
+
+68
+00:04:59,370 --> 00:05:03,170
+evaluation في حالة واحدة فقط إذا أنا قدرت أطبقه
+
+69
+00:05:03,170 --> 00:05:06,410
+على الـ training set، شو الـ training set؟ يعني في عندي
+
+70
+00:05:06,410 --> 00:05:09,930
+label، طيب هل الكلام هذا موجود؟ آه موجود، بيصير كل
+
+71
+00:05:09,930 --> 00:05:15,670
+label، كل class بمثابة cluster، كل class بمثابة
+
+72
+00:05:15,670 --> 00:05:21,910
+cluster وبروح بأخذ الـ class وبجسّم الـ data set
+
+73
+00:05:21,910 --> 00:05:24,210
+بدون الـ cluster زي ما واجهتكم في الـ slide السابقة
+
+74
+00:05:24,210 --> 00:05:30,020
+زي ما أرسلناها، يعني أنا الآن هي الـ data set بتاعي
+
+75
+00:05:30,020 --> 00:05:37,920
+مرة كمان، فصلت الـ cluster
+
+76
+00:05:37,920 --> 00:05:40,940
+أو فصلت الـ data set، الـ attribute والـ label أو الـ
+
+77
+00:05:40,940 --> 00:05:46,720
+class، جسمّلت
+
+78
+00:05:46,720 --> 00:05:49,200
+الـ data set، صار عندي الآن هي الـ label وهي الـ
+
+79
+00:05:49,200 --> 00:05:55,150
+attribute، الآن بأجي بأطبق الـ clustering، بأطبق الـ
+
+80
+00:05:55,150 --> 00:05:57,170
+clustering على الـ attributes اللي موجودة عندها
+
+81
+00:05:57,170 --> 00:06:02,830
+على الـ instances اللي موجودة، تمام، الآن فعلياً كل
+
+82
+00:06:02,830 --> 00:06:07,870
+instance بتبقى class وفي عندي مجموعة instances في
+
+83
+00:06:07,870 --> 00:06:10,470
+نفس الـ class، بينجّم أنه فعلياً الـ data already
+
+84
+00:06:10,470 --> 00:06:15,590
+منجسمة، فإذا أنا قدرت أربط ما بين الـ true cluster
+
+85
+00:06:15,590 --> 00:06:21,890
+اللي هي الـ label والـ predicted cluster اللي موجود
+
+86
+00:06:21,890 --> 00:06:26,610
+عندها، بقدر أنشئ شغل اسمها الـ Contingency Matrix
+
+87
+00:06:26,610 --> 00:06:29,930
+ومن الـ Contingency Matrix ممكن أن أتكلّم على شغل
+
+88
+00:06:29,930 --> 00:06:36,160
+أول metric، هسميها الـ Purity، تعالوا نتكلم عن الـ
+
+89
+00:06:36,160 --> 00:06:38,920
+Contingency Matrix، ايش الـ Contingency Matrix
+
+90
+00:06:38,920 --> 00:06:43,720
+بتقول؟ أن لدي ثلاثة .. طبعاً لاحظوا يا جماعة الخير
+
+91
+00:06:43,720 --> 00:06:47,960
+في موقفي، أنا بدي أختبر Clustering Algorithm في
+
+92
+00:06:47,960 --> 00:06:51,980
+عندي labeled data set، الـ labeled data set فيها عدد
+
+93
+00:06:51,980 --> 00:06:55,800
+classes معيّن N، لما بدي أستخدم الـ Clustering
+
+94
+00:06:55,800 --> 00:06:59,020
+Algorithm، بدي أقول جسمّلتها لـ N من الـ cluster لأن
+
+95
+00:06:59,020 --> 00:07:02,800
+كل cluster بدي يمثل Class، فأنا بفترض أنه عندي data
+
+96
+00:07:02,800 --> 00:07:07,680
+set مكوّنة من three classes، labeled data set مكوّنة
+
+97
+00:07:07,680 --> 00:07:13,080
+من three classes، بنسمّيهم T1 وT2 وT3، من true true
+
+98
+00:07:13,080 --> 00:07:18,520
+cluster أو true segment أو true partition، سمّوها زي
+
+99
+00:07:18,520 --> 00:07:24,380
+ما بدّكم، true label سمّوها زي ما بدّكم، وC1 وC2 وC3 هما
+
+100
+00:07:24,380 --> 00:07:28,060
+الـ clusters اللي أنشأتهم من الـ algorithm اللي
+
+101
+00:07:28,060 --> 00:07:31,580
+موجود عندها، ايش راح أجيب؟ ايش بفهم الـ contingency
+
+102
+00:07:31,580 --> 00:07:41,000
+matrix؟ أن في C1، C1 خمسة وعشرين element بينتمي لـ
+
+103
+00:07:41,000 --> 00:07:45,020
+T2 وخمسة
+
+104
+00:07:45,020 --> 00:07:50,410
+elements بينتمي لـ T3، وخمس عناصر بينتمي لـ T3، يعني
+
+105
+00:07:50,410 --> 00:07:56,730
+عندي 25 عنصر من T، ناتج
+
+106
+00:07:56,730 --> 00:08:06,470
+الـ clustering، C1 بيحتوي على 30 عنصر، 25 منهم حقيقة
+
+107
+00:08:06,470 --> 00:08:12,550
+من الـ class الثاني و5 من الـ class الثالث ولا
+
+108
+00:08:12,550 --> 00:08:18,880
+واحد من الـ class الأول، T2 أو cluster C2 بيحتوي على
+
+109
+00:08:18,880 --> 00:08:25,100
+35 عنصر، 15 من الـ class الأول و20 من الـ class
+
+110
+00:08:25,100 --> 00:08:32,220
+الثالث، cluster ثلاثة بيحتوي على عشر عناصر فقط، كلهم
+
+111
+00:08:32,220 --> 00:08:40,100
+كلهم بيتبعوا T1، الآن هذا الكلام إذا أنا فهمته
+
+112
+00:08:41,270 --> 00:08:45,670
+معناته أنا مش ضروري الـ Clustering algorithm تبعي
+
+113
+00:08:45,670 --> 00:08:49,250
+يكون صح مائة في المائة، ممتاز، طيب متى بيكون صح مائة
+
+114
+00:08:49,250 --> 00:08:57,710
+في المائة؟ إذا والله أنا إجيت قلت هيك مثلاً
+
+115
+00:08:57,710 --> 00:09:00,830
+حصرت على صورة واحدة من الصور التالية، فأنا هأتكلّم عن
+
+116
+00:09:00,830 --> 00:09:08,150
+الـ matrix، لو أنا إجيت قلت هنا والله عندي
+
+117
+00:09:08,150 --> 00:09:08,990
+هنا ثلاثين
+
+118
+00:09:12,600 --> 00:09:24,500
+وعندي هنا 20 وعندي هنا 50 وأنا
+
+119
+00:09:24,500 --> 00:09:28,740
+C1، C2،
+
+120
+00:09:28,740 --> 00:09:39,400
+وC3، والباقي أصفر، طبعاً هنا T1، T2، T3، وأنا تعمّدت أحط
+
+121
+00:09:39,400 --> 00:09:45,560
+القيم نفس الكمية، لحظوا معايا إنه فعلياً كل cluster
+
+122
+00:09:45,560 --> 00:09:50,720
+completely pure، صافي ما فيش فيه أي .. يعني كل
+
+123
+00:09:50,720 --> 00:09:53,800
+cluster مثل واحدة من الـ classes اللي موجودة عندي
+
+124
+00:09:53,800 --> 00:09:57,980
+كل cluster مثل واحدة فقط من الـ classes اللي موجودة
+
+125
+00:09:57,980 --> 00:10:01,920
+عندي، وهنا بتكلم إنه فعلياً كل cluster نقي تماماً
+
+126
+00:10:01,920 --> 00:10:06,740
+بيحتوي على عناصر من نفس الـ class فقط، عشان هي كان
+
+127
+00:10:06,740 --> 00:10:10,900
+بنتكلم إحنا على الـ purity، نقاوة أو نقاء، درجة
+
+128
+00:10:10,900 --> 00:10:17,700
+النقاء، طيب بما أن الحالة دي هي الـ optimal case أو
+
+129
+00:10:17,700 --> 00:10:21,640
+الـ ideal case واللي أنا فعلاً مش هأحصل عليها، أنا
+
+130
+00:10:21,640 --> 00:10:24,400
+هأحصل على شغل مشابه زي هيك من خلال الـ contingency
+
+131
+00:10:24,400 --> 00:10:28,020
+matrix، كيف أحسب الـ purity؟ الـ purity هي تساوي
+
+132
+00:10:28,020 --> 00:10:35,180
+عبارة عن مجموع الـ maximum في كل صف، الـ maximum عدد
+
+133
+00:10:35,180 --> 00:10:40,410
+maximum للـ Ti تنتمي لـ C، على الآن، الـ maximum خمسة و
+
+134
+00:10:40,410 --> 00:10:44,750
+عشرين، الـ maximum عشرين، الـ maximum عشرة، يعني خمسة و
+
+135
+00:10:44,750 --> 00:10:49,430
+عشرين زائد عشرين زائد عشرة، عندما أتكلّم عن خمسة و
+
+136
+00:10:49,430 --> 00:10:53,550
+خمسين، على كل الآن خمسة وخمسين، وفي عندي أضيفهم
+
+137
+00:10:53,550 --> 00:10:58,670
+هنا على خمسة وسبعين، بتكلم على الـ purity، الآن إن
+
+138
+00:10:58,670 --> 00:11:04,870
+عندي هنا ثلاثين، خمسة وثلاثين هي خمسة وستين، خمسة
+
+139
+00:11:04,870 --> 00:11:10,750
+و سبعين، معناته عندي أنا هنا خمسة اللي عندي هنا
+
+140
+00:11:10,750 --> 00:11:13,830
+نتكلم .. إحنا قلنا الـ maximum خمسة وأربعين ..
+
+141
+00:11:13,830 --> 00:11:21,510
+خمسة وخمسين .. خمسة وخمسين على خمسة وسبعين، هذه
+
+142
+00:11:21,510 --> 00:11:23,970
+الـ purity تبع الـ cluster أو تبع الـ contingency
+
+143
+00:11:23,970 --> 00:11:29,990
+matrix اللي موجودة عندي
+
+144
+00:11:29,990 --> 00:11:34,250
+طيب .. تعالوا نشوف المثال البسيط اللي عندي هذا
+
+145
+00:11:41,930 --> 00:11:45,370
+أنا مش بقول، بقول إن أنا الـ Purity بقدر أحسبها إذا
+
+146
+00:11:45,370 --> 00:11:50,690
+كانت بتعامل مع test set بتحتوي على target class
+
+147
+00:11:50,690 --> 00:11:56,970
+تخيّل، عشان يدمج التعريف هذا، الـ definition هذا، عشان
+
+148
+00:11:56,970 --> 00:12:00,610
+يدمج ما بين الشغلتين، بين إنه فعلياً الـ clustering
+
+149
+00:12:00,610 --> 00:12:05,230
+بتطبق على test set وأنا ما بقدرش أروح أقدر أعمل
+
+150
+00:12:05,230 --> 00:12:09,980
+evaluation إلا غير لو كان الـ label موجود، فجالي الـ
+
+151
+00:12:09,980 --> 00:12:12,960
+test set بتحتوي على target التي بنجمعها من الـ training
+
+152
+00:12:12,960 --> 00:12:20,520
+set ولا شو رأيكم؟ training
+
+153
+00:12:20,520 --> 00:12:25,220
+set، بيبقى الآن بقول، أفرض أن أنا في عندي test set
+
+154
+00:12:25,220 --> 00:12:29,900
+مكوّنة من 24 element بتنتمي لـ three different
+
+155
+00:12:29,900 --> 00:12:39,530
+classes، الـ O أو الـ circle، triangle، و square، ومجسّم
+
+156
+00:12:39,530 --> 00:12:45,490
+العناصر بالتساوي، 8، 8، 8، 8، بعد ما طبّقت الـ clustering
+
+157
+00:12:45,490 --> 00:12:50,510
+تبعتي، الـ cluster C1 فيها العناصر التالية، الـ cluster
+
+158
+00:12:50,510 --> 00:12:55,650
+C2، والـ cluster C3، طبعاً هنا في مصطلح جديد أضيفه
+
+159
+00:12:55,650 --> 00:13:01,630
+نقاء كل cluster، نقاء كل cluster بشكل مستقل، إذا
+
+160
+00:13:01,630 --> 00:13:07,380
+سألتكم، الـ cluster الأول بيمثل ايش؟ معظمكم حيقولوا والله
+
+161
+00:13:07,380 --> 00:13:12,880
+هذا بيمثل المثلثات، الـ triangles، واللي تحت
+
+162
+00:13:12,880 --> 00:13:16,480
+التاني راح يمثل المربعات الحمراء، وهذه راح تمثل الدوائر
+
+163
+00:13:16,480 --> 00:13:19,340
+الخضراء، مظبوط؟ فبالتالي أنا بقدر أحسب الـ purity
+
+164
+00:13:19,340 --> 00:13:22,300
+تبع كل cluster، الـ cluster الأول بيحتوي على 9 عناصر
+
+165
+00:13:22,300 --> 00:13:26,420
+والـ maximum كانت لمين؟ للمثلثات، معناته 6 على 9
+
+166
+00:13:26,420 --> 00:13:29,880
+لكن مش هي الـ target بتاعتي، أنا ما بهمنيش الـ purity
+
+167
+00:13:29,880 --> 00:13:34,820
+تبع كل class، أنا اللي بيهمني الـ purity لكل output
+
+168
+00:13:34,820 --> 00:13:40,340
+مرة واحدة للـ algorithm، الـ 24 element، هروح
+
+169
+00:13:40,340 --> 00:13:44,920
+أدور هنا، الـ maximum هنا 6، الـ maximum هنا 5، الـ
+
+170
+00:13:44,920 --> 00:13:49,980
+maximum هنا 5، 6 زائد 5 زائد 5 على 24، 16 على 24
+
+171
+00:13:49,980 --> 00:13:53,660
+درجة النقاء اللي بيعطينا إياها الـ cluster هذا بشكل
+
+172
+00:13:53,660 --> 00:14:00,460
+عام، 76.67% وهيك بتتمّ حساب الـ purity بتاعتنا هنا
+
+173
+00:14:00,460 --> 00:14:04,220
+طبعاً كمان مرة برجع بقول، أنا بقدر أتكلّم بشكل مبدئي
+
+174
+00:14:04,220 --> 00:14:09,910
+الـ majority تبع كل cluster، كذا غالبية تبع كل
+
+175
+00:14:09,910 -->
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/GPEcN85s2Oo_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/GPEcN85s2Oo_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..ab9fba34d7eabd9a968ea069d73522125024a2b9
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/GPEcN85s2Oo_raw.json
@@ -0,0 +1 @@
+{"segments": [{"id": 1, "seek": 2548, "start": 1.14, "end": 25.48, "text": "باسم الله و الحمد لله و الصلاة والسلام علي رسول الله هذا التسجيل الأخير ان شاء الله في chapter ال clustering عفوا قبل الأخير بيضللنا في تسجيل ان شاء الله هيكون عملي باعتماد ال python الصحيح فشوف في شغل ال python بعض الإبداعات منكم و بعضكم .. حلو حلو حلو طبعك ماستور", "tokens": [3555, 32277, 2304, 21984, 4032, 21542, 2304, 3215, 24976, 3224, 4032, 31767, 15040, 3660, 16070, 3794, 37440, 25894, 12602, 3794, 12610, 21984, 23758, 16712, 3794, 7435, 26895, 16247, 9778, 13546, 16472, 13412, 16606, 21984, 8978, 7187, 2423, 13630, 278, 6225, 5172, 14407, 12174, 36150, 16247, 9778, 13546, 4724, 1829, 11242, 1211, 1211, 8315, 8978, 6055, 3794, 7435, 26895, 16472, 13412, 16606, 21984, 8032, 1829, 30544, 6225, 2304, 20292, 4724, 995, 34268, 15042, 3215, 2423, 38797, 31767, 5016, 1829, 5016, 6156, 8592, 38688, 8978, 13412, 17082, 1211, 2423, 38797, 45030, 11242, 33688, 3555, 28259, 3615, 9307, 9154, 24793, 4032, 45030, 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0.95556640625}, {"start": 419.74, "end": 419.92, "word": " بدي", "probability": 0.5670166015625}, {"start": 419.92, "end": 420.26, "word": " ميثل", "probability": 0.681640625}, {"start": 420.26, "end": 420.64, "word": " Class", "probability": 0.681640625}], "temperature": 1.0}, {"id": 18, "seek": 44076, "start": 421.3, "end": 440.76, "text": "فأنا بفترض أنه عندي data set مكوّنة من three classes label data set مكوّنة من three classes بتسميهم T1 وT2 وT3 من true true cluster أو true segment أو true partition سميها زي ما بدك true label سميها زي ما بدكوا", "tokens": [5172, 10721, 8315, 4724, 5172, 2655, 43042, 14739, 3224, 18871, 16254, 1412, 992, 3714, 4117, 2407, 11703, 1863, 3660, 9154, 1045, 5359, 7645, 1412, 992, 3714, 4117, 2407, 11703, 1863, 3660, 9154, 1045, 5359, 39894, 38251, 1829, 16095, 314, 16, 4032, 51, 17, 4032, 51, 18, 9154, 2074, 2074, 13630, 34051, 2074, 9469, 34051, 2074, 24808, 8608, 2304, 1829, 11296, 30767, 1829, 19446, 47525, 4117, 2074, 7645, 8608, 2304, 1829, 11296, 30767, 1829, 19446, 47525, 4117, 14407], "avg_logprob": -0.24318909759704882, "compression_ratio": 1.6845238095238095, "no_speech_prob": 0.0, "words": [{"start": 421.3, "end": 421.62, "word": "فأنا", "probability": 0.5541178385416666}, {"start": 421.62, "end": 422.04, "word": " بفترض", "probability": 0.9183349609375}, {"start": 422.04, "end": 422.28, "word": " أنه", "probability": 0.453125}, {"start": 422.28, "end": 422.52, "word": " عندي", "probability": 0.849853515625}, {"start": 422.52, "end": 422.8, "word": " data", "probability": 0.475341796875}, {"start": 422.8, "end": 423.24, "word": " set", "probability": 0.88330078125}, {"start": 423.24, "end": 423.98, "word": " مكوّنة", "probability": 0.814453125}, {"start": 423.98, "end": 424.16, "word": " من", "probability": 0.99267578125}, {"start": 424.16, "end": 424.54, "word": " three", "probability": 0.68603515625}, {"start": 424.54, "end": 425.2, "word": " classes", "probability": 0.94677734375}, {"start": 425.2, "end": 426.54, "word": " label", "probability": 0.541015625}, {"start": 426.54, "end": 426.84, "word": " data", "probability": 0.84228515625}, {"start": 426.84, "end": 427.18, "word": " set", "probability": 0.93603515625}, {"start": 427.18, "end": 427.68, "word": " مكوّنة", "probability": 0.868896484375}, {"start": 427.68, "end": 427.76, "word": " من", "probability": 0.9921875}, {"start": 427.76, "end": 427.98, "word": " three", "probability": 0.77685546875}, {"start": 427.98, "end": 428.48, "word": " classes", "probability": 0.94482421875}, {"start": 428.48, "end": 429.52, "word": " بتسميهم", "probability": 0.728668212890625}, {"start": 429.52, "end": 429.96, "word": " T1", "probability": 0.9052734375}, {"start": 429.96, "end": 430.58, "word": " وT2", "probability": 0.7605794270833334}, {"start": 430.58, "end": 431.14, "word": " وT3", "probability": 0.9611002604166666}, {"start": 431.14, "end": 431.52, "word": " من", "probability": 0.253662109375}, {"start": 431.52, "end": 431.86, "word": " true", "probability": 0.64208984375}, {"start": 431.86, "end": 433.08, "word": " true", "probability": 0.53759765625}, {"start": 433.08, "end": 433.44, "word": " cluster", "probability": 0.92626953125}, {"start": 433.44, "end": 433.68, "word": " أو", "probability": 0.60546875}, {"start": 433.68, "end": 434.0, "word": " true", "probability": 0.9384765625}, {"start": 434.0, "end": 435.94, "word": " segment", "probability": 0.955078125}, {"start": 435.94, "end": 437.06, "word": " أو", "probability": 0.6025390625}, {"start": 437.06, "end": 437.42, "word": " true", "probability": 0.94482421875}, {"start": 437.42, "end": 437.96, "word": " partition", "probability": 0.97802734375}, {"start": 437.96, "end": 438.36, "word": " سميها", "probability": 0.81201171875}, {"start": 438.36, "end": 438.52, "word": " زي", "probability": 0.969482421875}, {"start": 438.52, "end": 438.58, "word": " ما", "probability": 0.9296875}, {"start": 438.58, "end": 438.96, "word": " بدك", "probability": 0.956298828125}, {"start": 438.96, "end": 439.4, "word": " true", "probability": 0.88720703125}, {"start": 439.4, "end": 439.84, "word": " label", "probability": 0.96240234375}, {"start": 439.84, "end": 440.2, "word": " سميها", "probability": 0.90185546875}, {"start": 440.2, "end": 440.34, "word": " زي", "probability": 0.994140625}, {"start": 440.34, "end": 440.42, "word": " ما", "probability": 0.9697265625}, {"start": 440.42, "end": 440.76, "word": " بدكوا", "probability": 0.9386393229166666}], "temperature": 1.0}, {"id": 19, "seek": 46902, "start": 442.16, "end": 469.02, "text": "وC1 وC2 وC3 هما الـ clusters اللي انشغلياهم من ال algorithm اللي موجود عندها ايش راح اجلب؟ ايش بفهم ال contingency matrix؟ انه في C1 C1 خمسة وعشرين element بينتمي ل T2 وخمسة element بينتمي ل T3 وخمس عناصر بينتمي ل T3", "tokens": [2407, 34, 16, 4032, 34, 17, 4032, 34, 18, 8032, 15042, 2423, 39184, 23313, 13672, 1829, 16472, 8592, 17082, 20292, 995, 16095, 9154, 2423, 9284, 13672, 1829, 3714, 29245, 23328, 43242, 11296, 1975, 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{"start": 450.56, "end": 450.88, "word": " بفهم", "probability": 0.98046875}, {"start": 450.88, "end": 451.0, "word": " ال", "probability": 0.94384765625}, {"start": 451.0, "end": 451.58, "word": " contingency", "probability": 0.6868896484375}, {"start": 451.58, "end": 453.28, "word": " matrix؟", "probability": 0.7529296875}, {"start": 453.28, "end": 454.18, "word": " انه", "probability": 0.924560546875}, {"start": 454.18, "end": 455.2, "word": " في", "probability": 0.9462890625}, {"start": 455.2, "end": 456.14, "word": " C1", "probability": 0.946533203125}, {"start": 456.14, "end": 457.4, "word": " C1", "probability": 0.626708984375}, {"start": 457.4, "end": 458.2, "word": " خمسة", "probability": 0.92919921875}, {"start": 458.2, "end": 459.1, "word": " وعشرين", "probability": 0.8543701171875}, {"start": 459.1, "end": 459.86, "word": " element", "probability": 0.87646484375}, {"start": 459.86, "end": 460.9, "word": " بينتمي", "probability": 0.68511962890625}, {"start": 460.9, "end": 461.0, "word": " ل", "probability": 0.432861328125}, {"start": 461.0, "end": 461.56, "word": " T2", "probability": 0.78369140625}, {"start": 461.56, "end": 465.02, "word": " وخمسة", "probability": 0.9099609375}, {"start": 465.02, "end": 465.44, "word": " element", "probability": 0.96533203125}, {"start": 465.44, "end": 466.04, "word": " بينتمي", "probability": 0.92626953125}, {"start": 466.04, "end": 466.2, "word": " ل", "probability": 0.9833984375}, {"start": 466.2, "end": 466.72, "word": " T3", "probability": 0.887451171875}, {"start": 466.72, "end": 467.38, "word": " وخمس", "probability": 0.893310546875}, {"start": 467.38, "end": 467.84, "word": " عناصر", "probability": 0.9508463541666666}, {"start": 467.84, "end": 468.16, "word": " بينتمي", "probability": 0.9609375}, {"start": 468.16, "end": 468.3, "word": " ل", "probability": 0.9794921875}, {"start": 468.3, "end": 469.02, "word": " T3", "probability": 0.966552734375}], "temperature": 1.0}, {"id": 20, "seek": 49365, "start": 470.09, "end": 493.65, "text": "يعني عندي 25 عنصر من T ناتج ال clustering C1 بيحتوي على 30 عنصر 25 منهم حقيقة من ال class التاني و 5 من ال class التالت و لا واحد من ال class الأول", "tokens": [40228, 22653, 18871, 16254, 3552, 18871, 9381, 2288, 9154, 314, 8717, 9307, 7435, 2423, 13630, 278, 383, 16, 4724, 1829, 33753, 45865, 15844, 2217, 18871, 9381, 2288, 3552, 9154, 16095, 11331, 38436, 28671, 9154, 2423, 1508, 16712, 7649, 1829, 4032, 1025, 9154, 2423, 1508, 16712, 6027, 2655, 4032, 20193, 36764, 24401, 9154, 2423, 1508, 16247, 12610], "avg_logprob": -0.22423244986617774, "compression_ratio": 1.5586206896551724, "no_speech_prob": 0.0, "words": [{"start": 470.09, "end": 470.41, "word": "يعني", "probability": 0.766845703125}, {"start": 470.41, "end": 470.65, "word": " عندي", "probability": 0.6339111328125}, {"start": 470.65, "end": 471.27, "word": " 25", "probability": 0.78564453125}, {"start": 471.27, "end": 472.11, "word": " عنصر", "probability": 0.98193359375}, {"start": 472.11, "end": 473.09, "word": " من", "probability": 0.90380859375}, {"start": 473.09, "end": 473.47, "word": " T", "probability": 0.77734375}, {"start": 473.47, "end": 476.73, "word": " ناتج", "probability": 0.67529296875}, {"start": 476.73, "end": 476.83, "word": " ال", "probability": 0.80419921875}, {"start": 476.83, "end": 477.39, "word": " clustering", "probability": 0.682373046875}, {"start": 477.39, "end": 479.95, "word": " C1", "probability": 0.5845947265625}, {"start": 479.95, "end": 481.55, "word": " بيحتوي", "probability": 0.77288818359375}, {"start": 481.55, "end": 481.75, "word": " على", "probability": 0.681640625}, {"start": 481.75, "end": 482.29, "word": " 30", "probability": 0.92626953125}, {"start": 482.29, "end": 483.61, "word": " عنصر", "probability": 0.9954427083333334}, {"start": 483.61, "end": 484.55, "word": " 25", "probability": 0.51953125}, {"start": 484.55, "end": 485.67, "word": " منهم", "probability": 0.971923828125}, {"start": 485.67, "end": 486.47, "word": " حقيقة", "probability": 0.8971354166666666}, {"start": 486.47, "end": 487.49, "word": " من", "probability": 0.9560546875}, {"start": 487.49, "end": 487.65, "word": " ال", "probability": 0.93017578125}, {"start": 487.65, "end": 487.91, "word": " class", "probability": 0.8916015625}, {"start": 487.91, "end": 488.53, "word": " التاني", "probability": 0.8837890625}, {"start": 488.53, "end": 489.19, "word": " و", "probability": 0.95361328125}, {"start": 489.19, "end": 489.55, "word": " 5", "probability": 0.5234375}, {"start": 489.55, "end": 491.19, "word": " من", "probability": 0.98583984375}, {"start": 491.19, "end": 491.31, "word": " ال", "probability": 0.92822265625}, {"start": 491.31, "end": 491.53, "word": " class", "probability": 0.978515625}, {"start": 491.53, "end": 492.01, "word": " التالت", "probability": 0.9796549479166666}, {"start": 492.01, "end": 492.35, "word": " و", "probability": 0.609375}, {"start": 492.35, "end": 492.55, "word": " لا", "probability": 0.54052734375}, {"start": 492.55, "end": 492.89, "word": " واحد", "probability": 0.91748046875}, {"start": 492.89, "end": 493.01, "word": " من", "probability": 0.9853515625}, {"start": 493.01, "end": 493.09, "word": " ال", "probability": 0.9599609375}, {"start": 493.09, "end": 493.31, "word": " class", "probability": 0.96533203125}, {"start": 493.31, "end": 493.65, "word": " الأول", "probability": 0.888427734375}], "temperature": 1.0}, {"id": 21, "seek": 52010, "start": 494.94, "end": 520.1, "text": "T2 أو cluster C2 بيحتوي على 35 عنصر 15 من ال class الأول و 20 من ال class التالت cluster تلاتة بيحتوي على عشر عناصر فقط كلهم كلهم بيتبعوا T1 الآن هذا الكلام إذا انا افهمته", "tokens": [51, 17, 34051, 13630, 383, 17, 4724, 1829, 33753, 45865, 15844, 6976, 18871, 9381, 2288, 2119, 9154, 2423, 1508, 16247, 12610, 4032, 945, 9154, 2423, 1508, 16712, 6027, 2655, 13630, 6055, 1211, 9307, 3660, 4724, 1829, 33753, 45865, 15844, 6225, 46309, 18871, 33546, 2288, 6156, 47432, 28242, 16095, 28242, 16095, 4724, 36081, 3555, 3615, 14407, 314, 16, 6024, 48506, 23758, 2423, 28820, 10943, 11933, 15730, 1975, 8315, 1975, 5172, 16095, 47395], "avg_logprob": -0.1857638932350609, "compression_ratio": 1.6325301204819278, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 494.94, "end": 495.64, "word": "T2", "probability": 0.820556640625}, {"start": 495.64, "end": 496.2, "word": " أو", "probability": 0.80859375}, {"start": 496.2, "end": 496.54, "word": " cluster", "probability": 0.499755859375}, {"start": 496.54, "end": 497.44, "word": " C2", "probability": 0.6282958984375}, {"start": 497.44, "end": 498.7, "word": " بيحتوي", "probability": 0.79266357421875}, {"start": 498.7, "end": 498.88, "word": " على", "probability": 0.853515625}, {"start": 498.88, "end": 499.66, "word": " 35", "probability": 0.81884765625}, {"start": 499.66, "end": 500.38, "word": " عنصر", "probability": 0.9900716145833334}, {"start": 500.38, "end": 501.6, "word": " 15", "probability": 0.72802734375}, {"start": 501.6, "end": 502.22, "word": " من", "probability": 0.9736328125}, {"start": 502.22, "end": 502.56, "word": " ال", "probability": 0.90576171875}, {"start": 502.56, "end": 502.86, "word": " class", "probability": 0.5693359375}, {"start": 502.86, "end": 503.38, "word": " الأول", "probability": 0.93505859375}, {"start": 503.38, "end": 503.92, "word": " و", "probability": 0.9091796875}, {"start": 503.92, "end": 504.4, "word": " 20", "probability": 0.7119140625}, {"start": 504.4, "end": 504.66, "word": " من", "probability": 0.990234375}, {"start": 504.66, "end": 504.84, "word": " ال", "probability": 0.91015625}, {"start": 504.84, "end": 505.1, "word": " class", "probability": 0.939453125}, {"start": 505.1, "end": 505.68, "word": " التالت", "probability": 0.9659830729166666}, {"start": 505.68, "end": 507.44, "word": " cluster", "probability": 0.705078125}, {"start": 507.44, "end": 508.16, "word": " تلاتة", "probability": 0.82745361328125}, {"start": 508.16, "end": 509.76, "word": " بيحتوي", "probability": 0.9334716796875}, {"start": 509.76, "end": 509.96, "word": " على", "probability": 0.80908203125}, {"start": 509.96, "end": 510.38, "word": " عشر", "probability": 0.7509765625}, {"start": 510.38, "end": 510.94, "word": " عناصر", "probability": 0.99267578125}, {"start": 510.94, "end": 511.32, "word": " فقط", "probability": 0.992431640625}, {"start": 511.32, "end": 512.22, "word": " كلهم", "probability": 0.860107421875}, {"start": 512.22, "end": 513.48, "word": " كلهم", "probability": 0.6392822265625}, {"start": 513.48, "end": 514.58, "word": " بيتبعوا", "probability": 0.9103515625}, {"start": 514.58, "end": 515.06, "word": " T1", "probability": 0.944580078125}, {"start": 515.06, "end": 517.04, "word": " الآن", "probability": 0.7081298828125}, {"start": 517.04, "end": 517.94, "word": " هذا", "probability": 0.9326171875}, {"start": 517.94, "end": 518.48, "word": " الكلام", "probability": 0.9617513020833334}, {"start": 518.48, "end": 519.18, "word": " إذا", "probability": 0.879150390625}, {"start": 519.18, "end": 519.38, "word": " انا", "probability": 0.6513671875}, {"start": 519.38, "end": 520.1, "word": " افهمته", "probability": 0.8857421875}], "temperature": 1.0}, {"id": 22, "seek": 54899, "start": 521.27, "end": 548.99, "text": "معناته أنا مش ضروري الـ Clustering algorithm تبعي يكون صح مائة في المائة ممتاز طب متى بيكون صح مائة في المائة إذا والله أنا إجيت قولت هيك مثلًا حصرت على صورة واحدة من الصور التالية فانا هتكلم عن ال matrix لو أنا إجيت قولت هنا والله عندي هنا تلاتين", "tokens": [2304, 3615, 8315, 47395, 41850, 37893, 48812, 2288, 13063, 1829, 2423, 39184, 2033, 48673, 9284, 6055, 3555, 3615, 1829, 7251, 30544, 20328, 5016, 3714, 16373, 3660, 8978, 9673, 16373, 3660, 3714, 2304, 2655, 31377, 23032, 3555, 44650, 7578, 4724, 1829, 30544, 20328, 5016, 3714, 16373, 3660, 8978, 9673, 16373, 3660, 11933, 15730, 16070, 43761, 41850, 11933, 7435, 36081, 12174, 12610, 2655, 39896, 4117, 50113, 1211, 14111, 995, 11331, 9381, 43500, 15844, 20328, 13063, 3660, 36764, 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"probability": 0.9931640625}, {"start": 538.87, "end": 538.99, "word": " من", "probability": 0.99169921875}, {"start": 538.99, "end": 539.23, "word": " الصور", "probability": 0.97607421875}, {"start": 539.23, "end": 539.73, "word": " التالية", "probability": 0.9814453125}, {"start": 539.73, "end": 540.33, "word": " فانا", "probability": 0.70703125}, {"start": 540.33, "end": 540.65, "word": " هتكلم", "probability": 0.934814453125}, {"start": 540.65, "end": 540.83, "word": " عن", "probability": 0.50537109375}, {"start": 540.83, "end": 540.95, "word": " ال", "probability": 0.9501953125}, {"start": 540.95, "end": 541.29, "word": " matrix", "probability": 0.73193359375}, {"start": 541.29, "end": 542.11, "word": " لو", "probability": 0.798828125}, {"start": 542.11, "end": 542.39, "word": " أنا", "probability": 0.80615234375}, {"start": 542.39, "end": 542.65, "word": " إجيت", "probability": 0.9544270833333334}, {"start": 542.65, "end": 542.99, "word": " قولت", "probability": 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{"start": 571.34, "end": 571.9, "word": " أصفر", "probability": 0.922607421875}, {"start": 571.9, "end": 573.9, "word": " طبعا", "probability": 0.9525146484375}, {"start": 573.9, "end": 574.12, "word": " هنا", "probability": 0.84765625}, {"start": 574.12, "end": 574.94, "word": " T1", "probability": 0.9345703125}, {"start": 574.94, "end": 576.44, "word": " T2", "probability": 0.8642578125}, {"start": 576.44, "end": 577.88, "word": " T3", "probability": 0.93310546875}, {"start": 577.88, "end": 578.08, "word": " وانا", "probability": 0.8645833333333334}, {"start": 578.08, "end": 578.76, "word": " اتعمدت", "probability": 0.794189453125}, {"start": 578.76, "end": 579.4, "word": " احط", "probability": 0.6492513020833334}, {"start": 579.4, "end": 579.9, "word": " القيم", "probability": 0.909912109375}, {"start": 579.9, "end": 580.28, "word": " نفس", "probability": 0.81640625}, {"start": 580.28, "end": 580.8, "word": " الكيفية", "probability": 0.8175455729166666}], "temperature": 1.0}, {"id": 24, "seek": 61141, "start": 582.22, "end": 611.42, "text": "لحظوا معايا إنه فعليا كل cluster completely pure صافي مافيش فيه أي .. يعني كل cluster مثل واحدة من ال classes اللي موجودة عندى كل cluster مثل واحدة فقط من ال classes اللي موجودة عندى وهنا بتكلم إنه فعليا كل cluster نقي تماما بيحتوي عناصر من نفس ال class فقط عشان هي كان بنتكلم احنا على ال purity نقاوة أو نقاء درجة النقاء", "tokens": [1211, 5016, 19913, 14407, 20449, 995, 25528, 36145, 3224, 6156, 3615, 20292, 995, 28242, 13630, 2584, 6075, 20328, 31845, 1829, 19446, 41185, 8592, 8978, 3224, 36632, 4386, 37495, 22653, 28242, 13630, 50113, 1211, 36764, 24401, 3660, 9154, 2423, 5359, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 7578, 28242, 13630, 50113, 1211, 36764, 24401, 3660, 6156, 47432, 9154, 2423, 5359, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 7578, 37037, 8315, 4724, 2655, 4117, 19528, 36145, 3224, 6156, 3615, 20292, 995, 28242, 13630, 8717, 38436, 46811, 10943, 995, 4724, 1829, 33753, 45865, 18871, 33546, 2288, 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{"start": 586.76, "end": 588.46, "word": " صافي", "probability": 0.8458658854166666}, {"start": 588.46, "end": 589.22, "word": " مافيش", "probability": 0.81103515625}, {"start": 589.22, "end": 589.66, "word": " فيه", "probability": 0.871826171875}, {"start": 589.66, "end": 589.92, "word": " أي", "probability": 0.7744140625}, {"start": 589.92, "end": 590.08, "word": " ..", "probability": 0.2366943359375}, {"start": 590.08, "end": 590.28, "word": " يعني", "probability": 0.947509765625}, {"start": 590.28, "end": 590.72, "word": " كل", "probability": 0.93017578125}, {"start": 590.72, "end": 591.16, "word": " cluster", "probability": 0.98095703125}, {"start": 591.16, "end": 591.84, "word": " مثل", "probability": 0.761474609375}, {"start": 591.84, "end": 592.24, "word": " واحدة", "probability": 0.9903971354166666}, {"start": 592.24, "end": 592.36, "word": " من", "probability": 0.9755859375}, {"start": 592.36, "end": 592.5, "word": " ال", "probability": 0.95068359375}, {"start": 592.5, "end": 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"probability": 0.97998046875}, {"start": 597.62, "end": 597.98, "word": " موجودة", "probability": 0.990234375}, {"start": 597.98, "end": 598.28, "word": " عندى", "probability": 0.860595703125}, {"start": 598.28, "end": 598.82, "word": " وهنا", "probability": 0.81494140625}, {"start": 598.82, "end": 599.26, "word": " بتكلم", "probability": 0.73834228515625}, {"start": 599.26, "end": 599.52, "word": " إنه", "probability": 0.9326171875}, {"start": 599.52, "end": 599.92, "word": " فعليا", "probability": 0.969482421875}, {"start": 599.92, "end": 600.26, "word": " كل", "probability": 0.9921875}, {"start": 600.26, "end": 600.9, "word": " cluster", "probability": 0.982421875}, {"start": 600.9, "end": 601.24, "word": " نقي", "probability": 0.98779296875}, {"start": 601.24, "end": 601.92, "word": " تماما", "probability": 0.9944661458333334}, {"start": 601.92, "end": 602.72, "word": " بيحتوي", "probability": 0.91455078125}, {"start": 602.72, "end": 603.28, "word": " عناصر", "probability": 0.99169921875}, {"start": 603.28, "end": 603.46, "word": " من", "probability": 0.9873046875}, {"start": 603.46, "end": 603.68, "word": " نفس", "probability": 0.99853515625}, {"start": 603.68, "end": 603.82, "word": " ال", "probability": 0.9873046875}, {"start": 603.82, "end": 604.14, "word": " class", "probability": 0.87744140625}, {"start": 604.14, "end": 604.92, "word": " فقط", "probability": 0.99658203125}, {"start": 604.92, "end": 606.5, "word": " عشان", "probability": 0.9680989583333334}, {"start": 606.5, "end": 606.6, "word": " هي", "probability": 0.98779296875}, {"start": 606.6, "end": 606.74, "word": " كان", "probability": 0.69091796875}, {"start": 606.74, "end": 607.12, "word": " بنتكلم", "probability": 0.81646728515625}, {"start": 607.12, "end": 607.3, "word": " احنا", "probability": 0.7509765625}, {"start": 607.3, "end": 607.6, "word": " على", "probability": 0.4619140625}, {"start": 607.6, "end": 607.74, "word": " ال", "probability": 0.91455078125}, {"start": 607.74, "end": 608.14, "word": " purity", "probability": 0.8759765625}, {"start": 608.14, "end": 609.28, "word": " نقاوة", "probability": 0.92685546875}, {"start": 609.28, "end": 610.02, "word": " أو", "probability": 0.85009765625}, {"start": 610.02, "end": 610.44, "word": " نقاء", "probability": 0.7333984375}, {"start": 610.44, "end": 610.9, "word": " درجة", "probability": 0.8668619791666666}, {"start": 610.9, "end": 611.42, "word": " النقاء", "probability": 0.90087890625}], "temperature": 1.0}, {"id": 25, "seek": 63686, "start": 612.56, "end": 636.86, "text": "طيب، بما أن الحالة دي هي الـ optimal case أو الـ ideal case واللي أنا فعلا مش هحصل عليها، أنا هحصل على شغل مشابه زي هيك من خلال الـ contingency matrix كيف أحسب الـ purity؟ الـ purity هي تساوي عبارة عن مجموع ال maximum في كل صفر ال maximum عدد maximum للـ Ti تنتمي لC", "tokens": [9566, 1829, 3555, 12399, 4724, 15042, 14739, 21542, 6027, 3660, 11778, 1829, 39896, 2423, 39184, 16252, 1389, 34051, 2423, 39184, 7157, 1389, 16070, 20292, 41850, 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العناصر بالتساوي 8888 بعد ما طبقت ال clustering تبعت ال cluster C1 فيها العناصر التالية ال cluster C2 و ال cluster C3 طبعا هنا في مصطلح جديد اضيفه نقاء كل cluster نقاء كل cluster بشكل مستقل اذا سألتك ال cluster الأول بمثل ايش؟", "tokens": [51, 470, 7846, 4032, 50, 358, 543, 4032, 2304, 7435, 38251, 18863, 1863, 33546, 2288, 20666, 2655, 3794, 995, 45865, 24587, 16919, 39182, 19446, 23032, 3555, 38149, 2423, 13630, 278, 6055, 3555, 34268, 2423, 13630, 383, 16, 8978, 11296, 18863, 1863, 33546, 2288, 16712, 6027, 10632, 2423, 13630, 383, 17, 4032, 2423, 13630, 383, 18, 23032, 3555, 3615, 995, 34105, 8978, 3714, 9381, 9566, 1211, 5016, 10874, 16254, 3215, 1975, 11242, 33911, 3224, 8717, 4587, 16606, 28242, 13630, 8717, 4587, 16606, 28242, 13630, 4724, 8592, 28820, 3714, 14851, 4587, 1211, 1975, 15730, 8608, 10721, 1211, 2655, 4117, 2423, 13630, 16247, 12610, 4724, 2304, 12984, 1211, 1975, 1829, 8592, 22807], "avg_logprob": -0.27244318750771607, "compression_ratio": 1.7534883720930232, 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{"start": 955.43, "end": 955.63, "word": " على", "probability": 0.740234375}, {"start": 955.63, "end": 955.85, "word": " three", "probability": 0.599609375}, {"start": 955.85, "end": 956.33, "word": " different", "probability": 0.91455078125}, {"start": 956.33, "end": 956.89, "word": " metrics", "probability": 0.7822265625}], "temperature": 1.0}, {"id": 40, "seek": 98697, "start": 957.77, "end": 986.97, "text": "3 مترات مختلفة لـ Purity وهي مطموعة منكوا حسابيتها لأنها سهلة ال maximum ال summation للماكسيممم في كل cluster على عدد ال elements كلها في ال data set وهي بتمثل ال purity في عندي مجرد مصطلحين أخرين أخرين بدي أسمعهم بدي أحرفهم اللي هو adjusted rank index وnormalize mutual information هي عبارة عن rank بحسب ال similarity between any two clusters", "tokens": [18, 44650, 2288, 9307, 3714, 46456, 46538, 3660, 5296, 39184, 430, 3051, 37037, 1829, 3714, 9566, 2304, 2407, 27884, 9154, 4117, 14407, 11331, 3794, 16758, 36081, 11296, 5296, 33456, 11296, 8608, 3224, 37977, 2423, 6674, 2423, 28811, 5296, 19528, 995, 4117, 3794, 32640, 2304, 2304, 8978, 28242, 13630, 15844, 6225, 3215, 3215, 2423, 4959, 28242, 11296, 8978, 2423, 1412, 992, 37037, 1829, 39894, 2304, 12984, 1211, 2423, 34382, 8978, 18871, 16254, 3714, 7435, 2288, 3215, 3714, 9381, 9566, 1211, 5016, 9957, 5551, 34740, 9957, 5551, 34740, 9957, 4724, 16254, 5551, 38251, 3615, 16095, 4724, 16254, 5551, 5016, 28480, 16095, 13672, 1829, 31439, 19871, 6181, 8186, 4032, 23157, 1125, 16917, 1589, 39896, 6225, 3555, 9640, 3660, 18871, 6181, 4724, 5016, 35457, 2423, 32194, 1296, 604, 732, 23313], "avg_logprob": -0.33021654716626864, "compression_ratio": 1.6148867313915858, "no_speech_prob": 0.00124359130859375, "words": [{"start": 957.77, "end": 958.05, "word": "3", "probability": 0.17626953125}, {"start": 958.05, "end": 959.03, "word": " مترات", "probability": 0.4018961588541667}, {"start": 959.03, "end": 959.03, "word": " مختلفة", "probability": 0.877685546875}, {"start": 959.03, "end": 959.29, "word": " لـ", "probability": 0.5615234375}, {"start": 959.29, "end": 959.59, "word": " Purity", "probability": 0.646484375}, {"start": 959.59, "end": 959.83, "word": " وهي", "probability": 0.6168212890625}, {"start": 959.83, "end": 960.17, "word": " مطموعة", "probability": 0.89853515625}, {"start": 960.17, "end": 960.49, "word": " منكوا", "probability": 0.6702473958333334}, {"start": 960.49, "end": 960.97, "word": " حسابيتها", "probability": 0.84111328125}, {"start": 960.97, "end": 961.23, "word": " لأنها", "probability": 0.8463541666666666}, {"start": 961.23, "end": 961.59, "word": " سهلة", "probability": 0.96728515625}, {"start": 961.59, "end": 962.17, "word": " ال", "probability": 0.44482421875}, {"start": 962.17, "end": 962.77, "word": " maximum", "probability": 0.36962890625}, {"start": 962.77, "end": 963.71, "word": " ال", "probability": 0.26904296875}, {"start": 963.71, "end": 964.07, "word": " summation", "probability": 0.55615234375}, {"start": 964.07, "end": 964.87, "word": " للماكسيممم", "probability": 0.683837890625}, {"start": 964.87, "end": 964.99, "word": " في", "probability": 0.68798828125}, {"start": 964.99, "end": 965.23, "word": " كل", "probability": 0.9814453125}, {"start": 965.23, "end": 965.63, "word": " cluster", "probability": 0.8486328125}, {"start": 965.63, "end": 965.95, "word": " على", "probability": 0.7734375}, {"start": 965.95, "end": 966.25, "word": " عدد", "probability": 0.9830729166666666}, {"start": 966.25, "end": 966.39, "word": " ال", "probability": 0.92919921875}, {"start": 966.39, "end": 966.71, "word": " elements", "probability": 0.814453125}, {"start": 966.71, "end": 967.07, "word": " كلها", "probability": 0.623779296875}, {"start": 967.07, "end": 967.41, "word": " في", "probability": 0.77587890625}, {"start": 967.41, "end": 967.53, "word": " ال", "probability": 0.8974609375}, {"start": 967.53, "end": 967.67, "word": " data", "probability": 0.432861328125}, {"start": 967.67, "end": 968.01, "word": " set", "probability": 0.9306640625}, {"start": 968.01, "end": 968.35, "word": " وهي", "probability": 0.526123046875}, {"start": 968.35, "end": 968.73, "word": " بتمثل", "probability": 0.80999755859375}, {"start": 968.73, "end": 968.83, "word": " ال", "probability": 0.7822265625}, {"start": 968.83, "end": 969.13, "word": " purity", "probability": 0.5244140625}, {"start": 969.13, "end": 969.77, "word": " في", "probability": 0.4169921875}, {"start": 969.77, "end": 970.15, "word": " عندي", "probability": 0.76953125}, {"start": 970.15, "end": 970.99, "word": " مجرد", "probability": 0.974365234375}, {"start": 970.99, "end": 971.59, "word": " مصطلحين", "probability": 0.9813639322916666}, {"start": 971.59, "end": 972.15, "word": " أخرين", "probability": 0.90185546875}, {"start": 972.15, "end": 973.91, "word": " أخرين", "probability": 0.8291015625}, {"start": 973.91, "end": 974.21, "word": " بدي", "probability": 0.6844482421875}, {"start": 974.21, "end": 974.61, "word": " أسمعهم", "probability": 0.9603271484375}, {"start": 974.61, "end": 974.89, "word": " بدي", "probability": 0.73291015625}, {"start": 974.89, "end": 975.47, "word": " أحرفهم", "probability": 0.9053955078125}, {"start": 975.47, "end": 975.87, "word": " اللي", "probability": 0.871826171875}, {"start": 975.87, "end": 975.93, "word": " هو", "probability": 0.33447265625}, {"start": 975.93, "end": 976.47, "word": " adjusted", "probability": 0.64599609375}, {"start": 976.47, "end": 976.91, "word": " rank", "probability": 0.252685546875}, {"start": 976.91, "end": 978.61, "word": " index", "probability": 0.75244140625}, {"start": 978.61, "end": 979.81, "word": " وnormalize", "probability": 0.4283854166666667}, {"start": 979.81, "end": 980.25, "word": " mutual", "probability": 0.9150390625}, {"start": 980.25, "end": 981.09, "word": " information", "probability": 0.90234375}, {"start": 981.09, "end": 982.49, "word": " هي", "probability": 0.406982421875}, {"start": 982.49, "end": 982.93, "word": " عبارة", "probability": 0.996826171875}, {"start": 982.93, "end": 983.27, "word": " عن", "probability": 0.99755859375}, {"start": 983.27, "end": 983.85, "word": " rank", "probability": 0.7822265625}, {"start": 983.85, "end": 984.81, "word": " بحسب", "probability": 0.6547037760416666}, {"start": 984.81, "end": 985.01, "word": " ال", "probability": 0.57177734375}, {"start": 985.01, "end": 985.45, "word": " similarity", "probability": 0.90478515625}, {"start": 985.45, "end": 985.79, "word": " between", "probability": 0.81689453125}, {"start": 985.79, "end": 986.31, "word": " any", "probability": 0.8251953125}, {"start": 986.31, "end": 986.49, "word": " two", "probability": 0.90673828125}, {"start": 986.49, "end": 986.97, "word": " clusters", "probability": 0.91650390625}], "temperature": 1.0}, {"id": 41, "seek": 99944, "start": 988.6, "end": 999.44, "text": "حسبة مش مطلوبة لكن فعلياً هي عبارة عن evaluation metric انا ممكن او جد استخدمها مع ال clustering اللي يعطيكوا العافية و بتمنالكوا التوفيق السلام عليكم ورحمة الله", "tokens": [5016, 3794, 49401, 37893, 3714, 9566, 1211, 37746, 3660, 44381, 6156, 3615, 20292, 995, 14111, 39896, 6225, 3555, 9640, 3660, 18871, 13344, 20678, 1975, 8315, 3714, 43020, 1975, 2407, 10874, 3215, 44713, 9778, 40448, 11296, 20449, 2423, 13630, 278, 13672, 1829, 37495, 9566, 1829, 4117, 14407, 18863, 31845, 10632, 4032, 39894, 27842, 6027, 4117, 14407, 16712, 38688, 1829, 4587, 21136, 37440, 25894, 24793, 4032, 2288, 35571, 3660, 21984], "avg_logprob": -0.30321559353151184, "compression_ratio": 1.4944444444444445, "no_speech_prob": 2.980232238769531e-07, "words": [{"start": 988.6, "end": 989.28, "word": "حسبة", "probability": 0.5787353515625}, {"start": 989.28, "end": 989.48, "word": " مش", "probability": 0.395263671875}, {"start": 989.48, "end": 990.06, "word": " مطلوبة", "probability": 0.916015625}, {"start": 990.06, "end": 990.42, "word": " لكن", "probability": 0.66015625}, {"start": 990.42, "end": 991.04, "word": " فعلياً", "probability": 0.6666015625}, {"start": 991.04, "end": 991.18, "word": " هي", "probability": 0.75244140625}, {"start": 991.18, "end": 991.54, "word": " عبارة", "probability": 0.9388427734375}, {"start": 991.54, "end": 991.66, "word": " عن", "probability": 0.98046875}, {"start": 991.66, "end": 992.2, "word": " evaluation", "probability": 0.685546875}, {"start": 992.2, "end": 992.76, "word": " metric", "probability": 0.85302734375}, {"start": 992.76, "end": 993.26, "word": " انا", "probability": 0.5648193359375}, {"start": 993.26, "end": 993.52, "word": " ممكن", "probability": 0.884765625}, {"start": 993.52, "end": 993.72, "word": " او", "probability": 0.5391845703125}, {"start": 993.72, "end": 993.88, "word": " جد", "probability": 0.740478515625}, {"start": 993.88, "end": 994.58, "word": " استخدمها", "probability": 0.9453125}, {"start": 994.58, "end": 994.92, "word": " مع", "probability": 0.90625}, {"start": 994.92, "end": 995.2, "word": " ال", "probability": 0.74951171875}, {"start": 995.2, "end": 996.0, "word": " clustering", "probability": 0.640380859375}, {"start": 996.0, "end": 996.34, "word": " اللي", "probability": 0.5684814453125}, {"start": 996.34, "end": 996.58, "word": " يعطيكوا", "probability": 0.79033203125}, {"start": 996.58, "end": 996.92, "word": " العافية", "probability": 0.9456380208333334}, {"start": 996.92, "end": 997.02, "word": " و", "probability": 0.8203125}, {"start": 997.02, "end": 997.74, "word": " بتمنالكوا", "probability": 0.656884765625}, {"start": 997.74, "end": 998.28, "word": " التوفيق", "probability": 0.9559326171875}, {"start": 998.28, "end": 998.6, "word": " السلام", "probability": 0.852783203125}, {"start": 998.6, "end": 998.92, "word": " عليكم", "probability": 0.95556640625}, {"start": 998.92, "end": 999.32, "word": " ورحمة", "probability": 0.891357421875}, {"start": 999.32, "end": 999.44, "word": " الله", "probability": 0.9560546875}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 999.5261875, "duration_after_vad": 962.4584687500012}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/GPEcN85s2Oo_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/GPEcN85s2Oo_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..8196cc85f4b8406ebf235a248ec80c82214d102f
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/GPEcN85s2Oo_raw.srt
@@ -0,0 +1,864 @@
+1
+00:00:01,140 --> 00:00:03,520
+باسم الله و الحمد لله و الصلاة والسلام علي رسول
+
+2
+00:00:03,520 --> 00:00:08,140
+الله هذا التسجيل الأخير ان شاء الله في chapter ال
+
+3
+00:00:08,140 --> 00:00:12,840
+clustering عفوا قبل الأخير بيضللنا في تسجيل ان شاء
+
+4
+00:00:12,840 --> 00:00:16,540
+الله هيكون عملي باعتماد ال python الصحيح فشوف في
+
+5
+00:00:16,540 --> 00:00:24,320
+شغل ال python بعض الإبداعات منكم و بعضكم .. حلو
+
+6
+00:00:24,320 --> 00:00:25,480
+حلو حلو طبعك ماستور
+
+7
+00:00:28,370 --> 00:00:31,030
+البداية الشبتر ان ال cluster هي عبارة عن عملية
+
+8
+00:00:31,030 --> 00:00:34,230
+تقسيم ال instances بناء على تشابه او similarities
+
+9
+00:00:34,230 --> 00:00:38,570
+ما بينهم لمجموعات في عند partition ال cluster و ال
+
+10
+00:00:38,570 --> 00:00:41,070
+partition ال cluster انه مايكونش في عنده overlap
+
+11
+00:00:41,070 --> 00:00:44,550
+clusters و في عنده hierarchical cluster انه انا
+
+12
+00:00:44,550 --> 00:00:48,870
+فعليا مقدر اشوف كل cluster بينتمي لأي cluster و
+
+13
+00:00:48,870 --> 00:00:51,330
+طبعا هان بتحكم في عدد ال clusters اللي انا بدي
+
+14
+00:00:51,330 --> 00:00:55,310
+اياها كل clusterبساطة، اليوم ان شاء الله نتكلم عن
+
+15
+00:00:55,310 --> 00:00:59,990
+جزئية evaluation طبعاً لما نتكلم عن evaluation
+
+16
+00:00:59,990 --> 00:01:07,030
+كتقييم ال ..
+
+17
+00:01:07,030 --> 00:01:11,390
+نتكلم عن التقييم، هل التقييم وارد في ال
+
+18
+00:01:11,390 --> 00:01:16,990
+clustering؟ التقييم كتقييم في ال clustering إذا ال
+
+19
+00:01:16,990 --> 00:01:21,650
+data 6 بقى unlabeled ولا عمره بيكون صحلأن انا
+
+20
+00:01:21,650 --> 00:01:27,410
+فعليا لازم اتدخل ل human عفوا المقصود ان التقييم
+
+21
+00:01:27,410 --> 00:01:35,220
+مستحيل يكون صحيح او حاليا بدي اقول انه يكاد يكونمن
+
+22
+00:01:35,220 --> 00:01:40,060
+المستحيل تطبيق التقييم إلا من خلال expert قادر
+
+23
+00:01:40,060 --> 00:01:45,460
+فعليا على دراسة كل instance و فعليا أنها تنتمي ل
+
+24
+00:01:45,460 --> 00:01:49,620
+cluster أو متشابه مع العناصر اللي موجودة عندها لكن
+
+25
+00:01:49,620 --> 00:01:54,920
+إحنا هلأ لما نتكلم عن ال clusteringأنا لدي
+
+26
+00:01:54,920 --> 00:01:58,140
+algorithm و data set و طبقت على ال data set هل في
+
+27
+00:01:58,140 --> 00:02:01,520
+مجال أعمل evaluation لل algorithm أو للناتج اللي
+
+28
+00:02:01,520 --> 00:02:06,160
+موجود؟ أه في مجال لكن في حالة واحدة فقط إذا انا
+
+29
+00:02:06,160 --> 00:02:10,720
+اعتمدت ان في عندي labelled data set طب احنا قلنا
+
+30
+00:02:10,720 --> 00:02:15,020
+من البداية ان
+
+31
+00:02:15,020 --> 00:02:17,800
+ال cluster بتشتغل على ال test set يعني ال label مش
+
+32
+00:02:17,800 --> 00:02:22,580
+موجود صحيح الفكرة وين ان انا بدي افصل ال data set
+
+33
+00:02:22,580 --> 00:02:31,250
+تبعتيمجموعة الـ attributes لحال و ال target label
+
+34
+00:02:31,250 --> 00:02:40,670
+لحالي وبعد هيك اعمل لهادي clustering بدي اعمل هنا
+
+35
+00:02:40,670 --> 00:02:44,590
+clustering لل data set اللي موجودة عندي هنا وبناء
+
+36
+00:02:44,590 --> 00:02:48,270
+على ال clusters انا عارف ان كل instance بتتبع اي
+
+37
+00:02:48,270 --> 00:02:54,960
+label فبصير انا بقى اقارن ال labelاللي عندي مع ال
+
+38
+00:02:54,960 --> 00:02:57,100
+clusters اللي هو اللي عندي هان وبناءً عن هيكت بحصل
+
+39
+00:02:57,100 --> 00:03:02,660
+على تقييم وبالتالي لما احنا بنتكلم على ال ال ال ال
+
+40
+00:03:02,660 --> 00:03:03,400
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+41
+00:03:03,400 --> 00:03:04,060
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+42
+00:03:04,060 --> 00:03:05,500
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+43
+00:03:05,500 --> 00:03:06,460
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+44
+00:03:06,460 --> 00:03:06,460
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+45
+00:03:06,460 --> 00:03:07,520
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+46
+00:03:07,520 --> 00:03:07,520
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+47
+00:03:07,520 --> 00:03:07,520
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+48
+00:03:07,520 --> 00:03:07,520
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+49
+00:03:07,520 --> 00:03:07,520
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+50
+00:03:07,520 --> 00:03:07,620
+ال ال ال ال
+
+51
+00:03:22,210 --> 00:03:28,550
+لأن النتائج اللي موجودة عندي ماحدش بيقول عنها صح
+
+52
+00:03:28,550 --> 00:03:31,570
+أو خطأ يعني انا استخدمت two different algorithms
+
+53
+00:03:31,570 --> 00:03:36,930
+وقلتلهم والله جسمولي ال data set كpartitional ل
+
+54
+00:03:36,930 --> 00:03:46,770
+three clusters طلعولي three clustersمش ضروري مش
+
+55
+00:03:46,770 --> 00:03:50,350
+ضروري العناصر اللي في ال cluster الأول هي نفسها
+
+56
+00:03:50,350 --> 00:03:51,970
+اللي في العناصر ال cluster التاني ناتج ال
+
+57
+00:03:51,970 --> 00:04:00,600
+algorithm وبالتالي مقارنة ال output شبه مستحيلةإذا
+
+58
+00:04:00,600 --> 00:04:02,640
+كنت أقول أن الـ Algorithm أعطاني نفس النتيجة أو
+
+59
+00:04:02,640 --> 00:04:05,880
+نفس الـ الـ فايدة من التاني، فلا تتميز التاني عنه
+
+60
+00:04:05,880 --> 00:04:10,360
+تمام، إلا فعليًا لو الـ Data كانت فعليًا الـ Data
+
+61
+00:04:10,360 --> 00:04:13,960
+Discriminant الـ Instances ميالة لـ Different Tree
+
+62
+00:04:13,960 --> 00:04:18,180
+Classes وكل واحدة، كل Instance تنتمي ل Class، يعني
+
+63
+00:04:18,180 --> 00:04:22,100
+في عندي Discriminant Attribute وجادرياش توصفليهم
+
+64
+00:04:22,100 --> 00:04:25,100
+أو توديليهم على الـ Certain Class أو الـ Target
+
+65
+00:04:25,100 --> 00:04:30,020
+Cluster عفواً بشكل كويس، لكن لما أنا فعليًابطبق
+
+66
+00:04:30,020 --> 00:04:34,000
+ممكن باعتمادي على ال training set ال training set
+
+67
+00:04:34,000 --> 00:04:39,000
+إذا أنا طبقت ال cluster algorithm على ال training
+
+68
+00:04:39,000 --> 00:04:43,020
+set تلاحظين معايا يا جماعة الخير؟ لما أنا بدي أعمل
+
+69
+00:04:43,020 --> 00:04:45,720
+evaluation .. الآن فعليا .. فعليا ليه clustering
+
+70
+00:04:45,720 --> 00:04:49,580
+unsupervised learning؟ يعني أنا بتجاهل ال label أو
+
+71
+00:04:49,580 --> 00:04:53,560
+ال label مش موجود في ال data set هذه واحدة لما أنا
+
+72
+00:04:53,560 --> 00:04:59,370
+بدي أعمله evaluation لل algorithm تمام؟بقدر اعمل
+
+73
+00:04:59,370 --> 00:05:03,170
+evaluation في حالة واحدة فقط اذا انا قدرت اطبقه
+
+74
+00:05:03,170 --> 00:05:06,410
+على training set شو training set يعني في عندي
+
+75
+00:05:06,410 --> 00:05:09,930
+label طب هل الكلام هذا موجود؟ اه موجود بصير كل
+
+76
+00:05:09,930 --> 00:05:15,670
+label كل class بمثابة cluster كل class بمثابة
+
+77
+00:05:15,670 --> 00:05:21,910
+cluster و بروح باخف ال class و بجسم ال data set
+
+78
+00:05:21,910 --> 00:05:24,210
+بدون ال cluster زي ما واجهتكوا في ال slide السابقة
+
+79
+00:05:24,210 --> 00:05:30,020
+زي ما رسلناها يعني انا الآنهي ال data set تبعي
+
+80
+00:05:30,020 --> 00:05:37,920
+كمان مرة فصلت ال cluster
+
+81
+00:05:37,920 --> 00:05:40,940
+أو فصلت ال data set ال attribute وال label أو ال
+
+82
+00:05:40,940 --> 00:05:46,720
+class جسم
+
+83
+00:05:46,720 --> 00:05:49,200
+ال data set صار عندى الآن هي ال label وهي ال
+
+84
+00:05:49,200 --> 00:05:55,150
+attribute الآن باجب اطبق ال clustering handطبق الـ
+
+85
+00:05:55,150 --> 00:05:57,170
+Clustering على الـ Attributes اللي موجودة عندها
+
+86
+00:05:57,170 --> 00:06:02,830
+على الـ Instances اللي موجودة تمام، الآن فعلياً كل
+
+87
+00:06:02,830 --> 00:06:07,870
+Instance بتبقى Class وفي عندى مجموعة Instances في
+
+88
+00:06:07,870 --> 00:06:10,470
+نفس ال class بين جسين أنه فعلياً ال data already
+
+89
+00:06:10,470 --> 00:06:15,590
+منجسمة فإذا أنا قدرت أربط ما بين ال true cluster
+
+90
+00:06:15,590 --> 00:06:21,890
+اللي هي ال label و ال predicted cluster اللي موجود
+
+91
+00:06:21,890 --> 00:06:26,610
+عندهابقدر أنشئ شغل اسمها الـ Contingency Matrix
+
+92
+00:06:26,610 --> 00:06:29,930
+ومن الـ Contingency Matrix ممكن أن اتكلم على شغل
+
+93
+00:06:29,930 --> 00:06:36,160
+اول metric هسميها الـ Durityتعالى نتكلم عن الـ
+
+94
+00:06:36,160 --> 00:06:38,920
+Contingency Matrix ايش الـ Contingency Matrix
+
+95
+00:06:38,920 --> 00:06:43,720
+بتقول ان لدي ثلاثة .. طبعا لاحظوا يا جماعة الخير
+
+96
+00:06:43,720 --> 00:06:47,960
+في موقزي انا بدي اختبر Clustering Algorithm في
+
+97
+00:06:47,960 --> 00:06:51,980
+عندي label data set ال label data set فيها عدد
+
+98
+00:06:51,980 --> 00:06:55,800
+classes معين N لما بدي استخدم ال Clustering
+
+99
+00:06:55,800 --> 00:06:59,020
+Algorithm بدي اقول جسمليها لـ N من ال cluster لأن
+
+100
+00:06:59,020 --> 00:07:02,800
+كل cluster بدي ميثل Classفأنا بفترض أنه عندي data
+
+101
+00:07:02,800 --> 00:07:07,680
+set مكوّنة من three classes label data set مكوّنة
+
+102
+00:07:07,680 --> 00:07:13,080
+من three classes بتسميهم T1 وT2 وT3 من true true
+
+103
+00:07:13,080 --> 00:07:18,520
+cluster أو true segment أو true partition سميها زي
+
+104
+00:07:18,520 --> 00:07:24,380
+ما بدك true label سميها زي ما بدكواوC1 وC2 وC3 هما
+
+105
+00:07:24,380 --> 00:07:28,060
+الـ clusters اللي انشغلياهم من ال algorithm اللي
+
+106
+00:07:28,060 --> 00:07:31,580
+موجود عندها ايش راح اجلب؟ ايش بفهم ال contingency
+
+107
+00:07:31,580 --> 00:07:41,000
+matrix؟ انه في C1 C1 خمسة وعشرين element بينتمي ل
+
+108
+00:07:41,000 --> 00:07:45,020
+T2 وخمسة
+
+109
+00:07:45,020 --> 00:07:50,410
+element بينتمي ل T3 وخمس عناصر بينتمي ل T3يعني
+
+110
+00:07:50,410 --> 00:07:56,730
+عندي 25 عنصر من T ناتج
+
+111
+00:07:56,730 --> 00:08:06,470
+ال clustering C1 بيحتوي على 30 عنصر 25 منهم حقيقة
+
+112
+00:08:06,470 --> 00:08:12,550
+من ال class التاني و 5 من ال class التالت و لا
+
+113
+00:08:12,550 --> 00:08:18,880
+واحد من ال class الأولT2 أو cluster C2 بيحتوي على
+
+114
+00:08:18,880 --> 00:08:25,100
+35 عنصر 15 من ال class الأول و 20 من ال class
+
+115
+00:08:25,100 --> 00:08:32,220
+التالت cluster تلاتة بيحتوي على عشر عناصر فقط كلهم
+
+116
+00:08:32,220 --> 00:08:40,100
+كلهم بيتبعوا T1 الآن هذا الكلام إذا انا افهمته
+
+117
+00:08:41,270 --> 00:08:45,670
+معناته أنا مش ضروري الـ Clustering algorithm تبعي
+
+118
+00:08:45,670 --> 00:08:49,250
+يكون صح مائة في المائة ممتاز طب متى بيكون صح مائة
+
+119
+00:08:49,250 --> 00:08:57,710
+في المائة إذا والله أنا إجيت قولت هيك مثلًا
+
+120
+00:08:57,710 --> 00:09:00,830
+حصرت على صورة واحدة من الصور التالية فانا هتكلم عن
+
+121
+00:09:00,830 --> 00:09:08,150
+ال matrix لو أنا إجيت قولت هنا والله عندي
+
+122
+00:09:08,150 --> 00:09:08,990
+هنا تلاتين
+
+123
+00:09:12,600 --> 00:09:24,500
+وعندي هنا 20 وعندي هنا 50 وانا
+
+124
+00:09:24,500 --> 00:09:28,740
+C1 C2
+
+125
+00:09:28,740 --> 00:09:39,400
+وC3 والباقي أصفر طبعا هنا T1 T2 T3 وانا اتعمدت احط
+
+126
+00:09:39,400 --> 00:09:45,560
+القيم نفس الكيفيةلحظوا معايا إنه فعليا كل cluster
+
+127
+00:09:45,560 --> 00:09:50,720
+completely pure صافي مافيش فيه أي .. يعني كل
+
+128
+00:09:50,720 --> 00:09:53,800
+cluster مثل واحدة من ال classes اللي موجودة عندى
+
+129
+00:09:53,800 --> 00:09:57,980
+كل cluster مثل واحدة فقط من ال classes اللي موجودة
+
+130
+00:09:57,980 --> 00:10:01,920
+عندى وهنا بتكلم إنه فعليا كل cluster نقي تماما
+
+131
+00:10:01,920 --> 00:10:06,740
+بيحتوي عناصر من نفس ال class فقط عشان هي كان
+
+132
+00:10:06,740 --> 00:10:10,900
+بنتكلم احنا على ال purity نقاوة أو نقاء درجة
+
+133
+00:10:10,900 --> 00:10:17,700
+النقاءطيب، بما أن الحالة دي هي الـ optimal case أو
+
+134
+00:10:17,700 --> 00:10:21,640
+الـ ideal case واللي أنا فعلا مش هحصل عليها، أنا
+
+135
+00:10:21,640 --> 00:10:24,400
+هحصل على شغل مشابه زي هيك من خلال الـ contingency
+
+136
+00:10:24,400 --> 00:10:28,020
+matrix كيف أحسب الـ purity؟ الـ purity هي تساوي
+
+137
+00:10:28,020 --> 00:10:35,180
+عبارة عن مجموع ال maximum في كل صفر ال maximum عدد
+
+138
+00:10:35,180 --> 00:10:40,410
+maximum للـ Ti تنتمي لCعلى الان ال maximum خمسة و
+
+139
+00:10:40,410 --> 00:10:44,750
+عشرين ال maximum عشرين ال maximum عشرة يعني خمسة و
+
+140
+00:10:44,750 --> 00:10:49,430
+عشرين زائد عشرين زائد عشرةعندما اتكلم عن خمسة و
+
+141
+00:10:49,430 --> 00:10:53,550
+خمسين على كل الان خمسة و خمسين و في عندى اضيفهم
+
+142
+00:10:53,550 --> 00:10:58,670
+هنا على خمسة و سبعين بتكلم على ال purity الان ان
+
+143
+00:10:58,670 --> 00:11:04,870
+عندي هان تلاتين خمسة و تلاتين هي خمسة و ستين خمسة
+
+144
+00:11:04,870 --> 00:11:10,750
+و سبعين معناته عندى انا هان خمسةاللي عندي هنا
+
+145
+00:11:10,750 --> 00:11:13,830
+نتكلم .. احنا قولنا ال maximum خمسة و أربعين ..
+
+146
+00:11:13,830 --> 00:11:21,510
+خمسة و خمسين .. خمسة و خمسين على خمسة و سبعين هذه
+
+147
+00:11:21,510 --> 00:11:23,970
+ال purity تبع ال cluster أو تبع ال contingency
+
+148
+00:11:23,970 --> 00:11:29,990
+matrix اللي موجودة عندي
+
+149
+00:11:29,990 --> 00:11:34,250
+طيب .. تعالى نشوف المثال البسيط اللي عندي هاد
+
+150
+00:11:41,930 --> 00:11:45,370
+أنا مش بقول، بقول إن أنا الـPurity بقدر أحسبها إذا
+
+151
+00:11:45,370 --> 00:11:50,690
+كانت بتعامل مع test set بتحتوي على target class
+
+152
+00:11:50,690 --> 00:11:56,970
+تخيل، عشان يدمج التعريف هذا الـdefinition هذا عشان
+
+153
+00:11:56,970 --> 00:12:00,610
+يدمج ما بين الشغلتين بين إنه فعليا الـclustering
+
+154
+00:12:00,610 --> 00:12:05,230
+تطبق على test set وأنا مقدرش أروح أقدر أعمل
+
+155
+00:12:05,230 --> 00:12:09,980
+evaluation إلا غير لو كان ال label موجودفجالي ال
+
+156
+00:12:09,980 --> 00:12:12,960
+test set بتحتوي على target التي بنجوزني training
+
+157
+00:12:12,960 --> 00:12:20,520
+set و لا شو رأيكوا training
+
+158
+00:12:20,520 --> 00:12:25,220
+set بيبقى الان بقول افترض ان انا في عندى test set
+
+159
+00:12:25,220 --> 00:12:29,900
+مكونة من 24 element بتنتمي ل three different
+
+160
+00:12:29,900 --> 00:12:39,530
+classes ال O او ال circleTriangle وSquare ومجسم
+
+161
+00:12:39,530 --> 00:12:45,490
+العناصر بالتساوي 8888 بعد ما طبقت ال clustering
+
+162
+00:12:45,490 --> 00:12:50,510
+تبعت ال cluster C1 فيها العناصر التالية ال cluster
+
+163
+00:12:50,510 --> 00:12:55,650
+C2 و ال cluster C3 طبعا هنا في مصطلح جديد اضيفه
+
+164
+00:12:55,650 --> 00:13:01,630
+نقاء كل cluster نقاء كل cluster بشكل مستقل اذا
+
+165
+00:13:01,630 --> 00:13:07,380
+سألتك ال cluster الأول بمثل ايش؟معظمكم حيقولوا و
+
+166
+00:13:07,380 --> 00:13:12,880
+الله هذا بيمثل المثلثات ال triangles و اللي تحت
+
+167
+00:13:12,880 --> 00:13:16,480
+التاني هيمثل المربعات الحمراء و هذه هيمثل الدوائر
+
+168
+00:13:16,480 --> 00:13:19,340
+الخضراء، مظبوط؟ فبالتالي أنا بقدر أحسب ال purity
+
+169
+00:13:19,340 --> 00:13:22,300
+تبع كل cluster ال cluster الأول بيحتوي على 9 عناصر
+
+170
+00:13:22,300 --> 00:13:26,420
+و ال maximum كانت لمين؟ للمثلثات، معناته 6 على 9
+
+171
+00:13:26,420 --> 00:13:29,880
+لكن مش هي ال target تبعتي، أنا مابهمنيش ال purity
+
+172
+00:13:29,880 --> 00:13:34,820
+تبع كل class أنا اللي بيهمني ال purity لكل output
+
+173
+00:13:34,820 --> 00:13:40,340
+مرة واحدةللـ algorithm ال element 24 element هروح
+
+174
+00:13:40,340 --> 00:13:44,920
+أدور هانالـ maximum هنا 6 الـ maximum هنا 5 الـ
+
+175
+00:13:44,920 --> 00:13:49,980
+maximum هنا 5 6 زائد 5 زايد 5 على 24 16 على 24
+
+176
+00:13:49,980 --> 00:13:53,660
+درجة النقاء اللي بيعطينا إياها ال cluster هذا بشكل
+
+177
+00:13:53,660 --> 00:14:00,460
+عام 76.67% و هيك بتتم حسبة ال purity تبعتنا هنا
+
+178
+00:14:00,460 --> 00:14:04,220
+طبعا كمان مرة برجع بقول أنا بقدر أتكلم بشكل مبدئي
+
+179
+00:14:04,220 --> 00:14:09,910
+ال majority تبع كل cluster كذاغالبية تبعت كل
+
+180
+00:14:09,910 --> 00:14:13,370
+cluster كده لكن ال purity تبعتها هتكون هذه مش
+
+181
+00:14:13,370 --> 00:14:17,330
+واضحة فعليا لو قلع عندي cluster مادة نسوشي و
+
+182
+00:14:17,330 --> 00:14:22,150
+بينتمي مثلا فقط ل two clusters ل two classes يعني
+
+183
+00:14:22,150 --> 00:14:25,770
+من نوعين مختلفين هقول ال purity لمين فبتصير ال
+
+184
+00:14:25,770 --> 00:14:29,990
+purity هذه غير واضحة أو بتصير مفهومها غير دقيق أنا
+
+185
+00:14:29,990 --> 00:14:34,770
+اللي بهمني ال purity تبعت ال cluster بشكل عامطبعاً
+
+186
+00:14:34,770 --> 00:14:38,790
+أنا فيه متريكز تانية ممكن تستخدم نفس المبدأ الـ
+
+187
+00:14:38,790 --> 00:14:41,230
+Ground Truth إن أنا فعلياً لازم يكون فيه training
+
+188
+00:14:41,230 --> 00:14:44,710
+data set وهذا مفهوم Ground Truth يعني الحقيقة
+
+189
+00:14:44,710 --> 00:14:47,690
+الأمر الواقع، إيش الأمر الواقع؟ الأمر الواقع ال
+
+190
+00:14:47,690 --> 00:14:51,510
+class اللي موجود عندها، اللي هي الأساس، تمام؟ وهذا
+
+191
+00:14:51,510 --> 00:14:57,250
+فعلياً أنا لما بطبق ال data setأو Clustering على
+
+192
+00:14:57,250 --> 00:14:59,690
+الـ Training Set اللي موجودة هنا في عندي الـ
+
+193
+00:14:59,690 --> 00:15:04,710
+Adjusted Random Index وفي عندي Normalized Mutual
+
+194
+00:15:04,710 --> 00:15:09,450
+Information وهذه بتديني قيم من صفر لواحد وكل ما
+
+195
+00:15:09,450 --> 00:15:15,390
+كانت القيمةأقرب للواحد معينته الـ purity تبعتي أو
+
+196
+00:15:15,390 --> 00:15:19,830
+الـ scale تبعي ال algorithm تبعتي أفضل الصحيح أنا
+
+197
+00:15:19,830 --> 00:15:25,010
+مش هاطلب منكوا العمليات الحسابية اللي موجودة عند
+
+198
+00:15:25,010 --> 00:15:28,810
+هان نفس الكلام هي في عند contingency matrix عند ال
+
+199
+00:15:28,810 --> 00:15:30,890
+actual class
+
+200
+00:15:32,410 --> 00:15:38,490
+عن طريق الـ Predicted Cluster في نفس الحسبة لكن
+
+201
+00:15:38,490 --> 00:15:43,770
+هنا بتكلم عن جداش الـ elements من كل عنصر تماما
+
+202
+00:15:43,770 --> 00:15:47,710
+الحسبة مش مطلوبة يا جماعة الخير لكن هوريكم إياها
+
+203
+00:15:47,710 --> 00:15:51,830
+إن شاء الله في العمل وبهيك نهينا شبترنا يعني أنا
+
+204
+00:15:51,830 --> 00:15:55,630
+الآن لما أتكلم على ال evaluation ممكن أتكلم على
+
+205
+00:15:55,630 --> 00:15:59,590
+three different metrics3 مترات مختلفة لـ Purity
+
+206
+00:15:59,590 --> 00:16:03,710
+وهي مطموعة منكوا حسابيتها لأنها سهلة ال maximum ال
+
+207
+00:16:03,710 --> 00:16:06,390
+summation للماكسيممم في كل cluster على عدد ال
+
+208
+00:16:06,390 --> 00:16:09,130
+elements كلها في ال data set وهي بتمثل ال purity
+
+209
+00:16:09,130 --> 00:16:14,890
+في عندي مجرد مصطلحين أخرين أخرين بدي أسمعهم بدي
+
+210
+00:16:14,890 --> 00:16:19,810
+أحرفهم اللي هو adjusted rank index وnormalize
+
+211
+00:16:19,810 --> 00:16:25,010
+mutual information هي عبارة عن rank بحسب ال
+
+212
+00:16:25,010 --> 00:16:30,060
+similarity between any two clustersحسبة مش مطلوبة
+
+213
+00:16:30,060 --> 00:16:33,520
+لكن فعلياً هي عبارة عن evaluation metric انا ممكن
+
+214
+00:16:33,520 --> 00:16:36,580
+او جد استخدمها مع ال clustering اللي يعطيكوا
+
+215
+00:16:36,580 --> 00:16:39,320
+العافية و بتمنالكوا التوفيق السلام عليكم ورحمة
+
+216
+00:16:39,320 --> 00:16:39,440
+الله
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/S8_leI0rRZ0_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/S8_leI0rRZ0_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..ebcfb669482e8b396d39574effc9dd605d207e2d
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/S8_leI0rRZ0_raw.srt
@@ -0,0 +1,1080 @@
+1
+00:00:00,000 --> 00:00:02,940
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:02,940 --> 00:00:07,260
+أهلا وسهلا فيكم بالمحاضرة الثانية في ال regression
+
+3
+00:00:07,260 --> 00:00:12,580
+وهنا هنتكلم عن ال multiple regression كنا في
+
+4
+00:00:12,580 --> 00:00:16,400
+المحاضرة الماضية اتكلمنا عن ال simple linear
+
+5
+00:00:16,400 --> 00:00:19,440
+regression وقلنا simple linear regression معناته
+
+6
+00:00:19,440 --> 00:00:23,960
+انا عندي معادلة خط مستقيم واحد فقط اللي هي Y عفوا
+
+7
+00:00:23,960 --> 00:00:25,400
+خليني ادهر ال pointer
+
+8
+00:00:37,800 --> 00:00:44,480
+قلنا في معادلة الخط المستقيم أن الـ Y تساوي الـ M
+
+9
+00:00:44,480 --> 00:00:59,140
+X زائد الـ B وقلنا أن الـ M عندها تساوي
+
+10
+00:00:59,140 --> 00:01:14,070
+مجميع X I ناقص وتوسط Xمضروبة في Y I ناقص متوسط الـ
+
+11
+00:01:14,070 --> 00:01:19,330
+Y على مجموع
+
+12
+00:01:19,330 --> 00:01:30,310
+X I ناقص متوسط الـ X كل تربيع والـ B
+
+13
+00:01:33,710 --> 00:01:39,590
+متوسط Y ناقص M
+
+14
+00:01:42,630 --> 00:01:47,090
+الـ X فشوفنا مع بعض كيف احنا وصلنا للمعادلة او
+
+15
+00:01:47,090 --> 00:01:49,950
+اشتغلنا مع بعض وشوفنا ال simple linear regression
+
+16
+00:01:49,950 --> 00:01:52,590
+اليوم ان شاء الله تعالى هنتكلم على ال multiple زي
+
+17
+00:01:52,590 --> 00:01:55,470
+ما وعدناكم هنتكلم على ال multiple regression وما
+
+18
+00:01:55,470 --> 00:01:58,210
+زلت بتكلم على ال simple linear regression ال
+
+19
+00:01:58,210 --> 00:02:01,450
+regression لكنه بتكلم على المultiple الان لما انا
+
+20
+00:02:01,450 --> 00:02:03,510
+بتكلم على ال multiple regression معناته انا بدى
+
+21
+00:02:03,510 --> 00:02:07,270
+اتنبأ بالعلاقة زي ما قلنا سابقا بين ال multiple
+
+22
+00:02:07,270 --> 00:02:11,010
+attributes او multiple variables في عندي more than
+
+23
+00:02:12,010 --> 00:02:14,770
+one independent attribute وقلنا من الأمثلة
+
+24
+00:02:14,770 --> 00:02:19,510
+الموجودة عليها ال income و ال education أو تأثير
+
+25
+00:02:19,510 --> 00:02:22,830
+ال income و ال education و ال living area على
+
+26
+00:02:22,830 --> 00:02:26,730
+تأثير
+
+27
+00:02:26,730 --> 00:02:31,610
+قيمة الدخل و التعليم على المنطقة اللي يعيش فيها
+
+28
+00:02:31,610 --> 00:02:35,290
+الشخص اللي موجود عندها طبعا لما بتكلم على زيادة
+
+29
+00:02:35,290 --> 00:02:38,410
+عدد ال variables أو عدد ال independent variables
+
+30
+00:02:39,300 --> 00:02:43,460
+معناته أنا بزيد من تعقيد عملية ال prediction لأنه
+
+31
+00:02:43,460 --> 00:02:47,460
+انا فعليا بدي اتكلم على .. بدي اوجد علاقة ما بين
+
+32
+00:02:47,460 --> 00:02:50,660
+كل ال attributes هذه مجتمعها طبعا يا جماعة الخير
+
+33
+00:02:50,660 --> 00:02:55,220
+عشان بس قبل ما انا اتكلم شغلة ليش احنا بالتحديد
+
+34
+00:02:55,220 --> 00:03:00,660
+قولنا linear regression معادلة خطية لأنه الرتبة
+
+35
+00:03:00,660 --> 00:03:05,360
+تبعتها هي لاحظوا يا جماعة الخير انا بتكلم
+
+36
+00:03:08,290 --> 00:03:11,430
+لما كنت بتكلم على الـ simple regression عفوا بالـ
+
+37
+00:03:11,430 --> 00:03:15,170
+simple regression عندي x و y ففي الآخر المعادلة
+
+38
+00:03:15,170 --> 00:03:19,930
+تبعت سواء كانت خط مستقيم أو polynomial بغض النظر
+
+39
+00:03:19,930 --> 00:03:26,930
+عن طبيعتها أنا في الآخر بتكلم في العلاقة في الـ 2D
+
+40
+00:03:26,930 --> 00:03:31,230
+ليش؟ لأن في عندي two attributes تمام طب لو كانوا
+
+41
+00:03:31,230 --> 00:03:33,650
+في عندي three attributes two independent و one
+
+42
+00:03:33,650 --> 00:03:37,550
+dependent معناته بتكلم على 3D طب لو كانوا four
+
+43
+00:03:38,380 --> 00:03:43,020
+طبعا، لاحظوا معايا في الـ linear .. linear هنصف
+
+44
+00:03:43,020 --> 00:03:49,460
+بقول خط طيب، هل ممكن يكون في عندي linear multiple
+
+45
+00:03:49,460 --> 00:03:53,260
+attributes؟ أه ممكن طبعا، تعالي خلينا نتخيل
+
+46
+00:03:53,260 --> 00:03:55,920
+المعادلة تبعتي بالشكل هذا ال multiple regression
+
+47
+00:03:55,920 --> 00:03:58,340
+لما يكون في عندك K independent attributes، هيوم
+
+48
+00:03:58,340 --> 00:04:02,660
+إيش هكونها؟ طبعا، بتكلم عن linear regression لأن
+
+49
+00:04:02,660 --> 00:04:06,560
+أعلى قيمة أو أعلى أصلة X بتكون واحد، هاي المفهوم
+
+50
+00:04:06,560 --> 00:04:13,730
+ال linearالان الـ predicted y بيتساوي ال intercept
+
+51
+00:04:13,730 --> 00:04:22,970
+B0 زائد ال mail M1 في X1 زائد M2 في X2 زائد زائد
+
+52
+00:04:22,970 --> 00:04:29,010
+Mk أو Bk في Xk ولمّا أنا بدي أجي أرسم معادلة بشكل
+
+53
+00:04:29,010 --> 00:04:32,290
+هذا أبسط المعادلات اللي ممكن أستوعبها أنا في الرسم
+
+54
+00:04:32,290 --> 00:04:35,950
+بعد هيكلما يكون لدي two independent variables ها
+
+55
+00:04:35,950 --> 00:04:41,050
+هي X1 و X2 two independent variables مع ال
+
+56
+00:04:41,050 --> 00:04:45,050
+dependent variables صاروا three attributes عشان
+
+57
+00:04:45,050 --> 00:04:48,830
+اقدر امثلهم انا او اتخيلهم صح بدي اتخيل ال 3D
+
+58
+00:04:48,830 --> 00:04:52,670
+space ممتاز طيب المعادلة الخطية في ال 3D space
+
+59
+00:04:52,670 --> 00:04:57,050
+معناته هي بتتكلم على surface سطح والسطح هذا
+
+60
+00:04:57,050 --> 00:05:03,840
+الومنين ميل هيكونمع الـ X و ميلم بيكون مع الـ X
+
+61
+00:05:03,840 --> 00:05:06,000
+التاني أو المحور التاني بما أن أنا في عيني الـ 2X
+
+62
+00:05:06,000 --> 00:05:09,680
+X1 و X2 و الـ Y ثابتة لأن الـ Y هي الـ predicted
+
+63
+00:05:09,680 --> 00:05:13,860
+value و أنا في عندي X1 و X2 بما أن في عندي ميلم مع
+
+64
+00:05:13,860 --> 00:05:20,400
+X1 و X2 وبناءً عليه أنا بتتكلم على معادلة خطية
+
+65
+00:05:20,400 --> 00:05:26,260
+لكنها في الـ 3D تمام، الآن لو أنا أفضل أو أعمل
+
+66
+00:05:26,260 --> 00:05:31,140
+predictionبالـ python بتمنى هذه الجزئية تكون سهلة
+
+67
+00:05:31,140 --> 00:05:34,320
+يعني مافيش فيها كلام انت بدك تستوعب طب لو كان في
+
+68
+00:05:34,320 --> 00:05:36,440
+عندي انا four attribute three independent
+
+69
+00:05:36,440 --> 00:05:40,180
+attribute جماعة الخير three independent attribute
+
+70
+00:05:40,180 --> 00:05:44,540
+و one independent attribute يعني صاروا اربعة ايش
+
+71
+00:05:44,540 --> 00:05:48,200
+الشكل تبعي اللي احب اتخيله في ال space في ال 4D
+
+72
+00:05:48,200 --> 00:05:51,900
+بسيط بتكلم على space مكعب ممكن تكون هذا ال space
+
+73
+00:05:51,900 --> 00:05:57,480
+cubeالمفروض عندما أزيد عدد الـ Attributes سأزيد
+
+74
+00:05:57,480 --> 00:06:01,880
+مخيلتي لكي أتكلم عليها لكن بفضل الله تبارك وتعالى
+
+75
+00:06:01,880 --> 00:06:06,220
+نحن بعد الـ 3D بنبطل نستوعب أيش اللي ممكن أصير
+
+76
+00:06:06,220 --> 00:06:09,520
+الآن بتعالي نشوف بالـ Python بدي أشغل على نفس
+
+77
+00:06:09,520 --> 00:06:12,780
+الطريقة أو نفس الفكرة السابقة استخدمت الـ NumPy
+
+78
+00:06:12,780 --> 00:06:17,440
+وروح وقلت له أنا في عندي Array لكن كل رو في الـ
+
+79
+00:06:17,440 --> 00:06:21,840
+Array بيحتوي على two attributes أو two variables
+
+80
+00:06:23,550 --> 00:06:27,310
+خمسة و ثلاثة يعني ال attribute X1 خمسة في الصف
+
+81
+00:06:27,310 --> 00:06:33,670
+الأول X2 ثلاثة X1 سبعة X2 خمسة و هكذا و ال Y ده هي
+
+82
+00:06:33,670 --> 00:06:37,670
+ال value تبعتهم لاحظوا ماتغيرش معايا ولا حاجة انا
+
+83
+00:06:37,670 --> 00:06:43,670
+غير انه غيرت بس ال X ال attributes تبعتي صارت في
+
+84
+00:06:43,670 --> 00:06:47,770
+ال 2D dimension 2D array و لاحظوا ماكنت لشري shape
+
+85
+00:06:47,770 --> 00:06:53,060
+لأنه خلاص ليش لأن انا كنت بده حلقت في صفوففي صفوف
+
+86
+00:06:53,060 --> 00:06:56,380
+وانتهى الأمر هنا مافيش داعي ان اعمله Reshape الـ y
+
+87
+00:06:56,380 --> 00:07:02,340
+.unarray وهي ال target attribute تبعتي نفس الكلام
+
+88
+00:07:02,340 --> 00:07:06,020
+from ASCII learn.linear model import linear
+
+89
+00:07:06,020 --> 00:07:09,520
+regression بنيت الموديل وعملته له fit فهنا راح
+
+90
+00:07:09,520 --> 00:07:14,850
+تعرف او بنى الموديل وحدد ال interceptأحدد قيمة الـ
+
+91
+00:07:14,850 --> 00:07:18,810
+slope للـ attribute الأول والـ attribute التاني أو
+
+92
+00:07:18,810 --> 00:07:20,810
+الـ coefficient للـ attribute الأول والـ attribute
+
+93
+00:07:20,810 --> 00:07:24,230
+التاني لو أنا طبعت بنفس القالية السابقة قلت له ال
+
+94
+00:07:24,230 --> 00:07:28,390
+model.coefficient و ال model.intercept طبع ليهم،
+
+95
+00:07:28,390 --> 00:07:34,170
+لاحظوا أنه طبع ليها ال model.coefficient جاب ليهم
+
+96
+00:07:34,170 --> 00:07:38,430
+على إنهم مصفوفة لأ و فيها two variablesأو two
+
+97
+00:07:38,430 --> 00:07:42,930
+values ليش؟ لأن أنا فعليًا عندي two independent
+
+98
+00:07:42,930 --> 00:07:47,550
+attributes X1 و X2 فانا روحت بس جملتها أكتر و
+
+99
+00:07:47,550 --> 00:07:50,190
+فصلتهم و طبعتهم بالشكل هذا قلت له model
+
+100
+00:07:50,190 --> 00:07:55,410
+.coefficient 0 عشان أجيب القيمة الأولى ضربتها في
+
+101
+00:07:55,410 --> 00:07:59,670
+X1 as a text زائد عشان أطبع معادلة الخط ال .. أو
+
+102
+00:07:59,670 --> 00:08:05,630
+بلاش ال .. ال linear space اللي موجود عندي هذا
+
+103
+00:08:09,310 --> 00:08:12,310
+تمام وبالتالي ما اتغيرش عندى في الشغل ولا حاجة انه
+
+104
+00:08:12,310 --> 00:08:14,730
+غير انه data set طب لو انا بعد data set بعد شو بدأ
+
+105
+00:08:14,730 --> 00:08:18,250
+اساوي بدل ما كنت انا تصيت او اخدت عمود واحد الآن
+
+106
+00:08:18,250 --> 00:08:21,630
+بدأ اخد عمودين او تلاتة او اربع عشان ال linear
+
+107
+00:08:21,630 --> 00:08:25,290
+regression اللي مولود خلينا ننتقل لل nonlinear مش
+
+108
+00:08:25,290 --> 00:08:28,750
+ضايل كتير عندنا في ال slides nonlinear regression
+
+109
+00:08:28,750 --> 00:08:33,770
+nonlinear معناته انا بتكلم على nonlinear line انا
+
+110
+00:08:33,770 --> 00:08:38,460
+في عندي خط لكن الخط هذا غير مستقيمأو ممكن يكون في
+
+111
+00:08:38,460 --> 00:08:41,880
+عندي surface ال surface هذا ممكن يكون على شكل
+
+112
+00:08:41,880 --> 00:08:45,780
+دائرة
+
+113
+00:08:45,780 --> 00:08:52,280
+مائلة أو slow أو ellipse بالشكل هذا فانا الآن بقلت
+
+114
+00:08:52,280 --> 00:09:00,700
+تتكلم على خط مستقيم الآن لما ال data مابتظهرش عندي
+
+115
+00:09:00,700 --> 00:09:01,980
+linear dependency
+
+116
+00:09:08,540 --> 00:09:12,100
+معناته انا ممكن ادور على accurate او احصل على
+
+117
+00:09:12,100 --> 00:09:14,460
+accurate model لو في حالة ان كان في عندي non
+
+118
+00:09:14,460 --> 00:09:16,700
+linear regression يعني بين قرصين الجامعة التخيار
+
+119
+00:09:16,700 --> 00:09:21,120
+انا ممكن اجرب و اجرب ال linear و اجرب ال non
+
+120
+00:09:21,120 --> 00:09:24,660
+linear و اشوف ايش المعادلة الأفضل example لو انا
+
+121
+00:09:24,660 --> 00:09:29,940
+قلتلك هى في عندى y تساوي w0 ال intercept لو انا
+
+122
+00:09:29,940 --> 00:09:33,820
+بدى اتكلم على معادل خط اللى هى نقطة التقاطع مع ال
+
+123
+00:09:33,820 --> 00:09:40,050
+yيوجد الـ Y و الـ W الـ coefficient تبع المتغير
+
+124
+00:09:40,050 --> 00:09:46,310
+الأول العلاقة الخطية الـ Y و W الـ W الـ Y و W الـ
+
+125
+00:09:46,310 --> 00:09:49,350
+W الـ Y و W الـ W الـ Y و W الـ Y و W الـ Y و W
+
+126
+00:09:49,350 --> 00:09:49,630
+الـ Y و W الـ Y و W الـ Y و W الـ Y و W الـ Y و W
+
+127
+00:09:49,630 --> 00:09:49,630
+الـ Y و W الـ Y و W الـ Y و W الـ Y و W الـ Y و W
+
+128
+00:09:49,630 --> 00:09:50,770
+الـ Y و W الـ Y و W الـ Y و W الـ Y و W الـ Y و W
+
+129
+00:09:50,770 --> 00:09:50,770
+الـ Y و W الـ Y و W الـ Y و W الـ Y و W الـ Y و W
+
+130
+00:09:50,770 --> 00:09:50,770
+الـ Y و W الـ Y و W الـ Y و W الـ Y و W الـ Y و W
+
+131
+00:09:50,770 --> 00:09:56,070
+الـ Y و W الـ Y و W الـ Y و W الـ Y و W الـ Y و W
+
+132
+00:09:56,070 --> 00:10:02,610
+الـ Y و W الـالـ equation تبعتي بتاخد different
+
+133
+00:10:02,610 --> 00:10:06,910
+forms أشكال مختلفة زي ما شوفنا في ملف ال Excel و
+
+134
+00:10:06,910 --> 00:10:11,670
+هنرجع لها على السريع في ملف ال Excel لما قلت له ال
+
+135
+00:10:11,670 --> 00:10:15,970
+line trend أو ال trend line كان فيه عنده
+
+136
+00:10:15,970 --> 00:10:18,450
+exponential عنده linear عنده logarithmic عنده
+
+137
+00:10:18,450 --> 00:10:22,330
+polynomial عنده power إلى آخره الآن أنا فيه عنده
+
+138
+00:10:22,330 --> 00:10:29,910
+ال exponential والعلاقة ما بين ال y و ال xإن الـ X
+
+139
+00:10:29,910 --> 00:10:35,370
+موجودة كأُص للـ exponential value E أُص B ضرب X و
+
+140
+00:10:35,370 --> 00:10:38,510
+الـ B هي الـ intercept اللي احنا بتكلم عليها يعني
+
+141
+00:10:38,510 --> 00:10:45,430
+ال coefficient تبعت ال X ال power value برضه
+
+142
+00:10:45,430 --> 00:10:50,150
+أنا ما زلت بتتكلم هنا هذه
+
+143
+00:10:50,150 --> 00:10:53,830
+المعادلة اللي موجودة عندي هنا ال growth saturation
+
+144
+00:10:53,830 --> 00:10:58,970
+model تبعتيو في عندى ال polynomial اللى احنا
+
+145
+00:10:58,970 --> 00:11:05,790
+شوفناها قبل لحظات polynomial هذا الرسمة لو كان
+
+146
+00:11:05,790 --> 00:11:08,230
+عندى بيانات و روحت رسمتها و قلت لها ارسملي ال
+
+147
+00:11:08,230 --> 00:11:13,010
+trend اللى موجود ارسملي المعادلة اللى موجودة مش
+
+148
+00:11:13,010 --> 00:11:16,150
+هكون في عندي مشكلة لان هذه مستحيل انا الاقي خط
+
+149
+00:11:16,150 --> 00:11:25,530
+مستقيم ما بين النقطة هاي نقفون النقطة هاي و النقطة
+
+150
+00:11:25,530 --> 00:11:30,270
+هاي مباشرةلحظه ليش؟ لأن الخط المستقيم أبعد لكن لو
+
+151
+00:11:30,270 --> 00:11:32,710
+انت قلتله والله انا ممكن اتكلم عن خط مستقيم في
+
+152
+00:11:32,710 --> 00:11:37,310
+المنطقة high نسبة الخطأ أقل لكن في الأول مستحيل
+
+153
+00:11:37,310 --> 00:11:40,430
+يكون لكن واضح ان ال trend تبعها non-linear
+
+154
+00:11:42,880 --> 00:11:47,180
+يعني انا بدي اجرب و احاول للفهم لل data و علاقة ال
+
+155
+00:11:47,180 --> 00:11:50,420
+attributes اللي اشتغل عليها هو اللي بيحدد انا فعلا
+
+156
+00:11:50,420 --> 00:11:54,380
+هشغل على linear ولا على non-linear طيب في الموضوع
+
+157
+00:11:54,380 --> 00:11:56,900
+ال evaluation يا جماعة الخير في الموضوع ال
+
+158
+00:11:56,900 --> 00:12:02,000
+evaluation انا بدي في عندي prediction في عندي true
+
+159
+00:12:02,000 --> 00:12:07,980
+values هي لأن خليناأهم metric لقياس ال regression
+
+160
+00:12:07,980 --> 00:12:12,700
+هو الـ root mean square error والبعض يعتمد فقط على
+
+161
+00:12:12,700 --> 00:12:15,600
+الـ mean square error وليس فارق كتير لأنني أريد
+
+162
+00:12:15,600 --> 00:12:19,020
+فرق و أزيل الجذر بعد ذلك لكن الـ root mean square
+
+163
+00:12:19,020 --> 00:12:22,540
+error ماهو ال error اللي موجود عندي؟ ال error هي
+
+164
+00:12:22,540 --> 00:12:27,450
+عبارة عن ال actual valueنقص الـ Predicted Value
+
+165
+00:12:27,450 --> 00:12:30,610
+لان انا بتكلم على continuous بتكلم على continuous
+
+166
+00:12:30,610 --> 00:12:34,270
+value انا عمال ال prediction و ال actual value
+
+167
+00:12:34,270 --> 00:12:36,970
+لازم تكون continuous الفرق بينهم هو نسبة الخطأ
+
+168
+00:12:36,970 --> 00:12:40,070
+اللي موجود عندها لو بدي اجي للرسم يا جماعة الخير
+
+169
+00:12:40,070 --> 00:12:44,830
+هذه النقطة بتمثل ال actual point النقطة الحقيقية
+
+170
+00:12:44,830 --> 00:12:50,490
+مصبوط؟ طيب و ال predicted value تبعتها اللي هتكون
+
+171
+00:12:50,490 --> 00:12:55,890
+هنا اللي على الخطكذلك هنا، لاحظوا الـ distance
+
+172
+00:12:55,890 --> 00:12:59,870
+المسافة اللي هنا بحسب الـ Euclidean distance اللي
+
+173
+00:12:59,870 --> 00:13:03,490
+احنا شوفناها لـ predicted value ناقص ل true value
+
+174
+00:13:03,490 --> 00:13:10,210
+تربيه، بصبوط؟ هاي الـ Euclidean الآن لو انا روح
+
+175
+00:13:10,210 --> 00:13:16,150
+اتجمعت كل المسافات هايوجسمتها على عدد النقاط اللي
+
+176
+00:13:16,150 --> 00:13:21,190
+موجودة عندها أنا بكون حصلت على الـ main square
+
+177
+00:13:21,190 --> 00:13:25,390
+error الـ main square error rotated بحطهم تحت
+
+178
+00:13:25,390 --> 00:13:29,520
+الجذر اللي موجود عندهاطبعا الـ Residual المقصود
+
+179
+00:13:29,520 --> 00:13:32,600
+فيها المسافة أو الـ Error الموجود بين العناصر اللي
+
+180
+00:13:32,600 --> 00:13:36,340
+موجودة عندك يعني بكل بساطة باخد الفروقات ما بين
+
+181
+00:13:36,340 --> 00:13:40,460
+الـ Predicted Value و الـ Actual Value بربعهم بجمع
+
+182
+00:13:40,460 --> 00:13:43,820
+الفروقات هذه بعد مربعات الفروقات و بجسمها على عدد
+
+183
+00:13:43,820 --> 00:13:47,860
+ال test value أو ال test set اللي موجودة عندها
+
+184
+00:13:47,860 --> 00:13:53,890
+طبعا لما تكونالفرق بينهم Zero معناته أنا فعليًا
+
+185
+00:13:53,890 --> 00:13:57,770
+أوصلت Actually للقيمة الحقيقية اللي موجودة عندهان
+
+186
+00:13:57,770 --> 00:14:01,490
+طبعًا الآن في عندي ال observation القيمة الحقيقية
+
+187
+00:14:01,490 --> 00:14:06,050
+طبعًا هو عمله بغير للرسم high كل ال X أو النقطة
+
+188
+00:14:06,050 --> 00:14:08,610
+السودة هي الحقيقية والخط اللي وقع الخط الأحمر
+
+189
+00:14:08,610 --> 00:14:10,950
+الكلام اللي أنا شرحته سابقًا هي فعليًا ال
+
+190
+00:14:10,950 --> 00:14:15,590
+predicted value اللي موجودة عندها وبالتالي مع كل
+
+191
+00:14:15,590 --> 00:14:18,870
+observation أنا فعليًا عندي ال Y الحقيقية ال
+
+192
+00:14:18,870 --> 00:14:23,780
+actual تساوي ال predictedزائد قيمة الخطأ اللي
+
+193
+00:14:23,780 --> 00:14:33,240
+موجود بينهم تمام okay معناته انا sum of error لو
+
+194
+00:14:33,240 --> 00:14:36,540
+انا بدى اجمع قيمة الخطأ فقط بجمعهم لكن احنا بنشتغل
+
+195
+00:14:36,540 --> 00:14:40,060
+على squared error تعالى نشوف ال implementation
+
+196
+00:14:40,060 --> 00:14:43,840
+ونشوف فعليا شغل مع data base موجودة في عندي data
+
+197
+00:14:43,840 --> 00:14:48,200
+base موجودة في ال .. ال .. الascular ال diabetes
+
+198
+00:14:48,200 --> 00:14:52,320
+اللي هي علاقة بمرض السكريfrom ascii learn import
+
+199
+00:14:52,320 --> 00:14:55,240
+dataset linear model اعملت import لهدول الشغلتين
+
+200
+00:14:55,240 --> 00:14:59,140
+مع بعض انا ال diabetes تساوي diabetes dot load
+
+201
+00:14:59,140 --> 00:15:02,420
+diabetes اعملت load لل dataset و اذا بقيت اطباعها
+
+202
+00:15:02,420 --> 00:15:06,920
+مش مشكلة روحت اعملت import لل non-bi طبعا انا كنت
+
+203
+00:15:06,920 --> 00:15:09,880
+بدي اعمل cut عشان اخد ال X لحالة و ممكن اخده طريقة
+
+204
+00:15:09,880 --> 00:15:14,300
+تانية بعيدا عن ال non-bi مش هستخدمها الآن X تساوي
+
+205
+00:15:14,300 --> 00:15:15,420
+ال diabetes dot
+
+206
+00:15:18,860 --> 00:15:24,920
+data 2.3 وكان شغالها على ال first attribute فقط اه
+
+207
+00:15:24,920 --> 00:15:28,120
+احنا بنشغل على ال linear نحصها على ال simple
+
+208
+00:15:28,120 --> 00:15:34,240
+linear فأخدت ال first attribute اللي هو ترقيه هيه
+
+209
+00:15:34,240 --> 00:15:38,020
+المحصور ما بين ال index 2 و index 3 خدت one
+
+210
+00:15:38,020 --> 00:15:43,250
+attribute فقطالان روحت في ال forum ال scale model
+
+211
+00:15:43,250 --> 00:15:47,910
+selection روحت ال data set عملت لها split صار في
+
+212
+00:15:47,910 --> 00:15:52,330
+عند X train او X test و Y train و Y test حسب ما
+
+213
+00:15:52,330 --> 00:15:55,390
+بنعرف و نسبة 30% لل test set ال data set اللي
+
+214
+00:15:55,390 --> 00:15:59,870
+موجود عندى يعني فيها حوالي 5000 record او اكتر
+
+215
+00:15:59,870 --> 00:16:05,040
+شوية modelلينيار موديل اللي انا عملته لها
+
+216
+00:16:05,040 --> 00:16:08,280
+important فوق لينيار regression اعمل fit حصلت على
+
+217
+00:16:08,280 --> 00:16:13,240
+ال coefficient اللي موجود عندهان روحت و قلت له ال
+
+218
+00:16:13,240 --> 00:16:16,860
+y predictه ساوي الموديل ده ت predict و زودته بال X
+
+219
+00:16:16,860 --> 00:16:21,920
+test اللي موجود عندهان قلت له هيه جيب لي ال label
+
+220
+00:16:21,920 --> 00:16:25,580
+هدول طبعا ال label ال predicted label ال actual
+
+221
+00:16:25,580 --> 00:16:30,140
+label هيه موجود عندهان تمام فانا روحت بعد هيه قلت
+
+222
+00:16:30,140 --> 00:16:35,830
+له اطبع لل interceptوالـ coefficient عشان اتأكد او
+
+223
+00:16:35,830 --> 00:16:41,950
+افحص المعادلة الخطية اللى موجودة عندى وفي الآخر
+
+224
+00:16:41,950 --> 00:16:46,790
+from asclean dot matrix import ال main square
+
+225
+00:16:46,790 --> 00:16:52,350
+error ال main square error او ال rooted main
+
+226
+00:16:52,350 --> 00:16:56,330
+squared error حسب احنا الآن هطبقها ال main square
+
+227
+00:16:56,330 --> 00:17:01,000
+errorاللي في ال slide السابق هنا أنا كنت بتكلم على
+
+228
+00:17:01,000 --> 00:17:05,080
+ال route route اللي هي الجدر الترديعي اللي موجود
+
+229
+00:17:05,080 --> 00:17:10,300
+عندي هنا فممكن انت تستدعي كذلك ال print ال mean
+
+230
+00:17:10,300 --> 00:17:14,440
+square error percent to F عشان بقى جيبلي ال two
+
+231
+00:17:14,440 --> 00:17:19,920
+digits بعد الفاصلة العشرية ال mean square error هي
+
+232
+00:17:19,920 --> 00:17:22,280
+الدالة اللي استدعيتها هنا او ال metric اللي
+
+233
+00:17:22,280 --> 00:17:28,150
+استدعيته وزودته بالy test و ال y predicted و
+
+234
+00:17:28,150 --> 00:17:33,310
+يدّيني ال value اللي موجودة عندنا وبهيك بنكون احنا
+
+235
+00:17:33,310 --> 00:17:40,430
+فعليا انتهينا من موضوع ال regression شبتر زريف و
+
+236
+00:17:40,430 --> 00:17:48,510
+خفيف نشتغل عليه بتمنى يكون .. بقدر توصل الفكرة
+
+237
+00:17:48,510 --> 00:17:53,690
+بشكل كويس بل في عندنا شغل اخرى اللي علاقة بال
+
+238
+00:17:53,690 --> 00:17:59,090
+assignmentلما أتكلم عن ال assignment أنا مش عارف
+
+239
+00:17:59,090 --> 00:18:03,730
+مش عامله hide اتكلم بال assignment انه جامعة الخير
+
+240
+00:18:03,730 --> 00:18:09,790
+لازم احنا نشتغل و نطبق مع بعض لازم لازم لازم الان
+
+241
+00:18:09,790 --> 00:18:16,270
+ايش مطلوب منك انت في عندك data set عندك data set و
+
+242
+00:18:16,270 --> 00:18:22,560
+ال data set تبعتك مخصصة لل regressionلينيار
+
+243
+00:18:22,560 --> 00:18:25,840
+ريجريشن او نون لينيار ريجريشن احنا لسه عما بتعرف
+
+244
+00:18:25,840 --> 00:18:29,800
+بدك تروح على ال data set اللى موجود عندكوا و تفحص
+
+245
+00:18:29,800 --> 00:18:37,060
+تتعرف على ال data set اللى بشكل كويس وبعد هيك تروح
+
+246
+00:18:37,060 --> 00:18:43,520
+تختار multiple multiple attribute
+
+247
+00:18:45,410 --> 00:18:53,590
+تعمل تعمل تعمل تعمل regression تعمل تعمل تعمل تعمل
+
+248
+00:18:53,590 --> 00:18:55,610
+تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل
+
+249
+00:18:55,610 --> 00:18:55,610
+تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل
+
+250
+00:18:55,610 --> 00:18:55,650
+تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل
+
+251
+00:18:55,650 --> 00:18:55,770
+تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل
+
+252
+00:18:55,770 --> 00:18:55,770
+تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل
+
+253
+00:18:55,770 --> 00:18:55,830
+تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل
+
+254
+00:18:55,830 --> 00:19:06,590
+تعمل تعمل تعمل تعمل تعمل تعمل
+
+255
+00:19:06,590 --> 00:19:09,450
+ت
+
+256
+00:19:09,890 --> 00:19:13,130
+تقارن بين كل الحالات اللي موجودة يعني بالتفصيل
+
+257
+00:19:13,130 --> 00:19:16,870
+بالآخر بالتفصيل بدك تروح تجرب linear regression
+
+258
+00:19:16,870 --> 00:19:19,050
+simple linear regression و multiple linear
+
+259
+00:19:19,050 --> 00:19:23,750
+regression ماشي الحال على one attribute وعلى two
+
+260
+00:19:23,750 --> 00:19:28,770
+attributes ال multiple اعتبرها two والsimple
+
+261
+00:19:28,770 --> 00:19:34,830
+الاعتبرها one لكن ال multiple تكون two attributes
+
+262
+00:19:34,830 --> 00:19:38,680
+at leastبتطبق عليها Linear وتطبق عليها Unlinear
+
+263
+00:19:38,680 --> 00:19:43,680
+طبعا المفروض هذا يتسلم يوم اتناش اتنين لكن بما ان
+
+264
+00:19:43,680 --> 00:19:48,700
+التواريخ كلها تشجلبت فهيكون في عناياش التبتيب تاني
+
+265
+00:19:48,700 --> 00:19:54,080
+للتسليم وحوضح اكتر ان شاء الله تعالى ان خلال ال
+
+266
+00:19:54,080 --> 00:19:57,900
+modelبتمنى لكم التوفيق واتمنى يكون الموضوع ال
+
+267
+00:19:57,900 --> 00:20:00,660
+regression واضح بالنسبة لكم وإذا في أي استفسار
+
+268
+00:20:00,660 --> 00:20:04,320
+الموديل من خلال الموديل أو ال email أو جلسات
+
+269
+00:20:04,320 --> 00:20:08,180
+النقاش اللي هنعملها لاحقا السلام عليكم ورحمة الله
+
+270
+00:20:08,180 --> 00:20:09,220
+وبركاته
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/URknbds3fEY_postprocess.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/URknbds3fEY_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..4cad50987127fdf38a96137c36518b34b3b0e430
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/URknbds3fEY_postprocess.srt
@@ -0,0 +1,2748 @@
+1
+00:00:04,940 --> 00:00:07,280
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:07,280 --> 00:00:12,260
+أهلا وسهلا فيكم في محاضرتنا المستمر .. في
+
+3
+00:00:12,260 --> 00:00:15,740
+محاضراتنا المستمرة في مساق ال data mining وما زلنا
+
+4
+00:00:15,740 --> 00:00:20,980
+بنتكلم في باب ال classification و بالتحديد هنتكلم
+
+5
+00:00:20,980 --> 00:00:24,660
+اليوم على decision tree induction كنا في المحاضرات
+
+6
+00:00:24,660 --> 00:00:27,540
+السابقة أو المحاضرة الأخيرة أضفنا شغلة جديدة كنا
+
+7
+00:00:27,540 --> 00:00:31,040
+بنتكلم على النايف بياسوالـ Naive bias كانت فعليًا
+
+8
+00:00:31,040 --> 00:00:34,320
+هي واحدة من الـ Probabilistic approach المستخدمة
+
+9
+00:00:34,320 --> 00:00:36,800
+في ال machine learning من أجل ال classification
+
+10
+00:00:36,800 --> 00:00:41,680
+وقلنا احنا بيلزمني ان اعمل حسبة لمجموعة من ال
+
+11
+00:00:41,680 --> 00:00:44,300
+probabilities انا في عند ال instance اللي بدي ..
+
+12
+00:00:44,300 --> 00:00:46,600
+اللي هي ال unseen instance اللي انا بدي اعملها
+
+13
+00:00:46,600 --> 00:00:50,440
+classification بناء على ال .. وبالتالي ال class
+
+14
+00:00:50,440 --> 00:00:54,380
+طبعة ال instance هاي الموجودة عندى تساوي ال
+
+15
+00:00:54,380 --> 00:00:58,370
+maximum probabilityلل probabilities of the class
+
+16
+00:00:58,370 --> 00:01:05,470
+في احتمالية ان تكون ال instance هذه مع ال class
+
+17
+00:01:05,470 --> 00:01:10,110
+المعين و لما هروحنا بالتفصيل قلت انا فعليا بحاجة
+
+18
+00:01:10,110 --> 00:01:14,070
+انه هي data set اروح انشئ الجدول هذا بحيث انه انا
+
+19
+00:01:14,070 --> 00:01:18,550
+فالأروح حسبت ال probability لكل element أو لكل
+
+20
+00:01:18,550 --> 00:01:21,770
+classes اللي موجودة عندى ومن ثم انتقلنا في الخطوة
+
+21
+00:01:21,770 --> 00:01:24,910
+اللي بعدها جسمت أخدت ال attributes اللي المفروض
+
+22
+00:01:24,910 --> 00:01:27,370
+اللي المفروض عندها nominal attributes أخدت
+
+23
+00:01:27,370 --> 00:01:30,950
+distinct values وعملت حساب لكل واحدة فيهم وانتبه
+
+24
+00:01:30,950 --> 00:01:35,520
+دائما وانتبه دائما ان انا فعليا هان قاعد باشتغلعلى
+
+25
+00:01:35,520 --> 00:01:38,840
+ان ال probability نفسها يعني الآن عدد ال yes في ال
+
+26
+00:01:38,840 --> 00:01:42,880
+data 6 اللي عندي هنا 4 على 10 ومن ثم مع كل route
+
+27
+00:01:42,880 --> 00:01:48,400
+او كل attribute تحت ال yes هيكون 4 وكل مجموع
+
+28
+00:01:48,400 --> 00:01:51,920
+العناصر تحت كل no هيكون 6 و هكذا و هذا مفتاح
+
+29
+00:01:51,920 --> 00:01:56,510
+النجاح للعناصر الموجودة و لما اجينا بدنا نصنفالـ
+
+30
+00:01:56,510 --> 00:01:59,230
+sunny و ال mild و ال height قلنا حسبت ال
+
+31
+00:01:59,230 --> 00:02:01,670
+probability لل yes اللي كانت 4 على 10 في ال
+
+32
+00:02:01,670 --> 00:02:04,690
+probability لل sunny على ال yes و قلنا هذا الجدول
+
+33
+00:02:04,690 --> 00:02:07,810
+الأساس في الموضوع هي sunny و yes هيها 4 على 10
+
+34
+00:02:07,810 --> 00:02:12,530
+مضروبة فيه العنصر التاني كانت mild ال probability
+
+35
+00:02:12,530 --> 00:02:17,190
+تبعت ال mild يعني بين جسين هي ال yes ها دي مضروبة
+
+36
+00:02:17,190 --> 00:02:22,410
+في هيفي الـ mild في الـ high وهذه العناصر كانت
+
+37
+00:02:22,410 --> 00:02:25,050
+بتمثل ال probability فانا حسبت ال probability لل
+
+38
+00:02:25,050 --> 00:02:27,850
+different classes اللي موجودة عندى واخدت ال
+
+39
+00:02:27,850 --> 00:02:31,810
+maximum probability على ان هذه هي الاكتر احتمالا
+
+40
+00:02:31,810 --> 00:02:36,090
+في موضوع ان هذا العنصر او هذه ال instance تنتمي لل
+
+41
+00:02:36,090 --> 00:02:40,850
+class اللي موجود عندها الان اليوم ان شاء الله
+
+42
+00:02:40,850 --> 00:02:45,620
+تعالى هننتقلالموضوع الجديد اللي هو موضوع ال
+
+43
+00:02:45,620 --> 00:02:49,500
+decision tree في التعامل او ك different classifier
+
+44
+00:02:49,500 --> 00:02:53,300
+ال decision tree هي واحدة من ال classifiers المهمة
+
+45
+00:02:53,300 --> 00:02:57,200
+جدا المستخدمة في موضوع ال classification وهميتها
+
+46
+00:02:57,200 --> 00:03:00,840
+نبتكمن ان ممكن انا ارسم الشجرة وبالتالي بصير تفسير
+
+47
+00:03:00,840 --> 00:03:04,000
+ال model اللي موجود عندى او فهم ال model اللي عندى
+
+48
+00:03:04,000 --> 00:03:07,210
+اكثر منغيره على سبيل المثال احنا قولنا في ال
+
+49
+00:03:07,210 --> 00:03:10,610
+classifier الماضي اللي هو naive bias ان انا فعليا
+
+50
+00:03:10,610 --> 00:03:13,970
+عند ال classifier هذا مهم او جيد لأنه انا بقدر
+
+51
+00:03:13,970 --> 00:03:17,090
+افسر ليش النتيجة طلعت معايا هيك بناء انا على
+
+52
+00:03:17,090 --> 00:03:21,310
+الاحتمالات اللي موجودة في ال decision tree كذلكفي
+
+53
+00:03:21,310 --> 00:03:24,590
+decision tree هي عبارة عن انه انا فعليا حبني
+
+54
+00:03:24,590 --> 00:03:26,930
+decision tree جماعة الخير لما انا بتكلم على
+
+55
+00:03:26,930 --> 00:03:31,210
+decision tree اتذكروا خلينا نتذكر بشكل سريع ال
+
+56
+00:03:31,210 --> 00:03:34,930
+binary search tree مابديش اكتر من هيك ال binary
+
+57
+00:03:34,930 --> 00:03:38,490
+search tree كانت العناصر تبعتها انه كل node على
+
+58
+00:03:38,490 --> 00:03:43,580
+الاكثر عندها two childمظبوط هذه هي ال binary tree
+
+59
+00:03:43,580 --> 00:03:47,140
+وكان فيه rule بيحكمها ال rule انه انا في ال binary
+
+60
+00:03:47,140 --> 00:03:51,200
+search tree ان كل القيم اللي على اليمين هان هتكون
+
+61
+00:03:51,200 --> 00:03:55,570
+اكبرمن ال element وكل القيم اللي موجود عندها هن
+
+62
+00:03:55,570 --> 00:03:59,330
+هتكون أصغر طب القيم المتساوية مالهاش وجود المكررة
+
+63
+00:03:59,330 --> 00:04:02,830
+مالهاش وجود وبالتالي ال element مع كل node ال node
+
+64
+00:04:02,830 --> 00:04:05,690
+اللي عنده القيم اللي موجودة هن هتكون أصغر من القيم
+
+65
+00:04:05,690 --> 00:04:08,810
+اللي موجودة هن وهذه طبيعتها هتكون أصغر من القيم
+
+66
+00:04:08,810 --> 00:04:12,330
+اللي موجودة عندها بمعنى أخر أن ال structure تبع ال
+
+67
+00:04:12,330 --> 00:04:15,250
+decision tree أنا already بعرفها هي عبارة عن
+
+68
+00:04:15,250 --> 00:04:18,270
+مجموعة من ال nodes و ال connection أو ال connected
+
+69
+00:04:18,270 --> 00:04:22,790
+أو الgraph with no circuit زي ما كنا نسميها في الـ
+
+70
+00:04:22,790 --> 00:04:25,670
+discrete mathematics أشبه بالـ flow chart زي ما
+
+71
+00:04:25,670 --> 00:04:28,750
+قلنا سابقا في عند الـ internal node و اللي أنا
+
+72
+00:04:28,750 --> 00:04:32,150
+فعليا هي ال value تبعت .. هتمثل ال value تبعت ال
+
+73
+00:04:32,150 --> 00:04:35,490
+attribute اللي هحمل عليها الفحص هسأل قداش ال GPA
+
+74
+00:04:35,490 --> 00:04:40,550
+أكبر أو تساوي كذا بروح يمين أقل أو false بروح يسار
+
+75
+00:04:40,550 --> 00:04:45,090
+و هكذا فهذه ال internal node اللي هي عادة non-leaf
+
+76
+00:04:45,950 --> 00:04:49,790
+بتحدد ال test تبع ال attribute ال branch بيمثل ال
+
+77
+00:04:49,790 --> 00:04:53,210
+outcome وصولا لل leaf اللي موجودة عندى و ال leaf
+
+78
+00:04:53,210 --> 00:04:58,070
+node بتمثل ال class و طبعا لازم كل شجرة يكون لها
+
+79
+00:04:58,070 --> 00:05:03,690
+root node تعالى نشوف ال data set البسيطة اللى
+
+80
+00:05:03,690 --> 00:05:08,870
+موجودة عندها ال data set هاي مكونة من 14 rowالـ
+
+81
+00:05:08,870 --> 00:05:12,490
+Age و ال income و ال student و ال credit rating و
+
+82
+00:05:12,490 --> 00:05:15,710
+ال class تبعتي و طبعا جماعة الخير لما احنا بنروح
+
+83
+00:05:15,710 --> 00:05:20,610
+باتجاه ال binary class يعني two classes الأمر اللي
+
+84
+00:05:20,610 --> 00:05:23,690
+أسهل عشان استوعب إيش اللي بيصير لإنه لما تصير في
+
+85
+00:05:23,690 --> 00:05:26,430
+عندي تلاتة هتتشعب الأمور شوية في الحسبة لكن هي
+
+86
+00:05:26,430 --> 00:05:32,030
+عبارة عن تكرار لما سبق الآن أنا هذا .. عندي مجموعة
+
+87
+00:05:32,030 --> 00:05:35,530
+من الطلاب أو بيانات مجموعة من الناس اللي اشترت
+
+88
+00:05:35,530 --> 00:05:39,190
+حاسبات و ال data set كانت قديمة في ال 2000فكان
+
+89
+00:05:39,190 --> 00:05:42,630
+بيسأل هل هذا الشخص مؤهل أو ممكن مع احتمال ان يشتري
+
+90
+00:05:42,630 --> 00:05:47,430
+جهاز ولا لأ بناء على حالته ال age لاحظ ال age أنا
+
+91
+00:05:47,430 --> 00:05:52,190
+بتكلم على discrete او categorial data ال income
+
+92
+00:05:52,190 --> 00:05:56,210
+high و low و medium طالب ولا غير طالب yes or no و
+
+93
+00:05:56,210 --> 00:06:00,750
+ال credit ratingعادي او معتد الولا excellent
+
+94
+00:06:00,750 --> 00:06:03,830
+بالنسبة للمتوسط الراتب تبعته وفي الآخر ال class
+
+95
+00:06:03,830 --> 00:06:07,330
+اللي موجود عندهم الان لما انا بدي ابني tree ال
+
+96
+00:06:07,330 --> 00:06:11,730
+tree هتاخد بالشكل هذا خلينا بس عشان ناخد على
+
+97
+00:06:11,730 --> 00:06:16,110
+السريع ناخد ال role أول عشان نتذكر و نشوف كيف بدي
+
+98
+00:06:16,110 --> 00:06:19,350
+اتعامل مع ال tree او كيف تشغل ك calisphere yes يث
+
+99
+00:06:19,350 --> 00:06:24,090
+و high و no fair
+
+100
+00:06:26,540 --> 00:06:32,680
+الـ target تبعتي؟ لا هذا أول روح بس أنا عشان أغير
+
+101
+00:06:32,680 --> 00:06:36,700
+بدي أحق هنا yes عشان تصير هذا ال data أشبه بال
+
+102
+00:06:36,700 --> 00:06:41,660
+unseen و أشوف بال classification تبعتها كيف بدها
+
+103
+00:06:41,660 --> 00:06:47,620
+تكون الآن زي ما قلنا اللي يفهد ال age ال income
+
+104
+00:06:47,620 --> 00:06:50,860
+student
+
+105
+00:06:50,860 --> 00:06:54,920
+و في الآخر اللي هي ال credit
+
+106
+00:07:02,220 --> 00:07:06,100
+rate حاجة على decision tree ال decision tree او ال
+
+107
+00:07:06,100 --> 00:07:09,400
+model لما تم بناءه جالبه بيقول اهم element في
+
+108
+00:07:09,400 --> 00:07:13,660
+القرار عندي ال edge و هنتعرف كمان لحظات ان شاء
+
+109
+00:07:13,660 --> 00:07:17,240
+الله تعالى كيف احنا اختارنا ال edge ليش ماكنتش ل
+
+110
+00:07:17,240 --> 00:07:20,060
+student او ل credit rating اللي هي ال attributes
+
+111
+00:07:20,060 --> 00:07:23,260
+التانية و لاحظة ان في عندي بالكامل في عندي
+
+112
+00:07:23,260 --> 00:07:27,950
+attribute غايب اللي هي موضوعالـ income في الـ
+
+113
+00:07:27,950 --> 00:07:30,530
+decision tree اللي موجود عندي يعني هو كأنه بيقول
+
+114
+00:07:30,530 --> 00:07:35,270
+ال income هان مش صاحب تأثير كتير على ال decision
+
+115
+00:07:35,270 --> 00:07:39,010
+أو على القرار اللي موجود عندي طب كيف هذا الكلام
+
+116
+00:07:39,010 --> 00:07:44,590
+صار؟ هنشوفه كمان شوية ليش؟ في دلالة تانية هان بيجي
+
+117
+00:07:44,590 --> 00:07:47,350
+بيقول إنه ال high الأقل تأثيرا أو مالش تأثير يعني
+
+118
+00:07:47,350 --> 00:07:50,130
+بقدر أنا أشيله أو أستغني عنه بجمع البيانات التانية
+
+119
+00:07:50,130 --> 00:07:55,510
+بتكون أسهل الآن ال ageYouth, middle age و senior
+
+120
+00:07:55,510 --> 00:07:59,210
+فى عندى تفرعات غير هيك لأ هدولة ال three discrete
+
+121
+00:07:59,210 --> 00:08:02,850
+values اللى موجودة عندى بال age تمام حسب ال role
+
+122
+00:08:02,850 --> 00:08:09,970
+عندهان يف هي ال يف إذا أنا سألته يف يعني خلاص كل
+
+123
+00:08:09,970 --> 00:08:14,010
+branch السابق هاي ماليش دخل فيها إذا كان هو
+
+124
+00:08:14,010 --> 00:08:19,770
+student غالبا هيشتري ومش هدور على الفيرم مش
+
+125
+00:08:19,770 --> 00:08:22,210
+هتلزمني تعال طلع معايا عندهان
+
+126
+00:08:26,000 --> 00:08:28,800
+و هذا الطالب بيكون هيشتري كمبيوتر لإيش؟ لأن إذا
+
+127
+00:08:28,800 --> 00:08:31,800
+كان هو في ال middle ايه؟ أو في اليث صغير أو شاب
+
+128
+00:08:31,800 --> 00:08:35,300
+يافع و طالب في نفس الوقت يعني طالب جامعة فغالبا
+
+129
+00:08:35,300 --> 00:08:38,820
+هذا هيحتاج كمبيوتر و من ثم هيروح يشتريه لو أنا بدي
+
+130
+00:08:38,820 --> 00:08:42,000
+أرجع لل data set اللي موجودة عندي هان وان اليث و
+
+131
+00:08:42,000 --> 00:08:49,200
+student و fair yes يث student و fair
+
+132
+00:08:51,960 --> 00:08:54,880
+عشان تلاحظ ان هدولة التنتين هما اللي كانوا اكتر
+
+133
+00:08:54,880 --> 00:09:00,340
+تأثيرا في حالة ال elements اللي مولودة وهكذا لو
+
+134
+00:09:00,340 --> 00:09:05,040
+كان still age في ال middle age مباشرة هيكون هيشتري
+
+135
+00:09:05,040 --> 00:09:08,040
+ال attribute لو كان senior
+
+136
+00:09:10,850 --> 00:09:14,250
+وال income rate اللي عنده fair غالبا مش هيشتريه
+
+137
+00:09:14,250 --> 00:09:17,210
+وهذه هيك بتصير موضوع ال decision او موضوع ال
+
+138
+00:09:17,210 --> 00:09:19,950
+classification يعني ال leaves اللي عندي في ال node
+
+139
+00:09:19,950 --> 00:09:23,850
+او عفوا في ال .. في ال trees ال leaf nodes بتمثل
+
+140
+00:09:23,850 --> 00:09:27,930
+ال classes اللي انا بقى ادور عليها وطبعا عمق
+
+141
+00:09:27,930 --> 00:09:33,210
+الشجرة وحجمها مرتبط بعدد ال attributes وحجم ال
+
+142
+00:09:33,210 --> 00:09:35,970
+data set اللي موجودة عندى
+
+143
+00:09:38,250 --> 00:09:42,710
+الأن ال algorithm المستخدم مع ال decision tree
+
+144
+00:09:42,710 --> 00:09:50,490
+اللي هو ال basic algorithm بنسميه C4.5 وهذا بيشتغل
+
+145
+00:09:50,490 --> 00:09:54,150
+في مبدأ ال top-down recursive divide and conquer
+
+146
+00:09:54,150 --> 00:09:58,730
+الان الناس اللي أخدت خوارزميات حتما مر عليها مصطلح
+
+147
+00:09:58,730 --> 00:10:03,170
+divide and conquer الفكرة في ال algorithm هذا ان
+
+148
+00:10:03,170 --> 00:10:07,810
+المشكلة الكبيرة جزئها بتقدر تسيطر عليهايعني
+
+149
+00:10:07,810 --> 00:10:11,630
+بنجوسين حل جزء جزء من ال data set اللي موجودة عندك
+
+150
+00:10:11,630 --> 00:10:14,890
+هنا و هنشوف كمان شوية و هذا المبدأ هو مبدأ ال
+
+151
+00:10:14,890 --> 00:10:17,870
+greedy طبعا و من ثم ال algorithm هذا أخد ال greedy
+
+152
+00:10:17,870 --> 00:10:21,450
+algorithm شو يعني greedy يعني الطماع فكرته بكل
+
+153
+00:10:21,450 --> 00:10:24,710
+بساطة أنه أنا بنظر لل best solution في ال current
+
+154
+00:10:24,710 --> 00:10:29,210
+stage ماليش على المدى البعيد إيش اللي بيصير عندي؟
+
+155
+00:10:30,520 --> 00:10:33,720
+هبدأ مع كل examples هاخد مع ال data ال attributes
+
+156
+00:10:33,720 --> 00:10:38,280
+لكل ال data set و اروح عشان اوجدها او اوجد من
+
+157
+00:10:38,280 --> 00:10:45,240
+خلالها ال route الان كل ال data set اللي عندي هنا
+
+158
+00:10:45,240 --> 00:10:52,780
+must be categorical الان في ال C4.5 كل ال
+
+159
+00:10:52,780 --> 00:10:56,500
+attribute لازم تكون categorical طب انا ماعنديش انا
+
+160
+00:10:56,500 --> 00:11:01,750
+عندي continuous value اعملها discretizationو كل بن
+
+161
+00:11:01,750 --> 00:11:06,030
+اديها label و اعتمد اشتغل على ال label اللي موجود
+
+162
+00:11:06,030 --> 00:11:09,810
+عندك هان يعني لما تيجي مثلا ال age نقول والله
+
+163
+00:11:09,810 --> 00:11:19,390
+الياث من 16 مثلا ل 22 هيث ال
+
+164
+00:11:19,390 --> 00:11:24,870
+age اقول مثلا من 23 الى 35 senior
+
+165
+00:11:26,900 --> 00:11:30,060
+وبالتالي انا بقدر اشتغل .. بما ان ال algorithm بدو
+
+166
+00:11:30,060 --> 00:11:33,260
+مني discrete او nominal data فبقدر اعمل
+
+167
+00:11:33,260 --> 00:11:37,140
+discretization بعمل binning و بعد هيك بروح بحط
+
+168
+00:11:37,140 --> 00:11:43,280
+label لكل bin او لكل interval في ال continuous
+
+169
+00:11:43,280 --> 00:11:47,000
+attribute اللي موجودة عندهم على الرغم من هيك هتكلم
+
+170
+00:11:47,000 --> 00:11:51,160
+كمان شوية بشكل بسيط في موضوع فعليا كيف ممكن انا
+
+171
+00:11:51,160 --> 00:11:54,620
+افحص لو كان عندي continuous في algorithm مختلفة
+
+172
+00:11:54,620 --> 00:11:55,680
+طيب
+
+173
+00:11:58,590 --> 00:12:03,350
+ممتاز معناته انا فعليا هاخد ال data set و ابدأ امر
+
+174
+00:12:03,350 --> 00:12:08,530
+على كل attribute و على كل ال rows و اجسم العناصر
+
+175
+00:12:08,530 --> 00:12:12,510
+اللي موجودة ال test attribute اللي هيمثل ال node
+
+176
+00:12:12,510 --> 00:12:16,170
+اللي هاخد عليها decision اللي سمينها بين جثين ال
+
+177
+00:12:16,170 --> 00:12:19,930
+internal nodes سواء كانت هاي او هاي او هاي ماليش
+
+178
+00:12:19,930 --> 00:12:24,510
+beliefs لأن ال leaves بتمثل ال classes الآن هذه ال
+
+179
+00:12:24,510 --> 00:12:29,850
+test nodesأو test attributes هختارها تبعًا
+
+180
+00:12:29,850 --> 00:12:34,690
+لهيوريستيك أو statistical measurement بناءً على
+
+181
+00:12:34,690 --> 00:12:38,510
+مجموعة من ال rules المكتسبة سابقًا أو مجموعة من ال
+
+182
+00:12:38,510 --> 00:12:43,130
+statistics هعتمدها مثل الinformation gain أو
+
+183
+00:12:43,130 --> 00:12:47,920
+الgenie indexاللي هنشوف طبعا احنا هنكتفي في ال
+
+184
+00:12:47,920 --> 00:12:51,460
+course هذا على حسبة ال information gain وممكن
+
+185
+00:12:51,460 --> 00:12:55,480
+ازودكوا لاحقا ب description او بشرح لواحدة من ال
+
+186
+00:12:55,480 --> 00:13:00,440
+algorithm التانية اللي موجودة بتاعنا متى بدي اوقف
+
+187
+00:13:00,440 --> 00:13:05,800
+بوقف لما بتكون كل يعني في كل مرة احنا قولنا divide
+
+188
+00:13:05,800 --> 00:13:11,020
+and conquer في ال data set بروح باخد ال data set و
+
+189
+00:13:11,020 --> 00:13:13,480
+ببدأ بشتغل على ال attribute الأول ال attribute هذا
+
+190
+00:13:13,480 --> 00:13:21,080
+جسم ال data set ل2 أو 3 data sets مع كل data set
+
+191
+00:13:21,080 --> 00:13:24,700
+بأخدها إذا ال data set هذه كل العناصر اللي فيها
+
+192
+00:13:24,700 --> 00:13:28,480
+بتنتمي لنفس ال class يعني خلاص مافيش شغل على ال
+
+193
+00:13:28,480 --> 00:13:32,680
+data set هاي بمعنى آخر أنا أجيت لل middle age هنا
+
+194
+00:13:32,680 --> 00:13:37,500
+لما روحت قلت طبعا احنا حسبنا قلنا اخترنا ان ال
+
+195
+00:13:37,500 --> 00:13:40,760
+index هو ال major او ال root تبعتي الأول test
+
+196
+00:13:40,760 --> 00:13:44,420
+attribute وجيت دورت في ال middle age
+
+197
+00:13:47,510 --> 00:13:58,370
+Middle Age Middle Age تلاتاشة
+
+198
+00:13:58,370 --> 00:14:02,890
+واربعتاش بكل ال middle age هدولة يشملهم هدولة
+
+199
+00:14:02,890 --> 00:14:07,250
+بينتميوا لنفس ال class كلهم yes وبالتالي عند ال
+
+200
+00:14:07,250 --> 00:14:09,810
+middle age مافيش عندي continuous خلاص أنا وصلت
+
+201
+00:14:09,810 --> 00:14:13,590
+للنهايةلأ، طيب، ممتاز، معناته أول condition للـ
+
+202
+00:14:13,590 --> 00:14:18,070
+stopping أن كل ال samples لل node المعضاها بتنتمي
+
+203
+00:14:18,070 --> 00:14:21,530
+لنفس ال class زي ما شوفنا مع ال middle edge الحالة
+
+204
+00:14:21,530 --> 00:14:24,970
+التانية، أنه أنا فعليا بضلني بأجسم أو بعمل
+
+205
+00:14:24,970 --> 00:14:32,250
+partitioning لحد ما أصل أنه no remaining sample لل
+
+206
+00:14:32,250 --> 00:14:37,540
+attributes الموجودة، بدي أرجع معاك كمان مرة عفواno
+
+207
+00:14:37,540 --> 00:14:40,260
+remaining attributes او خلصت كل ال attributes اللي
+
+208
+00:14:40,260 --> 00:14:45,120
+عندي او فعليا ماضلش عندي samples موجودة بدي ارجع
+
+209
+00:14:45,120 --> 00:14:48,840
+معاك كمان مرهان انا الان هاتفقنا ان ال age هو اول
+
+210
+00:14:48,840 --> 00:14:55,700
+واحد خلصت من ال middle age انا ايش
+
+211
+00:14:55,700 --> 00:15:04,270
+بقي عندي بقي عندي ال young ال youthو ال senior ال
+
+212
+00:15:04,270 --> 00:15:08,610
+data set تبعتي هتنجسم ل two data sets يث و senior
+
+213
+00:15:08,610 --> 00:15:15,110
+يث و senior معناته انا هحصل على هاي
+
+214
+00:15:15,110 --> 00:15:19,990
+ال data set اللي موجودة عندي ها هي اليث فهروح انا
+
+215
+00:15:19,990 --> 00:15:26,650
+اخد هتعامل مع ال data set بعد هيك هايعلى إنها data
+
+216
+00:15:26,650 --> 00:15:30,390
+set مستقلة و أعمل و أبدأ بالحسبة مرة تانية يعني
+
+217
+00:15:30,390 --> 00:15:36,370
+بين جوسين أصبحت اليف الآن هي ال branch الآن مين
+
+218
+00:15:36,370 --> 00:15:40,830
+ضال عندي income و student و ال credit هروح أدور
+
+219
+00:15:40,830 --> 00:15:45,850
+بين هدول مين اللي هتكون عند ال test node هانو هعمل
+
+220
+00:15:45,850 --> 00:15:50,210
+split لل data هذه ال data set انسي الباقي كله هعمل
+
+221
+00:15:50,210 --> 00:15:54,570
+split لل data set هذه بناء على selected attribute
+
+222
+00:15:54,570 --> 00:15:57,930
+بين جثين احنا شفنا بال example مسبقا انه ال
+
+223
+00:15:57,930 --> 00:16:01,530
+student فكانت هي ال student ال student هدفي yes و
+
+224
+00:16:01,530 --> 00:16:06,370
+no بناء عليهالـ data set بتنجي سيملة two data sets
+
+225
+00:16:06,370 --> 00:16:10,450
+كمان مرة واحدة مع ال yes و واحدة مع ال no و بنقل
+
+226
+00:16:10,450 --> 00:16:14,510
+طبعا بما انه انا student yes و no بروح بدور صارت
+
+227
+00:16:14,510 --> 00:16:17,450
+هدولة بينتم دولة class و هدولة كل partition بينتم
+
+228
+00:16:17,450 --> 00:16:22,100
+ال class معناته انا وجفتطيب فحصت ال .. عفوا فحصت
+
+229
+00:16:22,100 --> 00:16:26,320
+ال age و فحصت ال student و فحصت ال income و في
+
+230
+00:16:26,320 --> 00:16:28,940
+الآخر لاجيت ان انا فعليا مافيش عندي attributes
+
+231
+00:16:28,940 --> 00:16:32,200
+فخلصنا فهذه ال condition او stopping conditions
+
+232
+00:16:32,200 --> 00:16:35,900
+اللي انا ممكن اوقف عليها طالما ال data ستة بقعت
+
+233
+00:16:35,900 --> 00:16:40,840
+كبيرة و فيها شغل ال decision tree بياخد مني وجد في
+
+234
+00:16:40,840 --> 00:16:44,820
+موضوع القرار اللي موجود هنا كمان مرة بلخص بشكل
+
+235
+00:16:44,820 --> 00:16:50,430
+سريعمتى انا ممكن اوقف اظل ابحث مين اللي بيحدد ال
+
+236
+00:16:50,430 --> 00:16:53,630
+depth تبعت letter E ال depth تبعت letter E تحدد
+
+237
+00:16:53,630 --> 00:16:56,810
+تبع ال dimensionality تبع ال data set عدد ال
+
+238
+00:16:56,810 --> 00:17:01,550
+attributes و عدد ال rows الان متى بدي اوقف لما
+
+239
+00:17:01,550 --> 00:17:04,890
+تكون كل ال sample في ال given node تنتمي لنفس ال
+
+240
+00:17:04,890 --> 00:17:07,950
+class يعني لما انا اخترت ال attribute و روحت اعمل
+
+241
+00:17:07,950 --> 00:17:11,970
+splitلاجيت واحدة من الـ partitions اللي موجودة
+
+242
+00:17:11,970 --> 00:17:13,970
+بتنتمي لنفس ال class خلاص هاد ابنا مافيش فيها شغل
+
+243
+00:17:13,970 --> 00:17:16,870
+لإن هاد ال decision تبعتها مباشرة لإنها بتنتمي
+
+244
+00:17:16,870 --> 00:17:20,850
+لنفس ال class معناته خلاص اوصلت ال leave node ال
+
+245
+00:17:20,850 --> 00:17:29,750
+leave node تبعتي ال leave node ال leave لماالخيار
+
+246
+00:17:29,750 --> 00:17:32,690
+التاني أنه لما بكون فعليًا أنا عملت splitting لل
+
+247
+00:17:32,690 --> 00:17:35,250
+data set على كل ال attributes وخلصت ال attributes
+
+248
+00:17:35,250 --> 00:17:40,030
+تبعتي برضه ماعنديش شغل و there is no sample left
+
+249
+00:17:40,030 --> 00:17:43,610
+مابغيش عندي ولا حاجة في ال data set عشان أجسمها
+
+250
+00:17:43,610 --> 00:17:47,510
+على مستوى الرأس تعالوا نروح مع بعض من خلال نشوف ال
+
+251
+00:17:47,510 --> 00:17:52,910
+information gain و هي الأكثر و الأشهر استخدامها و
+
+252
+00:17:52,910 --> 00:17:55,830
+ال Gain Index هنتكلم على ال information gain بكل
+
+253
+00:17:55,830 --> 00:17:59,970
+بساطةالـ information gain بتعتمد على ال
+
+254
+00:17:59,970 --> 00:18:02,830
+probability مش احنا قلنا قبل شوية موضوع ال
+
+255
+00:18:02,830 --> 00:18:06,970
+splitting او الفصل في ال attributes بيعتمد اعتماد
+
+256
+00:18:06,970 --> 00:18:12,250
+كله على فعليا العناصر اللي موجودة على احتمال
+
+257
+00:18:12,250 --> 00:18:15,930
+يقولنا اما heuristic rules او statistical
+
+258
+00:18:15,930 --> 00:18:19,650
+measurement لما بتكلم على probability معناته انا
+
+259
+00:18:19,650 --> 00:18:22,950
+جاي بتتكلم على احتمالات ال statistics الى اخرين
+
+260
+00:18:23,780 --> 00:18:27,160
+بقول افترض ان الـ P I هي عبارة عن ال probability
+
+261
+00:18:27,160 --> 00:18:34,780
+of an arbitrary tuple في ال data ال 6 تبعتي تبعتي
+
+262
+00:18:34,780 --> 00:18:36,740
+تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي
+
+263
+00:18:36,740 --> 00:18:36,820
+تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي
+
+264
+00:18:36,820 --> 00:18:37,520
+تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي
+
+265
+00:18:37,520 --> 00:18:40,280
+تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي
+
+266
+00:18:40,280 --> 00:18:49,560
+تبعتي تبعتي تبعتي تبعتي تبعتي تبعتي تبع
+
+267
+00:18:51,740 --> 00:18:55,960
+الـ Probability للـ CD الـ CI على ال D على كل
+
+268
+00:18:55,960 --> 00:18:59,300
+Probability تبع ال data set اللي موجودة بكل بساطة
+
+269
+00:18:59,300 --> 00:19:04,400
+أنا في عندي تلت عمليات حسابية هعملها عشان أخد ال
+
+270
+00:19:04,400 --> 00:19:07,560
+decision و أحدد من ال test node اللي موجود عندي
+
+271
+00:19:07,560 --> 00:19:11,540
+الأولى هسميها ال expected information أو ال
+
+272
+00:19:11,540 --> 00:19:19,260
+entropy وهي لكل ال data set اللي موجودة عندي هنا
+
+273
+00:19:19,260 --> 00:19:27,600
+شو يعني؟الان مطلوب مني ان احسب ال information او
+
+274
+00:19:27,600 --> 00:19:31,140
+ال entropy لل classes اللي موجودة في ال data set
+
+275
+00:19:31,140 --> 00:19:34,700
+لكل ال data set وهنا بنجو سين وكأني بده يقوللي
+
+276
+00:19:34,700 --> 00:19:40,940
+احسب احتمالية او احسب ال probability لكل class في
+
+277
+00:19:40,940 --> 00:19:43,880
+ال data set عدد مرات ظهور ل class في ال data set
+
+278
+00:19:43,880 --> 00:19:46,840
+اللي موجودة عندي هنا وبعد هيك بروح طبق عليهم
+
+279
+00:19:46,840 --> 00:19:51,840
+العملية يعني انا لو كنت على سبيل المثالال data 6
+
+280
+00:19:51,840 --> 00:19:57,580
+تبعتي فيها عشر element أربعة منهم yes وستة منهم no
+
+281
+00:19:57,580 --> 00:20:01,040
+أنا
+
+282
+00:20:01,040 --> 00:20:04,100
+في عيني بتكلم على binary classification yes or no
+
+283
+00:20:04,100 --> 00:20:10,200
+أربعة yes وستة no ال information gained لل data 6
+
+284
+00:20:10,200 --> 00:20:16,720
+تبعتي كلها هي عبارة عن مجموع ناقص
+
+285
+00:20:16,720 --> 00:20:20,600
+مضروبة فيه ال probability تبعت ال data الأولى
+
+286
+00:20:22,150 --> 00:20:28,310
+احتمال ال class الأول 4 على 10 مضروبة في log ال 4
+
+287
+00:20:28,310 --> 00:20:33,210
+على 10 للأساس 2 زائد
+
+288
+00:20:34,590 --> 00:20:40,310
+6 على 10 مضروبة في ال logarithm 6 على 10 ال
+
+289
+00:20:40,310 --> 00:20:44,350
+logarithm ال binary logarithm و هكذا ليش القيمة
+
+290
+00:20:44,350 --> 00:20:48,030
+هتداني إشارة سالبة لأن ال logarithm تبعت ال binary
+
+291
+00:20:48,030 --> 00:20:52,690
+بتاعة الكسل هتطلع عندى سالب و إذا بتذكروا في عندى
+
+292
+00:20:52,690 --> 00:21:01,740
+log ال X على ال Yتساوي log X ناقص log Y وبما ان ال
+
+293
+00:21:01,740 --> 00:21:05,200
+Y عندي اكبر من ال X فستكون القيمة اللي عندي سالبة
+
+294
+00:21:05,200 --> 00:21:07,880
+عشان انا اخلص منها اخلص منها فكانت القيام اللي
+
+295
+00:21:07,880 --> 00:21:12,360
+عندي هان هتطلع قيم موجبة واضح الأمور ان شاء الله
+
+296
+00:21:12,360 --> 00:21:18,090
+جماعة الخيرالان يعني اول شغلة فعليا انا هسويها
+
+297
+00:21:18,090 --> 00:21:21,350
+هروح احسب ال probability لكل class او بين جثين
+
+298
+00:21:21,350 --> 00:21:27,670
+هحسب ال entropy هي عبارة عن حاصل .. عبارة عن مجموع
+
+299
+00:21:27,670 --> 00:21:33,310
+حاصل ضرب ال probability لكل class في ال logarithm
+
+300
+00:21:33,310 --> 00:21:38,830
+او ال binary log ل ال probability ل ال class اللي
+
+301
+00:21:38,830 --> 00:21:41,930
+موجود عندى و زي ما بقوله بال .. بال .. بال ..
+
+302
+00:21:42,360 --> 00:21:45,340
+بالمثال يتضح المقار كمان شوية هنتقل للمثال
+
+303
+00:21:45,340 --> 00:21:50,740
+بالتفصيل ان شاء الله تعالى الخطوة اللي بعد هيك بدي
+
+304
+00:21:50,740 --> 00:21:58,260
+اروح لكل attribute A احاول فعليا هيجسم ال data set
+
+305
+00:21:58,260 --> 00:22:02,040
+لمجموعة من ال partitions جداش عدد ال V هذه او جداش
+
+306
+00:22:02,040 --> 00:22:07,420
+عدد ال partitions بعدد ال distinct values اللي
+
+307
+00:22:07,420 --> 00:22:12,630
+موجودة عندى فيه ال attributeيعني ال age كان في
+
+308
+00:22:12,630 --> 00:22:19,910
+عندي تلاتة three three values يث و middle age و
+
+309
+00:22:19,910 --> 00:22:23,570
+senior ففعليا ال attribute ال age هي
+
+310
+00:22:26,960 --> 00:22:30,380
+الـ Attribute الـ Age يث و Middle Age والسينيور
+
+311
+00:22:30,380 --> 00:22:33,860
+هيلي الـ three distinct values ففعليا بناء على ال
+
+312
+00:22:33,860 --> 00:22:38,600
+attribute هذا هجسم ال data ستة باعتي كلها ل three
+
+313
+00:22:38,600 --> 00:22:43,860
+.. ل three subsets ل three partitions مع كل واحدة
+
+314
+00:22:43,860 --> 00:22:46,600
+من ال values اللي موجودة عندي هنا عشان انا فعليا
+
+315
+00:22:46,600 --> 00:22:52,190
+اروحأحسب ال information لل attribute اللي موجودة
+
+316
+00:22:52,190 --> 00:22:56,050
+عندها ايش ال information لل attribute ال
+
+317
+00:22:56,050 --> 00:23:01,870
+information لل attribute يساوي ال summationاحتمال
+
+318
+00:23:01,870 --> 00:23:04,870
+ال element اللي عندي او ال class اللي موجودة عندي
+
+319
+00:23:04,870 --> 00:23:08,310
+هنا لل attribute فيه ال information تبعت ال subset
+
+320
+00:23:08,310 --> 00:23:12,390
+اللي موجودة يعني بين جسيم ال subset الجديدة انا
+
+321
+00:23:12,390 --> 00:23:16,770
+هشتغل عليها و احسبها ال intro b السابقة بعد ما
+
+322
+00:23:16,770 --> 00:23:23,570
+احسب ال information لل attribute ال gain الانحياز
+
+323
+00:23:25,400 --> 00:23:28,740
+لأ ال element اللى موجود عندى هان أو التحصيل اللى
+
+324
+00:23:28,740 --> 00:23:33,400
+ممكن نسميها التحصيل ال a هي عبارة عن ال
+
+325
+00:23:33,400 --> 00:23:38,760
+information لل D الأولى ناقص ال information أو ال
+
+326
+00:23:38,760 --> 00:23:41,640
+entropy تبعت ال attribute اللى عندى ال entropy
+
+327
+00:23:41,640 --> 00:23:47,180
+تبعت ال attribute اللى عندى يعني أنا فعليا هاخد
+
+328
+00:23:47,180 --> 00:23:53,540
+هاي و هايهتراحهم من بعض بس ما تنسوش انه فعليا هذه
+
+329
+00:23:53,540 --> 00:23:59,580
+هي نفسها اللي فوق بس على different subset او على
+
+330
+00:23:59,580 --> 00:24:03,680
+different data set او بين جسين على subset set تبعا
+
+331
+00:24:03,680 --> 00:24:07,320
+لل values اللي جسمها لل partition اللي جسمت ليها
+
+332
+00:24:07,320 --> 00:24:11,480
+ال attribute اللي عندنا تعالوا نروح هن و نشوف
+
+333
+00:24:11,480 --> 00:24:17,140
+المثال اللي موجود عندنا قلنا في الخطوة رقم واحدفي
+
+334
+00:24:17,140 --> 00:24:21,600
+الخطوة رقم واحد قلنا انا اتفقنا ان انا فعليا هروح
+
+335
+00:24:21,600 --> 00:24:24,800
+احسب ال information gain او ال entropy لكل ال data
+
+336
+00:24:24,800 --> 00:24:29,260
+set ممتاز عشان احسب ال entropy لكل ال data set
+
+337
+00:24:29,260 --> 00:24:33,540
+بنذكر قلنا هو عبارة عن ال summation سالب واحد في
+
+338
+00:24:33,540 --> 00:24:40,160
+ال summation في probability لل I في log ل ال P I
+
+339
+00:24:40,160 --> 00:24:43,960
+ال probability لل I و ايش قلنا هاي ال classوالـ I
+
+340
+00:24:43,960 --> 00:24:46,920
+بيتساوى من واحد لأن بعدد ال classes اللي موجودة
+
+341
+00:24:46,920 --> 00:24:51,360
+حسب ال data set اللي موجودة عندها حسب ال data set
+
+342
+00:24:51,360 --> 00:24:53,900
+اللي موجودة عندها انا في عندى two different
+
+343
+00:24:53,900 --> 00:24:58,680
+classes only two different classes only اللي هم
+
+344
+00:24:58,680 --> 00:25:05,940
+yes و no حجم ال data set كل هجدش يا جماعة الخير 14
+
+345
+00:25:05,940 --> 00:25:11,280
+عدد ال yes 9 معناته ال probability تبعتها 9 على 14
+
+346
+00:25:13,570 --> 00:25:18,130
+الـ Probability للـ Yes 9 على 14 طب عدد الـ No
+
+347
+00:25:18,130 --> 00:25:24,810
+بجيتها 5 5 على 14 هي الاحتمالية تبعتها 5 على 14
+
+348
+00:25:24,810 --> 00:25:31,190
+وبهيك أنا حصلت على أول خطوةاللي هي عرفت ال
+
+349
+00:25:31,190 --> 00:25:34,790
+probability تبعت لـ classes اللي موجودة عندي اللي
+
+350
+00:25:34,790 --> 00:25:37,570
+هي ال probability لل yes و ال probability لل no
+
+351
+00:25:37,570 --> 00:25:40,030
+الخطوة التالية اللي المفروض ان انا اشتغل عليها
+
+352
+00:25:40,030 --> 00:25:43,410
+الان ان انا بدروح احسب ال information او ال
+
+353
+00:25:43,410 --> 00:25:48,210
+entropy تبعتي بالمعادلة التالية ال information
+
+354
+00:25:48,210 --> 00:25:57,610
+هنرمزلها لل I لل data set تبعتي تساوي تساوي
+
+355
+00:25:59,800 --> 00:26:04,940
+I تسعة كما خمسة تسعة و خمسة هدول هم الاربعتاش
+
+356
+00:26:04,940 --> 00:26:07,660
+تبعوتي يا جماعة الخير الان هي القانون تبع ال
+
+357
+00:26:07,660 --> 00:26:12,580
+information هيه بيلزمني فيها ان اعرف ال
+
+358
+00:26:12,580 --> 00:26:16,020
+probability لل yes و ال probability لل no وهذا
+
+359
+00:26:16,020 --> 00:26:24,260
+الكلام يساوي ماقص مضروبة فيه كام class and two
+
+360
+00:26:24,260 --> 00:26:27,790
+class هيهم هدوللو كانوا تلاتة هيكونوا تلاتة لو
+
+361
+00:26:27,790 --> 00:26:32,130
+أربعة هيكونوا أربعة إلى آخره مع كل واحدة فيهم الان
+
+362
+00:26:32,130 --> 00:26:36,270
+تسعة على أربعة اتناش هي تبعت ال class الأول اللي
+
+363
+00:26:36,270 --> 00:26:42,030
+بين جثين احنا قلنا ال yes مضروبة في ال binary
+
+364
+00:26:42,030 --> 00:26:48,970
+logarithm للتسعة على أربعة اتناشمجموعة لهم مجموعة
+
+365
+00:26:48,970 --> 00:26:54,010
+الخمسة تبعتها الخمسة تبعت النو خمسة على أربعة عاش
+
+366
+00:26:54,010 --> 00:27:01,670
+مضروبة في ال logarithm ال binary logarithm الخمسة
+
+367
+00:27:01,670 --> 00:27:07,950
+على أربعة عاش هذا ال gain تبعت كل ال data set
+
+368
+00:27:07,950 --> 00:27:11,230
+توزيعت ال data set عندي على two classes تذكر كمان
+
+369
+00:27:11,230 --> 00:27:17,750
+مرةواحدة اتين تلاتة اربعة خمسة no خمسة من اربعة
+
+370
+00:27:17,750 --> 00:27:21,290
+اتاشر معناته عندى تسعة yes والان قولنا هي قانونهم
+
+371
+00:27:21,290 --> 00:27:25,670
+قانون ال information او ال gain عفوا ال entropy لل
+
+372
+00:27:25,670 --> 00:27:30,730
+data set هي عبارة عن سالب واحد مضروبة في مجميع ل
+
+373
+00:27:30,730 --> 00:27:35,410
+probability لكل class مضروبة في ال log ل log ل
+
+374
+00:27:35,410 --> 00:27:38,650
+probability لكل class فانا هيني حسبت المعادلة اللى
+
+375
+00:27:38,650 --> 00:27:40,670
+موجودة عندى هتظهر من خلال
+
+376
+00:27:43,770 --> 00:27:51,650
+سلايد هيه وهذه
+
+377
+00:27:51,650 --> 00:27:59,370
+قيمتها point تسعة أربعة أو أربعة وتسعين من مية هذه
+
+378
+00:27:59,370 --> 00:28:03,130
+ثابتة هتكون لكل ال data set لكل training set اللي
+
+379
+00:28:03,130 --> 00:28:06,830
+أنا ببني عليها ال model ممتاز انا مشيت اول خطوة في
+
+380
+00:28:06,830 --> 00:28:12,030
+الحل الخطوة التالية ان انا فعليا بدي اروح اي اتنين
+
+381
+00:28:16,020 --> 00:28:22,480
+بدأ أحسب ال information لكل attribute موجود في ال
+
+382
+00:28:22,480 --> 00:28:28,200
+data set لكل attribute؟ صحيح فهأخد احسب ال intro
+
+383
+00:28:28,200 --> 00:28:33,140
+بالان او ال information gain لل age و احسب ال
+
+384
+00:28:33,140 --> 00:28:39,490
+informationGain للـ income لل student لل credit
+
+385
+00:28:39,490 --> 00:28:45,670
+rating و هكذا خليني انا ابدأ معاكوا و اذكركم ان
+
+386
+00:28:45,670 --> 00:28:48,670
+انا فعليا بحسب ال information gain لل attribute
+
+387
+00:28:52,790 --> 00:28:56,270
+تبقى على ال data set اللي موجودة عندها لأن ال
+
+388
+00:28:56,270 --> 00:28:59,750
+summation على عدد ال partitions ال summation ال V
+
+389
+00:28:59,750 --> 00:29:02,830
+زي ما قلنا قبل شوية هيها اللي هي عدد ال partitions
+
+390
+00:29:02,830 --> 00:29:08,650
+اللي عندها number of partitions حجم
+
+391
+00:29:08,650 --> 00:29:12,850
+ال partition لل data set عدد عناصر ال partition
+
+392
+00:29:12,850 --> 00:29:16,290
+لعدد عناصر ال data set ratio احتمال ولا لأ
+
+393
+00:29:16,290 --> 00:29:21,880
+probability ضرب ال informationلل data set أو لل
+
+394
+00:29:21,880 --> 00:29:25,700
+partition اللي موجودة عندي يعني مع كل partition
+
+395
+00:29:25,700 --> 00:29:30,060
+انا بجسمه هروح احسب ال information لل data set
+
+396
+00:29:30,060 --> 00:29:33,120
+لجديدة و هذه مبدأ ال divide and conquer زي ما قلنا
+
+397
+00:29:33,120 --> 00:29:36,300
+سابقا في الالجو في الخصائص اللي موجودة هنا خلينا
+
+398
+00:29:36,300 --> 00:29:41,780
+ناخد ال age ال age بجسم ال data set اللي عندي ل
+
+399
+00:29:41,780 --> 00:29:45,280
+three partitions بناء على مين؟ بناء على ان عندي
+
+400
+00:29:45,280 --> 00:29:51,120
+youthو middle age و senior فش عني غيرهم هايهم ال
+
+401
+00:29:51,120 --> 00:29:56,100
+different elements اللي موجودين عندى الآن إيش هروح
+
+402
+00:29:56,100 --> 00:30:08,600
+أساوي بهمش هروح أشتغل التالي هعمل جدول بسيط
+
+403
+00:30:08,600 --> 00:30:11,680
+إيش
+
+404
+00:30:11,680 --> 00:30:15,570
+ال values اللي موجودة عندى هناطب انا بتكلم على ال
+
+405
+00:30:15,570 --> 00:30:26,170
+age الان ك attribute ال value تبعتي جدش
+
+406
+00:30:26,170 --> 00:30:32,330
+منهم yes جدش منهم no و بدى اروح احسب ال intro بيه
+
+407
+00:30:32,330 --> 00:30:35,610
+تبعت ال yes و ال no
+
+408
+00:30:41,850 --> 00:30:47,750
+متفقين الآن احنا في عيننا قولنا three elements او
+
+409
+00:30:47,750 --> 00:30:59,670
+three different values موجودة عندى الأولى يث هى
+
+410
+00:30:59,670 --> 00:31:07,030
+واحدة يث تنتين تلاتة اربعة خمسة
+
+411
+00:31:10,000 --> 00:31:17,900
+no بتعد ال yes الان واحدة تنتين تلاتة تلاتة yes
+
+412
+00:31:17,900 --> 00:31:21,380
+وتنتين
+
+413
+00:31:21,380 --> 00:31:27,740
+no الان المطلوب مني هو فعليا انا عند خمسة yes
+
+414
+00:31:27,740 --> 00:31:32,760
+العدد هم هتوزع تلاتة و اتنين مقلوب مني احسب I
+
+415
+00:31:32,760 --> 00:31:38,540
+تلاتة و اتنينالـ Entropy للـ Yes والـ No تبع لل
+
+416
+00:31:38,540 --> 00:31:41,540
+class اللي موجود عندهم تعالى نشوف البعد هيك ال
+
+417
+00:31:41,540 --> 00:31:47,300
+middle age هي واحدة واحدة middle age اتنين تلاتة
+
+418
+00:31:47,300 --> 00:31:58,720
+اربعة اربعة middle age توزعتهم
+
+419
+00:31:58,720 --> 00:32:09,170
+واحدة yes تنتين yes تلاتة yesأربعة yes أربعة yes
+
+420
+00:32:09,170 --> 00:32:12,830
+هم كله عددهم أربعة فكم منهم أربعة yes معناته صفر
+
+421
+00:32:12,830 --> 00:32:18,930
+منهم no صحيح الكلام هيك و هيك صار في عندي أربعة و
+
+422
+00:32:18,930 --> 00:32:26,250
+zero بالنسبة لل senior الآن
+
+423
+00:32:26,250 --> 00:32:30,290
+صار في عندي تلاتة عفوا احنا قولنا هنا خمسة وهنا
+
+424
+00:32:30,290 --> 00:32:34,970
+أربعة مجموحهم تسعة جدش باقي عندي جدش باقي عندي
+
+425
+00:32:39,130 --> 00:32:43,930
+خمسة ليش؟ لأن ال data set حجمها 14 element فصار في
+
+426
+00:32:43,930 --> 00:32:47,070
+عندي تسعة rows موجودين مع ال value الأولى و
+
+427
+00:32:47,070 --> 00:32:50,070
+التانية لأنه ماتنساش و ماتنسيش أنه أنا قلت بدي
+
+428
+00:32:50,070 --> 00:32:55,270
+أجسم ال data set ل N من ال partition ال H بتجسم ال
+
+429
+00:32:55,270 --> 00:32:59,710
+data set اللي هي ال 14 row ل 3 partitions أنا حصلت
+
+430
+00:32:59,710 --> 00:33:04,610
+خمسة مع الياث مع الياثو 4 rows مع ال middle و خمسة
+
+431
+00:33:04,610 --> 00:33:08,430
+هم الباقين هيكونوا مع مين مع ال senior تعالى نعد
+
+432
+00:33:08,430 --> 00:33:14,270
+مع ال senior senior
+
+433
+00:33:14,270 --> 00:33:21,250
+yes senior yes no
+
+434
+00:33:22,980 --> 00:33:28,620
+senior yes وهي قيمة الأخيرة yes معناته انا عندي مع
+
+435
+00:33:28,620 --> 00:33:35,160
+ال senior تنتين yes و تلاتة no اتنين و تلاتة
+
+436
+00:33:35,160 --> 00:33:41,780
+وبالتالي انا لازم احسب ال entropy لتنين و تلاتة ال
+
+437
+00:33:41,780 --> 00:33:46,340
+entropy هاي او ال information gain كيف حسبناها
+
+438
+00:33:46,340 --> 00:33:51,320
+قانونها معروف سابقا ماتنسوش او ماتنسوش مطلقا عبارة
+
+439
+00:33:51,320 --> 00:33:58,630
+عن ناقصفي مجموع ال probabilities للبي في log ال
+
+440
+00:33:58,630 --> 00:34:04,270
+binary log للبي ال probability وال I تسوى من واحد
+
+441
+00:34:04,270 --> 00:34:13,010
+لعدد ال classes ساميه C الآن
+
+442
+00:34:14,700 --> 00:34:17,760
+ال data set هاي مش احنا قولنا divide and conquer
+
+443
+00:34:17,760 --> 00:34:21,940
+جسمنا ال data set والان بدي اعيد نفس الشغل عليها
+
+444
+00:34:21,940 --> 00:34:25,000
+نفس الحسبة فبرحت انا بدي احسب ال information gain
+
+445
+00:34:25,000 --> 00:34:30,520
+لهاي وهد اللي المفروض تساوي ناقص مضروبة فيه تلاتة
+
+446
+00:34:30,520 --> 00:34:37,040
+على خمسة في log أيوة جداش في ال binary log صحيح
+
+447
+00:34:37,040 --> 00:34:43,800
+تلاتة على خمسة زائد اتنين على خمسة في logاثنين على
+
+448
+00:34:43,800 --> 00:34:49,600
+خمسة هذه ال intro بالأولى هذه جمعة الخير صفر ليش
+
+449
+00:34:49,600 --> 00:34:59,080
+ناقص اربعة على خمسة اربعة على خمسة اربعة على خمسة
+
+450
+00:34:59,080 --> 00:35:07,160
+اربعة على اربعة sorry اربعة على اربعة في log ال
+
+451
+00:35:07,160 --> 00:35:13,210
+binary للاربعة على اربعة اللي هي واحد صفرزائد صفر
+
+452
+00:35:13,210 --> 00:35:21,090
+على أربعة في log صفر على أربعة ومن ثم القيمة هذه
+
+453
+00:35:21,090 --> 00:35:24,430
+هتروح عندي وهذه هي نفس اللي فوق بس مع تغيير ال
+
+454
+00:35:24,430 --> 00:35:30,110
+terms اللي موجودة عندها بنفس الحسبة وبالتالي أنا
+
+455
+00:35:30,110 --> 00:35:33,450
+حسبتها في الجدول فطلعت معايا هيها
+
+456
+00:35:39,160 --> 00:35:43,280
+خلصت؟ لأ لسه مخلصش بقال علي خطوة واحدة عشان اعرف
+
+457
+00:35:43,280 --> 00:35:51,340
+ان ال gain تبعت ال age جديش بدي اروح اقوله ال gain
+
+458
+00:35:51,340 --> 00:35:56,140
+تبعت ال data set اللي كلها اللي هي جمع الاي للتسعة
+
+459
+00:35:56,140 --> 00:36:02,380
+وخمسة حسبناها point تسعة اربعة صفر في ال slide
+
+460
+00:36:02,380 --> 00:36:03,020
+السادق هي
+
+461
+00:36:06,330 --> 00:36:10,670
+لما حسبناها هان لكل ال data set ال gain او ال
+
+462
+00:36:10,670 --> 00:36:13,470
+intro لكل ال data set حسبت الان ال intro ل ال age
+
+463
+00:36:13,470 --> 00:36:19,210
+هيها الان الخطوة اللي هشتغل عليها انه بدي اجيب ال
+
+464
+00:36:19,210 --> 00:36:23,510
+information gain لكل واحد فيهم طبعا المفروض انا
+
+465
+00:36:23,510 --> 00:36:27,350
+ممكن اشتغل الخطوة هاي تباعا اجرح اقوله مباشرة الان
+
+466
+00:36:27,350 --> 00:36:35,550
+ال information gain لل age تساوي
+
+467
+00:36:36,360 --> 00:36:40,700
+أو الـ Gain للـ Age تساوي ال Entropy لكل ال data
+
+468
+00:36:40,700 --> 00:36:46,120
+set نقص ال Entropy تبع ال Age ال
+
+469
+00:36:46,120 --> 00:36:53,940
+Gain لل Age تساوي ال Entropy لل data set 0.94 ناقص
+
+470
+00:36:53,940 --> 00:37:02,900
+ال Entropy ل ال Age اللي موجود عندى 6.94تساوي طبعا
+
+471
+00:37:02,900 --> 00:37:06,620
+ممكن تشتغل الخطوة التالية تشتغل مع ال income بنفس
+
+472
+00:37:06,620 --> 00:37:09,200
+ال concept ال income في عندي برضه .. برضه هان في
+
+473
+00:37:09,200 --> 00:37:12,420
+عندي three different values ال income في عندي
+
+474
+00:37:12,420 --> 00:37:16,340
+three different values high و medium و low
+
+475
+00:37:16,340 --> 00:37:19,840
+توزيعتهم بنفس الكيفية و بحسب ال entropy ل ال yes و
+
+476
+00:37:19,840 --> 00:37:28,780
+ال no و هكذا هى حسبت ال entropy ل ال ..Informat ..
+
+477
+00:37:28,780 --> 00:37:32,880
+لل income ال intro بي ل ال student ال intro بي ل
+
+478
+00:37:32,880 --> 00:37:39,660
+مين ل ال credit rating الآن خطوة تالية هروح رحسب
+
+479
+00:37:39,660 --> 00:37:45,500
+ال information gain او ال gain تبعت ال age و ال
+
+480
+00:37:45,500 --> 00:37:50,660
+gain تبعت هنا في slides مفقودة المفروض انا شكلي
+
+481
+00:37:50,660 --> 00:37:54,420
+نسيها او ما شابه لأ هي نفس ال .. okay بس مش مفصلة
+
+482
+00:37:54,420 --> 00:38:01,550
+فحسبت ال gain لل ageالـ gain للـ age هي
+
+483
+00:38:01,550 --> 00:38:08,250
+عبارة عن الـ entropy لكل ال data 6.94% ناقص ال
+
+484
+00:38:08,250 --> 00:38:13,450
+entropy تبعت ال age اللي هي 694 من الف و هيكون
+
+485
+00:38:13,450 --> 00:38:19,370
+الفرق بينهم 246 من الف و روحت حسبت ال incomeأو ال
+
+486
+00:38:19,370 --> 00:38:25,090
+gain لل income ال gain لل student و ال gain لل
+
+487
+00:38:25,090 --> 00:38:29,630
+credit rating لاحظ ال credit rating اقل ما يمكن
+
+488
+00:38:29,630 --> 00:38:36,270
+اقل اصغر واحدة من العناصر الموجودة عندى اقل
+
+489
+00:38:36,270 --> 00:38:40,830
+واحدة مع ال income مالهاش كان الهاش اقل تأثيرا
+
+490
+00:38:42,420 --> 00:38:47,460
+الفكرة ان انا بدي اروح اخد او بدي اعمل split على
+
+491
+00:38:47,460 --> 00:38:56,160
+ال maximum gain لل attributes مين
+
+492
+00:38:56,160 --> 00:39:05,760
+ال maximum؟ هي لان 244 من 1000 اكبر من اكبر قيمة
+
+493
+00:39:05,760 --> 00:39:09,680
+موجودة فيهم اللي هي هنا مع ال studentوهذا بتديني
+
+494
+00:39:09,680 --> 00:39:12,040
+إشارة إن ممكن ال student تكون هي ال next element
+
+495
+00:39:12,040 --> 00:39:14,920
+اللي أنحمل عليه splitting لكن مش قضيتي في الآخر
+
+496
+00:39:14,920 --> 00:39:26,420
+أنا هاي الآن الآن ال data set هرجعلها ال
+
+497
+00:39:26,420 --> 00:39:30,660
+data set الآن هنعملها partitioning هي ال data set
+
+498
+00:39:30,660 --> 00:39:37,180
+كيف ال partition تبعتي؟ بيبقى إنه قال لي إن ال age
+
+499
+00:39:37,180 --> 00:39:43,030
+هي هتكون الأساسكل الروز المحوطة باللون الأحمر هذه
+
+500
+00:39:43,030 --> 00:39:49,510
+أو بين جثين التبعت اليف هتمثل
+
+501
+00:39:49,510 --> 00:39:56,030
+one data set خمسة
+
+502
+00:39:56,030 --> 00:40:00,950
+روز تمام؟
+
+503
+00:40:00,950 --> 00:40:05,930
+بعد هيك ال middle age لحالهم اللي باللون الأزرق
+
+504
+00:40:05,930 --> 00:40:07,010
+عمالي بحوط عليهم
+
+505
+00:40:15,180 --> 00:40:19,840
+هدولة أربعة .. أربعة وضلوا ال senior العناصر
+
+506
+00:40:19,840 --> 00:40:23,460
+الباقية يعني بين قوسين إن ال data ستة بقى هتنجسم
+
+507
+00:40:23,460 --> 00:40:28,020
+الآن بعد ما أخدت ال route أنا هيها بقول ال age هي
+
+508
+00:40:28,020 --> 00:40:32,220
+الأساس لإن هي صاحبة الأكبر gain هيها فبدي أجسم ال
+
+509
+00:40:32,220 --> 00:40:35,000
+data ستة بقى لل three values اللي موجودة عندي يعني
+
+510
+00:40:35,000 --> 00:40:38,940
+ال youth و ال middle age و ال senior ممتاز
+
+511
+00:40:44,580 --> 00:40:48,980
+جسمناهم هذه ال data set اللى موجودة عندى الآن على
+
+512
+00:40:48,980 --> 00:40:54,480
+السريع شو هروح أساوي هاخد كل data set لان لاحظ ان
+
+513
+00:40:54,480 --> 00:40:56,040
+عمود ال student اختفت
+
+514
+00:40:58,670 --> 00:41:03,170
+عمود ال age اختفت ..عمود ال age اختفت ..الان كل
+
+515
+00:41:03,170 --> 00:41:08,270
+واحدة من ال data set هشتغل عليها بشكل مستقل لحد ما
+
+516
+00:41:08,270 --> 00:41:13,150
+احقق واحد من الشروط التلاتة اما فعليا كل ال
+
+517
+00:41:13,150 --> 00:41:17,690
+attributes او كل ال symbols تمتم لنفس ال classأو
+
+518
+00:41:17,690 --> 00:41:21,290
+ماضلش فيه عندي more attributes أنا جسمها أو ماضلش
+
+519
+00:41:21,290 --> 00:41:24,450
+فيه عنده rows بعد هيك يعني بين جثين حاجة لهان الآن
+
+520
+00:41:24,450 --> 00:41:28,890
+و هشتغل عليها بشكل مستقل هذه الآن new data set
+
+521
+00:41:28,890 --> 00:41:34,490
+هحسبلها information لمين؟ هذه كلها خمس عناصر اتنين
+
+522
+00:41:34,490 --> 00:41:39,330
+و تلاتة هذه ال information اللي اديه كلها ال ID
+
+523
+00:41:39,330 --> 00:41:42,630
+تبعتي I
+
+524
+00:41:43,610 --> 00:41:49,410
+تلا .. اتنين لليس و تلاتة لل no وهذا تساوي سالب في
+
+525
+00:41:49,410 --> 00:41:55,770
+مجموع .. في مجموع او بلاش نحط المجموع هيها اتنين
+
+526
+00:41:55,770 --> 00:42:02,790
+على خمسة في log اتنين على خمسة زائد تلاتة على خمسة
+
+527
+00:42:02,790 --> 00:42:09,060
+في log تلاتة على خمسةهذه المعلومات لكل ال data set
+
+528
+00:42:09,060 --> 00:42:12,940
+هذه as all ممتاز الآن كم attribute موجود عندي؟
+
+529
+00:42:12,940 --> 00:42:16,060
+عندي three different attributes عندي ال income و
+
+530
+00:42:16,060 --> 00:42:19,500
+عندي ال age يعفو ال student و ال credit rating
+
+531
+00:42:19,500 --> 00:42:23,640
+هروح أحسب ال information لمين؟ هروح أبدأ أبني
+
+532
+00:42:23,640 --> 00:42:27,500
+الجدول الآن لل attribute الأول مش اتفقنا هيك هشتغل
+
+533
+00:42:27,500 --> 00:42:31,360
+مع كل جدول على السريع أنا هشتغل بس مع هذه و الخطوة
+
+534
+00:42:31,360 --> 00:42:34,900
+التانية حاطر للباقية حاطر كواقلك الآن
+
+535
+00:42:37,170 --> 00:42:42,950
+مع العمود الأول ال income قلت
+
+536
+00:42:42,950 --> 00:42:49,250
+ال value تبعت ال income بعد هيك في عندي ال yes
+
+537
+00:42:49,250 --> 00:42:55,150
+وعندي ال no وعندي ال intro بلا ال yes و ال no بناء
+
+538
+00:42:55,150 --> 00:42:59,090
+على العدد اللي موجود عندي وبالتالي كام value موجود
+
+539
+00:42:59,090 --> 00:43:05,010
+عندي انا هان عندي low و medium و high هي
+
+540
+00:43:05,010 --> 00:43:05,290
+low
+
+541
+00:43:08,440 --> 00:43:16,120
+medium و high عد العناصر الموجودة مع بعضنا الان مع
+
+542
+00:43:16,120 --> 00:43:24,500
+ال law عندي قيمة واحدة فقط لمين بتنتمي لل yes واحد
+
+543
+00:43:24,500 --> 00:43:33,560
+yes و هنا صفر معناته ال entropy لواحد و صفر اجي
+
+544
+00:43:33,560 --> 00:43:35,780
+ل ال medium medium عندي تنتين
+
+545
+00:43:43,250 --> 00:43:50,310
+واحد yes وواحد no معناته انترو بي لواحد وواحد وضل
+
+546
+00:43:50,310 --> 00:43:53,950
+في عندي height انتين وبينتميوا لنفس ال class
+
+547
+00:43:53,950 --> 00:43:59,710
+معناته صفر واثنين انترو بي لصفر واثنين وذا بذكر ان
+
+548
+00:43:59,710 --> 00:44:03,650
+هاي القانون السابق اللي اعتند عليه حصل بحسب ال
+
+549
+00:44:03,650 --> 00:44:08,810
+gain الآن او بحسب ال information لل attribute اللي
+
+550
+00:44:08,810 --> 00:44:15,860
+موجود عندي من خلالالـ summation كمان مرة عدد ال
+
+551
+00:44:15,860 --> 00:44:21,840
+data set زي ما قلنا جديش جامعة الخير خمسة الان
+
+552
+00:44:21,840 --> 00:44:31,420
+واحد على خمسة في I واحد و صفر زائد هذه ال
+
+553
+00:44:31,420 --> 00:44:40,050
+information اتنين على خمسة في Iواحد و واحد زائد
+
+554
+00:44:40,050 --> 00:44:49,530
+اتنين على خمسة اتنين على خمسة صحيح اتنين على خمسة
+
+555
+00:44:49,530 --> 00:44:58,530
+في ال I صفر
+
+556
+00:44:58,530 --> 00:45:04,690
+و اتنين بحصل على ال information gain اللي موجود
+
+557
+00:45:04,690 --> 00:45:12,160
+عندي هان بعد هيك بقوله ال gainتبعت ال income هتمثل
+
+558
+00:45:12,160 --> 00:45:21,900
+ال ID اللي عندي فوق ناقص ال I لل income اللي
+
+559
+00:45:21,900 --> 00:45:28,380
+موجودة عندها هحسبها و فتالي بحسب لهذه و بحسب لل
+
+560
+00:45:28,380 --> 00:45:31,780
+العناصر
+
+561
+00:45:31,780 --> 00:45:37,640
+اللي موجودة عندى تماملل student بعيد الكرة و لل
+
+562
+00:45:37,640 --> 00:45:41,780
+credit rating و صاحب ال attribute صاحب أكبر gain
+
+563
+00:45:41,780 --> 00:45:46,480
+هو اللي حكون فعليا انا هعتمد وين في ال .. في
+
+564
+00:45:46,480 --> 00:45:49,740
+الرسمة او في decision node التالية حسب الحسبة
+
+565
+00:45:49,740 --> 00:45:54,200
+تبعتي حسبناها سابقا لازم انتوا تكملوها للاخر حسب
+
+566
+00:45:54,200 --> 00:45:57,740
+الحسبة تبعتي ال student حصلت اعلى game ال student
+
+567
+00:45:57,740 --> 00:46:02,680
+تبعتي حصلت اعلى game و بالتالي انا الان هان هصير
+
+568
+00:46:02,680 --> 00:46:07,260
+في عند ال studentهي الـ Internal node الجاية وفيها
+
+569
+00:46:07,260 --> 00:46:13,680
+two different values حقسم ال data set بعد هيك حقسم
+
+570
+00:46:13,680 --> 00:46:16,860
+ال data set تبعا لل nodes اللي موجودة عندي هيك و
+
+571
+00:46:16,860 --> 00:46:20,960
+بهكد صارت كل ال nodes بتنتمي لنفس ال class كل ال
+
+572
+00:46:20,960 --> 00:46:24,620
+samples بتنتمي لنفس ال class فهان بوقف هذه already
+
+573
+00:46:24,620 --> 00:46:28,260
+كلها بتنتمي لنفس ال class فانا وقفت هان ووقفت هان
+
+574
+00:46:28,260 --> 00:46:31,540
+هتكون ال final tree تبعتي طبعا هي الحسبة اللي
+
+575
+00:46:31,540 --> 00:46:36,430
+عندناها مرة تانية انا في الآخرالـ Tree تبعتي أحصل
+
+576
+00:46:36,430 --> 00:46:40,330
+عليها اللي احنا شفناها مسبقا المفروض قبل ما يبدأ
+
+577
+00:46:40,330 --> 00:46:50,130
+بالشغل اللي هي هذه ال income مابينتش عندي لإن
+
+578
+00:46:50,130 --> 00:46:54,770
+فعليا وزنها كان لا يذكر مقارنة بال data set و لما
+
+579
+00:46:54,770 --> 00:46:57,570
+أنا ماضلش عندي rows أو ماضلش عندي sample أروح
+
+580
+00:46:57,570 --> 00:47:01,650
+أجسمها الآن عشان
+
+581
+00:47:02,490 --> 00:47:06,390
+مانطولش عليكم بعد ما حسبنا العناصر اللي موجودة
+
+582
+00:47:06,390 --> 00:47:11,430
+عندها في ال continuous attributes في حالة ال
+
+583
+00:47:11,430 --> 00:47:14,470
+attributes اللي عندك continuous attribute ايش الحل
+
+584
+00:47:14,470 --> 00:47:19,610
+اعمل discretization اعملها categories جسمها لفئات
+
+585
+00:47:19,610 --> 00:47:22,830
+استخدم ال binning و اعطي label لكل bin و اشتغل
+
+586
+00:47:22,830 --> 00:47:28,710
+عليها بتكاشي تشتغل عليك في حل بسيط جدا الحل بيقولك
+
+587
+00:47:28,710 --> 00:47:33,760
+رتب ال data set تبع لل items اللي موجودة عندكرتبت
+
+588
+00:47:33,760 --> 00:47:38,260
+ال items تمام فصارت ال data sorted ان في حال كانت
+
+589
+00:47:38,260 --> 00:47:43,260
+عندي ال age عبارة عن number صار عندي تمنتعش خمسة و
+
+590
+00:47:43,260 --> 00:47:48,780
+عشرين تلاتين سبعة و تلاتين اربعين الان انت بقى
+
+591
+00:47:48,780 --> 00:47:55,500
+تيجي تفحص بين كل two nodes يعني هتاخد
+
+592
+00:47:55,500 --> 00:48:00,200
+ال midpoint اللي بين هدول الاتنين او الأسهل لك
+
+593
+00:48:01,200 --> 00:48:03,600
+فعلاً هي عبارة عن Discretization لكنها Binary
+
+594
+00:48:03,600 --> 00:48:07,780
+Discretization مع الأرقام انت ايش المقارنات تبعتك؟
+
+595
+00:48:07,780 --> 00:48:12,460
+اما هتقوللي أقل إذا قولت أقل من كده فهي أكبر أو
+
+596
+00:48:12,460 --> 00:48:16,340
+تساوي كده إذا قولت أكبر من أكبر من أو تساوي كده
+
+597
+00:48:16,340 --> 00:48:19,280
+فهي أقل من كده عكسها تماما فحكون بشغل عليها مع
+
+598
+00:48:19,280 --> 00:48:23,080
+binary يعني بين جسين بصير باخد decision هان بقوله
+
+599
+00:48:23,080 --> 00:48:30,500
+أقل أو تساوي خمسة وعشرين طب ما هي تمنتعش باجي هان
+
+600
+00:48:33,210 --> 00:48:39,230
+أقل أو تساوي تلاتين معتوا هدول في partitions و
+
+601
+00:48:39,230 --> 00:48:42,190
+هدول في partitions مع ال continuous attributes إذا
+
+602
+00:48:42,190 --> 00:48:45,830
+انت بدك تشتغل مع ال continuous values معناته انت
+
+603
+00:48:45,830 --> 00:48:49,990
+هيكون في عندك too many partitions لحد ما تصل ل
+
+604
+00:48:49,990 --> 00:48:55,300
+best point اللي بتعمل splitيعني هحسب الآن الجسم
+
+605
+00:48:55,300 --> 00:48:58,920
+كده كانت هان و لا لما كانوا تنتين و تلاتة و لما
+
+606
+00:48:58,920 --> 00:49:03,160
+كانوا تلاتة و اتنين و تجرب كلهم و تاخد أعلى gene
+
+607
+00:49:03,160 --> 00:49:06,900
+فيهم لأن في الآخر أنا بدور على ال gene لكل ال data
+
+608
+00:49:06,900 --> 00:49:12,320
+set تبعتي اللي موجودة عندي هان الان هدف الموضوع ال
+
+609
+00:49:12,320 --> 00:49:15,810
+spring لل continuous valuesلكن الـ Information
+
+610
+00:49:15,810 --> 00:49:21,330
+Game دائما بيحاز للـ attributes أو للـ test اللي
+
+611
+00:49:21,330 --> 00:49:25,230
+بيكون فيها two أو فيها many outcomes اللي فيها
+
+612
+00:49:25,230 --> 00:49:30,490
+values كتيرة عشان هي كانت في الأول عندى ال age
+
+613
+00:49:30,490 --> 00:49:33,190
+كانت هي أكثر ال values اللي موجودة جالك ممكن احنا
+
+614
+00:49:33,190 --> 00:49:37,070
+نحل هذه المشكلة و نعتمد أو نحاول نقضي على موضوع
+
+615
+00:49:37,070 --> 00:49:39,930
+انحياز ال values الكتيرة اللي هي موضوع ال gain
+
+616
+00:49:39,930 --> 00:49:43,500
+ratioالـ Gain Ratio فكرتها يا جماعة الخير انه انا
+
+617
+00:49:43,500 --> 00:49:48,240
+بده اروح احسب ال split info احنا سابقا كانت هذه
+
+618
+00:49:48,240 --> 00:49:52,240
+القيمة موجودة عندنا هي عدد عناصر ال partition على
+
+619
+00:49:52,240 --> 00:49:56,200
+.. على كل ال partition في موضوع ال probability لكل
+
+620
+00:49:56,200 --> 00:49:58,660
+ال partition اللي موجودة عندها و بعد ما بحسب ال
+
+621
+00:49:58,660 --> 00:50:02,280
+gain بروح بحط عليها ال split ratio و هيك برضه برجع
+
+622
+00:50:02,280 --> 00:50:07,180
+باخد ال maximum split ratio كذلك في عند ال gain
+
+623
+00:50:07,180 --> 00:50:13,020
+indexبيعتمد على الـ Multi-Valued Attributes بشكل
+
+624
+00:50:13,020 --> 00:50:19,340
+كبير الـ Ched بيعتمد على الـ Chi-Square عشان تحسب
+
+625
+00:50:19,340 --> 00:50:21,420
+الـ Independences أو في موضوع الـ Independences
+
+626
+00:50:21,420 --> 00:50:24,980
+وفي عند الكارت وإلى أخرى أي واحدة منهم أنا أختار
+
+627
+00:50:24,980 --> 00:50:28,580
+لعشان أنا أشتغل مافيش فرق ما بينهم كتير انت حسب ال
+
+628
+00:50:28,580 --> 00:50:32,500
+data set وحسب فهمك ال data set ممكن تختار أي واحدة
+
+629
+00:50:32,500 --> 00:50:36,810
+منهم لكن الأكثر عفواالأكتر استخداما الـ
+
+630
+00:50:36,810 --> 00:50:40,990
+Information Gain ومن ثم الجني أو العكس احنا بهيك
+
+631
+00:50:40,990 --> 00:50:44,190
+بنكون تقريبا خلصنا وضع لعينا one slide خلينا
+
+632
+00:50:44,190 --> 00:50:51,390
+ننهيها الآن رسمت لتري وحصلت على لتري و ال data set
+
+633
+00:50:51,390 --> 00:50:56,290
+تبعت كبيرة و كانت ال depth أو عمق الشجرة تبعت كتير
+
+634
+00:50:56,290 --> 00:51:01,370
+عالية طب ايش الحل؟ هاد احنا بنسميها ال tree هاد ..
+
+635
+00:51:01,370 --> 00:51:06,880
+او بيحصلنا على مرحلة اسمها ال overfittingمشكلة إنه
+
+636
+00:51:06,880 --> 00:51:10,900
+الـTree هذه جابته تماما مع مين؟ مع الـTraining
+
+637
+00:51:10,900 --> 00:51:14,060
+Data اللي أنا بديتها Overfit Fit يا شباب مناسب
+
+638
+00:51:14,060 --> 00:51:19,440
+ولمّا أقول Overfit مناسب بدرجة كبيرة لمين؟ للحالة
+
+639
+00:51:19,440 --> 00:51:23,240
+اللي هذه، يعني بين جوسينت وكأنه الشجرة هذه زبطت
+
+640
+00:51:23,240 --> 00:51:27,320
+حالها تماما مع الـDataset طب غير هي كانت لأ بتديني
+
+641
+00:51:27,320 --> 00:51:31,700
+مشاكل إيش الحل؟ الـOverfitting مع الـBinary Tree
+
+642
+00:51:31,700 --> 00:51:34,620
+أو مع الـDecision Tree بيعني Too Many Branches
+
+643
+00:51:37,860 --> 00:51:41,240
+ممكن يعكس الـ outlayer لو كان في عندي outlayer
+
+644
+00:51:41,240 --> 00:51:44,620
+موجودة عندي هان و بديني بور accuracy for unseen
+
+645
+00:51:44,620 --> 00:51:48,580
+هذا المفهوم ال outfitting ال overfitting ال
+
+646
+00:51:48,580 --> 00:51:51,880
+overfitting يعني اتنا سوات اكثر مع ال data set
+
+647
+00:51:51,880 --> 00:51:56,190
+اللي انا عملت عليها trainingو غير صالحة للـ .. للـ
+
+648
+00:51:56,190 --> 00:51:59,150
+correct prediction مع الـ unseen إيش الحل؟ في عندي
+
+649
+00:51:59,150 --> 00:52:02,150
+two approaches طبعا انت مش هتشتغل ولا واحد فيهم
+
+650
+00:52:02,150 --> 00:52:05,410
+هيتم الشغل تلقائي المفروض من خلال الـ python pre
+
+651
+00:52:05,410 --> 00:52:09,090
+-pruning انه انا فعليا ال attributes أو أدور على
+
+652
+00:52:09,090 --> 00:52:11,190
+ال attributes أو ال weak attribute و أخلص منها من
+
+653
+00:52:11,190 --> 00:52:19,550
+البداية انه .. ان اربط بناء الشجرة بالإيه؟ do not
+
+654
+00:52:19,550 --> 00:52:21,530
+split a node if ..
+
+655
+00:52:26,240 --> 00:52:28,680
+مالهاش علاقة كتير بالـ threshold الموجود يعني بين
+
+656
+00:52:28,680 --> 00:52:32,040
+جوسين أروح أحط minimum للـ threshold مش احنا قولنا
+
+657
+00:52:32,040 --> 00:52:36,500
+ال gain .. المفروض .. ال gain تبعتي أعلى gain طب
+
+658
+00:52:36,500 --> 00:52:38,780
+مابديش بس أحط gain أعلى gain و أروح أعمل .. و ألخ
+
+659
+00:52:38,780 --> 00:52:42,420
+.. و ألخم حالي في كل الحسبات لأ كمان هدول اللي تحت
+
+660
+00:52:42,420 --> 00:52:46,260
+اللي بدون gain قليلة من أول مرة بده أروح كلهم بدي
+
+661
+00:52:46,260 --> 00:52:50,160
+أعملهم neglect و مابديش إياهم طبعا هاي حيكون في
+
+662
+00:52:50,160 --> 00:52:53,400
+عندي تحدي كيف ممكن أختار ال threshold الصحيحة ال
+
+663
+00:52:53,400 --> 00:52:58,310
+boss browning بعد ما أنابنيت الشجرة بالكامل أروح
+
+664
+00:52:58,310 --> 00:53:03,150
+أبدأ أجشبر فيها بعبرة لإني أروح أفحص مين الأكثر
+
+665
+00:53:03,150 --> 00:53:06,970
+rows أو أكثر branches مستخدمة هي اللي أبقيها و
+
+666
+00:53:06,970 --> 00:53:11,450
+الأقل استخداما أخلص منها حسب ال data set اللي
+
+667
+00:53:11,450 --> 00:53:15,430
+موجود عندى أخر خطوة أو أخر slide في موضوع في موضوع
+
+668
+00:53:15,430 --> 00:53:18,630
+كي بدى أستدعيها الخطوات السابقة في ال python نفسها
+
+669
+00:53:18,630 --> 00:53:22,590
+from sklearn.tree import decision tree classifier
+
+670
+00:53:24,140 --> 00:53:27,880
+الموديل الـ Decision Tree Classifier عملت له fit
+
+671
+00:53:27,880 --> 00:53:31,720
+قلت له و هذه الجزئية في السطر هذا بتنبنى الشجرة
+
+672
+00:53:31,720 --> 00:53:36,500
+الآن ال
+
+673
+00:53:36,500 --> 00:53:39,340
+sample test نفسها لان شغالة نفسي بدا تست معاكم من
+
+674
+00:53:39,340 --> 00:53:44,060
+البداية جربتها مع ال kenia sniper وجربتها معالنايف
+
+675
+00:53:44,060 --> 00:53:48,840
+بايسين اروح تعمل ال test و هنحددني setosa بكل
+
+676
+00:53:48,840 --> 00:53:53,600
+تأكيد وبهيك بنكون احنا فعليا انتهينا من موضوع ال
+
+677
+00:53:53,600 --> 00:53:57,040
+decision tree لمحاضرتنا اليوم المطلوب بينكوا
+
+678
+00:53:57,040 --> 00:53:59,500
+تجربوا يا جماعة الخير في عندنا different data set
+
+679
+00:53:59,500 --> 00:54:02,780
+موجودة في ال slide سابقا جربوا الكلام هذا عليها و
+
+680
+00:54:02,780 --> 00:54:05,000
+جربوا الكلام عليها هذا كلام عليها يعني بينجو سين
+
+681
+00:54:05,000 --> 00:54:08,470
+هذا الكلام مش هتتقنوه من مرة و تنتين و تلاتةالشغل
+
+682
+00:54:08,470 --> 00:54:12,130
+التاني اللي بدي اياها منكوا بعد تجريب العمل يبدو
+
+683
+00:54:12,130 --> 00:54:15,730
+تعتبروها ك assignment عليكم الآن تبدو تروح تفكروا
+
+684
+00:54:15,730 --> 00:54:18,570
+او تدورولي كيف ممكن انا اذا كانت هذه عبارة عن ال
+
+685
+00:54:18,570 --> 00:54:21,930
+tree بعد ما انا عملتلها فت هل في مجال ارسم ال tree
+
+686
+00:54:21,930 --> 00:54:25,690
+تبعت بال بايثون اه في مجال وهذه متروكة لكم والسلام
+
+687
+00:54:25,690 --> 00:54:27,470
+عليكم ورحمة الله وبركاته
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/URknbds3fEY_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/URknbds3fEY_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..5b2172bfd87d652043bbf1b0bd2f4adc0835ed71
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/URknbds3fEY_raw.json
@@ -0,0 +1 @@
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{"start": 871.87, "end": 872.25, "word": " لل", "probability": 0.85205078125}, {"start": 872.25, "end": 872.75, "word": " attributes", "probability": 0.89208984375}, {"start": 872.75, "end": 873.43, "word": " الموجودة،", "probability": 0.855029296875}, {"start": 873.43, "end": 873.61, "word": " بدي", "probability": 0.6962890625}, {"start": 873.61, "end": 873.89, "word": " أرجع", "probability": 0.9466145833333334}, {"start": 873.89, "end": 874.19, "word": " معاك", "probability": 0.96630859375}, {"start": 874.19, "end": 874.49, "word": " كمان", "probability": 0.9796549479166666}, {"start": 874.49, "end": 874.95, "word": " مرة", "probability": 0.98583984375}, {"start": 874.95, "end": 876.31, "word": " عفوا", "probability": 0.8098958333333334}], "temperature": 1.0}, {"id": 36, "seek": 90078, "start": 877.28, "end": 900.78, "text": "no remaining attributes او خلصت كل ال attributes اللي عندي او فعليا ماضلش عندي samples موجودة بدي ارجع معاك كمان مرهان انا الان هاتفقنا ان ال age هو اول واحد خلصت من ال middle age انا ايش بقي عندي بقي عندي ال young ال youth", "tokens": [1771, 8877, 17212, 1975, 2407, 16490, 1211, 9381, 2655, 28242, 2423, 17212, 13672, 1829, 18871, 16254, 1975, 2407, 6156, 3615, 20292, 995, 19446, 11242, 1211, 8592, 18871, 16254, 10938, 3714, 29245, 23328, 3660, 4724, 16254, 1975, 47341, 3615, 20449, 995, 4117, 9122, 2304, 7649, 3714, 2288, 3224, 7649, 1975, 8315, 2423, 7649, 8032, 9307, 5172, 4587, 8315, 16472, 2423, 3205, 31439, 1975, 12610, 36764, 24401, 16490, 1211, 9381, 2655, 9154, 2423, 2808, 3205, 1975, 8315, 1975, 1829, 8592, 4724, 38436, 18871, 16254, 4724, 38436, 18871, 16254, 2423, 2037, 2423, 7503], "avg_logprob": -0.18990384680884226, "compression_ratio": 1.7628865979381443, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 877.28, "end": 877.54, "word": "no", "probability": 0.251708984375}, {"start": 877.54, "end": 877.94, "word": " remaining", "probability": 0.84716796875}, {"start": 877.94, "end": 878.64, "word": " attributes", 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decision و أحدد من ال test node اللي موجود عندي الأولى هسميها ال expected information أو ال entropy وهي لكل ال data set اللي موجودة عندي هنا شو يعني؟", "tokens": [6027, 39184, 8736, 2310, 24976, 39184, 6743, 2423, 39184, 37777, 15844, 2423, 413, 15844, 28242, 8736, 2310, 6055, 3555, 3615, 2423, 1412, 992, 13672, 1829, 3714, 29245, 23328, 3660, 4724, 28820, 4724, 3794, 41193, 3660, 41850, 8978, 18871, 16254, 6055, 1211, 2655, 6225, 2304, 20292, 9307, 11331, 3794, 16758, 10632, 8032, 25957, 1211, 11296, 6225, 8592, 7649, 5551, 9778, 3215, 2423, 3537, 4032, 5551, 24401, 3215, 9154, 2423, 1500, 9984, 13672, 1829, 3714, 29245, 23328, 18871, 16254, 16247, 12610, 7578, 8032, 38251, 1829, 11296, 2423, 5176, 1589, 34051, 2423, 30867, 37037, 1829, 5296, 28820, 2423, 1412, 992, 13672, 1829, 3714, 29245, 23328, 3660, 18871, 16254, 34105, 13412, 2407, 37495, 22653, 22807], "avg_logprob": -0.18777902038501842, "compression_ratio": 1.7738095238095237, "no_speech_prob": 5.960464477539063e-08, "words": 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ل ال probability ل ال class اللي موجود عندى و زي ما بقوله بال .. بال .. بال ..", "tokens": [6027, 7649, 37495, 22653, 1975, 12610, 13412, 17082, 37977, 6156, 3615, 20292, 995, 1975, 8315, 8032, 3794, 45865, 11296, 8032, 32887, 5016, 1975, 5016, 35457, 2423, 8482, 5296, 28820, 1508, 1975, 2407, 49374, 10874, 12984, 9957, 8032, 5016, 35457, 2423, 30867, 39896, 6225, 3555, 9640, 3660, 18871, 11331, 33546, 1211, 4386, 6225, 3555, 9640, 3660, 18871, 3714, 7435, 2304, 45367, 11331, 33546, 1211, 48812, 25513, 2423, 8482, 5296, 28820, 1508, 8978, 2423, 41473, 32674, 1975, 2407, 2423, 17434, 3565, 5296, 2423, 8482, 5296, 2423, 1508, 13672, 1829, 3714, 29245, 23328, 43242, 7578, 4032, 30767, 1829, 19446, 4724, 39648, 3224, 20666, 4386, 20666, 4386, 20666, 4386], "avg_logprob": -0.1954599069255703, "compression_ratio": 1.8789237668161436, "no_speech_prob": 1.7881393432617188e-07, "words": [{"start": 1274.5900000000001, "end": 1275.41, "word": "الان", "probability": 0.662353515625}, {"start": 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اللي بعد هيك بدي اروح لكل attribute A احاول فعليا هيجسم ال data set لمجموعة من ال partitions جداش عدد ال V هذه او جداش عدد ال partitions بعدد ال distinct values اللي موجودة عندى فيه ال attribute", "tokens": [3555, 45340, 12984, 6027, 7251, 2655, 11242, 5016, 9673, 4587, 9640, 9122, 2304, 7649, 13412, 2407, 10632, 8032, 29399, 4587, 1211, 5296, 19528, 12984, 6027, 20666, 2655, 5172, 9381, 26895, 16472, 13412, 16606, 21984, 37279, 6027, 7578, 33962, 9566, 2407, 3660, 13672, 1829, 39182, 39896, 4117, 4724, 16254, 1975, 32887, 5016, 5296, 28820, 19667, 316, 1975, 5016, 995, 12610, 6156, 3615, 20292, 995, 39896, 7435, 38251, 2423, 1412, 992, 32767, 7435, 2304, 2407, 27884, 9154, 2423, 644, 2451, 10874, 3215, 33599, 6225, 3215, 3215, 2423, 691, 29538, 1975, 2407, 10874, 3215, 33599, 6225, 3215, 3215, 2423, 644, 2451, 4724, 22488, 3215, 2423, 10644, 4190, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 7578, 8978, 3224, 2423, 19667], "avg_logprob": -0.12900640974696884, "compression_ratio": 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{"start": 1501.96, "end": 1503.5, "word": " حجم", "probability": 0.98681640625}, {"start": 1503.5, "end": 1503.62, "word": " ال", "probability": 0.978515625}, {"start": 1503.62, "end": 1503.8, "word": " data", "probability": 0.97265625}, {"start": 1503.8, "end": 1504.1, "word": " set", "probability": 0.96142578125}, {"start": 1504.1, "end": 1504.28, "word": " كل", "probability": 0.89990234375}, {"start": 1504.28, "end": 1504.66, "word": " هجدش", "probability": 0.71435546875}, {"start": 1504.66, "end": 1504.76, "word": " يا", "probability": 0.30517578125}, {"start": 1504.76, "end": 1504.94, "word": " جماعة", "probability": 0.9913736979166666}, {"start": 1504.94, "end": 1505.28, "word": " الخير", "probability": 0.983642578125}, {"start": 1505.28, "end": 1505.94, "word": " 14", "probability": 0.460205078125}, {"start": 1505.94, "end": 1507.04, "word": " عدد", "probability": 0.9835611979166666}, {"start": 1507.04, "end": 1507.16, "word": " ال", "probability": 0.98291015625}, {"start": 1507.16, "end": 1507.44, "word": " yes", "probability": 0.9150390625}, {"start": 1507.44, "end": 1507.96, "word": " 9", "probability": 0.57373046875}, {"start": 1507.96, "end": 1508.9, "word": " معناته", "probability": 0.861328125}, {"start": 1508.9, "end": 1509.04, "word": " ال", "probability": 0.90625}, {"start": 1509.04, "end": 1509.48, "word": " probability", "probability": 0.94580078125}, {"start": 1509.48, "end": 1510.18, "word": " تبعتها", "probability": 0.9678955078125}, {"start": 1510.18, "end": 1510.58, "word": " 9", "probability": 0.93408203125}, {"start": 1510.58, "end": 1510.82, "word": " على", "probability": 0.56201171875}, {"start": 1510.82, "end": 1511.28, "word": " 14", "probability": 0.98681640625}], "temperature": 1.0}, {"id": 63, "seek": 152807, "start": 1513.57, "end": 1528.07, "text": "الـ Probability للـ Yes 9 على 14 طب عدد الـ No بجيتها 5 5 على 14 هي الاحتمالية تبعتها 5 على 14 وبهيك أنا حصلت على أول خطوة", "tokens": [6027, 39184, 8736, 2310, 24976, 39184, 1079, 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انا اشتغل عليها الان ان انا بدروح احسب ال information او ال entropy تبعتي بالمعادلة التالية ال information هنرمزلها لل I لل data set تبعتي تساوي تساوي", "tokens": [6027, 20292, 39896, 6225, 28480, 2655, 2423, 8482, 6055, 3555, 34268, 5296, 39184, 5359, 13672, 1829, 3714, 29245, 23328, 3660, 18871, 16254, 13672, 1829, 39896, 2423, 8482, 24976, 2086, 4032, 2423, 8482, 24976, 572, 33962, 9566, 2407, 3660, 16712, 6027, 10632, 13672, 1829, 9673, 5172, 32887, 11242, 16472, 1975, 8315, 1975, 8592, 2655, 17082, 1211, 25894, 11296, 2423, 7649, 16472, 1975, 8315, 47525, 32887, 5016, 1975, 5016, 35457, 2423, 1589, 1975, 2407, 2423, 30867, 6055, 3555, 3615, 31371, 20666, 2304, 3615, 18513, 37977, 16712, 6027, 10632, 2423, 1589, 8032, 1863, 2288, 2304, 11622, 1211, 11296, 24976, 286, 24976, 1412, 992, 6055, 3555, 3615, 31371, 6055, 3794, 995, 45865, 6055, 3794, 995, 45865], "avg_logprob": -0.16731195112245273, "compression_ratio": 1.9868995633187774, "no_speech_prob": 5.960464477539063e-08, 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هنا", "probability": 0.1317138671875}, {"start": 2267.56, "end": 2267.72, "word": " في", "probability": 0.81396484375}, {"start": 2267.72, "end": 2268.1, "word": " slides", "probability": 0.783203125}, {"start": 2268.1, "end": 2268.84, "word": " مفقودة", "probability": 0.831103515625}, {"start": 2268.84, "end": 2269.38, "word": " المفروض", "probability": 0.96630859375}, {"start": 2269.38, "end": 2270.0, "word": " انا", "probability": 0.824951171875}, {"start": 2270.0, "end": 2270.66, "word": " شكلي", "probability": 0.78955078125}, {"start": 2270.66, "end": 2271.2, "word": " نسيها", "probability": 0.9197998046875}, {"start": 2271.2, "end": 2271.56, "word": " او", "probability": 0.897705078125}, {"start": 2271.56, "end": 2271.68, "word": " ما", "probability": 0.53369140625}, {"start": 2271.68, "end": 2272.06, "word": " شابه", "probability": 0.8138020833333334}, {"start": 2272.06, "end": 2272.24, "word": " لأ", "probability": 0.829833984375}, {"start": 2272.24, "end": 2272.38, "word": " هي", "probability": 0.81640625}, {"start": 2272.38, "end": 2272.6, "word": " نفس", "probability": 0.996337890625}, {"start": 2272.6, "end": 2272.74, "word": " ال", "probability": 0.67822265625}, {"start": 2272.74, "end": 2272.9, "word": " ..", "probability": 0.69580078125}, {"start": 2272.9, "end": 2273.24, "word": " okay", "probability": 0.5830078125}, {"start": 2273.24, "end": 2273.62, "word": " بس", "probability": 0.951904296875}, {"start": 2273.62, "end": 2273.78, "word": " مش", "probability": 0.9853515625}, {"start": 2273.78, "end": 2274.42, "word": " مفصلة", "probability": 0.961181640625}, {"start": 2274.42, "end": 2275.94, "word": " فحسبت", "probability": 0.9422607421875}, {"start": 2275.94, "end": 2276.06, "word": " ال", "probability": 0.9755859375}, {"start": 2276.06, "end": 2276.3, "word": " gain", "probability": 0.9609375}, {"start": 2276.3, "end": 2276.46, "word": " لل", "probability": 0.62451171875}, {"start": 2276.46, "end": 2276.94, "word": " age", "probability": 0.91015625}], "temperature": 1.0}, {"id": 92, "seek": 229815, "start": 2277.33, "end": 2298.15, "text": "الـ gain للـ age هي عبارة عن الـ entropy لكل ال data 6.94% ناقص ال entropy تبعت ال age اللي هي 694 من الف و هيكون الفرق بينهم 246 من الف و روحت حسبت ال income", "tokens": [6027, 39184, 6052, 24976, 39184, 3205, 39896, 6225, 3555, 9640, 3660, 18871, 2423, 39184, 30867, 5296, 28820, 2423, 1412, 1386, 13, 27032, 4, 8717, 995, 4587, 9381, 2423, 30867, 6055, 3555, 34268, 2423, 3205, 13672, 1829, 39896, 1386, 27032, 9154, 27188, 4032, 39896, 30544, 27188, 2288, 4587, 49374, 16095, 4022, 21, 9154, 27188, 4032, 12602, 2407, 33753, 11331, 35457, 2655, 2423, 5742], "avg_logprob": -0.24813987527574813, "compression_ratio": 1.475, "no_speech_prob": 0.0, "words": [{"start": 2277.33, "end": 2277.57, "word": "الـ", "probability": 0.4918212890625}, {"start": 2277.57, "end": 2277.75, "word": " gain", "probability": 0.223388671875}, {"start": 2277.75, "end": 2277.95, "word": " للـ", "probability": 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"text": "أو ال gain لل income ال gain لل student و ال gain لل credit rating لاحظ ال credit rating اقل ما يمكن اقل اصغر واحدة من العناصر الموجودة عندى اقل واحدة مع ال income مالهاش كان الهاش اقل تأثيرا", "tokens": [10721, 2407, 2423, 6052, 24976, 5742, 2423, 6052, 24976, 3107, 4032, 2423, 6052, 24976, 5397, 10990, 20193, 5016, 19913, 2423, 5397, 10990, 1975, 4587, 1211, 19446, 7251, 43020, 1975, 4587, 1211, 1975, 9381, 17082, 2288, 36764, 24401, 3660, 9154, 18863, 1863, 33546, 2288, 9673, 29245, 23328, 3660, 43242, 7578, 1975, 4587, 1211, 36764, 24401, 3660, 20449, 2423, 5742, 3714, 6027, 3224, 33599, 25961, 2423, 3224, 33599, 1975, 4587, 1211, 6055, 10721, 12984, 13546, 995], "avg_logprob": -0.3170833373069763, "compression_ratio": 1.7515151515151515, "no_speech_prob": 2.2649765014648438e-06, "words": [{"start": 2299.01, "end": 2299.27, "word": "أو", "probability": 0.534271240234375}, {"start": 2299.27, "end": 2299.37, "word": " ال", "probability": 0.5361328125}, {"start": 2299.37, "end": 2300.21, "word": " gain", "probability": 0.35107421875}, {"start": 2300.21, "end": 2300.57, "word": " لل", "probability": 0.79052734375}, {"start": 2300.57, "end": 2301.07, "word": " income", "probability": 0.77490234375}, {"start": 2301.07, "end": 2301.77, "word": " ال", "probability": 0.35595703125}, {"start": 2301.77, "end": 2302.05, "word": " gain", "probability": 0.43359375}, {"start": 2302.05, "end": 2303.27, "word": " لل", "probability": 0.8544921875}, {"start": 2303.27, "end": 2303.85, "word": " student", "probability": 0.92529296875}, {"start": 2303.85, "end": 2304.45, "word": " و", "probability": 0.35400390625}, {"start": 2304.45, "end": 2304.57, "word": " ال", "probability": 0.6826171875}, {"start": 2304.57, "end": 2304.89, "word": " gain", "probability": 0.9169921875}, {"start": 2304.89, "end": 2305.09, "word": " لل", "probability": 0.79345703125}, {"start": 2305.09, "end": 2305.51, "word": " credit", "probability": 0.90966796875}, {"start": 2305.51, "end": 2306.15, "word": " rating", "probability": 0.95849609375}, {"start": 2306.15, "end": 2306.55, "word": " لاحظ", "probability": 0.7714029947916666}, {"start": 2306.55, "end": 2306.73, "word": " ال", "probability": 0.62841796875}, {"start": 2306.73, "end": 2307.19, "word": " credit", "probability": 0.9599609375}, {"start": 2307.19, "end": 2307.97, "word": " rating", "probability": 0.97802734375}, {"start": 2307.97, "end": 2309.15, "word": " اقل", "probability": 0.75927734375}, {"start": 2309.15, "end": 2309.27, "word": " ما", "probability": 0.86181640625}, {"start": 2309.27, "end": 2309.63, "word": " يمكن", "probability": 0.958984375}, {"start": 2309.63, "end": 2309.95, "word": " اقل", "probability": 0.830078125}, {"start": 2309.95, "end": 2310.27, "word": " اصغر", "probability": 0.963623046875}, {"start": 2310.27, "end": 2310.53, "word": " واحدة", "probability": 0.984375}, {"start": 2310.53, "end": 2310.77, "word": " من", "probability": 0.705078125}, {"start": 2310.77, "end": 2312.55, "word": " العناصر", "probability": 0.885498046875}, {"start": 2312.55, "end": 2313.03, "word": " الموجودة", "probability": 0.8785400390625}, {"start": 2313.03, "end": 2313.23, "word": " عندى", "probability": 0.546875}, {"start": 2313.23, "end": 2316.27, "word": " اقل", "probability": 0.5982259114583334}, {"start": 2316.27, "end": 2316.57, "word": " واحدة", "probability": 0.888671875}, {"start": 2316.57, "end": 2316.89, "word": " مع", "probability": 0.5546875}, {"start": 2316.89, "end": 2317.05, "word": " ال", "probability": 0.93212890625}, {"start": 2317.05, "end": 2317.45, "word": " income", "probability": 0.97998046875}, {"start": 2317.45, "end": 2319.21, "word": " مالهاش", "probability": 0.717681884765625}, {"start": 2319.21, "end": 2319.39, "word": " كان", "probability": 0.9375}, {"start": 2319.39, "end": 2319.69, "word": " الهاش", "probability": 0.6494140625}, {"start": 2319.69, "end": 2320.33, "word": " اقل", "probability": 0.744140625}, {"start": 2320.33, "end": 2320.83, "word": " تأثيرا", "probability": 0.973046875}], "temperature": 1.0}, {"id": 94, "seek": 234784, "start": 2322.42, "end": 2347.84, "text": "الفكرة ان انا بدي اروح اخد او بدي اعمل split على ال maximum gain لل attributes مين ال maximum؟ هي لان 244 من 1000 اكبر من اكبر قيمة موجودة فيهم اللي هي هنا مع ال student", "tokens": [6027, 5172, 4117, 25720, 16472, 1975, 8315, 4724, 16254, 1975, 32887, 5016, 1975, 9778, 3215, 1975, 2407, 4724, 16254, 1975, 25957, 1211, 7472, 15844, 2423, 6674, 6052, 24976, 17212, 3714, 9957, 2423, 6674, 22807, 39896, 5296, 7649, 4022, 19, 9154, 9714, 1975, 4117, 26890, 9154, 1975, 4117, 26890, 12174, 32640, 3660, 3714, 29245, 23328, 3660, 8978, 16095, 13672, 1829, 39896, 34105, 20449, 2423, 3107], "avg_logprob": -0.2639423076923077, "compression_ratio": 1.4628571428571429, "no_speech_prob": 0.0, "words": [{"start": 2322.42, "end": 2323.04, "word": "الفكرة", "probability": 0.96044921875}, {"start": 2323.04, "end": 2323.9, "word": " ان", "probability": 0.33544921875}, {"start": 2323.9, "end": 2324.2, "word": " انا", "probability": 0.772705078125}, {"start": 2324.2, "end": 2324.48, "word": " بدي", "probability": 0.6942138671875}, {"start": 2324.48, "end": 2324.98, "word": " اروح", "probability": 0.9295247395833334}, {"start": 2324.98, "end": 2325.7, "word": " اخد", "probability": 0.791015625}, {"start": 2325.7, "end": 2325.92, "word": " او", "probability": 0.938720703125}, {"start": 2325.92, "end": 2326.18, "word": " بدي", "probability": 0.6124267578125}, {"start": 2326.18, "end": 2326.56, "word": " اعمل", "probability": 0.9876302083333334}, {"start": 2326.56, "end": 2327.06, "word": " split", "probability": 0.64208984375}, {"start": 2327.06, "end": 2327.46, "word": " على", "probability": 0.8564453125}, {"start": 2327.46, "end": 2327.68, "word": " ال", "probability": 0.7998046875}, {"start": 2327.68, "end": 2328.36, "word": " maximum", "probability": 0.94482421875}, {"start": 2328.36, "end": 2330.84, "word": " gain", "probability": 0.86962890625}, {"start": 2330.84, "end": 2332.18, "word": " لل", "probability": 0.755859375}, {"start": 2332.18, "end": 2332.78, "word": " attributes", "probability": 0.705078125}, {"start": 2332.78, "end": 2336.16, "word": " مين", "probability": 0.7470703125}, {"start": 2336.16, "end": 2336.3, "word": " ال", "probability": 0.89892578125}, {"start": 2336.3, "end": 2338.24, "word": " maximum؟", "probability": 0.739013671875}, {"start": 2338.24, "end": 2341.16, "word": " هي", "probability": 0.418212890625}, {"start": 2341.16, "end": 2342.74, "word": " لان", "probability": 0.4349365234375}, {"start": 2342.74, "end": 2343.4, "word": " 244", "probability": 0.5667724609375}, {"start": 2343.4, "end": 2344.4, "word": " من", "probability": 0.369140625}, {"start": 2344.4, "end": 2344.64, "word": " 1000", "probability": 0.411376953125}, {"start": 2344.64, "end": 2344.96, "word": " اكبر", "probability": 0.83740234375}, {"start": 2344.96, "end": 2345.06, "word": " من", "probability": 0.9892578125}, {"start": 2345.06, "end": 2345.38, "word": " اكبر", "probability": 0.9630533854166666}, {"start": 2345.38, "end": 2345.76, "word": " قيمة", "probability": 0.9895833333333334}, {"start": 2345.76, "end": 2346.18, "word": " موجودة", "probability": 0.97802734375}, {"start": 2346.18, "end": 2346.44, "word": " فيهم", "probability": 0.956787109375}, {"start": 2346.44, "end": 2346.56, "word": " اللي", "probability": 0.68505859375}, {"start": 2346.56, "end": 2346.7, "word": " هي", "probability": 0.84619140625}, {"start": 2346.7, "end": 2346.94, "word": " هنا", "probability": 0.452880859375}, {"start": 2346.94, "end": 2347.52, "word": " مع", "probability": 0.8544921875}, {"start": 2347.52, "end": 2347.6, "word": " ال", "probability": 0.923828125}, {"start": 2347.6, "end": 2347.84, "word": " student", "probability": 0.97216796875}], "temperature": 1.0}, {"id": 95, "seek": 237834, "start": 2348.9, "end": 2378.34, "text": "وهذا بتديني إشارة إن ممكن ال student تكون هي ال next element اللي أنحمل عليه splitting لكن مش قضيتي في الآخر أنا هاي الآن الآن ال data set هرجعلها ال data set الآن هنعملها partitioning هي ال data set كيف ال partition تبعتي؟ بيبقى إنه قال لي إن ال age هي هتكون الأساس", "tokens": [2407, 3224, 15730, 39894, 3215, 9957, 1829, 11933, 8592, 9640, 3660, 36145, 3714, 43020, 2423, 3107, 6055, 30544, 39896, 2423, 958, 4478, 13672, 1829, 14739, 5016, 42213, 47356, 30348, 44381, 37893, 12174, 11242, 1829, 31371, 8978, 6024, 95, 34740, 41850, 8032, 47302, 6024, 48506, 6024, 48506, 2423, 1412, 992, 8032, 47341, 3615, 1211, 11296, 2423, 1412, 992, 6024, 48506, 8032, 1863, 25957, 1211, 11296, 24808, 278, 39896, 2423, 1412, 992, 9122, 33911, 2423, 24808, 6055, 3555, 3615, 31371, 22807, 4724, 1829, 3555, 4587, 7578, 36145, 3224, 50239, 32239, 36145, 2423, 3205, 39896, 8032, 2655, 30544, 16247, 3794, 32277], "avg_logprob": -0.26309975108715017, "compression_ratio": 1.7215189873417722, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 2348.9, "end": 2349.28, "word": "وهذا", 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2677.17, "end": 2706.49, "text": "واحد و واحد زائد اتنين على خمسة اتنين على خمسة صحيح اتنين على خمسة في ال I صفر و اتنين بحصل على ال information gain اللي موجود عندي هان بعد هيك بقوله ال gain", "tokens": [14407, 24401, 4032, 36764, 24401, 30767, 16373, 3215, 1975, 2655, 1863, 9957, 15844, 16490, 2304, 3794, 3660, 1975, 2655, 1863, 9957, 15844, 16490, 2304, 3794, 3660, 20328, 5016, 1829, 5016, 1975, 2655, 1863, 9957, 15844, 16490, 2304, 3794, 3660, 8978, 2423, 286, 20328, 5172, 2288, 4032, 1975, 2655, 1863, 9957, 4724, 5016, 36520, 15844, 2423, 1589, 6052, 13672, 1829, 3714, 29245, 23328, 43242, 1829, 8032, 7649, 39182, 39896, 4117, 4724, 39648, 3224, 2423, 6052], "avg_logprob": -0.1487499940395355, "compression_ratio": 1.74, "no_speech_prob": 0.0, "words": [{"start": 2677.17, "end": 2677.89, "word": "واحد", "probability": 0.63818359375}, {"start": 2677.89, "end": 2678.39, "word": " و", "probability": 0.54833984375}, {"start": 2678.39, "end": 2678.95, "word": " واحد", "probability": 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"probability": 0.94921875}, {"start": 2689.79, "end": 2691.47, "word": " ال", "probability": 0.8310546875}, {"start": 2691.47, "end": 2693.23, "word": " I", "probability": 0.67333984375}, {"start": 2693.23, "end": 2698.53, "word": " صفر", "probability": 0.9464518229166666}, {"start": 2698.53, "end": 2700.09, "word": " و", "probability": 0.962890625}, {"start": 2700.09, "end": 2700.45, "word": " اتنين", "probability": 0.9525146484375}, {"start": 2700.45, "end": 2701.93, "word": " بحصل", "probability": 0.9339192708333334}, {"start": 2701.93, "end": 2702.11, "word": " على", "probability": 0.78515625}, {"start": 2702.11, "end": 2702.25, "word": " ال", "probability": 0.79150390625}, {"start": 2702.25, "end": 2702.67, "word": " information", "probability": 0.9111328125}, {"start": 2702.67, "end": 2703.11, "word": " gain", "probability": 0.74658203125}, {"start": 2703.11, "end": 2704.37, "word": " اللي", "probability": 0.88525390625}, {"start": 2704.37, "end": 2704.69, "word": " موجود", "probability": 0.9627278645833334}, {"start": 2704.69, "end": 2705.01, "word": " عندي", "probability": 0.5546875}, {"start": 2705.01, "end": 2705.23, "word": " هان", "probability": 0.5771484375}, {"start": 2705.23, "end": 2705.57, "word": " بعد", "probability": 0.81640625}, {"start": 2705.57, "end": 2705.73, "word": " هيك", "probability": 0.78369140625}, {"start": 2705.73, "end": 2706.07, "word": " بقوله", "probability": 0.8740234375}, {"start": 2706.07, "end": 2706.17, "word": " ال", "probability": 0.85986328125}, {"start": 2706.17, "end": 2706.49, "word": " gain", "probability": 0.93603515625}], "temperature": 1.0}, {"id": 108, "seek": 273368, "start": 2707.76, "end": 2733.68, "text": "تبعت ال income هتمثل ال ID اللي عندي فوق ناقص ال I لل income اللي موجودة عندها هحسبها و فتالي بحسب لهذه و بحسب لل العناصر اللي موجودة عندى تمام", "tokens": [2655, 3555, 34268, 2423, 5742, 8032, 39237, 12984, 1211, 2423, 7348, 13672, 1829, 18871, 16254, 6156, 30543, 8717, 995, 4587, 9381, 2423, 286, 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بعيد الكرة و لل credit rating و صاحب ال attribute صاحب أكبر gain هو اللي حكون فعليا انا هعتمد وين في ال .. في الرسمة او في decision node التالية حسب الحسبة تبعتي حسبناها سابقا لازم انتوا تكملوها للاخر حسب الحسبة تبعتي ال student حصلت اعلى game ال student تبعتي حصلت اعلى game و بالتالي انا الان هان هصير في عند ال student", "tokens": [1211, 1211, 3107, 4724, 3615, 25708, 33251, 25720, 4032, 24976, 5397, 10990, 4032, 20328, 39319, 3555, 2423, 19667, 20328, 39319, 3555, 5551, 4117, 26890, 6052, 31439, 13672, 1829, 11331, 30544, 6156, 3615, 20292, 995, 1975, 8315, 8032, 34268, 2304, 3215, 4032, 9957, 8978, 2423, 4386, 8978, 34892, 38251, 3660, 1975, 2407, 8978, 3537, 9984, 16712, 6027, 10632, 11331, 35457, 21542, 35457, 3660, 6055, 3555, 3615, 31371, 11331, 35457, 8315, 11296, 8608, 16758, 4587, 995, 5296, 31377, 2304, 16472, 2655, 14407, 6055, 24793, 1211, 2407, 11296, 24976, 47283, 2288, 11331, 35457, 21542, 35457, 3660, 6055, 3555, 3615, 31371, 2423, 3107, 11331, 36520, 2655, 1975, 3615, 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موجودة عندي هيك و بهكد صارت كل ال nodes بتنتمي لنفس ال class كل ال samples بتنتمي لنفس ال class فهان بوقف هذه already كلها بتنتمي لنفس ال class فانا وقفت هان ووقفت هان هتكون ال final tree تبعتي طبعا هي الحسبة اللي عندناها مرة تانية انا في الآخر", "tokens": [3224, 1829, 2423, 39184, 47836, 9984, 25724, 995, 10632, 4032, 41185, 11296, 732, 819, 4190, 11331, 4587, 38251, 2423, 1412, 992, 39182, 39896, 4117, 11331, 4587, 38251, 2423, 1412, 992, 6055, 3555, 3615, 995, 24976, 13891, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 1829, 39896, 4117, 4032, 39627, 4117, 3215, 20328, 9640, 2655, 28242, 2423, 13891, 39894, 29399, 2304, 1829, 5296, 1863, 36178, 2423, 1508, 28242, 2423, 10938, 39894, 29399, 2304, 1829, 5296, 1863, 36178, 2423, 1508, 6156, 3224, 7649, 4724, 30543, 5172, 29538, 1217, 28242, 11296, 39894, 29399, 2304, 1829, 5296, 1863, 36178, 2423, 1508, 6156, 7649, 995, 4032, 4587, 5172, 2655, 8032, 7649, 4032, 30543, 5172, 2655, 8032, 7649, 8032, 2655, 30544, 2423, 2572, 4230, 6055, 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"probability": 0.89599609375}, {"start": 2979.17, "end": 2979.55, "word": " موضوع", "probability": 0.986328125}, {"start": 2979.55, "end": 2979.71, "word": " ال", "probability": 0.94970703125}, {"start": 2979.71, "end": 2979.93, "word": " gain", "probability": 0.71044921875}, {"start": 2979.93, "end": 2980.35, "word": " ratio", "probability": 0.96923828125}], "temperature": 1.0}, {"id": 118, "seek": 300764, "start": 2981.0, "end": 3007.64, "text": "الـ Gain Ratio فكرتها يا جماعة الخير انه انا بده اروح احسب ال split info احنا سابقا كانت هذه القيمة موجودة عندنا هي عدد عناصر ال partition على .. على كل ال partition في موضوع ال probability لكل ال partition اللي موجودة عندها و بعد ما بحسب ال gain بروح بحط عليها ال split ratio و هيك برضه برجع باخد ال maximum split ratio كذلك في عند ال gain index", "tokens": [6027, 39184, 460, 491, 24269, 1004, 6156, 4117, 43500, 11296, 35186, 10874, 15042, 27884, 33962, 13546, 16472, 3224, 1975, 8315, 47525, 3224, 1975, 32887, 5016, 1975, 5016, 35457, 2423, 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test و هنحددني setosa بكل تأكيد وبهيك بنكون احنا فعليا انتهينا من موضوع ال decision tree لمحاضرتنا اليوم المطلوب بينكوا تجربوا يا جماعة الخير في عندنا different data set موجودة في ال slide سابقا جربوا الكلام هذا عليها و جربوا الكلام عليها هذا كلام عليها يعني بينجو سين هذا الكلام مش هتتقنوه من مرة و تنتين و تلاتة", "tokens": [6027, 8315, 33911, 4724, 47302, 3794, 9957, 1975, 32887, 5016, 6055, 25957, 1211, 2423, 1500, 4032, 8032, 1863, 24401, 3215, 22653, 992, 6447, 4724, 28820, 6055, 10721, 4117, 25708, 46599, 3224, 1829, 4117, 44945, 30544, 1975, 5016, 8315, 6156, 3615, 20292, 995, 16472, 47395, 1829, 8315, 9154, 3714, 2407, 11242, 45367, 2423, 3537, 4230, 5296, 2304, 5016, 46958, 43500, 8315, 45595, 20498, 9673, 9566, 1211, 37746, 49374, 4117, 14407, 6055, 7435, 25513, 14407, 35186, 10874, 15042, 27884, 33962, 13546, 8978, 43242, 8315, 819, 1412, 992, 3714, 29245, 23328, 3660, 8978, 2423, 4137, 8608, 16758, 4587, 995, 10874, 25513, 14407, 2423, 28820, 10943, 23758, 25894, 11296, 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"probability": 0.568359375}, {"start": 3226.22, "end": 3227.14, "word": " هنحددني", "probability": 0.595703125}, {"start": 3227.14, "end": 3228.06, "word": " setosa", "probability": 0.5838623046875}, {"start": 3228.06, "end": 3228.84, "word": " بكل", "probability": 0.962646484375}, {"start": 3228.84, "end": 3229.8, "word": " تأكيد", "probability": 0.988525390625}, {"start": 3229.8, "end": 3230.6, "word": " وبهيك", "probability": 0.7008056640625}, {"start": 3230.6, "end": 3230.92, "word": " بنكون", "probability": 0.7802734375}, {"start": 3230.92, "end": 3231.18, "word": " احنا", "probability": 0.9181315104166666}, {"start": 3231.18, "end": 3231.72, "word": " فعليا", "probability": 0.9266357421875}, {"start": 3231.72, "end": 3232.86, "word": " انتهينا", "probability": 0.9564208984375}, {"start": 3232.86, "end": 3233.12, "word": " من", "probability": 0.966796875}, {"start": 3233.12, "end": 3233.46, "word": " موضوع", "probability": 0.9827880859375}, {"start": 3233.46, "end": 3233.6, "word": " ال", "probability": 0.7392578125}, {"start": 3233.6, "end": 3233.86, "word": " decision", "probability": 0.91259765625}, {"start": 3233.86, "end": 3234.26, "word": " tree", "probability": 0.884765625}, {"start": 3234.26, "end": 3234.96, "word": " لمحاضرتنا", "probability": 0.8558349609375}, {"start": 3234.96, "end": 3235.38, "word": " اليوم", "probability": 0.949951171875}, {"start": 3235.38, "end": 3236.44, "word": " المطلوب", "probability": 0.9766845703125}, {"start": 3236.44, "end": 3237.04, "word": " بينكوا", "probability": 0.7356770833333334}, {"start": 3237.04, "end": 3237.66, "word": " تجربوا", "probability": 0.889892578125}, {"start": 3237.66, "end": 3237.74, "word": " يا", "probability": 0.98876953125}, {"start": 3237.74, "end": 3237.94, "word": " جماعة", "probability": 0.9957682291666666}, {"start": 3237.94, "end": 3238.34, "word": " الخير", "probability": 0.95751953125}, {"start": 3238.34, "end": 3238.52, "word": " في", "probability": 0.66552734375}, {"start": 3238.52, "end": 3238.72, "word": " عندنا", "probability": 0.6651611328125}, {"start": 3238.72, "end": 3238.98, "word": " different", "probability": 0.8671875}, {"start": 3238.98, "end": 3239.26, "word": " data", "probability": 0.53515625}, {"start": 3239.26, "end": 3239.5, "word": " set", "probability": 0.8935546875}, {"start": 3239.5, "end": 3239.86, "word": " موجودة", "probability": 0.971435546875}, {"start": 3239.86, "end": 3239.92, "word": " في", "probability": 0.8876953125}, {"start": 3239.92, "end": 3239.98, "word": " ال", "probability": 0.828125}, {"start": 3239.98, "end": 3240.24, "word": " slide", "probability": 0.93896484375}, {"start": 3240.24, "end": 3240.8, "word": " سابقا", "probability": 0.9815673828125}, {"start": 3240.8, "end": 3241.64, "word": " جربوا", "probability": 0.7900390625}, {"start": 3241.64, "end": 3242.02, "word": " الكلام", "probability": 0.9169921875}, {"start": 3242.02, "end": 3242.28, "word": " هذا", "probability": 0.63232421875}, {"start": 3242.28, "end": 3242.66, "word": " عليها", "probability": 0.942626953125}, {"start": 3242.66, "end": 3242.78, "word": " و", "probability": 0.30810546875}, {"start": 3242.78, "end": 3243.12, "word": " جربوا", "probability": 0.9117838541666666}, {"start": 3243.12, "end": 3243.42, "word": " الكلام", "probability": 0.9581705729166666}, {"start": 3243.42, "end": 3243.66, "word": " عليها", "probability": 0.789794921875}, {"start": 3243.66, "end": 3243.82, "word": " هذا", "probability": 0.3359375}, {"start": 3243.82, "end": 3243.96, "word": " كلام", "probability": 0.6397705078125}, {"start": 3243.96, "end": 3244.14, "word": " عليها", "probability": 0.8896484375}, {"start": 3244.14, "end": 3244.54, "word": " يعني", "probability": 0.764892578125}, {"start": 3244.54, "end": 3244.84, "word": " بينجو", "probability": 0.628631591796875}, {"start": 3244.84, "end": 3245.0, "word": " سين", "probability": 0.71142578125}, {"start": 3245.0, "end": 3245.24, "word": " هذا", "probability": 0.59326171875}, {"start": 3245.24, "end": 3245.56, "word": " الكلام", "probability": 0.96826171875}, {"start": 3245.56, "end": 3245.8, "word": " مش", "probability": 0.92529296875}, {"start": 3245.8, "end": 3246.5, "word": " هتتقنوه", "probability": 0.9229910714285714}, {"start": 3246.5, "end": 3246.62, "word": " من", "probability": 0.98681640625}, {"start": 3246.62, "end": 3246.86, "word": " مرة", "probability": 0.98876953125}, {"start": 3246.86, "end": 3247.0, "word": " و", "probability": 0.80126953125}, {"start": 3247.0, "end": 3247.2, "word": " تنتين", "probability": 0.69775390625}, {"start": 3247.2, "end": 3247.3, "word": " و", "probability": 0.794921875}, {"start": 3247.3, "end": 3247.74, "word": " تلاتة", "probability": 0.955810546875}], "temperature": 1.0}, {"id": 128, "seek": 326747, "start": 3247.95, "end": 3267.47, "text": "الشغل التاني اللي بدي اياها منكوا بعد تجريب العمل يبدو تعتبروها ك assignment عليكم الآن تبدو تروح تفكروا او تدورولي كيف ممكن انا اذا كانت هذه عبارة عن ال tree بعد ما انا عملتلها فت هل في مجال ارسم ال tree تبعت بال بايثون اه في مجال وهذه متروكة لكم والسلام عليكم ورحمة الله وبركاته", "tokens": [6027, 8592, 17082, 1211, 16712, 7649, 1829, 13672, 1829, 4724, 16254, 1975, 25528, 11296, 9154, 4117, 14407, 39182, 6055, 7435, 16572, 3555, 18863, 42213, 7251, 44510, 2407, 6055, 34268, 26890, 2407, 11296, 9122, 15187, 25894, 24793, 6024, 48506, 6055, 44510, 2407, 6055, 32887, 5016, 6055, 5172, 37983, 14407, 1975, 2407, 6055, 3215, 13063, 12610, 1829, 9122, 33911, 3714, 43020, 1975, 8315, 1975, 15730, 25961, 2655, 29538, 6225, 3555, 9640, 3660, 18871, 2423, 4230, 39182, 19446, 1975, 8315, 6225, 42213, 2655, 1211, 11296, 6156, 2655, 8032, 1211, 8978, 3714, 7435, 6027, 1975, 2288, 38251, 2423, 4230, 6055, 3555, 34268, 20666, 4724, 47302, 12984, 11536, 1975, 3224, 8978, 3714, 7435, 6027, 37037, 24192, 44650, 32887, 4117, 3660, 5296, 24793, 16070, 3794, 37440, 25894, 24793, 4032, 2288, 35571, 3660, 21984, 4032, 26890, 4117, 9307, 3224], "avg_logprob": -0.19584116720615474, "compression_ratio": 1.8988326848249026, "no_speech_prob": 0.0006766319274902344, "words": [{"start": 3247.95, "end": 3248.47, "word": "الشغل", "probability": 0.8416748046875}, {"start": 3248.47, "end": 3248.77, "word": " التاني", "probability": 0.9368489583333334}, {"start": 3248.77, "end": 3248.87, "word": " اللي", "probability": 0.830078125}, {"start": 3248.87, "end": 3249.09, "word": " بدي", "probability": 0.8291015625}, {"start": 3249.09, "end": 3249.37, "word": " اياها", "probability": 0.7386067708333334}, {"start": 3249.37, "end": 3249.85, "word": " منكوا", "probability": 0.83056640625}, {"start": 3249.85, "end": 3250.39, "word": " بعد", "probability": 0.8310546875}, {"start": 3250.39, "end": 3251.03, "word": " تجريب", "probability": 0.893310546875}, {"start": 3251.03, "end": 3251.43, "word": " العمل", "probability": 0.739501953125}, {"start": 3251.43, "end": 3252.13, "word": " يبدو", "probability": 0.4785563151041667}, {"start": 3252.13, "end": 3252.65, "word": " تعتبروها", "probability": 0.90537109375}, {"start": 3252.65, "end": 3252.79, "word": " ك", "probability": 0.70263671875}, {"start": 3252.79, "end": 3253.33, "word": " assignment", "probability": 0.8388671875}, {"start": 3253.33, "end": 3253.85, "word": " عليكم", "probability": 0.849365234375}, {"start": 3253.85, "end": 3254.17, "word": " الآن", "probability": 0.65185546875}, {"start": 3254.17, "end": 3254.79, "word": " تبدو", "probability": 0.8805338541666666}, {"start": 3254.79, "end": 3255.05, "word": " تروح", "probability": 0.98876953125}, {"start": 3255.05, "end": 3255.73, "word": " تفكروا", "probability": 0.8875732421875}, {"start": 3255.73, "end": 3255.89, "word": " او", "probability": 0.798828125}, {"start": 3255.89, "end": 3256.37, "word": " تدورولي", "probability": 0.88017578125}, {"start": 3256.37, "end": 3256.69, "word": " كيف", "probability": 0.947509765625}, {"start": 3256.69, "end": 3257.01, "word": " ممكن", "probability": 0.96728515625}, {"start": 3257.01, "end": 3257.27, "word": " انا", "probability": 0.899169921875}, {"start": 3257.27, "end": 3257.49, "word": " اذا", "probability": 0.837890625}, {"start": 3257.49, "end": 3257.77, "word": " كانت", "probability": 0.96875}, {"start": 3257.77, "end": 3257.95, "word": " هذه", "probability": 0.8251953125}, {"start": 3257.95, "end": 3258.31, "word": " عبارة", "probability": 0.988525390625}, {"start": 3258.31, "end": 3258.47, "word": " عن", "probability": 0.99365234375}, {"start": 3258.47, "end": 3258.57, "word": " ال", "probability": 0.40087890625}, {"start": 3258.57, "end": 3258.77, "word": " tree", "probability": 0.50146484375}, {"start": 3258.77, "end": 3259.63, "word": " بعد", "probability": 0.927734375}, {"start": 3259.63, "end": 3259.81, "word": " ما", "probability": 0.83349609375}, {"start": 3259.81, "end": 3259.95, "word": " انا", "probability": 0.88525390625}, {"start": 3259.95, "end": 3260.35, "word": " عملتلها", "probability": 0.86083984375}, {"start": 3260.35, "end": 3260.69, "word": " فت", "probability": 0.706298828125}, {"start": 3260.69, "end": 3260.93, "word": " هل", "probability": 0.771728515625}, {"start": 3260.93, "end": 3261.03, "word": " في", "probability": 0.92724609375}, {"start": 3261.03, "end": 3261.27, "word": " مجال", "probability": 0.9957682291666666}, {"start": 3261.27, "end": 3261.63, "word": " ارسم", "probability": 0.9306640625}, {"start": 3261.63, "end": 3261.73, "word": " ال", "probability": 0.60498046875}, {"start": 3261.73, "end": 3261.93, "word": " tree", "probability": 0.77978515625}, {"start": 3261.93, "end": 3262.23, "word": " تبعت", "probability": 0.89501953125}, {"start": 3262.23, "end": 3262.37, "word": " بال", "probability": 0.51708984375}, {"start": 3262.37, "end": 3262.79, "word": " بايثون", "probability": 0.710784912109375}, {"start": 3262.79, "end": 3263.31, "word": " اه", "probability": 0.73193359375}, {"start": 3263.31, "end": 3263.41, "word": " في", "probability": 0.94189453125}, {"start": 3263.41, "end": 3263.81, "word": " مجال", "probability": 0.9973958333333334}, {"start": 3263.81, "end": 3264.23, "word": " وهذه", "probability": 0.597412109375}, {"start": 3264.23, "end": 3264.63, "word": " متروكة", "probability": 0.73248291015625}, {"start": 3264.63, "end": 3264.97, "word": " لكم", "probability": 0.753662109375}, {"start": 3264.97, "end": 3265.69, "word": " والسلام", "probability": 0.94677734375}, {"start": 3265.69, "end": 3266.05, "word": " عليكم", "probability": 0.95654296875}, {"start": 3266.05, "end": 3266.45, "word": " ورحمة", "probability": 0.972900390625}, {"start": 3266.45, "end": 3266.73, "word": " الله", "probability": 0.95703125}, {"start": 3266.73, "end": 3267.47, "word": " وبركاته", "probability": 0.9685546875}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 3267.6745625, "duration_after_vad": 3113.517499999983}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/XptbH5_PJns_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/XptbH5_PJns_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..f082b277b139f036018854c32fda92ee6d316e2e
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/XptbH5_PJns_raw.srt
@@ -0,0 +1,1184 @@
+1
+00:00:01,030 --> 00:00:02,950
+بسم الله الرحمن الرحيم والصلاة والسلام على الرسول
+
+2
+00:00:02,950 --> 00:00:05,610
+الله أهلا و أهلا بكم في التسجيل الأخير أو في
+
+3
+00:00:05,610 --> 00:00:08,670
+المقطع الأخير من موضوع الـ Association role كنا
+
+4
+00:00:08,670 --> 00:00:12,050
+نتكلم في المحاضرة السابقة على ال FP Growth وقبلنا
+
+5
+00:00:12,050 --> 00:00:16,350
+.. أو في التسجيل السابق عفوا ال FP Growth وشوفنا
+
+6
+00:00:16,350 --> 00:00:21,290
+فعلا ال scalability و ال a priori algorithm سابقا
+
+7
+00:00:21,290 --> 00:00:25,110
+وطركني أقول مثل هذا تحلوه لوحدكم عشان تتدربوا عليه
+
+8
+00:00:25,510 --> 00:00:30,450
+الان اللى هنتكلم في جزئية ان انا فعليا موضوع ال
+
+9
+00:00:30,450 --> 00:00:37,450
+mining له different kinds of association rules ال
+
+10
+00:00:37,450 --> 00:00:40,730
+association
+
+11
+00:00:40,730 --> 00:00:46,330
+rules اللى عدي عبارة عن level واحدفهل في مجالي ان
+
+12
+00:00:46,330 --> 00:00:49,710
+انا اتكلم على multilevel association rules بمعنى
+
+13
+00:00:49,710 --> 00:00:54,450
+اخر if then else then بالشكل هذا involve concept
+
+14
+00:00:54,450 --> 00:00:57,050
+of different level of abstraction هل هذا ممكن
+
+15
+00:00:57,050 --> 00:00:59,890
+ممتاح او لا في ال multidimensional association
+
+16
+00:00:59,890 --> 00:01:03,710
+rules involve more than one dimension انا شغال ب
+
+17
+00:01:03,710 --> 00:01:08,900
+one dimension دائمااللي هي ال .. ال .. ال .. ال ..
+
+18
+00:01:08,900 --> 00:01:08,920
+ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال
+
+19
+00:01:08,920 --> 00:01:09,460
+.. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال ..
+
+20
+00:01:09,460 --> 00:01:17,480
+ال .. ال .. ال .. ال .. ال .. ال .. ال ..
+
+21
+00:01:17,480 --> 00:01:19,020
+ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال
+
+22
+00:01:19,020 --> 00:01:19,060
+.. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال ..
+
+23
+00:01:19,060 --> 00:01:19,620
+ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال
+
+24
+00:01:19,620 --> 00:01:19,720
+.. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال ..
+
+25
+00:01:19,720 --> 00:01:19,720
+ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال
+
+26
+00:01:19,720 --> 00:01:20,540
+.. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال ..
+
+27
+00:01:20,540 --> 00:01:21,420
+ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال
+
+28
+00:01:21,420 --> 00:01:24,100
+.. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال ..
+
+29
+00:01:24,100 --> 00:01:24,100
+ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال
+
+30
+00:01:24,100 --> 00:01:32,780
+.. ال .. ال .. ال .. ال .. ال .. الهذه عبارة عن
+
+31
+00:01:32,780 --> 00:01:37,920
+مسائل مفتوحة في موضوع الـ Association Rules ومازال
+
+32
+00:01:37,920 --> 00:01:43,900
+الناس عمالها بتحاول تشتغل عليهاهل الـ quantitative
+
+33
+00:01:43,900 --> 00:01:47,480
+هل الـ numeric values الاتريبوتس احنا سابقا شفنا
+
+34
+00:01:47,480 --> 00:01:53,000
+ان ال item موجود نفسه اشتراه و مااشتراهوش yes و no
+
+35
+00:01:53,000 --> 00:01:56,660
+صح حرناهم و لا بتحول في بداية العملية و بتحولهم ل
+
+36
+00:01:56,660 --> 00:01:59,460
+binary طب الآن هذا ال value كان في عندي different
+
+37
+00:01:59,460 --> 00:02:02,940
+values ال numeric values ال quantitative كيف ممكن
+
+38
+00:02:02,940 --> 00:02:06,240
+انا اتعامل مع ال association rules كذلك من الشغلات
+
+39
+00:02:06,240 --> 00:02:09,260
+المهمة بالنسبة لنا في الموضوع ال measurement احنا
+
+40
+00:02:09,260 --> 00:02:13,760
+اتعرفنا على ال support و ال confidenceو هدولة
+
+41
+00:02:13,760 --> 00:02:17,520
+كانوا هم الأساس طيب شو بده يصير لو انا كان في عندي
+
+42
+00:02:17,520 --> 00:02:20,940
+large support و large confidence لو انا كان هدولة
+
+43
+00:02:20,940 --> 00:02:24,100
+كبارة جدا يعني هو سيكون صير في عندي small number
+
+44
+00:02:24,100 --> 00:02:27,980
+من ال association rules بينموزيني يعني ان انا في
+
+45
+00:02:27,980 --> 00:02:37,040
+عندي علاقة أرضية عكسية ما بين ال support و ال
+
+46
+00:02:37,040 --> 00:02:44,990
+confidence و العدد ال association rulesوبالتالي كل
+
+47
+00:02:44,990 --> 00:02:49,690
+ما بزيد ال association rules بجل العدد اللي موجود
+
+48
+00:02:49,690 --> 00:02:54,870
+عندهم ال support small يعني انا اتومنس يعني ايش
+
+49
+00:02:54,870 --> 00:03:05,210
+افضل ال threshold او the best threshold ممكن
+
+50
+00:03:05,210 --> 00:03:10,270
+انا اطبقه في ال finding او في عملية البحث على ال
+
+51
+00:03:10,270 --> 00:03:13,640
+association rules اللي موجودة عندهمكذلك ان انا
+
+52
+00:03:13,640 --> 00:03:18,280
+ممكن يصير في موضوع ال confidence وال support بعض
+
+53
+00:03:18,280 --> 00:03:22,320
+ال misleading او بعض السوء الفهم خلينا نشوف ال
+
+54
+00:03:22,320 --> 00:03:26,820
+contingency table اللي موجود عندي هنا عملوا
+
+55
+00:03:26,820 --> 00:03:33,210
+استطلاع من 500 واحدحاول انه .. بيلعبوا .. بيلعبوا
+
+56
+00:03:33,210 --> 00:03:37,230
+كرة سلة و بيشربوا .. بين لعبين الكرة السلة و
+
+57
+00:03:37,230 --> 00:03:40,590
+بيشربوا حليب ولا مابيشربوش او خيانة اخد خمس سلاف
+
+58
+00:03:40,590 --> 00:03:44,390
+واحد و اشتغلوا ايه فكان من الخمس سلاف دول انه في
+
+59
+00:03:44,390 --> 00:03:48,390
+ألفين بيقولوا ان كل لعبين السلة لازم يشربوا الحليب
+
+60
+00:03:48,390 --> 00:03:51,570
+بينما ألف وسبعمائة و خمسين بيقولوا لأ مش ضروري
+
+61
+00:03:51,570 --> 00:03:56,540
+اللي بيشربوا الحليب هدول ما يكونوا بيلعبوا سلةكذلك
+
+62
+00:03:56,540 --> 00:04:04,460
+في الوف قالوا لأ الشرب الحليب مش مرتبط باللعب
+
+63
+00:04:04,460 --> 00:04:10,140
+السلة كرة السلة و 250 قالوا لا بيشربوا حليب ولا
+
+64
+00:04:10,140 --> 00:04:15,410
+بيلعبوا سلةيعني هو كأنه الاستطلاع بين رأيك انت
+
+65
+00:04:15,410 --> 00:04:20,290
+بتشرب حلو و بتلعب كرة سلة و تحاول أن تلعب انصارين
+
+66
+00:04:20,290 --> 00:04:24,690
+مع بعض يعني drinking milk و playing football هدولة
+
+67
+00:04:24,690 --> 00:04:27,770
+binary tables او binary attributes كانوا موجودين
+
+68
+00:04:27,770 --> 00:04:37,430
+عندي هيهم playing و drinking playing basketball و
+
+69
+00:04:37,430 --> 00:04:46,860
+ال values اللي موجودة عندهاyes و no و
+
+70
+00:04:46,860 --> 00:04:51,580
+العكس صحيح موجود في التنين تمام و هكذا هي
+
+71
+00:04:51,580 --> 00:04:54,500
+الاستطلاع فكانت ال contingency table تبع الاستطلاع
+
+72
+00:04:54,500 --> 00:04:57,620
+هي من ال contingency table اللي موجود عندها لما
+
+73
+00:04:57,620 --> 00:05:09,940
+انا جاعد بقول الفين تمامالنسبة 40% لعب كرة السلة
+
+74
+00:05:09,940 --> 00:05:16,600
+يؤدي إلى شرب الحليب الـ
+
+75
+00:05:16,600 --> 00:05:21,340
+Confidence
+
+76
+00:05:21,340 --> 00:05:29,640
+فعليا 2000 على 3000مصبوط لأن هؤلاء فئة الناس اللي
+
+77
+00:05:29,640 --> 00:05:33,900
+بتلعب السلة فعدد مرتبط على ال probability ألفين
+
+78
+00:05:33,900 --> 00:05:36,280
+على عدد اللي بيلعبوا سلة تلت تلاف ال high
+
+79
+00:05:36,280 --> 00:05:41,160
+confidence او ال support تبعت الأول على ال support
+
+80
+00:05:41,160 --> 00:05:46,240
+تبعت ال association rule على ال support تبعت الأول
+
+81
+00:05:46,240 --> 00:05:49,600
+من ال association rule ألفين على تلت تلاف سبعة
+
+82
+00:05:49,600 --> 00:05:55,730
+وسبعين في المائة هذه ال data is misleadingلأن ال
+
+83
+00:05:55,730 --> 00:05:58,270
+over all عندى percentage بين ال students او بين
+
+84
+00:05:58,270 --> 00:06:02,310
+الناس اللى زى شمالهم الاستطلاع بتكلموا عن شرب
+
+85
+00:06:02,310 --> 00:06:08,830
+الحليب هم عمارة عن خمسة و سبعين في المية تمام؟
+
+86
+00:06:08,830 --> 00:06:16,670
+وهذا الكلام اكتر من ستة و ستين في المية طيب تعالى
+
+87
+00:06:16,670 --> 00:06:23,930
+نشوفها لو انا جيت جلبت او اخدت ال playing football
+
+88
+00:06:23,930 --> 00:06:24,610
+و نطت
+
+89
+00:06:31,500 --> 00:06:36,520
+عشرين في المية لان عشرة على خمسة ألف و عشرة على
+
+90
+00:06:36,520 --> 00:06:37,240
+تلاتة و تلاتين
+
+91
+00:06:42,770 --> 00:06:51,250
+لكن ال support تبعتها confidence و ال support
+
+92
+00:06:51,250 --> 00:06:58,330
+تبعتها مجلال وبالتالي أنا مش هاخد ال role هذا لأن
+
+93
+00:06:58,330 --> 00:07:04,190
+هو فعليا higher support و higher confidence بينما
+
+94
+00:07:04,190 --> 00:07:07,690
+هو misleading وبالتالي موضوع ال support و ال
+
+95
+00:07:07,690 --> 00:07:13,370
+confidence لحالهمهو غير كافي بالنسبة لنا في موضوع
+
+96
+00:07:13,370 --> 00:07:16,790
+الـ Measuring تبع الـ Association Roles لأنه كما
+
+97
+00:07:16,790 --> 00:07:20,970
+رأينا نفسنا يمكن أن يكون هناك Misleading ماهو الحل
+
+98
+00:07:20,970 --> 00:07:25,330
+اللي نحن نتكلم عنه؟ هل يمكن أن يكون هناك زوّر؟ هل
+
+99
+00:07:25,330 --> 00:07:28,950
+يمكن أن يكون هناك Framework يشكل إضافة عندنا؟
+
+100
+00:07:36,110 --> 00:07:40,070
+الـ Correlation ممكن تستخدمها كمجارية ممكن
+
+101
+00:07:40,070 --> 00:07:43,430
+تستخدمها كمجارية تعمل تعمل تعمل تعمل تعمل تعمل
+
+102
+00:07:43,430 --> 00:07:44,910
+تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل
+
+103
+00:07:44,910 --> 00:07:45,010
+تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل
+
+104
+00:07:45,010 --> 00:07:45,270
+تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل
+
+105
+00:07:45,270 --> 00:07:45,630
+تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل
+
+106
+00:07:45,630 --> 00:07:45,630
+تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل
+
+107
+00:07:45,630 --> 00:07:45,630
+تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل تعمل
+
+108
+00:07:49,010 --> 00:07:54,510
+أنا ممكن أضيف الـ Correlation عشان يصير في عندي ك
+
+109
+00:07:54,510 --> 00:07:58,350
+Element تالت مع ال support و ال confidence عشان
+
+110
+00:07:58,350 --> 00:08:01,770
+انا اشوف العلاقة وبالتالي ال Correlation Major ليس
+
+111
+00:08:01,770 --> 00:08:06,210
+فقط بسبب ال support و ال confidence بل فقط بسبب ال
+
+112
+00:08:06,210 --> 00:08:09,370
+Correlation بين ال item set العلاقة ما بين ال item
+
+113
+00:08:09,370 --> 00:08:15,060
+set احنا متفقين ان ال A و ال Bتقاطع بينهم من
+
+114
+00:08:15,060 --> 00:08:19,880
+البداية في نعم و التقاطع بينهم في okay هذا كلام
+
+115
+00:08:19,880 --> 00:08:23,180
+صحيح يعني independent attributes لكن هل في ممكن
+
+116
+00:08:23,180 --> 00:08:26,840
+يكون في correlation بينهم و احنا مش شايفينه او ال
+
+117
+00:08:26,840 --> 00:08:31,990
+correlation هذا مش او لا ينتميأو لا يمثل بجموعة من
+
+118
+00:08:31,990 --> 00:08:34,270
+الـ Item Sets أو من الـ Items اللي موجودين في الـ
+
+119
+00:08:34,270 --> 00:08:38,570
+Item Set فممكن أنا أضيفه كذلك ممكن أنا أعتمد
+
+120
+00:08:38,570 --> 00:08:43,330
+أستخدم الـ Chi-Square تمام اللي لما اتكلمنا على
+
+121
+00:08:43,330 --> 00:08:47,690
+الـفي الـ Correlation أستخدم الـ Tri-Square لما
+
+122
+00:08:47,690 --> 00:08:50,850
+أكون في الـ Data اللي عندي هي categorial أو
+
+123
+00:08:50,850 --> 00:08:54,330
+nominal أو أعتمد على شغل بنسميها احنا ال left
+
+124
+00:08:54,330 --> 00:08:57,790
+analysis أو ال left correlation وهو عبارة عن
+
+125
+00:08:57,790 --> 00:09:02,290
+Correlation سهل الفكرة فيه بكل بساطة انه انا
+
+126
+00:09:02,290 --> 00:09:06,830
+المفروض ان ال item set ظهورها ال A و ال B
+
+127
+00:09:06,830 --> 00:09:11,370
+independent و ال occurrence تبعتهم غير مرتبطة في
+
+128
+00:09:11,370 --> 00:09:15,360
+ابعاطهمبالتالي ال probability تبع ال A اتحاد ال B
+
+129
+00:09:15,360 --> 00:09:20,100
+تساوي ال probability لل A في ال probability لل B
+
+130
+00:09:20,100 --> 00:09:25,300
+otherwise ال A و ال B are dependent يمكن أن يكون
+
+131
+00:09:25,300 --> 00:09:30,180
+بينهم dependent و ال correlation as دليل على ال
+
+132
+00:09:30,180 --> 00:09:35,270
+dependency اللي موجودةعندها فبكل بساطة ممكن انا
+
+133
+00:09:35,270 --> 00:09:37,790
+احنا اتفقنا كمان مرة لجماعة الخيار انه انا بدي
+
+134
+00:09:37,790 --> 00:09:40,970
+اضيف ال correlation ال correlation هذه اما بتكون H
+
+135
+00:09:40,970 --> 00:09:47,550
+I Square تمام او بتكون اللي هي ال left او بتكون ال
+
+136
+00:09:47,550 --> 00:09:50,350
+left measurement ال left بقول ليه لو كان في عندي
+
+137
+00:09:50,350 --> 00:09:55,360
+association rule A و BAA plus B as defined as
+
+138
+00:09:55,360 --> 00:10:00,020
+اللفت بعرف ليها انه تساوي ال probability للاتحادهم
+
+139
+00:10:00,020 --> 00:10:04,660
+على ال probability ل الحصل ضربهم وهذه تساوي ال
+
+140
+00:10:04,660 --> 00:10:06,780
+probability لل B difference ال A على ال
+
+141
+00:10:06,780 --> 00:10:10,160
+probability لل B الكلام أسهل بعيدا عن ال
+
+142
+00:10:10,160 --> 00:10:14,260
+probability اللفته ساوي ال confidence لل A و ال B
+
+143
+00:10:14,260 --> 00:10:18,140
+على ال support تبع ال B سابقا ال confidence هي
+
+144
+00:10:18,140 --> 00:10:23,720
+كانتالـ Support تبع الـ A و الـ B الـ Confidence
+
+145
+00:10:23,720 --> 00:10:29,260
+التي كانت الـ Support للـ A تبع الـ B على الـ
+
+146
+00:10:29,260 --> 00:10:35,340
+Support تبع الـ A الآن ستصبح المسألة كلها يتضف لها
+
+147
+00:10:35,340 --> 00:10:40,760
+الـ Support تبع الـ B وهكذا سأكون حققت الـ
+
+148
+00:10:40,760 --> 00:10:44,940
+Probability اللي موجودة عندها وبالتالي هي عبارة عن
+
+149
+00:10:44,940 --> 00:10:51,460
+الـ Ratioof confidence to expected confidence
+
+150
+00:10:51,460 --> 00:10:55,940
+وهكذا انا اتكلم ان هاتي عندى major تالت ممكن يكون
+
+151
+00:10:55,940 --> 00:10:59,660
+يضيفلي تحسين على موضوع ال selection للمولودها
+
+152
+00:10:59,660 --> 00:11:03,720
+والاصل انه انا كل ما بيجيل ابت المفروض ان ال lift
+
+153
+00:11:03,720 --> 00:11:08,340
+عشان اقدر افهمها صح اذا كانت ال lift قيمتها اكبر
+
+154
+00:11:08,340 --> 00:11:12,240
+من واحد معناته positively correlated معناته اذا
+
+155
+00:11:12,240 --> 00:11:18,260
+ظهر الاول هيظهر التانيطبعا هذه إشارة جيدة
+
+156
+00:11:18,260 --> 00:11:25,260
+Negatively correlated أقل من واحد معناته إذا ال ..
+
+157
+00:11:25,260 --> 00:11:30,440
+Discouraged occurrence .. معناته الظهر الأول لن
+
+158
+00:11:30,440 --> 00:11:35,660
+يظهر الثاني وإذا كانت واحد معناته هدول الاتنين
+
+159
+00:11:35,660 --> 00:11:40,260
+independent ومافيش correlation ما بينهم وبالتالي
+
+160
+00:11:40,260 --> 00:11:45,790
+ال .. الآن لو أنا سألت مين أفضل بالنسبة ليمن يدعي
+
+161
+00:11:45,790 --> 00:11:49,170
+support اكتر من يدعي موثوقية اكتر في ال confidence
+
+162
+00:11:49,170 --> 00:11:56,990
+المفروض لما تكون ال .. ال .. ال left عندي اكبر من
+
+163
+00:11:56,990 --> 00:12:00,380
+واحد وراها لما تكون العلاقة independentأقول
+
+164
+00:12:00,380 --> 00:12:03,680
+بالتانية اللي لما تكون ال lift أقل من واحد معناته
+
+165
+00:12:03,680 --> 00:12:09,100
+في عندي مشكلة حقيقية في ال association role اللي
+
+166
+00:12:09,100 --> 00:12:14,400
+ظهر عندي لأنه قيمته المفروض لما يظهر واحد يختفي
+
+167
+00:12:14,400 --> 00:12:16,780
+التاني طب ليش ظهروا التانين مع بعض في ال
+
+168
+00:12:16,780 --> 00:12:18,980
+association role هذا معناته في عندي مشكلة
+
+169
+00:12:18,980 --> 00:12:23,060
+وبالتانية ال role هذا لازم انا اتخلص منها هيك ممكن
+
+170
+00:12:23,060 --> 00:12:25,200
+احنا خلصنا محتويات ال chapter ان شاء الله تعالى
+
+171
+00:12:25,200 --> 00:12:29,470
+خلينا نروحبنشوف المثال اللي قمت بعمله مسبقاً في
+
+172
+00:12:29,470 --> 00:12:30,390
+الـ PyShare
+
+173
+00:12:54,110 --> 00:12:56,910
+طيب جماعة الخير خلينا نكمل في الفيلم نشوف ال
+
+174
+00:12:56,910 --> 00:13:00,630
+example
+
+175
+00:13:00,630 --> 00:13:04,410
+اللى موجود عندنا انا الان فروح جوجل اعمل import لل
+
+176
+00:13:04,410 --> 00:13:11,030
+pandas وعملي بدي ابني data set transaction من six
+
+177
+00:13:11,030 --> 00:13:17,040
+rows من ست صفوف و بدي اعمل import للعن طريق الـ
+
+178
+00:13:17,040 --> 00:13:20,540
+machine learning extend بدي processing import
+
+179
+00:13:20,540 --> 00:13:23,480
+transaction encoder وهذا ال transaction encoder
+
+180
+00:13:23,480 --> 00:13:27,080
+انا هستخدمه من أجل انه يتحول ال data set اللي
+
+181
+00:13:27,080 --> 00:13:31,900
+لديها ال data set هذه ل binary array وكذلك من ال
+
+182
+00:13:31,900 --> 00:13:34,840
+نفس ال machine learning extend بدي استخدم ال
+
+183
+00:13:34,840 --> 00:13:39,180
+frequent pattern وعملها import لل apriori هشوف في
+
+184
+00:13:39,180 --> 00:13:41,660
+ال hand ال apriori وفي المثال في ال code اللي
+
+185
+00:13:41,660 --> 00:13:42,680
+وراها هشوف
+
+186
+00:13:46,820 --> 00:13:48,400
+الخطوة الأولى كما قلنا في الفيديو الأولى هي ال
+
+187
+00:13:48,400 --> 00:13:51,640
+data set transactional data set طبعا انا انشأت
+
+188
+00:13:51,640 --> 00:13:55,540
+menu اللى بحسب المثال اللى موجود هنا سابقا حكيته
+
+189
+00:13:55,540 --> 00:13:59,940
+يعنى الخطوة الأولى انا استدعيت ل transaction
+
+190
+00:13:59,940 --> 00:14:05,860
+encoder تمام عشان احول ال array هذا ل 2d array بعد
+
+191
+00:14:05,860 --> 00:14:11,350
+الخطوة التالية روحت قلت له انا transactionalعن
+
+192
+00:14:11,350 --> 00:14:16,830
+طريق اتساوية TE.FET.TRANSFORM للـ data set اللي
+
+193
+00:14:16,830 --> 00:14:21,430
+موجود عندها و لما احاول ان اكتب قمر طبعا عشان اشوف
+
+194
+00:14:21,430 --> 00:14:26,110
+ال code اللي موجود عندها بعد هيك ال transaction ال
+
+195
+00:14:26,110 --> 00:14:28,750
+array تبعت اللي هي ال binary ال race ان سميها زي
+
+196
+00:14:28,750 --> 00:14:36,780
+ما بدك بندس data frame روح تحولت ل data frameهنا
+
+197
+00:14:36,780 --> 00:14:43,380
+في الأول انشأت data set عادية الري حولتها ل binary
+
+198
+00:14:43,380 --> 00:14:46,240
+array و الأن بدي أحولها ل data frame عشان ده من
+
+199
+00:14:46,240 --> 00:14:50,980
+خلال ال pandas أقدر أتعامل معاها و قلت له هيستخدم
+
+200
+00:14:50,980 --> 00:14:56,000
+ال columnsهذا الـ array الموجودة عندها كcolumn لمن
+
+201
+00:14:56,000 --> 00:15:01,000
+ال data frame اللي موجودة عندها الآن قلت له ال
+
+202
+00:15:01,000 --> 00:15:04,380
+frequent item set تبعتي تساوي ال a priori اللي انا
+
+203
+00:15:04,380 --> 00:15:09,720
+عملته on board فوق ال data frame work ال data
+
+204
+00:15:09,720 --> 00:15:12,700
+frame تبعتي هي ال minimum support اللي انا بدي
+
+205
+00:15:12,700 --> 00:15:18,220
+اشتغل عليها ستة واستخدم ال column names yes
+
+206
+00:15:18,220 --> 00:15:23,140
+استخدمهم لان انا بتتعامل مع ال columnاللي بتمثل
+
+207
+00:15:23,140 --> 00:15:25,980
+الـ attribute of value أو الـ items في ال sets
+
+208
+00:15:25,980 --> 00:15:31,020
+اللي موجودة عندي ما تنسوش ان ال data set هنا مافيش
+
+209
+00:15:31,020 --> 00:15:36,740
+فيها columns هي عبارة عن items فلما انا حولتها ل
+
+210
+00:15:36,740 --> 00:15:41,560
+binary data set او binary 2D array صارت ال milk و
+
+211
+00:15:41,560 --> 00:15:47,840
+ال onion و ال .. ميج و ال ..والـ items هاي عبارة
+
+212
+00:15:47,840 --> 00:15:50,660
+عن attributes أو أسماء الـ attributes و ال value
+
+213
+00:15:50,660 --> 00:15:52,860
+تبعتهم ال true و ال false ولكن هنشوفها في الموضوع
+
+214
+00:15:52,860 --> 00:15:57,330
+لما انا اروح عند عملية الطبعةعشان هي قلت له
+
+215
+00:15:57,330 --> 00:16:02,370
+استخدمها لأن ال data set مبنية على ال names على
+
+216
+00:16:02,370 --> 00:16:06,290
+المسميات وبالتالي ال frequent item set فرح جاب
+
+217
+00:16:06,290 --> 00:16:08,610
+ليها ليش؟ أنا قلت له ال minimum support لأنه ممكن
+
+218
+00:16:08,610 --> 00:16:11,710
+تتجهل من هناك ال support انت حر ممكن تتغيرها حسب
+
+219
+00:16:11,710 --> 00:16:15,870
+الحالة واتفقنا كل ما بقل ال support بتزيد عدد ال
+
+220
+00:16:15,870 --> 00:16:19,150
+minimum أو ال frequent item set فروحت طبعة ال
+
+221
+00:16:19,150 --> 00:16:24,650
+frequent item setعشان انا اجيب ال item set روحت من
+
+222
+00:16:24,650 --> 00:16:28,850
+نفس المكتبة تبعتي ال frequent patterns اللي عملت
+
+223
+00:16:28,850 --> 00:16:32,690
+منها support او import لل a priori روحت استدعيت
+
+224
+00:16:32,690 --> 00:16:37,050
+مين اللي عملت import لل association rules وقلت له
+
+225
+00:16:37,050 --> 00:16:41,630
+ال list تبع ال rules تساوي ال frequent item setقمت
+
+226
+00:16:41,630 --> 00:16:45,490
+بالاستخدام الاستخدام الخاص بالاسوشيشن رول و قمت
+
+227
+00:16:45,490 --> 00:16:53,590
+بالطبع بإطباع الهاتف الخاص بالهاتف الخاص بالهاتف
+
+228
+00:16:53,590 --> 00:16:53,770
+الخاص بالهاتف الخاص بالهاتف الخاص بالهاتف الخاص
+
+229
+00:16:53,770 --> 00:16:54,250
+بالهاتف الخاص بالهاتف الخاص بالهاتف الخاص بالهاتف
+
+230
+00:16:54,250 --> 00:16:54,490
+الخاص بالهاتف الخاص بالهاتف الخاص بالهاتف الخاص
+
+231
+00:16:54,490 --> 00:16:54,530
+بالهاتف الخاص بالهاتف الخاص بالهاتف الخاص بالهاتف
+
+232
+00:16:54,530 --> 00:16:54,530
+الخاص بالهاتف الخاص بالهاتف الخاص بالهاتف الخاص
+
+233
+00:16:54,530 --> 00:16:54,530
+بالهاتف الخاص بالهاتف الخاص بالهاتف الخاص بالهاتف
+
+234
+00:16:54,530 --> 00:16:54,570
+الخاص بالهاتف الخاص بالهاتف الخاص بالهاتف الخاص
+
+235
+00:16:54,570 --> 00:16:59,450
+بالهاتف الخاص بالهاتف الخاص بالهاتف الخاص بالهاتف
+
+236
+00:16:59,450 --> 00:17:03,190
+الخاصطبعا انا طبعت على تلت مرات في تلت جمال قباعة
+
+237
+00:17:03,190 --> 00:17:07,670
+الجملة الأولى كانت ب ال array او اللي احنا سميتها
+
+238
+00:17:07,670 --> 00:17:12,810
+ب binary2d array هيو راح اطبع لل array اللي موجودة
+
+239
+00:17:12,810 --> 00:17:19,250
+عندي من ست صفوف true
+
+240
+00:17:19,250 --> 00:17:20,030
+false
+
+241
+00:17:25,230 --> 00:17:28,910
+الجملة التانية جملة الطباعة كانت بتطبع ال item set
+
+242
+00:17:28,910 --> 00:17:32,590
+اللي عندي و ال support تبعتها فرح جالي هاي ال item
+
+243
+00:17:32,590 --> 00:17:35,350
+set و طبعا لما انا قلتله استخدم اسماء ال
+
+244
+00:17:35,350 --> 00:17:40,650
+attributes فهيش راح جابلي ال eggs و جابليها هان لو
+
+245
+00:17:40,650 --> 00:17:45,030
+انا قلتله نوم مش حطين عندي هاي ال minimum support
+
+246
+00:17:45,030 --> 00:17:53,650
+ال 6 من 10 اللي موجودة عندك هانفجاب لي هناك ست
+
+247
+00:17:53,650 --> 00:17:58,610
+عراصر فعليا مختلفة او عفوا ست frequent item sets
+
+248
+00:17:58,610 --> 00:18:01,970
+with minimum support بعتهم ستة من عشرة انا قصدت ان
+
+249
+00:18:01,970 --> 00:18:05,050
+اجربها مبتقال مثلها الاخر فالجملة الأخيرة لما قلت
+
+250
+00:18:05,050 --> 00:18:07,950
+له انا هات ال association rule فراح قال لي ال
+
+251
+00:18:07,950 --> 00:18:12,570
+association rule هي ال antecedent او ال consequent
+
+252
+00:18:12,570 --> 00:18:17,610
+طبعا في الأول ال antecedent implies ال consequent
+
+253
+00:18:17,770 --> 00:18:21,450
+هو الـ antecedent support وطبعاً في معلومات هنا
+
+254
+00:18:21,450 --> 00:18:27,630
+خفية لأن شاشة العرض أعتقد أنها غير كافية للتعامل
+
+255
+00:18:27,630 --> 00:18:31,630
+مع الأنصار الموجودة عندها لكن في الآخر قال لي هيي
+
+256
+00:18:31,630 --> 00:18:37,880
+ال left وفي عند ال averageطبعا ال lift واحد يعني
+
+257
+00:18:37,880 --> 00:18:42,400
+ال attributes اللي عندى independent فعليا هم مبدأش
+
+258
+00:18:42,400 --> 00:18:45,240
+يوجد علاقة وبالتالي انا ممكن اكتفي بال support وال
+
+259
+00:18:45,240 --> 00:18:51,800
+confidence اللي موجودة عندنا طيب لو انا بدى اروح
+
+260
+00:18:51,800 --> 00:18:55,900
+طبعا خليني بس نجرب هان زى ما قلنا هاي هان خمسة او
+
+261
+00:18:55,900 --> 00:19:02,580
+بلاش اربعة من عشرةهذه هي ترشيلتي الخاصة بيها
+
+262
+00:19:16,120 --> 00:19:22,460
+عندما قلت له
+
+263
+00:19:22,460 --> 00:19:26,660
+خلّي ال confidence خمسة من عشرة فقال لي عندي تلاتة
+
+264
+00:19:26,660 --> 00:19:33,440
+و عشرين rules association و ال support تبعتهم هيها
+
+265
+00:19:47,420 --> 00:19:51,500
+العناصر الموجودة هنا
+
+266
+00:20:10,880 --> 00:20:15,900
+بس ليش مايعرضهاش مش عارف الصحيح بس في الآخر ال
+
+267
+00:20:15,900 --> 00:20:19,200
+data موجودة عليها طيب بالمثال التاني لما انا بدأ
+
+268
+00:20:19,200 --> 00:20:23,800
+استخدم ال app ال fp growth ولشه مجرد بدك تستخدم
+
+269
+00:20:23,800 --> 00:20:28,740
+بكتب اسمه python fp growth هي نفس ال data set قلت
+
+270
+00:20:28,740 --> 00:20:32,860
+له ال frequent pattern تبعتي ال minimum support
+
+271
+00:20:32,860 --> 00:20:37,680
+تبعتي equal 3وهنا ايقول الـ 7 من 10 مش 6 من 10
+
+272
+00:20:37,680 --> 00:20:43,020
+عفوا الحسب زي ما انا .. طبعا هنا التجريب هيرن
+
+273
+00:20:43,020 --> 00:20:51,140
+للمثال اللي موجود هنا طبعا
+
+274
+00:20:51,140 --> 00:20:56,240
+هنا بتتكلم على الابريوليه وان كان هنا ال FB growth
+
+275
+00:20:56,240 --> 00:20:58,460
+defined frequent pattern ال data ال data set
+
+276
+00:20:58,460 --> 00:21:03,100
+مباشرة لاحظوا انا جزئيتي التحويل مش مسئوليتي اصلا
+
+277
+00:21:04,100 --> 00:21:10,120
+لان بشتغل على ال data set مباشرة اتنين مجرد كان
+
+278
+00:21:10,120 --> 00:21:11,820
+السبعة مباشرة طبعا اسهل في ال coding
+
+279
+00:21:17,200 --> 00:21:20,040
+الـ FD Growth and Generate Association Rules فقلت
+
+280
+00:21:20,040 --> 00:21:22,060
+له انا هاي ال better او هاي ال association
+
+281
+00:21:22,060 --> 00:21:26,540
+التابعتي تمام ال better التابعي هيه ال milk طبعا
+
+282
+00:21:26,540 --> 00:21:32,060
+اتفقنا ان ال better هي عبارة عن العناصر اللي انا
+
+283
+00:21:32,060 --> 00:21:37,040
+عامالي بجيبها طبعا هو بدأ مع انصر وانصرين الاخرين
+
+284
+00:21:37,040 --> 00:21:39,740
+لما راح جاب ال association rule و كيف بدأ اقرأ ال
+
+285
+00:21:39,740 --> 00:21:42,680
+rules هي ال rule الأول طبعا هي عبارة عن جيسون في
+
+286
+00:21:42,680 --> 00:21:45,840
+الآخر النتيجة تبعتي للي ال rule الأول هي
+
+287
+00:21:51,680 --> 00:21:57,640
+الملك يعني كيندي
+
+288
+00:21:57,640 --> 00:22:02,680
+بيز واليوغرد وهذا ال confidence تبعتها خمسة أو
+
+289
+00:22:02,680 --> 00:22:10,240
+سبعين في المية التانية ال support تبعتها مية في
+
+290
+00:22:10,240 --> 00:22:14,080
+المية إلى آخرهم من العراسر ال confidence عفوا من
+
+291
+00:22:14,080 --> 00:22:16,980
+العراسر الموجودة هناهذه كانت جامعة الخير ..
+
+292
+00:22:16,980 --> 00:22:24,540
+انتهينا من موضوع ال .. ال association role .. هرفق
+
+293
+00:22:24,540 --> 00:22:29,580
+لكم ملفين ال coding هنا .. عشان تجربوا في موضوع ..
+
+294
+00:22:29,580 --> 00:22:35,440
+لو بقيت تجرب .. شغلة عندك .. وتشوف ال result اللي
+
+295
+00:22:35,440 --> 00:22:37,260
+موجود .. الله يعطيكم العافية .. والسلام عليكم
+
+296
+00:22:37,260 --> 00:22:37,720
+ورحمة الله
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/aBdn0U7iDfc_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/aBdn0U7iDfc_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..8ceb5dfe2a38de2779b1862b962121f970719c10
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/aBdn0U7iDfc_raw.json
@@ -0,0 +1 @@
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اللي عندي finite set ليش يعني finite set؟ مجموعة محددة فبقول عنها إيش؟ nominal بقول عنها nominal مثل ال fruits اللي أنا ممكن أتعامل معاها ال fruits اللي بنتعامل معاها جدش عددها؟", "tokens": [6027, 148, 48506, 32771, 6027, 3555, 995, 4386, 32771, 6027, 3555, 995, 11933, 15730, 25961, 2655, 2423, 2487, 13672, 1829, 18871, 16254, 4386, 2423, 2487, 13672, 1829, 18871, 16254, 19362, 992, 32239, 8592, 37495, 22653, 19362, 992, 22807, 3714, 7435, 2304, 2407, 27884, 3714, 24401, 41891, 6156, 3555, 39648, 18871, 11296, 11933, 1829, 8592, 22807, 41641, 4724, 39648, 18871, 11296, 41641, 50113, 1211, 2423, 12148, 13672, 1829, 41850, 3714, 43020, 5551, 2655, 3615, 10943, 1211, 20449, 995, 11296, 2423, 12148, 13672, 1829, 4724, 29399, 3615, 10943, 1211, 20449, 995, 11296, 10874, 3215, 8592, 6225, 3215, 3215, 11296, 22807], "avg_logprob": -0.1723484911701896, "compression_ratio": 1.9270833333333333, "no_speech_prob": 0.0, "words": [{"start": 862.85, "end": 863.23, "word": "الآن", "probability": 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0.60205078125}, {"start": 1056.24, "end": 1056.6, "word": " صح؟", "probability": 0.92431640625}], "temperature": 1.0}, {"id": 43, "seek": 108536, "start": 1056.93, "end": 1085.37, "text": "بالآخر احنا هنا بنتكلم بشباب عشان ما نبعدش كتير على المسميات أو الحالات اللي بتهمني لو انا اجيت سألت الأقسام أو أسماء الأقسام أو أرقام الأقسام مثلا Computer Science 901 تطوير برمجيات 902 901 و 902 بنفع نقول عنها nominal؟ اه nominal ليش؟ لأن هذه بتمثل category بتمثل فئة", "tokens": [3555, 6027, 148, 95, 34740, 1975, 5016, 8315, 34105, 44945, 2655, 4117, 19528, 4724, 8592, 3555, 16758, 6225, 8592, 7649, 19446, 8717, 3555, 22488, 8592, 9122, 2655, 13546, 15844, 9673, 38251, 1829, 9307, 34051, 21542, 6027, 9307, 13672, 1829, 39894, 16095, 22653, 45164, 1975, 8315, 1975, 7435, 36081, 8608, 10721, 1211, 2655, 16247, 4587, 3794, 10943, 34051, 5551, 38251, 16606, 16247, 4587, 3794, 10943, 34051, 5551, 2288, 4587, 10943, 16247, 4587, 3794, 10943, 50113, 15040, 22289, 8976, 4289, 16, 6055, 9566, 2407, 13546, 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"probability": 0.911376953125}, {"start": 1074.51, "end": 1075.03, "word": " برمجيات", "probability": 0.9775390625}, {"start": 1075.03, "end": 1075.89, "word": " 902", "probability": 0.97900390625}, {"start": 1075.89, "end": 1077.07, "word": " 901", "probability": 0.885009765625}, {"start": 1077.07, "end": 1077.25, "word": " و", "probability": 0.82275390625}, {"start": 1077.25, "end": 1078.09, "word": " 902", "probability": 0.89794921875}, {"start": 1078.09, "end": 1079.91, "word": " بنفع", "probability": 0.75439453125}, {"start": 1079.91, "end": 1080.09, "word": " نقول", "probability": 0.781005859375}, {"start": 1080.09, "end": 1080.29, "word": " عنها", "probability": 0.994384765625}, {"start": 1080.29, "end": 1081.41, "word": " nominal؟", "probability": 0.6539306640625}, {"start": 1081.41, "end": 1082.37, "word": " اه", "probability": 0.706298828125}, {"start": 1082.37, "end": 1082.77, "word": " nominal", "probability": 0.97998046875}, {"start": 1082.77, "end": 1083.77, "word": " ليش؟", "probability": 0.78076171875}, {"start": 1083.77, "end": 1083.89, "word": " لأن", "probability": 0.860107421875}, {"start": 1083.89, "end": 1084.01, "word": " هذه", "probability": 0.2369384765625}, {"start": 1084.01, "end": 1084.37, "word": " بتمثل", "probability": 0.9427490234375}, {"start": 1084.37, "end": 1084.73, "word": " category", "probability": 0.82666015625}, {"start": 1084.73, "end": 1085.05, "word": " بتمثل", "probability": 0.8411865234375}, {"start": 1085.05, "end": 1085.37, "word": " فئة", "probability": 0.9659830729166666}], "temperature": 1.0}, {"id": 44, "seek": 111491, "start": 1085.87, "end": 1114.91, "text": "بغض النظر عن القيمة اللي أنا كتبتها لكن لو انا اجيت و قلتلك في عندي مجموعة بتمثل ال first second و ال third شو رأيكوا؟ هل هذه ممكن nominal؟ nominal", "tokens": [3555, 17082, 11242, 28239, 19913, 2288, 18871, 25062, 32640, 3660, 13672, 1829, 41850, 9122, 2655, 3555, 2655, 11296, 44381, 45164, 1975, 8315, 1975, 7435, 36081, 4032, 12174, 1211, 2655, 23275, 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بتكلم على categories أو أسماء أو تلات أصنافات الأول والتاني والتالت مصبوط؟ خلنا نقول الفائزين أو ال winners الأول والتاني والتالت لكن هذه فيها ميزة مش موجودة في ال colors في المجموع اللي فوق", "tokens": [15819, 2071, 4724, 3794, 5551, 9381, 26890, 25894, 8315, 41641, 4724, 3794, 10874, 995, 37746, 22653, 41641, 11778, 3224, 41641, 41641, 8032, 47302, 41641, 5296, 33456, 3224, 6156, 3615, 20292, 995, 12174, 995, 22488, 39894, 4117, 19528, 15844, 10479, 34051, 5551, 38251, 16606, 34051, 6055, 1211, 9307, 5551, 9381, 8315, 5172, 9307, 16247, 12610, 16070, 2655, 7649, 1829, 16070, 2655, 6027, 2655, 3714, 9381, 3555, 2407, 9566, 22807, 16490, 1211, 8315, 8717, 39648, 27188, 16373, 11622, 9957, 34051, 2423, 17193, 16247, 12610, 16070, 2655, 7649, 1829, 16070, 2655, 6027, 2655, 44381, 29538, 8978, 11296, 3714, 1829, 11622, 3660, 37893, 3714, 29245, 23328, 3660, 8978, 2423, 4577, 8978, 9673, 7435, 2304, 45367, 13672, 1829, 6156, 30543], "avg_logprob": -0.1990840500541802, "compression_ratio": 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"word": " الأول", "probability": 0.966064453125}, {"start": 1138.33, "end": 1138.73, "word": " والتاني", "probability": 0.98388671875}, {"start": 1138.73, "end": 1139.29, "word": " والتالت", "probability": 0.9766845703125}, {"start": 1139.29, "end": 1140.25, "word": " لكن", "probability": 0.9091796875}, {"start": 1140.25, "end": 1140.69, "word": " هذه", "probability": 0.74755859375}, {"start": 1140.69, "end": 1141.09, "word": " فيها", "probability": 0.9853515625}, {"start": 1141.09, "end": 1141.75, "word": " ميزة", "probability": 0.9932861328125}, {"start": 1141.75, "end": 1142.73, "word": " مش", "probability": 0.98876953125}, {"start": 1142.73, "end": 1143.23, "word": " موجودة", "probability": 0.984619140625}, {"start": 1143.23, "end": 1143.35, "word": " في", "probability": 0.95263671875}, {"start": 1143.35, "end": 1143.45, "word": " ال", "probability": 0.9658203125}, {"start": 1143.45, "end": 1143.81, "word": " colors", "probability": 0.7607421875}, {"start": 1143.81, "end": 1144.81, "word": " في", "probability": 0.748046875}, {"start": 1144.81, "end": 1145.15, "word": " المجموع", "probability": 0.918212890625}, {"start": 1145.15, "end": 1145.29, "word": " اللي", "probability": 0.893310546875}, {"start": 1145.29, "end": 1145.59, "word": " فوق", "probability": 0.9638671875}], "temperature": 1.0}, {"id": 46, "seek": 117782, "start": 1149.08, "end": 1177.82, "text": "إن القيمة إلها معنى معنى ترتيبي بمعنى آخر لو أنا إجيت قولت ال color تبعي blue my favorite color blue واحد تاني هيقولي white بتفرج؟ هل بين جسين في أولوية للأبيض عن الأزرق أو العكس؟ لأ مافيش لكن لما إجيت أنا قولت ال first", "tokens": [28814, 1863, 25062, 32640, 3660, 11933, 1211, 11296, 20449, 1863, 7578, 20449, 1863, 7578, 6055, 2288, 31371, 21292, 4724, 2304, 3615, 1863, 7578, 19753, 34740, 45164, 41850, 11933, 7435, 36081, 12174, 12610, 2655, 2423, 2017, 6055, 3555, 3615, 1829, 3344, 452, 2954, 2017, 3344, 36764, 24401, 6055, 7649, 1829, 39896, 39648, 1829, 2418, 39894, 5172, 47341, 22807, 8032, 1211, 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1160.58, "end": 1160.94, "word": " blue", "probability": 0.9287109375}, {"start": 1160.94, "end": 1161.62, "word": " واحد", "probability": 0.820556640625}, {"start": 1161.62, "end": 1161.9, "word": " تاني", "probability": 0.970703125}, {"start": 1161.9, "end": 1162.26, "word": " هيقولي", "probability": 0.7091471354166666}, {"start": 1162.26, "end": 1162.72, "word": " white", "probability": 0.91162109375}, {"start": 1162.72, "end": 1168.04, "word": " بتفرج؟", "probability": 0.72833251953125}, {"start": 1168.04, "end": 1169.72, "word": " هل", "probability": 0.765625}, {"start": 1169.72, "end": 1169.9, "word": " بين", "probability": 0.9462890625}, {"start": 1169.9, "end": 1170.36, "word": " جسين", "probability": 0.70556640625}, {"start": 1170.36, "end": 1170.82, "word": " في", "probability": 0.88623046875}, {"start": 1170.82, "end": 1171.44, "word": " أولوية", "probability": 0.859130859375}, {"start": 1171.44, "end": 1171.92, "word": " للأبيض", "probability": 0.9224853515625}, {"start": 1171.92, "end": 1172.16, "word": " عن", "probability": 0.97412109375}, {"start": 1172.16, "end": 1172.7, "word": " الأزرق", "probability": 0.8736572265625}, {"start": 1172.7, "end": 1172.98, "word": " أو", "probability": 0.59619140625}, {"start": 1172.98, "end": 1173.74, "word": " العكس؟", "probability": 0.9024658203125}, {"start": 1173.74, "end": 1173.88, "word": " لأ", "probability": 0.837890625}, {"start": 1173.88, "end": 1174.3, "word": " مافيش", "probability": 0.84814453125}, {"start": 1174.3, "end": 1175.0, "word": " لكن", "probability": 0.73486328125}, {"start": 1175.0, "end": 1175.24, "word": " لما", "probability": 0.923583984375}, {"start": 1175.24, "end": 1175.54, "word": " إجيت", "probability": 0.890625}, {"start": 1175.54, "end": 1175.72, "word": " أنا", "probability": 0.73046875}, {"start": 1175.72, "end": 1176.2, "word": " قولت", "probability": 0.9490559895833334}, {"start": 1176.2, "end": 1177.24, "word": " ال", "probability": 0.841796875}, {"start": 1177.24, "end": 1177.82, "word": " first", "probability": 0.91845703125}], "temperature": 1.0}, {"id": 47, "seek": 120847, "start": 1182.71, "end": 1208.47, "text": "winner وقلت ال second او ال third winner وال second winner تفرج ال values عن بعضها تفرج على الرغم انها categorian وهذا يجعلنا نروح باتجاه فئة جديدة اللي هي ال ordinal هيتكلم و يوداني على فئة جديدة اللي هي فئات ال ordinal تمام يا جماعة الخير؟", "tokens": [9136, 1193, 4032, 4587, 1211, 2655, 2423, 1150, 1975, 2407, 2423, 2636, 8507, 16070, 1150, 8507, 6055, 5172, 47341, 2423, 4190, 18871, 45030, 11242, 11296, 6055, 5172, 47341, 15844, 34892, 17082, 2304, 16472, 11296, 19250, 952, 37037, 15730, 7251, 7435, 30241, 8315, 8717, 32887, 5016, 4724, 9307, 7435, 40294, 6156, 19986, 3660, 10874, 16254, 41891, 13672, 1829, 39896, 2423, 4792, 2071, 8032, 36081, 4117, 19528, 4032, 7251, 23328, 7649, 1829, 15844, 6156, 19986, 3660, 10874, 16254, 41891, 13672, 1829, 39896, 6156, 19986, 9307, 2423, 4792, 2071, 46811, 10943, 35186, 10874, 15042, 27884, 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"probability": 0.680908203125}, {"start": 1197.63, "end": 1198.11, "word": " يجعلنا", "probability": 0.76708984375}, {"start": 1198.11, "end": 1198.31, "word": " نروح", "probability": 0.9080403645833334}, {"start": 1198.31, "end": 1198.87, "word": " باتجاه", "probability": 0.9422607421875}, {"start": 1198.87, "end": 1199.73, "word": " فئة", "probability": 0.9542643229166666}, {"start": 1199.73, "end": 1200.27, "word": " جديدة", "probability": 0.98583984375}, {"start": 1200.27, "end": 1200.45, "word": " اللي", "probability": 0.60595703125}, {"start": 1200.45, "end": 1200.77, "word": " هي", "probability": 0.9443359375}, {"start": 1200.77, "end": 1201.13, "word": " ال", "probability": 0.9267578125}, {"start": 1201.13, "end": 1201.71, "word": " ordinal", "probability": 0.81396484375}, {"start": 1201.71, "end": 1202.63, "word": " هيتكلم", "probability": 0.71722412109375}, {"start": 1202.63, "end": 1202.81, "word": " و", "probability": 0.303466796875}, {"start": 1202.81, "end": 1203.75, "word": " يوداني", "probability": 0.61212158203125}, {"start": 1203.75, "end": 1203.87, "word": " على", "probability": 0.71533203125}, {"start": 1203.87, "end": 1204.11, "word": " فئة", "probability": 0.98388671875}, {"start": 1204.11, "end": 1204.57, "word": " جديدة", "probability": 0.98828125}, {"start": 1204.57, "end": 1204.83, "word": " اللي", "probability": 0.8447265625}, {"start": 1204.83, "end": 1204.91, "word": " هي", "probability": 0.9560546875}, {"start": 1204.91, "end": 1205.33, "word": " فئات", "probability": 0.7464192708333334}, {"start": 1205.33, "end": 1206.09, "word": " ال", "probability": 0.947265625}, {"start": 1206.09, "end": 1206.63, "word": " ordinal", "probability": 0.8525390625}, {"start": 1206.63, "end": 1207.69, "word": " تمام", "probability": 0.988037109375}, {"start": 1207.69, "end": 1207.77, "word": " يا", "probability": 0.763671875}, {"start": 1207.77, "end": 1207.93, "word": " جماعة", "probability": 0.99462890625}, {"start": 1207.93, "end": 1208.47, "word": " الخير؟", "probability": 0.8714192708333334}], "temperature": 1.0}, {"id": 48, "seek": 123848, "start": 1208.84, "end": 1238.48, "text": "الأن يعني ال ordinal هي عبارة عن حالة خاصة حالة خاصة من من ال categorial أو من ال nominal بحيث إنه في عندي معنى أو sequence موجودة في معاني الكلمات مش بالضرورة تظهر بال sequence بس القيمة إلها معنى ترتيبي تماما مثل الرتب العسكرية بيجي يقولني نقيب و رقيب صح؟", "tokens": [6027, 33456, 37495, 22653, 2423, 4792, 2071, 39896, 6225, 3555, 9640, 3660, 18871, 11331, 6027, 3660, 16490, 33546, 3660, 11331, 6027, 3660, 16490, 33546, 3660, 9154, 9154, 2423, 19250, 831, 34051, 9154, 2423, 41641, 4724, 5016, 1829, 12984, 36145, 3224, 8978, 18871, 16254, 20449, 1863, 7578, 34051, 8310, 3714, 29245, 23328, 3660, 8978, 20449, 7649, 1829, 33251, 19528, 9307, 37893, 20666, 11242, 2288, 13063, 3660, 6055, 19913, 3224, 2288, 20666, 8310, 4724, 3794, 25062, 32640, 3660, 11933, 1211, 11296, 20449, 1863, 7578, 6055, 2288, 31371, 21292, 46811, 10943, 995, 50113, 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"probability": 0.9967041015625}, {"start": 1227.58, "end": 1227.72, "word": " بال", "probability": 0.939453125}, {"start": 1227.72, "end": 1228.24, "word": " sequence", "probability": 0.93701171875}, {"start": 1228.24, "end": 1229.0, "word": " بس", "probability": 0.950927734375}, {"start": 1229.0, "end": 1229.5, "word": " القيمة", "probability": 0.978515625}, {"start": 1229.5, "end": 1229.72, "word": " إلها", "probability": 0.7220052083333334}, {"start": 1229.72, "end": 1230.04, "word": " معنى", "probability": 0.99462890625}, {"start": 1230.04, "end": 1230.6, "word": " ترتيبي", "probability": 0.9351806640625}, {"start": 1230.6, "end": 1231.94, "word": " تماما", "probability": 0.9811197916666666}, {"start": 1231.94, "end": 1232.16, "word": " مثل", "probability": 0.969970703125}, {"start": 1232.16, "end": 1232.46, "word": " الرتب", "probability": 0.8896484375}, {"start": 1232.46, "end": 1233.08, "word": " العسكرية", "probability": 0.9766845703125}, {"start": 1233.08, "end": 1236.02, "word": " بيجي", "probability": 0.882568359375}, {"start": 1236.02, "end": 1236.26, "word": " يقولني", "probability": 0.6857096354166666}, {"start": 1236.26, "end": 1236.58, "word": " نقيب", "probability": 0.87060546875}, {"start": 1236.58, "end": 1236.66, "word": " و", "probability": 0.978515625}, {"start": 1236.66, "end": 1237.1, "word": " رقيب", "probability": 0.9334309895833334}, {"start": 1237.1, "end": 1238.48, "word": " صح؟", "probability": 0.8294270833333334}], "temperature": 1.0}, {"id": 49, "seek": 126102, "start": 1239.72, "end": 1261.02, "text": "عقيد ولواء أو ملازم وملازم أول فهي كل واحدة فيهم الرتبة بتفرج عن التاني على الرغم إنها categorial فئة مصبوط فئة الملازمين فئة العقدة فئة العمدة إلى آخرهم فبالتالي أنا جاعت بأتكلم .. أتكلم على فئات أتكلم على فئات لكنه الكلمات تحمل دلالة ترتيبية", "tokens": [3615, 4587, 25708, 4032, 1211, 2407, 16606, 34051, 3714, 1211, 31377, 2304, 4032, 42213, 31377, 2304, 5551, 12610, 6156, 3224, 1829, 28242, 36764, 24401, 3660, 8978, 16095, 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1358.24, "word": " بال", "probability": 0.491455078125}, {"start": 1358.24, "end": 1358.48, "word": " value", "probability": 0.9755859375}, {"start": 1358.48, "end": 1358.78, "word": " أكتر", "probability": 0.9267578125}, {"start": 1358.78, "end": 1358.94, "word": " من", "probability": 0.99365234375}, {"start": 1358.94, "end": 1359.38, "word": " التانية", "probability": 0.9612630208333334}, {"start": 1359.38, "end": 1360.52, "word": " مثلا", "probability": 0.934814453125}, {"start": 1360.52, "end": 1361.1, "word": " لما", "probability": 0.705078125}, {"start": 1361.1, "end": 1361.32, "word": " بدي", "probability": 0.647216796875}, {"start": 1361.32, "end": 1361.88, "word": " بتكلم", "probability": 0.92333984375}, {"start": 1361.88, "end": 1362.3, "word": " على", "probability": 0.83056640625}, {"start": 1362.3, "end": 1362.7, "word": " ال", "probability": 0.90966796875}, {"start": 1362.7, "end": 1363.1, "word": " gender", "probability": 0.9599609375}, {"start": 1363.1, "end": 1365.02, 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الأهمية لكن لو كانت اللي بتكلم على ال diagnosis لفيروس او لمرض معين ال positive أهم مليون مرة من ال negative على الرغم ان ال negative موجود لكن قيمة ال positive high", "tokens": [2304, 9381, 3555, 2407, 9566, 1975, 2655, 1863, 9957, 44945, 36178, 16247, 16095, 10632, 44381, 45164, 25961, 2655, 13672, 1829, 39894, 4117, 19528, 15844, 2423, 15217, 5296, 5172, 13546, 41779, 1975, 2407, 5296, 29973, 11242, 20449, 9957, 2423, 3353, 5551, 16095, 3714, 20292, 11536, 3714, 25720, 9154, 2423, 3671, 15844, 34892, 17082, 2304, 16472, 2423, 3671, 3714, 29245, 23328, 44381, 12174, 32640, 3660, 2423, 3353, 1090], "avg_logprob": -0.20907182346529035, "compression_ratio": 1.6666666666666667, "no_speech_prob": 1.1920928955078125e-06, "words": [{"start": 1368.91, "end": 1369.43, "word": "مصبوط", "probability": 0.799072265625}, {"start": 1369.43, "end": 1369.91, "word": " اتنين", "probability": 0.75164794921875}, {"start": 1369.91, "end": 1370.17, "word": " بنفس", "probability": 0.976318359375}, 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التاني", "probability": 0.9075520833333334}], "temperature": 1.0}, {"id": 60, "seek": 155069, "start": 1522.65, "end": 1550.69, "text": "و هنا انا بأتكلم ضمن range ال value تبعتي ضمن range لاحظ باتكلمش على discrete و continuous باتكلم على ان القيمة تبعتي هذه تقاس تبعا لمجموعة من ال units لمجموعة من ال units مثال عليها ال temperature درجة الحرارة الآن لو جينا و قولنا درجة الحرارة في الغرفة هذه تقارب العشرين او عشرين", "tokens": [2407, 34105, 1975, 8315, 4724, 10721, 2655, 4117, 19528, 48812, 27842, 3613, 2423, 2158, 6055, 3555, 3615, 31371, 48812, 27842, 3613, 20193, 5016, 19913, 4724, 9307, 4117, 19528, 8592, 15844, 27706, 4032, 10957, 4724, 9307, 4117, 19528, 15844, 16472, 25062, 32640, 3660, 6055, 3555, 3615, 31371, 29538, 6055, 4587, 32277, 6055, 3555, 3615, 995, 32767, 7435, 2304, 2407, 27884, 9154, 2423, 6815, 32767, 7435, 2304, 2407, 27884, 9154, 2423, 6815, 50113, 6027, 25894, 11296, 2423, 4292, 11778, 47341, 3660, 21542, 2288, 9640, 3660, 6024, 48506, 45164, 10874, 1829, 8315, 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بعيد في الان؟ لما انا بتكلم على continuous .. او discrete", "tokens": [1211, 2407, 1975, 8315, 1975, 7435, 36081, 8608, 10721, 1211, 2655, 4117, 4724, 16254, 6225, 29973, 4117, 6055, 3215, 9957, 1829, 6225, 29973, 4117, 20666, 4386, 20666, 3794, 1863, 3660, 16070, 8592, 3224, 2288, 16070, 1829, 20498, 16070, 3794, 995, 27884, 16070, 3215, 38436, 28671, 16070, 12984, 7649, 10632, 3714, 43020, 7251, 1863, 5016, 35457, 12399, 3714, 9381, 3555, 13063, 22807, 23032, 1829, 3555, 12399, 2423, 7649, 29538, 2423, 28820, 10943, 32239, 8592, 6225, 2304, 6027, 4724, 5016, 995, 12610, 4724, 31377, 25708, 4032, 45030, 25708, 8978, 2423, 7649, 22807, 5296, 15042, 1975, 8315, 39894, 4117, 19528, 15844, 10957, 4386, 1975, 2407, 27706], "avg_logprob": -0.22295673549748385, "compression_ratio": 1.6851851851851851, "no_speech_prob": 0.0, "words": [{"start": 2405.73, "end": 2405.97, "word": "لو", "probability": 0.95263671875}, {"start": 2405.97, "end": 2406.13, "word": " انا", "probability": 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ممكن تكون هذه finite و discrete لأنه بين الملي والتاني gap عادة الامور هذه ممكن تعمل شوية ربكة بسيطة في التفريق في المقابل continuous", "tokens": [67, 5606, 7600, 1975, 15730, 41850, 39894, 4117, 19528, 20666, 9381, 1863, 9566, 1829, 31767, 1863, 9566, 1829, 16247, 12610, 16712, 7649, 1829, 16712, 6027, 2655, 34892, 16758, 3615, 33962, 10943, 3794, 5296, 24401, 16712, 1211, 9307, 9957, 4032, 45636, 995, 23032, 1211, 34268, 15844, 9673, 20292, 9307, 13672, 1829, 3714, 29245, 23328, 3660, 4724, 43042, 3224, 3714, 43020, 6055, 30544, 29538, 19362, 4032, 27706, 5296, 33456, 3224, 49374, 9673, 20292, 16070, 2655, 7649, 1829, 7417, 6225, 18513, 3660, 2423, 10943, 13063, 29538, 3714, 43020, 6055, 25957, 1211, 13412, 2407, 10632, 12602, 3555, 4117, 3660, 4724, 3794, 1829, 9566, 3660, 8978, 16712, 5172, 16572, 4587, 8978, 9673, 4587, 16758, 1211, 10957], "avg_logprob": -0.1520647264218756, "compression_ratio": 1.8553191489361702, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 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classification هذه كل ال data sets الآن في عنده تلاتمية و ستين data sets الأولى مثلا ال two gigahertz indoor channel measurement نتكلم عن ال wifi signals", "tokens": [3224, 24192, 39896, 2423, 1508, 1089, 399, 29538, 28242, 2423, 1412, 6352, 6024, 48506, 8978, 43242, 3224, 6055, 1211, 9307, 2304, 10632, 4032, 8608, 2655, 9957, 1412, 6352, 16247, 12610, 7578, 50113, 15040, 2423, 732, 8741, 64, 35655, 24029, 2269, 13160, 8717, 2655, 4117, 19528, 18871, 2423, 35246, 12354], "avg_logprob": -0.4846874952316284, "compression_ratio": 1.3496932515337423, "no_speech_prob": 0.0, "words": [{"start": 3590.0, "end": 3590.6, "word": "هذه", "probability": 0.49090576171875}, {"start": 3590.6, "end": 3590.6, "word": " هي", "probability": 0.65283203125}, {"start": 3590.6, "end": 3590.72, "word": " ال", "probability": 0.53515625}, {"start": 3590.72, "end": 3591.54, "word": " classification", "probability": 0.64208984375}, {"start": 3591.54, "end": 3592.38, "word": " هذه", "probability": 0.186767578125}, 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\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/aBdn0U7iDfc_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/aBdn0U7iDfc_raw.srt
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index 0000000000000000000000000000000000000000..c0e58fa1c28e63cf8b5ae674f5ef3ce6c23c14e5
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@@ -0,0 +1,3080 @@
+1
+00:00:05,030 --> 00:00:07,210
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:07,210 --> 00:00:11,270
+اليوم ان شاء الله تعالى هنكمل في ال chapter التاني
+
+3
+00:00:11,270 --> 00:00:16,410
+اللي هي data understanding وكنا حكينا المرات
+
+4
+00:00:16,410 --> 00:00:19,730
+الماضية على مجموعة او اتناقشنا في مجموعة من
+
+5
+00:00:19,730 --> 00:00:24,430
+الأسئلة اللي لها علاقة بفهم البياناتفي حد بيذكرنا
+
+6
+00:00:24,430 --> 00:00:28,250
+شباب مجموعة من الأسئلة كانت الأسئلة بتتمحور حوالين
+
+7
+00:00:28,250 --> 00:00:33,310
+شغلات أساسية اللي لها علاقة في فهم البيانات وإيش
+
+8
+00:00:33,310 --> 00:00:36,810
+المقصود وإيش البنيا من البيانات حد بيقدر يجاوبنا
+
+9
+00:00:36,810 --> 00:00:49,210
+حجم البيانات المتوفرة أيوة غيره هل
+
+10
+00:00:49,210 --> 00:00:54,710
+هناك مصادر أخرى لل data ممكن تدعمها غيرههل
+
+11
+00:00:54,710 --> 00:01:02,290
+الصلاحية .. هل البيانات هذه valid or invalid؟ كل
+
+12
+00:01:02,290 --> 00:01:07,790
+ال data حكاها السؤال، أيوةهل ال data artificial
+
+13
+00:01:07,790 --> 00:01:12,790
+ولا real data والسؤال الأهم من كل هذا هل ال data
+
+14
+00:01:12,790 --> 00:01:17,850
+هذه بتحل المشكلة هاي ولا لأ relevant to the
+
+15
+00:01:17,850 --> 00:01:21,450
+problem or not تمام لأنه لو ماكنتش relevant وكانت
+
+16
+00:01:21,450 --> 00:01:25,430
+valid وكانت كبيرة وفيها مصادر أخرى عالفاضي ماتنفعش
+
+17
+00:01:25,430 --> 00:01:28,570
+مع ال task اللي أنا بدي أشتغل عليها وكلنا اتكلمنا
+
+18
+00:01:28,570 --> 00:01:30,230
+أن أنواع البيانات بشكل عام
+
+19
+00:01:33,140 --> 00:01:36,220
+Structured Data اللي احنا متعامل مع الجداول وفي
+
+20
+00:01:36,220 --> 00:01:39,200
+عندي unstructured زي الصور و ال audio و ال text و
+
+21
+00:01:39,200 --> 00:01:42,880
+الاخره في عندك Dynamic Data انه بيصير في عندي
+
+22
+00:01:42,880 --> 00:01:46,860
+تحديث مستمر على البيانات اللي موجودة عندي وفي عندي
+
+23
+00:01:46,860 --> 00:01:50,360
+Static Data البيانات مابيصيرش عليها تحديل السؤال
+
+24
+00:01:50,360 --> 00:01:54,160
+الآن لو كان في عندي صورة و الصورة هذه انا بتصفحها
+
+25
+00:01:54,160 --> 00:01:58,910
+في اليوم عشر مرات بتغير على محتوى هالحاجةلأ
+
+26
+00:01:58,910 --> 00:02:01,390
+وبالتالي هي static واحد يقول يا دكتور لما هو ممكن
+
+27
+00:02:01,390 --> 00:02:04,750
+انا اروح اعدل عليها ال Photoshop كم مرة هتعدل
+
+28
+00:02:04,750 --> 00:02:09,370
+عليها مرتين تلاتة بس في الآخر هترجع static ومش
+
+29
+00:02:09,370 --> 00:02:11,890
+هتكون في ال data وزي ما قلنا المرة الماضية احنا
+
+30
+00:02:11,890 --> 00:02:19,090
+فعليا شغلنا هيكون في داخل ال static data الان ال
+
+31
+00:02:19,090 --> 00:02:24,470
+data set اللي عنديبشكل عام الان مش هقول عليها
+
+32
+00:02:24,470 --> 00:02:27,990
+database ولا هقول عليها data source هتصير هي
+
+33
+00:02:27,990 --> 00:02:31,970
+بمثابة data set اللي هي غالبا هتكون عبارة عن جدول
+
+34
+00:02:31,970 --> 00:02:36,430
+واحد بيجمع كل ال data اللي موجودة لما اتعامل معاها
+
+35
+00:02:36,430 --> 00:02:39,490
+الان ال data sets اللي عندي بدي أفهم ان هنا فيه
+
+36
+00:02:39,490 --> 00:02:42,740
+ممكن يكون عبارة عن مجموعة من ال recordsو ال record
+
+37
+00:02:42,740 --> 00:02:45,740
+إما من relational data أو data matrix مصفوفات
+
+38
+00:02:45,740 --> 00:02:51,560
+بتحتوي على بيانات document data ممكن يتحول ل
+
+39
+00:02:51,560 --> 00:02:54,940
+record بحيث إنه انا يكون في عندي مثلا في ال data
+
+40
+00:02:54,940 --> 00:02:59,080
+set أو في ال folder اللي معايا في عندي عشر ملفات
+
+41
+00:02:59,080 --> 00:03:04,160
+text files معناته أنا بتكلم على عشر أرز عشر صفوف
+
+42
+00:03:04,160 --> 00:03:08,960
+الأعمدة هي عبارة عن ال frequent terms اللي موجودة
+
+43
+00:03:08,960 --> 00:03:12,920
+common ما بينالـ three .. الـ ten documents هدول
+
+44
+00:03:12,920 --> 00:03:16,640
+بدور على الكلمات الأساسية و بنشوفهم فممكن أنا أعمل
+
+45
+00:03:16,640 --> 00:03:20,280
+record بناء على ال data ال transactional data في
+
+46
+00:03:20,280 --> 00:03:24,700
+ال graph data كلكوا بتعرفوا أو بتستخدموا ال google
+
+47
+00:03:24,700 --> 00:03:27,260
+maps و كلكوا درستوا data structure و discrete
+
+48
+00:03:27,260 --> 00:03:30,080
+mathematics و تعرفتهوا على ال graphs ال graph هو
+
+49
+00:03:30,080 --> 00:03:33,240
+عبارة عن مجموعة .. أنزوج مرتب من النقاط و الجسور
+
+50
+00:03:33,240 --> 00:03:38,610
+اللي بينها مصبوط فهذه عبارة عنفالـ Graph والشبكات
+
+51
+00:03:38,610 --> 00:03:41,710
+أو الشبكات تمثل بالـ Graph بشكل كويس سواء كان على
+
+52
+00:03:41,710 --> 00:03:45,170
+الشبكة العنكبوتية ولا في ال social networks أو حتى
+
+53
+00:03:45,170 --> 00:03:52,630
+في التراكيب النووية إلى آخره الآن في ال order data
+
+54
+00:03:52,630 --> 00:03:57,210
+البيانات المرتبطة بالزمن وانت شفت خلال ال
+
+55
+00:03:57,210 --> 00:03:59,890
+assignment البسيط اللي كان عندما انتوا عملتم التحث
+
+56
+00:03:59,890 --> 00:04:03,630
+عن ال time seriesالـ temporal والـ special
+
+57
+00:04:03,630 --> 00:04:06,350
+والشغلات هذه طبعا بعيدا عن ال special كان في عند
+
+58
+00:04:06,350 --> 00:04:10,730
+ال time series وال temporal وال sequence ذاتها هي
+
+59
+00:04:10,730 --> 00:04:14,970
+عبارة عن مرتبطة أو data مرتبطة بعمل الزمن بعمل
+
+60
+00:04:14,970 --> 00:04:22,130
+الزمن طيب الآن الفيديو هل هو ordered بس ordered
+
+61
+00:04:22,130 --> 00:04:26,170
+ترتيب و ترتيب زمني ولا لأ يعني بينجو سين لما أنا
+
+62
+00:04:26,170 --> 00:04:30,380
+باجي باستعرض الفيديوالفيديو هو عبارة عن sequence
+
+63
+00:04:30,380 --> 00:04:33,900
+of images صح؟ مجموعة من الصور أو بين جسيم of ال
+
+64
+00:04:33,900 --> 00:04:37,780
+frame وكل frame ممكن يكون مكوّن من مجموعة صور ففي
+
+65
+00:04:37,780 --> 00:04:41,060
+الآخر أنا مستحيل أنتقل لل frame التاني قبل ما أشوف
+
+66
+00:04:41,060 --> 00:04:44,540
+.. أستعرض ال frame الأول وكذلك عند التسجيل لما تم
+
+67
+00:04:44,540 --> 00:04:48,120
+تسجيل الفيديو هذا تم تسجيل ال frame الأول قبل ال
+
+68
+00:04:48,120 --> 00:04:51,680
+frame التاني ففعليا هو عبارة عن ordered و مرتبط
+
+69
+00:04:51,680 --> 00:04:56,130
+بزمنمن ال order كذلك ال genetic sequence زي ما
+
+70
+00:04:56,130 --> 00:04:59,490
+حكينا سابقا وشوفنا ال special و ال data و ال image
+
+71
+00:04:59,490 --> 00:05:03,550
+data او حكينا نوع من التبسيط المحاضرات الماضية
+
+72
+00:05:03,550 --> 00:05:09,630
+الان هذا الجدول بمثل record الجدول
+
+73
+00:05:09,630 --> 00:05:14,930
+صفوف و أعمدة هي ال data تبعتي و هذا اللي فوق ال
+
+74
+00:05:14,930 --> 00:05:18,330
+header تبع الأعمدة و الصفوف في عندي three
+
+75
+00:05:18,330 --> 00:05:22,560
+documents تلت ملفات textوهذه الـ frequent term
+
+76
+00:05:22,560 --> 00:05:27,700
+team و coach و play و ball و soccer و game و win و
+
+77
+00:05:27,700 --> 00:05:31,980
+lost و ال time out و ال season إلى آخره أنا بتكلم
+
+78
+00:05:31,980 --> 00:05:35,740
+على بيانات جمعناها اللي هي علاقة عن text أو
+
+79
+00:05:35,740 --> 00:05:41,640
+تغريدات على سبيل المثال من لناس محبين للكورةفهي ان
+
+80
+00:05:41,640 --> 00:05:45,220
+في الآخر ك text file أخدت ال frequent word الكلمات
+
+81
+00:05:45,220 --> 00:05:48,700
+المتكررة و حطيتهم في قالب أو حطيتهم في أعمدة و
+
+82
+00:05:48,700 --> 00:05:52,060
+شكلت صفوف زي ما هي هنا كذلك في ال market
+
+83
+00:05:52,060 --> 00:05:56,260
+transaction set انا ممكن هي في ال transaction
+
+84
+00:05:56,260 --> 00:05:59,380
+الأول في عندي مجموعة من ال items و لما نتكلم على
+
+85
+00:05:59,380 --> 00:06:02,220
+ال transaction set ممكن نشوف كيف بدى اعمل ال
+
+86
+00:06:02,220 --> 00:06:05,960
+processing بحيث ان احولها ل binary matrix
+
+87
+00:06:08,290 --> 00:06:11,030
+الان يعني لما انا بدي اتكلم على ال data set ال
+
+88
+00:06:11,030 --> 00:06:13,670
+data set تبعتي هي عبارة عن مجموعة من ال data
+
+89
+00:06:13,670 --> 00:06:19,270
+objects ال rows تبعتي data object وال data object
+
+90
+00:06:19,270 --> 00:06:23,160
+هي تمثل ال entityاللي أنا بشتغل عليها، ممكن تكون
+
+91
+00:06:23,160 --> 00:06:26,380
+طالب المدرسة، ممكن تكون السهم اللي أنا بدأ درسه في
+
+92
+00:06:26,380 --> 00:06:29,900
+السوق، بدنا يبقى في حالته، بدي .. ال .. ال ..
+
+93
+00:06:29,900 --> 00:06:31,740
+اليوم اللي أنا بدأ أتوقع في حجم المطنر اللي بديه
+
+94
+00:06:31,740 --> 00:06:35,540
+ينزل، فهي كل واحدة فيهم بتمثل entity أوروبت و عادة
+
+95
+00:06:35,540 --> 00:06:37,920
+ال data set تبعتي أو ال object تبعتي ممكن أنا
+
+96
+00:06:37,920 --> 00:06:40,300
+أجيبها من ال sales .. كما قلت لك في ال sales
+
+97
+00:06:40,300 --> 00:06:44,950
+database، معناة ال entities تبعوتي ال customerو ال
+
+98
+00:06:44,950 --> 00:06:48,650
+store items و المبيعات يعني العناصر اللي أنا
+
+99
+00:06:48,650 --> 00:06:52,070
+ببيعها و الزبون و إيش أنا باعته مش هيلترا ال
+
+100
+00:06:52,070 --> 00:06:58,510
+database الان هدولة كلتهم ممكن يمثلولي ال data set
+
+101
+00:06:58,510 --> 00:07:01,650
+كذلك في ال medical لما أنا بتكلم في ال medical في
+
+102
+00:07:01,650 --> 00:07:06,070
+الطب بتكلم على المريض بتكلم على الأعراض بتكلم على
+
+103
+00:07:06,070 --> 00:07:11,840
+ال diagnosis بتكلم على الطبيبطبيب مهم اسم الطبيب
+
+104
+00:07:11,840 --> 00:07:16,640
+مهم في التشخيص في العلاج و كذا ما مش قطيع للمراجعة
+
+105
+00:07:16,640 --> 00:07:21,580
+اسمه إجرائي لكن فعليا في ال database عشان ال
+
+106
+00:07:21,580 --> 00:07:25,180
+knowledge اسم الطبيب لا يعني شيء تم تشخيص المريض
+
+107
+00:07:25,180 --> 00:07:29,060
+هذا بكذا من اللي شخصه بيعني ليش كتير بس فعليا هو
+
+108
+00:07:29,060 --> 00:07:32,900
+فعليا حالة حقيقية للمرض اللي أنا بدي أعالجه كذلك
+
+109
+00:07:32,900 --> 00:07:35,740
+ال database تبعت الجامعة فيها الطالب و المدرس و
+
+110
+00:07:35,740 --> 00:07:38,970
+المساقى و الاخرينالان شغلة او واحدة من الشغلات
+
+111
+00:07:38,970 --> 00:07:42,790
+المهمة بالنسبة لنا احنا عادة بجينا في ال database
+
+112
+00:07:42,790 --> 00:07:56,090
+بنقول عنه record او table او raw مصبوط الان هنقل
+
+113
+00:07:56,090 --> 00:08:01,150
+عليه اسم sampleأو example أو instance وهذه أشهر
+
+114
+00:08:01,150 --> 00:08:05,010
+المسميات data point و طب الأخرهم يعني ممكن تفتح
+
+115
+00:08:05,010 --> 00:08:08,130
+الكتاب و تلاقي بتكلم يقولك أخدنا example example
+
+116
+00:08:08,130 --> 00:08:12,350
+يعني one row one entity one object of data تمام؟
+
+117
+00:08:12,350 --> 00:08:17,470
+بمثل ال entity هاي ال data object هاي عادة توصف من
+
+118
+00:08:17,470 --> 00:08:20,230
+خلال ال attributes لاحظوا كأني بتكلم عن ال
+
+119
+00:08:20,230 --> 00:08:24,420
+database بتكلم على relational databaseليش؟ لأن الـ
+
+120
+00:08:24,420 --> 00:08:28,500
+structure هي أفضل شغلة لها الجداول عشان أحصل على
+
+121
+00:08:28,500 --> 00:08:32,760
+structure ثابت وبالتالي ال entity أو ال object
+
+122
+00:08:32,760 --> 00:08:36,660
+بتمثل ال rows وال attribute بتمثل الوصف تبع ال
+
+123
+00:08:36,660 --> 00:08:40,820
+rows هذه أو الصفوف اللي موجودة عندها الآن احنا
+
+124
+00:08:40,820 --> 00:08:45,100
+هنروح باتجاه الأعمد لأن في عندنا شوية شغل أو في
+
+125
+00:08:45,100 --> 00:08:51,260
+شوية كلام عليهم لازم نفهمه و نفهمه كويس أولا
+
+126
+00:08:53,080 --> 00:08:57,240
+الـ attribute أو ال data field اللي موجود عندنا
+
+127
+00:08:57,240 --> 00:09:01,480
+هنا بيمثله فعليا ال characteristic أو الخاصية اللي
+
+128
+00:09:01,480 --> 00:09:05,940
+بتهمني يعني بنجو سيل لما بيجي بقول انه في عندي ال
+
+129
+00:09:05,940 --> 00:09:10,260
+attribute اللي اسمه ال age ايش ال values اللي هنا
+
+130
+00:09:10,260 --> 00:09:16,800
+number بتمثل العمر لما بلاقي خمسين يعني انا بعرف
+
+131
+00:09:16,800 --> 00:09:20,660
+خمسين سنة ولا لأ لما بلاقي خمستعش يعني خمستعشر سنة
+
+132
+00:09:21,560 --> 00:09:27,900
+بس مش ممكن ألاجى 250 سنة ولا شو رايكوا؟ في .. في
+
+133
+00:09:27,900 --> 00:09:30,760
+أيام زمان .. اه ماشي الحالة طب في أيام زمان كانش
+
+134
+00:09:30,760 --> 00:09:34,280
+اسمه الف سنة إلا خمسين عاما .. هذا بقى فترة الدعوة
+
+135
+00:09:34,280 --> 00:09:39,080
+فكان عمره جديش صلى الله عليه وسلم على نبينا محمد
+
+136
+00:09:39,080 --> 00:09:46,860
+فالفكرة أن هذه ال attribute تعطيني وصف عن .. يعني
+
+137
+00:09:46,860 --> 00:09:52,780
+بتديني وصف لمين؟لل record اللي موجود الان باجي
+
+138
+00:09:52,780 --> 00:10:01,680
+بلاقي مثلا ال gender بقول email مثلا 45 تمام اللي
+
+139
+00:10:01,680 --> 00:10:06,760
+بتكلم مثلا healthy yes
+
+140
+00:10:06,760 --> 00:10:12,860
+فهي كل واحدة من ال attributes هذه بتحمل ميزةللـ
+
+141
+00:10:12,860 --> 00:10:15,880
+Entity .. عفوًا للـ Object ككل للشخص اللي عمّال
+
+142
+00:10:15,880 --> 00:10:22,120
+نتكلم عليه و عادةً هاي بنسميها احنا Feature و
+
+143
+00:10:22,120 --> 00:10:25,220
+مصطلح الـ Feature هو الأكثر استخداما مع الـ Data
+
+144
+00:10:25,220 --> 00:10:29,720
+Mining و Data Science ممكن
+
+145
+00:10:29,720 --> 00:10:32,160
+هذه الـ Feature سميها Dimension أو Variable
+
+146
+00:10:33,310 --> 00:10:38,830
+Dimension أو Variable الأهم من تسمياتها و كلياتها
+
+147
+00:10:38,830 --> 00:10:41,770
+على الرغم من أنك لازم تحفظها و تنيز ما بينها بشكل
+
+148
+00:10:41,770 --> 00:10:48,170
+كويس بدنا نتكلم على ال attribute types مش هي اللي
+
+149
+00:10:48,170 --> 00:10:51,930
+بتوصف البيانات أصبت مش هي اللي بتوصف ال object أو
+
+150
+00:10:51,930 --> 00:10:55,030
+ال entity اللي عندي الآن في ال database ايش
+
+151
+00:10:55,030 --> 00:10:59,810
+البيانات اللي عندي ال database
+
+152
+00:11:01,870 --> 00:11:07,010
+ايش ال data اللي عندي ال number؟ ال numeric ال
+
+153
+00:11:07,010 --> 00:11:14,250
+numeric هاي integer و float مادة من ال float غيره
+
+154
+00:11:14,250 --> 00:11:25,050
+gate text و ال text هذه character و var character
+
+155
+00:11:25,050 --> 00:11:28,090
+مظبوط غيره blob
+
+156
+00:11:30,730 --> 00:11:37,670
+binary large object غيره؟ إيش ال seal of؟ text
+
+157
+00:11:37,670 --> 00:11:42,630
+كبير؟ طب مافيه عشان؟ ماحنا قولنا خلاص text يعني
+
+158
+00:11:42,630 --> 00:11:46,970
+خلاص ده كل ال data type بغض النظر عن الحجم غيره؟
+
+159
+00:11:46,970 --> 00:11:56,330
+sequence؟ ال boolean غيره؟
+
+160
+00:11:56,330 --> 00:11:59,510
+قريبا هي ال data type اللي أنا بتعامل معاهاالآن
+
+161
+00:11:59,510 --> 00:12:03,110
+على الرغم من أهمية الـ Data Types هذه إلا إنه مش
+
+162
+00:12:03,110 --> 00:12:06,670
+هنعتمد عليها اعتماد كبير في التعامل مع الـ Data
+
+163
+00:12:06,670 --> 00:12:13,450
+Science أو في الـ Data Mining هعتمد مسميات شوية أو
+
+164
+00:12:13,450 --> 00:12:18,130
+بيانات وصفية للـ Data اللي موجودة عندها يعني مثلا
+
+165
+00:12:18,130 --> 00:12:20,750
+الـ Numeric أكيد هتكون الـ Numeric لكن هشوف إن في
+
+166
+00:12:20,750 --> 00:12:25,850
+عندي مسميات شوية مختلفةالها علاقة مثلا هل ال value
+
+167
+00:12:25,850 --> 00:12:30,870
+اللي أنا بتعامل معاها continuous ولا discrete؟ هل
+
+168
+00:12:30,870 --> 00:12:36,890
+هي بتمثل فعليا real number؟ رقم حقيقي ولا ratio؟
+
+169
+00:12:36,890 --> 00:12:41,330
+فالان لو انا اجيت وقلتلك هي انواع ال data أو انواع
+
+170
+00:12:41,330 --> 00:12:44,350
+ال attributes عندك في انواع ال data set nominal
+
+171
+00:12:44,350 --> 00:12:51,830
+nominal يعني categorial او فئوي او فئات
+
+172
+00:12:55,230 --> 00:13:03,310
+binary ثنائي ordinal ايش ordinal ترتيبي او مرتب
+
+173
+00:13:03,310 --> 00:13:09,210
+numerical رقمي طب ممكن يكون هناك تقاطعات او
+
+174
+00:13:09,210 --> 00:13:14,310
+تداخلات بينهم اه ممكن ليش هذا الكلام مهم يا شباب
+
+175
+00:13:14,310 --> 00:13:17,250
+لأن عاملا احنا متكلم في ال data understanding بدي
+
+176
+00:13:17,250 --> 00:13:20,730
+افهم البيانات اللي عندى عشان اعرف ايش بدي اخد
+
+177
+00:13:20,730 --> 00:13:28,540
+اجراءات لاحقا هبدأ معالـ Nominal Attributes الـ
+
+178
+00:13:28,540 --> 00:13:32,100
+Nominal Attributes Nominal Attributes يعني قاعد
+
+179
+00:13:32,100 --> 00:13:36,740
+بأتكلم أنا إنه ال data اللي عندي عبارة عن category
+
+180
+00:13:36,740 --> 00:13:44,560
+أو state أو أسماء أو مسميات لشغلات مثل لو أنا كنت
+
+181
+00:13:44,560 --> 00:13:49,960
+قلتلك في عندي مجموعة ال color تمام؟
+
+182
+00:13:49,960 --> 00:13:53,340
+black و blue, brown, grey, red, white هذه مجموعة
+
+183
+00:13:53,340 --> 00:14:00,110
+ألوانيعني ال attribute كله ياته تمام بياخد واحدة
+
+184
+00:14:00,110 --> 00:14:04,010
+من القيام الست اللي موجودة عندى في المجموعة هاي
+
+185
+00:14:04,010 --> 00:14:09,990
+هاي بسميها إيش category دلوقتي بتكلم على مستويات
+
+186
+00:14:09,990 --> 00:14:17,390
+الطلبة ممتاز جيد جدا جيد مقبول قراصب مصبوط فهاي
+
+187
+00:14:17,390 --> 00:14:23,230
+مستويات وكل واحدة بتمثل category بتمثل فئةالآن
+
+188
+00:14:23,230 --> 00:14:28,090
+غالبا .. غالبا إذا كانت ال text اللي عندي .. ال
+
+189
+00:14:28,090 --> 00:14:34,810
+text اللي عندي finite set ليش يعني finite set؟
+
+190
+00:14:34,810 --> 00:14:40,570
+مجموعة محددة فبقول عنها إيش؟ nominal بقول عنها
+
+191
+00:14:40,570 --> 00:14:44,610
+nominal مثل ال fruits اللي أنا ممكن أتعامل معاها
+
+192
+00:14:44,610 --> 00:14:51,100
+ال fruits اللي بنتعامل معاها جدش عددها؟في الآخر جد
+
+193
+00:14:51,100 --> 00:14:55,180
+ما بدها تكبر فهي limited وبالتالي فبتكلم على
+
+194
+00:14:55,180 --> 00:14:59,500
+categorial أو بسميها nominal وهذا الكلام في ال
+
+195
+00:14:59,500 --> 00:15:03,060
+marital status الحالة الاجتماعية في ال occupation
+
+196
+00:15:03,060 --> 00:15:11,020
+في الوظائف في ال ID numbers كيف؟ الآن لو سألتك عدد
+
+197
+00:15:11,020 --> 00:15:15,490
+الطلاب في الجامعة الإسلامية كده؟خمستاشر ألف الان
+
+198
+00:15:15,490 --> 00:15:18,890
+الرقم هذا اللي موجود عندك واحد ألفين و سبعتاشر
+
+199
+00:15:18,890 --> 00:15:25,810
+واحد اتنين تلاتة أربعة ليه يكون أخر أربع أرقام بس
+
+200
+00:15:25,810 --> 00:15:28,670
+بس في الآخر في الآخر أنا معايا ورقيا شباب بس من
+
+201
+00:15:28,670 --> 00:15:32,750
+الورق بضيعوش على الفاضي مش مشكلة مش مشكلة الان
+
+202
+00:15:32,750 --> 00:15:39,160
+finite ولا مش finiteكل رقم بيمثل قيمة مستقلة،
+
+203
+00:15:39,160 --> 00:15:42,800
+تمام؟ ممكن أقول عنه category، فئة، لكن فعلياً
+
+204
+00:15:42,800 --> 00:15:47,780
+category فيها طالب واحد، لأ، وهنا مشكلتنا الآن، مش
+
+205
+00:15:47,780 --> 00:15:52,060
+لأنه رقمه، مش لأنه العدد تبعهم كبير، الآن لو أنا
+
+206
+00:15:52,060 --> 00:15:55,680
+سأل نرجع لموضوع الفواكه، كام نوع من الفواكه ممكن
+
+207
+00:15:55,680 --> 00:16:00,380
+تعد انت؟خمسين .. ستين .. سبعين .. مية .. متين ..
+
+208
+00:16:00,380 --> 00:16:03,640
+تلات مية .. فيه فواكه ما بتعرفاش .. حتما تمام؟ بس
+
+209
+00:16:03,640 --> 00:16:08,900
+في الآخر مسميات واضحة و غير متداخلة لما باتش بتكلم
+
+210
+00:16:08,900 --> 00:16:15,060
+في ال marital status الحالة الإجتماعية اربع قيم
+
+211
+00:16:15,060 --> 00:16:21,620
+صح؟ ولا خمسة؟ أعزب متزوج .. خليني .. طلقته قبل ما
+
+212
+00:16:21,620 --> 00:16:27,150
+تزوج وزوجه طيب أعزب متزوجأرمل ومطلق أو مطلق و أرمل
+
+213
+00:16:27,150 --> 00:16:31,250
+مظبوط أربع في غيرهم علنية وخير الخامس إذا كان بدك
+
+214
+00:16:31,250 --> 00:16:36,730
+تحطها okay في الآخر finite وهذه كل واحدة ال label
+
+215
+00:16:36,730 --> 00:16:40,890
+تبعها أو النص تبعها معروف category فئة بس رقم
+
+216
+00:16:40,890 --> 00:16:44,790
+الطالب مفهوش يقول عنه فئة لكن لو جيت بولت السنة
+
+217
+00:16:44,790 --> 00:16:49,410
+تبع تسجيل الطالب بنفع تصير فئة جزء من ال number
+
+218
+00:16:49,410 --> 00:16:52,950
+فصارت تصير فئة احنا مابداش نخرب اقتها كتير الآن ال
+
+219
+00:16:52,950 --> 00:16:57,610
+occupation الوظائفمعروف الوظائف ومحصورة زي ما قلنا
+
+220
+00:16:57,610 --> 00:17:09,490
+و ال zip code الأرقام طيب نعم نعم نعم في
+
+221
+00:17:09,490 --> 00:17:13,970
+الآخر
+
+222
+00:17:13,970 --> 00:17:17,850
+جداش بده يزيد العدد يا مؤمن ما هو شوف مفهوم ال
+
+223
+00:17:17,850 --> 00:17:22,520
+finiteيعني في countable و في countably infinite
+
+224
+00:17:22,520 --> 00:17:26,260
+يعني مسموح فيه التزايد بس في الآخر في اللحظة اللي
+
+225
+00:17:26,260 --> 00:17:32,340
+أنا بدي أقرر أحصر الأعداد بأحصرها مش هيزيد مش
+
+226
+00:17:32,340 --> 00:17:35,300
+هيزيد عن سبعة مليار على رأي رامي كل ان كل هي كل مش
+
+227
+00:17:35,300 --> 00:17:38,770
+هتلاقي بشر اكتر من هي صح؟بالآخر احنا هنا بنتكلم
+
+228
+00:17:38,770 --> 00:17:42,430
+بشباب عشان ما نبعدش كتير على المسميات أو الحالات
+
+229
+00:17:42,430 --> 00:17:47,570
+اللي بتهمني لو انا اجيت سألت الأقسام أو أسماء
+
+230
+00:17:47,570 --> 00:17:53,470
+الأقسام أو أرقام الأقسام مثلا Computer Science 901
+
+231
+00:17:53,470 --> 00:18:00,290
+تطوير برمجيات 902 901 و 902 بنفع نقول عنها
+
+232
+00:18:00,290 --> 00:18:04,730
+nominal؟ اه nominal ليش؟ لأن هذه بتمثل category
+
+233
+00:18:04,730 --> 00:18:10,490
+بتمثل فئةبغض النظر عن القيمة اللي أنا كتبتها لكن
+
+234
+00:18:10,490 --> 00:18:16,930
+لو انا اجيت و قلتلك في عندي مجموعة بتمثل ال first
+
+235
+00:18:16,930 --> 00:18:22,610
+second و
+
+236
+00:18:22,610 --> 00:18:30,310
+ال third شو
+
+237
+00:18:30,310 --> 00:18:34,910
+رأيكوا؟ هل هذه ممكن nominal؟ nominal
+
+238
+00:18:37,310 --> 00:18:42,590
+nominal بس أصبر علينا nominal بس جاوبني nominal ده
+
+239
+00:18:42,590 --> 00:18:48,550
+nominal nominal هاي nominal لأنه فعليا قاعد بتكلم
+
+240
+00:18:48,550 --> 00:18:52,830
+على categories أو أسماء أو تلات أصنافات الأول
+
+241
+00:18:52,830 --> 00:18:57,330
+والتاني والتالت مصبوط؟ خلنا نقول الفائزين أو ال
+
+242
+00:18:57,330 --> 00:19:02,730
+winners الأول والتاني والتالت لكن هذه فيها ميزة مش
+
+243
+00:19:02,730 --> 00:19:05,590
+موجودة في ال colors في المجموع اللي فوق
+
+244
+00:19:09,080 --> 00:19:15,140
+إن القيمة إلها معنى معنى ترتيبي بمعنى آخر لو أنا
+
+245
+00:19:15,140 --> 00:19:20,580
+إجيت قولت ال color تبعي blue my favorite color
+
+246
+00:19:20,580 --> 00:19:28,040
+blue واحد تاني هيقولي white بتفرج؟
+
+247
+00:19:28,040 --> 00:19:33,740
+هل بين جسين في أولوية للأبيض عن الأزرق أو العكس؟
+
+248
+00:19:33,740 --> 00:19:37,820
+لأ مافيش لكن لما إجيت أنا قولت ال first
+
+249
+00:19:42,710 --> 00:19:50,030
+winner وقلت ال second او ال third winner وال
+
+250
+00:19:50,030 --> 00:19:56,050
+second winner تفرج ال values عن بعضها تفرج على
+
+251
+00:19:56,050 --> 00:19:59,730
+الرغم انها categorian وهذا يجعلنا نروح باتجاه فئة
+
+252
+00:19:59,730 --> 00:20:04,110
+جديدة اللي هي ال ordinal هيتكلم و يوداني على فئة
+
+253
+00:20:04,110 --> 00:20:08,470
+جديدة اللي هي فئات ال ordinal تمام يا جماعة الخير؟
+
+254
+00:20:08,840 --> 00:20:13,420
+الأن يعني ال ordinal هي عبارة عن حالة خاصة حالة
+
+255
+00:20:13,420 --> 00:20:19,000
+خاصة من من ال categorial أو من ال nominal بحيث إنه
+
+256
+00:20:19,000 --> 00:20:25,660
+في عندي معنى أو sequence موجودة في معاني الكلمات
+
+257
+00:20:25,660 --> 00:20:30,040
+مش بالضرورة تظهر بال sequence بس القيمة إلها معنى
+
+258
+00:20:30,040 --> 00:20:36,660
+ترتيبي تماما مثل الرتب العسكرية بيجي يقولني نقيب و
+
+259
+00:20:36,660 --> 00:20:43,560
+رقيب صح؟عقيد ولواء أو ملازم وملازم أول فهي كل
+
+260
+00:20:43,560 --> 00:20:46,220
+واحدة فيهم الرتبة بتفرج عن التاني على الرغم إنها
+
+261
+00:20:46,220 --> 00:20:50,540
+categorial فئة مصبوط فئة الملازمين فئة العقدة فئة
+
+262
+00:20:50,540 --> 00:20:54,660
+العمدة إلى آخرهم فبالتالي أنا جاعت بأتكلم .. أتكلم
+
+263
+00:20:54,660 --> 00:21:00,220
+على فئات أتكلم على فئات لكنه الكلمات تحمل دلالة
+
+264
+00:21:00,220 --> 00:21:05,650
+ترتيبيةتمام؟ في داخلها وهذا هو ال nominal كذلك من
+
+265
+00:21:05,650 --> 00:21:08,510
+ال .. من ال .. من ال .. عفوا من ال original كذلك
+
+266
+00:21:08,510 --> 00:21:11,590
+من ال nominal في عندي special type اللي هو ال
+
+267
+00:21:11,590 --> 00:21:16,610
+binary هي عبارة عن categorial data أو nominal data
+
+268
+00:21:16,610 --> 00:21:22,050
+لكن ال values اللي عندي فقط two values مش ضروري
+
+269
+00:21:22,050 --> 00:21:27,430
+يكونوا 01 01 one case منهم true false white و
+
+270
+00:21:27,430 --> 00:21:33,810
+black positive و negativehigh و low success و fail
+
+271
+00:21:33,810 --> 00:21:40,550
+اي category او اي مجموعة فقط من two values تمام
+
+272
+00:21:40,550 --> 00:21:47,590
+بسميها ايش؟ binary كيف
+
+273
+00:21:47,590 --> 00:21:52,330
+يعني عكس بعض؟ يعني مثلا انا عندي فئاتين الأول
+
+274
+00:21:52,330 --> 00:21:55,630
+والتاني فقط هاي الناس اللي أنا بدور عليهم الترتيب
+
+275
+00:21:55,630 --> 00:22:02,480
+الأول والتاني زي فئات الدمتمام اللي هي ال R تبعتها
+
+276
+00:22:02,480 --> 00:22:07,900
+مش الفئة ال A لإنه A وB اه تمام؟ الآن لو إجينا
+
+277
+00:22:07,900 --> 00:22:11,380
+نتكلم على تشغيل .. يعني إذا كانت أنت بتفرضها إن
+
+278
+00:22:11,380 --> 00:22:15,260
+هذا هي ال opposite تبعتها okay لكن في الآخر أنا
+
+279
+00:22:15,260 --> 00:22:19,260
+بتكلم إن هي فعليا two different values only في ال
+
+280
+00:22:19,260 --> 00:22:23,560
+value أو في ال attribute اللي موجودة عندهالكن في
+
+281
+00:22:23,560 --> 00:22:27,280
+ال binary values بدي أنتبه عشان أكون فاهم صح ال
+
+282
+00:22:27,280 --> 00:22:30,400
+data اللي عندي هل ال data هذه أو ال binary هذا
+
+283
+00:22:30,400 --> 00:22:34,520
+symmetric ولا asymmetric بمعنى هل القيمتين هدولة
+
+284
+00:22:34,520 --> 00:22:38,480
+لهم نفس الوزن في التعامل ولا أنا مهتم بال value
+
+285
+00:22:38,480 --> 00:22:43,100
+أكتر من التانية مثلا لما بدي بتكلم على ال gender
+
+286
+00:22:43,100 --> 00:22:47,400
+في عالم المساواة بتكلم على ال equality التانتين في
+
+287
+00:22:47,400 --> 00:22:52,410
+نفس الأهميةمصبوط اتنين بنفس الأهمية لكن لو كانت
+
+288
+00:22:52,410 --> 00:22:57,790
+اللي بتكلم على ال diagnosis لفيروس او لمرض معين ال
+
+289
+00:22:57,790 --> 00:23:02,830
+positive أهم مليون مرة من ال negative على الرغم ان
+
+290
+00:23:02,830 --> 00:23:07,240
+ال negative موجود لكن قيمة ال positive highأهم
+
+291
+00:23:07,240 --> 00:23:11,440
+بالنسبة لي اللي انا بتقطع عليها action مختلفة وهذه
+
+292
+00:23:11,440 --> 00:23:15,060
+بسميها احنا اذا لو كان في عندي غير تساوي او
+
+293
+00:23:15,060 --> 00:23:23,200
+القيمتين غير متساويات فبسميها asymmetric حكينا
+
+294
+00:23:23,200 --> 00:23:29,640
+مع ال ordinal بشكل كويس ال numeric في ال numeric
+
+295
+00:23:29,640 --> 00:23:35,000
+الآن كل الأرقام اللي ممكن تخطر على بالناnumeric
+
+296
+00:23:35,000 --> 00:23:43,760
+لكنها تصنف كذلك لتلت فئات quantitative كم وفي عندي
+
+297
+00:23:43,760 --> 00:23:50,340
+interval scaled وفي عندي ratio scaled هنبدأ مع ال
+
+298
+00:23:50,340 --> 00:23:53,800
+quantitative ال quantitative او الكم عادة لما
+
+299
+00:23:53,800 --> 00:23:58,300
+بتكلم على ال age بتكلم على الشغلات اللي بدي اعرف
+
+300
+00:23:58,300 --> 00:24:03,660
+عددها او بدي اعرف كميتها بحط رقم بحط value يعني
+
+301
+00:24:03,660 --> 00:24:08,820
+الآنلو انت روحت بدك تشتري ثاكهة ودخلت ال
+
+302
+00:24:08,820 --> 00:24:12,820
+supermarket ولاجيته بيجي بيقولك تلاتة كيلو او مثلا
+
+303
+00:24:12,820 --> 00:24:16,700
+ال كيلو مثلا بخمس شكل وروحت انت تاخد اتنين كيلو
+
+304
+00:24:16,700 --> 00:24:21,180
+عند الميزان لما حط على الميزان لاجى مثلا اتنين
+
+305
+00:24:21,180 --> 00:24:27,360
+كيلو متين جرام شو وضع المتين جرام هدول؟يا ما بيشيل
+
+306
+00:24:27,360 --> 00:24:30,740
+من الإبداع أو بيحسبك عليهم تمام؟ وبالتالي أنا
+
+307
+00:24:30,740 --> 00:24:33,700
+بتكلم على ال weight اللي أنت أخدته اتنين و اتنين
+
+308
+00:24:33,700 --> 00:24:38,620
+من عشرة، مصبوط؟ وبالتالي هذه إلها كمية معينة لازم
+
+309
+00:24:38,620 --> 00:24:41,740
+تنجسط بيجي بيقول في ال new في الأطفال حديثي
+
+310
+00:24:41,740 --> 00:24:46,180
+الولادة لما بيجي بيقولي والله طوله كده مثلا ستين
+
+311
+00:24:46,180 --> 00:24:49,960
+أو سبعين صنطي فهو فعليا بيقصد ستين أو سبعين صنط
+
+312
+00:24:49,960 --> 00:24:54,340
+بالمبلغ بالعفو بالرقم اللي كتبهلما بيجي بكتب وزنه
+
+313
+00:24:54,340 --> 00:25:00,240
+2450 جرام لان ال 50 جرام بتفرج معاه مابنضلش يكتب 2
+
+314
+00:25:00,240 --> 00:25:06,700
+.5 كيلو جرام ففعليا هو قاعد بيكتب exact quantity
+
+315
+00:25:06,700 --> 00:25:14,020
+كقمية موجودة و طبعا سواء كانت الكمية انتجر او real
+
+316
+00:25:14,020 --> 00:25:17,480
+number ما مش قضية كتير بس في الآخر بنتعامل مع كمية
+
+317
+00:25:17,480 --> 00:25:23,710
+موجودة بال interval scaled النوع التانيو هنا انا
+
+318
+00:25:23,710 --> 00:25:28,110
+بأتكلم ضمن range ال value تبعتي ضمن range لاحظ
+
+319
+00:25:28,110 --> 00:25:32,470
+باتكلمش على discrete و continuous باتكلم على ان
+
+320
+00:25:32,470 --> 00:25:36,670
+القيمة تبعتي هذه تقاس تبعا لمجموعة من ال units
+
+321
+00:25:36,670 --> 00:25:43,190
+لمجموعة من ال units مثال عليها ال temperature درجة
+
+322
+00:25:43,190 --> 00:25:46,030
+الحرارة الآن لو جينا و قولنا درجة الحرارة في
+
+323
+00:25:46,030 --> 00:25:50,690
+الغرفة هذه تقارب العشرين او عشرين
+
+324
+00:25:53,880 --> 00:26:00,540
+لو كانت 19 أنا غلطان؟ طب لو كانت 21؟ برضه لأ، ليش؟
+
+325
+00:26:00,540 --> 00:26:04,660
+لأن الفرق اللي بنتكلم فيه بسيط و في نفس الوجد
+
+326
+00:26:04,660 --> 00:26:10,820
+ماحدش هيحس فيه أو يبين جوسين هيميزه 100% أقولك حتى
+
+327
+00:26:10,820 --> 00:26:12,940
+درجة الحرارة اللي احنا بنقراها من خلال نشارات
+
+328
+00:26:12,940 --> 00:26:13,440
+الأخبار
+
+329
+00:26:16,880 --> 00:26:20,980
+plus minus يعني هو بديك درجة الحرارة القصوى أو
+
+330
+00:26:20,980 --> 00:26:25,940
+العظمة المتوقعة والصغرة أو الدنيا المتوقعة، مظبوط؟
+
+331
+00:26:25,940 --> 00:26:30,920
+خلال اليوم لكن في أي وجد في اليوم؟ ماعرفش، الآن
+
+332
+00:26:30,920 --> 00:26:34,480
+فعليا لكن هو في اليوم الفلاني زي اليوم مثلا ستة
+
+333
+00:26:34,480 --> 00:26:41,840
+عشر اتنين الفين وعشرين ال high temperature في ال
+
+334
+00:26:41,840 --> 00:26:48,010
+high temperature عشرين واللهتم بريتشار سابعة
+
+335
+00:26:53,720 --> 00:26:57,920
+المربوطة بإيش الآن؟ أكيد إيش ال unit تبعتي هنا؟
+
+336
+00:26:57,920 --> 00:27:02,180
+درجة الحرارة سيلز ولا فارينهايت بس في الآخر في
+
+337
+00:27:02,180 --> 00:27:07,780
+الآخر الرقم هذا لا يعبر عن القيمة الحقيقية اللي
+
+338
+00:27:07,780 --> 00:27:11,380
+كانت في اليوم هو عمل estimation وتوقع درجة الحرارة
+
+339
+00:27:11,380 --> 00:27:15,700
+بتكون كذا لكن فعليا جاسا جديش على مدار الساعة لأنه
+
+340
+00:27:15,700 --> 00:27:20,830
+أساسا في أي يوم عاديساعات الليل .. ساعات الليل
+
+341
+00:27:20,830 --> 00:27:25,970
+أبرد من ساعات النهار وأول الليل أدفع من آخره مصدوق
+
+342
+00:27:25,970 --> 00:27:30,390
+انا لأ و العكس كذلك أول النهار أبرد من وسطه وأبرد
+
+343
+00:27:30,390 --> 00:27:33,670
+من آخره لأن في حركة في حركة دوران الأرض والشمس
+
+344
+00:27:33,670 --> 00:27:37,350
+الاخر كلها بتأثر لكن الآن ال value اللي كمان مرة
+
+345
+00:27:37,350 --> 00:27:40,350
+أهم يميز هذه ال values أو هذه القيم اللي احنا
+
+346
+00:27:40,350 --> 00:27:46,710
+بنسميها interval ضمن range ثابت معروفة يعني مثلا
+
+347
+00:27:48,020 --> 00:27:52,540
+قدش أقل درجة حرارة ممكن تكون عندنا في فلسطين صفر
+
+348
+00:27:52,540 --> 00:27:56,600
+على جبال الشيخ مثلا على جبل الجرمق الجبال الشيخ مش
+
+349
+00:27:56,600 --> 00:28:01,300
+عندنا الجليل الجليل الأعلى عندنا تمام الآن صفر
+
+350
+00:28:01,300 --> 00:28:07,700
+سالب تلاتة تلاتة مش قضية كتير و أعلى درجة حرارة
+
+351
+00:28:07,700 --> 00:28:13,360
+خمسة و تلاتين اربعين اريحة في الأغوار هي ال range
+
+352
+00:28:13,360 --> 00:28:17,460
+تابعي من صفر لاربعينو صفر ل 40 مدورش فيه ولا مرة
+
+353
+00:28:17,460 --> 00:28:21,920
+على ال fraction دائما بتكلم على مجموعة من القيم و
+
+354
+00:28:21,920 --> 00:28:26,040
+عشان هيك بنسميها احنا equal size scale يعني انا
+
+355
+00:28:26,040 --> 00:28:30,240
+قلتلي 10 ولا قلتلي 12 صح انا بعرف مقدار درجة
+
+356
+00:28:30,240 --> 00:28:33,420
+الحرارة زي بعض بس في الآخر مش فارقة كتير معايا
+
+357
+00:28:33,420 --> 00:28:40,300
+الان تميز هذه درجة ال interval scale ان في إلها
+
+358
+00:28:40,300 --> 00:28:45,720
+ordered بفهمه انالمّا بيقولّي 15 حتمًا الجو أبرد
+
+359
+00:28:45,720 --> 00:28:51,540
+من 20 و أدفع من 10 فهذا ال order أنا صرت بفهم في
+
+360
+00:28:51,540 --> 00:28:55,460
+ال interval لأنه أنا بعرف ال interval دائمًا من
+
+361
+00:28:55,460 --> 00:29:00,640
+إلى و من هنا بتتغير القيم اللي موجودة عندي الشغل
+
+362
+00:29:00,640 --> 00:29:07,160
+التاني انه أنا فعليًا في ال interval scale مافيش
+
+363
+00:29:07,160 --> 00:29:11,080
+real zero أتعامل معاه لما بيجي يقولّي درجة الحرارة
+
+364
+00:29:11,080 --> 00:29:18,450
+بكرا متوقعة تكون صفرفعليا صفر؟ ممكن أو ممكن لأ، بس
+
+365
+00:29:18,450 --> 00:29:21,490
+الواقع بيقول إذا صارت صفر، كل شغلة فيها ميّه بدا
+
+366
+00:29:21,490 --> 00:29:25,550
+تتجمد، شئنا أمأ بينها، لأنها كانت الطبيعة، ولا لأ؟
+
+367
+00:29:25,550 --> 00:29:28,750
+فعليا تتجمدت؟ يعني فتحت المصورة هيك وما نزلتش
+
+368
+00:29:28,750 --> 00:29:32,110
+الميّه؟ لأ، وبالتالي فعليا مش صفر، على الرغم من
+
+369
+00:29:32,110 --> 00:29:35,550
+أنه جالس درجة الحرارة صفر، بالنسبة له، بالنسبة له،
+
+370
+00:29:35,550 --> 00:29:38,430
+هي يمكن حوالين الصفر، يعني هو اتوقع أنها تنزل أقل
+
+371
+00:29:38,430 --> 00:29:43,760
+من واحد،أو تصل للواحد أو ممكن تصل لأقل قالك درجة
+
+372
+00:29:43,760 --> 00:29:47,680
+الحرارة واحد مع minus one أو minus two plus or
+
+373
+00:29:47,680 --> 00:29:52,500
+minus two ممكن تصل سالب واحد فعليا لكن فعليا هل
+
+374
+00:29:52,500 --> 00:29:55,740
+الصفر اللي قالي يا ده هو الصفر الحقيقي اللي احنا
+
+375
+00:29:55,740 --> 00:29:59,220
+بنتعامل معاه لأ لأ لأ حتما لأ وبالتالي في ال
+
+376
+00:29:59,220 --> 00:30:03,530
+interval انا ماعنديش صفرأو بينجوسين حتى لو شفتوا
+
+377
+00:30:03,530 --> 00:30:07,730
+هذا الصفر فيه بمثل interval يعني هيكد لو أنا باجيت
+
+378
+00:30:07,730 --> 00:30:10,930
+قولت في درجة الحرارة جماعة الخير القيم المعطالة
+
+379
+00:30:10,930 --> 00:30:17,610
+كان plus or minus اتنين وجيت شو .. وجيت قولتلك
+
+380
+00:30:17,610 --> 00:30:22,370
+درجة الحرارة صفر هذه
+
+381
+00:30:22,370 --> 00:30:27,210
+تلت قيم، مصبوط؟ هذه فواقع .. ال value هذه فواقعها
+
+382
+00:30:27,210 --> 00:30:34,990
+تلت قيم تلتة؟ خمس قيمسالب اتنين سالب واحد والصفر
+
+383
+00:30:34,990 --> 00:30:39,450
+والواحد والاتنين طب الصفر دي بتمثل اي واحدة من
+
+384
+00:30:39,450 --> 00:30:44,070
+الخمسة دول الله أعلم عشانك بنقول no true zero تمام
+
+385
+00:30:44,070 --> 00:30:48,130
+في القيامة دي مافيش true zero interval scale
+
+386
+00:30:53,300 --> 00:30:59,620
+لما باجي بقول الأسبوع الرابع من الشهر عادة الأسبوع
+
+387
+00:30:59,620 --> 00:31:05,380
+اللي عندي بيبدأ مانواجتهاش مثلا من السبت لكن
+
+388
+00:31:05,380 --> 00:31:10,260
+الأسبوع الرابع من الشهر مين قال أنه بدأ السبت؟ لأن
+
+389
+00:31:10,260 --> 00:31:13,020
+أول أسبوع بيبدأ من أول يوم في الشهر، ده بتعد سبعة
+
+390
+00:31:13,020 --> 00:31:18,550
+أيام تمام؟ وبتصير إيش؟هيك بيصير تعد أسبوع فأنا
+
+391
+00:31:18,550 --> 00:31:21,030
+بصير آخر أسبوع في الشهر بتكلم عليه الأسبوع الرابع
+
+392
+00:31:21,030 --> 00:31:24,790
+اللي موجود عندي هل فهو صدف يوم سبت أو لأ ففعلا مش
+
+393
+00:31:24,790 --> 00:31:27,990
+.. مش .. مش دقيق أنه أنا لازم أبدأ من يوم السبت بس
+
+394
+00:31:27,990 --> 00:31:34,730
+مصطلح و من الشغلات اللي احنا بنتكلم عليها النوع
+
+395
+00:31:34,730 --> 00:31:41,230
+التالت في ال quantitative ال ratio scaled وهذا ال
+
+396
+00:31:41,230 --> 00:31:45,580
+ratio لما أنا بتكلم عليهنسبة مئوية والنسبة المئوية
+
+397
+00:31:45,580 --> 00:31:51,060
+جماعة الخير الصفر وارد فيها لما تكون ال value
+
+398
+00:31:51,060 --> 00:31:55,820
+تبعتي صفر وجسمتها على العشرة صفر مش النسبة أو
+
+399
+00:31:55,820 --> 00:32:00,540
+الرشو هي عبارة عن عملية قسمة تمام ليش أنا محتاجها
+
+400
+00:32:00,540 --> 00:32:05,320
+درجة
+
+401
+00:32:05,320 --> 00:32:15,530
+الحرارة اليوم أدفع مرتين من امبارح كلمة مرتين هيمش
+
+402
+00:32:15,530 --> 00:32:22,470
+نسبة؟ مصبوط ولا لأ؟ طيب، لو أنا اجيت قولت راتبي
+
+403
+00:32:22,470 --> 00:32:27,070
+أعلى خمس مرات من راتب فلان بره تكلمتي على نسبة
+
+404
+00:32:27,070 --> 00:32:34,210
+بلاش، الآن بعض الدول العمولات تبعتها أرقامها بتخوف
+
+405
+00:32:34,210 --> 00:32:37,930
+لبنان و سوريا و إيران و تركيا أعتقد لما بتكلم
+
+406
+00:32:37,930 --> 00:32:41,650
+بالليرة، روسيا، الهند
+
+407
+00:32:44,420 --> 00:32:47,760
+اليمن ما شاء الله خبرة في الاقتصاد كلكم صرتوا ما
+
+408
+00:32:47,760 --> 00:32:52,000
+شاء الله عليكم الآن العمل .. العملة بروح بده يشتري
+
+409
+00:32:52,000 --> 00:32:58,200
+مثلا البطارية .. باش بده يشتري علبة عصير بيجي
+
+410
+00:32:58,200 --> 00:33:02,060
+بيقولك حاجة مثلا خمس سلاف ليرة بده يشتري سيارة
+
+411
+00:33:02,060 --> 00:33:07,760
+بيقولك سبعتناشر مليون ليرة مش في محاضرة الاقتصاد
+
+412
+00:33:07,760 --> 00:33:14,440
+انا الفكرة اللي انا بوصلك إياها الآن تخيل17 مليون
+
+413
+00:33:14,440 --> 00:33:19,840
+ليرة و إذا كنت تضيف عليهم ضريبة بنسبة كذا فبصير
+
+414
+00:33:19,840 --> 00:33:25,320
+الرقم هذا شوية بخوف أبدأ أقول واحد سبعة تلاتة خمسة
+
+415
+00:33:25,320 --> 00:33:32,580
+و هاي اتنين جدّيش اقصروا مازالوا سبعة عشر مليون و
+
+416
+00:33:32,580 --> 00:33:37,620
+خمسة و عشرين ألف و متين و تلتمية و واحد و سبعين
+
+417
+00:33:37,620 --> 00:33:43,940
+ليرةتخيل نفسك بدك تعمل عملية ضرب بالرقم برقم زي
+
+418
+00:33:43,940 --> 00:33:49,360
+هذا جدش بدك واجده ع ال calculator ماشي الحل ع ال
+
+419
+00:33:49,360 --> 00:33:54,400
+calculator جدش بدك واجده واجد ادخالهم جدش بداخل
+
+420
+00:33:54,400 --> 00:33:58,160
+معاك بينما لو انا اجيت قلتلك الأرقام اللي زي هذه
+
+421
+00:33:58,160 --> 00:34:02,400
+انا هعملها scaling لواحد
+
+422
+00:34:03,440 --> 00:34:06,560
+1 من 10 مثلا بدي أجسم على 10 مليون كل الأرقام اللي
+
+423
+00:34:06,560 --> 00:34:09,580
+عندي أجسم عليها على 10 مليون فالرقم اللي عندي هذا
+
+424
+00:34:09,580 --> 00:34:14,640
+كده ايش بيصير؟ 1.7 مع ال truncation أو مع ال
+
+425
+00:34:14,640 --> 00:34:17,580
+roundation ال zero هذا ايش؟ اخر رقم هو اللي انا
+
+426
+00:34:17,580 --> 00:34:22,620
+بحتفظ فيه فشو رأيكم؟ مين أسهل؟ الرقم هذا ولا 17
+
+427
+00:34:22,620 --> 00:34:31,820
+.25371؟ لأ أكيد 1.7 أسهل1.7 أسهل فالان بعض ال data
+
+428
+00:34:31,820 --> 00:34:34,500
+.. بعض ال data صعب ان انا أروح و أحط فيها الأصفار
+
+429
+00:34:34,500 --> 00:34:38,280
+فبروح بيجي و بقولي حجم الاقتصاد كان في البلد
+
+430
+00:34:38,280 --> 00:34:44,900
+الفلاني على سبيل المثال بروح بيقولي مثلا ال dollar
+
+431
+00:34:44,900 --> 00:34:50,360
+بالmillion و بروح بيقولي مثلا 15
+
+432
+00:34:53,070 --> 00:34:56,890
+15 مليون مافيش داعي الأصفار كلها هي نسبة فجسم
+
+433
+00:34:56,890 --> 00:35:01,490
+الرقم اللي عنده على جداش على المليون اللي موجهة
+
+434
+00:35:01,490 --> 00:35:04,250
+هنا ليش لأنه زي ما قلتلك هي بتخفف علينا في ال
+
+435
+00:35:04,250 --> 00:35:07,310
+computation انت الآن لو أنا جيت فعليا قلتلك اضرب
+
+436
+00:35:07,310 --> 00:35:14,270
+للرقم هذا في تلاتة بعيدا عن ال calculator وضرب 1.7
+
+437
+00:35:14,270 --> 00:35:18,670
+في تلاتة حتما
+
+438
+00:35:18,670 --> 00:35:22,610
+هذا هياخد معاك أقل وقتاطبعاً لما بيجي بيقولك ان
+
+439
+00:35:22,610 --> 00:35:25,170
+الرقم هذا بتتحول ل binary وعملية الضرب بال binary
+
+440
+00:35:25,170 --> 00:35:28,470
+يعني كل digit بتدخل في العملية فبياخد مني وقت كتير
+
+441
+00:35:28,470 --> 00:35:31,490
+في عملية ال processing انا بكفيني حجم ال data اللي
+
+442
+00:35:31,490 --> 00:35:34,450
+ماخد عامة ال 100 ألف record كمان بيقولي هذا بياخد
+
+443
+00:35:34,450 --> 00:35:39,830
+مش عارف كم مليون digits فلازم نعمل ratio scaling
+
+444
+00:35:39,830 --> 00:35:43,870
+او بعض ال data بتكون فعليا هي عبارة عن ratio scale
+
+445
+00:35:43,870 --> 00:35:47,130
+temperature in Kelvin
+
+446
+00:35:49,870 --> 00:35:55,090
+درجة الحرارة بالكيلفن او بالفهرين هايت شو رأيكوا؟
+
+447
+00:35:55,090 --> 00:35:59,070
+مش هي عبارة عن نسبة؟ لما بتحول درجة الحرارة عبارة
+
+448
+00:35:59,070 --> 00:36:04,830
+عن طق سيلق عبارة عن طرح وقسمة أحيانا ال counts و
+
+449
+00:36:04,830 --> 00:36:08,290
+ال length الأميال أو الأطوال ممكن تكون عندي كذلك
+
+450
+00:36:08,290 --> 00:36:13,210
+كذلك من الشغلات اللي لازم نفهمها مع ال data set
+
+451
+00:36:13,210 --> 00:36:17,250
+اللي هي ال discrete و ال continuous شو يعني
+
+452
+00:36:17,250 --> 00:36:24,130
+discrete؟منفصل continuous متصل يا عيني عليكم كويس
+
+453
+00:36:24,130 --> 00:36:27,670
+الآن لما بتكون ال values اللي موجودة عندي هنا
+
+454
+00:36:27,670 --> 00:36:36,090
+finite منتهية منتهية شو يعني منتهية شباب محدودة
+
+455
+00:36:36,090 --> 00:36:41,670
+معروفين خمس خيارات عشرة عشرين تلاتين مية متين
+
+456
+00:36:41,670 --> 00:36:50,530
+مليون limited مليار أي رقم بدك تلفظهتمام؟ هذه رقم
+
+457
+00:36:50,530 --> 00:36:53,830
+معدود وبالتالي احنا نقدر نصلّه فهذا بسميه انا
+
+458
+00:36:53,830 --> 00:37:02,330
+discrete تالي تمام؟ لكن لو انا اجيت سألتك الأرقام
+
+459
+00:37:02,330 --> 00:37:07,210
+ما بين صفر و واحد في ال interval من صفر و واحد
+
+460
+00:37:07,210 --> 00:37:13,370
+جدّيش الأرقام الموجودة countably infinite حرام
+
+461
+00:37:13,370 --> 00:37:18,270
+عليك يا شيخ infinite اه من صفر لواحد infinite عارف
+
+462
+00:37:18,270 --> 00:37:32,020
+ليش؟هذه صفر point واحد لسه
+
+463
+00:37:32,020 --> 00:37:40,220
+ماتكلمش على صفار بعد جداش بدك توجف بعد
+
+464
+00:37:40,220 --> 00:37:47,880
+جداش fish limit تمام؟ وهذا فعليا infiniteمجموعة
+
+465
+00:37:47,880 --> 00:37:51,100
+غير منتهية وبالتالي المجموعة المنتهية أنا مستحيل
+
+466
+00:37:51,100 --> 00:37:56,700
+إيش أعدها لكن هنا بيجي يقولي ال discrete attribute
+
+467
+00:37:56,700 --> 00:38:00,240
+هو عبارة عن attribute بيحتوي على finite أو
+
+468
+00:38:00,240 --> 00:38:08,040
+countably infinite set شو يعني countably infinite؟
+
+469
+00:38:11,760 --> 00:38:16,000
+المجموعة غير منتهية لكن ممكن تجي عند حد معين فيها
+
+470
+00:38:16,000 --> 00:38:21,220
+يعني مثلا اجي اقولك عدد الأيام اللي على الكورة
+
+471
+00:38:21,220 --> 00:38:25,700
+الأرضية من
+
+472
+00:38:25,700 --> 00:38:28,280
+يوم الناس اللي صار ال big bang او الانفجار الكوني
+
+473
+00:38:28,280 --> 00:38:34,180
+العظيم حسب تعوت الجيلوجيا غداش عمر الكورة الأرضية
+
+474
+00:38:34,180 --> 00:38:36,420
+او عمر الحياة على الكورة الأرضية
+
+475
+00:38:39,180 --> 00:38:43,320
+انت ملاحظ؟ عملك بتديني رقم والرقم هذا جد مابدو
+
+476
+00:38:43,320 --> 00:38:47,720
+يكون كبير بقى تقولي .. بتقولي مستمر مستمر أخريته
+
+477
+00:38:47,720 --> 00:38:53,080
+اليوم لما نعيش بكرة بنعده عشان هي غير منتهية لكن
+
+478
+00:38:53,080 --> 00:39:00,080
+هياش مستمرة في العدد بس كوني أنا بعدهم كون انه
+
+479
+00:39:00,080 --> 00:39:03,140
+ممكن انا اعد Sir countable
+
+480
+00:39:06,570 --> 00:39:09,150
+ماشي الحال هو برقملك إياها جالك مليون مليون في
+
+481
+00:39:09,150 --> 00:39:12,030
+جيار الكبير هاي اليوم رقم صفر او اليوم رقم واحد
+
+482
+00:39:12,030 --> 00:39:17,050
+اول يوم و هذا كان قبل مثلا مش عارف تريليون سنة مش
+
+483
+00:39:17,050 --> 00:39:20,990
+مليون .. كام تريليون سنة لاحظوا أنه كونه دالي
+
+484
+00:39:20,990 --> 00:39:25,370
+أعداد لكن في الأيام الآن لو أنا إجيت اتطلعت في ال
+
+485
+00:39:25,370 --> 00:39:31,630
+gap بين كل يوم و التاني خلّيني
+
+486
+00:39:31,630 --> 00:39:37,840
+أقول للتفاصيل تبعته اليوم 24 ساعةماشي الحال الاربع
+
+487
+00:39:37,840 --> 00:39:43,600
+عشرين ساعة او الساعة فيها ستين دقيقة والستين دقيقة
+
+488
+00:39:43,600 --> 00:39:50,680
+فيها ستين ثانية الستان ثانية فيها milli second
+
+489
+00:39:50,680 --> 00:39:59,500
+مظبوط بس في لحظة من اللحظات هيجف على الرغم ان احنا
+
+490
+00:39:59,500 --> 00:40:04,520
+فعليا شايفينها infinite set لكن المجموعة هذه ممكن
+
+491
+00:40:04,520 --> 00:40:11,210
+تعدلو انا اجيت سألتك بدي عمرك تديني عمرك بال ..
+
+492
+00:40:11,210 --> 00:40:17,210
+بالسنة والشهر واليوم والساعة والدقيقة والثانية
+
+493
+00:40:17,210 --> 00:40:25,330
+ممكن ينحسب، مصبور؟ طيب،
+
+494
+00:40:25,330 --> 00:40:29,670
+الان هذه الكلام ليش عمال بحاول بازيد و بعيد في
+
+495
+00:40:29,670 --> 00:40:33,630
+الان؟ لما انا بتكلم على continuous .. او discrete
+
+496
+00:40:35,050 --> 00:40:39,070
+عشرة أرقام الأقسام اللي عندي عشرة عشرين تلاتين
+
+497
+00:40:39,070 --> 00:40:47,250
+أربعين خمسين finite مصبوط ليش لأنه فعليا مافيش
+
+498
+00:40:47,250 --> 00:40:52,130
+عندي أنا أي حاجة بين الأربعين والخمسين مافيش عندي
+
+499
+00:40:52,130 --> 00:40:55,430
+ولا قسم رقم واحد واربعين أو خمسة واربعين أو تسعة
+
+500
+00:40:55,430 --> 00:40:58,810
+واربعين هذه الأرقام اللي موجودة عندي هذه فهذه بقول
+
+501
+00:40:58,810 --> 00:41:03,460
+عنها إيشdiscrete يعني لو كانت الأرقام أو القيم
+
+502
+00:41:03,460 --> 00:41:08,100
+اللي عندهان finite او كان تبلي infinite values
+
+503
+00:41:08,100 --> 00:41:12,000
+فبقول عنها دي discrete values الآن لو بسكت المصطرة
+
+504
+00:41:12,000 --> 00:41:16,080
+انا يا شباب بسكت المصطرة اللي بجينا نستخدمها زمان
+
+505
+00:41:16,080 --> 00:41:18,920
+ماعرفش دايما تستخدموها ولا لأ تلاتين صنط طولة
+
+506
+00:41:18,920 --> 00:41:24,320
+بقولها وكل صنط فيه عشرة milli صح؟ الان لو انا بدي
+
+507
+00:41:24,320 --> 00:41:29,140
+اطلع على عدد الصنطيات اللي موجودةdiscrete اذا أنا
+
+508
+00:41:29,140 --> 00:41:32,240
+بتكلم بالصنطي الصنطي الأول التاني التالت الرابع
+
+509
+00:41:32,240 --> 00:41:36,260
+الخامس لحد التلاتين واذا طلعت على المليات اللي
+
+510
+00:41:36,260 --> 00:41:40,720
+موجودة برضه ممكن تكون هذه finite و discrete لأنه
+
+511
+00:41:40,720 --> 00:41:47,460
+بين الملي والتاني gap عادة الامور هذه ممكن تعمل
+
+512
+00:41:47,460 --> 00:41:53,520
+شوية ربكة بسيطة في التفريق في المقابل continuous
+
+513
+00:41:54,680 --> 00:41:59,560
+ماذا يعني continuous؟ بين أي قيمتين في ال
+
+514
+00:41:59,560 --> 00:42:04,320
+continuous بين أي قيمتين ممكن ألاقي قيمة غيرهم كفش
+
+515
+00:42:04,320 --> 00:42:11,980
+جاب بين أي قيمتين بلاجي قيم بينهم الآن في العشر
+
+516
+00:42:11,980 --> 00:42:17,200
+وعشرين وتلاتين ماكانش فيه مصبوط؟ الأرقام اللي احنا
+
+517
+00:42:17,200 --> 00:42:23,700
+كتبناها أرقام الطلابالان اقول عنها continuous ولا
+
+518
+00:42:23,700 --> 00:42:28,920
+اقول عنها discrete لان مافيش و نص في عندى واحد هي
+
+519
+00:42:28,920 --> 00:42:34,260
+ال unit تبعتي هي unit القياس تبعتي الان discrete
+
+520
+00:42:34,260 --> 00:42:41,980
+الان continuous لما يكون في عندى real number لما
+
+521
+00:42:41,980 --> 00:42:48,450
+يكون في عندىreal number يعني هيك أحط في بالي أنا
+
+522
+00:42:48,450 --> 00:42:54,930
+أي أعداد كانت عبارة عن integer integer accountable
+
+523
+00:42:54,930 --> 00:42:59,150
+integer accountable معناه تقعد بتروح وين؟ باتجاه
+
+524
+00:42:59,150 --> 00:43:03,930
+ال discrete ال discrete ليش؟ لأنه بين أي قيمتين
+
+525
+00:43:03,930 --> 00:43:10,750
+مابلجيش إيش قيمة عادة إن يا جماعة الخيرإذا لاجيت
+
+526
+00:43:10,750 --> 00:43:15,130
+كلام بسيط جدا مالوش علاقة بالرياضيات إذا ال step
+
+527
+00:43:15,130 --> 00:43:18,170
+between
+
+528
+00:43:18,170 --> 00:43:25,510
+any two values as a jump لو
+
+529
+00:43:25,510 --> 00:43:29,650
+كانت بتحسها هذه زي قفزة أو في مدى فهذه غالبا
+
+530
+00:43:29,650 --> 00:43:35,190
+discrete لو
+
+531
+00:43:35,190 --> 00:43:42,130
+كانت الخطوة أو الانتقال as smallor tiny step لو
+
+532
+00:43:42,130 --> 00:43:47,010
+كانت خطوة بسيطة معناته أنا بتكلم على إيش؟
+
+533
+00:43:47,010 --> 00:43:52,730
+continuous عشان
+
+534
+00:43:52,730 --> 00:43:58,670
+هيك لما باجه على الأرقام أو المسافات أو ما شابه
+
+535
+00:43:58,670 --> 00:44:02,770
+ممكن أنا أدرج فيها لحد ما أصل الملي متر لأن لما
+
+536
+00:44:02,770 --> 00:44:07,180
+أصل الملي ما جديش خطوة بين الملي والتانيلكن الملي
+
+537
+00:44:07,180 --> 00:44:11,280
+مع الـ kilometer بتصير الآن فعلياً العدد كبير و
+
+538
+00:44:11,280 --> 00:44:14,620
+join steps وبالتالي أنا بتكلم على small او بتكلم
+
+539
+00:44:14,620 --> 00:44:19,480
+عفوا على continuous values temperature و ال height
+
+540
+00:44:19,480 --> 00:44:25,560
+و ال weight شو رايكوا فيهم continuous continuous
+
+541
+00:44:25,560 --> 00:44:29,440
+او لأنه فيه fraction و زي ما قلنا قبل شوية بالمثال
+
+542
+00:44:29,440 --> 00:44:33,040
+السابق لما اتكلمنا على الأطفال او زن الأطفال حديثي
+
+543
+00:44:33,040 --> 00:44:40,180
+الولادةرح كتب الطبيب 2450 جرام لو الميزان اللى وزن
+
+544
+00:44:40,180 --> 00:44:46,700
+عليه الطفل كتبه 53 هتلاقيه هيكتبه 53 ليش؟ لأن ال
+
+545
+00:44:46,700 --> 00:44:50,080
+value فعليا لازم تكون بتفاصيلها الدقيقة الأبعد حد
+
+546
+00:44:50,080 --> 00:44:54,660
+الان هل ممكن الولد اللى بعديه او قبله جداش ال
+
+547
+00:44:54,660 --> 00:44:59,720
+value ممكن تكون طب ممكن يكون اربع .. ممكن يكون ..
+
+548
+00:44:59,720 --> 00:45:04,760
+جداش احنا قولنا 45يصير خمسين أو يصير اتخاذ اتخاذ
+
+549
+00:45:04,760 --> 00:45:05,600
+اتخاذ اتخاذ اتخاذ اتخاذ اتخاذ اتخاذ اتخاذ اتخاذ
+
+550
+00:45:05,600 --> 00:45:07,880
+اتخاذ اتخاذ اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز
+
+551
+00:45:07,880 --> 00:45:08,280
+اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز
+
+552
+00:45:08,280 --> 00:45:08,840
+اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز
+
+553
+00:45:08,840 --> 00:45:14,580
+اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز
+
+554
+00:45:14,580 --> 00:45:20,420
+اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز اتخاز
+
+555
+00:45:20,420 --> 00:45:28,370
+اتخاز اتخاز اتخاز افي كل document بيحتوي على
+
+556
+00:45:28,370 --> 00:45:31,690
+مجموعة من الكلمات فعندي رقم ال document وعدد
+
+557
+00:45:31,690 --> 00:45:34,450
+الكلمات اللي فيها فعدد الكلمات ال attribute هذا
+
+558
+00:45:34,450 --> 00:45:38,590
+discrete ولا continuous؟ discrete لأن القيم متقطعة
+
+559
+00:45:38,590 --> 00:45:43,710
+ومافيش بينها روابط لأنه في الآخر بتكلم على أعداد
+
+560
+00:45:51,890 --> 00:45:55,330
+بعد ما حاولنا نفهم ال data .. ال attributes وال
+
+561
+00:45:55,330 --> 00:45:59,290
+data set اللي موجود عندى من ضمن ال understanding
+
+562
+00:45:59,290 --> 00:46:06,950
+لازم أروح أحاول أعمل تحليل استكشافي للبيانات و هذا
+
+563
+00:46:06,950 --> 00:46:10,330
+التحليل الاستكشافي بطلبش مني خبرة كتيرة يعني ممكن
+
+564
+00:46:10,330 --> 00:46:13,430
+تكون بس مشكلتي مع الرسم عشان أحاول أفهم ال trend
+
+565
+00:46:13,430 --> 00:46:17,230
+تبع ال data أحاول أعمل visualization هذا ال trend
+
+566
+00:46:17,230 --> 00:46:22,820
+أو هذا ال ..التحليل الاستكشافي مهمته جدا .. مهم
+
+567
+00:46:22,820 --> 00:46:26,980
+جدا بالنسبة لي عشان يعرفنا ايه هو الرايح اذا انا
+
+568
+00:46:26,980 --> 00:46:31,400
+فعليا واقف على ارضية صلبة ال hypothesis تبعتي
+
+569
+00:46:31,400 --> 00:46:34,700
+الفرضيات اللي انا بشتغل عليها فعليا هتجيب النتيجة
+
+570
+00:46:34,700 --> 00:46:39,060
+المطلوبة ولا لأ وبناء عليه انا بالنسبة لإينا
+
+571
+00:46:39,060 --> 00:46:42,620
+الدراسة التحليلية الأولية هذه او التحليل
+
+572
+00:46:42,620 --> 00:46:48,140
+الاستطلاعي مهم جداو عادة هذا انا جاعد عمالي بحاول
+
+573
+00:46:48,140 --> 00:46:54,000
+زي ما بقوله انكوش ال data او اجلب ال data و غالبا
+
+574
+00:46:54,000 --> 00:46:57,300
+بستخدم فيها ال visualization عملية الرسم بحاول
+
+575
+00:46:57,300 --> 00:47:01,520
+ارسمها باشكال مختلفة عشان اشوف انماط البيانات اللي
+
+576
+00:47:01,520 --> 00:47:06,300
+ممكن عندي هضربلك مثال بسيط جدا هنا لو انا جيت قلت
+
+577
+00:47:06,300 --> 00:47:13,860
+على ال x axis هنا او على ال او على ال x y هنا فيه
+
+578
+00:47:13,860 --> 00:47:27,420
+بدي ارسممجموعة من النقاط نقاط باللون الأحمر بالشكل
+
+579
+00:47:27,420 --> 00:47:36,840
+هذا و نقاط باللون الأسود و
+
+580
+00:47:36,840 --> 00:47:40,880
+هاد ال data set تبعتي مكونة من two classes لحد
+
+581
+00:47:40,880 --> 00:47:42,760
+الآن أنا قاعد بأرسم في ال save side
+
+582
+00:47:46,880 --> 00:47:50,520
+ولمّا حطيت النقاط السودة هذه هان أو صار في تداخل
+
+583
+00:47:50,520 --> 00:47:54,160
+بالشكل
+
+584
+00:47:54,160 --> 00:47:59,580
+هذا هصير في عندي قناعة ان هدول ال two classes
+
+585
+00:47:59,580 --> 00:48:08,580
+متداخلين لدرجة ان من المستحيل اقدر افصل بينهم تفصل
+
+586
+00:48:08,580 --> 00:48:13,840
+بس كيف؟ راح اخسر نتفة انا مستعد اخسر كتير بس قداش
+
+587
+00:48:16,410 --> 00:48:21,170
+يعني هتقولي الآن محمد
+
+588
+00:48:21,170 --> 00:48:23,770
+بيقولي بدي أحط خط بالشكل هذا وهذا بنمثل نسبة ال
+
+589
+00:48:23,770 --> 00:48:28,050
+error صحيح؟ وهذه الخسارة كان بيتكلم عليها محمد
+
+590
+00:48:28,050 --> 00:48:32,050
+okay أنا ممكن أتفق معاه لكن ممكن أقوله كمان يا
+
+591
+00:48:32,050 --> 00:48:36,390
+محمد أنه فعليا ماعنديش خسارة مطلقا بس كل المطلوب
+
+592
+00:48:36,390 --> 00:48:41,750
+مني أن أعيد الرسم هذه في
+
+593
+00:48:41,750 --> 00:48:47,890
+ال 3D لما جيت رسمتها في ال 3Dلاقيت انه فعليا
+
+594
+00:48:47,890 --> 00:48:56,050
+المستوى
+
+595
+00:48:56,050 --> 00:49:01,770
+الـ Z أفرج مع النقاط هذه وصارت
+
+596
+00:49:01,770 --> 00:49:09,270
+النقاط الحمرة هيها شو
+
+597
+00:49:09,270 --> 00:49:13,750
+رأيك يا محمد الآن؟ في مجال ان انا افصل بينهم بدون
+
+598
+00:49:13,750 --> 00:49:15,490
+ما اخسر؟ اه في مجال
+
+599
+00:49:18,370 --> 00:49:26,390
+يعني فعليا شوية حطيتلك اياهم هيك وانت بتطلع الآن
+
+600
+00:49:26,390 --> 00:49:31,030
+شو شايف انت شايف ال cover تبعت ال pointer شايف ال
+
+601
+00:49:31,030 --> 00:49:34,230
+pointer على الرغم ان انا قاعد بقولك ان ال pointer
+
+602
+00:49:34,230 --> 00:49:40,170
+موجود بتقوللي ابد انا مش جادر اشوفه ممتاز روحت
+
+603
+00:49:40,170 --> 00:49:44,740
+عملت rotate فقطيعني بدل ما انت كنت شايف 2D خليك
+
+604
+00:49:44,740 --> 00:49:49,820
+تشوف 3D بالشكل هذا فصار في مجال اتكلم على ان ال
+
+605
+00:49:49,820 --> 00:49:52,800
+object site هذا بدون الدراسة الاستكشافية او
+
+606
+00:49:52,800 --> 00:49:58,520
+التحليل الاستكشافي لل data مش هيكون في نتيجة مرضية
+
+607
+00:49:58,520 --> 00:50:02,300
+بمعنى يا شباب اذا انا ماحاولتش اشوف افهم ال data
+
+608
+00:50:02,300 --> 00:50:06,540
+قبل ما اروح فيها انا في الآخر هاروح فيها هيكون كل
+
+609
+00:50:06,540 --> 00:50:11,760
+جهديعلى الفاضي لإيش؟ لإن إذا ضليت بالمنظر هذا ما
+
+610
+00:50:11,760 --> 00:50:15,980
+هي تحكول فيه عندي ال system هتدي نسبة خطأ مرتفعة
+
+611
+00:50:15,980 --> 00:50:21,980
+الجال محمد عليها بس شوية إيش هخسر بينما .. بينما
+
+612
+00:50:21,980 --> 00:50:26,120
+إنه أنا فعليا شغل بسيط يا هاشم كان بيقوللي لأ يعني
+
+613
+00:50:26,120 --> 00:50:29,400
+أنت ممكن تحصل على model يفصل بينهم بدون أي خسارة و
+
+614
+00:50:29,400 --> 00:50:34,890
+ال accuracy one hundred percentهذا الكلام بقويني
+
+615
+00:50:34,890 --> 00:50:37,990
+أو بديني confidence عالي ان انا استمر ان انا شغال
+
+616
+00:50:37,990 --> 00:50:41,610
+في ال track الصح ان ال data هذه ممكن من البداية
+
+617
+00:50:41,610 --> 00:50:46,030
+تكون تديني نتيجة نحا الشغل التاني اذا انت كنت عادة
+
+618
+00:50:46,030 --> 00:50:53,450
+بتدور على donor او ناس على اي نوع من ال funds اللي
+
+619
+00:50:53,450 --> 00:50:57,030
+ممكن تفعلك اياها الناس او المؤسسات الناس بهم هتشوف
+
+620
+00:50:57,030 --> 00:51:01,710
+result فإذا انت مجرد تتكلم معاهعلى الفاضل، لكن
+
+621
+00:51:01,710 --> 00:51:04,550
+بتقول هو هي في عندك دراسة تحليلية بسيطة على وين
+
+622
+00:51:04,550 --> 00:51:08,630
+إحنا رايحين تمام؟ ممكن تصير في عندك توفر قناعة
+
+623
+00:51:08,630 --> 00:51:13,690
+أكتر للشخص اللي موجود عندها هدف الدراسة التحليلية
+
+624
+00:51:13,690 --> 00:51:20,610
+الأساسي أنه أنت فعليا تصير تتعامل أو تندمج أنت و
+
+625
+00:51:20,610 --> 00:51:23,410
+البيانات تصير تحس في البيانات أو في ال data اللي
+
+626
+00:51:23,410 --> 00:51:26,410
+موجودة عندك بشكل عفوي تصير يعني بين قوسين يعني
+
+627
+00:51:26,410 --> 00:51:31,500
+تصير أنت و البيانات واحدتصير فاهم البيانات زي ما
+
+628
+00:51:31,500 --> 00:51:35,400
+انت فاهم حاجة جسمك متى بده يرتاح، متى بدك تاكل،
+
+629
+00:51:35,400 --> 00:51:39,920
+متى بدك تاخد shower إلى آخره هذه حاجتك انت
+
+630
+00:51:39,920 --> 00:51:42,560
+بتعرفها، اكتر واحد بتقدرها في اللحظة اللي بتصير
+
+631
+00:51:42,560 --> 00:51:46,100
+انت familiar مع البيانات بالشكل هذا معناته انت
+
+632
+00:51:46,100 --> 00:51:50,120
+تأكد تماما على خطوات ناجحة بإذن الله في موضوع ال
+
+633
+00:51:50,120 --> 00:51:55,860
+project الشغل التاني إذا انا عملت الدراسة
+
+634
+00:51:55,860 --> 00:52:01,470
+الاستطلاعية هذهبتقوّل فرضيات تبعتي وبتقول فعليا
+
+635
+00:52:01,470 --> 00:52:04,390
+انا بقدر اجيب مجموعة من الفرضيات القوية اللي انا
+
+636
+00:52:04,390 --> 00:52:08,890
+ابني عليها اه شوف بتكون عينك قوية على رأي اهاب
+
+637
+00:52:08,890 --> 00:52:14,530
+وانت بتتكلم انه انا فعليا قادر على انجاز كذا وفي
+
+638
+00:52:14,530 --> 00:52:17,810
+موضوع ال pilot study و الدراسة التحليلية انا خدت
+
+639
+00:52:17,810 --> 00:52:23,550
+تجربة بسيطة فقط في المقترح يسالة الدكتوراهكان
+
+640
+00:52:23,550 --> 00:52:26,650
+بيقولوا لازم على الأقل تمور تلت فصول قلت له أنا
+
+641
+00:52:26,650 --> 00:52:29,910
+عند مقترح و أنا في الفصل التاني قلت مقترح تبعي
+
+642
+00:52:29,910 --> 00:52:35,110
+جاهز ماحدش سمععملت دراسة استطلاعية زي هيكت تحليل
+
+643
+00:52:35,110 --> 00:52:38,650
+قلت لهم أنا جاهز وعندي دراسة تحليلية بس سمعوا
+
+644
+00:52:38,650 --> 00:52:43,630
+دراسة استطلاعية و بيسموها pilot study قال تعالي
+
+645
+00:52:43,630 --> 00:52:46,790
+اعمل presentation عملت presentation فقرروني ودخلت
+
+646
+00:52:46,790 --> 00:52:50,710
+ال discussion ال proposal defense وانا في الفصل
+
+647
+00:52:50,710 --> 00:52:54,190
+التاني ليش؟ لأنه بيقولك لسه يعني انت مش فاهم
+
+648
+00:52:54,190 --> 00:52:57,870
+الموضوع بس كون ان في عندي دراسة انا اساسية
+
+649
+00:52:57,870 --> 00:53:01,370
+وتحليلية استطلاعية مش على كل شيء عيني انا اخد
+
+650
+00:53:02,390 --> 00:53:06,370
+prototype ففعليا يثبت للناس اللي موجودين ان الفكرة
+
+651
+00:53:06,370 --> 00:53:11,170
+هي applicable أو ممكن يكتبلها إيش النجاح و هذا كله
+
+652
+00:53:11,170 --> 00:53:14,230
+بديك زي ما قلتلك بديك بخليك تعيش مع ال data حقيقة
+
+653
+00:53:14,230 --> 00:53:20,750
+و تبني فرضيات قوية ال data هذه لوين ممكن اتواصلك
+
+654
+00:53:20,750 --> 00:53:26,870
+بدي أديك مثال بسيط جدا الان فينا online shop
+
+655
+00:53:26,870 --> 00:53:32,860
+الدكان الإلكتروني أو متجر إلكترونيوالمتجر هذا كان
+
+656
+00:53:32,860 --> 00:53:37,700
+عنده زباين عنده قائمة بالزباين اللي موجودين عنده
+
+657
+00:53:37,700 --> 00:53:43,520
+فبعد سنة راح عمل دراسة بده يشوف عدد او بده يشوف
+
+658
+00:53:43,520 --> 00:53:50,300
+الزبائن تابعونه عدد مرات الزيارة للمتجر هذا الان
+
+659
+00:53:50,300 --> 00:53:56,230
+in the count عدد مرات الزيارةأو بنجوسين نسميها عدد
+
+660
+00:53:56,230 --> 00:54:00,950
+مرات الشراء ان شئت وفي عندى ال customer age أعمار
+
+661
+00:54:00,950 --> 00:54:06,650
+الناس من الدراسة اللى موجودة عندى هان ايش بقى الآن
+
+662
+00:54:06,650 --> 00:54:14,120
+نعم عمر ال 50 ل 80 اكتر ناس ماشتغلهاالان كمان مرة
+
+663
+00:54:14,120 --> 00:54:18,060
+هى الرسماء راح جالك هى كل الزباين تعونى وعدد مرات
+
+664
+00:54:18,060 --> 00:54:22,580
+الشراء اللى تمت من خلال المتجر خلال السنة واضح ان
+
+665
+00:54:22,580 --> 00:54:31,820
+الناس اللى بتراوحوا من ال 51 او 52 سنة لحد 83
+
+666
+00:54:31,820 --> 00:54:41,340
+تقريبا تمام او لأ 78بالـ 78 هدولة أكثر الناس شراء
+
+667
+00:54:41,340 --> 00:54:48,000
+عن الموقع يعني بينجوسين فئة الشباب نافرة من .. من
+
+668
+00:54:48,000 --> 00:54:53,140
+الموقع أو بينجوسين إن الموقع هدب اتناسب مع المسنين
+
+669
+00:54:53,140 --> 00:55:00,420
+أكثر من الشباب مصبوط؟ طب هو ممكن تكون الشغلات اللي
+
+670
+00:55:00,420 --> 00:55:08,540
+معروضة موجهة للمسنين الآن إذا صاحب المتجرقرر يزيد
+
+671
+00:55:08,540 --> 00:55:12,680
+عدد الزبائن اللي موجودين عنده إيش المفروض يساوي
+
+672
+00:55:12,680 --> 00:55:19,320
+يروح يدرس هدول إيش الشغلات اللي أخدوها أو آلية عرض
+
+673
+00:55:19,320 --> 00:55:22,760
+البضاعة أو آلية تسويقها أو أو إلى آخره ويحاول
+
+674
+00:55:22,760 --> 00:55:26,920
+يسقطها على الفئة اللي هو إيش بده يستهدفها عشان
+
+675
+00:55:26,920 --> 00:55:30,160
+يقدر يجيب نتيجة الآن هذا الكلام مستحيل كنت أنا
+
+676
+00:55:30,160 --> 00:55:35,680
+أفهمه لو فعليا طلعت فقط على الـ two attributesالـ
+
+677
+00:55:35,680 --> 00:55:39,980
+Age والـ Count أو عدد مرات الشراء و لا شو رايكوا؟
+
+678
+00:55:39,980 --> 00:55:44,340
+من المستحيل أن تصلّى هيك شغلة لكن بالـ Graph صار
+
+679
+00:55:44,340 --> 00:55:47,880
+في عندى Pattern واضح و ال Pattern هذا لو أنا خطبت
+
+680
+00:55:47,880 --> 00:55:52,680
+فيه ال Top Level Manager في المؤسسة هيفهمه بدون أي
+
+681
+00:55:52,680 --> 00:55:59,200
+مشاكل تمام يا جماعة الخير؟ طيب احنا تقريبا خلصنا
+
+682
+00:55:59,200 --> 00:56:05,400
+اليومالان بدأ نجمع data set لأول خطوة عملية انا
+
+683
+00:56:05,400 --> 00:56:09,980
+بدي اشغل عليها ال data set هي بتكون تتناسب مع ال
+
+684
+00:56:09,980 --> 00:56:13,160
+task سابق انا طلبت منكوا تبدوا تشكلوا مجموعات
+
+685
+00:56:13,160 --> 00:56:17,460
+وفتحتلكوا على ال forum على ال model ان زعيم
+
+686
+00:56:17,460 --> 00:56:21,560
+المجموعة زعيم العصابة يحط أسماء عصابته الان شو
+
+687
+00:56:21,560 --> 00:56:25,640
+المطلوب مني في ال data sets مطلوب مني شغلتين مطلوب
+
+688
+00:56:25,640 --> 00:56:28,960
+مني اختار two data sets واحدة لل classification
+
+689
+00:56:33,880 --> 00:56:39,520
+والتاني للـ regression شو
+
+690
+00:56:39,520 --> 00:56:43,340
+يعني classification؟ بدي اعمل ال predict لل label
+
+691
+00:56:43,340 --> 00:56:46,580
+ال predict لل category وال regression بدي اعمل ال
+
+692
+00:56:46,580 --> 00:56:51,420
+predict لل value ال continuous value تمام؟ بل وين
+
+693
+00:56:51,420 --> 00:56:54,940
+بدي اجيبهم؟ ال internet مليانة هاي قدامك تلت نماذج
+
+694
+00:56:54,940 --> 00:56:58,970
+ال kaggleوهذه الـ Completed Platform بتقدر الـ
+
+695
+00:56:58,970 --> 00:57:01,770
+Machine Learning و الـ Data Science ممكن تجرب فيها
+
+696
+00:57:01,770 --> 00:57:04,630
+ال Algorithm و ال Data Sets الاخره بتوفرلك Jupiter
+
+697
+00:57:04,630 --> 00:57:07,510
+Notebooks بالبايتون في عندك ال UCI Machine
+
+698
+00:57:07,510 --> 00:57:10,350
+Learning Repository بتوفرلك مجموعة من ال Data Sets
+
+699
+00:57:10,350 --> 00:57:13,670
+وإن كان بعضها قديم لكن في ال description تبعتها
+
+700
+00:57:13,670 --> 00:57:17,330
+واضحة وفي عندك من ال Data Quests كمان ممكن تختار
+
+701
+00:57:17,330 --> 00:57:22,710
+ايش المطلوب منك انت الآن كمجموعة؟ بدي اروح انا
+
+702
+00:57:22,710 --> 00:57:27,840
+ادور مثلاعلى ال classification data set ممكن انا
+
+703
+00:57:27,840 --> 00:57:39,060
+اروح اقوله مباشرة هنا free classification data set
+
+704
+00:57:39,060 --> 00:57:44,620
+وممكن اروح اقوله هاي كاجل على سبيل المثال
+
+705
+00:57:44,620 --> 00:57:51,480
+classification
+
+706
+00:57:51,480 --> 00:57:57,370
+مخطئين في كتابتها مش خاطيةهي الان find datasets
+
+707
+00:57:57,370 --> 00:58:08,990
+classification في الكاجل classification
+
+708
+00:58:08,990 --> 00:58:12,930
+في هنا في انا اربعمية و اتنين و عشرين data set في
+
+709
+00:58:12,930 --> 00:58:16,330
+competition في ال competition موجودة ال data set
+
+710
+00:58:16,330 --> 00:58:22,850
+hair diseases موجودة على ال UCI وهذه موجودة تم
+
+711
+00:58:22,850 --> 00:58:24,050
+تحميلها قبل سنتين
+
+712
+00:58:27,350 --> 00:58:32,110
+Google Landmark Data Set Blood Cell Image الاخرين
+
+713
+00:58:32,110 --> 00:58:36,010
+أنا الآن في المرحلة يا شباب بأنصحك تبعد عن ال data
+
+714
+00:58:36,010 --> 00:58:38,530
+set المكوّنة من الصور و من ال audio files و ال
+
+715
+00:58:38,530 --> 00:58:41,670
+text files هذه هنجيها في ال project الان ال data
+
+716
+00:58:41,670 --> 00:58:44,090
+set اللي هتشتغل عليها assignment اللي بين جثين
+
+717
+00:58:44,090 --> 00:58:49,490
+اللي هتتدرب عليها تمام تكون structured تكون
+
+718
+00:58:49,490 --> 00:58:52,730
+structured يعني مثلا لو أنا روحت هنا على ال UCI
+
+719
+00:58:57,270 --> 00:59:00,510
+في جوجل data sets في مجموعة كبيرة شباب انت مجرد
+
+720
+00:59:00,510 --> 00:59:07,750
+اكتب بس free data sets UCI
+
+721
+00:59:07,750 --> 00:59:17,450
+machine learning data sets بال
+
+722
+00:59:17,450 --> 00:59:20,830
+UCI في ال repository اللي موجود عندي هان الميزة عن
+
+723
+00:59:20,830 --> 00:59:26,510
+الكاجل او عن المواقع التانيةإنه فعليا بدي أمصن في
+
+724
+00:59:26,510 --> 00:59:30,070
+ال data set بسهولة يعني لو أنا قلتله في ال default
+
+725
+00:59:30,070 --> 00:59:33,230
+task هتلاقي فيه عنده classification, regression,
+
+726
+00:59:33,410 --> 00:59:35,930
+clustering إلى آخرين أنا بدي data set ل
+
+727
+00:59:35,930 --> 00:59:38,730
+classification واحدة ل regression فممكن قادي
+
+728
+00:59:38,730 --> 00:59:43,790
+مباشرة هان أروح على ال classification مجرد أختار
+
+729
+00:59:43,790 --> 00:59:44,530
+في ال classification
+
+730
+00:59:50,000 --> 00:59:53,520
+هذه هي ال classification هذه كل ال data sets الآن
+
+731
+00:59:53,520 --> 00:59:56,780
+في عنده تلاتمية و ستين data sets الأولى مثلا ال
+
+732
+00:59:56,780 --> 00:59:59,880
+two gigahertz indoor channel measurement نتكلم عن
+
+733
+00:59:59,880 --> 01:00:03,340
+ال wifi signalsتمام بقول ال classification
+
+734
+01:00:03,340 --> 01:00:07,020
+multivariate ال data types ال attributes real عدد
+
+735
+01:00:07,020 --> 01:00:12,940
+الصفوف 7840 عدد ال attributes خمسة والسنة اللي تم
+
+736
+01:00:12,940 --> 01:00:16,440
+عليها رفع البيانات اللي موجودة يعني مثلا لو أجينا
+
+737
+01:00:16,440 --> 01:00:23,590
+اتكلمنا عن ال .. ال nearing .. السيرartificial
+
+738
+01:00:23,590 --> 01:00:26,950
+character أو الناس اللي في عندها المشكلة في السمع
+
+739
+01:00:26,950 --> 01:00:31,670
+نفس الكلام انت ممكن تدور على ال data set اللي انت
+
+740
+01:00:31,670 --> 01:00:35,050
+بتشوفها مناسب لكن .. لكن بما ان احنا بنشتغل
+
+741
+01:00:35,050 --> 01:00:39,410
+كمجموعات مطلوب منك اسم ال data set و description
+
+742
+01:00:39,410 --> 01:00:45,570
+تبعتها و ال URL تبعتها تحطهم وينعلى ال forum عشان
+
+743
+01:00:45,570 --> 01:00:48,990
+اللي بيحط مثلا الشباب في الأول مجموعة الأولى اختار
+
+744
+01:00:48,990 --> 01:00:52,170
+ال data set خلاص انت مجبر تدور على data set تاني
+
+745
+01:00:52,170 --> 01:00:57,510
+وما تسألنيش يا دكتور انا اللي بيعمل post قبل هو
+
+746
+01:00:57,510 --> 01:01:00,510
+صاحب السبق في ال data set اللي موجودة ليش؟ لأني
+
+747
+01:01:00,510 --> 01:01:02,910
+بدي أحاول يكون في عندى أكبر قدر ممكن من ال
+
+748
+01:01:02,910 --> 01:01:08,770
+variation بين المجموعات انت و نصيبك اشتهدلأ لأ لأ
+
+749
+01:01:08,770 --> 01:01:11,110
+لأ هذه يا شباب النواقع اللي انا طرحتها على ال
+
+750
+01:01:11,110 --> 01:01:14,610
+slides قدامك هي عبارة عن بقعة samples يعني الجوجل
+
+751
+01:01:14,610 --> 01:01:18,250
+فيها data sets الفيسبوك بتوفرك data sets لتويتر
+
+752
+01:01:18,250 --> 01:01:21,770
+بتوفرك data sets لكن انا في المرحلة الحالية بقولك
+
+753
+01:01:21,770 --> 01:01:27,510
+المقلوب منك data set a structured data setإيش
+
+754
+01:01:27,510 --> 01:01:32,390
+هتعمل فيها بس جيبها افهم افهم عن إيش بتتكلم عدد ال
+
+755
+01:01:32,390 --> 01:01:35,170
+instances عدد ال attributes اللي فيها أنواع ال
+
+756
+01:01:35,170 --> 01:01:38,170
+attributes اللي فيها إيش هي عشان المحاضرة الجاية
+
+757
+01:01:38,170 --> 01:01:46,890
+فعليا إحنا هنبدأ نشتغل مع أول Python
+
+758
+01:01:46,890 --> 01:01:51,230
+أو RapidMiner واحد
+
+759
+01:01:51,230 --> 01:01:54,760
+اللي بدي يشتغل إيش بدي فيه جنته الأربعة؟الان احنا
+
+760
+01:01:54,760 --> 01:01:56,980
+من المحاضرة الجاية هنبدأ نتكلم عن ال data
+
+761
+01:01:56,980 --> 01:02:00,220
+preparation محاضراتنا التلاتة الماضيات او التنتين
+
+762
+01:02:00,220 --> 01:02:02,660
+الماضيات كانوا في ال data understanding في فهم
+
+763
+01:02:02,660 --> 01:02:07,000
+البيانات الان في تحضير البيانات لل mining تلزمك ال
+
+764
+01:02:07,000 --> 01:02:09,920
+data set عشان لما اقولك روح تدور على ال noise وقل
+
+765
+01:02:09,920 --> 01:02:13,240
+في عندك noise في ال data set ولا لأ طبعا الشباب
+
+766
+01:02:13,240 --> 01:02:17,580
+عشان برضه نكون منصفين الشغل الشغل بدي يكون جماعي
+
+767
+01:02:17,580 --> 01:02:21,420
+يعني ماترضاش انت ان واحد عندك في المجموع يكون
+
+768
+01:02:21,420 --> 01:02:25,250
+اتكالي معتمدي عليك لأنه مش هياخد نفس علامتكأو بين
+
+769
+01:02:25,250 --> 01:02:31,030
+بوسين حرام تنزل انت لعلامته برضه
+
+770
+01:02:31,030 --> 01:02:36,770
+بتشغله اللي انت بتشوفه مناسب غالبا ترضه
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/aMsNbWzP5iY.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/aMsNbWzP5iY.srt
new file mode 100644
index 0000000000000000000000000000000000000000..d36eb7fb68fcfa1a0d7aa356a7c665ac4e128a22
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/aMsNbWzP5iY.srt
@@ -0,0 +1,1719 @@
+1
+00:00:01,850 --> 00:00:03,950
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:03,950 --> 00:00:09,330
+أهلا وسهلا بكم إخواني وأخواتي في لقاء أو في تسجيل
+
+3
+00:00:09,330 --> 00:00:13,170
+لكن هذه المرة شغل عملي بالبايثون ل data preparation
+
+4
+00:00:13,850 --> 00:00:16,490
+المثال الذي أنا هشتغل عليه إن شاء الله تعالى سيغطي
+
+5
+00:00:16,490 --> 00:00:20,810
+كثيرًا من الجوانب المهمة التي ممكن تلزمكم سواء خلال
+
+6
+00:00:20,810 --> 00:00:24,890
+الـ course أو لاحقًا طبعًا، لن أخفيكم، أنا هشتغل على الـ
+
+7
+00:00:24,890 --> 00:00:28,810
+database الـ iris، طبعًا الـ database صغيرة نوعًا ما
+
+8
+00:00:28,810 --> 00:00:33,230
+عملت عليها بعض الـ modification أو بين قوسين استحدثت
+
+9
+00:00:33,230 --> 00:00:38,110
+بعض المشاكل فيها، يعني أضفت كمان attribute، عملت
+
+10
+00:00:38,110 --> 00:00:40,890
+redundant rows، أضفت
+
+11
+00:00:43,780 --> 00:00:48,120
+العمود الـ raw id، الـ raw number الذي قدامنا، شايفينه؟
+
+12
+00:00:48,120 --> 00:00:52,440
+نحن هنا، وعملت فيها بعض الـ noise data، دخلت values
+
+13
+00:00:52,440 --> 00:00:56,000
+كبيرة جدًا، يعني مثلًا بدل ما هي تكون مثلًا خمسة فاصلة
+
+14
+00:00:56,000 --> 00:00:59,400
+واحد، زي القيمة التي ستظهر، دخلت واحدة و خمسين
+
+15
+00:00:59,400 --> 00:01:02,360
+وخمسين، طبعًا واضح أنه سيكون الاتجاه خاطئًا، عشان
+
+16
+00:01:02,360 --> 00:01:06,220
+أحددها، هذه كلها قياسات دخلتها بالسالب، دخلت قيمة أو
+
+17
+00:01:06,220 --> 00:01:10,390
+اثنتين بالسالب، عشان أنا أقدر أعملهم handling، فلنّينا
+
+18
+00:01:10,390 --> 00:01:13,830
+نشوف مع بعض، طبعًا أنا هشتغل على الـ .. الـ .. الـ buy
+
+19
+00:01:13,830 --> 00:01:18,190
+charm الأصلي، والأصل أن يكون فيه، عندي أنا، أفتح ملف
+
+20
+00:01:18,190 --> 00:01:23,270
+وأعمل load للـ data set، لكن عشان أخرج من جزئية أن
+
+21
+00:01:23,270 --> 00:01:26,550
+والله كل مرة أريد أن أكرر نفس العمل السابق إلى آخره،
+
+22
+00:01:26,550 --> 00:01:30,370
+سأشتغل معكم، أن أعمل خلال الـ .. الـ Jupyter notebook،
+
+23
+00:01:30,370 --> 00:01:33,470
+والـ Jupyter notebook هي عبارة عن نظام interpreter،
+
+24
+00:01:33,470 --> 00:01:39,910
+ليس نظام compiler، طبعًا نعرف الفرق بين الاثنين، أنه بالـ
+
+25
+00:01:39,910 --> 00:01:42,390
+interpreter أنا أشتغل statement by statement، و
+
+26
+00:01:42,390 --> 00:01:46,330
+أعمل run وأنتقل لما بعدها، بينما بالـ
+
+27
+00:01:46,330 --> 00:01:50,210
+بالـ compiler، لا، أنا أشغل دائمًا البرنامج من البداية،
+
+28
+00:01:50,210 --> 00:01:53,990
+عشان هيك بتلاقي الـ Google colab، معظم الـ online
+
+29
+00:01:53,990 --> 00:01:58,310
+editors أو التي لنقل online platforms التي
+
+30
+00:01:58,310 --> 00:02:00,610
+موجودة لـ data science أو لـ machine learning
+
+31
+00:02:00,610 --> 00:02:06,000
+تشتغل عليها موضوع الـ Jupyter notebook أو نظام الـ
+
+32
+00:02:06,000 --> 00:02:09,420
+notebook، لنقل بشكل سريع، ما الذي قمت به،
+
+33
+00:02:09,420 --> 00:02:12,460
+طبعًا كل هذا لا يخفى على أحد منكم، أنه أنا عملت
+
+34
+00:02:12,460 --> 00:02:16,440
+import للـ pandas، وهي الـ library المسؤولة عن قراءة
+
+35
+00:02:16,440 --> 00:02:20,760
+الـ data framework، وأنا من الآن، الـ data تبعتي
+
+36
+00:02:20,760 --> 00:02:24,320
+موجودة في iris file، موجود على نفس المجلد الذي
+
+37
+00:02:24,320 --> 00:02:27,500
+موجود عليه الملف الذي موجود عندي هنا، فببساطة أنا عملت
+
+38
+00:02:27,500 --> 00:02:30,840
+عشان أتأكد أن عملية القراءة تمت بشكل صحيح، فذهبت
+
+39
+00:02:30,840 --> 00:02:35,730
+عملت data.head، طبعًا في ميزة هنا، أيها الكرام، أنا
+
+40
+00:02:35,730 --> 00:02:38,910
+لست بحاجة، في الـ notebook أو في الـ Jupyter notebook،
+
+41
+00:02:38,910 --> 00:02:42,170
+أن أستخدم جملة print، مجرد أنني أذهب إلى الـ
+
+42
+00:02:42,170 --> 00:02:45,390
+مجرد أن أكتب اسم الـ variable، فيقوم بتنفيذ الكثير من الـ
+
+43
+00:02:45,390 --> 00:02:50,210
+tasks، وهي أيضًا ميزة أسهل من موضوع الـ printing أو
+
+44
+00:02:50,210 --> 00:02:53,850
+الجزء .. هذه الأشياء الكثير من الكتابة وأنا أعمل print
+
+45
+00:02:53,850 --> 00:02:57,050
+أو أطلب منه أن يطبع لي بعض الـ values الموجودة
+
+46
+00:02:57,050 --> 00:02:59,850
+عندي، سأقوم بإعادة التشغيل من البداية، فقط لأتأكد
+
+47
+00:02:59,850 --> 00:03:00,350
+أتأكد
+
+48
+00:03:05,140 --> 00:03:08,620
+ممتاز، الخطوة الأولى تمت، تم قراءة الـ data file، وهي
+
+49
+00:03:08,620 --> 00:03:12,620
+تبدأ بـ header file، طبعًا يمكنك وضع عدد الـ headers
+
+50
+00:03:12,620 --> 00:03:17,120
+التي تريدها، ثلاثة أو خمسة أو عشرة، ما تريد، من الـ
+
+51
+00:03:17,120 --> 00:03:21,700
+values الموجودة عندك، طيب أول خطوة أنا أريد
+
+52
+00:03:21,700 --> 00:03:25,180
+أن أفعلها، أريد أن أحاول استقراء الـ data التي عندي بشكل عام،
+
+53
+00:03:25,180 --> 00:03:28,180
+أو أريد أن آخذ نظرة على الـ data الموجودة، قلنا لابد
+
+54
+00:03:28,180 --> 00:03:31,640
+من فهم الـ data بشكل جيد، طبعًا أنا أعود وأقول أن الـ
+
+55
+00:03:31,640 --> 00:03:34,620
+iris، جميع الأعمدة التي فيها عبارة عن numerical، فهذه
+
+56
+00:03:34,620 --> 00:03:40,240
+values، باستثناء الـ label، الـ values الموجودة
+
+57
+00:03:40,240 --> 00:03:44,680
+عندي، هذه من A1 إلى A5، هي عبارة عن قياسات لزهرة
+
+58
+00:03:44,680 --> 00:03:49,320
+السوسن، طبعًا أيها الكرام، العمود الخامس، أنا هذا
+
+59
+00:03:49,320 --> 00:03:53,120
+أنا أنشأته إنشاءً، بناءً على عمل معين، لأرى العلاقة بينها عند
+
+60
+00:03:53,120 --> 00:03:58,240
+الـ correlation، ونعمل عليها، تمام، الآن كل ما أريد
+
+61
+00:03:58,240 --> 00:04:03,100
+أن أفعل هو import للـ
+
+62
+00:04:03,100 --> 00:04:03,780
+matplotlib
+
+63
+00:04:14,870 --> 00:04:20,290
+library matplotlib.pyplot
+
+64
+00:04:20,290 --> 00:04:25,950
+وطبعًا أنا ممكن أستدعي الـ class هذا بشكل مباشر، لكن
+
+65
+00:04:25,950 --> 00:04:29,750
+أنا ممكن أختصر الـ class  as plt، كما وضعنا
+
+66
+00:04:29,750 --> 00:04:34,140
+لـ pandas إذا كنا نستخدم الـ pd، سأذهب الآن، الـ data
+
+67
+00:04:34,140 --> 00:04:39,360
+التي عندي، اسمها data، إذا شئت، أنا أُقلل load الذي
+
+68
+00:04:39,360 --> 00:04:44,360
+عندي، سأقول له d تساوي data، لأظهر، أكتب الـ d فقط، و
+
+69
+00:04:44,360 --> 00:04:50,240
+سأقول له الـ d.، يوجد لدينا function اسمها hist، و
+
+70
+00:04:50,240 --> 00:04:54,600
+المقصود فيها الـ histogram، و plt.show
+
+71
+00:04:57,690 --> 00:05:02,150
+مجرد استدعاء الـ Python library اسمها
+
+72
+00:05:02,150 --> 00:05:05,430
+mathematical plotting library for python
+
+73
+00:05:09,300 --> 00:05:12,980
+matplotlib، وأريد أن أرسم الـ data، هذه الجملة فقط، لأني
+
+74
+00:05:12,980 --> 00:05:15,140
+لا أريد أن أكتب كلمة data، سأضع حرف الـ D وأمضي على
+
+75
+00:05:15,140 --> 00:05:17,720
+السريع، يعني لأريح نفسي، كما أقول لكم، هذا ما
+
+76
+00:05:17,720 --> 00:05:21,600
+طبعًا هنا مباشرةً، طبعًا التي التي التي التي التي التي
+
+77
+00:05:21,600 --> 00:05:22,080
+التي التي التي التي التي التي التي التي التي
+
+78
+00:05:22,080 --> 00:05:22,200
+التي التي التي التي التي التي التي التي التي
+
+79
+00:05:22,200 --> 00:05:22,260
+التي التي التي التي التي التي التي التي التي
+
+80
+00:05:22,260 --> 00:05:25,300
+التي التي التي التي التي التي التي التي التي
+
+81
+00:05:25,300 --> 00:05:25,320
+التي التي التي التي التي التي التي التي التي
+
+82
+00:05:25,320 --> 00:05:35,520
+التي التي
+
+83
+00:05:35,520 --> 00:05:38,590
+الآن أقول أن تم رسمها، طبعًا الرسمة أين هي؟
+
+84
+00:05:38,590 --> 00:05:53,210
+لابد أن أراها، أين هي؟
+
+85
+00:05:53,210 --> 00:05:59,410
+لابد
+
+86
+00:05:59,410 --> 00:06:00,370
+أن أراها
+
+87
+00:06:03,600 --> 00:06:09,300
+سأقوم بعمل insert cell locally، مع أنه من المفترض أن
+
+88
+00:06:09,300 --> 00:06:15,480
+التزامن بين الاثنين يكون تامًا،  هنا الـ cell
+
+89
+00:06:15,480 --> 00:06:22,210
+هو الـ library أو الناتج الذي ظهر عندي، طبعًا هنا، نرى
+
+90
+00:06:22,210 --> 00:06:26,530
+الـ histogram، توزيع الـ data بين A1, A2, A3, A4,
+
+91
+00:06:26,630 --> 00:06:31,530
+A5, A6، طبعًا، هذا هو الصحيح، طبعًا عندما قلت لكم أنا
+
+92
+00:06:31,530 --> 00:06:35,050
+أجري العمل على تسجيل الفيديو، واجهت مشكلة أنني لا أعرف
+
+93
+00:06:35,050 --> 00:06:38,190
+ما الذي تعطّل لدي في الـ python، واضطررت أن أنزل من جديد،
+
+94
+00:06:38,190 --> 00:06:42,310
+صار يظهر عندي الـ histogram، الذي أنا في الحقيقة، حتى اللحظة، لست
+
+95
+00:06:42,310 --> 00:06:46,330
+قادراً على فهمه،  أشياء، على كل حال، طبعًا، هو استثنى الـ raw
+
+96
+00:06:46,330 --> 00:06:49,710
+number الذي موجود عندي هنا، الـ
+
+97
+00:06:49,710 --> 00:06:52,850
+الـ الخامس، لم يمثلني لأنه ليس فيه distribution،  قال لي
+
+98
+00:06:52,850 --> 00:06:54,810
+والله في واحد، معظم الـ distribution في عندي
+
+99
+00:06:54,810 --> 00:06:57,550
+value كبيرة جداً، واضح أنه في عندي value كبيرة جدًا، و
+
+100
+00:06:57,550 --> 00:07:00,830
+الباقية، تكاد القيم لا تظهر بالنسبة لها،
+
+101
+00:07:00,830 --> 00:07:05,570
+التوزيع بين العناصر الموجودة عندي، واضح أنه
+
+102
+00:07:05,570 --> 00:07:11,390
+أربعة أو خمسة، بينها علاقة ربما لست
+
+103
+00:07:11,390 --> 00:07:15,350
+أعرفها، خليني، لكن بالمجمل، هو يعطيني، أنا، الـ histogram
+
+104
+00:07:15,350 --> 00:07:20,460
+يعطيني الصورة عن الـ data الموجودة، فلننتقل
+
+105
+00:07:20,460 --> 00:07:24,840
+للخطوة التالية، الآن لو أتيت على سبيل المثال،
+
+106
+00:07:24,840 --> 00:07:29,320
+كلنا متفقون أن العمود الأول، هذا الذي هو الـ raw
+
+107
+00:07:29,320 --> 00:07:32,540
+number، غير مفيد، وأنا أريد هذا العمود، أريد
+
+108
+00:07:32,540 --> 00:07:37,360
+أن أحذفه، بكل بساطة، أذهب وأقول d.
+
+109
+00:07:37,360 --> 00:07:43,020
+drop الـ
+
+110
+00:07:43,020 --> 00:07:52,350
+drop هذه تحتاج مني اسم الـ raw number، طبعًا
+
+111
+00:07:52,350 --> 00:07:59,410
+الـ axis تساوي 1، الـ x axis، طبعًا التي تمثل الصفوف،
+
+112
+00:07:59,410 --> 00:08:03,690
+تمثل 0، والأعمدة تمثل 1، طبعًا يوجد لدينا
+
+113
+00:08:03,690 --> 00:08:08,830
+command in place، هذا مهم جدًا،  أجعلها true، يعني
+
+114
+00:08:08,830 --> 00:08:12,990
+التعديل يكون مباشرًا، صحيح، طبعًا بعدها،
+
+115
+00:08:12,990 --> 00:08:19,740
+ممكن أن أذهب وأقول له الـ d. head فقط 3، فقط لأن
+
+116
+00:08:19,740 --> 00:08:23,860
+أنا أريد أن أرى العناصر الموجودة، ماذا سيحدث لها؟
+
+117
+00:08:23,860 --> 00:08:27,920
+ممتاز، تم حذفها، سأقول، كل ما فعلته هنا لأنني
+
+118
+00:08:27,920 --> 00:08:31,100
+ذهبت وقلت له d.drop، أعطيته اسم الـ attribute الذي
+
+119
+00:08:31,100 --> 00:08:37,150
+أريده، ومن ثم أنا ذهبت، قلت له، هذا الحدث في
+
+120
+00:08:37,150 --> 00:08:43,110
+الإشارة من مجموعة الأعمدة، والـ inplace، طبعًا،
+
+121
+00:08:43,110 --> 00:08:45,650
+هذا نفس الكلام نفسه، لأنه لماذا، لماذا
+
+122
+00:08:45,650 --> 00:08:48,170
+الـ axis مهم، أيها الكرام، لأنني أيضًا، نفس الـ
+
+123
+00:08:48,170 --> 00:08:51,530
+function هذه من الـ data framework التي هي D، التي
+
+124
+00:08:51,530 --> 00:08:54,230
+هي الـ pandas كـ framework، أنا أستخدم الـ method
+
+125
+00:08:54,230 --> 00:08:56,910
+تبعها، الـ drop، أيضًا، أستخدمها للصفوف، وبناءً على
+
+126
+00:08:56,910 --> 00:09:00,110
+ذلك، أنا لابد أن أحدد الـ axis، طبعًا أنا ممكن أذهب، أنا
+
+127
+00:09:00,110 --> 00:09:04,940
+أكتب هنا قائمة بالـ rows أو بالأعمدة التي أريد
+
+128
+00:09:04,940 --> 00:09:11,160
+إياها، لو أنا أريد أن أحذف مجموعة من الأعمدة، أريد أن أقول
+
+129
+00:09:11,160 --> 00:09:18,860
+A1 و A2 و A3، طبعًا، أذكرهم كنص، كما كنا ..
+
+130
+00:09:18,860 --> 00:09:22,790
+كما رأينا في المثال السابق، ممتاز، النقطة التي
+
+131
+00:09:22,790 --> 00:09:25,750
+بعدها، ننتقل الآن، يعني أنا قد حذفت
+
+132
+00:09:25,750 --> 00:09:31,990
+العناصر التي ليست لها لازمة عندي، فلأبقَ في
+
+133
+00:09:31,990 --> 00:09:35,170
+موضوع حذف الصفوف، عندما نتكلم، أنا أريد أن أحذف صفًّا
+
+134
+00:09:35,170 --> 00:09:39,510
+معينًا، نأخذ كمثال ونحاول، طيب الآن لو أنا أريد أن أبحث
+
+135
+00:09:39,510 --> 00:09:41,990
+عن الـ duplicates، الآن أنا أريد أن أمشي على الـ
+
+136
+00:09:41,990 --> 00:09:44,670
+duplicates وأرى أين يوجد duplicates في الـ rows، و
+
+137
+00:09:44,670 --> 00:09:49,350
+أذهب وأحذفها، كما قلت لكم، الـ data هذه عملت
+
+138
+00:09:49,350 --> 00:09:54,650
+عليها شئياً، اصطنعت فيها بعض الأخطاء، من أجل أن أُظهر
+
+139
+00:09:54,650 --> 00:09:57,710
+البيانات الموجودة عندي، إذا أنا الآن أريد
+
+140
+00:09:57,710 --> 00:10:03,850
+أن أشتغل على الـ duplicates، معناته سأذهب وأقول له D.drop_duplicates
+
+141
+00:10:03,850 --> 00:10:06,290
+drop_duplicates
+
+142
+00:10:12,090 --> 00:10:15,090
+طبعًا مهم في موضوع الـ duplicates، عندما أريد
+
+143
+00:10:15,090 --> 00:10:19,510
+أن أحذفها، أنني أفهم القيم التي أريدها أن تتكرر، هل
+
+144
+00:10:19,510 --> 00:10:22,450
+التكرار قيمة معينة في عمود معين، يعني على سبيل
+
+145
+00:10:22,450 --> 00:10:26,650
+المثال، لو أنا الآن ذهبت وكتبت له، وقلت له أنا أريد
+
+146
+00:10:26,650 --> 00:10:32,050
+التكرار فقط في عمود A5، معناته،  الثلاث قيم هذه
+
+147
+00:10:32,050 --> 00:10:36,740
+التي ظهرت أمامي، وكل الـ values الموجودة، point
+
+148
+00:10:36,740 --> 00:10:40,480
+ثلاث في خمسة،  تحدد أم لا، أريدها في عمودين
+
+149
+00:10:40,480 --> 00:10:43,920
+اثنين وثلاثة، اثنين وثلاثة، اثنين وثلاثة، أم أريدها
+
+150
+00:10:43,920 --> 00:10:48,140
+في أربعة أعمدة، أو أربعة أعمدة، أو ما شابه، عشان
+
+151
+00:10:48,140 --> 00:10:50,500
+هكذا، دائمًا أول attribute الذي يطلبه مني في الـ
+
+152
+00:10:50,500 --> 00:10:54,440
+duplicates، هي الـ subset، الـ subset هنا هي عبارة
+
+153
+00:10:54,440 --> 00:10:59,320
+عن مجموعة الـ attributes التي أريدها، ما هي الـ
+
+154
+00:10:59,320 --> 00:11:04,040
+attributes التي أريدها؟ مرّة أخرى، هي A واحدة، هي
+
+155
+00:11:04,040 --> 00:11:07,760
+كانت، أنا أقول له، أين يوجد rows التكرار
+
+156
+00:11:07,760 --> 00:11:14,290
+تبعها، أو القيمة تتكرر فيها، الـ values تبع A1
+
+157
+00:11:14,290 --> 00:11:18,790
+يعدّها as duplicate rows، إذا أنا وضعت هنا
+
+158
+00:11:18,790 --> 00:11:24,770
+مرّة أخرى A2، معناته أنا أقول له أين يوجد rows A1
+
+159
+00:11:24,770 --> 00:11:28,690
+و A2 متشابهتان، فهذه duplicate rows، أتمنى أن تكون
+
+160
+00:11:28,690 --> 00:11:32,370
+الصورة واضحة، في A3، خليني فقط أجربها على سبيل
+
+161
+00:11:32,370 --> 00:11:36,910
+المثال على A1
+
+162
+00:11:37,440 --> 00:11:44,840
+Okay،  ما أقول، عملت هذه أيضًا، جيد، خمسة،
+
+163
+00:11:44,840 --> 00:11:48,700
+طيب، الـ values التي بعدها، هي، أنني أريد أن
+
+164
+00:11:48,700 --> 00:11:52,720
+أقول له ماذا سيحدث لها في موضوع الـ keep في حالة وجود
+
+165
+00:11:52,720 --> 00:11:55,860
+duplicates، ماذا سيحدث؟ لأن يوجد لدينا ثلاثة خيارات في
+
+166
+00:11:55,860 --> 00:11:59,240
+الـ keep، في الـ False، لا تحتفظ بشيء، يعني
+
+167
+00:11:59,240 --> 00:12:04,970
+جميع الـ rows المكررة احذفها، هل هذا الكلام منطقي؟ يعني
+
+168
+00:12:04,970 --> 00:12:10,870
+لا يبقى أي row، في الـ attribute A5 قيمته 0.310، على
+
+169
+00:12:10,870 --> 00:12:13,650
+سبيل المثال، إذا أنا وضعت الـ False، فتبقى القيمة
+
+170
+00:12:13,650 --> 00:12:17,410
+التالية التي بعدها هي الـ first، فتبقى الـ False
+
+171
+00:12:17,410 --> 00:12:22,970
+بتؤخذ، False
+
+172
+00:12:22,970 --> 00:12:27,030
+فهكذا لا يُخزّن شيء، first
+
+173
+00:12:29,160 --> 00:12:33,020
+احتفظ بالقيمة الأولى فقط، أو القيمة التي تجدها، أو
+
+174
+00:12:33,020 --> 00:12:36,400
+الـ last، في الآخر
+
+223
+00:17:00,360 --> 00:17:07,220
+قبل هيك في عندي  doc describe  الـ function هاي
+
+224
+00:17:07,220 --> 00:17:09,460
+describe نعم
+
+225
+00:17:12,280 --> 00:17:15,960
+معلومات كاملة عن الـ Attribute Statistical
+
+226
+00:17:15,960 --> 00:17:20,480
+Description المتوسط الحسابي، الـ Standardization
+
+227
+00:17:20,480 --> 00:17:26,540
+الـ Minimum، المتوسط، أو الربع الأول، أو الربع الثاني
+
+228
+00:17:26,540 --> 00:17:31,100
+أو الربع الثالث، طبعاً بيقول لي فيه إن الـ maximum
+
+229
+00:17:31,100 --> 00:17:35,580
+value  هذي سبعة و خمسين، سنتي، سبعة و خمسين سنتي قياس
+
+230
+00:17:35,580 --> 00:17:39,500
+الزهرة، هذا الكلام يكاد يكون مستحيل، طبعاً في عندي
+
+231
+00:17:39,500 --> 00:17:43,480
+قيمة سالبة، هان هكذا، أنا صرت أنا قادر أشوف إيش الـ
+
+232
+00:17:43,480 --> 00:17:47,000
+data أو وين مشاكل الـ data، بالإضافة للموضوع، طبعاً مش
+
+233
+00:17:47,000 --> 00:17:50,300
+مبين الـ missing عندي هان إلا غير من خلال الـ count
+
+234
+00:17:50,300 --> 00:17:53,500
+إلا من غير من خلال الـ count، ممتاز، معناته أنا صار
+
+235
+00:17:53,500 --> 00:17:54,200
+في عندي الآن
+
+236
+00:17:56,930 --> 00:18:00,190
+معرفة الـ Missing اللي موجودة، طبعاً ممكن أنا أحصل
+
+237
+00:18:00,190 --> 00:18:05,430
+للـ Missing، لو كتبت الـ .. أو عملت الـ code التالي
+
+238
+00:18:05,430 --> 00:18:08,490
+أنا بدي أروح أقول له الـ missing equal
+
+239
+00:18:13,760 --> 00:18:19,980
+PD.BANDAS.DATAFRAME وانشغل
+
+240
+00:18:19,980 --> 00:18:24,820
+DataFrame جديد، وأسمي الـ attribute اللي فيه
+
+241
+00:18:24,820 --> 00:18:36,660
+missing، والـ value تبعته، الـ D.IS NULL، وأقول له
+
+242
+00:18:36,660 --> 00:18:42,220
+sum، هذه الـ function المفروض إنها بدها تمر على كل
+
+243
+00:18:42,220 --> 00:18:46,280
+الـ data frame اللي موجود عندي، والـ data وإن في عندي
+
+244
+00:18:46,280 --> 00:18:49,700
+Null تروح تحاول تعدّلها، تبعاً لمين؟ الـ attributes
+
+245
+00:18:49,700 --> 00:18:54,940
+اللي موجودة عندها، okay، عشان يجيب لي الـ value اللي
+
+246
+00:18:54,940 --> 00:18:58,900
+موجودة، أنا بضرب هقول له هات لي الـ missing اللي عندك
+
+247
+00:18:58,900 --> 00:19:06,020
+هدول، هيديني ثابت، جملة الطباعة، run وإن أنا أخطأت، آه
+
+248
+00:19:06,020 --> 00:19:07,120
+في أقواس هنا
+
+249
+00:19:12,290 --> 00:19:20,350
+هي راح جاب لي الـ a1, a2, a3, a4, a5، والـ label، هدول
+
+250
+00:19:20,350 --> 00:19:23,530
+طبعاً قال لي إن هذه عدد الـ missing اللي موجود عندك
+
+251
+00:19:23,530 --> 00:19:27,970
+موجودة في a1, a3, a2، الآخرين، طبعاً ليش أنا أعمل
+
+252
+00:19:27,970 --> 00:19:30,570
+هيك يا جماعة الخير؟ طبعاً هي البيان اللي أحصلها
+
+253
+00:19:30,570 --> 00:19:34,200
+من هنا، لكن برضه هي في طريقة ثانية ممكن أحصر الـ
+
+254
+00:19:34,200 --> 00:19:37,440
+missing بشكل واضح مع كل attribute، طبعاً لو أنتَ
+
+255
+00:19:37,440 --> 00:19:40,700
+سألتني، الـ missing اللي هان شو ممكن أسوي فيه؟ ممكن
+
+256
+00:19:40,700 --> 00:19:43,980
+أعبيه بالـ mean، أو أعبيه بالـ median، مش فارقة كتير
+
+257
+00:19:43,980 --> 00:19:48,060
+معايا، ممكن أعمله drop، بس الـ label اللي هان، حتماً
+
+258
+00:19:48,060 --> 00:19:51,700
+لازم أعمله drop، لأن هذا ما بينفع يظل، ليش؟ لأن أنا
+
+259
+00:19:51,700 --> 00:19:54,780
+عندي قياسات ومش معروف نوع الزهرة، فأنا لازم أعمله
+
+260
+00:19:54,780 --> 00:19:58,620
+drop، طيب بما إنه صار لنا نتكلم على الـ drop، خليني
+
+261
+00:19:58,620 --> 00:20:04,300
+أروح أحذف الـ .. الـ attribute اللي فيها الـ label
+
+262
+00:20:04,300 --> 00:20:14,300
+أولاً، وهي اللي بدي أحطها هنا comment، drop rows with
+
+263
+00:20:14,300 --> 00:20:20,340
+null value in a certain attribute، اللي هسويه الآن، هروح أنا أقول
+
+264
+00:20:22,730 --> 00:20:28,730
+اللي هو data equal data، الـ data frame اللي
+
+265
+00:20:28,730 --> 00:20:36,330
+موجود عندي، الـ data، أو الـ data.label.
+
+266
+00:20:36,330 --> 00:20:51,030
+not null
+
+267
+00:20:53,220 --> 00:20:58,060
+not null هكذا
+
+268
+00:20:58,060 --> 00:21:05,080
+أنا قاعد بقى أقول له نفذ لي إياها، وهذه الجملة تماماً
+
+269
+00:21:05,080 --> 00:21:09,620
+تكافئ جملة ثانية هكتبها الآن، ممكن أنا أروح أقول له
+
+270
+00:21:09,620 --> 00:21:16,680
+data equal
+
+271
+00:21:16,680 --> 00:21:23,530
+data frame اللي موجود عندي، بداخلها بيدي
+
+272
+00:21:23,530 --> 00:21:27,730
+.not null
+
+273
+00:21:29,960 --> 00:21:36,000
+null، والـ not null هاي بدي أزودها بالـ data باسم الـ
+
+274
+00:21:36,000 --> 00:21:41,260
+attribute اللي موجود عندنا، اللي هي مين؟ الـ label
+
+275
+00:21:41,260 --> 00:21:46,300
+سواء نفذت الجملة اللي فوق أو نفذت الجملة اللي تحت
+
+276
+00:21:46,300 --> 00:21:52,160
+الـ two، هيدوني نفس النتيجة، وهي إنه هيعمل drop
+
+277
+00:21:52,160 --> 00:21:57,270
+لـ الـ attribute اللي فيه الـ label، يبقى
+
+278
+00:21:57,270 --> 00:22:01,470
+فيه missing، هيرن، عشان نتأكد بدي أعيد الـ code تبع الـ
+
+279
+00:22:01,470 --> 00:22:09,210
+missing هذا الآن، ها، وهيرن، لاحظوا إنه ما فيش عندي
+
+280
+00:22:09,210 --> 00:22:12,250
+missing الآن في الـ label، طبعاً سواء نفذنا الجملة
+
+281
+00:22:12,250 --> 00:22:15,590
+الأولى يا جماعة الخير، أو الجملة الثانية، نفس الكلام
+
+282
+00:22:15,590 --> 00:22:19,370
+لكن مع اختلاف طبعاً، بنعتمد على الـ data أنا جا
+
+283
+00:22:19,370 --> 00:22:24,710
+عنها، اللي بقوله، خلص الـ data دي بتساوي d.where الـ
+
+284
+00:22:24,710 --> 00:22:30,670
+label not null اللي هي الـ values تبعته exist أو not null
+
+285
+00:22:30,670 --> 00:22:34,030
+تمام، هي كانت، أنا عملت drop، طيب بما إن وصلنا نتكلم
+
+286
+00:22:34,030 --> 00:22:37,250
+عن handling للـ missing، وهي أول واحدة عملناها هان
+
+287
+00:22:37,250 --> 00:22:41,750
+خليني أروح بعد هي كده، إيش نساوي؟ أروح نعمل الـ fill
+
+288
+00:22:41,750 --> 00:22:47,890
+بالاعتماد على الـ a2 و a3، هبتروح نعمل لهم fill بالـ
+
+289
+00:22:47,890 --> 00:22:53,730
+mean، طبعاً ليش ما بدي أعبي a1 بالـ mean؟ عندي 57
+
+290
+00:22:59,560 --> 00:23:05,720
+مقارنة بين الـ a1 و a3، خمسة وخمسة كبيرة، المين فلو
+
+291
+00:23:05,720 --> 00:23:08,960
+أنا بدي أخزن الـ median، بيمشي حالها، القيمة الوسيطة، و
+
+292
+00:23:08,960 --> 00:23:11,720
+قلنا الـ median فيها ميزة، إن لما بيعتمد عليها
+
+293
+00:23:11,720 --> 00:23:18,020
+ممكن تضيع تأثير الـ value الكبيرة الموجودة، وحد
+
+294
+00:23:18,020 --> 00:23:22,400
+هنرجع كمان مرة بنعالج الـ noise، خلينا فقط مع المين
+
+295
+00:23:23,090 --> 00:23:35,030
+هروح أبدأ بـ data of a واحد، بدها تساوي data of a
+
+296
+00:23:35,030 --> 00:23:43,870
+واحد.fillna، اللي هي not available، بإيش بدي
+
+297
+00:23:43,870 --> 00:23:49,930
+أعملها؟ في الـ data of a واحد
+
+298
+00:23:55,660 --> 00:24:04,060
+.mean، كمان هذه الأولى هنسخها
+
+299
+00:24:04,060 --> 00:24:17,100
+لـ a اتنين
+
+300
+00:24:17,100 --> 00:24:21,360
+لـ a اتنين
+
+301
+00:24:23,150 --> 00:24:26,010
+طبعاً يا جماعة الخير أنا بقى أشتغل، ولا يهمني أين
+
+302
+00:24:26,010 --> 00:24:29,850
+الخطأ أو الـ missing اللي موجودة، إذا أنا بدي الـ
+
+303
+00:24:29,850 --> 00:24:33,250
+missing، ممكن في عندي conditions، هنشوفها كمان شوية
+
+304
+00:24:33,250 --> 00:24:35,050
+زي ما لما بتدور على الـ maximum value، اللي هي
+
+305
+00:24:35,050 --> 00:24:39,390
+السبعة و خمسين، ممكن أنا أروح أطبق عليها بشكل كويس
+
+306
+00:24:39,390 --> 00:24:46,650
+انسخ هاي تلاتة
+
+307
+00:24:50,400 --> 00:24:54,340
+طبعاً أنا عملت هدول بالـ mean، وهدول بالـ median، ووراهم
+
+308
+00:24:54,340 --> 00:25:00,540
+مباشرة بدي أقول له هات لي إيش؟ حسب لي الـ missing
+
+309
+00:25:00,540 --> 00:25:05,600
+حطيتهم في نفس الـ cell عشان ما يكونش عندي مشكلة، وإن
+
+310
+00:25:05,600 --> 00:25:07,620
+شاء الله، آه، ليش هيك؟
+
+311
+00:25:16,070 --> 00:25:21,470
+مش خطأ، ودليل إنه ما ضلش في عندي values مفقودة
+
+312
+00:25:21,470 --> 00:25:29,430
+بالموجود، طب لو أنا راح قلت له d.describe
+
+313
+00:25:35,930 --> 00:25:40,790
+أوكي، كله صاروا 151، مصبوط، هي كان ما بيعيش الخياشة ده a
+
+314
+00:25:40,790 --> 00:25:45,650
+value is trying to be set to a copy of a slice
+
+315
+00:25:45,650 --> 00:25:51,030
+from that frame work، هي أشبه بالـ warning، نعم هذا هو
+
+316
+00:25:51,030 --> 00:25:57,250
+a setting with copy warning، هو بيحذرني إنه بيصير في
+
+317
+00:25:57,250 --> 00:26:03,110
+عندي تعديل على الـ data، بناءً على الـ data الموجودة، هو
+
+318
+00:26:03,110 --> 00:26:07,210
+عمال بيقول، استخدم loc، أو عمال بيقول استخدم iloc
+
+319
+00:26:07,210 --> 00:26:11,030
+بدل، مش قضيتنا كتير، بس في الآخر أنا هي الـ value
+
+320
+00:26:11,030 --> 00:26:16,630
+تبعتهم، أعمل لها iloc، ومفروض الآن ما فيش عندي
+
+321
+00:26:16,630 --> 00:26:21,910
+missing مطلقاً، طيب ننتقل بعد هيك للجزئية، إن والله
+
+322
+00:26:21,910 --> 00:26:26,690
+شو وضع الـ noise data؟ وين الـ noise data تبعي؟ طبعاً
+
+323
+00:26:26,690 --> 00:26:29,430
+أنا ممكن أستدل على noise data، أولاً بما إنه أنا
+
+324
+00:26:29,430 --> 00:26:32,990
+بتكلم على measurement، معناته هذه مش سالب تلاتة، هذه
+
+325
+00:26:32,990 --> 00:26:36,960
+تلاتة، وبما إنه أنا بتكلم على Measurement لوردة، برضه مش
+
+326
+00:26:36,960 --> 00:26:40,320
+منطقي يكون في عندي الـ maximum value هي 57، عشان هي
+
+327
+00:26:40,320 --> 00:26:44,540
+دائماً دراسة مفيدة للـ data، أو الـ contents اللي
+
+328
+00:26:44,540 --> 00:26:50,060
+موجودة عندي في كل الـ data set، طيب إيش الحل؟ كيف
+
+329
+00:26:50,060 --> 00:26:53,340
+بدنا نشوف، طبعاً هذه إشارات عندي، طبعاً في عندي طريقة
+
+330
+00:26:53,340 --> 00:27:00,120
+ثانية كمان، ممكن أنا أروح أشتغل عليها، لو أنا قلت
+
+331
+00:27:00,120 --> 00:27:03,200
+هذه الـ attributes equal، اللي هي الـ list تبعنا
+
+332
+00:27:03,200 --> 00:27:08,580
+اللي فوق، خليني بس أنسخها بدل ما إيش أكتب من ثاني
+
+333
+00:27:08,580 --> 00:27:11,760
+okay
+
+334
+00:27:15,030 --> 00:27:17,410
+هو، عاد تظهر، وضالة في الـ list، يعني، أوى المشكلة في
+
+335
+00:27:17,410 --> 00:27:21,930
+الموضوع، لأ، بدي أعدّل عليها، الـ label أنا مش بحاجة
+
+336
+00:27:21,930 --> 00:27:27,030
+ألاقيه، okay، هذه مجموعة الـ attributes اللي موجودة
+
+337
+00:27:27,030 --> 00:27:31,790
+عندي، فأنا بدي أروح أعمل .. بدي أرسم figure، هي plot
+
+338
+00:27:31,790 --> 00:27:41,070
+plt.figure، حجم الـ figure قد إيش؟ هي big size
+
+339
+00:27:44,660 --> 00:27:52,600
+مثلاً، دعوني أختار عشرين، عشرة، تمام، الـ figure هذا
+
+340
+00:27:52,600 --> 00:27:59,040
+يحتاج الـ data دي، of attributes اللي هم الخمسة
+
+341
+00:27:59,040 --> 00:28:02,840
+attributes اللي موجودة عندي، طبعاً الـ label اللي احنا
+
+342
+00:28:02,840 --> 00:28:09,200
+بدنا إياها هي nominal، لأنها مرتبة، تمام، أو بدي أروح .
+
+343
+00:28:09,200 --> 00:28:12,940
+attributes
+
+344
+00:28:12,940 --> 00:28:20,700
+.boxplot
+
+345
+00:28:20,700 --> 00:28:24,500
+الـ box plot يا جماعة الخير، هذه عبارة عشان تحدد الـ
+
+346
+00:28:24,500 --> 00:28:30,870
+outlier اللي موجود عندي، ممكن أضع للرسمة title، plt
+
+347
+00:28:30,870 --> 00:28:34,290
+.title، هذا الكلام ممكن يلزمَني في شرح التسجيل
+
+348
+00:28:34,290 --> 00:28:38,070
+الجديد اللي هو إيش؟ اللي له علاقة بالـ visualisation
+
+349
+00:28:38,070 --> 00:28:47,650
+iris attributes، وفي
+
+350
+00:28:47,650 --> 00:28:54,350
+الآخر بدي أروح أقول له show للرسم اللي موجود عندي
+
+351
+00:28:54,350 --> 00:29:02,760
+و run، آها، تمام، لاحظوا معايا الآن، هذه الرسمة جاب لي
+
+352
+00:29:02,760 --> 00:29:07,280
+الـ data، طبعاً واضح، بقول، الـ data الـ range تبعي
+
+353
+00:29:07,280 --> 00:29:10,540
+المسموح فيه، الـ outlier المسموح فيه، اللي هو داخل
+
+354
+00:29:10,540 --> 00:29:12,980
+المربعات السوداء، طبعاً اللي دول، من الخطوط السوداء
+
+355
+00:29:12,980 --> 00:29:15,240
+طبعاً إحنا لما نرسم الـ outlier، لاحظوا إن إن شاء الله
+
+356
+00:29:15,240 --> 00:29:19,580
+تعالى هنفهم الكلام بشكل كويس، بشكل أحسن، لكن واضح إن
+
+357
+00:29:19,580 --> 00:29:23,600
+هذه outlier، وهذه outlier، لأنهم بعاد تماماً، هذه جايّة
+
+358
+00:29:23,600 --> 00:29:26,400
+مع الـ fit، خليني، طبعاً لو أنا بدي أغير القيمتين هدول
+
+359
+00:29:26,610 --> 00:29:29,450
+القيمتين هدول، إحنا شفناهم، عاملين، وهي هذه سالب
+
+360
+00:29:29,450 --> 00:29:35,110
+تلاتة، وهذه سبعة وخمسين، سبعة وخمسين، تمام، طيب بدنا
+
+361
+00:29:35,110 --> 00:29:37,970
+الآن نشوف كيف بدي أتعامل مع الـ noise data اللي
+
+362
+00:29:37,970 --> 00:29:42,410
+موجودة، مع الـ noise data، بدنا ننتقل، ونكتب code
+
+363
+00:29:42,410 --> 00:29:44,510
+نشوف كيف بدي أتعامل، أو بدي أتخلص من الـ code مع الـ
+
+364
+00:29:44,510 --> 00:29:46,430
+noise data اللي موجودة
+
+365
+00:29:50,740 --> 00:29:54,560
+طيب أول حاجة أنا بدي أعرف الـ 57 هذه اللي في الـ
+
+366
+00:29:54,560 --> 00:29:57,140
+attribute الأول، جاية في أي row، عشان أروح فوق، أو
+
+367
+00:29:57,140 --> 00:30:00,060
+أروح أعدلها أو ما شابه، أنا okay، بعرف في العمود
+
+368
+00:30:00,060 --> 00:30:06,160
+الأول، لكن في أي row ما بعرف، تمام، determine the
+
+369
+00:30:06,160 --> 00:30:08,620
+noise value
+
+370
+00:30:12,090 --> 00:30:17,050
+location، أو بين قوسين الـ row، الآن عشان أحدد الـ row
+
+371
+00:30:17,050 --> 00:30:21,310
+اللي موجود، أو اللي فيه الـ data، طبعاً أنا عندي الـ
+
+372
+00:30:21,310 --> 00:30:24,190
+data، وأنا بعرف إنه موجود في الـ attribute الأول
+
+373
+00:30:24,190 --> 00:30:29,950
+فأنا بروح بقول له، اديني الـ row وين، إن الـ attribute
+
+374
+00:30:29,950 --> 00:30:36,610
+عفواً، a1 equal
+
+375
+00:30:36,610 --> 00:30:42,930
+57، إيش اللي أنا سويته هنا؟ هنا رحت وقلت له أنا بدي
+
+376
+00:30:42,930 --> 00:30:51,890
+الـ row، الـ row اللي فيه a1 equal 57، a1، لاحظوا أنا
+
+377
+00:30:51,890 --> 00:30:54,510
+بإعتماعي على الـ data، طبعاً هو لو كان فيه أكثر من
+
+378
+00:30:54,510 --> 00:30:58,450
+واحد شو يصير؟ هيديني الـ rows اللي موجودة عندهم، فراح
+
+379
+00:30:58,450 --> 00:31:02,490
+قال لي الـ row 113، هي الـ row 113، طبعاً هنقول لكم يا
+
+380
+00:31:02,490 --> 00:31:07,590
+جماعة الخير، معالجة الـ noise data غالباً manual، طبعاً
+
+381
+00:31:07,590 --> 00:31:11,430
+الـ data preparation معظمها manual، تمام، وبالتحديد
+
+382
+00:31:11,430 --> 00:31:14,930
+الـ noise ذاتَه، أنا حددتها الآن، معناته لو كان في عندي
+
+383
+00:31:14,930 --> 00:31:18,050
+أكثر من row، أكثر من row، هتكون موجودة عندي، يعني لو
+
+384
+00:31:18,050 --> 00:31:21,950
+على سبيل المثال، على سبيل المثال بدي أنا أروح أكتب
+
+385
+00:31:21,950 --> 00:31:27,950
+code مشابه للـ code هذا، بس من باب العلم
+
+386
+00:31:27,950 --> 00:31:37,550
+يعني أروح أقول له a5 بدأ تساوي تلاتة مثلاً، و
+
+387
+00:31:38,640 --> 00:31:41,420
+لاحظوا، هذاني القائمة، وبالتالي أنا بدي أعمل
+
+388
+00:31:41,420 --> 00:31:45,540
+handling لكل واحد من هدول بشكل مستقل، لما يكونوا
+
+389
+00:31:45,540 --> 00:31:47,920
+لكن هدول أنا ما بيهمنيش، أنا اللي بيهمني هالـ 113
+
+390
+00:31:47,920 --> 00:31:52,040
+تمام، طب مع الـ 113 هذا شو أنا بدي أروح أساوي الآن؟
+
+391
+00:31:52,040 --> 00:31:54,760
+بدي أعدل الـ value، الآن هذا الـ value مكتوب يا جماعة
+
+392
+00:31:54,760 --> 00:32:00,600
+الخير 57، 5
+
+445
+00:35:43,450 --> 00:35:46,350
+شغلة قبل أخيرة، لما أنا بدي اشتغل على موضوع الـ
+
+446
+00:35:46,350 --> 00:35:49,100
+correlation، أنا الـ data موجودة عندي، والـ attributes
+
+447
+00:35:49,100 --> 00:35:52,200
+اللي عندي كلها numeric، معناته أنا بدي أطبق الـ
+
+448
+00:35:52,200 --> 00:35:57,120
+correlation، في عندي method اسمها dot correlation
+
+449
+00:35:57,120 --> 00:36:00,660
+شوفي
+
+450
+00:36:00,660 --> 00:36:05,440
+مسحت الـ command، run، راح حسب الـ person الـ
+
+451
+00:36:05,440 --> 00:36:09,120
+correlation، وقال لي والله هي الـ attributes اللي عندك
+
+452
+00:36:10,330 --> 00:36:15,530
+لكن واضح أن في عندي على، طبعاً القطر، يا جماعة الخير
+
+453
+00:36:15,530 --> 00:36:19,330
+المفروض كله يكون ايش؟ واحد، لأن الـ attribute مع نفسه
+
+454
+00:36:19,330 --> 00:36:23,850
+واحد، الـ attribute الأول والثاني ما فيش dependency
+
+455
+00:36:23,850 --> 00:36:29,550
+مطلقاً، الأول والثالث فوق الخمسين، فوق الثمانين، الأول
+
+456
+00:36:29,550 --> 00:36:33,530
+والرابع فوق الثمانين، الأول والخامس فوق الثمانين
+
+457
+00:36:33,530 --> 00:36:43,250
+لكن الثالث والرابع 95%، الثالث والخامس 95%،
+
+458
+00:36:43,250 --> 00:36:49,510
+الرابع والخامس 99%، طيب الآن بس أنا بدي أحذف واحد
+
+459
+00:36:49,510 --> 00:36:52,850
+من الـ correlation اللي هو الخامس هذا، طب أنا بدي
+
+460
+00:36:52,850 --> 00:36:54,750
+أقول أن والله الـ attributes اللي عندي الـ
+
+461
+00:36:54,750 --> 00:36:58,530
+correlation تبعته فوق فوق الـ 97%، هي اللي بدي
+
+462
+00:36:58,530 --> 00:37:03,190
+أحذفها، أنتم بالمثال كان عندكم فوق الـ 80%، الآن
+
+463
+00:37:03,190 --> 00:37:08,980
+أجيب في الواجبات الآن يا جماعة الخير لهذا الكلام، ليش؟
+
+464
+00:37:08,980 --> 00:37:14,000
+لأن أنا فعلياً فعلياً الـ attribute الخامس هو عبارة
+
+465
+00:37:14,000 --> 00:37:17,840
+كان عن واحد ونص، حاصل ضرب الـ values اللي موجودة
+
+466
+00:37:17,840 --> 00:37:21,580
+تعالوا احسبوها أنتم هيك، واحد ونص في
+
+467
+00:37:24,940 --> 00:37:30,300
+1.5، 4، 6، 1.5، هنتلقى طبعاً صار في بعض التغييرات على
+
+468
+00:37:30,300 --> 00:37:35,560
+الـ values، 1، 2، 1.5، الفكرة أنه أنا طبعاً عملت
+
+469
+00:37:35,560 --> 00:37:37,580
+rounding للـ values اللي موجودة، عشان يصير فيه
+
+470
+00:37:37,580 --> 00:37:40,860
+اختلاف، ما تصيرش يعني مية في المية، فجأة هو بس واضح
+
+471
+00:37:40,860 --> 00:37:44,020
+أن الـ value تسعة، تلت تسعات يعني، وكانها واحد، طب ايش
+
+472
+00:37:44,020 --> 00:37:46,760
+الحال؟ أوكي، الـ attribute هذا أنا بدي أحذفه، كيف بدي
+
+473
+00:37:46,760 --> 00:37:49,500
+أروح أحذف الـ attribute؟ كيف بدي أحذف الـ attribute
+
+474
+00:37:49,500 --> 00:37:50,180
+يا جماعة الخير؟
+
+475
+00:37:54,700 --> 00:38:00,440
+قلنا فيه نقطة، رقتين اللي هي حدف الـ attribute بس
+
+476
+00:38:00,440 --> 00:38:07,800
+هذا، مع الـ null أولاً، حذفنا الـ attribute الأول، drop
+
+477
+00:38:07,800 --> 00:38:18,700
+أو الـ function اسمها drop، drop
+
+478
+00:38:18,700 --> 00:38:22,160
+a5, replace
+
+479
+00:38:24,110 --> 00:38:30,040
+وأروح أقول له احسب الـ correlation مرة ثانية، هي run
+
+480
+00:38:30,040 --> 00:38:34,700
+ممتاز، هي جاني الـ data، طار الـ attribute، والـ
+
+481
+00:38:34,700 --> 00:38:38,340
+correlation، طبعاً هذه من الأصل أنها ما تتغيرش، لكن
+
+482
+00:38:38,340 --> 00:38:43,660
+الحسبة بتظل نوعاً ما فيها اختلافات بالنسبة للكل، طيب
+
+483
+00:38:43,660 --> 00:38:46,500
+خلصنا الآن في موضوع الـ correlation، شفنا موضوع الـ
+
+484
+00:38:46,500 --> 00:38:49,660
+data، ضل آخر جزئية كنت أنا بدي أعرفها منكم اللي هي
+
+485
+00:38:49,660 --> 00:38:55,360
+جزئية تقسيم الـ data لـ two different sets، وكتبتهم
+
+486
+00:38:55,360 --> 00:39:01,630
+على الـ file اللي موجود هنا، طيب الآن عشان أنا أجزم الـ
+
+487
+00:39:01,630 --> 00:39:09,750
+data from escalare.model
+
+488
+00:39:09,750 --> 00:39:12,910
+underscore selection
+
+489
+00:39:26,800 --> 00:39:32,640
+هذا الكود بينفذ stratified sampling على الـ data
+
+490
+00:39:32,640 --> 00:39:37,290
+الموجودة، طبعاً احنا كنا طالبين منكم الـ data set اللي
+
+491
+00:39:37,290 --> 00:39:39,890
+موجودة عندكم، هي الـ data أو الـ data اللي أنتم
+
+492
+00:39:39,890 --> 00:39:43,970
+حملتوها، تجسّمها، بتكلم عشان تفاصيل ثانية لحد اللحظة
+
+493
+00:39:43,970 --> 00:39:49,510
+طبعاً هدفي إلى استخدام الـ train test split، هذا ممكن
+
+494
+00:39:49,510 --> 00:39:52,510
+يرجع لي بمجموعتين، وممكن يرجع لي بأربعة، ممكن يرجع لي
+
+495
+00:39:52,510 --> 00:39:56,090
+بمجموعتين، وممكن يرجع لي بأربعة، لكن أنا بدي اشتغل
+
+496
+00:39:56,090 --> 00:39:59,710
+فقط على نظام مجموعتين، ولما بنحتاج الأربعة بنتكلم
+
+497
+00:39:59,710 --> 00:40:07,060
+عليهم، فالمجموعة الأولى أنا بدي اسميها train set، كما
+
+498
+00:40:07,060 --> 00:40:15,560
+ثانية test set، equal اللي هو اللي .. خليني بس أقوله
+
+499
+00:40:15,560 --> 00:40:23,580
+as، طبعاً هذه ميزة الـ as، TTS، TTS، وTTS هذا اللي هي
+
+500
+00:40:23,580 --> 00:40:28,640
+train test split، بياخذ مني الـ data اللي هي دي
+
+501
+00:40:28,640 --> 00:40:35,860
+بياخذ مني الـ test أو الـ train size، والباقي طبعاً
+
+502
+00:40:35,860 --> 00:40:41,600
+بياخذ النسبة التالية، point، ثلاثة من عشرة، كده أنا
+
+503
+00:40:41,600 --> 00:40:45,800
+عم بقول له بدي للـ test set حجمها ثلاثين في
+
+504
+00:40:45,800 --> 00:40:49,920
+المئة من الـ data set اللي موجودة عندي، ومن ثم أنا
+
+505
+00:40:49,920 --> 00:40:54,280
+بدي أروح أتحقق، هي في عندي الـ train، والسبعين في
+
+506
+00:40:54,280 --> 00:40:56,280
+المئة حتظهر للـ train، هي train
+
+507
+00:40:59,560 --> 00:41:13,260
+set.head ثلاثة، ونفس الكلام test set.head ثلاثة
+
+508
+00:41:13,260 --> 00:41:18,160
+وهي run، هد
+
+509
+00:41:18,160 --> 00:41:22,140
+النتائج، ثمانية فيهم، عاد عشان هدول جابهم كل واحد لحال، و
+
+510
+00:41:22,140 --> 00:41:23,120
+غالباً، هدول الأخيرة
+
+511
+00:41:25,690 --> 00:41:28,370
+غالباً هذه الأخيرة، بدي أعملهم كل واحدة لحالي بشكل
+
+512
+00:41:28,370 --> 00:41:35,390
+مستقل، هاي run هاي
+
+513
+00:41:35,390 --> 00:41:42,590
+الـ train set، وهي الـ test set، run
+
+514
+00:41:42,590 --> 00:41:47,090
+طبعاً، ادّى الـ two different sets موجودة، ضل هلّأ موضوع
+
+515
+00:41:47,090 --> 00:41:50,230
+موضوع الـ train set اللي أنا أكتبها على الـ
+
+516
+00:41:53,880 --> 00:41:58,620
+موضوع كتبتها على الـ disk، بسيط جداً، أنا للآن في عندي
+
+517
+00:41:58,620 --> 00:42:04,700
+الـ pandas، dot، زي ما كنت بقوله، read csv، بروح بقوله to
+
+518
+00:42:04,700 --> 00:42:14,440
+csv، وبديله اسم الملف، أي train set
+
+519
+00:42:21,360 --> 00:42:30,340
+tsv .. يا عفو، إن هاد الـ train set، train set، run، و
+
+520
+00:42:30,340 --> 00:42:36,120
+بقى آخذ test set بنفس الكيفية، test set، dot
+
+521
+00:42:36,120 --> 00:42:40,280
+underscore csv
+
+522
+00:42:44,940 --> 00:42:50,960
+testset.csv، run، وبهيك احنا بنكون إن شاء الله
+
+523
+00:42:50,960 --> 00:42:54,160
+انتهينا من الـ application، بس عشان أنا أتأكد، ممكن
+
+524
+00:42:54,160 --> 00:42:59,260
+أروح أدور على الـ files اللي موجودة عندي، احنا من
+
+525
+00:42:59,260 --> 00:43:04,730
+الأسماء هو طبعاً الأسماء كلها مرتبة، ترتيب train set
+
+526
+00:43:04,730 --> 00:43:11,730
+وهي train set، وهي test set، الآن seconds ago، هاي الـ
+
+527
+00:43:11,730 --> 00:43:17,230
+data موجودين كـ excel file أو كـ csv file، إن شاء
+
+528
+00:43:17,230 --> 00:43:20,850
+الله، بتكون المعلومات سهلة، بتعيدوا الفيديو مرة
+
+529
+00:43:20,850 --> 00:43:25,310
+وثنتين، بحيث إنكم تستوعبوا، وإن شاء الله تعالى الله
+
+530
+00:43:25,310 --> 00:43:28,610
+يعطيكم العافية، والسلام عليكم ورحمة الله وبركاته
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/aMsNbWzP5iY_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/aMsNbWzP5iY_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..c3334c972132ce525561d3aafbfd1dd4f48b0a94
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/aMsNbWzP5iY_raw.json
@@ -0,0 +1 @@
+{"segments": [{"id": 1, "seek": 1317, "start": 1.85, "end": 13.17, "text": "بسم الله والحمد لله والصلاة والسلام على رسول الله أهلا وسهلا بكم أخواني وأخواتي في لقاء أو في تسجيل لكن هذه المرة شغل عملي بالبيثون ل data preparation", "tokens": [3555, 38251, 21984, 16070, 35571, 3215, 24976, 3224, 16070, 9381, 15040, 3660, 16070, 3794, 37440, 15844, 12602, 3794, 12610, 21984, 5551, 3224, 15040, 46952, 3224, 15040, 4724, 24793, 5551, 9778, 2407, 7649, 1829, 36725, 9778, 2407, 9307, 1829, 8978, 5296, 4587, 16606, 34051, 8978, 6055, 3794, 7435, 26895, 44381, 29538, 9673, 25720, 13412, 17082, 1211, 6225, 2304, 20292, 20666, 21292, 12984, 11536, 5296, 1412, 13081], "avg_logprob": -0.1727035969044223, "compression_ratio": 1.5636363636363637, "no_speech_prob": 2.980232238769531e-07, "words": [{"start": 1.85, "end": 2.17, "word": "بسم", "probability": 0.764404296875}, {"start": 2.17, "end": 2.29, "word": " الله", "probability": 0.9677734375}, {"start": 2.29, "end": 2.55, "word": " والحمد", "probability": 0.8802083333333334}, {"start": 2.55, "end": 2.71, "word": " لله", "probability": 0.956787109375}, {"start": 2.71, "end": 2.99, "word": " والصلاة", "probability": 0.83966064453125}, {"start": 2.99, "end": 3.29, "word": " والسلام", "probability": 0.9736328125}, {"start": 3.29, "end": 3.45, "word": " على", "probability": 0.6025390625}, {"start": 3.45, "end": 3.73, "word": " رسول", "probability": 0.9895833333333334}, {"start": 3.73, "end": 3.95, "word": " الله", "probability": 0.9365234375}, {"start": 3.95, "end": 4.99, "word": " أهلا", "probability": 0.9313151041666666}, {"start": 4.99, "end": 5.31, "word": " وسهلا", "probability": 0.890625}, {"start": 5.31, "end": 5.53, "word": " بكم", "probability": 0.89208984375}, {"start": 5.53, "end": 6.67, "word": " أخواني", "probability": 0.861328125}, {"start": 6.67, "end": 7.15, "word": " وأخواتي", "probability": 0.88330078125}, {"start": 7.15, "end": 7.31, "word": " في", "probability": 0.931640625}, {"start": 7.31, "end": 8.39, "word": " لقاء", "probability": 0.9755859375}, {"start": 8.39, "end": 8.61, "word": " أو", "probability": 0.91064453125}, {"start": 8.61, "end": 8.75, "word": " في", "probability": 0.88671875}, {"start": 8.75, "end": 9.33, "word": " تسجيل", "probability": 0.9957275390625}, {"start": 9.33, "end": 9.85, "word": " لكن", "probability": 0.58935546875}, {"start": 9.85, "end": 10.19, "word": " هذه", "probability": 0.465576171875}, {"start": 10.19, "end": 10.19, "word": " المرة", "probability": 0.7149658203125}, {"start": 10.19, "end": 10.83, "word": " شغل", "probability": 0.90625}, {"start": 10.83, "end": 11.17, "word": " عملي", "probability": 0.9537760416666666}, {"start": 11.17, "end": 11.83, "word": " بالبيثون", "probability": 0.69366455078125}, {"start": 11.83, "end": 12.09, "word": " ل", "probability": 0.440185546875}, {"start": 12.09, "end": 12.55, "word": " data", "probability": 0.81396484375}, {"start": 12.55, "end": 13.17, "word": " preparation", "probability": 0.93408203125}], "temperature": 1.0}, {"id": 2, "seek": 4089, "start": 13.85, "end": 40.89, "text": "المثال اللى انا هشتغل عليه ان شاء الله تعالى هيغطي كتير من الجوانب المهمة اللى ممكن تلزمكوا سواء خلال ال course او لاحقا طبعا لأ اخفيكم انا هشتغل على ال database ال iris طبعا ال database صغيرة نوعا ما عملت عليها بعض ال modification او بين جثين استنعت بعض المشاكل فيها يعني اضفت كمان attribute عملت redundant rows اضفت", "tokens": [45340, 12984, 6027, 13672, 7578, 1975, 8315, 8032, 8592, 2655, 17082, 1211, 47356, 16472, 13412, 16606, 21984, 37279, 6027, 7578, 8032, 1829, 17082, 9566, 1829, 9122, 2655, 13546, 9154, 25724, 2407, 7649, 3555, 9673, 16095, 3660, 13672, 7578, 3714, 43020, 6055, 1211, 11622, 2304, 4117, 14407, 8608, 2407, 16606, 16490, 1211, 6027, 2423, 1164, 1975, 2407, 5296, 39319, 4587, 995, 23032, 3555, 3615, 995, 5296, 10721, 1975, 9778, 41185, 24793, 1975, 8315, 8032, 8592, 2655, 17082, 1211, 15844, 2423, 8149, 2423, 3418, 271, 23032, 3555, 3615, 995, 2423, 8149, 20328, 17082, 48923, 8717, 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duplicate values اللي موجودة عندها وبعد ذلك in place حيث ان ال value أو التأثير هتكون مباشرة على القيمة اللي موجودة عندى equal true", "tokens": [995, 33753, 5172, 19913, 8978, 25062, 32640, 3660, 16247, 12610, 7578, 6156, 47432, 34051, 25062, 32640, 3660, 38392, 6055, 7435, 3215, 11296, 34051, 2423, 39184, 1036, 8978, 6024, 95, 34740, 41850, 4724, 16254, 12174, 32640, 3660, 36764, 24401, 3660, 9154, 2423, 39184, 23976, 4190, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 11296, 46599, 22488, 29910, 23275, 294, 1081, 11331, 1829, 12984, 16472, 2423, 2158, 34051, 16712, 10721, 12984, 13546, 8032, 2655, 30544, 3714, 3555, 33599, 25720, 15844, 25062, 32640, 3660, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 7578, 2681, 2074], "avg_logprob": -0.2731799522599021, "compression_ratio": 1.7826086956521738, "no_speech_prob": 1.1920928955078125e-07, "words": [{"start": 749.16, "end": 749.56, "word": "احتفظ", "probability": 0.718353271484375}, {"start": 749.56, "end": 749.66, "word": " في", 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عشان", "probability": 0.96875}, {"start": 2572.58, "end": 2572.76, "word": " انا", "probability": 0.600830078125}, {"start": 2572.76, "end": 2573.3, "word": " اتأكد", "probability": 0.8841796875}, {"start": 2573.3, "end": 2574.16, "word": " ممكن", "probability": 0.951904296875}, {"start": 2574.16, "end": 2574.56, "word": " اروح", "probability": 0.9493815104166666}, {"start": 2574.56, "end": 2575.0, "word": " ادور", "probability": 0.931640625}, {"start": 2575.0, "end": 2575.32, "word": " على", "probability": 0.83544921875}, {"start": 2575.32, "end": 2575.92, "word": " ال", "probability": 0.935546875}, {"start": 2575.92, "end": 2576.66, "word": " files", "probability": 0.919921875}, {"start": 2576.66, "end": 2577.0, "word": " اللي", "probability": 0.9296875}, {"start": 2577.0, "end": 2577.6, "word": " موجودة", "probability": 0.9832763671875}, {"start": 2577.6, "end": 2578.26, "word": " عندى", "probability": 0.7353515625}, {"start": 2578.26, "end": 2579.08, "word": " احنا", "probability": 0.6944986979166666}, {"start": 2579.08, "end": 2579.26, "word": " من", "probability": 0.2230224609375}, {"start": 2579.26, "end": 2579.72, "word": " الأسماء", "probability": 0.7598470052083334}, {"start": 2579.72, "end": 2579.84, "word": " هو", "probability": 0.58740234375}, {"start": 2579.84, "end": 2580.08, "word": " طبعا", "probability": 0.839599609375}, {"start": 2580.08, "end": 2580.36, "word": " الأسماء", "probability": 0.8722330729166666}, {"start": 2580.36, "end": 2580.66, "word": " كلها", "probability": 0.9833984375}, {"start": 2580.66, "end": 2581.58, "word": " مرتبة", "probability": 0.9612630208333334}, {"start": 2581.58, "end": 2582.4, "word": " ترتيب", "probability": 0.889892578125}], "temperature": 1.0}, {"id": 108, "seek": 260861, "start": 2583.83, "end": 2608.61, "text": "ترين سيت وهي ترين سيت وهي تست سيت الآن seconds ago هاي ال data موجودين ك excel file او ك csv file ان شاء الله بتكون المعلومات سهلة بتعيدوا الفيديو مرة وتنتين بحيث انكوا تستوعبوا وان شاء الله تعالى الله عطيكم العافية والسلام عليكم ورحمة الله وبركاته", "tokens": [2655, 2288, 9957, 8608, 36081, 37037, 1829, 6055, 2288, 9957, 8608, 36081, 37037, 1829, 6055, 14851, 8608, 36081, 6024, 48506, 3949, 2057, 8032, 47302, 2423, 1412, 3714, 29245, 23328, 9957, 9122, 24015, 3991, 1975, 2407, 9122, 28277, 85, 3991, 16472, 13412, 16606, 21984, 39894, 30544, 9673, 30241, 20498, 9307, 8608, 3224, 37977, 39894, 3615, 25708, 14407, 27188, 1829, 16254, 2407, 3714, 25720, 4032, 2655, 29399, 9957, 4724, 5016, 1829, 12984, 16472, 4117, 14407, 6055, 14851, 45367, 3555, 14407, 4032, 7649, 13412, 16606, 21984, 37279, 6027, 7578, 21984, 6225, 9566, 1829, 24793, 18863, 31845, 10632, 16070, 3794, 37440, 25894, 24793, 4032, 2288, 35571, 3660, 21984, 4032, 26890, 4117, 9307, 3224], "avg_logprob": -0.27073863555084576, "compression_ratio": 1.8181818181818181, "no_speech_prob": 1.0669231414794922e-05, "words": [{"start": 2583.83, "end": 2584.29, "word": "ترين", "probability": 0.39056396484375}, {"start": 2584.29, "end": 2584.73, "word": " سيت", "probability": 0.87158203125}, {"start": 2584.73, "end": 2585.73, "word": " وهي", "probability": 0.5517578125}, {"start": 2585.73, "end": 2586.07, "word": " ترين", "probability": 0.7454427083333334}, {"start": 2586.07, "end": 2586.49, "word": " سيت", "probability": 0.94921875}, {"start": 2586.49, "end": 2587.25, "word": " وهي", "probability": 0.8857421875}, {"start": 2587.25, "end": 2587.85, "word": " تست", "probability": 0.5858154296875}, {"start": 2587.85, "end": 2588.31, "word": " سيت", "probability": 0.962646484375}, {"start": 2588.31, "end": 2588.87, "word": " الآن", "probability": 0.537017822265625}, {"start": 2588.87, "end": 2590.39, "word": " seconds", "probability": 0.1439208984375}, {"start": 2590.39, "end": 2590.95, "word": " ago", "probability": 0.8310546875}, {"start": 2590.95, "end": 2591.63, "word": " هاي", "probability": 0.4583740234375}, {"start": 2591.63, "end": 2591.73, "word": " ال", "probability": 0.94287109375}, {"start": 2591.73, "end": 2592.07, "word": " data", "probability": 0.966796875}, {"start": 2592.07, "end": 2593.31, "word": " موجودين", "probability": 0.9674072265625}, {"start": 2593.31, "end": 2593.67, "word": " ك", "probability": 0.94189453125}, {"start": 2593.67, "end": 2594.37, "word": " excel", "probability": 0.21484375}, {"start": 2594.37, "end": 2594.87, "word": " file", "probability": 0.84619140625}, {"start": 2594.87, "end": 2595.49, "word": " او", "probability": 0.76171875}, {"start": 2595.49, "end": 2595.69, "word": " ك", "probability": 0.900390625}, {"start": 2595.69, "end": 2596.25, "word": " csv", "probability": 0.825439453125}, {"start": 2596.25, "end": 2596.59, "word": " file", "probability": 0.9228515625}, {"start": 2596.59, "end": 2597.07, "word": " ان", "probability": 0.92041015625}, {"start": 2597.07, "end": 2597.23, "word": " شاء", "probability": 0.968505859375}, {"start": 2597.23, "end": 2597.25, "word": " الله", "probability": 0.9541015625}, {"start": 2597.25, "end": 2597.67, "word": " بتكون", "probability": 0.744140625}, {"start": 2597.67, "end": 2598.95, "word": " المعلومات", "probability": 0.9610595703125}, {"start": 2598.95, "end": 2599.33, "word": " سهلة", "probability": 0.9747721354166666}, {"start": 2599.33, "end": 2599.95, "word": " بتعيدوا", "probability": 0.69183349609375}, {"start": 2599.95, "end": 2600.41, "word": " الفيديو", "probability": 0.91796875}, {"start": 2600.41, "end": 2600.85, "word": " مرة", "probability": 0.97021484375}, {"start": 2600.85, "end": 2601.57, "word": " وتنتين", "probability": 0.7540283203125}, {"start": 2601.57, "end": 2602.21, "word": " بحيث", "probability": 0.8406982421875}, {"start": 2602.21, "end": 2602.51, "word": " انكوا", "probability": 0.6710611979166666}, {"start": 2602.51, "end": 2603.67, "word": " تستوعبوا", "probability": 0.93486328125}, {"start": 2603.67, "end": 2604.47, "word": " وان", "probability": 0.546142578125}, {"start": 2604.47, "end": 2604.65, "word": " شاء", "probability": 0.908935546875}, {"start": 2604.65, "end": 2604.77, "word": " الله", "probability": 0.94775390625}, {"start": 2604.77, "end": 2605.11, "word": " تعالى", "probability": 0.92724609375}, {"start": 2605.11, "end": 2605.31, "word": " الله", "probability": 0.483642578125}, {"start": 2605.31, "end": 2605.51, "word": " عطيكم", "probability": 0.67401123046875}, {"start": 2605.51, "end": 2605.95, "word": " العافية", "probability": 0.955078125}, {"start": 2605.95, "end": 2606.55, "word": " والسلام", "probability": 0.8478190104166666}, {"start": 2606.55, "end": 2606.87, "word": " عليكم", "probability": 0.938232421875}, {"start": 2606.87, "end": 2607.27, "word": " ورحمة", "probability": 0.9703369140625}, {"start": 2607.27, "end": 2607.57, "word": " الله", "probability": 0.9716796875}, {"start": 2607.57, "end": 2608.61, "word": " وبركاته", "probability": 0.98525390625}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 2609.1101875, "duration_after_vad": 2481.2287499999898}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/cUQb5hESOvo.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/cUQb5hESOvo.srt
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@@ -0,0 +1,2751 @@
+1
+00:00:05,030 --> 00:00:08,110
+أعوذ بالله السلام عليهم بسم الله الرحمن الرحيم
+
+2
+00:00:08,110 --> 00:00:11,910
+الحمد لله والصلاة والسلام على رسول الله أهلًا وسهلًا
+
+3
+00:00:11,910 --> 00:00:15,150
+فيكم، نسأل الله لكم ولنا السلام دائمًا ولجميع
+
+4
+00:00:15,150 --> 00:00:18,710
+المسلمين، وإن شاء الله تزول هذه الغمة، ونلقاكم من
+
+5
+00:00:18,710 --> 00:00:22,220
+جديد. اليوم هنستعرض مع بعض إن شاء الله تعالى
+
+6
+00:00:22,220 --> 00:00:27,400
+المحاضرات المصورة لموضوع الـ data mining، ومن ثم
+
+7
+00:00:27,400 --> 00:00:31,100
+سنعمل review سريعة. لو وقفنا... كنا بدأنا في
+
+8
+00:00:31,100 --> 00:00:33,800
+chapter data mining... data mining chapter ثلاثة
+
+9
+00:00:33,800 --> 00:00:36,760
+في الـ classification، وقلنا الـ classification هي
+
+10
+00:00:36,760 --> 00:00:40,600
+عبارة عن classical task تقليدية أو مهمة
+
+11
+00:00:40,600 --> 00:00:43,680
+التقليدية في الـ machine learning. هدفها أن
+
+12
+00:00:43,680 --> 00:00:49,160
+أعمل فعليًا prediction لـ discrete أو لـ nominal value
+
+13
+00:00:49,160 --> 00:00:52,240
+اللتي سميناها الـ categorical value، ولما حاولنا نعرف
+
+14
+00:00:52,240 --> 00:00:55,240
+الـ classification مع بعض، كنتم تذكرون كنا نقول أن
+
+15
+00:00:55,240 --> 00:00:59,320
+الـ classification هي عبارة عن عملية لتحديد عضوية
+
+16
+00:00:59,320 --> 00:01:06,530
+العناصر في مجموعات معرفة مسبقًا. وتكلمنا أو وضعنا
+
+17
+00:01:06,530 --> 00:01:09,770
+الرسم هذا على السريع، وقلنا أنه يمثل الـ
+
+18
+00:01:09,770 --> 00:01:13,230
+model الخاص بالـ classification، أنه أُضيف الـ raw
+
+19
+00:01:13,230 --> 00:01:16,390
+data، يُحدد الـ algorithm، الـ algorithm يبني الـ model،
+
+20
+00:01:16,390 --> 00:01:19,110
+والـ model بعد ذلك يجب أن يكون قادرًا على الـ
+
+21
+00:01:19,110 --> 00:01:25,180
+prediction بشكل صحيح. وبالتالي، الـ classification هي
+
+22
+00:01:25,180 --> 00:01:28,920
+عبارة عن تقنية تُستخدم في موضوع الـ prediction
+
+23
+00:01:28,920 --> 00:01:34,080
+للعضوية، لعضوية العناصر في المجموعة. وتكلمنا أن
+
+24
+00:01:34,080 --> 00:01:37,620
+فعليًا في الـ classification task، يوجد لديّ two
+
+25
+00:01:37,620 --> 00:01:40,300
+steps. أي classification task، لإنجازها، يوجد لديّ
+
+26
+00:01:40,300 --> 00:01:43,460
+two steps. الأولى هي construction للموديل،
+
+27
+00:01:43,460 --> 00:01:47,160
+بناء الموديل، بحيث أن أحاول من خلال الخطوات
+
+28
+00:01:47,160 --> 00:01:53,090
+هذه أن أعرف علاقة الـ attribute مع الـ class، أعرف
+
+29
+00:01:53,090 --> 00:01:55,490
+علاقة الـ attribute بالـ class، وهذه تُسمى
+
+30
+00:01:55,490 --> 00:01:58,890
+مرحلة الـ training، والتي دائمًا آخذ جزءًا من الـ data
+
+31
+00:01:58,890 --> 00:02:02,450
+set، التي تُسمى الـ training set، وشاهدنا مثالها سابقًا.
+
+32
+00:02:02,450 --> 00:02:05,410
+الخطوة الثانية أو المحل، الخطوة الثانية التي
+
+33
+00:02:05,410 --> 00:02:08,890
+هي الـ model usage، استخدامه، بحيث أن أجد الـ
+
+34
+00:02:08,890 --> 00:02:13,090
+label أو الـ target class لـ data set، أو عفواً، لـ
+
+35
+00:02:13,090 --> 00:02:18,970
+sample set الموجودة لديّ مسبقًا. وقلنا مهم جدًا أن
+
+36
+00:02:18,970 --> 00:02:21,450
+الـ model أو الـ classification model يتمتع بالـ
+
+37
+00:02:21,450 --> 00:02:24,790
+accuracy، بالدقة، وبالـ speed، سرعة الحساب،
+
+38
+00:02:24,790 --> 00:02:28,110
+والـ robustness، الـ robustness،  التي تعني
+
+39
+00:02:28,110 --> 00:02:33,710
+قدرة الـ classifier هذا على أن يتعامل أو
+
+40
+00:02:33,710 --> 00:02:36,950
+يقدر أن يعطيني  prediction دقيقة عندما تكون الـ data
+
+41
+00:02:36,950 --> 00:02:39,370
+تحتوي على noise أو missing data. تكلمنا عن
+
+42
+00:02:39,370 --> 00:02:42,830
+الـ scalability والـ interpretability للـ data set، أو
+
+43
+00:02:42,830 --> 00:02:46,910
+عفوًا، للـ classifier. ويُخبرنا هذه مجموعة من الـ
+
+44
+00:02:46,910 --> 00:02:50,050
+algorithms الموجودة، وكنا في المحاضرة الماضية مع
+
+45
+00:02:50,050 --> 00:02:53,850
+بعض، في آخر محاضرة، الـ k-nearest neighbor.  طبعًا لو
+
+46
+00:02:53,850 --> 00:02:57,880
+سألت الآن سؤالًا، والمفروض منكم أن تأخذوا لحظة قبل
+
+47
+00:02:57,880 --> 00:03:02,460
+أن تجيبوا عليّ،  على ماذا يعتمد الـ k-nearest neighbor
+
+48
+00:03:02,460 --> 00:03:08,700
+؟ المفروض الآن أن تبدأوا تفكرون في الإجابة. الـ k-
+
+49
+00:03:08,700 --> 00:03:11,760
+nearest neighbor يعتمد على تصنيف العناصر تبعًا
+
+50
+00:03:11,760 --> 00:03:17,360
+للنقاط المجاورة له. وقلنا هذا هو واحد من
+
+51
+00:03:17,360 --> 00:03:20,530
+الـ instance-based. تذكرون معي؟ ماذا هو؟ كنا
+
+52
+00:03:20,530 --> 00:03:23,850
+نتحدث عن ماذا؟ Instance-Based. Instance-Based يعني
+
+53
+00:03:23,850 --> 00:03:28,250
+يعتمد على الـ data set بدون بناء model، يعتمد على
+
+54
+00:03:28,250 --> 00:03:33,050
+الـ data set بدون بناء models، وبالتالي
+
+55
+00:03:33,050 --> 00:03:38,230
+لا يوجد لديّ أي model، ولا يعتمد إلا على العمل في الـ
+
+56
+00:03:38,230 --> 00:03:41,650
+memory، يعني بين  الـ جسيم الحساب، وهذا يعطيني
+
+57
+00:03:41,650 --> 00:03:46,580
+دائمًا الـ Result بناءً على الـ majority  الخاصة بالـ
+
+58
+00:03:46,580 --> 00:03:49,600
+جيران الموجودة عنده.  وقلنا بالـ K أنه يجب
+
+59
+00:03:49,600 --> 00:03:53,440
+أن أُحدد عدد العناصر الموجودة عنده. ومررنا
+
+60
+00:03:53,440 --> 00:03:57,600
+بشكل سريع، وقلنا كيف أحسب التشابه أو أحسب القرب أو
+
+61
+00:03:57,600 --> 00:04:00,680
+البعد بين النقاط أو الـ objects، وقلنا يعتمد على
+
+62
+00:04:00,680 --> 00:04:03,740
+شيء نسميه similarity function، والـ similarity
+
+63
+00:04:03,740 --> 00:04:06,620
+function، عندما تكون لديّ أرقام، معناته أتحدث
+
+64
+00:04:06,620 --> 00:04:09,180
+عن Euclidean distance أو Manhattan distance أو
+
+65
+00:04:09,180 --> 00:04:12,750
+غيرها من الأشياء، وشاهدنا المعادلات مع بعضنا،
+
+66
+00:04:12,750 --> 00:04:17,110
+وَفرّقنا بينهم، وبين العناصر الموجودة.  ما الذي يطلبه
+
+67
+00:04:17,110 --> 00:04:19,510
+الـ k-nearest neighbor، حسب ما شرحنا في المحاضرة
+
+68
+00:04:19,510 --> 00:04:23,610
+الأخيرة؟ كان يطلب مني أن أُحدد الـ K، وهي عدد
+
+69
+00:04:23,610 --> 00:04:26,910
+الجيران الذين سأُجري بينهم voting، يعني لو
+
+70
+00:04:26,910 --> 00:04:30,150
+قلتُ، سأُصنف الجار هذا أو سأُصنف الـ
+
+71
+00:04:30,150 --> 00:04:32,330
+object الجديد بناءً على العناصر الموجودة
+
+72
+00:04:32,330 --> 00:04:36,210
+وبالتالي، أنا أتحدث عن أن لديّ فعليًا
+
+73
+00:04:37,240 --> 00:04:41,100
+عشرة جيران، حسب أغلبهم. الأغلبية طبعًا، أتحدث هنا على
+
+74
+00:04:41,100 --> 00:04:45,880
+ستة. الستة ماذا تصنفه؟ أذهب وأصنفه تبعًا للستة الذين
+
+75
+00:04:45,880 --> 00:04:50,720
+موجودين لديّ. سأحدد الـ distance method التي سأستخدمها
+
+76
+00:04:50,720 --> 00:04:53,940
+كمقياس. وبالتالي، بعد أن حددت الـ K،
+
+77
+00:04:53,940 --> 00:04:58,240
+أحسب الـ distance بين الـ sample الموجودة لديّ،
+
+78
+00:04:58,240 --> 00:05:01,300
+وكل الـ data set أو الـ training set التي
+
+79
+00:05:01,300 --> 00:05:04,580
+موجودة لديّ هنا.  ممكن أعتمد الـ Euclidean أو الـ
+
+80
+00:05:04,580 --> 00:05:08,410
+Manhattan. أرتب البيانات، وقلنا موضوع الترتيب ليس
+
+81
+00:05:08,410 --> 00:05:11,650
+مهم إلا عندما تكون الـ data set كبيرة، يصبح عليه
+
+82
+00:05:11,650 --> 00:05:16,150
+حصر، يسهل عليّ أن أحصر العناصر الأقرب، الـ
+
+83
+00:05:16,150 --> 00:05:21,810
+k-nearest، مجموعة العناصر العشرة، أصحاب أقصر مسافة
+
+84
+00:05:21,810 --> 00:05:25,130
+بين الـ sample الموجودة لديهم،  أجري بينهم voting،
+
+85
+00:05:25,130 --> 00:05:28,300
+بحيث أُحدد الأغلبية. وشاهدنا المثال الموجود
+
+86
+00:05:28,300 --> 00:05:33,040
+هنا، وكيف اشتغلنا على الـ Euclidean، وإذا تتذكرون،
+
+87
+00:05:33,040 --> 00:05:36,220
+المفروض أن المعادلة الخاصة بنا هذه، حسب الـ Euclidean
+
+88
+00:05:36,220 --> 00:05:40,420
+distance، فيها الجذر التربيعي. وطبعًا،  لأجل التسهيل،
+
+89
+00:05:40,420 --> 00:05:43,440
+عندما نتحدث عن الجذر التربيعي والجذر التربيعي
+
+90
+00:05:43,440 --> 00:05:48,400
+موجود في كل المعادلات، من باب المقارنة، ممكن أن
+
+91
+00:05:48,400 --> 00:05:54,050
+أتغاضى عنه، لأن الأكبر تحت الجذر، أو أكبر عنصر تحت
+
+92
+00:05:54,050 --> 00:05:58,490
+الجذر، سيبقى أكبر عنصر خارج... خارج الجذر، عندما...
+
+93
+00:05:58,490 --> 00:06:03,670
+يعني مثلاً، جذر الـ 16، جذر الـ 25، جذر الـ 13، جذر
+
+94
+00:06:03,670 --> 00:06:06,850
+التسعة. أصغر واحدة فيهم جذر التسعة، التي هي ثلاثة.
+
+95
+00:06:08,510 --> 00:06:12,350
+وأكبر واحدة فيهم جذر الخمسة وعشرين، خمسة. كذلك،
+
+96
+00:06:12,350 --> 00:06:15,570
+الخمسة وعشرون هي أكبر value، والتسعة هي أصغر value
+
+97
+00:06:15,570 --> 00:06:18,490
+موجودة لديّ. وبالتالي، كنت أقول أنه ممكن من
+
+98
+00:06:18,490 --> 00:06:21,550
+ناحية الحساب السريع، لأني أخلص من
+
+99
+00:06:21,550 --> 00:06:26,930
+المقارنات السريعة،  ممكن أن أتغاضى عن الجذر التربيعي،
+
+100
+00:06:26,930 --> 00:06:32,470
+وأبقى أتكلم على الـ Euclidean distance. وشاهدنا
+
+101
+00:06:32,470 --> 00:06:36,150
+مع بعض المثال، وانتهينا من المثال هذا. قلنا
+
+102
+00:06:36,150 --> 00:06:40,660
+في حالة أن كانت الـ data set الموجودة لديّ
+
+103
+00:06:40,660 --> 00:06:44,960
+تحتوي على nominal attributes أو categorical
+
+104
+00:06:44,960 --> 00:06:48,300
+attributes، قلنا هنا يلزم أن أرى
+
+105
+00:06:48,300 --> 00:06:52,260
+طريقة، لأني لا أستطيع أن أحسب مسافة بين عنصرين لو
+
+106
+00:06:52,260 --> 00:06:57,080
+قلنا مثلاً، أنا male و female في الـ
+
+107
+00:06:57,080 --> 00:07:02,760
+gender attribute، المسافة بينهما غير معرفة، لا أستطيع
+
+108
+00:07:02,760 --> 00:07:08,840
+أن أتحدث عنها. وبالتالي، الآن، لو قلنا أحمد،
+
+109
+00:07:08,840 --> 00:07:14,120
+أحمد مع الـ E في الوسط هنا، ما هي المسافة
+
+110
+00:07:14,120 --> 00:07:17,120
+بينهما؟ طبعًا، نحن متفقون أن الأسماء لا تدخل في
+
+111
+00:07:17,120 --> 00:07:20,200
+الحسابات لديّ، لأنها دائمًا غير مفيدة. وبالتالي، أنا
+
+112
+00:07:20,200 --> 00:07:23,900
+أثناء التحضير، سأزيلها. ولكن في النهاية، عندما
+
+113
+00:07:23,900 --> 00:07:26,580
+يكون لديّ string أو text أو كما سميناها في
+
+114
+00:07:26,580 --> 00:07:29,520
+لغة الـ data mining، categorical data أو nominal
+
+115
+00:07:29,520 --> 00:07:33,170
+data، كيف سأحسبها أو سأحسب المقارنة بينها؟ هذا
+
+116
+00:07:33,170 --> 00:07:35,970
+الكلام صعب في الـ Euclidean distance والـ Manhattan.
+
+117
+00:07:35,970 --> 00:07:40,510
+فلذلك، في الـ k-nearest neighbor، يصبح عليّ العمل. هل فعليًا الـ
+
+118
+00:07:40,510 --> 00:07:43,730
+term هاتان متطابقتان؟ إذا كانت الـ two terms متطابقتان،
+
+119
+00:07:43,730 --> 00:07:47,050
+معناته أضع لهما صفرًا. إذا كانت الـ two terms مختلفتان، يعني
+
+120
+00:07:47,050 --> 00:07:50,590
+أبعد ما يمكن عن بعض أو بعيدتان عن بعض، أضع الفرق بينهما
+
+121
+00:07:50,590 --> 00:07:56,170
+واحدًا. وطبعًا،  تحدثنا بعد ذلك عن أهمية الـ scaling في
+
+122
+00:07:56,170 --> 00:08:01,120
+موضوع الـ k-nearest neighbor. وقلنا من أهم... أهم مميزاته
+
+123
+00:08:01,120 --> 00:08:04,160
+الـ robustness اتجاه الـ noisy data والـ
+
+124
+00:08:04,160 --> 00:08:08,420
+effectiveness في موضوع مرحلة الـ training.
+
+125
+00:08:08,420 --> 00:08:13,100
+العيوب: تحديد الـ K... أي K هي الأنسب
+
+126
+00:08:13,100 --> 00:08:17,740
+للموضوع الذي أعمل عليه. مفهوم الـ distance غير
+
+127
+00:08:17,740 --> 00:08:20,380
+واضح، خصوصًا عندما تظهر لديّ الـ categorical data، و
+
+128
+00:08:20,380 --> 00:08:23,940
+هذه  تتمتع بـ computation cost عالية. تخيل الـ
+
+129
+00:08:23,940 --> 00:08:27,040
+data set فيها مئة ألف record. وبالتالي، عندما أريد
+
+130
+00:08:27,040 --> 00:08:29,680
+أن أُجري evaluation أو عفواً، أن أُجري prediction لـ
+
+131
+00:08:29,680 --> 00:08:34,520
+class لـ one example، معناته سأذهب وأحسب مئة ألف
+
+132
+00:08:34,520 --> 00:08:38,180
+distance.  طيب لو كان لديّ في المقابل،  لديّ
+
+133
+00:08:38,180 --> 00:08:42,960
+عشرة أو مئة سأُجري عليهم testing، مئة في مئة ألف،
+
+134
+00:08:42,960 --> 00:08:46,440
+معناته نحن نتحدث عن عشرة ملايين تقريبًا
+
+135
+00:08:46,440 --> 00:08:51,160
+computation. وبالتالي، العملية ستأخذ مني وقتًا
+
+136
+00:08:51,160 --> 00:08:55,540
+طويلًا. الآن، عندما رأينا الـ code، أهم شيء في الـ code السابق،
+
+137
+00:08:55,540 --> 00:09:00,890
+إذا كنتم تتذكرون،  أخذت من scikit-learn،
+
+138
+00:09:00,890 --> 00:09:08,330
+KNeighborsClassifier. KNeighborsClassifier. KNeighborsClassifier.
+
+139
+00:09:08,330 --> 00:09:11,520
+KNeighborsClassifier. KNeighborsClassifier. الخاصة بالـ K-nearest neighbor، وأعطيتها الـ
+
+140
+00:09:11,520 --> 00:09:15,420
+K الخاصة بي، تساوي خمسة. وهنا نتذكر، قلنا دائمًا الـ X
+
+141
+00:09:15,420 --> 00:09:18,680
+الخاصة بك أو الـ K الخاصة بك، يجب أن تكون كبيرة
+
+142
+00:09:18,680 --> 00:09:22,660
+كفاية، وتكون دائمًا قادرة على إعطائي الـ predictions أو
+
+143
+00:09:22,660 --> 00:09:25,780
+أن تُجري الـ voting الصحيح، لأنه ليس معقولًا مثلاً أن تكون
+
+144
+00:09:25,780 --> 00:09:28,640
+لديّ two binary أو two labels، وأذهب وأقول
+
+145
+00:09:28,640 --> 00:09:32,510
+سآخذ مثلاً أربعة أو ستة، ستة، يعني الاحتمال أن
+
+146
+00:09:32,510 --> 00:09:35,270
+يكون خمسة خمسة، على الأقل، أحتاج أكثر، في حالة
+
+147
+00:09:35,270 --> 00:09:38,510
+الـ binary classification، لأُقدر أن الـ voting
+
+148
+00:09:38,510 --> 00:09:42,710
+يميل لأحد الـ classes الموجودة لديهم.  وتذكروا جيدًا، وتذكروا جميعًا أنني عندما
+
+149
+00:09:42,710 --> 00:09:46,950
+تحدثت عن الـ k-nearest neighbors، وأعطيتها الـ test
+
+150
+00:09:46,950 --> 00:09:50,050
+attribute، test sample الخاصة بي التي بنيتها هنا، و
+
+151
+00:09:50,050 --> 00:09:53,110
+مع الـ K الخاصة بي،  التي تساوي خمسة، فعليًا أعطاني من
+
+152
+00:09:53,110 --> 00:09:56,710
+بينهم هذه العناصر، وما هي الـ distances الموجودة
+
+153
+00:09:56,710 --> 00:09:59,990
+بينها، وبقي عليّ أن أعود إلى الـ data set، أحصل على
+
+154
+00:09:59,990 --> 00:10:03,890
+الـ label الخاصة بهذه العناصر، وأُجري بينها voting. كان
+
+155
+00:10:03,890 --> 00:10:07,830
+هذا... حتى هنا أنهينا محاضرتنا السابقة عند
+
+156
+00:10:07,830 --> 00:10:11,530
+هذا المثال، وأتمنى أن أكون قد وفقت في أن
+
+157
+00:10:11,530 --> 00:10:16,340
+أذكركم بعد انقطاع أسبوع من الدراسة، بما سبق في موضوع
+
+158
+00:10:16,340 --> 00:10:22,180
+الـ classification. لكن تعالوا لنرى قبل أن ننتقل
+
+159
+00:10:22,180 --> 00:10:26,760
+إلى الموضوع الجديد، تعالوا لنرى هذا المثال، المفروض أن
+
+160
+00:10:26,760 --> 00:10:29,320
+هذا المثال ليس موجودًا لديكم في الـ slides، أنتم
+
+161
+00:10:29,320 --> 00:10:31,700
+المفروض أن...  المفروض أن الـ slides معكم، وتبدأون
+
+162
+00:10:31,700 --> 00:10:34,100
+بتراجعوها باستمرار. لو نظرتُ إلى الـ attributes
+
+163
+00:10:34,100 --> 00:10:38,840
+أو إلى الـ data set الموجودة هنا، وأجب معي، أو
+
+164
+00:10:42,800 --> 00:10:46,240
+أجبوا معي على السؤال التالي: ما هو الـ data type
+
+165
+00:10:46,240 --> 00:10:50,840
+الخاص بالـ outlook؟  المفروض
+
+166
+00:10:50,840 --> 00:10:52,360
+nominal، صحيح.
+
+167
+00:10:55,100 --> 00:11:00,320
+الـ data type الخاص بالـ temperature، numeric.
+
+168
+00:11:00,320 --> 00:11:03,800
+وإن
+
+169
+00:11:03,800 --> 00:11:10,700
+قلتم ratio أو interval، كلامكم صحيح، كـ interval،
+
+170
+00:11:10,700 --> 00:11:15,300
+وليس كـ ratio.  الـ play golf أو play
+
+171
+00:11:15,300 --> 00:11:18,820
+golf، binary classification، يعني لديّ two labels،
+
+172
+00:11:18,820 --> 00:11:23,160
+yes و no، حسب الـ data set الموجودة لديّ، و
+
+173
+00:11:23,160 --> 00:11:29,460
+المطلوب أن أذهب وأحصل على الـ class الخاصة بالـ instance
+
+174
+00:11:29,460 --> 00:11:36,100
+التي فيها الـ sunny، وهذه طبعًا في الـ outlook، الـ
+
+175
+00:11:36,100 --> 00:11:3
+
+223
+00:15:38,860 --> 00:15:44,660
+تبع للـ distance اللي صارت التنين، هذه هتظهر أول
+
+224
+00:15:44,660 --> 00:15:49,780
+واحدة. ليش؟ لأنه الآن لما بتتساوى القيم، بصير ظهور
+
+225
+00:15:49,780 --> 00:15:52,800
+تبع الـ value هو الأول، هو اللي بياخد في الترتيب.
+
+226
+00:15:53,670 --> 00:15:56,810
+الظهور تبع الـ values هي اللي بتاخد في الترتيب.
+
+227
+00:15:56,810 --> 00:16:00,570
+وبالتالي هذي هتكون أول واحدة فوق. الآن لو أنا والـ
+
+228
+00:16:00,570 --> 00:16:03,390
+key and nearest neighbor equal one. إيش الـ key
+
+229
+00:16:03,390 --> 00:16:09,510
+تبعتي أو الـ label تبعتي true، وبالتالي هتكون عندي
+
+230
+00:16:09,510 --> 00:16:15,170
+yes. طيب في حالة أن الـ key تبعتي equal تلاتة، تلاتة
+
+231
+00:16:15,170 --> 00:16:20,210
+هي واحدة، نتين، تلاتة، معناته هي واحدة، هي نتين، هي
+
+232
+00:16:20,210 --> 00:16:26,420
+تلاتة. الـ majority بينهم نتين yes وواحدة no، يعني
+
+233
+00:16:26,420 --> 00:16:33,080
+بنتكلم على 66% yes و33% no، وبالتالي الـ majority
+
+234
+00:16:33,080 --> 00:16:39,420
+تبعتي لـ playing golf equal yes، تمام. الخطوة الأخيرة
+
+235
+00:16:39,420 --> 00:16:44,540
+لو أنا قلت له K equal خمسة، K equal خمسة، معناته بده
+
+236
+00:16:44,540 --> 00:16:51,320
+يدور على الـ shortest distances. أي واحدة، نتين، هذه
+
+237
+00:16:51,320 --> 00:17:00,640
+تلاتة، وهذه أربعة، وهذه خمسة. الـ label سبعتها واحدة،
+
+238
+00:17:00,640 --> 00:17:07,980
+نتين، تلاتة، أربعة، وهذه خمسة. الآن بدي أعمل voting ما
+
+239
+00:17:07,980 --> 00:17:11,080
+بين الخمسة اللي موجودة عندي. واحدة، اتنين، تلاتة،
+
+240
+00:17:11,080 --> 00:17:14,960
+أربعة yes، 80% yes، و20% no.
+
+241
+00:17:14,960 --> 00:17:19,480
+وبالتالي لما تكون الـ key تبعتي equal five، معناته
+
+242
+00:17:19,480 --> 00:17:22,400
+برضه الـ golf تبعتي، أو الـ playing golf يعني فرصة
+
+243
+00:17:22,400 --> 00:17:25,580
+أني ألعب الـ golf في الظروف المناخية اللي موجودة في
+
+244
+00:17:25,580 --> 00:17:27,920
+الـ data set اللي موجودة عندي، فرصة عالية  اللي أشارناها
+
+245
+00:17:27,920 --> 00:17:30,480
+yes، تمام.
+
+246
+00:17:32,780 --> 00:17:38,280
+طيب، سؤال، ونفرض تقدروا تجاوبوا عليه، بما أنه هذا الـ
+
+247
+00:17:38,280 --> 00:17:41,400
+attribute هو الـ dominant attribute، يعني هو صاحب
+
+248
+00:17:41,400 --> 00:17:45,500
+القرار في موضوع الـ classification، درجة الحرارة. في
+
+249
+00:17:45,500 --> 00:17:49,120
+حين، أنت لو أنت تخيلنا أن لو كان الجو ماطر، ممكن
+
+250
+00:17:49,120 --> 00:17:54,140
+يأثر في لعبة الـ golf ولا مش هيأثر؟ بتعرفوا إيش
+
+251
+00:17:54,140 --> 00:17:58,710
+يعني لعبة golf؟ ممكن تشوفوا اليوتيوب، how to play
+
+252
+00:17:58,710 --> 00:18:01,770
+golf، وبيعلموكم إياه، وتتفرجوا عليها، في الآخر هي
+
+253
+00:18:01,770 --> 00:18:06,370
+رياضة بالعصب، وبيضربوا الكورة عشان يسقطها في حفرة.
+
+254
+00:18:06,370 --> 00:18:10,750
+الآن، بما أن هذا الـ dominant attribute، إيش الحلول
+
+255
+00:18:10,750 --> 00:18:15,690
+اللي قدامي؟ وهل لو أنا غيرت، ممكن أحصل على
+
+256
+00:18:15,690 --> 00:18:20,590
+different result؟ اه، ممكن. أول حل موجود قدامي تماماً
+
+257
+00:18:20,590 --> 00:18:27,330
+زي ما بتبادر لذهنك الآن، أن أعمل scaling. صحيح، ممكن
+
+258
+00:18:27,330 --> 00:18:31,710
+أنا أعمل scaling، لو صارت هذه أربعة ونص، أربعة و
+
+259
+00:18:31,710 --> 00:18:36,110
+تلاتة من عشرة، أربعة point واحد، تلاتة point ستة
+
+260
+00:18:36,110 --> 00:18:40,770
+واحد point تمانية، واحد point سبعة، اتنين point zero
+
+261
+00:18:40,770 --> 00:18:45,410
+تلاتة point تلاتة، واحد point ستة، تلاتة point اتنين
+
+262
+00:18:45,410 --> 00:18:49,850
+اتنين point تلاتة، اتنين point أربعة، أربعة point
+
+263
+00:18:49,850 --> 00:18:54,730
+zero، تلاتة point اتنين، وطبيعي الحال هتصير واحد
+
+264
+00:18:54,730 --> 00:18:55,070
+point
+
+265
+00:18:57,730 --> 00:19:00,870
+8. إيش اللي صار عندي بعد الـ scaling؟ طبعاً أعمل الـ
+
+266
+00:19:00,870 --> 00:19:04,870
+ratio، قسمت على عشرة، أو ضربت في عشر، أو سالب واحد.
+
+267
+00:19:04,870 --> 00:19:10,170
+شو بتتوقع تصير الـ distance؟ هتقل بين جثين، هتصير فيه
+
+268
+00:19:10,170 --> 00:19:16,310
+عندي أنا أربعة ونص ناقص واحد وتمانية، اللي هي بين
+
+269
+00:19:16,310 --> 00:19:21,510
+جثين 2.9. لاحظوا أن 2.9 صارت قريبة من القيم اللي
+
+270
+00:19:21,510 --> 00:19:25,970
+موجودة، وإذا كمان روحت دربت في عشرة أو سالب 2، ممكن
+
+271
+00:19:25,970 --> 00:19:32,650
+أقلل الـ weight تبعتها، بتصير الـ value balance، تفكير
+
+272
+00:19:32,650 --> 00:19:38,110
+منطقي، لكن هل فعلياً يقودني للنتيجة أفضل؟ بده تجربة
+
+273
+00:19:38,110 --> 00:19:42,650
+وعشان بناءً على هيك، أعتبرها assignment لك، واتقارنها
+
+274
+00:19:42,650 --> 00:19:48,580
+ما بين، في حالة كانت الـ ratio، عملت ratio data، تمام؟
+
+275
+00:19:48,580 --> 00:19:55,220
+أو اشتغلت على الـ numeric data اللي موجودة. حل
+
+276
+00:19:55,220 --> 00:20:00,960
+الثاني، هل في حلول ثانية؟ اه، في حلول ثانية. استخدموا
+
+277
+00:20:00,960 --> 00:20:05,440
+أدمغتكم، هوش الشغلات اللي كنا بنسويها مع الـ data
+
+278
+00:20:05,440 --> 00:20:08,820
+الموجودة. جماعة الخير، أنا بتكلم على درجة الحرارة.
+
+279
+00:20:08,820 --> 00:20:14,970
+درجة الحرارة، شو يعني؟ عادة لما بنقول درجة الجو،
+
+280
+00:20:14,970 --> 00:20:18,010
+بسألُك كيف الجو اليوم يا فلان أو يا فلانة، والله الجو
+
+281
+00:20:18,010 --> 00:20:23,150
+حار، شوب كتير بارد، ماحدش بيقول لي عشرين وتلاتة أو
+
+282
+00:20:23,150 --> 00:20:26,510
+أربعين وكذا، فبالتالي ممكن لو أنا... بالضبط لو أنا
+
+283
+00:20:26,510 --> 00:20:31,030
+حولتها لـ categorical، ممكن تفرج معايا. طيب، هاي حولتها
+
+284
+00:20:31,030 --> 00:20:38,650
+لـ categorical، شو يعني categorical؟ أن
+
+285
+00:20:38,650 --> 00:20:41,390
+أنا حطيتها لفئات، على الـ data set اللي موجودة
+
+286
+00:20:41,390 --> 00:20:48,970
+عندي، عشان بس تكونوا في الصورة. من عشرين، أقل أو تساوي
+
+287
+00:20:48,970 --> 00:20:55,650
+عشرين، استخدمنا cool. أكبر
+
+288
+00:20:55,650 --> 00:21:03,330
+من عشرين وأقل أو تساوي أربعين، استخدمنا أقل من أربعين،
+
+289
+00:21:03,330 --> 00:21:10,770
+عفواً، استخدمنا mild. وفوق الأكبر أو تساوي الأربعين،
+
+290
+00:21:13,100 --> 00:21:18,600
+روحنا استخدمنا الـ hot. اتذكروا
+
+291
+00:21:18,600 --> 00:21:23,120
+أن كانت عندي hand، تمانتاشر درجة الحرارة في الـ test
+
+292
+00:21:23,120 --> 00:21:26,820
+sample اللي موجودة عندي hand، الآن. وبالتالي لما أنا
+
+293
+00:21:26,820 --> 00:21:30,820
+بداجي أفحص درجة الحرارة اللي موجودة، خمسة وأربعين،
+
+294
+00:21:30,820 --> 00:21:35,940
+hot، تلاتة وأربعين hot، واحدة وأربعين hot، ستة و
+
+295
+00:21:35,940 --> 00:21:41,060
+تلاتين mild، cool، cool، cool، mild، cool.
+
+296
+00:21:45,290 --> 00:21:52,930
+Mild، Mild، Hot، Mild، تمام؟
+
+297
+00:21:52,930 --> 00:21:55,950
+هذه الـ data set، وبينما هذه الـ 18 هتكون عندي cool.
+
+298
+00:21:55,950 --> 00:21:59,790
+الآن صارت كل الـ data عندي categorical، وبالتالي صارت
+
+299
+00:21:59,790 --> 00:22:04,310
+كل الـ attributes اللي عندي نفس الـ weight، شو
+
+300
+00:22:04,310 --> 00:22:10,430
+ضال عليّ أحسب الـ distance؟ طيب، أنا هسكت دقيقة، هعمل
+
+301
+00:22:10,430 --> 00:22:15,270
+pause دقيقة، أترك لكم مجال، أجيب الحسبة تبعتي. أستخدم
+
+302
+00:22:15,270 --> 00:22:19,050
+Manhattan ولا أستخدم الـ Euclidean distance لحساب
+
+303
+00:22:19,050 --> 00:22:22,690
+الـ similarity ما بين العناصر اللي موجودة عندنا.
+
+304
+00:22:28,290 --> 00:22:32,770
+طيب... الآن، بما أن كل الـ data categorical، معناته صفر
+
+305
+00:22:32,770 --> 00:22:35,830
+وواحد، هتصير المعادلة تبعتي، وخلينا مش فارق كتير
+
+306
+00:22:35,830 --> 00:22:39,530
+معايا من هاتن أو إكلوديا، مش فارق كتير، في الآخر أنا
+
+307
+00:22:39,530 --> 00:22:45,570
+بدي أجمع أصفار وواحدات. sunny وsunny، zero، زائد
+
+308
+00:22:45,570 --> 00:22:51,390
+hot وcool، واحد، لأن اتفقنا في حالة التشابه صفر، في
+
+309
+00:22:51,390 --> 00:22:58,750
+حالة الاختلاف واحد. زائد normal وhigh، واحد، زائد
+
+310
+00:22:58,750 --> 00:23:03,690
+false وtrue، واحد. وبالتالي هذه القيمة تلاتة. الـ
+
+311
+00:23:03,690 --> 00:23:09,170
+attribute اللي بعدها، sunny 0، زائد hot واحد، زائد
+
+312
+00:23:09,170 --> 00:23:13,950
+واحد، زائد صفر، وهذا يساوي اتنين. ولاحظ، لاحظ كل الـ
+
+313
+00:23:13,950 --> 00:23:17,030
+values تبعتي بالدور حوالين الـ range اللي موجود
+
+314
+00:23:17,030 --> 00:23:21,410
+عندي هان، اما بين الأربعة والصفر. هذه القيم اللي
+
+315
+00:23:21,410 --> 00:23:25,070
+موجودة عندي هان. طبعاً أنا مجهز هان عشان ما نضيعش
+
+316
+00:23:25,070 --> 00:23:29,190
+الوقت في الحساب. هذه
+
+317
+00:23:29,190 --> 00:23:30,510
+الـ computation بالكامل.
+
+318
+00:23:35,230 --> 00:23:47,810
+تمام؟ shortest distance مع الـ K equal واحد، اتنين،
+
+319
+00:23:47,810 --> 00:23:54,590
+أول اتنين هي... لأ، في عندي واحد، هيها الـ
+
+320
+00:23:54,590 --> 00:24:03,970
+label تبعتها no، والـ label هيختلف عن السابقة. في
+
+321
+00:24:03,970 --> 00:24:07,210
+المثال السابق، كانت لما الـ K تبعتي equal واحد، كان
+
+322
+00:24:07,210 --> 00:24:12,990
+بيقول لي ألعب، تمام؟ وبالتالي لما أنا اشتغلت هان،
+
+323
+00:24:12,990 --> 00:24:18,450
+بيقول لي no. هيها، ليش؟ ماحدش يقول لي، لأن؟ ليش يا دكتور
+
+324
+00:24:18,450 --> 00:24:21,470
+مش هذه الـ yes هي اللي كانت؟ لأن عندي الـ sorting،
+
+325
+00:24:21,470 --> 00:24:24,990
+هذا الـ attribute، أو عفواً، هذا الروح، هياخد المرتبة
+
+326
+00:24:24,990 --> 00:24:29,550
+الأولى. يعني، بينجو سي، لما أنت بتيجي ترتب، خلينا نتكلم
+
+327
+00:24:29,550 --> 00:24:33,110
+بالـ bubble sort. شو مفهوم الـ bubble sort؟ بضلني
+
+328
+00:24:33,110 --> 00:24:36,590
+أقارن العنصر، لما بلاقي أصغر عنصر، ما بدي أش اساوي
+
+329
+00:24:36,590 --> 00:24:41,210
+فيه، أحركه للأعلى. بضلني أقارن العنصر مع عناصر
+
+330
+00:24:41,210 --> 00:24:44,370
+الجابلة، لحد ما بلاقي أصغر عنصر، بصير أرفعه. بهيك أنا
+
+331
+00:24:44,370 --> 00:24:50,430
+بأضمن، بدور على الـ minimum value، بروح بحطها فوق.
+
+332
+00:24:50,430 --> 00:24:54,330
+بدور على الـ minimum وبعملها shift، وهكذا، وبالتالي
+
+333
+00:24:55,510 --> 00:24:59,750
+هذه هي أول واحدة ستحصل عليها. أنت مش مصدق؟ خد الـ
+
+334
+00:24:59,750 --> 00:25:06,270
+data set هذه على الـ Excel، واعمل لها sort تبعاً للـ
+
+335
+00:25:06,270 --> 00:25:09,350
+distance، وستجد أن الـ attribute هذه ستكون أول
+
+336
+00:25:09,350 --> 00:25:15,430
+attribute موجود عندك. تمام؟ لو الـ K equal 3، هاي
+
+337
+00:25:15,430 --> 00:25:22,000
+واحدة، وهي واحدة، وهي واحدة. أنا عندي أربعة، فأخد أول
+
+338
+00:25:22,000 --> 00:25:27,040
+تلاتة. واحد، اتنين، تلاتة، الـ majority تبعتها yes.
+
+339
+00:25:27,040 --> 00:25:32,960
+وبالتالي هتكون yes. لو قلت له خمسة، هضيف الواحد هذه
+
+340
+00:25:32,960 --> 00:25:37,740
+معهم كمان، وهتيجي وراهم الاتنين هذه. الآن، تعالَ
+
+341
+00:25:37,740 --> 00:25:39,260
+نشوف الـ label اللي صارت عندي هنا.
+
+342
+00:25:42,540 --> 00:25:49,660
+صار في عندي 1، 2، 3، 60% yes، و40% no. وبالتالي لما
+
+343
+00:25:49,660 --> 00:25:52,980
+تكون الخمسة، الـ K تبعتي equal خمسة، معناته المجلة
+
+344
+00:25:52,980 --> 00:25:58,180
+تبعتي بتقول yes. ملاحظين معايا تأثير فعلياً الـ
+
+345
+00:25:58,180 --> 00:26:01,770
+processing على الـ data set؟ جدّاً مهم، جدّاً مهم. بتمنى
+
+346
+00:26:01,770 --> 00:26:05,610
+أن يكون هذا الموضوع أصبح اليوم يعني من بديهيات
+
+347
+00:26:05,610 --> 00:26:11,210
+لديكم، ومن ثم أنه إحنا فعلياً أصبحنا غطينا كل جوانب
+
+348
+00:26:11,210 --> 00:26:14,370
+الـ K nearest neighbor، إن شاء الله تبارك وتعالى.
+
+349
+00:26:14,370 --> 00:26:19,510
+تمام. الآن، هنتقل إن شاء الله تبارك وتعالى للـ
+
+350
+00:26:19,510 --> 00:26:23,690
+algorithm الثاني. للـ algorithm الثاني، اللي هو بيبني
+
+351
+00:26:23,690 --> 00:26:28,390
+شبه model، تمام، وبيعتمد على الـ probabilistic. الـ
+
+352
+00:26:28,390 --> 00:26:32,050
+classification، هيعتمد على نظرية الاحتمالات في الـ
+
+353
+00:26:32,050 --> 00:26:36,750
+classification، وفهمها اللي
+
+354
+00:26:36,750 --> 00:26:41,690
+هو الـ naive Bayesian algorithm، أو الـ bias، يعني
+
+355
+00:26:41,690 --> 00:26:45,790
+classification، وبالتحديد الـ naive bias classifier.
+
+356
+00:26:45,790 --> 00:26:50,390
+طيب.
+
+357
+00:26:50,390 --> 00:26:56,640
+الآن إحنا اتفقنا... اتفقنا سابقاً أن الـ K nearest neighbor
+
+358
+00:26:56,640 --> 00:27:02,340
+هو عبارة عن instance based model، مصبوط. يعني بيعتمد
+
+359
+00:27:02,340 --> 00:27:06,420
+دائماً في كل مرة، مع كل sample، بروح بعمل حسبة للـ
+
+360
+00:27:06,420 --> 00:27:09,440
+distance من الـ sample الأولى في الـ training set للـ
+
+361
+00:27:09,440 --> 00:27:13,220
+sample الأخيرة، تمام. وبدور على الـ data set اللي
+
+362
+00:27:13,220 --> 00:27:19,760
+موجودة عندها. في الـ Bayesian، شوية الأمور مختلفة. الـ
+
+363
+00:27:19,760 --> 00:27:24,970
+Bayesian model، أو الـ Naive bias، هو عبارة عن very fast
+
+364
+00:27:24,970 --> 00:27:29,910
+model وsimple classification في نفس الوقت. مناسب
+
+365
+00:27:29,910 --> 00:27:33,450
+جدّاً مع الـ high dimensional data set اللي موجودة
+
+366
+00:27:33,450 --> 00:27:38,330
+عندي، لأنه
+
+367
+00:27:38,330 --> 00:27:41,250
+فعلياً ما فيش فيه parameters. لو كانت فيه parameters موجودة،
+
+368
+00:27:41,250 --> 00:27:44,730
+ما فيش فيه parameters كتير أعتمد عليها. العناصر أو الـ
+
+369
+00:27:44,730 --> 00:27:49,690
+Naive bias بشكل عام بيعتمد على الـ probabilistic، و
+
+370
+00:27:49,690 --> 00:27:54,410
+بوصف العلاقة ما بين العناصر أو الـ attributes والـ
+
+371
+00:27:54,410 --> 00:27:59,790
+label بناءً على احتمالات. خلينا نيجي نقول، أذكركم
+
+372
+00:27:59,790 --> 00:28:03,090
+بس بالاحتمالات اللي موجودة عندي هان. لو كان أنا في
+
+373
+00:28:03,090 --> 00:28:11,870
+عندي صندوق بيحتوي على عشرة samples، 6
+
+374
+00:28:11,870 --> 00:28:17,410
+plus و4 minus.
+
+375
+00:28:25,310 --> 00:28:32,810
+الآن بلاش plus، خلينا نرسم عمود بالشكل هذا، لحاجة في
+
+376
+00:28:32,810 --> 00:28:39,670
+بالي. يعني الآن، وجئت قلت لك قداش احتمال أنه يطلع
+
+377
+00:28:39,670 --> 00:28:42,770
+معايا plus، عشان بس نذكرك بالاحتمالات.
+
+378
+00:28:45,650 --> 00:28:49,910
+6 على 10، صحيح. الـ probability تبعت الـ plus 6 على 10.
+
+379
+00:28:49,910 --> 00:28:56,810
+والـ probability طبعاً
+
+380
+00:28:56,810 --> 00:29:02,310
+عشرة، هي حجم الـ space، اللي أنا، population اللي أنا
+
+381
+00:29:02,310 --> 00:29:10,010
+بقى اشتغل عليها. طبعاً هذه 4 على 10. الآن
+
+382
+00:29:10,010 --> 00:29:16,670
+في عندي مصطلحات زي الـ most likely، الـ prior، الـ
+
+383
+00:29:16,670 --> 00:29:20,530
+posterior، الـ probability إلى آخرها. الـ posterior،
+
+384
+00:29:20,530 --> 00:29:23,130
+السابق، الـ most likely، اللي هي الأغلب الظن، أو
+
+385
+00:29:23,130 --> 00:29:26,870
+الغالب، العناصر الموجودة، أو الأكثر احتمالا، وكل هذه
+
+386
+00:29:26,870 --> 00:29:30,210
+الحسبة تبعتي بناءً على الـ probabilities. إحنا
+
+387
+00:29:30,210 --> 00:29:33,770
+متفقين الآن... إحنا متفقين الآن أن أنا، هي الـ
+
+388
+00:29:33,770 --> 00:29:36,130
+probability تبعتي. لكن لو أنا جئت وقلت لك مش بس
+
+389
+00:29:36,130 --> 00:29:41,670
+على الـ final shape، وبدخل معاها الـ color، وروحت و
+
+390
+00:29:41,670 --> 00:29:43,670
+قلت لك في عندي الـ dash هذه.
+
+391
+00:29:49,240 --> 00:30:00,200
+
+445
+00:34:21,990 --> 00:34:29,110
+عليها أو أخلص منها عفواً، بس الآن خلّيني أقول هنا C
+
+446
+00:34:29,110 --> 00:34:34,430
+of X الـ class لـ X يساوي الـ maximum probability
+
+447
+00:34:34,430 --> 00:34:39,660
+لمين؟ الـ B لـ Probability لـ الـ class يعني بينجو
+
+448
+00:34:39,660 --> 00:34:42,580
+سيم يجي ويقول لي والله الـ instance الفلانية اللي
+
+449
+00:34:42,580 --> 00:34:49,080
+هي الـ dash هذه الـ class طبعتها الـ class طبعت الـ
+
+450
+00:34:49,080 --> 00:34:52,440
+dash هذه تساوي الـ maximum probability
+
+451
+00:34:52,440 --> 00:34:56,260
+probability يعني بدي آخذ أعلى probability لمين؟ لـ
+
+452
+00:34:56,260 --> 00:34:59,080
+الـ classes أنا في عندي two classes يعني بدي أحسب
+
+453
+00:34:59,080 --> 00:35:02,360
+two probabilities الـ probability لـ الـ class أنَّها
+
+454
+00:35:02,360 --> 00:35:08,530
+تكون زائد أو تكون عمود، تمام؟ فمضروبة انه جداش
+
+455
+00:35:08,530 --> 00:35:12,310
+احتمال عناصر... مجموع العناصر اللي موجودة عندي هنا
+
+456
+00:35:12,310 --> 00:35:17,150
+مع الـ class اللي عندي، وبما أنَّه عملية مقارنة زي ما
+
+457
+00:35:17,150 --> 00:35:20,890
+خلصت سابقاً من الجذر التربيعي، ممكن أخلص الآن من
+
+458
+00:35:20,890 --> 00:35:25,250
+المقام لأن ما بدي أجسم على ثابت، فممكن أنا أخلص منه
+
+459
+00:35:25,250 --> 00:35:29,890
+وبالتالي أنا بُصغر المسألة تبعتي للـ argument X
+
+460
+00:35:29,890 --> 00:35:33,390
+تعالَ نشوف العناصر، إيش المقصود فيها بشكل سريع
+
+461
+00:35:34,040 --> 00:35:40,160
+المعادلة السابقة اللي إحنا ظهرت عندنا هنا الـ
+
+462
+00:35:40,160 --> 00:35:44,900
+posterior probability اللي هيقول لنا posterior سابقاً
+
+463
+00:35:44,900 --> 00:35:49,400
+الـ class على الـ conditional probability تبعت الـ
+
+464
+00:35:49,400 --> 00:35:52,930
+class والـ attributes اللي موجودة عندي هنا الـ
+
+465
+00:35:52,930 --> 00:35:57,510
+Probability لـ X على الـ class، الـ likelihood اللي
+
+466
+00:35:57,510 --> 00:36:01,650
+هي فعلياً الاحتمال اللي أنا بدور عليه، وهو عبارة عن
+
+467
+00:36:01,650 --> 00:36:05,850
+summation سنشوفها قليلاً الآن، Probability تبع الـ
+
+468
+00:36:05,850 --> 00:36:10,710
+class نفسه، الـ prior اللي موجود عندي هنا، والـ X الـ
+
+469
+00:36:10,710 --> 00:36:15,170
+predictor، الـ probability اللي أنا فعلياً بدي أشوفها
+
+470
+00:36:15,170 --> 00:36:18,370
+تعالَ نشوفه عشان نفهم الكلام هذا، والمعادلة من
+
+471
+00:36:18,370 --> 00:36:21,130
+ناحية الحساب، لأن شوية الأمور لو بدأت تبقى في
+
+472
+00:36:21,130 --> 00:36:27,150
+المعادلات الرياضية، هتغم الأمور علينا، لأن إحنا في
+
+473
+00:36:27,150 --> 00:36:31,250
+جماعة هنا على غرار الناس اللي كانت بدأت تلعب golf
+
+474
+00:36:31,250 --> 00:36:34,870
+قررت تروح على البحر، على الشاطئ، الآن هل بدهم يروحوا
+
+475
+00:36:34,870 --> 00:36:37,390
+على الشاطئ ولا ما يروحوش؟ والله قالوا في عندنا ثلاث
+
+476
+00:36:37,390 --> 00:36:42,870
+عوامل أساسية: الطقس، المظهر مشمس ولا ممطر ولا غائم،
+
+477
+00:36:42,870 --> 00:36:47,850
+درجة الحرارة، والـ humidity اللي هي الرطوبة، نفس
+
+478
+00:36:47,850 --> 00:36:50,790
+المثال السابق، لكن غيرنا الـ label من playing golf لـ
+
+479
+00:36:50,790 --> 00:36:53,310
+beach
+
+480
+00:36:54,570 --> 00:36:58,550
+الآن مطلوب مني أشتغل كالتالي: بدي أعمل جدول بسيط
+
+481
+00:36:58,550 --> 00:37:02,290
+الجدول مثل هذا الجدول، هلق إحنا هنشتغل معاكم بكل
+
+482
+00:37:02,290 --> 00:37:06,970
+بساطة، إيش بده يساوي؟ أنا بدي أعمل prediction لـ data
+
+483
+00:37:06,970 --> 00:37:12,390
+set بناءً على probability، أنا الآن هاد الـ data set
+
+484
+00:37:12,390 --> 00:37:15,990
+أو الـ training set تبعتي جاهزة وثابتة، الآن اللي
+
+485
+00:37:15,990 --> 00:37:21,470
+هرَوح أسويه، هرَوح أحسب علاقة الـ X، الـ outlook مع الـ
+
+486
+00:37:21,470 --> 00:37:25,600
+label، الـ Probability تبعتها مع الـ... مع الـ sunny
+
+487
+00:37:25,600 --> 00:37:29,300
+الـ... الـ Probability تبعتها... عفواً، الـ Outlook
+
+488
+00:37:29,300 --> 00:37:31,980
+فيها كم value، different value، three values: sunny
+
+489
+00:37:31,980 --> 00:37:36,920
+وrainy وcloudy، علاقة الـ sunny مع الـ yes ومع الـ
+
+490
+00:37:36,920 --> 00:37:41,020
+no، علاقة الـ rainy مع الـ yes ومع الـ no، علاقة الـ
+
+491
+00:37:41,020 --> 00:37:44,400
+cloudy مع الـ yes مع الـ no، وأفصل في الجدول اللي
+
+492
+00:37:44,400 --> 00:37:50,000
+موجود عندي، يعني بدك تيجي لكل attribute بشكل مستقل
+
+493
+00:37:50,000 --> 00:37:55,380
+هذا الجدول، حاجة أقول والله أنا بدي أتكلم على الـ
+
+494
+00:37:55,380 --> 00:38:01,380
+outlook، طبعاً جابلي جماعة الخير، لو أنا سألتك، لأن الـ
+
+495
+00:38:01,380 --> 00:38:05,840
+going للـ beach للـ yes وللـ no زي ما حسبنا هنا الـ
+
+496
+00:38:05,840 --> 00:38:09,140
+probability للـ yes جداش تساوي؟ الـ data 6 فيها
+
+497
+00:38:09,140 --> 00:38:15,620
+عشرة، هنا واحدة، اثنين، ثلاث، أربعة yes، أربعة على
+
+498
+00:38:15,620 --> 00:38:20,340
+عشرة، الـ probability للـ no ستة على عشرة بكل تأكيد
+
+499
+00:38:20,340 --> 00:38:27,530
+بدون ما أروح أضطر أعدّ الـ yes مظبوطة، الـ outlook الـ
+
+500
+00:38:27,530 --> 00:38:34,230
+outlook الآن فيها three different values، في
+
+501
+00:38:34,230 --> 00:38:38,830
+عندي الـ sunny، في
+
+502
+00:38:38,830 --> 00:38:49,690
+عندي الـ rainy وفي عندي الـ cloudy، ممتاز، طيب وأنا في
+
+503
+00:38:49,690 --> 00:38:54,950
+عندي فعلياً في الـ labels في عندي الـ yes وفي عندي
+
+504
+00:38:54,950 --> 00:39:02,450
+الـ No، الـ beach، صح؟
+
+505
+00:39:02,450 --> 00:39:05,810
+الآن
+
+506
+00:39:05,810 --> 00:39:10,130
+كم واحدة sunny عندي؟ أنا واحدة، اثنين، ثلاث، أربعة
+
+507
+00:39:10,130 --> 00:39:16,170
+ممتاز، علاقة الأربع الـ sunny هدول المفروض يكونوا
+
+508
+00:39:16,170 --> 00:39:22,350
+مُجسَّمات على الـ yes والـ no، الـ yes جداش؟ أربعة، طيب
+
+509
+00:39:22,350 --> 00:39:26,890
+الآن بدي أقول sunny وyes، يعني أنا بدي أجسّم على
+
+510
+00:39:26,890 --> 00:39:32,470
+أربعة يا جماعة الخير، وأنَّه ستة، مضبوط، لأن الـ over
+
+511
+00:39:32,470 --> 00:39:36,030
+all probability تبعت الـ yes، ظهور الـ yes فقط أربع
+
+512
+00:39:36,030 --> 00:39:40,290
+عناصر، أربع مرات، وظهور الـ no ست مرات، إذا كانت الـ
+
+513
+00:39:40,290 --> 00:39:43,170
+yes مرتبطة بالـ classes هاي، فعشان أنا أحسب الـ
+
+514
+00:39:43,170 --> 00:39:48,650
+probability تبعت الـ yes والـ sunny، الـ sunny هاي
+
+515
+00:39:48,650 --> 00:39:49,670
+مرة yes
+
+516
+00:39:55,170 --> 00:40:00,990
+اثنين، ثلاث، أربعة، صح؟ ليش هذه لا؟ لأن هذه جاء الـ label
+
+517
+00:40:00,990 --> 00:40:03,550
+تبعتها no، هاي خلّصنا الأربع الـ sunny اللي موجودة
+
+518
+00:40:03,550 --> 00:40:06,410
+عندها، يعني بينجو، اثنين، الـ sunny الـ probability
+
+519
+00:40:06,410 --> 00:40:15,970
+تبعتها ثلاث على أربعة، زائد جداش؟ جداش واحد على ستة
+
+520
+00:40:17,560 --> 00:40:20,760
+خلاص، أنت ما فيش داعي إنك أنت عايش تنظر لباقي
+
+521
+00:40:20,760 --> 00:40:23,600
+العناصر، مجموع الـ sun اللي فوق على العناصر اللي
+
+522
+00:40:23,600 --> 00:40:29,940
+موجودة عندي هنا، الـ rainy الآن جداش؟ حسّبة الـ yes ما
+
+523
+00:40:29,940 --> 00:40:34,440
+زالت أربعة، والنقل ستة، rainy بدي أشتغل عليها نفس
+
+524
+00:40:34,440 --> 00:40:42,160
+الكلام، rainy واحدة، اثنين، ثلاث، في عندي ثلاث rainy
+
+525
+00:40:42,160 --> 00:40:49,180
+والثلاث جايات كلهن من نفس الـ class، معناته صفر على
+
+526
+00:40:49,180 --> 00:40:57,220
+أربعة زائد ثلاث على ستة، وهلّق بيقول لك طريقة كيف
+
+527
+00:40:57,220 --> 00:41:00,200
+تتأكد من حيث تفكر إن كل الـ probability بتاعتك صح
+
+528
+00:41:00,200 --> 00:41:06,140
+cloudy الآن برضه نفس الكلام، أربعة على ستة،
+
+529
+00:41:06,140 --> 00:41:12,100
+cloudy فيها واحدة مع الـ yes وهم ثلاث، واثنين مع
+
+530
+00:41:15,120 --> 00:41:20,080
+الستة، الآن لو عديت العناصر تبعت الـ yes، ثلاث على
+
+531
+00:41:20,080 --> 00:41:24,520
+أربعة زائد صفر على أربعة زائد واحد على أربعة، تطلع
+
+532
+00:41:24,520 --> 00:41:31,420
+أربعة على أربعة، لو عديت عناصر إنَّه واحد على ستة
+
+533
+00:41:31,420 --> 00:41:34,820
+زائد ثلاث على ستة زائد اثنين على ستة، تطلع ستة على
+
+534
+00:41:34,820 --> 00:41:38,740
+ستة، وهي فعلياً الـ probability، لازم مجموع الاحتمالات
+
+535
+00:41:38,740 --> 00:41:43,600
+كلها تكون عندي واحد، ممتاز، هذا بالنسبة للـ attribute
+
+536
+00:41:43,600 --> 00:41:44,180
+الأول
+
+537
+00:41:46,970 --> 00:41:49,970
+وبدي أروح أحسبها للـ attribute الثاني بنفس الكيفية،
+
+538
+00:41:49,970 --> 00:41:55,530
+temperature
+
+539
+00:41:55,530 --> 00:41:59,870
+temperature كان فيه... كان value عندي، عندي three
+
+540
+00:41:59,870 --> 00:42:04,410
+values: high، وlow، وmild، الـ low نبدأ مع الـ low هاي
+
+541
+00:42:04,410 --> 00:42:11,250
+واحدة، هاي اثنين، اثنين بدهم يتوزّعوا على الـ yes والـ
+
+542
+00:42:11,250 --> 00:42:17,570
+no، الآن صفر no، و no، معناته صفر على أربعة، واثنين
+
+543
+00:42:17,570 --> 00:42:23,870
+على ستة مع الـ no، طيب خلّصنا من الـ من الـ low، الـ mild
+
+544
+00:42:23,870 --> 00:42:32,710
+الـ mild هي واحدة، اثنين، ثلاث، ثلاث عناصر، الثلاث
+
+545
+00:42:32,710 --> 00:42:36,560
+عناصر هدول يتوزّعوا ما بين الـ yes والـ no، هي الـ
+
+546
+00:42:36,560 --> 00:42:40,700
+mild الأولى yes، الـ mild الثانية no، والـ mild
+
+547
+00:42:40,700 --> 00:42:45,900
+الأخيرة no، معناته الآن هم هيكونوا واحد على أربعة مع الـ
+
+548
+00:42:45,900 --> 00:42:52,580
+yes اللي هي الأولى هاي، واثنين على ستة في حالة الـ no، و
+
+549
+00:42:52,580 --> 00:42:58,320
+بكمل الجدول لكل العناصر اللي موجودة عندي هنا، الـ
+
+550
+00:42:58,320 --> 00:43:00,580
+probability تبعت الـ beach، ممكن أحطّ لإيه؟ أنا كتبت
+
+551
+00:43:00,580 --> 00:43:05,790
+هنا قبل شوية، ممكن أحطها في نهاية الجدول، عشان أنا
+
+552
+00:43:05,790 --> 00:43:09,790
+أشتغل على العناصر اللي موجودة عندي فعلياً، ستة على عشرة
+
+553
+00:43:09,790 --> 00:43:15,230
+... الآن أربعة على عشرة، المفروض
+
+554
+00:43:15,230 --> 00:43:19,550
+في كل واحدة من هدول، ما يلاحظ أربعة على عشرة... أربعة على عشرة
+
+555
+00:43:19,550 --> 00:43:24,980
+... أربعة على عشرة، ليش أربعة؟ لأن فعلاً أربعة على الـ yes، و
+
+556
+00:43:24,980 --> 00:43:28,220
+هدول لازم يكون مجموعهم أربعة في كل attribute، وهدول
+
+557
+00:43:28,220 --> 00:43:31,260
+مجموعهم لازم يكون ستة، وفي المحصلة ستة على عشرة
+
+558
+00:43:31,260 --> 00:43:36,140
+ممتاز، الآن لاحظوا هذه الـ computation كم مرة هأعملها؟
+
+559
+00:43:36,140 --> 00:43:43,120
+لمرة واحدة على نفس الـ data set، هأعملها لمرة واحدة
+
+560
+00:43:43,120 --> 00:43:46,180
+فقط، ولما الـ data... ولما الـ data set ما صار
+
+561
+00:43:46,180 --> 00:43:51,030
+عليها تغيير، هتظل هذه موجودة عندي، إيش اللي حيصير
+
+562
+00:43:51,030 --> 00:43:55,810
+لاحقاً، عشان أطبّق المعادلة السابقة هذه، هأشتغل كالتالي:
+
+563
+00:43:55,810 --> 00:44:01,030
+بيجي بقول: بالله شوف اللي، إيش الـ label تبعت الـ
+
+564
+00:44:01,030 --> 00:44:06,810
+sunny والـ mild والـ high، إيش الـ label تبعت الـ
+
+565
+00:44:06,810 --> 00:44:12,130
+sunny، sunny
+
+566
+00:44:12,130 --> 00:44:17,450
+و mild، و
+
+567
+00:44:17,450 --> 00:44:18,850
+high، درجة الحرارة
+
+568
+00:44:21,880 --> 00:44:27,460
+عشان بدي أرجع معاكم للجدول السابق، تمّ ذكره في
+
+569
+00:44:27,460 --> 00:44:34,380
+المعادلة، المعادلة بتقول: الـ argmax لـ CI اللي
+
+570
+00:44:34,380 --> 00:44:37,000
+هي الـ class، الـ probability للـ CI مضروبة في الـ
+
+571
+00:44:37,000 --> 00:44:44,120
+probability لـ X على الـ CI، طيب هلّق قد بنفسر لك
+
+572
+00:44:44,120 --> 00:44:47,920
+إيّاها أوضح، وبنفسر لك إيّاها أوضح مع الأرقام، نرجع هنا
+
+573
+00:44:47,920 --> 00:44:54,580
+الـ probability للـ class، هو قاعد بيقول لي: بدور على الـ
+
+574
+00:44:54,580 --> 00:44:58,480
+argmax، بدور على الـ maximum probability لكل classes
+
+575
+00:44:58,480 --> 00:45:02,740
+كم class أنا عندي؟ عندي two classes، يعني بين جثين
+
+576
+00:45:02,740 --> 00:45:05,600
+الجماعة الخير، هو عمال بيسألني، بيسألني الـ
+
+577
+00:45:05,600 --> 00:45:10,800
+probability تبعت الـ element اللي موجود عندها على
+
+578
+00:45:10,800 --> 00:45:14,520
+أنّه يكون الـ class، والـ instance اللي أعطاني إيّاها
+
+579
+00:45:17,240 --> 00:45:19,840
+مش قلنا هذه اللي أنا بدور عليها، قاعد؟ هاي الـ
+
+580
+00:45:19,840 --> 00:45:23,160
+value، هو بدي تجيب لي الـ probability تبعت الـ class
+
+581
+00:45:23,160 --> 00:45:27,760
+مع الـ given instance اللي موجودة عندي هنا، طيب،
+
+582
+00:45:27,760 --> 00:45:31,080
+الآن حسب الـ data set، معناته أنا بدي أروح أشتغل
+
+583
+00:45:31,080 --> 00:45:36,960
+كالتالي: مرة مع الـ yes ومرة مع no، هذا الكلام بيقول
+
+584
+00:45:36,960 --> 00:45:42,480
+إيه؟ الـ probability مع الـ yes، الـ label مع مين؟ مع
+
+585
+00:45:42,480 --> 00:45:51,040
+الـ given data set، الـ sunny والـ mild والـ high، إيش الـ
+
+586
+00:45:51,040 --> 00:45:56,340
+probability تبعت high؟ أولاً بقول: هذه تساوي الـ
+
+587
+00:45:56,340 --> 00:46:02,260
+probability تبعت الـ yes، مضروبة
+
+588
+00:46:02,260 --> 00:46:09,520
+في الـ probability تبعت مين؟ تبعت الـ instance اللي
+
+589
+00:46:09,520 --> 00:46:14,590
+موجودة عندي هنا، أي instance، طب الـ instance تبعتي
+
+590
+00:46:14,590 --> 00:46:20,510
+مكونة من الـ outlook والـ temperature والـ humidity
+
+591
+00:46:20,510 --> 00:46:25,390
+مضبوط؟ كمان مرة، الـ instance تبعتي هنا اللي هي الـ X
+
+592
+00:46:25,390 --> 00:46:33,830
+هذه اللي أنا الآن هيها، مكونة من الـ outlook والـ
+
+593
+00:46:33,830 --> 00:46:39,000
+temperature والـ humidity، و بدي أروح بقول لي: علاقة كل
+
+594
+00:46:39,000 --> 00:46:41,580
+الـ values اللي موجودة عندهم بالـ class مين؟ بالـ
+
+595
+00:46:41,580 --> 00:46:47,740
+class yes، يعني بين جثين، هي عبارة عن الـ probability
+
+596
+00:46:47,740 --> 00:46:53,700
+لـ
+
+597
+00:46:53,700 --> 00:47:01,840
+S، للـ sunny، الـ outlook، equal
+
+598
+00:47:01,840 --> 00:47:04,980
+sunny مع الـ yes
+
+599
+00:47:08,130 --> 00:47:15,570
+مضروبة في الـ attribute الثانية، الـ probability تبعت
+
+600
+00:47:15,570 --> 00:47:26,130
+الـ temperature على الـ yes، هاي الـ sunny أو
+
+601
+00:47:26,130 --> 00:47:34,470
+الآن mild، هاي الـ mild، الـ temperature تبعتي high
+
+602
+00:47:37,170 --> 00:47:44,970
+هي الـ high، بكل بساطة بقول: ليه؟ ثلاث على أربعة، أو
+
+603
+00:47:44,970 --> 00:47:47,530
+عفواً، من الأول، أربعة على عشرة، تبع الـ yes، الـ
+
+604
+00:47:47,530 --> 00:47:50,050
+probability اللي موجودة عندي هنا، أربعة على عشرة
+
+605
+00:47:50,050 --> 00:47:57,970
+مضروبة في ثلاث على أربعة، مضروبة في اثنين، عفواً
+
+606
+00:47:57,970 --> 00:48:04,640
+واحد على أربعة، في اثنين على أربعة، وبهيك بكون أنا بدي
+
+607
+00:48:04,640 --> 00:48:13,800
+أعيد الحسبة تبعت لمين؟ لكل العناصر الموجودة، يعني الـ
+
+608
+00:48:13,800 --> 00:48:17,720
+probability للـ yes، طبعاً أنا فصلت لكم إيّاها عشان
+
+609
+00:48:17,720 --> 00:48:21,540
+ما تنسوهاش، لأن لاحظوا إن هي عبارة عن عملية ضرب
+
+610
+00:48:21,540 --> 00:48:26,320
+هادي لـ probability تبعت
+
+611
+00:48:26,320 --> 00:48:33,860
+الـ X على Ci، على class، تساوي لـ probability لمن؟ للـ
+
+612
+00:48:33,860 --> 00:48:42,700
+values x i على... هي بنجسّم الـ product للـ x i على
+
+613
+00:48:42,700 --> 00:48:50,080
+الـ class اللي موجودة عندها x j، والـ j equal 1 to n،
+
+614
+00:48:50,080 --> 00:48:57,240
+بعدد الـ attributes اللي موجودة عندها، الآن الـ
+
+615
+00:48:57,240 --> 00:49:03
+
+667
+00:53:34,950 --> 00:53:41,710
+Outlook equals sunny يا جماعة الخير اللي
+
+668
+00:53:41,710 --> 00:53:44,330
+هي الـ attribute الأول، خلاص هي إحنا هنعتمدها بالشكل
+
+669
+00:53:44,330 --> 00:53:50,330
+هذا على الـ yes مضروبة في الـ probability للـ mild
+
+670
+00:53:50,330 --> 00:53:54,070
+اللي هي الـ attribute الثاني على الـ yes مضروبة في
+
+671
+00:53:54,070 --> 00:53:56,830
+الـ probability للـ attribute الثالث اللي هي الـ low
+
+672
+00:53:56,830 --> 00:54:00,730
+على الـ yes، بنجي نسينيج، هي عمود الـ yes، كل شغل على
+
+673
+00:54:00,730 --> 00:54:07,740
+الكيون على العمود هذا، sunny هي الـ value، هي الـ
+
+674
+00:54:07,740 --> 00:54:17,800
+value، و normal هي هيها
+
+675
+00:54:17,800 --> 00:54:22,160
+normal normal
+
+676
+00:54:22,160 --> 00:54:28,680
+بس عشان الـ example يكون تمام، بالـ normal هيها الآن
+
+677
+00:54:28,680 --> 00:54:38,860
+بكل بساطة، أربعة على عشرة ضرب ثلاثة على أربعة ضرب واحد
+
+678
+00:54:38,860 --> 00:54:45,460
+على أربعة ضرب اثنين على أربعة، وإذا أنا بدي أطلع الـ calculator
+
+679
+00:54:45,460 --> 00:54:50,980
+على السريع عشان أشوف حسابة هل في فعلياً تأثير للـ
+
+680
+00:54:50,980 --> 00:54:52,140
+element هذا أو لأ
+
+681
+00:54:56,850 --> 00:55:04,090
+قولنا أربعة على عشرة ضرب ثلاثة على أربعة ضرب واحد
+
+682
+00:55:04,090 --> 00:55:13,790
+على أربعة ضرب، طفت الـ calculator، أربعة
+
+683
+00:55:13,790 --> 00:55:24,110
+تقسيم عشرة ضرب ثلاثة تقسيم أربعة ضرب واحد تقسيم
+
+684
+00:55:24,110 --> 00:55:24,750
+أربعة
+
+685
+00:55:27,550 --> 00:55:34,890
+ضرب اثنين تقسيم أربعة anyway
+
+686
+00:55:34,890 --> 00:55:41,550
+الـ calculator خذلتنا في الآخر، الـ probability لأنه
+
+687
+00:55:41,550 --> 00:55:45,750
+بدي أعمل الـ probability لأنه لنفس الـ instance M N
+
+688
+00:55:45,750 --> 00:55:49,070
+حتكون
+
+689
+00:55:49,070 --> 00:55:53,810
+الـ probability لأنه مضروبة
+
+690
+00:56:14,390 --> 00:56:17,910
+القيم المقابلة لهم اللي عمال يحوطهم باللون الأزرق
+
+691
+00:56:20,470 --> 00:56:23,350
+بالإضافة للقيمة الأخيرة، ما تنسوهاش طبعاً، هاي اللي
+
+692
+00:56:23,350 --> 00:56:27,190
+هي في الأول، الـ probability لأنه كلها حتصير في
+
+693
+00:56:27,190 --> 00:56:37,470
+عندها ستة على عشرة مضروبة في واحد على ستة مضروبة في اثنين على ستة
+
+694
+00:56:37,470 --> 00:56:46,630
+مضروبة في اثنين على ستة، طبعاً لو إحنا فعلياً ٣٦ المقام هنا
+
+695
+00:56:46,630 --> 00:56:51,010
+أكبر من هنا، فغالباً اللي بالنتيجة حتكون yes، والـ
+
+696
+00:56:51,010 --> 00:56:56,290
+computation هي اللي بتحكم الموضوع، بتمنى تكون الآن
+
+697
+00:56:56,290 --> 00:57:00,010
+أصبحت الصورة بالنسبة لنا واضحة، كيف الـ naive baysian
+
+698
+00:57:00,010 --> 00:57:04,410
+بيشتغل، الفكرة أنه أبني الجدول، إذا أنت بنيت أو أنت
+
+699
+00:57:04,410 --> 00:57:08,690
+بنيت الجدول صح، معناته أنا مافيش عندي مشكلة، طيب في
+
+700
+00:57:08,690 --> 00:57:11,010
+حالة، هذا مثال ثاني على السريع
+
+701
+00:57:14,970 --> 00:57:19,530
+بغض النظر، إحنا مش هنطول عليكم إن شاء الله تعالى، و
+
+702
+00:57:19,530 --> 00:57:22,550
+بنفترض إنكم حتكونوا متابعين معانا، وبيكونوا كأنّه
+
+703
+00:57:22,550 --> 00:57:28,790
+في فرصة تشتغلوا، وزيادة الآن، هاي الـ data set كام
+
+704
+00:57:28,790 --> 00:57:31,470
+attribute؟ ثلاثة على نفس الغرار الـ attribute
+
+705
+00:57:31,470 --> 00:57:34,210
+السابق، السابق اللي لها دخل في الموضوع؟ لأ، هذا رقم
+
+706
+00:57:34,210 --> 00:57:37,270
+العينة، أو رقم الـ sample، الـ class تبعتي binary
+
+707
+00:57:37,270 --> 00:57:41,210
+class، ما فرجتش كتير يا جماعة الخير، بدي أبني الجدول
+
+708
+00:57:41,210 --> 00:57:44,030
+السابق بالكامل
+
+709
+00:57:46,870 --> 00:57:52,690
+هو بيقولوا، بدوا مني لـ class، مصبوط، الـ attribute A1
+
+710
+00:57:52,690 --> 00:57:59,670
+إيش الـ attribute A1 فيه values؟ طبعاً هنا في عندي
+
+711
+00:57:59,670 --> 00:58:05,130
+yes، واحد أو صفر، واحد في الـ attribute الأول كام
+
+712
+00:58:05,130 --> 00:58:08,250
+value؟ في عندي صفر، واحد، اثنين، يعني في عندي three
+
+713
+00:58:08,250 --> 00:58:12,850
+values، صفر، واحد، اثنين، أنا بكتبه من مرتب أفضل
+
+714
+00:58:12,850 --> 00:58:14,830
+إليه، الـ attribute الثاني
+
+715
+00:58:17,880 --> 00:58:20,240
+مع الـ labels اللي موجودة، إيش في عندي برضه values؟
+
+716
+00:58:20,240 --> 00:58:29,700
+صفر، واحد، اثنين، برضه ما عندي مشكلة، صفر، واحد، اثنين، الـ attribute الثالث اللي
+
+717
+00:58:29,700 --> 00:58:33,800
+أنا هشتغل عليه فقط
+
+718
+00:58:33,800 --> 00:58:43,000
+قيمتين، واحد، اثنين، وهنا في الآخر الـ probability للـ class، الـ
+
+719
+00:58:43,000 --> 00:58:45,880
+probability للـ class تبعتي، جدّش الـ probability..
+
+720
+00:58:45,880 --> 00:58:50,900
+كام class فيه؟ عندي three classes، عفواً، مصبوط الـ..
+
+721
+00:58:50,900 --> 00:59:01,360
+واحد، اثنين، ثلاثة، هاتوا، هل بدنا كمان عمود الـ class
+
+722
+00:59:01,360 --> 00:59:06,540
+اللي موجود عندي هنا، واحد
+
+723
+00:59:06,540 --> 00:59:09,400
+اثنين، ثلاثة
+
+724
+00:59:11,920 --> 00:59:17,300
+أي، ثلاثة، الـ
+
+725
+00:59:17,300 --> 00:59:23,540
+class الأول، واحد، واحد، اثنين، ثلاثة، أربعة، أربعة على
+
+726
+00:59:23,540 --> 00:59:31,500
+عشرة، الـ class الثاني، اثنين، واحد، اثنين، ثلاثة، ثلاثة
+
+727
+00:59:31,500 --> 00:59:36,100
+على عشرة، وهدا الأخير، ثلاثة على عشرة، مجموعهم عشرة
+
+728
+00:59:36,100 --> 00:59:41,890
+على عشرة، بدي أجي للعلاقة العناصر مع الـ class الأول
+
+729
+00:59:41,890 --> 00:59:48,170
+اللي موجود عندي هنا، صفر و واحد، هاي صفر، هاي صفر
+
+730
+00:59:48,170 --> 00:59:52,410
+اثنين مع
+
+731
+00:59:52,410 --> 00:59:59,230
+الواحد، أربعة، الـ
+
+732
+00:59:59,230 --> 01:00:04,910
+class واحد، معناته اثنين على أربعة، وحتمًا.. حتماً
+
+733
+01:00:04,910 --> 01:00:11,020
+الصفر مع الـ class الثاني، صفر على عشرة.. صفر على
+
+734
+01:00:11,020 --> 01:00:18,160
+جدّش، الاثنين على ثلاثة، وهنا صفر على ثلاثة، ليش؟ لأن
+
+735
+01:00:18,160 --> 01:00:21,020
+هون فعلياً الصفر هادي بينت مرتين فقط مع الـ
+
+736
+01:00:21,020 --> 01:00:24,240
+attribute الأول، وبالتالي أنا هنا بشغل في الـ
+
+737
+01:00:24,240 --> 01:00:28,560
+attribute الأول، الـ value الثانية، الواحد، الواحد هي
+
+738
+01:00:28,560 --> 01:00:37,560
+في المربع، واحد، واحد، واحد، واحد، أربعة عناصر، برضه حتكون
+
+739
+01:00:37,560 --> 01:00:41,220
+عندها القيمة على أربعة يا جماعة الخير، ما تنساش، وهذه
+
+740
+01:00:41,220 --> 01:00:46,760
+حتكون على ثلاثة، وهذه حتكون على ثلاثة، الآن واحد و
+
+741
+01:00:46,760 --> 01:00:55,800
+واحد هي.. okay، وهي كمان واحد، ممتاز، يعني اثنين على
+
+742
+01:00:55,800 --> 01:00:59,880
+أربعة، اثنين
+
+743
+01:00:59,880 --> 01:01:07,100
+على أربعة، هذه واحدة، وهذه اثنين، طيب جدّش الواحد على
+
+744
+01:01:07,100 --> 01:01:14,440
+ثلاثة، واحد وثلاثة هيها، ما، واحد على ثلاثة، وجدّش
+
+745
+01:01:14,440 --> 01:01:20,220
+مع الواحد والاثنين هيها، الـ probability تبعتها، ضال
+
+746
+01:01:20,220 --> 01:01:25,140
+عند الـ value الأخيرة الموجودة
+
+747
+01:01:25,140 --> 01:01:31,320
+عندي لمين؟ للثنين، هي الثنين، هي الثنين، هي الثنين، في
+
+748
+01:01:31,320 --> 01:01:34,060
+عندي أربعة قيم، الأربعة قيم منهم
+
+749
+01:01:37,600 --> 01:01:41,080
+ولا واحدة مع الـ attribute أو مع الـ class الأول، صفر
+
+750
+01:01:41,080 --> 01:01:44,640
+على أربعة، ولو أنت جمعت فعلياً هنا، اثنين على أربعة
+
+751
+01:01:44,640 --> 01:01:50,720
+أو اثنين على أربعة، لازم يطلع معاك أربعة على أربعة
+
+752
+01:01:50,720 --> 01:01:54,040
+لأن هما الـ maximum أربعة، عفواً، إن هنا اثنين على
+
+753
+01:01:54,040 --> 01:02:00,060
+أربعة، الآن مع الواحد ولا مافيش شيء مع الاثنين هي
+
+754
+01:02:00,060 --> 01:02:04,880
+واحدة، هي اثنين، وبالتالي هنا
+
+755
+01:02:11,280 --> 01:02:16,080
+هذه اثنين على ثلاثة، وهذه اثنين على ثلاثة، لو جمعت
+
+756
+01:02:16,080 --> 01:02:18,420
+العناصر اللي موجودة عندي هنا، والعناصر اللي عندي
+
+757
+01:02:18,420 --> 01:02:21,660
+هنا، لازم تاخد ثلاثة وواحد صحيح، وهذه تاخد واحد
+
+758
+01:02:21,660 --> 01:02:27,000
+صحيح، كمليّة الجدول، نفس الصورة السابقة، حيكون الجدول
+
+759
+01:02:27,000 --> 01:02:32,980
+هيه عندي بالتمام، ومجرد إن أنا أعمل الجدول هذا
+
+760
+01:02:32,980 --> 01:02:39,420
+بيسهل عليّ جداً إن أحسب العناصر، خليني على السريع بس
+
+761
+01:02:39,420 --> 01:02:45,260
+أحط المثال الأخير، لو أنا افترضت إن أنا عندي واحد
+
+762
+01:02:45,260 --> 01:02:52,620
+واحد واثنين، ما أعرفش، أنا كتبت بشكل random، هل فعلياً
+
+763
+01:02:52,620 --> 01:02:57,380
+هذه إيش الاحتمال تبعتها إنّها تظهر عندي، أو إيش الـ
+
+764
+01:02:57,380 --> 01:03:02,560
+class تبعتها اللي توجد عندها، هذه مع الـ class الأول
+
+765
+01:03:02,560 --> 01:03:04,160
+بدي أحسبها
+
+766
+01:03:09,260 --> 01:03:16,820
+و بدي أحسبها مع الـ class الثاني، وبدي أحسبها مع الـ
+
+767
+01:03:16,820 --> 01:03:26,560
+class الثالث، طيب مع الـ class الأول، واحد، وين الـ
+
+768
+01:03:26,560 --> 01:03:31,440
+واحد؟ هيها يا جماعة الخير، الـ attribute الثاني برضه
+
+769
+01:03:31,440 --> 01:03:36,460
+واحد، الـ attribute الثالث كانت اثنين، هيها، معناته
+
+770
+01:03:36,460 --> 01:03:40,240
+أنا بدي آخذ الاحتمال تبع الـ row للـ class الأول
+
+771
+01:03:40,240 --> 01:03:49,580
+معناته أنا بدي أضرب القيم اللي عليها تحتها
+
+772
+01:03:49,580 --> 01:03:55,160
+الخط هذه في بعضها، الـ probability تبعتي الواحد
+
+773
+01:03:55,160 --> 01:03:59,160
+أربعة على عشرة مضروبة في الـ probability، واحد على
+
+774
+01:03:59,160 --> 01:04:03,440
+واحد، اللي هي attribute A1 equal واحد على واحد
+
+775
+01:04:03,440 --> 01:04:10,760
+مضروبة في الـ probability، A1A2 equal واحد على واحد، مضروبة
+
+776
+01:04:10,760 --> 01:04:15,000
+في الـ probability، الـ
+
+777
+01:04:15,000 --> 01:04:18,280
+probability للواحد as class، مضروبة في الـ
+
+778
+01:04:18,280 --> 01:04:23,440
+probability للـ A1 equal واحد على واحد، مضروبة في الـ
+
+779
+01:04:23,440 --> 01:04:29,860
+probability للـ A2 equal واحد على واحد، مضروبة في الـ
+
+780
+01:04:29,860 --> 01:04:36,420
+probability تبعت الـ A3 equal اثنين على الواحد، اللي هي
+
+781
+01:04:36,420 --> 01:04:39,640
+القيم اللي أنا حددتها، هيها، هذا بجيبها للـ class
+
+782
+01:04:39,640 --> 01:04:42,320
+الأول، بجيبها للـ class الثاني، بجيبها للـ class
+
+783
+01:04:42,320 --> 01:04:47,160
+الثالث، ومن ثم هاي
+
+784
+01:04:47,160 --> 01:04:52,300
+الحسبة اللي موجودة عندي الآن، بدور على الـ maximum
+
+785
+01:04:52,300 --> 01:05:00,970
+عندي ٢٥ من ألف، أربعة وأربعين، ٢٥٠ من عشرة آلاف، وأربعة وأربعين
+
+786
+01:05:00,970 --> 01:05:05,150
+من عشرة آلاف، و ١١١ من عشرة آلاف، الـ most
+
+787
+01:05:05,150 --> 01:05:10,610
+probability تبعتي، والـ maximum probability أربعة
+
+788
+01:05:10,610 --> 01:05:14,050
+من مئة، أكيد أكبر من اثنين من مئة، وأكبر من واحد من
+
+789
+01:05:14,050 --> 01:05:18,850
+مئة، وبالتالي أغلب الظن إن هذه الـ instance حتُصنّف
+
+790
+01:05:18,850 --> 01:05:23,750
+مع الـ class الثاني، مع الـ class الثاني، لكن أنا
+
+791
+01:05:23,750 --> 01:05:30,560
+انتبهت لشغلة وأنا بقى أشتغل في الحسبة، وهي إن الـ
+
+792
+01:05:30,560 --> 01:05:38,820
+instances اللي أنا كتبتها موجودة بس
+
+793
+01:05:38,820 --> 01:05:43,670
+إيش الـ class تبعتها؟ ثلاثة، يعني صار في عندي
+
+794
+01:05:43,670 --> 01:05:47,170
+misclassification، هل هذه مسئوليتي؟ لأ، مش مسئوليتي
+
+795
+01:05:47,170 --> 01:05:52,310
+أنا اشتغلت عليها لأن أَخْضَعْتها لاحتمالات تمام، وهذه
+
+796
+01:05:52,310 --> 01:05:55,770
+وزنها كان واحدة من العناصر اللي موجودة، لكن الـ node
+
+797
+01:05:55,770 --> 01:05:58,170
+تبعتي هذه حسب الاحتمالات أو حسب الـ naive baysian
+
+798
+01:05:58,170 --> 01:06:03,950
+بتطلع لمين؟ مع العنصر الـ class two اللي موجود
+
+799
+01:06:03,950 --> 01:06:09,130
+عندها، الآن زي ما قلنا، الـ Naive Bayesian، ختاماً للكلام
+
+800
+01:06:09,130 --> 01:06:11,950
+اللي إحنا اشتغلناه، طبعاً، يا جماعة الخير، في إنّكم data
+
+801
+01:06:11,950 --> 01:06:15,210
+set موجودة سابقاً في الـ examples السابقة، جرّبوا
+
+802
+01:06:15,210 --> 01:06:18,050
+عليها Naive Bayesian، ما تستناش، ما تقوليش،  ملّون، بدي
+
+803
+01:06:18,050 --> 01:06:20,270
+أسئلة، في عندك الـ data set اللي موجود في الـ slides
+
+804
+01:06:20,270 --> 01:06:23,960
+واللي أنا اشتغلت عليها سابقاً، كـ classifier في عنده
+
+805
+01:06:23,960 --> 01:06:25,960
+strict assumptions زي ما قلنا، about الـ data اللي
+
+806
+01:06:25,960 --> 01:06:28,400
+هو الـ independent attributes، والـ normal
+
+807
+01:06:28,400 --> 01:06:32,920
+distribution تبع الـ data اللي موجودة، وهذا بيخليه
+
+808
+01:06:32,920 --> 01:06:35,920
+fast، very fast، أو extremely fast في الـ training
+
+809
+01:06:35,920 --> 01:06:38,060
+وفي الـ prediction، في الـ training لأنه بيبني
+
+810
+01:06:38,060 --> 01:06:41,020
+الجدول مرة واحدة، وفي الـ prediction مافيش.. يعني
+
+811
+01:06:41,020 --> 01:06:43,540
+الـ computation تبعتها قليلة، straightforward
+
+812
+01:06:43,540 --> 01:06:47,900
+probabilistic prediction، بيعتمد على الـ
+
+813
+01:06:47,900 --> 01:06:52,640
+probabilities تماماً، على الاحتمالات، سهل جداً إنّي أفسر
+
+814
+01:06:52,640 --> 01:06:58,620
+ليش طلع هيك، مش بحاجة إنّي أعمل tuning لـ parameter
+
+815
+01:06:58,620 --> 01:07:06,120
+لأن فعلياً أنا ما شفتش أي حاجة بيطلب مني بما
+
+816
+01:07:06,120 --> 01:07:12,360
+إنّه في عندي strict and
+
+817
+01:07:12,360 --> 01:07:17,040
+complicated
+
+818
+01:07:17,040 --> 01:07:22,370
+model، فعلياً الـ Naive Bayesian زي ما إحنا شفنا في
+
+819
+01:07:22,370 --> 01:07:30,490
+حسابه سهل، نعم، لكنه مش سهل إنّي أطبقه في كل مكان، طبعاً
+
+820
+01:07:30,490 --> 01:07:35,690
+ما هي المطلوب إن أنا فعلياً، وين أنا بدي أروح أطبق
+
+821
+01:07:35,690 --> 01:07:38,330
+الـ Naive Bayesian؟ فعلياً أنا بقدر أروح أستخدمه أو
+
+822
+01:07:38,330 --> 01:07:40,990
+ممكن اشتغل كويس لما يكون الـ Naive Assumption
+
+823
+01:07:40,990 --> 01:07:46,240
+فعلياً موجودة مع الـ data، يعني بين قوسين أنا شبه
+
+824
+01:07:46,240 --> 01:07:49,320
+متأكد إن الـ attributes اللي عندي كلها independent
+
+825
+01:07:49,320 --> 01:07:53,740
+attributes، لكن أنت الكلام متأكد منه ولا مش متأكد
+
+826
+01:07:53,740 --> 01:07:57,840
+منه؟ ما بعرفش، ما بيعرفش، الحل كيف بتتأكد من الـ
+
+827
+01:07:57,840 --> 01:08:00,740
+dependency من الـ attributes؟ بدك ترجع للـ data
+
+828
+01:08:00,740 --> 01:08:03,940
+preparation وتفحص الـ correlation ما بين الـ
+
+829
+01:08:03,940 --> 01:08:07,600
+attributes، وزي ما شفنا في عندنا الـ chi-square، و
+
+830
+01:08:07,600 --> 01:08:12,230
+في عندنا إيش كمان؟ الـ Pearson coefficient، إلى
+
+831
+01:08:12,230 --> 01:08:16,010
+آخره هو، بناءً على هيك أنت بتصير تدور على تفهم الـ
+
+832
+01:08:16,010 --> 01:08:19,310
+data set أكثر، very well separated categories، لما
+
+833
+01:08:19,310 --> 01:08:22,350
+يكون الـ categories اللي عنده فعلياً finite، و
+
+834
+01:08:22,350 --> 01:08:26,130
+مفصلين عن بعض، مافيش بينهم يعني، بين قوسين الـ data
+
+835
+01:08:26,130 --> 01:08:29,830
+set بتفرج بشكل كويس، وإحنا لاحظنا في المثال السابق
+
+836
+01:08:29,830 --> 01:08:33,070
+إنّه فعلياً عمل misclassification للـ point اللي
+
+837
+01:08:33,070 --> 01:08:36,870
+موجودة عندها، very high dimensional data، لما تكون
+
+838
+01:08:36,870 --> 01:08:41,870
+الـ data تبعتي عالية جداً، أو فيها عدد كبير من الـ
+
+839
+01:08:41,870 --> 01:08:45,630
+attributes، ممكن أنا أشتغل، آخر شغلة في محاضرتنا هي
+
+840
+01:08:45,630
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/cUQb5hESOvo_postprocess.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/cUQb5hESOvo_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..f0fdebdfd769d90d1cdf700cefed6bdf1bb63725
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/cUQb5hESOvo_postprocess.srt
@@ -0,0 +1,3504 @@
+1
+00:00:05,030 --> 00:00:08,110
+أعوذ بالله السلام عليهم باسم الله الرحمن الرحيم
+
+2
+00:00:08,110 --> 00:00:11,910
+الحمد لله والصلاة والسلام على رسول الله أهلا وسهلا
+
+3
+00:00:11,910 --> 00:00:15,150
+فيكم او ناسأل الله لكم و لنا السلام دائما و لجميع
+
+4
+00:00:15,150 --> 00:00:18,710
+المسلمين و ان شاء الله بتزولها الغمة و بنلقاكم من
+
+5
+00:00:18,710 --> 00:00:22,220
+جديداللي اليوم هنستقنف مع بعض ان شاء الله تعالى
+
+6
+00:00:22,220 --> 00:00:27,400
+المحاضرات المصورة لموضوع ال data mining ومن ثم
+
+7
+00:00:27,400 --> 00:00:31,100
+هنعمل review سريعة لو احنا وقفنا .. كنا بدينا في
+
+8
+00:00:31,100 --> 00:00:33,800
+chapter data mining .. data mining chapter تلاتة
+
+9
+00:00:33,800 --> 00:00:36,760
+في ال classification وقلنا ال classification هي
+
+10
+00:00:36,760 --> 00:00:40,600
+عبارة عن classical task تقليدية او المهمة
+
+11
+00:00:40,600 --> 00:00:43,680
+التقليدية في ال machine learning هدفها ان انا
+
+12
+00:00:43,680 --> 00:00:49,160
+فعليا اعمل prediction لdiscrete او لنومينال value
+
+13
+00:00:49,160 --> 00:00:52,240
+اللي حسمناها ال categorial value و لما حاولنا نعرف
+
+14
+00:00:52,240 --> 00:00:55,240
+ال classification مع بعض كنتوا فاكرين كنا بنقول ان
+
+15
+00:00:55,240 --> 00:00:59,320
+ال classification هي عبارة عن عملية لتحديد عضوية
+
+16
+00:00:59,320 --> 00:01:06,530
+العناصر إلى مجموعات معرفة مسبقاوتكلمنا أو حطينا
+
+17
+00:01:06,530 --> 00:01:09,770
+الرسم هاي على السريع وقلنا انه هذه هي بتمثل ال
+
+18
+00:01:09,770 --> 00:01:13,230
+model تبع ال classification انه انا بزود ال raw
+
+19
+00:01:13,230 --> 00:01:16,390
+data بحدد ال algorithm ال algorithm بيبني model
+
+20
+00:01:16,390 --> 00:01:19,110
+وال model بعد هيك المفروض يكون قادر على ال
+
+21
+00:01:19,110 --> 00:01:25,180
+prediction بشكل صحيح وبالتاليالـ classification هي
+
+22
+00:01:25,180 --> 00:01:28,920
+عبارة عن تقنية يستخدم في موضوع ال prediction
+
+23
+00:01:28,920 --> 00:01:34,080
+للممبرشب لعضوية العناصر المجموعة واتكلمنا انه
+
+24
+00:01:34,080 --> 00:01:37,620
+فعليا في ال classification task انا فيه عندي two
+
+25
+00:01:37,620 --> 00:01:40,300
+steps اي classification task عشان انجزها انا فيه
+
+26
+00:01:40,300 --> 00:01:43,460
+عندي two steps الأولى ال construction للموديل
+
+27
+00:01:43,460 --> 00:01:47,160
+ابناء الموديل بحيث انه انا احاول من خلال الخطوات
+
+28
+00:01:47,160 --> 00:01:53,090
+هذه اتعرف علىعلاقة الـ attribute مع ال class اتعرف
+
+29
+00:01:53,090 --> 00:01:55,490
+على علاقة ال attribute بال class وهذه بيسميناها
+
+30
+00:01:55,490 --> 00:01:58,890
+مرحلة لل training واللي دائما باخد جزء من ال data
+
+31
+00:01:58,890 --> 00:02:02,450
+set اللي بيسميها ال training set وشوفنا مثالها ده
+
+32
+00:02:02,450 --> 00:02:05,410
+سابقا اللحظة التانية او المحل الخطوة التانية اللي
+
+33
+00:02:05,410 --> 00:02:08,890
+هي ال model usage استخدامه بحيث انه انا اوجد ال
+
+34
+00:02:08,890 --> 00:02:13,090
+label او ال target class ل data set او عفوا ل
+
+35
+00:02:13,090 --> 00:02:18,970
+sample set موجودة عندى مسبقاوقلنا مهم جدا ان ال
+
+36
+00:02:18,970 --> 00:02:21,450
+model او ال classification model تبعي يتمتع بال
+
+37
+00:02:21,450 --> 00:02:24,790
+accuracy بالدقة بال speed سرعة ال computation
+
+38
+00:02:24,790 --> 00:02:28,110
+الموجودة robustness ال robustness اللى مبسوط فيها
+
+39
+00:02:28,110 --> 00:02:33,710
+اللى مجددش قدرة ال classifier هذا علىانه يتعامل او
+
+40
+00:02:33,710 --> 00:02:36,950
+يقدر يديني اكيرية prediction لما تكون ال data
+
+41
+00:02:36,950 --> 00:02:39,370
+بتحتوي على noise او missing data اتكلمنا عن
+
+42
+00:02:39,370 --> 00:02:42,830
+scalability و ال interpretability لل data set او
+
+43
+00:02:42,830 --> 00:02:46,910
+عفوا لل classifier و بيقولنا هذه مجموعة من ال
+
+44
+00:02:46,910 --> 00:02:50,050
+algorithms الموجودة و كنا المحاضرة الماضية هنا مع
+
+45
+00:02:50,050 --> 00:02:53,850
+بعض في اخر محاضرة ال canary's neighbor طبعا لو انا
+
+46
+00:02:53,850 --> 00:02:57,880
+سألت الآن سؤال و المفروض منك انت هيك تاخد لحظةجبل
+
+47
+00:02:57,880 --> 00:03:02,460
+ما انت تجاوبني، على إيش كان الـk-nearest neighbor
+
+48
+00:03:02,460 --> 00:03:08,700
+بيعتمد؟ المفروض الآن انت تبدأ تفكر في الإجابة الـk
+
+49
+00:03:08,700 --> 00:03:11,760
+-nearest neighbor بيعتمد على تصنيف العناصر تبعا
+
+50
+00:03:11,760 --> 00:03:17,360
+للنقاط المجاورة له وقولنا هذا هو عن واحد من
+
+51
+00:03:17,360 --> 00:03:20,530
+الـinstance basedفاكرين معايا ايش هو؟ انا كنا
+
+52
+00:03:20,530 --> 00:03:23,850
+بنتكلم ايش هو؟ Instance Based Instance Based يعني
+
+53
+00:03:23,850 --> 00:03:28,250
+بيعتمد على ال data set بدون بناء model بيعتمد على
+
+54
+00:03:28,250 --> 00:03:33,050
+ال data set بدون بناء ال models الموجودة وبالتالي
+
+55
+00:03:33,050 --> 00:03:38,230
+مافيش عندي اي model ولا بيعتمد فقط على العمل في ال
+
+56
+00:03:38,230 --> 00:03:41,650
+memory يعني بين ال جسيم ال computation وهذا بيديني
+
+57
+00:03:41,650 --> 00:03:46,580
+دائماالـ Result تبعته بناءً على ال majority تبعت
+
+58
+00:03:46,580 --> 00:03:49,600
+للجيران اللي موجود عينيه هان وقلنا بال K إنه أنا
+
+59
+00:03:49,600 --> 00:03:53,440
+لازم أحدد عدل العناصر اللي موجودة عينيهان ومرينا
+
+60
+00:03:53,440 --> 00:03:57,600
+بشكل سريع وقلنا كيف بحسب التشابه أو بحسب القرب أو
+
+61
+00:03:57,600 --> 00:04:00,680
+البعد ما بين النقاط أو ال objects وقلنا بيعتمد على
+
+62
+00:04:00,680 --> 00:04:03,740
+شغلة بنسميها similarity function و ال similarity
+
+63
+00:04:03,740 --> 00:04:06,620
+function هي لما تكون عندي أرقام معناته أنا بتكلم
+
+64
+00:04:06,620 --> 00:04:09,180
+على Euclidean distance أو Manhattan distance أو
+
+65
+00:04:09,180 --> 00:04:12,750
+غيرها من الشغلات هي وشوفنا المعادلاتمع بعضنا
+
+66
+00:04:12,750 --> 00:04:17,110
+وفرقنا بينهم وبين العناصر اللي موجودة ايش بيتطلب
+
+67
+00:04:17,110 --> 00:04:19,510
+من ال kennery snippet حسب ما شرحنا المحاضرة
+
+68
+00:04:19,510 --> 00:04:23,610
+الأخيرة كان بيتطلب مني ان احدد ال K و هي قولنا عدد
+
+69
+00:04:23,610 --> 00:04:26,910
+الجيران اللي انا بدي اعمل بينهم voting يعني لو
+
+70
+00:04:26,910 --> 00:04:30,150
+قولنا انا والله بدي اصنف الجار هذا او بدي اصنف ال
+
+71
+00:04:30,150 --> 00:04:32,330
+object الجديدة بناء على العناصر اللي موجودة
+
+72
+00:04:32,330 --> 00:04:36,210
+وبالتالي انا قاعد بقى اتكلم انه انا في عندى فعليا
+
+73
+00:04:37,240 --> 00:04:41,100
+عشر جيران حسب أغلبيتهم الأغلبية طبعا بتكلم هنا على
+
+74
+00:04:41,100 --> 00:04:45,880
+ستة الست إيش بتصنفه بروح بصنفهم تبع للست اللي
+
+75
+00:04:45,880 --> 00:04:50,720
+موجودين عندى بدي أحدد ال distance method اللي بدي
+
+76
+00:04:50,720 --> 00:04:53,940
+أستخدمها ك metric وبالتالي أنا بعد ما حددت ال K
+
+77
+00:04:53,940 --> 00:04:58,240
+بحسب ال distance بين ال sample اللي موجودة عندى
+
+78
+00:04:58,240 --> 00:05:01,300
+وكل ال data set اللي أو ال training set اللي
+
+79
+00:05:01,300 --> 00:05:04,580
+موجودة عندى هنا ممكن اعتمد ال Euclidean او ال
+
+80
+00:05:04,580 --> 00:05:08,410
+Manhattanبرتب البيانات وقولنا هذي موضوع الترتيب مش
+
+81
+00:05:08,410 --> 00:05:11,650
+مهم إلا غير لما تكون ال data set كبيرة بصير عليه
+
+82
+00:05:11,650 --> 00:05:16,150
+حصر عليه بسهل عليه أن أحصر العناصر الأقصر ال
+
+83
+00:05:16,150 --> 00:05:21,810
+kenyerist مجموعة العناصر العشرة أصحاب أقصر مسافة
+
+84
+00:05:21,810 --> 00:05:25,130
+ما بين ال sample الموجودين عندها بعمل بينهم voting
+
+85
+00:05:25,130 --> 00:05:28,300
+بحيث أن احدد المجارتينوشوفنا ال example الموجود
+
+86
+00:05:28,300 --> 00:05:33,040
+هنا وكيف اشتغلنا على ال Eclidean واذا بتتذكروا
+
+87
+00:05:33,040 --> 00:05:36,220
+المفروض ان المعادلة تبعتنا هذه حسب ال Eclidean
+
+88
+00:05:36,220 --> 00:05:40,420
+distance فيها الجدر التربيعي وطبعا لجماعة الخير
+
+89
+00:05:40,420 --> 00:05:43,440
+لما احنا بنتكلم الجدر التربيعي والجدر التربيعي
+
+90
+00:05:43,440 --> 00:05:48,400
+موجود في كل المعادلات انا من باب المقارنة ممكن انا
+
+91
+00:05:48,400 --> 00:05:54,050
+استغني عنه لأنه الكبير تحت الجدرأو أكبر عنصر تحت
+
+92
+00:05:54,050 --> 00:05:58,490
+الجذر هيظل أكبر عنصر خارج .. برا الجذر لما أنا ..
+
+93
+00:05:58,490 --> 00:06:03,670
+يعني مثلا جذر ال 16، جذر ال 25، جذر ال 13، جذر
+
+94
+00:06:03,670 --> 00:06:06,850
+التسعة، أصغر واحدة فيهم جذر التسعة، اللي هي تلاتة
+
+95
+00:06:08,510 --> 00:06:12,350
+هو أكبر واحدة فيهم جذر الخمسة وعشرين خمسة كذلك
+
+96
+00:06:12,350 --> 00:06:15,570
+الخمسة وعشرين هي أكبر value والتسعة هي أصغر value
+
+97
+00:06:15,570 --> 00:06:18,490
+موجودة عندي وبالتالي كنت أنا بقول انه ممكن من
+
+98
+00:06:18,490 --> 00:06:21,550
+ناحية calculation على السريع عشان أنا أخلص من
+
+99
+00:06:21,550 --> 00:06:26,930
+المقارنات السريعة ممكن أستغني عن الجذر التربيعي
+
+100
+00:06:26,930 --> 00:06:32,470
+وابقى ما زلت بتكلم على ال Eclidean distance وشوفنا
+
+101
+00:06:32,470 --> 00:06:36,150
+مع بعض ال example وانتهينا من ال example هذا قلنا
+
+102
+00:06:36,150 --> 00:06:40,660
+في حالةان والله كانت ال data set اللي موجودة عندي
+
+103
+00:06:40,660 --> 00:06:44,960
+بتحتوي على nominal attributes او categorial
+
+104
+00:06:44,960 --> 00:06:48,300
+attributes قلنا هان بيلزمني ان انا فعليا اشوف
+
+105
+00:06:48,300 --> 00:06:52,260
+طريقة لان مابقدرش احسب مسافة ما بين عنصرين لو
+
+106
+00:06:52,260 --> 00:06:57,080
+اجينا اقول انا والله مثلا انا male و female في ال
+
+107
+00:06:57,080 --> 00:07:02,760
+gender attribute ال distance بينهم جداش مش هقدر
+
+108
+00:07:02,760 --> 00:07:08,840
+اتكلم عليهم وبالتالي الآن لو اجينا اقول انا احمدو
+
+109
+00:07:08,840 --> 00:07:14,120
+أحمد مع ال E اللي في الوسط هنا جدّيش ال distance
+
+110
+00:07:14,120 --> 00:07:17,120
+بينهم طبعا إحنا متفقين إن الأسماء مابتدخلش في
+
+111
+00:07:17,120 --> 00:07:20,200
+الحسبة اللي عندي لأنه دائما useless وبالتالي أنا
+
+112
+00:07:20,200 --> 00:07:23,900
+خلال ال preparation بقى أشيلها لكن في الآخر لما
+
+113
+00:07:23,900 --> 00:07:26,580
+بكون أنا في عندي string أو text أو زي ما سمناها
+
+114
+00:07:26,580 --> 00:07:29,520
+لغة ال data mining categorical data أو nominal
+
+115
+00:07:29,520 --> 00:07:33,170
+dataكيف بدي أحسبهم أو بدي أحسب المقارنة بينهم؟ هذا
+
+116
+00:07:33,170 --> 00:07:35,970
+الكلام صعب في الـEuclidean distance و المنهاتين
+
+117
+00:07:35,970 --> 00:07:40,510
+فلو في الكنياري سنيبر فبتصير أنا أشتغل هل فعليا ال
+
+118
+00:07:40,510 --> 00:07:43,730
+term هدولة match إذا كانت ال two terms match
+
+119
+00:07:43,730 --> 00:07:47,050
+معناته بحطلهم صفر إذا ال two terms مختلفات يعني
+
+120
+00:07:47,050 --> 00:07:50,590
+أبعد ما يمكن عن بعض أو بعاد عن بعض بحط الفرق بينهم
+
+121
+00:07:50,590 --> 00:07:56,170
+واحد وطبعا حكينا بعد هي كده عن مهمية ال scaling في
+
+122
+00:07:56,170 --> 00:08:01,120
+موضوع الكنياري سنيبروقلنا من أهمه .. أهم ميزاته
+
+123
+00:08:01,120 --> 00:08:04,160
+robustness باتجاه الـ noisy data و ال
+
+124
+00:08:04,160 --> 00:08:08,420
+effectiveness في موضوع مرحلة ال training ال
+
+125
+00:08:08,420 --> 00:08:13,100
+disadvantages تحديد ال K .. أي K هي الأكتر مناسبة
+
+126
+00:08:13,100 --> 00:08:17,740
+للموضوع اللي أنا بأشغل عليه ال distanceمفهوم not
+
+127
+00:08:17,740 --> 00:08:20,380
+clear خصوصا لما ظهرت عندي ال categorical data و
+
+128
+00:08:20,380 --> 00:08:23,940
+هذه موجودة عندها ال computation cost عالية تخيل ال
+
+129
+00:08:23,940 --> 00:08:27,040
+data set فيها مائة الف record وبالتالي لما انا بدي
+
+130
+00:08:27,040 --> 00:08:29,680
+اعمل evaluation او عفوا بدي اعمل prediction ل
+
+131
+00:08:29,680 --> 00:08:34,520
+class ل one example معناته بيدروح احسبمئة ألف
+
+132
+00:08:34,520 --> 00:08:38,180
+distance طيب لو كانت في عندي في المقابل في عندي
+
+133
+00:08:38,180 --> 00:08:42,960
+عشرة او مية بدي اعملهم testing مية في مائة ألف
+
+134
+00:08:42,960 --> 00:08:46,440
+معناته احنا صارنا بتكلمها عشرة مليون تقريبا
+
+135
+00:08:46,440 --> 00:08:51,160
+computation وبالتالي العملية شوية هتاخد مني وجهة
+
+136
+00:08:51,160 --> 00:08:55,540
+طويلة الان لما شوفنا ال code أهم في ال code السادق
+
+137
+00:08:55,540 --> 00:09:00,890
+اذا كنا بتتذكروا معانا بدي اعمل importأخذت من أسكي
+
+138
+00:09:00,890 --> 00:09:08,330
+لير نيبرز أسكي لير نيبرز نيبرز أسكي لير نيبرز
+
+139
+00:09:08,330 --> 00:09:11,520
+نيبرز نيبرزتبعت ال K nearest neighbor و اتديته ال
+
+140
+00:09:11,520 --> 00:09:15,420
+K تبعتي equal خمسة و هنا نتذكر قلنا دائما ال X
+
+141
+00:09:15,420 --> 00:09:18,680
+تبعتك او ال K تبعتك لازم تكون فيها لازم تكون large
+
+142
+00:09:18,680 --> 00:09:22,660
+enough و تكون دائما تقدر تديني ال predictions او
+
+143
+00:09:22,660 --> 00:09:25,780
+تعمل ال voting الصح لأنه مش معقول مثلا تكون في
+
+144
+00:09:25,780 --> 00:09:28,640
+عندي two binary او two labels و اروح اقول والله
+
+145
+00:09:28,640 --> 00:09:32,510
+بدي اخد مثلا اربعة او ستةستة يعني الاحتمال انه
+
+146
+00:09:32,510 --> 00:09:35,270
+ممكن يكون خمسة خمسة على الاقل انا بحتاج اد في حالة
+
+147
+00:09:35,270 --> 00:09:38,510
+ال binary classification عشان اقدر انه ال voting
+
+148
+00:09:38,510 --> 00:09:42,710
+بينحاز لواحد من ال classes اللي موجودة عندهم و
+
+149
+00:09:42,710 --> 00:09:46,950
+اتذكر تماما و اتذكروا جميعا انه انا هلأ لما اتكلمت
+
+150
+00:09:46,950 --> 00:09:50,050
+على ال kenya restaurantneighbors و اديته ال test
+
+151
+00:09:50,050 --> 00:09:53,110
+attribute test sample تبعتي اللي انا بنيتها هان و
+
+152
+00:09:53,110 --> 00:09:56,710
+مع ال key تبعتي ال equal خمسة فعليا راح اداني من
+
+153
+00:09:56,710 --> 00:09:59,990
+هم العناصر هدول و جداش ال distances اللي موجودة
+
+154
+00:09:59,990 --> 00:10:03,890
+بينهم وضل علي انا ان ارجع على ال data set اجيب ال
+
+155
+00:10:03,890 --> 00:10:07,830
+label تبعتي العناصر هدول و اعمل بينهم voting كان
+
+156
+00:10:07,830 --> 00:10:11,530
+هذا .. لحد احنا نهينا محاضرتنا السادقة عند ال
+
+157
+00:10:11,530 --> 00:10:16,340
+example هذا و بتمنىان يكون انجحت على عجالة ان
+
+158
+00:10:16,340 --> 00:10:22,180
+اذكرك بعد انقطاع اسبوع من الدراسة بما سبق في موضوع
+
+159
+00:10:22,180 --> 00:10:26,760
+ال classificationلكن تعالى نشوف قبل ما ننتقل
+
+160
+00:10:26,760 --> 00:10:29,320
+للموضوع الجديد تعالى نشوف هذا المثال المفروض ان
+
+161
+00:10:29,320 --> 00:10:31,700
+هذا المثال مش موجود معاكوا في ال slides فانت
+
+162
+00:10:31,700 --> 00:10:34,100
+المفروض انت المفروض ال slides معاكوا و بتبدوا
+
+163
+00:10:34,100 --> 00:10:38,840
+تراجعوا عليها باستمرار لو انا نظرتلك لل attributes
+
+164
+00:10:38,840 --> 00:10:42,800
+او لل data set اللي موجودة عندهان وجاوب معايا او
+
+165
+00:10:42,800 --> 00:10:46,240
+جاوبوا معايا على السؤال التالي ايش ال data type
+
+166
+00:10:46,240 --> 00:10:50,840
+تبع ال outlook المفروض
+
+167
+00:10:50,840 --> 00:10:52,360
+nominal صحيح
+
+168
+00:10:55,100 --> 00:11:00,320
+الـ data type تبع ال temperature numeric
+
+169
+00:11:00,320 --> 00:11:03,800
+وإن
+
+170
+00:11:03,800 --> 00:11:10,700
+قلت انت ratio او ال interval كلامك صحيح ك interval
+
+171
+00:11:10,700 --> 00:11:15,300
+مش ك ratio nominal nominal ال golf play أو play
+
+172
+00:11:15,300 --> 00:11:18,820
+golf binary classification يعني عندي two labels
+
+173
+00:11:18,820 --> 00:11:23,160
+yes و no حسب ال data set اللي موجودة عندي و
+
+174
+00:11:23,160 --> 00:11:29,460
+المطلوب ان اناأروح أجيب ال class تبعت ال instance
+
+175
+00:11:29,460 --> 00:11:36,100
+اللي فيها ال sunny وهذه طبعا في ال outlook ال
+
+176
+00:11:36,100 --> 00:11:39,800
+temperature بعد
+
+177
+00:11:39,800 --> 00:11:44,440
+هي كان ال humidity و ال windy
+
+178
+00:11:47,670 --> 00:11:51,910
+الان مع الـ K equal واحد والـ K equal تلاتة والـ K
+
+179
+00:11:51,910 --> 00:11:56,670
+equal خمسة طبعا ملاحظين بالمثال الآن في الأمثلة
+
+180
+00:11:56,670 --> 00:11:59,610
+السابقة اللي اشتغلنا عليها كانت فقط عند الـ
+
+181
+00:11:59,610 --> 00:12:03,250
+numeric data طب الآن لأ صار في عندي nominal وفي
+
+182
+00:12:03,250 --> 00:12:06,840
+عندي numericطبعا ليش المثال هذا أنا تعمدت أجيبه
+
+183
+00:12:06,840 --> 00:12:09,840
+اليوم تعمدت أجيبه عشان أقولك في الحالة اللي زي هذه
+
+184
+00:12:09,840 --> 00:12:13,520
+أنا هتكون في عندي dominant attribute يعني في عندي
+
+185
+00:12:13,520 --> 00:12:17,800
+attribute هو المسيطر هو اللي هياخد ال data set أو
+
+186
+00:12:17,800 --> 00:12:20,920
+ال classification process بمنحاه يعني بينجو سين هو
+
+187
+00:12:20,920 --> 00:12:25,040
+هيكون صاحب القرار تخيل خلينا نشتغل مع بعض من باب
+
+188
+00:12:25,040 --> 00:12:29,450
+التسهيل نشتغل على موضوع المنهات in distanceحسب الـ
+
+189
+00:12:29,450 --> 00:12:31,610
+Manhattan distance يعني انا بدي استخدم الـ
+
+190
+00:12:31,610 --> 00:12:34,170
+absolute value هو بيقول في ال Manhattan ال
+
+191
+00:12:34,170 --> 00:12:44,510
+summation لل X ناقص X واحد X اتنين و I اعفوا I
+
+192
+00:12:44,510 --> 00:12:50,490
+واحد و I اتنين و I equal واحد مع كل ال attributes
+
+193
+00:12:50,490 --> 00:12:53,550
+اللي موجودة عندها هذا في حالة ال numerical طب في
+
+194
+00:12:53,550 --> 00:12:58,760
+حالة ال ..الـ nominal معناته انا بدي استخدم صفر في
+
+195
+00:12:58,760 --> 00:13:02,760
+حالة التساوي الواحد في حالة الاختلاف وبالتالي
+
+196
+00:13:02,760 --> 00:13:07,080
+بتصير المعادلة اللي عندي هان الان sunny و sunny
+
+197
+00:13:07,080 --> 00:13:17,740
+الفرق بينهم zero زائد ال absolute value 45 ناقص 18
+
+198
+00:13:17,740 --> 00:13:27,830
+زائد high و normal الاختلاف واحدزائد true و false
+
+199
+00:13:27,830 --> 00:13:32,330
+اختلاف بينهم واحد معناته هي القيمة اللي موجودة
+
+200
+00:13:32,330 --> 00:13:39,150
+عندى اللي بعدها sunny zero زائد تلاتة و أربعين
+
+201
+00:13:39,150 --> 00:13:46,890
+ناقص تمانتعش زائد high واحدة مختلفة true zero و
+
+202
+00:13:46,890 --> 00:13:50,710
+هكذا طبعا حنا بنتكلم احنا عندى هنا سبعة و عشرين
+
+203
+00:13:50,710 --> 00:13:54,290
+سبعة و عشرين و اتنين هنا تسعة و عشرين هنا في عندى
+
+204
+00:14:20,610 --> 00:14:24,670
+ملاحظين دائما ال attribute الخاص بال temperature
+
+205
+00:14:24,670 --> 00:14:25,050
+هنا
+
+206
+00:14:27,900 --> 00:14:31,880
+هيكون هو الـ dominant attribute لأنه فعليا المساء
+
+207
+00:14:31,880 --> 00:14:35,480
+هو اللي بيقرر وزنه او ال scale تبعته ال weight
+
+208
+00:14:35,480 --> 00:14:38,800
+تبعته في موضوع ال computation تبعتي بتفرق كبير
+
+209
+00:14:38,800 --> 00:14:43,960
+كتير عن العناصر التانية او ال attributes التانية
+
+210
+00:14:43,960 --> 00:14:48,040
+اللي موجودة طيب بدنا نكمل ال computation هنكمل ال
+
+211
+00:14:48,040 --> 00:14:51,420
+computation هاي ال computation بالكامل موجودة الآن
+
+212
+00:14:51,420 --> 00:14:53,040
+قدامي ممتاز
+
+213
+00:15:00,250 --> 00:15:02,470
+طبعا مافيش مشكلة .. مش فارق .. احنا اتفقنا سابق ان
+
+214
+00:15:02,470 --> 00:15:05,530
+جربنا بال inclusion جربنا بالمنهاتين وماكانش كتير
+
+215
+00:15:05,530 --> 00:15:09,010
+الفرق ما بينهم ..الان تسعة و عشرين .. ستة و عشرين
+
+216
+00:15:09,010 --> 00:15:11,970
+.. ستة و عشرين .. واحد و عشرين .. الى اخره .. بدي
+
+217
+00:15:11,970 --> 00:15:15,350
+حسب ال Kenya nearest neighbor ..الان يا جماعة
+
+218
+00:15:15,350 --> 00:15:20,190
+الخير بدك تنتبه لشغل مهم جدا .. بالمثال هذا واضح
+
+219
+00:15:20,190 --> 00:15:23,090
+ان في عندي high distance اعطتني اتنين
+
+220
+00:15:26,920 --> 00:15:31,440
+تنين وهي كمان واحدة تنين لما أنا بدي أعمل sorting
+
+221
+00:15:31,440 --> 00:15:34,600
+تبع لل distance حسب الخطوة السابقة اللي حكينا فيها
+
+222
+00:15:34,600 --> 00:15:38,860
+أول واحدة لإنه هذه .. لما يقولوا sort لل data set
+
+223
+00:15:38,860 --> 00:15:44,660
+تبع لل distance اللي صارت التنين هذه هتظهر أول
+
+224
+00:15:44,660 --> 00:15:49,780
+واحدة ليش؟ لأنه الآن لما بتتساوى القيم بصير ظهور
+
+225
+00:15:49,780 --> 00:15:52,800
+تبع ال value هو الأول هو اللي بياخد في الترتيب
+
+226
+00:15:53,670 --> 00:15:56,810
+الظهور تبع ال values هي اللي بتاخد في الترتيب
+
+227
+00:15:56,810 --> 00:16:00,570
+وبالتالي هذي هتكون أول واحدة فوق الآن لو انا و ال
+
+228
+00:16:00,570 --> 00:16:03,390
+key and nearest neighbor equal one ايش ال key
+
+229
+00:16:03,390 --> 00:16:09,510
+تبعتي او ال label تبعتي true وبالتالي هتكون عندي
+
+230
+00:16:09,510 --> 00:16:15,170
+yes طيب في حالة ان ال key تبعتي equal تلاتة تلاتة
+
+231
+00:16:15,170 --> 00:16:20,210
+هي واحدة تنتين تلاتة معناته هي واحدة هي تنتين هي
+
+232
+00:16:20,210 --> 00:16:26,420
+تلاتةالـ majority بينهم تنتين yes و واحدة no يعني
+
+233
+00:16:26,420 --> 00:16:33,080
+بنتكلم على 66% yes و 33% no وبالتالي ال majority
+
+234
+00:16:33,080 --> 00:16:39,420
+تبعتي ل playing golf equal yes تمام الخطوة الأخيرة
+
+235
+00:16:39,420 --> 00:16:44,540
+لو أنا قلتله K equal خمسة K equal خمسة معناته بده
+
+236
+00:16:44,540 --> 00:16:51,320
+يدور على ال shortest distances أي واحدة تنتينهذه
+
+237
+00:16:51,320 --> 00:17:00,640
+تلاتة وهذه أربعة وهذه خمسة ال label سبعتهم واحدة
+
+238
+00:17:00,640 --> 00:17:07,980
+تنتين تلاتة أربعة وهذه خمسةالآن بدي أعمل voting ما
+
+239
+00:17:07,980 --> 00:17:11,080
+بين الخمسة اللي موجودة عندي واحدة، اتنين، تلاتة،
+
+240
+00:17:11,080 --> 00:17:14,960
+أربعة yes تمانين في المية yes وعشرين في المية no
+
+241
+00:17:14,960 --> 00:17:19,480
+وبالتالي لما تكون ال key تبعتي equal five معناته
+
+242
+00:17:19,480 --> 00:17:22,400
+برضه ال golf تبعتي أو ال playing golf يعني فرصة
+
+243
+00:17:22,400 --> 00:17:25,580
+أني ألعب ال golf في الظروف المناخية اللي موجودة في
+
+244
+00:17:25,580 --> 00:17:27,920
+ال data set اللي موجودة عندي فوجها اللي أشارناها
+
+245
+00:17:27,920 --> 00:17:30,480
+yes تمام
+
+246
+00:17:32,780 --> 00:17:38,280
+طيب سؤال ونفرض تقدروا تجاوبه عليه بما انه هذا ال
+
+247
+00:17:38,280 --> 00:17:41,400
+attribute هو ال dominant attribute يعني هو صاحب
+
+248
+00:17:41,400 --> 00:17:45,500
+القرار في موضوع ال classification درجة الحرارة في
+
+249
+00:17:45,500 --> 00:17:49,120
+حين انت لو انت تخيلنا ان لو كان الجو ماطر ممكن
+
+250
+00:17:49,120 --> 00:17:54,140
+يأثر في لعبة ال golf ولا مش هيأثر؟ بتعرفوش ايش
+
+251
+00:17:54,140 --> 00:17:58,710
+يعني لعبة golf؟ممكن تشوفوا اليوتيوب how to play
+
+252
+00:17:58,710 --> 00:18:01,770
+golf وبيعلموكوا إياه و تتفرجوا عليها في الآخر هي
+
+253
+00:18:01,770 --> 00:18:06,370
+رياضة بالعصب و بيضربوا الكورة عشان يسقطها في حفرة
+
+254
+00:18:06,370 --> 00:18:10,750
+الآن بما أن هذا ال dominant attribute ايش الحلول
+
+255
+00:18:10,750 --> 00:18:15,690
+اللي قدامي؟ وهل لو أنا غيرت ممكن احصل على
+
+256
+00:18:15,690 --> 00:18:20,590
+different result؟ اه ممكن اول حل موجود قدامي تماما
+
+257
+00:18:20,590 --> 00:18:27,330
+زي ما بتبادر لذهنك الآن ان اعمل scalingصحيح ممكن
+
+258
+00:18:27,330 --> 00:18:31,710
+انا اعمل scaling لو صارت هذه اربعة و نص اربعة و
+
+259
+00:18:31,710 --> 00:18:36,110
+تلاتة من عشرة اربعة point واحد تلاتة point ستة
+
+260
+00:18:36,110 --> 00:18:40,770
+واحد point تمانية واحد point سبعة اتنين point zero
+
+261
+00:18:40,770 --> 00:18:45,410
+تلاتة point تلاتة واحد point ستة تلاتة point اتنين
+
+262
+00:18:45,410 --> 00:18:49,850
+اتنين point تلاتة اتنين point اربعة اربعة point
+
+263
+00:18:49,850 --> 00:18:54,730
+zero تلاتة point اتنين و طبيعتي الحال هتصير واحد
+
+264
+00:18:54,730 --> 00:18:55,070
+point
+
+265
+00:18:57,730 --> 00:19:00,870
+8 ايش اللي صار عندى بعد ال scaling طبعا اعمل ال
+
+266
+00:19:00,870 --> 00:19:04,870
+ratio جسمتها على عشرة او ضربت في عشر او سالب واحد
+
+267
+00:19:04,870 --> 00:19:10,170
+شو بتتوقع تصير ال distance هتقل بين جثين هتصير فيه
+
+268
+00:19:10,170 --> 00:19:16,310
+عندى انا اربعة و نص ناقص واحد و تمانيةاللي هي بين
+
+269
+00:19:16,310 --> 00:19:21,510
+جثين 2.9 لاحظوا أن 2.9 صارت قريبة من القيم اللي
+
+270
+00:19:21,510 --> 00:19:25,970
+موجودة وإذا كمان روحت دربت في عشر أو سالب 2 ممكن
+
+271
+00:19:25,970 --> 00:19:32,650
+أقلل ال weight تبعته بتصير ال value balance تفكير
+
+272
+00:19:32,650 --> 00:19:38,110
+منطقي لكن هل فعليا يقودني للنتيجة أفضل بده تجربة
+
+273
+00:19:38,110 --> 00:19:42,650
+وعشان بناء على هيك اعتبرها assignment لك واتقارنه
+
+274
+00:19:42,650 --> 00:19:48,580
+ما بينفي حالة كانت ال ratio اعملت ratio data تمام
+
+275
+00:19:48,580 --> 00:19:55,220
+او اشتغلت على ال numeric data اللي موجودة حل
+
+276
+00:19:55,220 --> 00:20:00,960
+التاني هل في حلول تانية اه في حلول تانية استحثوا
+
+277
+00:20:00,960 --> 00:20:05,440
+ادمغاتكوا هوش الشغلات اللي كنا بنسويها مع ال data
+
+278
+00:20:05,440 --> 00:20:08,820
+الموجودة جماعة الخير انا بتكلم على درجة الحرارة
+
+279
+00:20:08,820 --> 00:20:14,970
+درجة الحرارة شو يعني عادة لما بنقول درجة الجولو
+
+280
+00:20:14,970 --> 00:20:18,010
+سألك كيف الجو اليوم يا فلان أو يا فلانة والله الجو
+
+281
+00:20:18,010 --> 00:20:23,150
+حار شوب كتير بارد ماحدش بيقوللي عشرين و تلاتة أو
+
+282
+00:20:23,150 --> 00:20:26,510
+اربعين وكذا فبالتالي ممكن لو انا .. بالضبط لو انا
+
+283
+00:20:26,510 --> 00:20:31,030
+حولتها ل categorial ممكن تفرج معايا طيب هاي حولتها
+
+284
+00:20:31,030 --> 00:20:38,650
+ل categorial شو يعني categorial؟ ان
+
+285
+00:20:38,650 --> 00:20:41,390
+انا حطيتها لفئات تبقى على ال data set اللي موجودة
+
+286
+00:20:41,390 --> 00:20:48,970
+عندىعشان بس تكونوا في الصورة من عشرين أقل أو تساوي
+
+287
+00:20:48,970 --> 00:20:55,650
+عشرين استخدمنا cool أكبر
+
+288
+00:20:55,650 --> 00:21:03,330
+من عشرين وأقل أو تساوي أربعين استخدم أقل من أربعين
+
+289
+00:21:03,330 --> 00:21:10,770
+عفوا استخدمنا mild وفوق الأكبر أو تساوي الأربعين
+
+290
+00:21:13,100 --> 00:21:18,600
+روحنا استخدمنا ال hot اتذكروا
+
+291
+00:21:18,600 --> 00:21:23,120
+ان كانت عندي hand تمانتاش درجة الحرارة في ال test
+
+292
+00:21:23,120 --> 00:21:26,820
+sample اللي موجودة عندي hand الآن وبالتالي لما انا
+
+293
+00:21:26,820 --> 00:21:30,820
+بداجي افحص درجة الحرارة اللي موجودة خمسة و أربعين
+
+294
+00:21:30,820 --> 00:21:35,940
+hot تلاتة و أربعين hot واحدة و أربعين hot ستة و
+
+295
+00:21:35,940 --> 00:21:41,060
+تلاتين mild cool cool cool mild cool
+
+296
+00:21:45,290 --> 00:21:52,930
+Mild Mild Hot Mild تمام؟
+
+297
+00:21:52,930 --> 00:21:55,950
+هذه ال data set و بينما هذه ال 18 هتكون عندي cool
+
+298
+00:21:55,950 --> 00:21:59,790
+الآن صارت كل ال data عندي categorical و بانجو سين
+
+299
+00:21:59,790 --> 00:22:04,310
+صارت كل ال attributes اللي عند نفس ال weight شو
+
+300
+00:22:04,310 --> 00:22:10,430
+ضال علي أحسب ال distanceطيب انا هسكت دقيقة هعمل
+
+301
+00:22:10,430 --> 00:22:15,270
+pause دقيقة اتركلك مجال اجيش الحسبة تبعتي استخدم
+
+302
+00:22:15,270 --> 00:22:19,050
+Manhattan ولا استخدم ال Euclidean distance لحساب
+
+303
+00:22:19,050 --> 00:22:22,690
+ال similarity ما بين العناصر اللي موجودة عندنا
+
+304
+00:22:28,290 --> 00:22:32,770
+طيب ..الان بما ان كل ال data categorial معناته صفر
+
+305
+00:22:32,770 --> 00:22:35,830
+و واحد هتصير المعادلة تبعتي و خلينا مش فارق كتير
+
+306
+00:22:35,830 --> 00:22:39,530
+معايا من هاتن او اكلوديا مش فارق كتير في الآخر انا
+
+307
+00:22:39,530 --> 00:22:45,570
+بدي اجمع أصفار و واحدات sunny و sunny zero زائد
+
+308
+00:22:45,570 --> 00:22:51,390
+hot و cool واحد انه اتفقنا في حالة التشابه صفر في
+
+309
+00:22:51,390 --> 00:22:58,750
+حالة الاختلاف واحدزائد normal و high واحد زائد
+
+310
+00:22:58,750 --> 00:23:03,690
+false و true واحد وبالتالي هذه القيمة تلاتةالـ
+
+311
+00:23:03,690 --> 00:23:09,170
+attribute اللي بعدها sunny 0 زائد hot واحد زائد
+
+312
+00:23:09,170 --> 00:23:13,950
+واحد زائد صفر وهذا يساوي اتنين و لاحظ لاحظ كل ال
+
+313
+00:23:13,950 --> 00:23:17,030
+values تبعتي بالدور حوالين ال range اللي موجود
+
+314
+00:23:17,030 --> 00:23:21,410
+عندي هان اما بين الأربعة والصفر هذه القيم اللي
+
+315
+00:23:21,410 --> 00:23:25,070
+موجودة عندي هان طبعا انا مجهز هان عشان مانجضيش
+
+316
+00:23:25,070 --> 00:23:29,190
+الوقت في الحساب هذه
+
+317
+00:23:29,190 --> 00:23:30,510
+ال computation بالكامل
+
+318
+00:23:35,230 --> 00:23:47,810
+تمام؟ shortest distance مع ال k equal واحد اتنين
+
+319
+00:23:47,810 --> 00:23:54,590
+اول اتنين هي .. لأ في عندي واحد هيها ال
+
+320
+00:23:54,590 --> 00:24:03,970
+label تبعتها no وال label هيختلفت عن السابقةفي
+
+321
+00:24:03,970 --> 00:24:07,210
+المثال السابق كانت لما الـK تبعتي equal واحد كان
+
+322
+00:24:07,210 --> 00:24:12,990
+بيقوللي ألعب تمام؟ وبالتالي لما أنا اشتغلت هاين
+
+323
+00:24:12,990 --> 00:24:18,450
+بيقوللي no هيها ليش محدش يقوللي لأن؟ ليش يا دكتور
+
+324
+00:24:18,450 --> 00:24:21,470
+مش هذه ال yes هي اللي كانت؟ لأن عندي ال sorting
+
+325
+00:24:21,470 --> 00:24:24,990
+هذا ال attribute أو عفوًا هذا الروح هياخد المرتبة
+
+326
+00:24:24,990 --> 00:24:29,550
+الأولى يعني بينجو سي لما انت بتجي ترتب خلينا نتكلم
+
+327
+00:24:29,550 --> 00:24:33,110
+بال bubble sortشو مفهوم ال bubble sort؟ بضلني
+
+328
+00:24:33,110 --> 00:24:36,590
+أقارن العنصر لما بلاقي أصغر عنصر مابدأياش أساوي
+
+329
+00:24:36,590 --> 00:24:41,210
+فيه أحركه للأعلى بضلني أقارن العنصر مع عناصر
+
+330
+00:24:41,210 --> 00:24:44,370
+الجابلة لحد ما بلاقي أصغر عنصر بصير أرفعه بهيك أنا
+
+331
+00:24:44,370 --> 00:24:50,430
+بأضمن بدور على ال minimum value بروح بحطها فوق
+
+332
+00:24:50,430 --> 00:24:54,330
+بدور على ال minimum و بعملها shift وهكذا وبالتالي
+
+333
+00:24:55,510 --> 00:24:59,750
+هذه هي أول واحدة ستحصل عليها انت مش مصدق؟ خد ال
+
+334
+00:24:59,750 --> 00:25:06,270
+data set هذه على ال Excel و اعمل لها sort تبعا لل
+
+335
+00:25:06,270 --> 00:25:09,350
+distance و ستجد ان ال attribute هذه ستكون أول
+
+336
+00:25:09,350 --> 00:25:15,430
+attribute موجود عندك تمام؟ لو ال K equal 3 هاي
+
+337
+00:25:15,430 --> 00:25:22,000
+واحد وهي واحدو هاي واحد انا عندي اربعة فهاخد اول
+
+338
+00:25:22,000 --> 00:25:27,040
+تلاتة واحد اتنين تلاتة ال majority تبعتهم yes
+
+339
+00:25:27,040 --> 00:25:32,960
+وبالتالي هتكون yes لو قلتله خمسة هضيف الواحد هذه
+
+340
+00:25:32,960 --> 00:25:37,740
+معاهم كمان و هتيجي وراهم الاتنين هذه الآن تعالى
+
+341
+00:25:37,740 --> 00:25:39,260
+نشوف ال label اللي صارت عندي هنا
+
+342
+00:25:42,540 --> 00:25:49,660
+صار في عندى 1 2 3 60% yes و 40% no وبالتالي لما
+
+343
+00:25:49,660 --> 00:25:52,980
+تكون الخمسة ال K تبعتي equal خمسة معناته المجلة
+
+344
+00:25:52,980 --> 00:25:58,180
+تبعتي بتقول yes ملاحظين معايا تأثير فعليا ال
+
+345
+00:25:58,180 --> 00:26:01,770
+processing على ال data set جداش مهم جداش مهمبتمنى
+
+346
+00:26:01,770 --> 00:26:05,610
+ان تكون هذه الموضوع اصبح اليوم يعني من بدهيات
+
+347
+00:26:05,610 --> 00:26:11,210
+لديكم ومن ثم انه احنا فعليا اصبحت غطينا كل جوانب
+
+348
+00:26:11,210 --> 00:26:14,370
+الـk nearest neighbor ان شاء الله تبارك وتعالى
+
+349
+00:26:14,370 --> 00:26:19,510
+تمام الآن هنتقل ان شاء الله تبارك وتعالى لل
+
+350
+00:26:19,510 --> 00:26:23,690
+algorithm التاني لل algorithm التاني اللي هو بيبني
+
+351
+00:26:23,690 --> 00:26:28,390
+شبه model تمام وبيعتمد على ال probabilisticالـ
+
+352
+00:26:28,390 --> 00:26:32,050
+classification هيعتمد على نظرية الاحتمالات في ال
+
+353
+00:26:32,050 --> 00:26:36,750
+classification و فهمها اللي
+
+354
+00:26:36,750 --> 00:26:41,690
+هو ال naive Bayesian algorithm او ال bias يعني
+
+355
+00:26:41,690 --> 00:26:45,790
+classification وبالتحديد ال naive bias classifier
+
+356
+00:26:45,790 --> 00:26:50,390
+طيب
+
+357
+00:26:50,390 --> 00:26:56,640
+الان احنا اتفقنا .. اتفقنا سابقاإن الكنيري سنابر
+
+358
+00:26:56,640 --> 00:27:02,340
+هو عبارة عن instance based model مصبوط يعني بيعتمد
+
+359
+00:27:02,340 --> 00:27:06,420
+دائما في كل مرة مع كل sample بروح بعمل حسبة لل
+
+360
+00:27:06,420 --> 00:27:09,440
+distance من ال sample الأولى في ال training set لل
+
+361
+00:27:09,440 --> 00:27:13,220
+sample الأخيرة تمام وبدور على ال data set اللي
+
+362
+00:27:13,220 --> 00:27:19,760
+موجودة عندها في ال bison شوية الأمور مختلفة ال
+
+363
+00:27:19,760 --> 00:27:24,970
+bison modelأو الـ Naive bias هو عبارة عن very fast
+
+364
+00:27:24,970 --> 00:27:29,910
+model وsimple classification في نفس الوقت مناسب
+
+365
+00:27:29,910 --> 00:27:33,450
+جدا مع ال high dimensional data set اللي موجودة
+
+366
+00:27:33,450 --> 00:27:38,330
+عندي لأنه
+
+367
+00:27:38,330 --> 00:27:41,250
+فعليا مافيش فيه براميتر لو كانت فيه برامتر موجودة
+
+368
+00:27:41,250 --> 00:27:44,730
+مافيش فيه برامتر كتير أعتمد عليها العناصر أو الـ
+
+369
+00:27:44,730 --> 00:27:49,690
+Naive bias بشكل عام بيعتمد على ال probabilisticو
+
+370
+00:27:49,690 --> 00:27:54,410
+بوصف العلاقة ما بين العناصر او ال attributes و ال
+
+371
+00:27:54,410 --> 00:27:59,790
+label بناء على احتمالات خلّينا نيجي نقول اذكركوا
+
+372
+00:27:59,790 --> 00:28:03,090
+بس بالاحتمالات اللي موجودة عندى هان لو كان انا في
+
+373
+00:28:03,090 --> 00:28:11,870
+عندى صندوق بيحتوي على عشر sample 6
+
+374
+00:28:11,870 --> 00:28:17,410
+plus و 4 minus
+
+375
+00:28:25,310 --> 00:28:32,810
+الان بلاش plus خلينا نحق عمود بالشكل هذا لحاجة في
+
+376
+00:28:32,810 --> 00:28:39,670
+بالي يعني الان وجيت قلتلك قداش احتمال انه يطلع
+
+377
+00:28:39,670 --> 00:28:42,770
+معايا plus عشان بس نذكرك بالاحتمالات
+
+378
+00:28:45,650 --> 00:28:49,910
+6 على 10 صحيح ال probability تبعت ال plus 6 على 10
+
+379
+00:28:49,910 --> 00:28:56,810
+و ال probability طبعا
+
+380
+00:28:56,810 --> 00:29:02,310
+عشرة هي حجم ال space اللي انا population اللي انا
+
+381
+00:29:02,310 --> 00:29:10,010
+بقى اشتغل عليها طبعا هذه 4 على 10 الآن
+
+382
+00:29:10,010 --> 00:29:16,670
+في عند مصطلحات زي ال most likelyالـ prior الـ
+
+383
+00:29:16,670 --> 00:29:20,530
+posterior الـ probability إلى آخرها الـ posterior
+
+384
+00:29:20,530 --> 00:29:23,130
+السابق الـ most likely اللي هي الأغلب الظن أو
+
+385
+00:29:23,130 --> 00:29:26,870
+الغلبة العناصر الموجودة أو الأكثر احتمالا و كل هذه
+
+386
+00:29:26,870 --> 00:29:30,210
+الحسبة تباعتي بناء على ال probabilities احنا
+
+387
+00:29:30,210 --> 00:29:33,770
+متفقين الآن .. احنا متفقين الآن ان انا هي ال
+
+388
+00:29:33,770 --> 00:29:36,130
+probability تباعتي لكن لو انا جيت و قلتلك مش بس
+
+389
+00:29:36,130 --> 00:29:41,670
+على ال final shape و بدخل معاها ال color و روحت و
+
+390
+00:29:41,670 --> 00:29:43,670
+قلتلك في عندي ال dash هذه
+
+391
+00:29:49,240 --> 00:30:00,200
+شو هتساوي؟ عليش هتصنفها؟ plus ولا column؟ مش هتقدر
+
+392
+00:30:00,200 --> 00:30:05,940
+تصنفها ليش؟ لإن هذه لا هي column ولا هي جاية plus
+
+393
+00:30:06,640 --> 00:30:10,880
+طيب إذا أنا قلتلك اللون جزء من حسبك شوبك تساوي
+
+394
+00:30:10,880 --> 00:30:15,320
+معناته هتختلف معايا الحسبة تماما و هصير ابني انا
+
+395
+00:30:15,320 --> 00:30:20,140
+اخد علاقة الشكل مع ال label و علاقة اللون مع ال
+
+396
+00:30:20,140 --> 00:30:22,920
+label و بناء انا على ال probability ال probability
+
+397
+00:30:22,920 --> 00:30:28,320
+تبعت الأحمر 6 على 11أو .. اه عفوا ال probability
+
+398
+00:30:28,320 --> 00:30:32,400
+بتاعة الأحمر 6 على 10 و ال probability تبعت الأسود
+
+399
+00:30:32,400 --> 00:30:36,380
+4 على 10 و كذلك في كل واحدة منهم وبالتالي الحسبة
+
+400
+00:30:36,380 --> 00:30:40,660
+تبعتي هتصير بناء على العنصر اللي موجود عندى هاني
+
+401
+00:30:40,660 --> 00:30:45,340
+ال naive bias نايف من اسمه جامعة الخير ان هو سهل
+
+402
+00:30:45,340 --> 00:30:52,260
+او trivial ليش انه مبني على trivial assumption ان
+
+403
+00:30:52,260 --> 00:30:57,790
+ال generative model هذاتمام؟ بده يشتغل على الموضوع
+
+404
+00:30:57,790 --> 00:31:02,410
+ال classification وبيفترض انه في عندي ان ال data
+
+405
+00:31:02,410 --> 00:31:07,550
+فيها normal distribution وبناء على هيكاد وفي عندي
+
+406
+00:31:07,550 --> 00:31:10,910
+independent attributes وبالتالي انا مافيش عندي
+
+407
+00:31:10,910 --> 00:31:14,870
+مشكلة في موضوع العناصر يعني naive assumption ان كل
+
+408
+00:31:14,870 --> 00:31:17,430
+ال data اللي عندي هي عبارة عن independent
+
+409
+00:31:17,430 --> 00:31:21,590
+attributes ومن ثم انا قاعد بأتكلم انه في عندي
+
+410
+00:31:22,500 --> 00:31:28,520
+normal distribution لل data اللي موجودة عندها طيب
+
+411
+00:31:28,520 --> 00:31:31,520
+عشان نحاول نسهل و نوصل للمعادلة اللي انا هشتغل
+
+412
+00:31:31,520 --> 00:31:37,780
+عليها هروح اشتغل على حسبة ال probability الان هذا
+
+413
+00:31:37,780 --> 00:31:41,560
+ال probability وفي
+
+414
+00:31:41,560 --> 00:31:46,240
+عند اللون حسبة اللون خلينا
+
+415
+00:31:46,240 --> 00:31:51,410
+نغير بس شغلة سريعة هيكأجي أهان على المثال هذا أجي
+
+416
+00:31:51,410 --> 00:31:57,290
+أقول في عندي plus سودة هيصار مازال عشرة وصار في
+
+417
+00:31:57,290 --> 00:32:04,610
+عندي عمود أحمر معناته أن الأن ال probability تبعت
+
+418
+00:32:04,610 --> 00:32:11,050
+ال plus صحيح واحد اتنين تلاتة أربعة خمسة ستة ستة
+
+419
+00:32:11,050 --> 00:32:16,510
+على عشرة بنفس المنطق و ال probability تبعت العمود
+
+420
+00:32:17,590 --> 00:32:24,710
+تساوي اربع على عشرة هذا الشكل مصبوط هذا ال final
+
+421
+00:32:24,710 --> 00:32:29,350
+هذا ال label طب ال color ال probability تبعت ال
+
+422
+00:32:29,350 --> 00:32:36,970
+red واحد اتنين تلاتة اربع خمسة ستة ستة على عشرة و
+
+423
+00:32:36,970 --> 00:32:44,970
+ال probability تبعت ال black تساوي اربع على عشرة
+
+424
+00:32:45,630 --> 00:32:50,510
+لاحظين ان هاي ال label تبعتي و هاي ال color تبعتي
+
+425
+00:32:50,510 --> 00:32:53,410
+بما انه صار في عندي color و صار في عندي label
+
+426
+00:32:53,410 --> 00:32:57,710
+معناته انا ال label هاد ال posterior معروفة مسبقا
+
+427
+00:32:57,710 --> 00:33:01,880
+يعني من العناصر المعطائليو انا بتروح ادور على ال
+
+428
+00:33:01,880 --> 00:33:05,600
+most likelihood او ال most likely property على
+
+429
+00:33:05,600 --> 00:33:09,900
+الاكتر الظن لوين هتكون وبالتالي هدور على شغل
+
+430
+00:33:09,900 --> 00:33:13,600
+بسميها انا يا جماعة الخير conditional properties
+
+431
+00:33:19,820 --> 00:33:23,800
+الـ class و الـ feature قدّاش علاقة ال class مع ال
+
+432
+00:33:23,800 --> 00:33:27,680
+feature هاي عشان نفهمها بشكل صحيح خلّينا نفترض ..
+
+433
+00:33:27,680 --> 00:33:32,860
+نفترض ان انا في عندى instance X فيها مجموعة ال
+
+434
+00:33:32,860 --> 00:33:40,740
+attribute من X1 ل Xn وفي عندى M classes M من ال
+
+435
+00:33:40,740 --> 00:33:46,520
+classالـ conditional probability تبعت لـ class CI
+
+436
+00:33:46,520 --> 00:33:49,860
+على ال X على ال instance هاي يعني بين قوسين ان ال
+
+437
+00:33:49,860 --> 00:33:53,960
+instance هي تحتوي لل class اللي موجود عندهان تساوي
+
+438
+00:33:53,960 --> 00:33:58,360
+ال probability لل class مضروبة في ال probability
+
+439
+00:33:58,360 --> 00:34:02,260
+لل instance في ال classes على ال probability لل
+
+440
+00:34:02,260 --> 00:34:07,000
+instance نفسها احتمال ظهور ال instance طيب انا
+
+441
+00:34:07,000 --> 00:34:12,010
+فعليا ال instance اللي موجودة عندهانقدش احتمالها
+
+442
+00:34:12,010 --> 00:34:15,410
+تكون ظهورها؟ الأصل تكون صفر ليش الأصل تكون صفر؟
+
+443
+00:34:15,410 --> 00:34:18,370
+لأن هي instance جديدة مش بالضرورة موجودة في ال
+
+444
+00:34:18,370 --> 00:34:21,990
+data set مسبقاً وبالتالي أنا .. هذه مدعاة أني أخلص
+
+445
+00:34:21,990 --> 00:34:29,110
+عليها أو أخلص منها عفواً بس الآن خلّيني أقول هنا C
+
+446
+00:34:29,110 --> 00:34:34,430
+of X ال class ل X يساوي ال maximum probability
+
+447
+00:34:34,430 --> 00:34:39,660
+لمين؟الـ B لـ Probability ل ال class يعني بينجو
+
+448
+00:34:39,660 --> 00:34:42,580
+سيم يجي و يقول لي والله ال instance الفلانية اللي
+
+449
+00:34:42,580 --> 00:34:49,080
+هي ال dash هذه ال class طبعتها ال class طبعت ال
+
+450
+00:34:49,080 --> 00:34:52,440
+dash هذه تساوي ال probability ال maximum
+
+451
+00:34:52,440 --> 00:34:56,260
+probability يعني بدي أخد أعلى probability لمين؟ ل
+
+452
+00:34:56,260 --> 00:34:59,080
+ال classes أنا في عندي two classes يعني بدي أحسب
+
+453
+00:34:59,080 --> 00:35:02,360
+two probabilities ال probability ل ال class أنها
+
+454
+00:35:02,360 --> 00:35:08,530
+تكون زائد أو تكون عمودتمام؟ فمضروبة انه جديش
+
+455
+00:35:08,530 --> 00:35:12,310
+احتمال عناصر .. مجموع العناصر اللي موجودة عندي هان
+
+456
+00:35:12,310 --> 00:35:17,150
+مع ال class اللي عندي و بما انه عملية مقارنة زي ما
+
+457
+00:35:17,150 --> 00:35:20,890
+خلصت سابقا من الجدر التربيعي ممكن اخلص الآن من
+
+458
+00:35:20,890 --> 00:35:25,250
+المقام لان مابدي اجسم على ثابت فممكن انا اخلص منه
+
+459
+00:35:25,250 --> 00:35:29,890
+وبالتالي انا بصجر المسألة تبعتي لل argument X
+
+460
+00:35:29,890 --> 00:35:33,390
+تعالى نشوف العناصر ايش المقصود فيها بشكل سريع
+
+461
+00:35:34,040 --> 00:35:40,160
+المعادلة السابقة اللي احنا ظهرت عندنا هنا ال
+
+462
+00:35:40,160 --> 00:35:44,900
+posterior probability اللي هيقولنا posterior سابقا
+
+463
+00:35:44,900 --> 00:35:49,400
+ال class على ال conditional probability تبعت ال
+
+464
+00:35:49,400 --> 00:35:52,930
+class وال attributes اللي موجودة عندي هناالـ
+
+465
+00:35:52,930 --> 00:35:57,510
+Probability لـ X على ال class الـ likelihood اللي
+
+466
+00:35:57,510 --> 00:36:01,650
+هي فعليا الاحتمال اللي أنا بدور عليه وهو عبارة عن
+
+467
+00:36:01,650 --> 00:36:05,850
+summation سنشوفها قليلا الان Probability تبع ال
+
+468
+00:36:05,850 --> 00:36:10,710
+class نفسه ال prior اللي موجود عندي هناو ال X ال
+
+469
+00:36:10,710 --> 00:36:15,170
+predictor ال probability اللي انا فعليا بدي اشوفها
+
+470
+00:36:15,170 --> 00:36:18,370
+تعالى نشوفه عشان نفهم الكلام هذا و المعادلة من
+
+471
+00:36:18,370 --> 00:36:21,130
+ناحية حساب لإن شوية الأمور لو بدت تبقى في
+
+472
+00:36:21,130 --> 00:36:27,150
+المعادلات الرياضية هت غم الأمور علينا لأن احنا في
+
+473
+00:36:27,150 --> 00:36:31,250
+جماعة هنا على غرار الناس اللي كانت بدت تلعب golf
+
+474
+00:36:31,250 --> 00:36:34,870
+قررت تروح على البحر على الشطالان هل بدهم يروحوا
+
+475
+00:36:34,870 --> 00:36:37,390
+على الشاطئ ولا ميروحوش؟ والله قالوا في عندنا تلت
+
+476
+00:36:37,390 --> 00:36:42,870
+عوامل أساسية الطقس المظهر مشمس و لا ممطر و لا غائم
+
+477
+00:36:42,870 --> 00:36:47,850
+درجة الحرارة و ال humidity اللي هي الرقوبة نفس
+
+478
+00:36:47,850 --> 00:36:50,790
+المثال السابق لكن غيرنا ال label من playing golf ل
+
+479
+00:36:50,790 --> 00:36:53,310
+beach
+
+480
+00:36:54,570 --> 00:36:58,550
+الان مطلوب مني اشتغل كالتالي بدي اعمل جدول بسيط
+
+481
+00:36:58,550 --> 00:37:02,290
+الجدول مثل هذا الجدول هلاقيت هنشتغل معاكم بكل
+
+482
+00:37:02,290 --> 00:37:06,970
+بساطة ايش بده يساوي انا بدي اعمل prediction ل data
+
+483
+00:37:06,970 --> 00:37:12,390
+set بناء على probability انا الان هاد ال data set
+
+484
+00:37:12,390 --> 00:37:15,990
+او ال training set تبعتي جاهزة و ثابتة الان اللي
+
+485
+00:37:15,990 --> 00:37:21,470
+هروح اسويه هروح احسب علاقة ال X ال outlook مع ال
+
+486
+00:37:21,470 --> 00:37:25,600
+labelالـ Probability تبعتها مع الـ .. مع الـ sunny
+
+487
+00:37:25,600 --> 00:37:29,300
+ال .. ال Probability تبعتها .. عفواً ال Outlook
+
+488
+00:37:29,300 --> 00:37:31,980
+فيها كام value different value، three values sunny
+
+489
+00:37:31,980 --> 00:37:36,920
+و rainy و cloudy علاقة ال sunny مع ال yes و مع ال
+
+490
+00:37:36,920 --> 00:37:41,020
+no علاقة ال rainy مع ال yes و مع ال no علاقة ال
+
+491
+00:37:41,020 --> 00:37:44,400
+cloudy مع ال yes مع ال no و أفصل في الجدول اللي
+
+492
+00:37:44,400 --> 00:37:50,000
+موجود عندى يعني بدك تيجي لكل attribute بشكل مستقل
+
+493
+00:37:50,000 --> 00:37:55,380
+هذا الجدولحاجة اقول والله انا بدي اتكلم على ال
+
+494
+00:37:55,380 --> 00:38:01,380
+outlook طبعا جابلي جماعة الخير لو انا سألتك لان ال
+
+495
+00:38:01,380 --> 00:38:05,840
+going لل beach لل yes و ال no زي ما حسبنا هان ال
+
+496
+00:38:05,840 --> 00:38:09,140
+probability لل yes جد ايش تساوي ال data 6 فيها
+
+497
+00:38:09,140 --> 00:38:15,620
+عشرة عندهان واحدة اتين تلاتة اربعة yes اربعة على
+
+498
+00:38:15,620 --> 00:38:20,340
+عشرة ال probability لل no ستة على عشرة بكل تأكيد
+
+499
+00:38:20,340 --> 00:38:27,530
+بدون ما اروح اضطر اعدال yes مظبوطة ال outlook ال
+
+500
+00:38:27,530 --> 00:38:34,230
+outlook الآن فيها three different values في
+
+501
+00:38:34,230 --> 00:38:38,830
+عندي ال sunny في
+
+502
+00:38:38,830 --> 00:38:49,690
+عندي الريني و في عندي ال cloudy ممتاز طيب و أنا في
+
+503
+00:38:49,690 --> 00:38:54,950
+عندي فعليا في ال labels في عندي ال yesو في عندى
+
+504
+00:38:54,950 --> 00:39:02,450
+الـ No ال beach صح؟
+
+505
+00:39:02,450 --> 00:39:05,810
+الان
+
+506
+00:39:05,810 --> 00:39:10,130
+كام واحدة sunny عندى انا واحدة تنتين تلاتة اربعة
+
+507
+00:39:10,130 --> 00:39:16,170
+ممتاز علاقة الاربع ال sunny هدول المفروض يكونوا
+
+508
+00:39:16,170 --> 00:39:22,350
+مجسمات على ال yes و ال no ال yes جديشأربعة طيب
+
+509
+00:39:22,350 --> 00:39:26,890
+الآن بدي أقول sunny و yes يعني أنا بدي أجسم على
+
+510
+00:39:26,890 --> 00:39:32,470
+أربعة يا جماعة الخير و أنه ستة مصبوط لأن ال over
+
+511
+00:39:32,470 --> 00:39:36,030
+all probability تبعت ال yes ظهور ال yes فقط أربع
+
+512
+00:39:36,030 --> 00:39:40,290
+عناصر أربع مرات و ظهور ال no ست مرات إذا كانت ال
+
+513
+00:39:40,290 --> 00:39:43,170
+yes مرتبطة بال classes هاي فعشان أنا أحسب ال
+
+514
+00:39:43,170 --> 00:39:48,650
+probability تبعت ال yes و ال sunny ال sunny هاي
+
+515
+00:39:48,650 --> 00:39:49,670
+مرة yes
+
+516
+00:39:55,170 --> 00:40:00,990
+تنتين تلاتة أصبت؟ ليش هذه لأ؟ لأن هذه جال ال label
+
+517
+00:40:00,990 --> 00:40:03,550
+تبعتها no هاي خلصنا الأربعة ال sunny اللي موجودة
+
+518
+00:40:03,550 --> 00:40:06,410
+عندها يعني بينجوستين ال sunny ال probability
+
+519
+00:40:06,410 --> 00:40:15,970
+تبعتها تلاتة على أربعة زائد جداش جداش واحد على ستة
+
+520
+00:40:17,560 --> 00:40:20,760
+خلاص انت مافيش داعي انك انت عايش تنظر لباقي
+
+521
+00:40:20,760 --> 00:40:23,600
+العناصر مجموع ال sun اللي فوق على العناصر اللي
+
+522
+00:40:23,600 --> 00:40:29,940
+موجودة عندي هان ال rainy الان جدش حسبة ال yes ما
+
+523
+00:40:29,940 --> 00:40:34,440
+زالت أربعة و النقل ستة rainy بدي أشغل عليها نفس
+
+524
+00:40:34,440 --> 00:40:42,160
+الكلام rainy واحدة تنتين تلاتة في عندي تلاتة rainy
+
+525
+00:40:42,160 --> 00:40:49,180
+والتلاتة جايات كلهمنفس ال class معناته zero على
+
+526
+00:40:49,180 --> 00:40:57,220
+أربعة زائد تلاتة على ستة و هلجت بيقولك طريقة كيف
+
+527
+00:40:57,220 --> 00:41:00,200
+تتأكد من حيث تفتكر ان كل ال probability بتبعتك صح
+
+528
+00:41:00,200 --> 00:41:06,140
+cloudy الآن برضه نفس الكلام على أربعة على ستة
+
+529
+00:41:06,140 --> 00:41:12,100
+cloudy فيها واحدة مع ال yes و هم تلاتة و تنتين مع
+
+530
+00:41:15,120 --> 00:41:20,080
+الستة الان لو عديت العناصر تبعت ال yes تلاتة على
+
+531
+00:41:20,080 --> 00:41:24,520
+أربعة زائد صفر على أربعة زائد واحد على أربعة تطلع
+
+532
+00:41:24,520 --> 00:41:31,420
+أربعة على أربعة لو عديت عناصر انه واحد على ستة
+
+533
+00:41:31,420 --> 00:41:34,820
+زائد تلاتة على ستة زائد تانين على ستة تطلع ستة على
+
+534
+00:41:34,820 --> 00:41:38,740
+ستة وهي فعليا ال probability لازم مجموع الاحتمالات
+
+535
+00:41:38,740 --> 00:41:43,600
+كلها تكون عندى واحد ممتاز هذا بالنسبة لل attribute
+
+536
+00:41:43,600 --> 00:41:44,180
+الأول
+
+537
+00:41:46,970 --> 00:41:49,970
+و بدي أروح أحسبها لل attribute التاني بنفس الكيفية
+
+538
+00:41:49,970 --> 00:41:55,530
+temperature
+
+539
+00:41:55,530 --> 00:41:59,870
+temperature كان فيه .. كان value عندي عندي three
+
+540
+00:41:59,870 --> 00:42:04,410
+values high و low و mild ال low نبدأ مع ال low هاي
+
+541
+00:42:04,410 --> 00:42:11,250
+واحدة هاي تنتين اتنين بدهم يتوزعوا على ال yes و ال
+
+542
+00:42:11,250 --> 00:42:17,570
+no الآن صفرno و no معناته صفر على أربعة و اتنين
+
+543
+00:42:17,570 --> 00:42:23,870
+على ستة مع ال no طيب خلصنا من ال من ال low ال mild
+
+544
+00:42:23,870 --> 00:42:32,710
+ال mild هي واحدة تنتين تلاتة تلاتة عناصر التلاتة
+
+545
+00:42:32,710 --> 00:42:36,560
+عناصر هدول يتوزعوا ما بين ال yes و ال noهي الـ
+
+546
+00:42:36,560 --> 00:42:40,700
+mild الأولى yes الـ mild التانية no والـ mild
+
+547
+00:42:40,700 --> 00:42:45,900
+الأخيرة no معناته الآن هم هيكونوا 1 على 4 مع ال
+
+548
+00:42:45,900 --> 00:42:52,580
+yes اللي هي الأولى هاي و 2 على 6 في حالة ال no و
+
+549
+00:42:52,580 --> 00:42:58,320
+بكمل الجدول لكل العناصر اللي موجودة عندي هان ال
+
+550
+00:42:58,320 --> 00:43:00,580
+probability تبعت ال beach ممكن أحط لإيه أنا كتبت
+
+551
+00:43:00,580 --> 00:43:05,790
+هان قبل شوية ممكن أحطها في نهاية الجدولعشان انا
+
+552
+00:43:05,790 --> 00:43:09,790
+اشغل على العناصر اللي موجودة عندي فعليا 6 على 10
+
+553
+00:43:09,790 --> 00:43:15,230
+.. ار ..الان 4 على 10 المفروض
+
+554
+00:43:15,230 --> 00:43:19,550
+في كل واحدة من هدول ما هيلاحظ 4 على 10 .. 4 على 10
+
+555
+00:43:19,550 --> 00:43:24,980
+.. 4 على 10ليش أربع؟ لأنه فعلاً أربع على ال yes و
+
+556
+00:43:24,980 --> 00:43:28,220
+هدول لازم يكون مجموحهم أربع في كل attribute و هدول
+
+557
+00:43:28,220 --> 00:43:31,260
+مجموحهم لازم يكون ستة و في المحصلة ستة على عشر
+
+558
+00:43:31,260 --> 00:43:36,140
+ممتاز الآن لاحظوا هذه ال computation كم مرة هعملها
+
+559
+00:43:36,140 --> 00:43:43,120
+لمرة واحدة على نفس ال data set هعملها لمرة واحدة
+
+560
+00:43:43,120 --> 00:43:46,180
+فقط و هتظل ال data .. و لما ال data set ماصارش
+
+561
+00:43:46,180 --> 00:43:51,030
+عليها تغيير هتظلها هذه موجودة عندىإيش اللي حيصير
+
+562
+00:43:51,030 --> 00:43:55,810
+لاحقا عشان اطبق المعادلة السابقة هذه هشغل كالتالي
+
+563
+00:43:55,810 --> 00:44:01,030
+بيجي بقول بالله شوف اللي إيش ال label تبعت ال
+
+564
+00:44:01,030 --> 00:44:06,810
+sunny و ال mild و ال high إيش ال label تبعت ال
+
+565
+00:44:06,810 --> 00:44:12,130
+sunny sunny
+
+566
+00:44:12,130 --> 00:44:17,450
+و mild و
+
+567
+00:44:17,450 --> 00:44:18,850
+high درجة الحرارة
+
+568
+00:44:21,880 --> 00:44:27,460
+عشان بدي ارجع معاكم للجدول السابق تم ذكرك في
+
+569
+00:44:27,460 --> 00:44:34,380
+المعادلة المعادلة بتقول الارج ماكس لا لل CI اللي
+
+570
+00:44:34,380 --> 00:44:37,000
+هي ال class ال probability لل CI مضروبة في ال
+
+571
+00:44:37,000 --> 00:44:44,120
+probability لا ال X على ال CI طيب هلأ قد بنفسرلك
+
+572
+00:44:44,120 --> 00:44:47,920
+إياها أوضح و بنفسرك إياها أوضح مع الأرقام نرجع هنا
+
+573
+00:44:47,920 --> 00:44:54,580
+ال probability لل classهو قاعد بيقوللي بدور على ال
+
+574
+00:44:54,580 --> 00:44:58,480
+argmax بدور على ال maximum probability لكل classes
+
+575
+00:44:58,480 --> 00:45:02,740
+كام class انا عندي؟ عندي two classes يعني بين جثين
+
+576
+00:45:02,740 --> 00:45:05,600
+الجامعة الخير هو عمال بيسألني بيسألني ال
+
+577
+00:45:05,600 --> 00:45:10,800
+probability تبعت ال element اللي موجود عندها على
+
+578
+00:45:10,800 --> 00:45:14,520
+انه يكون ال class و ال instance اللي اعطاني اياها
+
+579
+00:45:17,240 --> 00:45:19,840
+مش قولنا هذه اللي أنا بدور عليها قاعد؟ هاي ال
+
+580
+00:45:19,840 --> 00:45:23,160
+value هو بدي تجيبلي ال probability تبعت ال class
+
+581
+00:45:23,160 --> 00:45:27,760
+مع ال given instance اللي موجودة عندي هنا طيب،
+
+582
+00:45:27,760 --> 00:45:31,080
+الآن حسب ال data set معناته أنا بدي أروح أشتغل
+
+583
+00:45:31,080 --> 00:45:36,960
+كتالي مرة مع ال yes و مرة مع انه هذا الكلام بيقول
+
+584
+00:45:36,960 --> 00:45:42,480
+ايه؟ ال probability مع ال yes ال label مع مين؟ مع
+
+585
+00:45:42,480 --> 00:45:51,040
+ال given data set ال sunnyو mild و high ايش ال
+
+586
+00:45:51,040 --> 00:45:56,340
+probability تبعت high اولا بقول لهذه تساوي ال
+
+587
+00:45:56,340 --> 00:46:02,260
+probability تبعت ال yes مضروبة
+
+588
+00:46:02,260 --> 00:46:09,520
+في ال probability تبعت مين تبعت ال instance اللى
+
+589
+00:46:09,520 --> 00:46:14,590
+موجودة عندى هنا اي instanceطب ال instance تبعتي
+
+590
+00:46:14,590 --> 00:46:20,510
+مكونة من ال outlook و ال temperature و ال humidity
+
+591
+00:46:20,510 --> 00:46:25,390
+مصبوط؟ كمان مرة ال instance تبعتي هان اللي هي ال X
+
+592
+00:46:25,390 --> 00:46:33,830
+هذه اللي أنا الآن هيها مكونة من ال outlook و ال
+
+593
+00:46:33,830 --> 00:46:39,000
+temperature و ال humidityوبدي اروح بقوللي علاقة كل
+
+594
+00:46:39,000 --> 00:46:41,580
+ال values اللي موجودة عندهم بال class مين بال
+
+595
+00:46:41,580 --> 00:46:47,740
+class yes يعني بين جثين هي عبارة عن ال probability
+
+596
+00:46:47,740 --> 00:46:53,700
+لل
+
+597
+00:46:53,700 --> 00:47:01,840
+S لل sunny ال outlook equal
+
+598
+00:47:01,840 --> 00:47:04,980
+sunny مع ال yes
+
+599
+00:47:08,130 --> 00:47:15,570
+مضروبة في ال attribute التانية ال probability تبعت
+
+600
+00:47:15,570 --> 00:47:26,130
+ال temperature على ال yes هاي ال sunny او
+
+601
+00:47:26,130 --> 00:47:34,470
+الآن mild هاي ال mild ال temperature تبعتي high
+
+602
+00:47:37,170 --> 00:47:44,970
+هي ال high بكل بساطة بقول ليه تلاتة على اربعة او
+
+603
+00:47:44,970 --> 00:47:47,530
+عفوا من الاول اربعة على عشرة تبع ال yes ال
+
+604
+00:47:47,530 --> 00:47:50,050
+probability اللي موجودة عندى هان اربعة على عشرة
+
+605
+00:47:50,050 --> 00:47:57,970
+مضروبة في تلاتة على اربعة مضروبة في اتنين واعفوا
+
+606
+00:47:57,970 --> 00:48:04,640
+واحد على اربعة في اتنين على اربعةوبهك بكون انا بدي
+
+607
+00:48:04,640 --> 00:48:13,800
+اعيد الحسبة تبعت لمين لكل العناصر الموجودة يعني ال
+
+608
+00:48:13,800 --> 00:48:17,720
+probability لل yes طبعا انا فصلتلكوا ياها عشان
+
+609
+00:48:17,720 --> 00:48:21,540
+ماتنسوهاش لانوا لاحظوا ان هي عبارة عن عملية ضرب
+
+610
+00:48:21,540 --> 00:48:26,320
+هادي ل probability تبعت
+
+611
+00:48:26,320 --> 00:48:33,860
+ال X على Ci على class تساوي ل probabilityلمن؟ لل
+
+612
+00:48:33,860 --> 00:48:42,700
+values x i على .. هي بنجسيل ال product لل x i على
+
+613
+00:48:42,700 --> 00:48:50,080
+ال class اللي موجود عندها x j و ال j equal 1 to n
+
+614
+00:48:50,080 --> 00:48:57,240
+بعدد ال attributes اللي موجودة عندها الآن ال
+
+615
+00:48:57,240 --> 00:49:03,280
+probability لل yes حسبناها 4 ع العشرة هي ..الـ
+
+616
+00:49:03,280 --> 00:49:08,200
+sunny مع ال yes كانت 3 على 4 حسب الجدول السابق ال
+
+617
+00:49:08,200 --> 00:49:13,880
+mild مع ال yes 1 على 4 ال high مع ال yes طبعا زي
+
+618
+00:49:13,880 --> 00:49:18,860
+ما قلتلك هذه بتمثل ال outlook ال sunny ال
+
+619
+00:49:18,860 --> 00:49:21,400
+temperature و ال humidity اللي هي ال attributes
+
+620
+00:49:21,400 --> 00:49:25,000
+اللي موجودة عندها مع ال yes و فحسبناها فكانت
+
+621
+00:49:25,000 --> 00:49:32,820
+الدانيال value high اللي هي 375 من عشرة ألفممتاز
+
+622
+00:49:32,820 --> 00:49:37,800
+هدي ال probability لمن؟ لل yes يعني بين جوسين انه
+
+623
+00:49:37,800 --> 00:49:43,920
+احتمال انه تكون هادي ال instance انه نروح في
+
+624
+00:49:43,920 --> 00:49:48,180
+الظروف هادية على الشاطئ هي احتماليتها حسب ال data
+
+625
+00:49:48,180 --> 00:49:51,900
+set اللي موجودة عندها طب لو احتمال اننا مانروحش
+
+626
+00:49:51,900 --> 00:49:54,660
+احنا لسه مااخدناش قرار فالان بما انه class تاني
+
+627
+00:49:54,660 --> 00:49:58,180
+فهروح احسب نفس الحسبة السابقة بس مع مين يا جماعة
+
+628
+00:49:58,180 --> 00:50:10,280
+الخير مع النومsunny و ال mild و ال high ممتاز
+
+629
+00:50:10,280 --> 00:50:16,760
+تساوي probability of no حسبناها اذا كانت هذه اربع
+
+630
+00:50:16,760 --> 00:50:20,500
+على عشر فالتاني هتكون ستة على عشر اللي هم فعلا
+
+631
+00:50:20,500 --> 00:50:24,460
+مجسمين مضروبة في ال probability تبعت ال sunny على
+
+632
+00:50:24,460 --> 00:50:29,120
+ال no مضروبة في ال probability تبعت ال mild تبعت
+
+633
+00:50:29,120 --> 00:50:33,040
+ال temperatureفي الـ No مضروبة في ال probability
+
+634
+00:50:33,040 --> 00:50:38,160
+تبع ال humidity اللي هي المفروض عندي high على no و
+
+635
+00:50:38,160 --> 00:50:54,060
+هكذا وبالتالي الحسبة تبعتي هتكون بالشكل هذا الان
+
+636
+00:50:54,060 --> 00:50:59,390
+القانون بيقولليفي ال classification في ال
+
+637
+00:50:59,390 --> 00:51:03,730
+classification هتشتغل على ال instance اللي موجودة
+
+638
+00:51:03,730 --> 00:51:09,750
+عندنا وهي هتشتغل على ال maximum probability ال
+
+639
+00:51:09,750 --> 00:51:13,570
+احتمال الاكبر الان عندك رقمين بغض النظر جداش
+
+640
+00:51:13,570 --> 00:51:15,930
+الرقمين يا جماعة الخير اللي طلعوا مين اكبر من
+
+641
+00:51:15,930 --> 00:51:21,850
+التاني مية و احد عشرة على عشرة الف ولا تلاتمية
+
+642
+00:51:21,850 --> 00:51:25,860
+خمسة و سبعين على عشرة الف اكيدالـ maximum value
+
+643
+00:51:25,860 --> 00:51:30,700
+تبعتي هيها هان معناته ال most likely تبع ال
+
+644
+00:51:30,700 --> 00:51:36,160
+existence اللي موجودة عندي هان عبارة عنyes غالبا
+
+645
+00:51:36,160 --> 00:51:41,820
+لو كان الظرف sunny مشرق او مشمس والدرجة الحرارة
+
+646
+00:51:41,820 --> 00:51:46,800
+متوسطة والرقوبة عالية غالبا هروح على البحر بناء او
+
+647
+00:51:46,800 --> 00:51:50,720
+على الشاطئ بناء على ال data set الاحتمالات انتبه
+
+648
+00:51:50,720 --> 00:51:55,860
+معايا او انتبه معايا كمان مرة الجدول هذا الجدول
+
+649
+00:51:55,860 --> 00:52:01,100
+هذا هيظل قائم عندى هيظل قائم عندى قول ما ال data
+
+650
+00:52:01,100 --> 00:52:08,940
+set هيلم تتغيركم مرة بحسبه؟ لمرة واحدة وكأنه
+
+651
+00:52:08,940 --> 00:52:13,020
+model وكأنه model بس مش model حساب أصبحت الآن
+
+652
+00:52:13,020 --> 00:52:16,060
+العملية عملية إيش؟ computation لكن ال computation
+
+653
+00:52:16,060 --> 00:52:20,660
+مش مع كل ال data set يعني الآن تخيلوا لو روحت أنا
+
+654
+00:52:20,660 --> 00:52:23,680
+غيرت في ال instance .. في ال instance high بعد
+
+655
+00:52:23,680 --> 00:52:27,900
+إذنكم وروحت قولت والله إنه أنا بدي أروح أبدل بدال
+
+656
+00:52:27,900 --> 00:52:28,960
+high high low
+
+657
+00:52:33,280 --> 00:52:37,200
+بدل ال high low ايش اللي هتفرق معايا؟ هرجع للجدول
+
+658
+00:52:37,200 --> 00:52:42,780
+اللي هو الجدول تبعي هذا وحاجة
+
+659
+00:52:42,780 --> 00:52:52,120
+أشتغل كتالي طبعا
+
+660
+00:52:52,120 --> 00:53:01,180
+عشان بس أظل نتذكر ال sunny و
+
+661
+00:53:01,180 --> 00:53:06,830
+mildو low هذه ال instances اللي موجودة عندي و أنا
+
+662
+00:53:06,830 --> 00:53:11,410
+بدي أضطر أرجع للجدول الآن بكل بساطة الحسبة السابقة
+
+663
+00:53:11,410 --> 00:53:18,450
+تبعتي هتكون كالتالي ال probability لل yes على ال
+
+664
+00:53:18,450 --> 00:53:22,670
+sunny مش حد كل الكلمات و ال m ال s و ال m و ال low
+
+665
+00:53:22,670 --> 00:53:29,690
+تساوي ال probability لل yes مضروبة في ال
+
+666
+00:53:29,690 --> 00:53:34,950
+probability ل ال sunny على ال yesهي المفروض فيها
+
+667
+00:53:34,950 --> 00:53:41,710
+الـ Outlook equals sunny يا جماعة الخير اللي
+
+668
+00:53:41,710 --> 00:53:44,330
+هي ال attribute الأول خلاص هي احنا هنعتمدها بالشكل
+
+669
+00:53:44,330 --> 00:53:50,330
+هذا على ال yes مضروبة في ال probability لل mild
+
+670
+00:53:50,330 --> 00:53:54,070
+اللي هي ال attribute التاني على ال yes مضروبة في
+
+671
+00:53:54,070 --> 00:53:56,830
+ال probability لل attribute التالت اللي هي ال low
+
+672
+00:53:56,830 --> 00:54:00,730
+على ال yes بنجو سينيج هي عمود ال yes كل شغل على
+
+673
+00:54:00,730 --> 00:54:07,740
+الكيون على العمود هذا sunny هي ال valuemy هي ال
+
+674
+00:54:07,740 --> 00:54:17,800
+value و normal هي هيها
+
+675
+00:54:17,800 --> 00:54:22,160
+normal normal
+
+676
+00:54:22,160 --> 00:54:28,680
+بس عشان ال example يكون تمام بال normal هيها الان
+
+677
+00:54:28,680 --> 00:54:38,860
+بكل بساطة أربعة على عشرة ضرب المحوطات3 على 4 ضرب 1
+
+678
+00:54:38,860 --> 00:54:45,460
+على 4 ضرب 2 على 4 وإذا أنا بدي أطلع ال calculator
+
+679
+00:54:45,460 --> 00:54:50,980
+على السريع عشان أشوف حسبة هل في فعليا تأثير لل
+
+680
+00:54:50,980 --> 00:54:52,140
+element هذا أو لأ
+
+681
+00:54:56,850 --> 00:55:04,090
+قولنا أربعة على عشرة ضرب تلاتة على أربعة ضرب واحد
+
+682
+00:55:04,090 --> 00:55:13,790
+على أربعة ضرب طفت ال calculator أربعة
+
+683
+00:55:13,790 --> 00:55:24,110
+تقسيم عشرة ضرب تلاتة تقسيم أربعة ضرب واحد تقسيم
+
+684
+00:55:24,110 --> 00:55:24,750
+أربعة
+
+685
+00:55:27,550 --> 00:55:34,890
+درب اتنين تقسيم اربعة anyway
+
+686
+00:55:34,890 --> 00:55:41,550
+ال calculator خذلتنا في الآخر ال probability لانه
+
+687
+00:55:41,550 --> 00:55:45,750
+بدي اعمل ال probability لانه لنفس ال instance M N
+
+688
+00:55:45,750 --> 00:55:49,070
+هتكون
+
+689
+00:55:49,070 --> 00:55:53,810
+ال probability لانه مضروبة
+
+690
+00:56:14,390 --> 00:56:17,910
+القيم المقابلة لهم اللي عمال يحوقهم باللون الأزرق
+
+691
+00:56:20,470 --> 00:56:23,350
+بالاضافة للقيمة الأخيرة ما تنسوهاش طبعا هاي اللي
+
+692
+00:56:23,350 --> 00:56:27,190
+هي في الأول ال probability لانه كلها هتصير في
+
+693
+00:56:27,190 --> 00:56:37,470
+عندها 6 على 10 مضروبة في 1 على 6 مضروبة في 2 على 6
+
+694
+00:56:37,470 --> 00:56:46,630
+مضروبة في 2 على 6 طبعا لو احنا فعليا36 المقام هنا
+
+695
+00:56:46,630 --> 00:56:51,010
+أكبر من هنا فغالبا اللي بالتباعتي هتكون yes و ال
+
+696
+00:56:51,010 --> 00:56:56,290
+computation هي اللي بتحكم الموضوع بتمنى تكون الأن
+
+697
+00:56:56,290 --> 00:57:00,010
+أصبحت الصورة بالنسبة لنا واضحة كيف النييف بايسان
+
+698
+00:57:00,010 --> 00:57:04,410
+بيشتغل الفكرة انه ابني الجدول اذا انت بنيت او انت
+
+699
+00:57:04,410 --> 00:57:08,690
+بنيت الجدول صح معناته انا مافيش عندى مشكلة طيب في
+
+700
+00:57:08,690 --> 00:57:11,010
+حالة هذه مثال تاني على السريع
+
+701
+00:57:14,970 --> 00:57:19,530
+بغض النظر احنا مش هنطول عليكم ان شاء الله تعالى و
+
+702
+00:57:19,530 --> 00:57:22,550
+بنفترض انكوا هتكونوا متابعين معانا و بيكونوا كأنه
+
+703
+00:57:22,550 --> 00:57:28,790
+في فرصة تشتغلوا وزيادة الان هاي ال data set كام
+
+704
+00:57:28,790 --> 00:57:31,470
+attribute؟ تلاتة على نفس الغرار ال attribute
+
+705
+00:57:31,470 --> 00:57:34,210
+السابق السابق اللي لها دخل في الموضوع؟ لأ هذا رقم
+
+706
+00:57:34,210 --> 00:57:37,270
+العينة او رقم ال sample ال class تبعتي binary
+
+707
+00:57:37,270 --> 00:57:41,210
+class مافرجتش كتير يا جماعة الخير بدي ابني الجدول
+
+708
+00:57:41,210 --> 00:57:44,030
+السابق بالكامل
+
+709
+00:57:46,870 --> 00:57:52,690
+هو بيقولوا بدوا منى ل class مصبوط ال attribute a1
+
+710
+00:57:52,690 --> 00:57:59,670
+ايش ال attribute a1 فيه values طبعا هنا في عندى
+
+711
+00:57:59,670 --> 00:58:05,130
+yes واحد او صفر واحد في ال attribute الاول كام
+
+712
+00:58:05,130 --> 00:58:08,250
+value في عندى صفر واحد اتنين يعني في عندى three
+
+713
+00:58:08,250 --> 00:58:12,850
+values صفر واحد اتنين انا بكتبه من مرتبات افضل
+
+714
+00:58:12,850 --> 00:58:14,830
+اليه ال attribute التانى
+
+715
+00:58:17,880 --> 00:58:20,240
+مع ال labels اللي موجودة ايش في عندي برضه values
+
+716
+00:58:20,240 --> 00:58:29,700
+012 برضه ماعندي مشكلة 012 ال attribute التالت اللي
+
+717
+00:58:29,700 --> 00:58:33,800
+انا هشتغل عليه فقط
+
+718
+00:58:33,800 --> 00:58:43,000
+قيمتين 112 وهنا في الآخر ال probability لل classال
+
+719
+00:58:43,000 --> 00:58:45,880
+probability لل class تبعتي جدش ال probability ..
+
+720
+00:58:45,880 --> 00:58:50,900
+كام class فيه؟ عندى three classes عفوا مصبوط ال ..
+
+721
+00:58:50,900 --> 00:59:01,360
+واحد اتنين تلاتة هاتوا هل بدنا كمان اعمود ال class
+
+722
+00:59:01,360 --> 00:59:06,540
+اللى موجود عندى هان واحد
+
+723
+00:59:06,540 --> 00:59:09,400
+اتنين تلاتة
+
+724
+00:59:11,920 --> 00:59:17,300
+أي تلاتة ال
+
+725
+00:59:17,300 --> 00:59:23,540
+class الأول واحد واحد اتنين تلاتة اربعة اربعة على
+
+726
+00:59:23,540 --> 00:59:31,500
+عشرة ال class التاني اتنين واحد اتنين تلاتة تلاتة
+
+727
+00:59:31,500 --> 00:59:36,100
+على عشرة وهدت الأخير تلاتة على عشرة مجموحهم عشرة
+
+728
+00:59:36,100 --> 00:59:41,890
+على عشرةبدي أجي العلاقة العناصر مع ال class الأول
+
+729
+00:59:41,890 --> 00:59:48,170
+اللي موجود عندي هنا صفر و واحد هاي صفر هاي صفر
+
+730
+00:59:48,170 --> 00:59:52,410
+تنتين مع
+
+731
+00:59:52,410 --> 00:59:59,230
+الواحد أربعة ال
+
+732
+00:59:59,230 --> 01:00:04,910
+class واحد معناته اتنين على أربعة وحتما ..حتما
+
+733
+01:00:04,910 --> 01:00:11,020
+الصفر مع ال class التانيصفر على عشرة .. صفر على
+
+734
+01:00:11,020 --> 01:00:18,160
+جداش الاتنين على تلاتة وهنا صفر على تلاتة ليش؟ لأن
+
+735
+01:00:18,160 --> 01:00:21,020
+هون فعليا الصفرها دي بينت مرتين فقط مع ال
+
+736
+01:00:21,020 --> 01:00:24,240
+attribute الأول وبالتالي أنا هنا بشغل في ال
+
+737
+01:00:24,240 --> 01:00:28,560
+attribute الأول ال value التانية الواحد الواحد هي
+
+738
+01:00:28,560 --> 01:00:37,560
+في المربع واحد واحد واحد واحد اربع عناصربرضه هتكون
+
+739
+01:00:37,560 --> 01:00:41,220
+عندها القيمة على أربعة يا جماعة الخير ماتنساش وهذه
+
+740
+01:00:41,220 --> 01:00:46,760
+هتكون على تلاتة وهذه هتكون على تلاتة الان واحد و
+
+741
+01:00:46,760 --> 01:00:55,800
+واحد هي .. okay وهي كمان واحد ممتاز يعني اتنين على
+
+742
+01:00:55,800 --> 01:00:59,880
+أربعة اتنين
+
+743
+01:00:59,880 --> 01:01:07,100
+على أربعة هذه واحدة وهذه اتنين طيبجدّش الواحد على
+
+744
+01:01:07,100 --> 01:01:14,440
+تلاتة واحد و تلاتة هيها مات واحد على تلاتة وجدّش
+
+745
+01:01:14,440 --> 01:01:20,220
+مع الواحد والتنين هيها ال probability تبعتها ضال
+
+746
+01:01:20,220 --> 01:01:25,140
+عند ال value الأخيرة الموجودة
+
+747
+01:01:25,140 --> 01:01:31,320
+عندى لمين؟ للتنين هي التنين هي التنين هي التنين في
+
+748
+01:01:31,320 --> 01:01:34,060
+عندى أربع قيم الأربع قيم منهم
+
+749
+01:01:37,600 --> 01:01:41,080
+ولا واحدة مع ال attribute أو مع ال class الأول صفر
+
+750
+01:01:41,080 --> 01:01:44,640
+على أربعة و لو انت جمعت فعليا هان اتنين على أربعة
+
+751
+01:01:44,640 --> 01:01:50,720
+او اتنين على أربعة لازم يطلع معاك أربعة على أربعة
+
+752
+01:01:50,720 --> 01:01:54,040
+لأن هما ال maximum أربعة عفوا ان هان اتنين على
+
+753
+01:01:54,040 --> 01:02:00,060
+أربعة الان مع الواحد و لا مافيش شي مع التنين هي
+
+754
+01:02:00,060 --> 01:02:04,880
+واحدة هي تنتين وبالتالي هان
+
+755
+01:02:11,280 --> 01:02:16,080
+هذه اتنين على تلاتة وهذه اتنين على تلاتة لو جمعت
+
+756
+01:02:16,080 --> 01:02:18,420
+العناصر اللي موجودة عندي هان و العناصر اللي عندي
+
+757
+01:02:18,420 --> 01:02:21,660
+هان لازم تاخد تلاتة و واحد صحيح وهذه تاخد واحد
+
+758
+01:02:21,660 --> 01:02:27,000
+صحيح كملية الجدول نفس الصورة السابقة هكون الجدول
+
+759
+01:02:27,000 --> 01:02:32,980
+هيه عندى بالتمام و مجرد ان انا اعمل الجدول هذا
+
+760
+01:02:32,980 --> 01:02:39,420
+بيسهل علي جدا ان احسبالعناصر خليني على السريع بس
+
+761
+01:02:39,420 --> 01:02:45,260
+احط المثال الأخير لو انا افترضت ان انا عندي واحد
+
+762
+01:02:45,260 --> 01:02:52,620
+واحد واتنين ماعرفش انا كتبت بشكل random هل فعليا
+
+763
+01:02:52,620 --> 01:02:57,380
+هذه ايش الاحتمال تبعتها انها تظهر عندى او ايش ال
+
+764
+01:02:57,380 --> 01:03:02,560
+class تبعتها اللى توجد عندها هذه مع ال class الاول
+
+765
+01:03:02,560 --> 01:03:04,160
+بدي احسبها
+
+766
+01:03:09,260 --> 01:03:16,820
+و بدي أحسبها مع ال class التاني و بدي أحسبها مع ال
+
+767
+01:03:16,820 --> 01:03:26,560
+class التالت طيب مع ال class الأول واحد وين ال
+
+768
+01:03:26,560 --> 01:03:31,440
+واحد هيها يا جماعة الخير ال attribute التاني برضه
+
+769
+01:03:31,440 --> 01:03:36,460
+واحد ال attribute التالت كانت اتنين هيها معناته
+
+770
+01:03:36,460 --> 01:03:40,240
+انا بدي اخد الاحتمال تبع ال rowللـ class الأول
+
+771
+01:03:40,240 --> 01:03:49,580
+معناته أنا بدي أضرب القيم اللي عليها تحتها
+
+772
+01:03:49,580 --> 01:03:55,160
+الخط هذه في بعضها ال probability تبعتي الواحد
+
+773
+01:03:55,160 --> 01:03:59,160
+أربعة على عشرة مضروبة في ال probability واحد على
+
+774
+01:03:59,160 --> 01:04:03,440
+واحد اللي هي attribute A1 equal واحد على واحد
+
+775
+01:04:03,440 --> 01:04:10,760
+مضروبة في ال probability A1A2 equal 1 على 1 مضروبة
+
+776
+01:04:10,760 --> 01:04:15,000
+في ال probability ال
+
+777
+01:04:15,000 --> 01:04:18,280
+probability للواحد as class مضروبة في ال
+
+778
+01:04:18,280 --> 01:04:23,440
+probability لل A1 equal 1 على 1 مضروبة في ال
+
+779
+01:04:23,440 --> 01:04:29,860
+probability لل A2 equal 1 على 1 مضروبة في ال
+
+780
+01:04:29,860 --> 01:04:36,420
+probability تبعت ال A3 equal2 على الواحد اللي هي
+
+781
+01:04:36,420 --> 01:04:39,640
+القيم اللي انا حددتها هيها هذا بجيبها لل class
+
+782
+01:04:39,640 --> 01:04:42,320
+الأول بجيبها لل class التاني بجيبها لل class
+
+783
+01:04:42,320 --> 01:04:47,160
+التالت و من ثم هاي
+
+784
+01:04:47,160 --> 01:04:52,300
+الحسبة اللي موجودة عندي الآن بدور على ال maximum
+
+785
+01:04:52,300 --> 01:05:00,970
+عندي 25 من ألف أربعة وأربعين250 من عشرة ألاف و 444
+
+786
+01:05:00,970 --> 01:05:05,150
+من عشرة ألاف و 111 من عشرة ألاف ال most
+
+787
+01:05:05,150 --> 01:05:10,610
+probability تبعتي و ال maximum probability أربعة
+
+788
+01:05:10,610 --> 01:05:14,050
+من مية أكيد أكبر من اتنين من مية و أكبر من واحد من
+
+789
+01:05:14,050 --> 01:05:18,850
+مية وبالتالي أغلب الظن ان هذه ال instance هتتصنف
+
+790
+01:05:18,850 --> 01:05:23,750
+مع ال class التاني مع ال class التاني لكن أنا
+
+791
+01:05:23,750 --> 01:05:30,560
+انتبهت لشغلة و أنا بقى أشتغل في الحسبةو هي ان ال
+
+792
+01:05:30,560 --> 01:05:38,820
+instances اللي أنا كتبتها موجودة بس
+
+793
+01:05:38,820 --> 01:05:43,670
+ايش ال class تبعتها؟تلاتة يعني صار في عندي
+
+794
+01:05:43,670 --> 01:05:47,170
+misclassification هل هذه مسئوليتي؟ لا مش مسئوليتي
+
+795
+01:05:47,170 --> 01:05:52,310
+انا اشتغلت عليها لان اخضعتها لاحتمالات تمام و هذه
+
+796
+01:05:52,310 --> 01:05:55,770
+وزنها كان واحدة من العناصر اللي موجودة لكن ال node
+
+797
+01:05:55,770 --> 01:05:58,170
+تبعتي هذه حسب الاحتمالات او حسب ال naive bison
+
+798
+01:05:58,170 --> 01:06:03,950
+بتطلع لمين؟ مع العنصر ال class two اللي موجود
+
+799
+01:06:03,950 --> 01:06:09,130
+عندهاالأن زي ما قلنا الـ Naive Bison ختاما للكلام
+
+800
+01:06:09,130 --> 01:06:11,950
+اللي احنا اشتغلناه طبعا جامعة الخير في انكو data
+
+801
+01:06:11,950 --> 01:06:15,210
+set موجودة سابقا في ال examples السابقات جربوا
+
+802
+01:06:15,210 --> 01:06:18,050
+عليها Naive Bison ما تستناش ما تقوليش ملون بدي
+
+803
+01:06:18,050 --> 01:06:20,270
+اسئلة في عندك ال data set اللي موجود في ال slides
+
+804
+01:06:20,270 --> 01:06:23,960
+و اللي انا اشتغلت عليها سابقاكـClassifier في عنده
+
+805
+01:06:23,960 --> 01:06:25,960
+strict assumptions زي ما قلنا about ال data اللي
+
+806
+01:06:25,960 --> 01:06:28,400
+هو ال independent attributes و ال normal
+
+807
+01:06:28,400 --> 01:06:32,920
+distribution تبع ال data اللي موجودة وهذا بيخليه
+
+808
+01:06:32,920 --> 01:06:35,920
+fast .. very fast أو extremely fast في ال training
+
+809
+01:06:35,920 --> 01:06:38,060
+و في ال prediction في ال training لأنه بيبني
+
+810
+01:06:38,060 --> 01:06:41,020
+الجدول مرة واحدة و في ال prediction مفيش .. يعني
+
+811
+01:06:41,020 --> 01:06:43,540
+ال competition تبعت قليلة straightforward
+
+812
+01:06:43,540 --> 01:06:47,900
+probabilistic prediction بيعتمد على ال
+
+813
+01:06:47,900 --> 01:06:52,640
+probabilities تماما على الاحتمالاتسهل جدا اني افسر
+
+814
+01:06:52,640 --> 01:06:58,620
+ليش طلع هيك مش بحاجة ان اعمل tuning لاني parameter
+
+815
+01:06:58,620 --> 01:07:06,120
+لان فعليا انا ماشوفتش اي حاجة بيطلب مني بما
+
+816
+01:07:06,120 --> 01:07:12,360
+انه في عندي strict and
+
+817
+01:07:12,360 --> 01:07:17,040
+complicated
+
+818
+01:07:17,040 --> 01:07:22,370
+modelفعليا الـ Naive Bison زي ما حنا شوفنا في
+
+819
+01:07:22,370 --> 01:07:30,490
+حسبته سهل نعم لكنه مش سهل ان اطبقه في كل مكان طبعا
+
+820
+01:07:30,490 --> 01:07:35,690
+ماهي المطلوب ان انا فعليا وين انا بدي اروح اطبق
+
+821
+01:07:35,690 --> 01:07:38,330
+الـ Naive Bison فعليا انا بقدر اروح استخدمه او
+
+822
+01:07:38,330 --> 01:07:40,990
+ممكن اشتغل كويس لما يكون الـ Naive Assumption
+
+823
+01:07:40,990 --> 01:07:46,240
+فعليا موجودة مع ال data يعني بين جثينان انا شبه
+
+824
+01:07:46,240 --> 01:07:49,320
+متأكد ان ال attributes اللى عندى كلها independent
+
+825
+01:07:49,320 --> 01:07:53,740
+attributes لكن انت الكلام متأكد منه ولا مش متأكد
+
+826
+01:07:53,740 --> 01:07:57,840
+منه؟ مابعرفش، مابيش الحل كيف بتتأكد من ال
+
+827
+01:07:57,840 --> 01:08:00,740
+dependency من ال attributes؟ بدك ترجع لل data
+
+828
+01:08:00,740 --> 01:08:03,940
+preparation و تفحص ال correlation ما بين ال
+
+829
+01:08:03,940 --> 01:08:07,600
+attributes و زى ما شوفنا في عندنا ال chi-square و
+
+830
+01:08:07,600 --> 01:08:12,230
+في عندنا ال اش كمان؟الـ Pearson coefficient إلى
+
+831
+01:08:12,230 --> 01:08:16,010
+آخره هو بناءً على هيك انت بتصير تدور على تفهم ال
+
+832
+01:08:16,010 --> 01:08:19,310
+data set أكتر very well separated categories لما
+
+833
+01:08:19,310 --> 01:08:22,350
+يكون ال categories اللي عنده فعليًا finite و
+
+834
+01:08:22,350 --> 01:08:26,130
+مفصلين عن بعض مافيش بينهم يعني بين جثين ال data
+
+835
+01:08:26,130 --> 01:08:29,830
+set بتفرج بشكل كويس و احنا لاحظين في المثال السابق
+
+836
+01:08:29,830 --> 01:08:33,070
+انه فعليًا عمل misclassification لل point اللي
+
+837
+01:08:33,070 --> 01:08:36,870
+موجودة عندها very high dimensional data لما تكون
+
+838
+01:08:36,870 --> 01:08:41,870
+ال data تبعتيالعالية جدا او فيها عدد كبير من ال
+
+839
+01:08:41,870 --> 01:08:45,630
+attributes ممكن انا اشتغل اخر شغلة في محاضرتنا هي
+
+840
+01:08:45,630 --> 01:08:49,270
+ال code ال code ال bython المفروض اللي انا بدي
+
+841
+01:08:49,270 --> 01:08:52,310
+اشتغله على السريع في code ال bython اللي موجود
+
+842
+01:08:52,310 --> 01:08:55,810
+عندي اعملت import لل data set فصلت ال features
+
+843
+01:08:55,810 --> 01:08:59,770
+حددت ال labels كما المثال السابق تماما مع ال naive
+
+844
+01:08:59,770 --> 01:09:03,590
+byes يعني مع ال kenyar snapperتمام؟ هذا شغل ال
+
+845
+01:09:03,590 --> 01:09:07,530
+data set احضار ال data set from ال k .. ال sklearn
+
+846
+01:09:07,530 --> 01:09:12,390
+.naive biased import gaussian لما قلتلكوا في عندي
+
+847
+01:09:12,390 --> 01:09:14,990
+توزيع طبيعي أو ال gaussian distribution الموجود في
+
+848
+01:09:14,990 --> 01:09:19,430
+ال .. هذا ال assumption تبعتي الأساسية as ..
+
+849
+01:09:19,430 --> 01:09:23,070
+حطيتله alias name هنا بنيت عليه model و قلتله اعمل
+
+850
+01:09:23,070 --> 01:09:27,170
+training على ال feature و ال label هذا الكلام
+
+851
+01:09:27,170 --> 01:09:32,010
+ماكانش موجود إذا بتتذكره وينفي ال data set او مع
+
+852
+01:09:32,010 --> 01:09:35,770
+.. عفوا مع ال canary snapper فالان اوجد العلاقة ما
+
+853
+01:09:35,770 --> 01:09:39,790
+بين ال features و ال labels بنجو سينت بنى جدول
+
+854
+01:09:39,790 --> 01:09:43,650
+الاحتمالات اللى بدناها قبل شوية و لما هى اللى
+
+855
+01:09:43,650 --> 01:09:47,390
+قلتله هى فى عندى test sample روح اعملهايها و روح
+
+856
+01:09:47,390 --> 01:09:50,450
+اعملها prediction فلما راح اعملها prediction
+
+857
+01:09:50,450 --> 01:09:54,470
+هيديني ال label تبعتها بناء على جدول الاحتمالات
+
+858
+01:09:54,470 --> 01:09:59,180
+اللى حصل منها فى حد فيكوا بيتذكرفي مرحلة الـ
+
+859
+01:09:59,180 --> 01:10:01,080
+Prediction مع الـ Canary Snapper أشكال اللي بيطلع
+
+860
+01:10:01,080 --> 01:10:01,420
+معايا
+
+861
+01:10:05,300 --> 01:10:08,140
+لأ بالزمكوا المراجعة دي باستمرار عشان تتذكروا
+
+862
+01:10:08,140 --> 01:10:11,620
+وبهيك .. لأ انا بذكرك انه كان بيديني ال distances
+
+863
+01:10:11,620 --> 01:10:15,340
+بيديني ال shortest five distance او shortest k
+
+864
+01:10:15,340 --> 01:10:20,280
+distances و ال index تبعت ال attributes تبعتها هذا
+
+865
+01:10:20,280 --> 01:10:24,020
+مثال بتمنى موجود معاكم وموجود بين اديكم بال slides
+
+866
+01:10:24,020 --> 01:10:27,200
+مثال ال golf السابق اللي احنا شوفناه روحوا طبقوا
+
+867
+01:10:27,200 --> 01:10:28,560
+عليه ال ..
+
+868
+01:10:31,690 --> 01:10:34,870
+الـ Naive Bison Algorithm وبدو اشتغلوا بحيث انكوا
+
+869
+01:10:34,870 --> 01:10:38,750
+تفهموا اللي موجود هنا في الختام بدي اذكر انه في
+
+870
+01:10:38,750 --> 01:10:44,050
+عندنا forum موجود منتده حواري على الموضل لأي سؤال
+
+871
+01:10:44,050 --> 01:10:47,950
+لكل محاضراتنا باستمرار فإذا في عندك او عندك اي
+
+872
+01:10:47,950 --> 01:10:52,180
+سؤالمشكورين اضيفوا السؤال على ال forum وانا ان شاء
+
+873
+01:10:52,180 --> 01:10:56,120
+الله تعالى برد عليكوا بالإجابة الشافية اللى
+
+874
+01:10:56,120 --> 01:10:59,380
+بترضيكوا بإذن الله تبارك وتعالى بتمنى لكوا السلامة
+
+875
+01:10:59,380 --> 01:11:02,560
+دوما والسلام عليكم ورحمة الله والمحاضرة الجاية
+
+876
+01:11:02,560 --> 01:11:06,300
+بنكمل في decision algorithm يعطيكم العافية
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/dTOEQghcXrk_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/dTOEQghcXrk_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..70d658aa112609005581668a313e6d2b104c6fe2
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/dTOEQghcXrk_raw.json
@@ -0,0 +1 @@
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"بالمثال اللي عندي الان ال transaction واحد هي ال ID واحد بيحتوي على تلت عناصر milk و bread و eggs ال transaction سبعة هي بيحتوي على milk و حبوب الإفطار", "tokens": [3555, 45340, 12984, 6027, 13672, 1829, 18871, 16254, 2423, 7649, 2423, 14425, 36764, 24401, 39896, 2423, 7348, 36764, 24401, 4724, 1829, 33753, 45865, 15844, 6055, 1211, 2655, 18871, 33546, 2288, 5392, 4032, 5961, 4032, 6466, 2423, 14425, 8608, 3555, 27884, 39896, 4724, 1829, 33753, 45865, 15844, 5392, 4032, 11331, 3555, 37746, 33688, 5172, 9566, 9640], "avg_logprob": -0.21442521629588945, "compression_ratio": 1.5675675675675675, "no_speech_prob": 0.0, "words": [{"start": 695.33, "end": 695.93, "word": "بالمثال", "probability": 0.8856201171875}, {"start": 695.93, "end": 696.07, "word": " اللي", "probability": 0.68017578125}, {"start": 696.07, "end": 696.41, "word": " عندي", "probability": 0.80126953125}, {"start": 696.41, "end": 697.85, "word": " الان", "probability": 0.47412109375}, {"start": 697.85, "end": 698.41, 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عبارة عن مجموعة بتحتوي على K من ال items يعني لما قلت انا ال three item set معناته انا بتكلم على مجموعة مكونة من تلت عناصر four item set four item set عفوا ال set of four items و هكذا", "tokens": [6027, 39184, 591, 3174, 992, 20449, 8315, 47395, 39896, 6225, 3555, 9640, 3660, 18871, 3714, 7435, 2304, 2407, 27884, 39894, 33753, 45865, 15844, 591, 9154, 2423, 4754, 37495, 22653, 5296, 15042, 12174, 1211, 2655, 1975, 8315, 2423, 1045, 3174, 992, 20449, 8315, 47395, 1975, 8315, 39894, 4117, 19528, 15844, 3714, 7435, 2304, 2407, 27884, 3714, 30544, 3660, 9154, 6055, 1211, 2655, 18871, 33546, 2288, 1451, 3174, 992, 1451, 3174, 992, 6225, 5172, 14407, 2423, 992, 295, 1451, 4754, 4032, 8032, 4117, 15730], "avg_logprob": -0.22307981999523668, "compression_ratio": 1.8070175438596492, "no_speech_prob": 0.0, "words": [{"start": 776.05, "end": 776.25, "word": "الـ", "probability": 0.6029052734375}, {"start": 776.25, "end": 776.35, "word": " K", "probability": 0.5869140625}, {"start": 776.35, "end": 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عدد مرات ظهور ال X تمام على ال cardinality تبع ال data set اللى موجودة عندى", "tokens": [4117, 8848, 23275, 8978, 43242, 7578, 3714, 9381, 9566, 1211, 5016, 24525, 2304, 3224, 4972, 1406, 4972, 1406, 309, 311, 257, 14135, 5296, 15042, 1975, 2655, 4117, 19528, 15844, 14135, 20449, 8315, 47395, 6225, 3555, 9640, 3660, 18871, 12174, 32640, 3660, 1975, 2407, 8717, 35457, 3660, 46811, 10943, 295, 264, 14425, 300, 8306, 1783, 6225, 3215, 3215, 3714, 2288, 9307, 1357, 116, 3224, 13063, 2423, 1783, 46811, 10943, 15844, 2423, 2920, 259, 1860, 6055, 3555, 3615, 2423, 1412, 992, 13672, 7578, 3714, 29245, 23328, 3660, 43242, 7578], "avg_logprob": -0.20951704122126102, "compression_ratio": 1.5339366515837105, "no_speech_prob": 0.0, "words": [{"start": 827.01, "end": 827.51, "word": "كذلك", "probability": 0.7533365885416666}, {"start": 827.51, "end": 827.67, "word": " في", "probability": 0.32763671875}, {"start": 827.67, "end": 827.93, "word": " عندى", "probability": 0.52392578125}, {"start": 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"word": " rule", "probability": 0.845703125}, {"start": 1348.57, "end": 1349.65, "word": " و", "probability": 0.71142578125}, {"start": 1349.65, "end": 1349.89, "word": " بدى", "probability": 0.704345703125}, {"start": 1349.89, "end": 1350.23, "word": " احسب", "probability": 0.8863932291666666}, {"start": 1350.23, "end": 1350.39, "word": " ال", "probability": 0.86181640625}, {"start": 1350.39, "end": 1351.03, "word": " support", "probability": 0.9931640625}, {"start": 1351.03, "end": 1354.89, "word": " هان", "probability": 0.489990234375}, {"start": 1354.89, "end": 1356.25, "word": " مباشرة", "probability": 0.9747314453125}, {"start": 1356.25, "end": 1356.55, "word": " بدى", "probability": 0.819091796875}, {"start": 1356.55, "end": 1356.71, "word": " اروح", "probability": 0.8024088541666666}, {"start": 1356.71, "end": 1357.07, "word": " اخد", "probability": 0.8359375}, {"start": 1357.07, "end": 1357.21, "word": " ال", "probability": 0.9638671875}, {"start": 1357.21, "end": 1357.75, "word": " elements", "probability": 0.8662109375}, {"start": 1357.75, "end": 1358.69, "word": " اتحاد", "probability": 0.951416015625}, {"start": 1358.69, "end": 1358.83, "word": " ال", "probability": 0.77587890625}, {"start": 1358.83, "end": 1359.11, "word": " b", "probability": 0.7021484375}, {"start": 1359.11, "end": 1361.15, "word": " ليش", "probability": 0.94482421875}, {"start": 1361.15, "end": 1361.27, "word": " ال", "probability": 0.88720703125}, {"start": 1361.27, "end": 1361.57, "word": " items", "probability": 0.90185546875}, {"start": 1361.57, "end": 1361.87, "word": " اللى", "probability": 0.8046875}, {"start": 1361.87, "end": 1362.39, "word": " موجودة", "probability": 0.959228515625}, {"start": 1362.39, "end": 1362.81, "word": " عندى", "probability": 0.936767578125}, {"start": 1362.81, "end": 1364.49, "word": " milk", "probability": 0.8046875}], "temperature": 1.0}, {"id": 56, "seek": 139662, "start": 1367.94, "end": 1396.62, "text": "و bread عفوا و cereal و sugar مظبوط الان روح نعد ال elements هذول و الموجودات مع بعض موجودات مع بعض هي هم هان ولا مرة zero طبعا اشتغلت بشكل عشوائي خلينا نقول ال milk و ال bread", "tokens": [2407, 5961, 6225, 5172, 14407, 4032, 26199, 4032, 5076, 3714, 19913, 3555, 2407, 9566, 2423, 7649, 12602, 2407, 5016, 8717, 22488, 2423, 4959, 8032, 8848, 12610, 4032, 9673, 29245, 23328, 9307, 20449, 45030, 11242, 3714, 29245, 23328, 9307, 20449, 45030, 11242, 39896, 8032, 2304, 8032, 7649, 49429, 3714, 25720, 4018, 23032, 3555, 3615, 995, 1975, 8592, 2655, 17082, 1211, 2655, 4724, 8592, 28820, 6225, 8592, 2407, 16373, 1829, 16490, 1211, 9957, 995, 8717, 39648, 2423, 5392, 4032, 2423, 5961], "avg_logprob": -0.298632824420929, "compression_ratio": 1.5191256830601092, "no_speech_prob": 0.0, "words": [{"start": 1367.94, "end": 1368.28, "word": "و", "probability": 0.19384765625}, {"start": 1368.28, "end": 1368.8, "word": " bread", "probability": 0.1483154296875}, {"start": 1368.8, "end": 1370.18, "word": " عفوا", "probability": 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{"start": 1381.34, "end": 1381.84, "word": " الموجودات", "probability": 0.951416015625}, {"start": 1381.84, "end": 1381.98, "word": " مع", "probability": 0.9921875}, {"start": 1381.98, "end": 1382.64, "word": " بعض", "probability": 0.994140625}, {"start": 1382.64, "end": 1384.12, "word": " موجودات", "probability": 0.774505615234375}, {"start": 1384.12, "end": 1384.28, "word": " مع", "probability": 0.9912109375}, {"start": 1384.28, "end": 1384.64, "word": " بعض", "probability": 0.99658203125}, {"start": 1384.64, "end": 1384.98, "word": " هي", "probability": 0.386962890625}, {"start": 1384.98, "end": 1385.32, "word": " هم", "probability": 0.84716796875}, {"start": 1385.32, "end": 1386.4, "word": " هان", "probability": 0.67822265625}, {"start": 1386.4, "end": 1388.26, "word": " ولا", "probability": 0.8076171875}, {"start": 1388.26, "end": 1388.92, "word": " مرة", "probability": 0.97412109375}, {"start": 1388.92, "end": 1390.24, "word": " zero", "probability": 0.36279296875}, {"start": 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bread association with bread هروح اخد ال two elements هدول milk و bread هي واحد milk و bread هي اتنين milk و bread هي تلاتة milk و bread هي اربعة معناته اربعة على تسعة بينما كان في الأول zero على تسعة يعني انا دائما بدي اخداش", "tokens": [28674, 74, 9134, 5961, 14598, 365, 5961, 8032, 32887, 5016, 1975, 9778, 3215, 2423, 732, 4959, 8032, 3215, 12610, 5392, 4032, 5961, 39896, 36764, 24401, 5392, 4032, 5961, 39896, 1975, 2655, 1863, 9957, 5392, 4032, 5961, 39896, 6055, 1211, 9307, 3660, 5392, 4032, 5961, 39896, 1975, 25513, 27884, 20449, 8315, 47395, 1975, 25513, 27884, 15844, 6055, 3794, 27884, 49374, 15042, 25961, 8978, 16247, 12610, 4018, 15844, 6055, 3794, 27884, 37495, 22653, 1975, 8315, 11778, 16373, 15042, 4724, 16254, 1975, 9778, 3215, 33599], "avg_logprob": -0.31664157344634275, "compression_ratio": 1.8324324324324324, "no_speech_prob": 0.0, "words": [{"start": 1400.92, "end": 1401.74, "word": "milk", "probability": 0.554656982421875}, {"start": 1401.74, "end": 1402.56, "word": 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"probability": 0.373291015625}, {"start": 1410.9, "end": 1411.14, "word": " bread", "probability": 0.8388671875}, {"start": 1411.14, "end": 1411.38, "word": " هي", "probability": 0.716796875}, {"start": 1411.38, "end": 1412.02, "word": " واحد", "probability": 0.973388671875}, {"start": 1412.02, "end": 1412.4, "word": " milk", "probability": 0.193603515625}, {"start": 1412.4, "end": 1412.88, "word": " و", "probability": 0.98291015625}, {"start": 1412.88, "end": 1413.16, "word": " bread", "probability": 0.93603515625}, {"start": 1413.16, "end": 1413.4, "word": " هي", "probability": 0.91943359375}, {"start": 1413.4, "end": 1414.16, "word": " اتنين", "probability": 0.951171875}, {"start": 1414.16, "end": 1414.58, "word": " milk", "probability": 0.58154296875}, {"start": 1414.58, "end": 1414.92, "word": " و", "probability": 0.99169921875}, {"start": 1414.92, "end": 1415.22, "word": " bread", "probability": 0.94580078125}, {"start": 1415.22, "end": 1415.5, "word": " هي", "probability": 0.908203125}, {"start": 1415.5, "end": 1416.26, "word": " تلاتة", "probability": 0.9290771484375}, {"start": 1416.26, "end": 1416.6, "word": " milk", "probability": 0.82568359375}, {"start": 1416.6, "end": 1416.88, "word": " و", "probability": 0.994140625}, {"start": 1416.88, "end": 1417.08, "word": " bread", "probability": 0.9541015625}, {"start": 1417.08, "end": 1417.32, "word": " هي", "probability": 0.90478515625}, {"start": 1417.32, "end": 1417.84, "word": " اربعة", "probability": 0.8328450520833334}, {"start": 1417.84, "end": 1418.64, "word": " معناته", "probability": 0.7654622395833334}, {"start": 1418.64, "end": 1419.38, "word": " اربعة", "probability": 0.8444010416666666}, {"start": 1419.38, "end": 1419.86, "word": " على", "probability": 0.6357421875}, {"start": 1419.86, "end": 1420.7, "word": " تسعة", "probability": 0.9871419270833334}, {"start": 1420.7, "end": 1421.32, "word": " بينما", "probability": 0.9208984375}, {"start": 1421.32, "end": 1421.56, "word": " كان", "probability": 0.92822265625}, {"start": 1421.56, "end": 1421.66, "word": " في", "probability": 0.87890625}, {"start": 1421.66, "end": 1422.04, "word": " الأول", "probability": 0.74267578125}, {"start": 1422.04, "end": 1422.42, "word": " zero", "probability": 0.3310546875}, {"start": 1422.42, "end": 1422.74, "word": " على", "probability": 0.78515625}, {"start": 1422.74, "end": 1423.52, "word": " تسعة", "probability": 0.9814453125}, {"start": 1423.52, "end": 1424.1, "word": " يعني", "probability": 0.891845703125}, {"start": 1424.1, "end": 1424.3, "word": " انا", "probability": 0.838134765625}, {"start": 1424.3, "end": 1424.7, "word": " دائما", "probability": 0.8372395833333334}, {"start": 1424.7, "end": 1424.96, "word": " بدي", "probability": 0.6904296875}, {"start": 1424.96, "end": 1425.6, "word": " اخداش", "probability": 0.67242431640625}], "temperature": 1.0}, {"id": 58, "seek": 145476, "start": 1425.94, "end": 1454.76, "text": "بدي أخد ال relative support بناء على أعداد ال elements اللي موجودة هنا عشان هيك دائما بنلاقي انه ال probability للاتحاد عدد بقى مرات ظهورهم وهذا هو اللي بنسميه ال relative support ال relative support اللي بنرمزله بال S", "tokens": [3555, 16254, 5551, 9778, 3215, 2423, 4972, 1406, 44945, 16606, 15844, 5551, 22488, 18513, 2423, 4959, 13672, 1829, 3714, 29245, 23328, 3660, 34105, 6225, 8592, 7649, 39896, 4117, 11778, 16373, 15042, 44945, 15040, 38436, 16472, 3224, 2423, 8482, 24976, 9307, 5016, 18513, 6225, 3215, 3215, 4724, 4587, 7578, 3714, 2288, 9307, 1357, 116, 3224, 13063, 16095, 37037, 15730, 31439, 13672, 1829, 44945, 38251, 1829, 3224, 2423, 4972, 1406, 2423, 4972, 1406, 13672, 1829, 44945, 2288, 2304, 11622, 43761, 20666, 318], "avg_logprob": -0.3283178953476894, "compression_ratio": 1.6818181818181819, "no_speech_prob": 0.0, "words": [{"start": 1425.94, "end": 1426.3, "word": "بدي", "probability": 0.213623046875}, {"start": 1426.3, "end": 1426.82, "word": " أخد", "probability": 0.657958984375}, {"start": 1426.82, "end": 1427.06, 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1433.7, "word": " هيك", "probability": 0.856201171875}, {"start": 1433.7, "end": 1434.46, "word": " دائما", "probability": 0.8063151041666666}, {"start": 1434.46, "end": 1435.0, "word": " بنلاقي", "probability": 0.80517578125}, {"start": 1435.0, "end": 1435.74, "word": " انه", "probability": 0.70263671875}, {"start": 1435.74, "end": 1436.34, "word": " ال", "probability": 0.4267578125}, {"start": 1436.34, "end": 1442.56, "word": " probability", "probability": 0.40576171875}, {"start": 1442.56, "end": 1444.3, "word": " للاتحاد", "probability": 0.81829833984375}, {"start": 1444.3, "end": 1444.62, "word": " عدد", "probability": 0.7574055989583334}, {"start": 1444.62, "end": 1444.86, "word": " بقى", "probability": 0.7762044270833334}, {"start": 1444.86, "end": 1445.26, "word": " مرات", "probability": 0.8662109375}, {"start": 1445.26, "end": 1445.9, "word": " ظهورهم", "probability": 0.815576171875}, {"start": 1445.9, "end": 1446.38, "word": " وهذا", "probability": 0.7197265625}, {"start": 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"temperature": 1.0}, {"id": 67, "seek": 167452, "start": 1658.2, "end": 1674.52, "text": "إذا كانت الـ item set اللي عندي تجاوزت", "tokens": [28814, 15730, 25961, 2655, 2423, 39184, 3174, 992, 13672, 1829, 18871, 16254, 6055, 7435, 995, 2407, 11622, 2655], "avg_logprob": -0.4983552819804141, "compression_ratio": 0.9841269841269841, "no_speech_prob": 0.0, "words": [{"start": 1658.2, "end": 1658.72, "word": "إذا", "probability": 0.620361328125}, {"start": 1658.72, "end": 1669.72, "word": " كانت", "probability": 0.760498046875}, {"start": 1669.72, "end": 1669.86, "word": " الـ", "probability": 0.3231201171875}, {"start": 1669.86, "end": 1670.88, "word": " item", "probability": 0.560546875}, {"start": 1670.88, "end": 1671.24, "word": " set", "probability": 0.281494140625}, {"start": 1671.24, "end": 1671.44, "word": " اللي", "probability": 0.6358642578125}, {"start": 1671.44, "end": 1671.84, "word": " عندي", "probability": 0.7342529296875}, {"start": 1671.84, "end": 1674.52, "word": " 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{"start": 2064.19, "end": 2064.67, "word": " هي", "probability": 0.57861328125}, {"start": 2064.67, "end": 2065.07, "word": " عبارة", "probability": 0.970947265625}, {"start": 2065.07, "end": 2065.19, "word": " عن", "probability": 0.76318359375}, {"start": 2065.19, "end": 2065.31, "word": " أن", "probability": 0.158203125}, {"start": 2065.31, "end": 2065.35, "word": " الـ", "probability": 0.668701171875}, {"start": 2065.35, "end": 2065.63, "word": " support", "probability": 0.63916015625}, {"start": 2065.63, "end": 2066.11, "word": " تبعتها", "probability": 0.800537109375}, {"start": 2066.11, "end": 2066.55, "word": " أكبر", "probability": 0.91357421875}, {"start": 2066.55, "end": 2066.71, "word": " من", "probability": 0.98291015625}, {"start": 2066.71, "end": 2066.87, "word": " الـ", "probability": 0.828857421875}, {"start": 2066.87, "end": 2067.03, "word": " minimum", "probability": 0.5107421875}, {"start": 2067.03, "end": 2067.49, "word": " support", "probability": 0.98095703125}, {"start": 2067.49, "end": 2067.69, "word": " هي", "probability": 0.166748046875}, {"start": 2067.69, "end": 2068.19, "word": " من", "probability": 0.1298828125}, {"start": 2068.19, "end": 2068.63, "word": " هنا", "probability": 0.873046875}, {"start": 2068.63, "end": 2069.43, "word": " تمام", "probability": 0.6610107421875}, {"start": 2069.43, "end": 2069.89, "word": " و", "probability": 0.2252197265625}, {"start": 2069.89, "end": 2069.99, "word": " ال", "probability": 0.67626953125}, {"start": 2069.99, "end": 2070.39, "word": " confidence", "probability": 0.908203125}, {"start": 2070.39, "end": 2070.99, "word": " تبعتها", "probability": 0.935546875}, {"start": 2070.99, "end": 2071.31, "word": " أكبر", "probability": 0.9300130208333334}, {"start": 2071.31, "end": 2071.47, "word": " من", "probability": 0.98779296875}, {"start": 2071.47, "end": 2071.61, "word": " ال", "probability": 0.9228515625}, {"start": 2071.61, "end": 2071.87, "word": " minimum", "probability": 0.712890625}, {"start": 2071.87, "end": 2072.75, "word": " confidence", "probability": 0.429931640625}, {"start": 2072.75, "end": 2073.45, "word": " condition", "probability": 0.826171875}, {"start": 2073.45, "end": 2073.87, "word": " اللي", "probability": 0.6982421875}, {"start": 2073.87, "end": 2074.79, "word": " موجودة", "probability": 0.9442138671875}, {"start": 2074.79, "end": 2075.63, "word": " عندها", "probability": 0.901611328125}, {"start": 2075.63, "end": 2081.59, "word": " الأبريوري", "probability": 0.7072998046875}, {"start": 2081.59, "end": 2081.91, "word": " هو", "probability": 0.96240234375}, {"start": 2081.91, "end": 2082.39, "word": " عبارة", "probability": 0.9822998046875}, {"start": 2082.39, "end": 2082.93, "word": " عن", "probability": 0.9970703125}, {"start": 2082.93, "end": 2083.79, "word": " الأشهر", "probability": 0.896728515625}, {"start": 2083.79, "end": 2084.37, "word": " algorithm", "probability": 0.6083984375}, {"start": 2084.37, "end": 2085.05, "word": " موجود", "probability": 0.9296875}, {"start": 2085.05, "end": 2085.81, "word": " مع", "probability": 0.576171875}, {"start": 2085.81, "end": 2085.95, "word": " ال", "probability": 0.9716796875}, {"start": 2085.95, "end": 2086.39, "word": " association", "probability": 0.67529296875}, {"start": 2086.39, "end": 2086.87, "word": " rules", "probability": 0.826171875}, {"start": 2086.87, "end": 2087.47, "word": " حنتكلم", "probability": 0.7503509521484375}, {"start": 2087.47, "end": 2088.31, "word": " فيه", "probability": 0.935791015625}, {"start": 2088.31, "end": 2089.01, "word": " الأن", "probability": 0.79638671875}, {"start": 2089.01, "end": 2089.17, "word": " ان", "probability": 0.42626953125}, {"start": 2089.17, "end": 2089.33, "word": " شاء", "probability": 0.92041015625}, {"start": 2089.33, "end": 2089.39, "word": " الله", "probability": 0.96142578125}, {"start": 2089.39, "end": 2089.83, "word": " تبارك", "probability": 0.9364013671875}, {"start": 2089.83, "end": 2090.19, "word": " وتعالى", "probability": 0.82672119140625}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 2090.5621875, "duration_after_vad": 1947.903124999994}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/dY2Slj6BExM_postprocess.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/dY2Slj6BExM_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..4f4b0eac01a5012f59da96576004d70f724081b8
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+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/dY2Slj6BExM_postprocess.srt
@@ -0,0 +1,3464 @@
+1
+00:00:05,010 --> 00:00:07,150
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:07,150 --> 00:00:10,630
+اليوم إن شاء الله تعالى هنبدأ بالفعل بالفصل التاني
+
+3
+00:00:10,630 --> 00:00:13,970
+أو بال chapter التاني من مساق تنقيب البيانات واللي
+
+4
+00:00:13,970 --> 00:00:16,810
+هو عنوانه data understanding and preparation أو
+
+5
+00:00:16,810 --> 00:00:21,710
+البعض بيسميه data processing data preprocessing
+
+6
+00:00:21,710 --> 00:00:26,070
+فعليا ال chapter كله يتوحي محور حوالين فهم
+
+7
+00:00:26,070 --> 00:00:31,150
+البيانات وكيف ممكن أنا أجهزها لعملية ال mining وما
+
+8
+00:00:31,150 --> 00:00:35,860
+تنساش أنه لما ذكرنا وطبعا يعني بذكرك في ما مضىقلنا
+
+9
+00:00:35,860 --> 00:00:39,140
+إن عملية الـ Data Mining هي عبارة عن عملية مكونة
+
+10
+00:00:39,140 --> 00:00:45,340
+من 7 مراحل بتبدأ من Data Cleaning Data Selection
+
+11
+00:00:45,340 --> 00:00:50,180
+Data Integration ممتاز Data Selection Data
+
+12
+00:00:50,180 --> 00:00:54,360
+Transformation Data Mining Pattern Evaluation
+
+13
+00:00:54,360 --> 00:01:00,380
+Knowledge Presentation ولاحظ CleaningIntegration,
+
+14
+00:01:00,380 --> 00:01:04,700
+Selection, Transformation قاعد بتكلم على أربع
+
+15
+00:01:04,700 --> 00:01:10,080
+خطوات من سبعة بتكلموا على تجهيز البيانات فقط قبل
+
+16
+00:01:10,080 --> 00:01:14,260
+ال mining وبالتالي لازم يكون في عندنا شغل في
+
+17
+00:01:14,260 --> 00:01:18,400
+المرحلة هاي وال chapter هذا هو المعنى بيش بالجزئية
+
+18
+00:01:18,400 --> 00:01:22,140
+بسم الله نبدأ ال chapter اللي موجود عندنا عادة
+
+19
+00:01:22,140 --> 00:01:27,340
+جماعة الخير المفروض قبل ما أنا أبدأ أي شغلة أكون
+
+20
+00:01:27,340 --> 00:01:31,810
+في عندى تصور عنهاانت ليش جيت الجامعة؟ عشان والله
+
+21
+00:01:31,810 --> 00:01:35,730
+أنا بدي أدرس كذا IT، بدي أدرس طب، بدي أدرس هندسة
+
+22
+00:01:35,730 --> 00:01:41,550
+فبتيجي على الجامعة وانت فيه عندك هدف الهدف هذا انت
+
+23
+00:01:41,550 --> 00:01:48,350
+ماوصلتلهوش، انت بتسعى لتحقيقه وفرت كل الظروف
+
+24
+00:01:48,350 --> 00:01:52,510
+المناسبة لتحقيق الهدف بدءًا من دراستك في الثانوية
+
+25
+00:01:52,510 --> 00:01:56,790
+العامة يعني مش معقول واحد كان مثلا بدأ طب وكان
+
+26
+00:01:56,790 --> 00:02:00,920
+بنام على الساعة تمانيةأو بجد معظم وقته على الـ
+
+27
+00:02:00,920 --> 00:02:05,000
+PUBG، صح؟ فكان بيجتهد، بيجتهد بحيث أنه يجيب المعدل
+
+28
+00:02:05,000 --> 00:02:08,180
+اللي بيسمحله كلية الطب و في داخل كلية الطب بدأاش
+
+29
+00:02:08,180 --> 00:02:12,620
+يدرس و يجتهد لحد بعد سبع سنوات أو ست سنوات من
+
+30
+00:02:12,620 --> 00:02:18,200
+الدراسة بيتخرج بشهادة أو حصل على شهادة الطب الآن
+
+31
+00:02:18,200 --> 00:02:25,440
+كذلك ال gold miners المواقبين عن الذهب بيفهموا
+
+32
+00:02:25,440 --> 00:02:31,540
+تماما إيش هدفهمإنه يجمّع أكبر قدر ممكن من الدهب،
+
+33
+00:02:31,540 --> 00:02:35,960
+ممتاز وين بده يدور عليه؟ بديش على شط البحر عندنا
+
+34
+00:02:35,960 --> 00:02:40,400
+في غزة يدور على الدهب في أماكن محددة ومعروفة
+
+35
+00:02:40,400 --> 00:02:46,580
+عالميا وبنقبوا باستمرار فيها، تمام؟ وبالتالي، لازم
+
+36
+00:02:46,580 --> 00:02:50,600
+يكون في عندي معرفة واضحة للبيئة اللي أنا بدي أشتغل
+
+37
+00:02:50,600 --> 00:02:54,260
+فيها كذلك إحنا في الـ Data Mining، البيئة تبعتنا
+
+38
+00:02:54,260 --> 00:02:58,790
+مين؟الـ Data، البيانات وانا بدي أستخرج معرفة من
+
+39
+00:02:58,790 --> 00:03:03,770
+البيانات الآن الـ Miner لما بدي يروح يفحر نفق من
+
+40
+00:03:03,770 --> 00:03:09,210
+أجل التنقيب ماينفعش يفحره في تربة رملية، تمام؟
+
+41
+00:03:09,210 --> 00:03:12,510
+لازم تكون الجبل أو المنطقة اللي بدي يفحر فيها لها
+
+42
+00:03:12,510 --> 00:03:16,630
+مواصفات معينة على الأقل تلب الحد الأدنى من ال
+
+43
+00:03:16,630 --> 00:03:19,730
+safety له ولا بدي يطبق عليه ويموت وهو بنجّب عن
+
+44
+00:03:19,730 --> 00:03:24,250
+الدهب مش هتصبط الأمور فبالتالي لازم يكون فهم عميق
+
+45
+00:03:26,670 --> 00:03:29,510
+لـ Data Mining أو لـ Data Analysis اللي بتصير
+
+46
+00:03:29,510 --> 00:03:32,670
+عندنا هنا وبالتالي لازم أفهم .. أفهم البيانات اللي
+
+47
+00:03:32,670 --> 00:03:36,470
+موجودة عادة إحنا عندنا في عالم الـ Software في أي
+
+48
+00:03:36,470 --> 00:03:40,970
+نظام في أي نظام موجود عندنا في عندنا شغلتين
+
+49
+00:03:40,970 --> 00:03:46,070
+أساسيات الـ Input و الـ Output ال Input و ال
+
+50
+00:03:46,070 --> 00:03:49,330
+Output في الـ Data Mining كذلك في عندنا Input و
+
+51
+00:03:49,330 --> 00:03:53,780
+Output ال Input تبعنا هي الـ Data و ال Outputالـ
+
+52
+00:03:53,780 --> 00:03:56,700
+Knowledge أو الـ Pattern بن جوسين الـ Pattern هذا
+
+53
+00:03:56,700 --> 00:04:00,340
+هو الـ Knowledge تبعتي اللي بدأ أطلع فيها هل في
+
+54
+00:04:00,340 --> 00:04:05,000
+علاقة بين ال input و ال output؟ ليه يا مؤمن بتقول
+
+55
+00:04:05,000 --> 00:04:09,160
+لأ؟ لأ، في علاقة دائما بين ال input بس بجيت شكلك
+
+56
+00:04:09,160 --> 00:04:12,800
+بجيت أسرحت في السؤال أنت بعيد في علاقة واضحة بين
+
+57
+00:04:12,800 --> 00:04:16,780
+ال input و ال output و ناخد مثال بسيط الآن لو جيت
+
+58
+00:04:16,780 --> 00:04:20,280
+و قلتلك أنت as a developerبتعملّي function أو
+
+59
+00:04:20,280 --> 00:04:26,740
+method بتحسب صعب الراتب للموظفين شوف بزيكا ايش
+
+60
+00:04:26,740 --> 00:04:31,380
+بيلزمك بعيدا عن لغة البرمجة وكده وكده وكده ايش
+
+61
+00:04:31,380 --> 00:04:34,400
+اللي بيلزمك بلزمني ال input مجموعة ال argument
+
+62
+00:04:34,400 --> 00:04:39,090
+اللي انا بدي امررها لل function اللي هيبدي الراتب
+
+63
+00:04:39,090 --> 00:04:43,630
+الأساسي، إيش عنده علوات، جدش حجم الضريبة، جدش في
+
+64
+00:04:43,630 --> 00:04:47,350
+عليه ديون، تمام؟ أو مستقطعات، وبالتالي هدولة
+
+65
+00:04:47,350 --> 00:04:50,710
+كلهاتهم بدي أدخلهم على الـ function وداخل الـ
+
+66
+00:04:50,710 --> 00:04:52,950
+function أو بلاش قبل أن أتكلم عن داخل الـ function
+
+67
+00:04:52,950 --> 00:04:57,330
+خارج ال output من الـ function قيمة واحدة فقط،
+
+68
+00:04:57,330 --> 00:05:01,870
+صافر راتب، ممتاز، يعني في علاقة واضحة بين ال input
+
+69
+00:05:02,790 --> 00:05:05,870
+والـ output ال input بعد ما بنعملها processing
+
+70
+00:05:05,870 --> 00:05:10,910
+بتطلع عند ال output جزئية ال processing هي مبنية
+
+71
+00:05:10,910 --> 00:05:14,830
+كذلك على فهمك لل input لما بروح بيجي و بقولك على
+
+72
+00:05:14,830 --> 00:05:20,630
+سبيل المثال صافر راتب هو يساوي صافر راتب مضيوفه
+
+73
+00:05:20,630 --> 00:05:24,070
+العلوات ال commission مخصومة منه الضريبة تمام
+
+74
+00:05:24,070 --> 00:05:26,790
+ومطروحة منه الاستحقاقات اللي عليه أو الديون
+
+75
+00:05:26,790 --> 00:05:30,850
+الموجودة عليه شو بتساوي؟ مافيش مجال ال
+
+76
+00:05:30,850 --> 00:05:36,340
+implementation لهاطريقة واحدة الـ Basic Salary
+
+77
+00:05:36,340 --> 00:05:40,960
+تساوي الـ Basic Salary ضارب قيمة الضريبة، مظبوط
+
+78
+00:05:40,960 --> 00:05:44,620
+زائد الـ Commission ناقص الاستقطاعات اللي موجودة
+
+79
+00:05:44,620 --> 00:05:49,380
+في مجال تعمل implementation غير هيك؟ كيف يا مؤمن؟
+
+80
+00:05:49,380 --> 00:05:53,900
+مافي مجال، معناه تقريبا شكل مش فاهم عليك أنا اليوم
+
+81
+00:05:53,900 --> 00:05:58,840
+خليكي مركز معايا، تمام؟ الآن مافيش مجال، طب همش
+
+82
+00:05:58,840 --> 00:06:02,420
+المعادلة هاي أنت كتبتها على مزاجكولا انحكمتي
+
+83
+00:06:02,420 --> 00:06:05,680
+بقوانين انحكمتي بقانون المؤسسة كيف تحسب الراتب
+
+84
+00:06:05,680 --> 00:06:13,060
+وهنا نفس الكلام في ال data mining بشكل عام و بال
+
+85
+00:06:13,060 --> 00:06:18,740
+machine learning بشكل خاص تمام؟ ليش؟ لأنه الآن في
+
+86
+00:06:18,740 --> 00:06:21,360
+الجزئيات في ال mining هستخدم machine learning
+
+87
+00:06:21,360 --> 00:06:25,890
+algorithm ال algorithm هذا هياخد منيالـ input الـ
+
+88
+00:06:25,890 --> 00:06:29,310
+data و يدّيني pattern فهيروح يعملها analysis
+
+89
+00:06:29,310 --> 00:06:32,950
+اختيار لعملية ال analysis و التحليل الهدف لازم
+
+90
+00:06:32,950 --> 00:06:37,550
+يكون يتوافق مع ال output المرجو وبالتالي أنا هنا
+
+91
+00:06:37,550 --> 00:06:40,450
+لازم يكون أفهم العلاقة إيش ال input و ال output
+
+92
+00:06:40,450 --> 00:06:46,070
+أكثر من أي شغلة من المعرفة إيه إيش بدو يصير في
+
+93
+00:06:46,070 --> 00:06:49,310
+بينهم لأن غالبا في ال implementation أنا مش هتعب
+
+94
+00:06:49,310 --> 00:06:53,920
+رأس كتير هيدوني ال formulaوأكتبها الصبر وكان الله
+
+95
+00:06:53,920 --> 00:06:56,460
+بالسر عليهم، مظبوط؟ في الـ .. في الـ Machine
+
+96
+00:06:56,460 --> 00:06:59,240
+Learning أو في الـ Data Mining بدي أفهم الـ Input
+
+97
+00:06:59,240 --> 00:07:03,320
+و أفهم الـ Output و أختار Algorithm من الـ Machine
+
+98
+00:07:03,320 --> 00:07:06,960
+Learning يكون مناسب لل task و أقول له اتفضل، هو
+
+99
+00:07:06,960 --> 00:07:10,460
+اللي بدي يعمل Analysis يعني أنا فعلياً ماليش علاقة
+
+100
+00:07:10,460 --> 00:07:15,920
+كبيرة كيف آلة الـ Input للـ Output بس إلي علاقة
+
+101
+00:07:15,920 --> 00:07:20,440
+إنه فعلياً بدي أحدد Input لتناسب مع الـ Output
+
+102
+00:07:20,440 --> 00:07:20,880
+المرجو
+
+103
+00:07:23,440 --> 00:07:27,440
+كذلك بالنسبة للـ preparation أنا متكلم في الان في
+
+104
+00:07:27,440 --> 00:07:29,680
+ال data understanding ليش مهمة في ال data
+
+105
+00:07:29,680 --> 00:07:34,120
+preparation معروف عندنا مصطلح في عالم البرامجيات
+
+106
+00:07:34,120 --> 00:07:40,100
+garbage in garbage out عمركاش تتوقع أن يكون في
+
+107
+00:07:40,100 --> 00:07:43,720
+عندي result محترمة إذا كانت ال input اللي عنده
+
+108
+00:07:43,720 --> 00:07:49,920
+سيئة إذا أنت مدتنيشقيمة صافر الراتب واضحة، عفوا،
+
+109
+00:07:49,920 --> 00:07:55,720
+الراتب الأساسي واضحة ماحددتليش بشكل دقيق ماجددش
+
+110
+00:07:55,720 --> 00:07:58,340
+قيمة الضريبة وماجددش قيمة الاستقلاعات اللي على
+
+111
+00:07:58,340 --> 00:08:03,200
+الموظف هذا ماقولتليش ال formula اللي تصاغ عليها
+
+112
+00:08:03,200 --> 00:08:07,020
+المعادلة هذه، ماتلومنيش لأن ال garbage انت اتديتني
+
+113
+00:08:07,020 --> 00:08:12,240
+garbage فاخدت مني garbage وفي ال data mining ال
+
+114
+00:08:12,240 --> 00:08:13,560
+low quality data
+
+115
+00:08:16,610 --> 00:08:21,630
+معناته low quality mining result إذا أنا مااخترتش
+
+116
+00:08:21,630 --> 00:08:26,750
+منطقة التنقيب بشكل .. بشكل مناسب بشكل دقيق معناته
+
+117
+00:08:26,750 --> 00:08:35,530
+مش هحصل على النتيجة المقلوبة، نعم ممتاز،
+
+118
+00:08:35,530 --> 00:08:39,730
+بس مش أنت اللي بتستخرجها فعليافعليًا مش أنت اللي
+
+119
+00:08:39,730 --> 00:08:42,670
+بتستخرجها، مين اللي بدورلك على الـ pattern هذه؟
+
+120
+00:08:42,670 --> 00:08:45,230
+الـ tools أو بين جثين الـ machine learning
+
+121
+00:08:45,230 --> 00:08:48,230
+algorithm مش احنا اتفقنا إن الـ data mining هي
+
+122
+00:08:48,230 --> 00:08:52,150
+عبارة عن multidisciplinary topic جمع من ال
+
+123
+00:08:52,150 --> 00:08:53,790
+database، من ال programming، من ال machine
+
+124
+00:08:53,790 --> 00:08:56,550
+learning، من ال statistics جزء ال machine learning
+
+125
+00:08:56,550 --> 00:08:59,150
+تستخدم في عملية ال mining نفسها أو بين جثين في
+
+126
+00:08:59,150 --> 00:09:04,180
+عملية التحليل عملية البحث عن ال patternمجرد انت ..
+
+127
+00:09:04,180 --> 00:09:07,900
+انت بعد ما تفهم ال data و تفهم ال output اللي بدي
+
+128
+00:09:07,900 --> 00:09:12,040
+يطلع دورك تختار machine learning algorithm مناسب
+
+129
+00:09:12,040 --> 00:09:16,860
+تقول قصته بالظبط في لوح و لا في data يعني أنه مش
+
+130
+00:09:16,860 --> 00:09:21,440
+أنظمة أو قليلة مش .. مسألة مش أنظمة أو قليلة فعليا
+
+131
+00:09:21,440 --> 00:09:25,040
+فيها مشاكل أو يعني بعدين تيجي تقولي أنا والله بدي
+
+132
+00:09:25,040 --> 00:09:30,180
+أحسب رواتب الموظفين بحيث أنه أعلى راتب للموظففي
+
+133
+00:09:30,180 --> 00:09:37,220
+صافر راتب لا يتجاوز لـ 1500 دولار تمام؟ وأتفاجأ ..
+
+134
+00:09:37,220 --> 00:09:40,840
+أتفاجأ أنه في ال input اللي عندي ك basic salary
+
+135
+00:09:40,840 --> 00:09:47,480
+فيه موظفين رواتبهم الإبتدائية أكتر من 1500 ومافيش
+
+136
+00:09:47,480 --> 00:09:51,540
+عنده درائب ومافيش عنده خصومات ممتاز، عشان هيك
+
+137
+00:09:51,540 --> 00:09:56,680
+بنقولك garbage in garbage out فإذا كانت الآن ال
+
+138
+00:09:56,680 --> 00:10:01,320
+quality تبعت ال product دائمامعتمد اعتماد كله على
+
+139
+00:10:01,320 --> 00:10:05,260
+الـ Input على الـ Quality تبعات الـ Input واحد
+
+140
+00:10:05,260 --> 00:10:07,300
+يقول لي بس مش هذا اللي بيصير يا دكتور في عالم
+
+141
+00:10:07,300 --> 00:10:09,680
+التنقيب اللي احنا بيشوفه على الـ National
+
+142
+00:10:09,680 --> 00:10:13,300
+Geographic بروح بيحفر و بلاقي دهب بفو جبل ما يروح
+
+143
+00:10:13,300 --> 00:10:17,940
+يحفر و يلاقي الدهب هذا جديش بحث عن الأرض جديش
+
+144
+00:10:17,940 --> 00:10:23,700
+استأجار معدات جديش ناس جالدين على العمل و بيفهموا
+
+145
+00:10:23,700 --> 00:10:26,280
+في التخص في المجال اللي بيشتغلوا فيه فبتلاقي عنده
+
+146
+00:10:26,280 --> 00:10:30,660
+الـ Mechanic عشان لو اتعطلت الآلةمباشرة يصلحها
+
+147
+00:10:30,660 --> 00:10:35,360
+بيلاقي عنده الخبير اللي في التربة بيعرف اللي عنده
+
+148
+00:10:35,360 --> 00:10:39,820
+سواج على رأي أبو حاسم، تمام؟ فبكون فعليا هو جهد
+
+149
+00:10:39,820 --> 00:10:46,440
+وفر input .. input على مستوى الهدف تبعه، تمام يا
+
+150
+00:10:46,440 --> 00:10:51,940
+أحمد؟ في
+
+151
+00:10:51,940 --> 00:10:56,620
+فهم البيانات أو فهمك للبيانات لازم تطرح على نفسك
+
+152
+00:10:56,620 --> 00:11:01,880
+مجموعة من الأسئلةالأسئلة هذه مهمة في الجزئية
+
+153
+00:11:01,880 --> 00:11:03,800
+الأولى من ال chapter اللي هي data understanding
+
+154
+00:11:06,730 --> 00:11:10,750
+في الـ Basic Question هاي لازم أنت زي ما قلتلك
+
+155
+00:11:10,750 --> 00:11:15,310
+عشان تحصل على معرفة أو مفاهم كويس تروح تسأل مجموعة
+
+156
+00:11:15,310 --> 00:11:18,790
+من الأسئلة وهذه general question تقريبا أنت وغيرك
+
+157
+00:11:18,790 --> 00:11:22,370
+هتسأله نفسك و هتلاقي أن بعضها ممكن تكرر الآن بشكل
+
+158
+00:11:22,370 --> 00:11:25,950
+أو بآخر من ضمن الأسئلة أو تقول معاك لنفس المعنى مش
+
+159
+00:11:25,950 --> 00:11:29,870
+قضية لكن كلها تصب في مرحلة واحد أو في اتجاه واحد
+
+160
+00:11:29,870 --> 00:11:36,480
+إنك أنت تفهم البيانات قبلما تشتغل ليش هذا الكلام؟
+
+161
+00:11:36,480 --> 00:11:39,240
+عشان انا اعرف وين .. اعرف وين حدودي، ايش أرض
+
+162
+00:11:39,240 --> 00:11:42,340
+الصلبة اللي أنا واقف عليها عشان أبدأ المرحلة
+
+163
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+التالية بجلب جو زي ما بيقولوا واطمئن .. واتجنب ال
+
+164
+00:11:46,060 --> 00:11:49,140
+risk اللي ممكن تصير لأن عملية ال analysis في جامعة
+
+165
+00:11:49,140 --> 00:11:52,060
+الخير احنا اليوم بنتعلم لكن في ال real world أو في
+
+166
+00:11:52,060 --> 00:11:54,840
+العالم لما انت بدك تستخدم ال machine learning
+
+167
+00:11:54,840 --> 00:11:59,150
+algorithm هذا ممكن يشغله عشر أيامأو 11 يوم أو
+
+168
+00:11:59,150 --> 00:12:03,610
+أسبوع أو أكثر هو بيعمل بحاول يقرأ البيانات ويحللها
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+169
+00:12:03,610 --> 00:12:09,450
+جهازك الشخص مش هيخدمك بدك تروح تحجز cloud server
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+170
+00:12:09,450 --> 00:12:14,510
+بدك تدفع مبلغ محترم فجابل ما أنا بدي أخدها التجربة
+
+171
+00:12:14,510 --> 00:12:18,250
+هاي وأكثر لازم أكون فاهم كويس أيش البيانات اللي
+
+172
+00:12:18,250 --> 00:12:24,330
+موجودة عندي وبالتالي الفهم هذا هو بمثل درعك في
+
+173
+00:12:24,330 --> 00:12:30,290
+مواجهة المشكلة اللي موجودةأول حاجة أو أول سؤال بدي
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+174
+00:12:30,290 --> 00:12:35,330
+يتبادر لذهننا هل البيانات هذه بتحل المشكلة
+
+175
+00:12:35,330 --> 00:12:41,570
+المطلوبة ولا لأ قبل ما أبدأ فيها ضربنا مثال
+
+176
+00:12:41,570 --> 00:12:47,490
+محاضرات الماضية كان لما قلنا نحاول نعمل system
+
+177
+00:12:47,490 --> 00:12:53,930
+بيتنبأ بيهالتحصيل أو نسبة التحصيل للطالب في
+
+178
+00:12:53,930 --> 00:12:57,310
+المرحلة الإبتدائية بناء على الحالة الصحية وهذا
+
+179
+00:12:57,310 --> 00:13:01,410
+النموذج خليه في بالك لأنه هنكرره كثير كذكر ليش؟
+
+180
+00:13:01,410 --> 00:13:04,490
+لأنه سهل نوقّع الناس اللي بنعيشه وممكن نستوعبه
+
+181
+00:13:04,490 --> 00:13:13,810
+بسهولة الآن ال data هذه عشان أحل المشكلة هذه فعليا
+
+182
+00:13:13,810 --> 00:13:20,120
+ممكن أنا أروح أجمعها فقط من السجل المدرسيالسجل
+
+183
+00:13:20,120 --> 00:13:23,280
+للمدرسة كتير وبدي يقوللي إن والله كان في الأول
+
+184
+00:13:23,280 --> 00:13:26,780
+ابتدائي كذا وجاب معدل كذا كان في الصف الفلاني في
+
+185
+00:13:26,780 --> 00:13:30,460
+تاني ابتدائي وجاب كذا، مصبوط؟ الشغلات التانية مش
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+186
+00:13:30,460 --> 00:13:36,560
+متوفرة مطلقا بعد هيك هطرح سؤال تاني، بينفع أنا
+
+187
+00:13:36,560 --> 00:13:40,680
+أقول والله بدي أتنبأ بمستوى تحصيل الطالب في
+
+188
+00:13:40,680 --> 00:13:45,060
+المرحلة الإبتدائية بناء على بيانات سوق فلسطين
+
+189
+00:13:45,060 --> 00:13:50,420
+للأوراق المالية؟طبعاً لأ، فلازم .. هذا السؤال مهم،
+
+190
+00:13:50,420 --> 00:13:54,200
+هل ال data set اللي موجودة عندهان بتحل المشكلة ولا
+
+191
+00:13:54,200 --> 00:13:59,060
+بتحلهاش؟ مينجو سين، relevant للمشكلة ولا لأ؟ فلازم
+
+192
+00:13:59,060 --> 00:14:04,940
+أول شغلة أن تكون ال data set لها علاقة بالهدف، في
+
+193
+00:14:04,940 --> 00:14:10,280
+مثال صاف الراتب، بنفعش أروح أزوأك تقولني والله
+
+194
+00:14:10,280 --> 00:14:13,990
+يحسبلي صاف الراتب؟و تروح تدخلي argument للـ
+
+195
+00:14:13,990 --> 00:14:18,490
+function تبعتي جاب 95 في تنقيب البيانات و جاب 63
+
+196
+00:14:18,490 --> 00:14:22,310
+في برمجة 2 و جاب 70 مثلا في ال operating system
+
+197
+00:14:22,310 --> 00:14:31,410
+أبداك أكتر؟ مين اللي اعترض على 95 بس؟ بحسب أبداك
+
+198
+00:14:31,410 --> 00:14:37,030
+أكتر انا مظبط كتير أكيد يعني هذا بيكون غالبا الأول
+
+199
+00:14:37,030 --> 00:14:41,710
+على الدفعة مافيش مشكلةأمه دا عياله غير أن أمه دا
+
+200
+00:14:41,710 --> 00:14:46,530
+عياله هو يجتهد ويستهلهم هذا أهم شغلة طيب كذلك في
+
+201
+00:14:46,530 --> 00:14:52,270
+بعض الأسئلة العامة اللي ممكن أنا أستفيد منها قداش
+
+202
+00:14:52,270 --> 00:14:58,930
+حجم البيانات المتوفرة عندك بعد ما أنا فعليا حددت
+
+203
+00:14:58,930 --> 00:15:04,090
+أن ال data هذه relevant لل task هذه وبتحلل الهدف
+
+204
+00:15:04,090 --> 00:15:07,760
+وبتوصلني للهدف اللي أنا بدياهجدّيش حجم البيانات
+
+205
+00:15:07,760 --> 00:15:12,340
+اللي موجودة عندى؟ ده سؤال مهم عادة بال machine
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+00:15:12,340 --> 00:15:16,300
+learning بيجيب نقول عشان نقدر نتعلم صح تدّى بحدود
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+خمسين ألف record عشان أقدر أتعلم صح و أشغل صح و
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+208
+00:15:21,540 --> 00:15:24,120
+بالمناسبة ممكن الخمسين ألف هدول يكونوا جلال في
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+209
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+task معينة وممكن يكون في عندي task تانية يكفيهم200
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+record حسب دقة أو حسب ال quality تبع ال input أو
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+00:15:36,430 --> 00:15:39,790
+ال data اللي موجودة عندها هنشوف خلال ال course في
+
+212
+00:15:39,790 --> 00:15:42,970
+مثلا ال iris database بتكلم على زهر السوسن أو
+
+213
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+أنواع السوسنيات بتكلم على تلات أنواع و بتكلم على
+
+214
+00:15:46,470 --> 00:15:50,770
+مقييس طول البتلة و طول الزهرة و الكأس تبع الزهرة
+
+215
+00:15:50,770 --> 00:15:54,920
+إلى آخرهوالقياسات هذه دقيقة ومشتغلين عليها بشكل
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+محترم غالبا تستخدم for training سهل عشان سهل
+
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+00:15:58,160 --> 00:16:03,560
+الواحد بيستوعبها وحجمها صغير لكن هذا الكلام
+
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+مابينفعش عشان أتكلم على تصنيفات مختلفة الـ150 هدول
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+00:16:09,140 --> 00:16:11,740
+مابينفعش أروح مثلا أنا على وزارة الصحة أو على
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+مستشفى الشفاء باسم الأورام أقولهم والله جماعة
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+00:16:14,460 --> 00:16:19,480
+الخير بدّونا صور مقطعية لمرضى سرطان الرئة الله
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+00:16:19,480 --> 00:16:24,530
+يبعد عنكم الشر جميع المسلمين يا ربالآن يقولوا
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+العشر هدول كافيات يبنوا system قادر بالتنبؤ أو
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+00:16:33,410 --> 00:16:39,690
+يساعدني حتمًا لأ حتمًا لأ وبالتالي حجم البيانات
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+لازم يكون كافي للتعليم وهذا الكلام مش هيصير في
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+00:16:47,150 --> 00:16:51,010
+المجال زي ما قلتلك إلا غير من واقع خبرة تراكمية في
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+228
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+العملاليوم احنا فعليا مش عارف لما أقولك الواجب
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+المرة اللي جاية بدي data set كذا ممكن تجيبلي data
+
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+00:16:57,450 --> 00:17:01,050
+set من ألفين record موجودة معظمها موجود لل
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+00:17:01,050 --> 00:17:05,430
+training للتدريب وفي بعضها موجودة على مواقع Kaggle
+
+232
+00:17:05,430 --> 00:17:08,090
+محطوطة ل competition وممكن تدفع عليها فلوس و
+
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+00:17:08,090 --> 00:17:10,850
+بتلاقيها real data set و بتلاقيها بمئات الألاف ال
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+00:17:10,850 --> 00:17:14,910
+records و أحيانا ب gigabytes حجمها عشان تعملها
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+00:17:20,580 --> 00:17:27,320
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+00:17:27,320 --> 00:17:35,580
+أكتر و بتكون ال result تبعتك أفضل بدك
+
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+فضاء عين واسع اديبلك مثال من واقعنا احنا بقولوا
+
+239
+00:17:41,080 --> 00:17:46,140
+فلان طبيب حاذق في التخصص اللي بشتغل فيه جهجير
+
+240
+00:17:46,140 --> 00:17:51,780
+بلغتنا اهل غزة صح؟ ليش بنقول عنه الصفة هاي؟بس لأنه
+
+241
+00:17:51,780 --> 00:17:59,500
+من أول حلقة بشخص صح لأ مر عليه حالات بلغتنا برضه
+
+242
+00:17:59,500 --> 00:18:03,420
+احنا أهل غزة بعدد شعر رأسه وبالتالي صار عنده
+
+243
+00:18:03,420 --> 00:18:07,520
+knowledge أو experience عالية جدا بمجرد يتعرف أو
+
+244
+00:18:07,520 --> 00:18:12,000
+يسمع من الشخص الأعراض اللي بيشكيها تمام بيقدر يحدد
+
+245
+00:18:12,000 --> 00:18:16,820
+المرض بشكل دقيق تمام هذا لا يعني اللي لا يخطئلكنه
+
+246
+00:18:16,820 --> 00:18:21,980
+فعلياً نسبة الدقة عنده في التشخيص مرتفعة جدا، تكاد
+
+247
+00:18:21,980 --> 00:18:27,380
+تكون كاملة من أين؟ من وقع خبرة، بينفعش طبيب بهمش
+
+248
+00:18:27,380 --> 00:18:31,830
+بيجيش طبيب مبارح يتخرجيقول أنا عندي خبرة أفضل من
+
+249
+00:18:31,830 --> 00:18:35,190
+فلان لأ العامل الزمن وعدد التجارب اللي مر فيها
+
+250
+00:18:35,190 --> 00:18:39,070
+بالمناسبة كل تجربة مر فيها .. كل طبيب بعالج ..
+
+251
+00:18:39,070 --> 00:18:43,650
+عفوا كل مريض بعالجه الطبيب هي عبارة عن instance رو
+
+252
+00:18:43,650 --> 00:18:48,210
+.. رو .. record في ال data set تبعته بيحاول يكتسب
+
+253
+00:18:48,210 --> 00:18:53,050
+من خلاله خبرة وبالتالي بعد ما هي ال data relevant
+
+254
+00:18:53,050 --> 00:18:58,630
+حجم البيانات مهم جداً هل هذه هي كل ال data set؟
+
+255
+00:19:01,490 --> 00:19:04,630
+Okay انت قلتلي هاي حجمها قلتلي والله عندي الف
+
+256
+00:19:04,630 --> 00:19:11,290
+record ضروري تسأل نفسك فعليا هل في مجال هذه كل ال
+
+257
+00:19:11,290 --> 00:19:15,610
+data set ولا في جزء مخفي أنا مش قادر أصلّه مش من
+
+258
+00:19:15,610 --> 00:19:18,970
+ال .. بدورش على knowledge يا .. يا هاشم بأدور على
+
+259
+00:19:18,970 --> 00:19:23,960
+بيانات يعني بين قوسين هل في مجال الألف هدوليصيروا
+
+260
+00:19:23,960 --> 00:19:30,920
+1500 أو 1500.5 يصيروا 3000 يعني بين جثين هل هناك
+
+261
+00:19:30,920 --> 00:19:34,220
+مصدر آخر للبيانات هذي ممكن أن أحصل عليه الآن أنا
+
+262
+00:19:34,220 --> 00:19:38,420
+فعليًا أول ما طرقت طرقت باب مستشفى الشفاء التخصص
+
+263
+00:19:38,420 --> 00:19:42,760
+المطلوب لكن بعرف سين من الأطباء شاطر وكتير من
+
+264
+00:19:42,760 --> 00:19:47,380
+المرض هذول بتوجهوا لعنده فممكن أنا هذا الطبيب أن
+
+265
+00:19:47,380 --> 00:19:52,910
+أروح ألاقي عنده سجلات إضافية وبالتالي أوسعال data
+
+266
+00:19:52,910 --> 00:19:56,150
+set تبعتي عشان هيك بدك تسأل نفسك هل هي كل ال data
+
+267
+00:19:56,150 --> 00:20:01,990
+set هاي ولا في مجال تكون أكبر هل ال data set هاي
+
+268
+00:20:01,990 --> 00:20:06,290
+representative enough كافية لتمثيل الحالات اللي
+
+269
+00:20:06,290 --> 00:20:10,930
+أنا بقى أشتغل فيها احنا خدنا مثال طلاب المدرسة و
+
+270
+00:20:10,930 --> 00:20:15,210
+نسبة تحصيلهم طب ما هي بياناتهم الدراسية موجودة في
+
+271
+00:20:15,210 --> 00:20:19,610
+المدرسة لكن هل هي كافية للحالة اللي أنا بقى أتكلم
+
+272
+00:20:19,610 --> 00:20:24,720
+فيهااللي هي بنجو سين كانت .. نذكركوا بالحالة بناءً
+
+273
+00:20:24,720 --> 00:20:28,760
+على وضعه الصح يجدش نسبة تحصيله لأ غير كافية
+
+274
+00:20:28,760 --> 00:20:33,220
+المعرفة دي مفعش ال data set مش represented بتمثلش
+
+275
+00:20:33,220 --> 00:20:36,140
+كل البيانات لكن في مثال ال iris اللي ذكرته قبل
+
+276
+00:20:36,140 --> 00:20:41,160
+لحظات اللي هو الزهرات أو الزهور كان فيه شغلات
+
+277
+00:20:41,160 --> 00:20:46,860
+معروفة قال هي الوردة أو هي الزهرة كأس ارتفاعه حجمه
+
+278
+00:20:46,860 --> 00:20:53,070
+البتلة بولها و عرضها قياسات تابعةفي غير هي كانت
+
+279
+00:20:53,070 --> 00:20:56,130
+موجودة في الوردة قالك لا ماعنديش هي الموجودة
+
+280
+00:20:56,130 --> 00:21:01,410
+الريحة مش هتطلع في الكمبيوتر و بالتالي خلصنا منها
+
+281
+00:21:01,410 --> 00:21:05,410
+انسى الموضوع مصبوط فهذه كانت فعليا ال four
+
+282
+00:21:05,410 --> 00:21:08,850
+attributes اللي أنا ذكرتهم enough representative
+
+283
+00:21:08,850 --> 00:21:14,910
+وبشكل كافي للزهرات الموجودة ثم إنه بدي أرجع للعدد
+
+284
+00:21:14,910 --> 00:21:20,710
+فعليا ال data هي as rows بتمثل تلت أنواع من
+
+285
+00:21:20,710 --> 00:21:25,190
+الزهرات هدولولّا بس بتمثّل نوع واحد؟ إذا بتمثّل
+
+286
+00:21:25,190 --> 00:21:30,510
+نوع واحد ده تستفيد منها حاجة وبالتالي لازم يكون في
+
+287
+00:21:30,510 --> 00:21:34,830
+عندي variation بحيث أنه الطابق كل الفئات لما بدي
+
+288
+00:21:34,830 --> 00:21:39,270
+أعلم النظام ييجي يقولّي true، false، positive و
+
+289
+00:21:39,270 --> 00:21:44,070
+negative لازم أعرض عليه عينات من الاتنين positive
+
+290
+00:21:44,070 --> 00:21:46,310
+و negative عشان يتعرف على خصائص high يا رامي
+
+291
+00:21:46,310 --> 00:21:50,110
+ويتعرف على خصائص high وفي الآخر يقدر ياخد decision
+
+292
+00:21:54,700 --> 00:22:00,360
+هل ال data تبعتي فيها outlier ولا لأ cross
+
+293
+00:22:00,360 --> 00:22:08,100
+outliers ولا فيها اي شغلة غير اعتيادية الان لو انا
+
+294
+00:22:08,100 --> 00:22:12,940
+اجيت و قلتلك كالتالي بدي ارسم هنا رسمة بسيطة قلتلك
+
+295
+00:22:12,940 --> 00:22:18,220
+حاولت ارسم ال data 6 تبعتي في ال 2D و لجيتها
+
+296
+00:22:18,220 --> 00:22:20,820
+عمالها هيك
+
+297
+00:22:28,530 --> 00:22:36,390
+وأجينا هنا قلنا لك في عندي كام
+
+298
+00:22:36,390 --> 00:22:45,470
+من البيانات هنا لكن النسبة الأكتر ال red الأن ..
+
+299
+00:22:45,470 --> 00:22:50,950
+الأن لو أنا قلت بدي أعمل model يحاكي ال data هذا
+
+300
+00:22:50,950 --> 00:22:54,910
+أو ال situation اللي عندي أفضل model هيكون
+
+301
+00:22:54,910 --> 00:23:00,700
+straight line قط مستقيممع ال data اللي موجودة
+
+302
+00:23:00,700 --> 00:23:05,740
+عندهم أكيد
+
+303
+00:23:05,740 --> 00:23:11,080
+نرجع بنأكد plus or minus من ال accuracy صحيح؟ طب
+
+304
+00:23:11,080 --> 00:23:19,400
+بس هدول .. هدول .. هدول فعلياً وجودهم هيعمل إن ال
+
+305
+00:23:19,400 --> 00:23:23,720
+line يروح باتجاههم ولا شو رايكوا؟ لإن يعرفوا إن مش
+
+306
+00:23:23,720 --> 00:23:29,000
+نقطة واحدةولا نقطتين في مجبوعة هدولة بدي أخد قرار
+
+307
+00:23:29,000 --> 00:23:31,300
+فيهم هل هو دول outlier ولا لأ إذا كانت نقطة
+
+308
+00:23:31,300 --> 00:23:34,900
+ونقطتين ممكن أحذفهم ممكن يكونوا عشر أو عشرين واضطر
+
+309
+00:23:34,900 --> 00:23:39,900
+أحذفهم الآن بنيجي مثلا بقولك في مجال تربية الأبناء
+
+310
+00:23:39,900 --> 00:23:49,620
+قوعك تكذب قدام ابنك ليش؟ هي بس مرة واحدة اتصرف
+
+311
+00:23:49,620 --> 00:23:54,560
+التصرف هذا قدامه وخلاصوهو كفيل إنه يعيده مرة أو
+
+312
+00:23:54,560 --> 00:23:57,780
+تنتين أو تلاتة أو عشرة ولمّا تيجي تقوله كذا بتقولك
+
+313
+00:23:57,780 --> 00:24:02,680
+ما أنت كذا وولد كذا، عملت كذا، مصبوط؟ وبالتالي ال
+
+314
+00:24:02,680 --> 00:24:07,600
+outlier هذا مش لازم يكون موجود فعشان هيك لازم أنا
+
+315
+00:24:07,600 --> 00:24:12,080
+أفهم ال data تبعتي تكون إيش صحيحة وعادة جماعة
+
+316
+00:24:12,080 --> 00:24:17,090
+الخير يمكن كمان النقاط اللي أنا رسمته هايتكون
+
+317
+00:24:17,090 --> 00:24:20,530
+كثيرة، المفروض تكون أقل، ليش؟ لأن المفروض ..
+
+318
+00:24:20,530 --> 00:24:24,250
+المفروض أن الـ data هذه normal و ال outlier زي ما
+
+319
+00:24:24,250 --> 00:24:27,770
+قلنا هو الشواذ .. الشاذ يعني نجي بنقول والله سألنا
+
+320
+00:24:27,770 --> 00:24:31,810
+أهل الشبكات في الجامعة الإسلامية كام request بيجي
+
+321
+00:24:31,810 --> 00:24:36,190
+لل server تباعنا في اليوم؟ قالك والله إنه ممكن
+
+322
+00:24:36,190 --> 00:24:40,350
+يجيني مثلا خمسين ألف أو يجينا عشرة آلاف أو سبعة ..
+
+323
+00:24:40,350 --> 00:24:44,570
+سبعة آلاف في اليوم تيجي فترة التسجيل، بيكون عند
+
+324
+00:24:44,570 --> 00:24:50,180
+الذروةعشرين ألف عشرين ألف request لصفحة الجامعة
+
+325
+00:24:50,180 --> 00:24:57,720
+لسيرفر الجامعة هذا ال normal تمام لكن
+
+326
+00:24:57,720 --> 00:25:02,100
+صار فيه هنا في بعض الأوقات صار في عندنا عليه جلطش
+
+327
+00:25:02,100 --> 00:25:06,860
+العشرين ألف صار خمسين أو صار مائة ألف request لو
+
+328
+00:25:06,860 --> 00:25:11,480
+اتحققنا في هدول في ال traffic العالي ممكن نلاقي
+
+329
+00:25:11,480 --> 00:25:15,190
+احناانتروجين او Daniel of service attack عامله كان
+
+330
+00:25:15,190 --> 00:25:19,930
+بتتوقع بتتعرضله سيرفر الجامعة لأنه كمان مرة انت
+
+331
+00:25:19,930 --> 00:25:26,210
+المفروض تعرف ال pattern الحقيقي بعدين بتقرر شو وضع
+
+332
+00:25:26,210 --> 00:25:29,030
+ال pattern بيجي طباء القلب بيجي بيقولك والله انه
+
+333
+00:25:29,030 --> 00:25:35,410
+ال frequent لما بروح بياخد ال SG لتخطيط القلب مجرد
+
+334
+00:25:35,410 --> 00:25:39,800
+يطلع عليه الطبيبولا يعملها في عندك اضطراب لأ مراكز
+
+335
+00:25:39,800 --> 00:25:44,460
+سليمة ليش؟ لأن هو أساساً حفظ النمط الطبيعي كيف
+
+336
+00:25:44,460 --> 00:25:49,540
+ممكن يكون وبناء عليه بياخد decision على العناصر
+
+337
+00:25:49,540 --> 00:25:53,040
+الموجودة وبالتالي أنا بدي أحاول أعرف بعد ما شوفت
+
+338
+00:25:53,040 --> 00:25:56,060
+حجم البيانات وهل هي مكتملة أو لأ و representative
+
+339
+00:25:56,060 --> 00:25:59,280
+هل فيها outlier ولا لأ، اتفضل يا خالد
+
+340
+00:26:05,510 --> 00:26:10,730
+مثلا إذا عددهم اكتار هم مش outlier يعني مثلا أجي
+
+341
+00:26:10,730 --> 00:26:17,150
+هيك نيجي نقول كالتالي فلان عنده عشرة من الأبناء
+
+342
+00:26:17,150 --> 00:26:24,850
+كلهم مجتهدين نشيطين مؤدبين و و و لكن واحد منهم فلت
+
+343
+00:26:24,850 --> 00:26:30,150
+اه انت عكست الشغل تمام اعكس الشغل تمام بيصير اللي
+
+344
+00:26:30,150 --> 00:26:34,330
+ميحد هو ال outlierأيوة، ففعلياً العدد بيلعب دور
+
+345
+00:26:34,330 --> 00:26:37,870
+أنا هنا لما رسمت حاولت .. حاولت .. حاولت أرسم عشر
+
+346
+00:26:37,870 --> 00:26:41,370
+نقاط في المقابلة ممكن رسمت خمسين أو ستين نقطة هنا،
+
+347
+00:26:41,370 --> 00:26:44,810
+تمام؟ عادت راجعت، إذا كان لاحظت ومسحتهم، لأنه
+
+348
+00:26:44,810 --> 00:26:48,250
+فعليا عشر على خمسين لأ، إلهم وزن، لكن أربعة أو
+
+349
+00:26:48,250 --> 00:26:53,250
+اتنين إلى خمسين، نوعا ما الوزن إيش، بقل، تمام؟
+
+350
+00:26:53,250 --> 00:26:56,390
+فدائما الـoutlier بالعدد، عدده قليل
+
+351
+00:26:59,240 --> 00:27:03,800
+كيف لو أنا أنت أخدته؟ طيب ممتاز، الآن إنت لو حملت
+
+352
+00:27:03,800 --> 00:27:09,540
+الـoutlier في حسبانك وروح تعدّل معادلة الخط هاي،
+
+353
+00:27:09,540 --> 00:27:13,480
+شو بتساوي؟ المفروض إن الخط يجي هان، على الأقل على
+
+354
+00:27:13,480 --> 00:27:21,160
+حدود المنطقة الحمراء، هاي، اللي هو الخط المقطع،
+
+355
+00:27:21,160 --> 00:27:24,480
+هذا العمل اللي بحاول أرسمه هان، ولا لأ؟ ما تقولين
+
+356
+00:27:24,480 --> 00:27:26,800
+إنه ليه مش تأثير؟ لأ، إيه اللي هو تأثير في الوزن؟
+
+357
+00:27:26,800 --> 00:27:35,080
+ممتازطب مين أدق؟ الخط اللي في الأول و لا الخط هذا؟
+
+358
+00:27:35,080 --> 00:27:39,440
+الأول، ليش؟ لأنه عامل fit تقريبا في نص البيانات أو
+
+359
+00:27:39,440 --> 00:27:45,520
+بين جوسين نسبة الخطأ فيه أقل لمن؟
+
+360
+00:27:45,520 --> 00:27:49,540
+طب أنا مابهمش، و أنا بدي أرجعلك للنقطة هذه، هذه
+
+361
+00:27:49,540 --> 00:27:56,400
+الآن بعد ما كانت نسبة ال accuracy تبعتها حوالي 98%
+
+362
+00:27:56,400 --> 00:28:03,200
+أصارت ال accuracy تبعتها 70%أه قصده يا دكتور أنه
+
+363
+00:28:03,200 --> 00:28:05,880
+ما بنفعش احنا نفضلنا نعدل كتير في ال data أو نرفع
+
+364
+00:28:05,880 --> 00:28:08,840
+منها أسيارة يا عم انت ليش بتظلك تفترض كتير احنا
+
+365
+00:28:08,840 --> 00:28:14,360
+بنقولك ال outlier قيم شاذة لأن هي عبارة نسبة قليلة
+
+366
+00:28:14,360 --> 00:28:20,500
+جدا لكن تؤثر .. تؤثر سلبا .. الآن بدي أجي أقولك
+
+367
+00:28:20,500 --> 00:28:24,440
+كالتالي حضرت جنابك ما شاء الله من المجتهدين ومعدلك
+
+368
+00:28:24,440 --> 00:28:30,080
+دائما علاماتك .. علاماتك تسعين مش هقول أكتر ولا
+
+369
+00:28:30,080 --> 00:28:35,030
+بدي أقول تسعينتجسّرت في الـ data mining و حطيتلك
+
+370
+00:28:35,030 --> 00:28:40,250
+أربعين وين راح معدّى لك؟ وين راح معدّى لك؟ يا
+
+371
+00:28:40,250 --> 00:28:43,330
+دكتور والله ما هو هذا أنا، مش أنا بس المادة يعني
+
+372
+00:28:43,330 --> 00:28:46,770
+ماظبطتش معايا بس في الآخر بتصير الأربعين هذه
+
+373
+00:28:46,770 --> 00:28:50,710
+outlier ماشي الحال، بس الفكرة اللي أنا بدي أقوله
+
+374
+00:28:50,710 --> 00:28:56,130
+إن ال outlier هي عبارة عن قيم unfrequent غير
+
+375
+00:28:56,130 --> 00:29:01,470
+متكررة، لكن وجودهايؤثر، بدك تقولي إن هذه الأربعين
+
+376
+00:29:01,470 --> 00:29:06,810
+لو كانت ضمن فصلين أو تلت فصول، مش هتأثر في المعدل؟
+
+377
+00:29:06,810 --> 00:29:10,910
+بتأثر و بتأثر كتير، في اللحظة اللي بتخلص منها أنت
+
+378
+00:29:10,910 --> 00:29:15,650
+بتحس أن المعدل بجيب مثال على الـ outlier الـ
+
+379
+00:29:15,650 --> 00:29:20,370
+outlier كمان يا شباب هي قيمة حقيقية موجودة لكن
+
+380
+00:29:20,370 --> 00:29:27,370
+وجودها يتنافى تماما مع ال trend العام اللي موجودة
+
+381
+00:29:27,370 --> 00:29:31,580
+فيه إيش؟الـ data set اللي موجودة هنا عشان هيك أول
+
+382
+00:29:31,580 --> 00:29:35,820
+حاجة فيها إن إيش أشيلها عشان هيك بهمش أنا برضه في
+
+383
+00:29:35,820 --> 00:29:39,040
+مثال العلامات بنروح ونقوله جداش أنا معدلك يا فلان
+
+384
+00:29:39,040 --> 00:29:44,480
+أنا متأكد إنك أنت هتديه معدلك بدون ما تحسب المادة
+
+385
+00:29:44,480 --> 00:29:48,520
+هي لأن مش هي اللي بتعكس صورتك نعم يعني لو أجد مثلا
+
+386
+00:29:48,520 --> 00:29:52,600
+إحنا بنعمل data mining على علاقة مثلا التدخين
+
+387
+00:29:52,600 --> 00:29:53,620
+بالسرطان تمام
+
+388
+00:29:59,050 --> 00:30:03,330
+أكيد .. هي حق .. شوية .. شوية .. شوية أنا قلت إن
+
+389
+00:30:03,330 --> 00:30:07,130
+الـ outlier مش حقيقية؟ لأ الـ outlier هي قيمة
+
+390
+00:30:07,130 --> 00:30:17,030
+حقيقية لكن نسبتها قليلة جدا تمام
+
+391
+00:30:17,030 --> 00:30:20,490
+إيش
+
+392
+00:30:20,490 --> 00:30:25,030
+ال task تبعتك بدك تقول الآن؟ أنك بتصير الدكتور بطل
+
+393
+00:30:25,030 --> 00:30:31,350
+مدخنين بالسرطانمش علاقة السرطان بالتدخين انت تقول
+
+394
+00:30:31,350 --> 00:30:37,090
+كل مصاب بالسرطان الرئة هو مدخن لا مش ضروري
+
+395
+00:30:37,090 --> 00:30:43,210
+بالمناسبة في أحيانا أنا بكون دراستي فقط تتمحور
+
+396
+00:30:43,210 --> 00:30:47,570
+حوالين تحديد ال outlier لأن هذا اللي بكون أنا معنى
+
+397
+00:30:47,570 --> 00:30:53,730
+فيه مثالمثال اللي لما بعمل الـ DNA sequence
+
+398
+00:30:53,730 --> 00:30:58,590
+analysis تحليل الـ DNA عشان الأمراض الوراثية ما هو
+
+399
+00:30:58,590 --> 00:31:01,530
+في بعض الأمراض الوراثية مرتبطة أو الأمراض الوراثية
+
+400
+00:31:01,530 --> 00:31:05,190
+مرتبطة بالـ DNA في شذوذ معين فممكن أنا أروح أعمل
+
+401
+00:31:05,190 --> 00:31:10,530
+بحث عنها و أدور HAN في المنطقة هذه عشان أعمل
+
+402
+00:31:10,530 --> 00:31:13,850
+detection أن HAN في outlier و ما تنساش أنه إحنا
+
+403
+00:31:13,850 --> 00:31:18,300
+لما عرضنا منالـ Descriptive Tasks تبع الـ Data
+
+404
+00:31:18,300 --> 00:31:21,400
+Mining كانت واحدة منهم تحديد الـ Outlier لكن كمان
+
+405
+00:31:21,400 --> 00:31:25,060
+مرة يا جماعة الخير بنرجع بنقول إن وجود الـ Outlier
+
+406
+00:31:25,060 --> 00:31:31,860
+في الـ Data بيسحب .. بيسحب ال result باتجاه منحنة
+
+407
+00:31:31,860 --> 00:31:39,460
+مختلف تماما .. تماما .. لو أنت كنت بتعلم .. الله
+
+408
+00:31:39,460 --> 00:31:44,390
+مصلي عليك .. ولد صغير عملية الضربجداول الدرب و
+
+409
+00:31:44,390 --> 00:31:50,550
+روحت في لحظة .. حفظته جد .. من التنين للستة حفظته
+
+410
+00:31:50,550 --> 00:31:57,150
+ليه صح و في السابعة .. في السابعة عند قيمتين ..
+
+411
+00:31:57,150 --> 00:32:00,490
+عند قيمتين او في تلت قيمتين .. سبعة و تمانية و
+
+412
+00:32:00,490 --> 00:32:05,250
+تسعة لأن في اللي جابلهم هيصيدك و لا لا .. هيصيدك
+
+413
+00:32:05,250 --> 00:32:08,770
+لأنه هيقارن في القيم السابقة في السابعة و تمانية و
+
+414
+00:32:08,770 --> 00:32:15,500
+تسعة علمتواياهم غلطو بعد هي كانت تروح تقوله مثلا
+
+415
+00:32:15,500 --> 00:32:23,760
+اضرب 27 في 3 او 27 في 6 شو بده يصير وضعه؟ فتقول
+
+416
+00:32:23,760 --> 00:32:27,040
+ليش ان النتيجة .. لازم .. لازم يديني نتيجة صحيحة؟
+
+417
+00:32:27,040 --> 00:32:29,900
+ليش؟ لأنه صار انتقامتين او تلاتة اللي حاطيتله
+
+418
+00:32:29,900 --> 00:32:34,000
+اياهم ضمن سبعين قيمة تقريبا أو ستين .. سبعين قيمة
+
+419
+00:32:34,000 --> 00:32:37,360
+كان فيهم صحيحات حاطيتله تلاتة خطأ لكن هدولة
+
+420
+00:32:37,360 --> 00:32:41,710
+التلاتة الخطأأثروا جداً على النتائج اللي بدها تطلع
+
+421
+00:32:41,710 --> 00:32:45,230
+وبالتالي في الحالة هذه أنا لازم أخلص من ال outlier
+
+422
+00:32:45,230 --> 00:32:53,350
+عشان تبقى النتيجة ترجع عايش لو أضعها الطبيعي هنا
+
+423
+00:32:53,350 --> 00:32:59,490
+هنخد شوية مع بعض في موضوع ال data اللي عندي هل
+
+424
+00:32:59,490 --> 00:33:05,370
+فيها أي جزء صناعيArtificial data يعني الـ data هذه
+
+425
+00:33:05,370 --> 00:33:12,270
+تم إدخالها بشكل صناعي أو بشكل آلي لل data set
+
+426
+00:33:12,270 --> 00:33:19,910
+مثلا،
+
+427
+00:33:19,910 --> 00:33:22,750
+الآن عندنا هان عماد بيقول ناتج عن ال data mining
+
+428
+00:33:22,750 --> 00:33:28,530
+مثلا، بس في برضه عند بعض ال input ممكن تدخل على ال
+
+429
+00:33:28,530 --> 00:33:33,150
+data set بشكل آلي بدون data miningالـ sensors
+
+430
+00:33:33,150 --> 00:33:39,470
+المجسات الآن بدي تسأل نفسك ال data set هاي مينجو
+
+431
+00:33:39,470 --> 00:33:46,130
+سينج ال fabricated data أو ال fake data ال data
+
+432
+00:33:46,130 --> 00:33:54,530
+المزيفة أو المزورة أو ال ال generated data هل هي
+
+433
+00:33:54,530 --> 00:34:00,070
+ممكن تديني real result؟ لأ لأ شوية ال sensor
+
+434
+00:34:00,070 --> 00:34:05,100
+بيعملش generationالـ sensor بيعمل collecting أنا
+
+435
+00:34:05,100 --> 00:34:08,480
+باتكلمش على collecting وعشان قلتلك فيها حنخض شوية
+
+436
+00:34:08,480 --> 00:34:14,400
+الآن كمان مرة البيانات اللي عندي أنا اللي تدخل لل
+
+437
+00:34:14,400 --> 00:34:22,680
+data للنظام مصدرين إما آلة تمام أو human أو human
+
+438
+00:34:22,680 --> 00:34:27,340
+الآن لو أنا ديت بدي أتكلم على database اللي لها
+
+439
+00:34:27,340 --> 00:34:31,860
+علاقة بالتنبؤ هل الجو ماطر أو لاو جيت قولت والله
+
+440
+00:34:31,860 --> 00:34:37,180
+أنا معنى بال temperature و
+
+441
+00:34:37,180 --> 00:34:42,980
+ال .. ال outlook اللي هو المظهر العام للجو و ال
+
+442
+00:34:42,980 --> 00:34:47,060
+humidity و
+
+443
+00:34:47,060 --> 00:34:58,120
+في عندي rainy الجو ماطر yes و no الآن
+
+444
+00:35:01,710 --> 00:35:08,330
+في الحالة هذه ال data set اللي عندي ال temperature
+
+445
+00:35:08,330 --> 00:35:15,250
+ايش مصدرها؟ sensor مصدر الحرارة مظبوط ميزان
+
+446
+00:35:15,250 --> 00:35:21,590
+الحرارة طب ال humidity كذلك فيه sensor بقيس درجة
+
+447
+00:35:21,590 --> 00:35:28,340
+الرطوبة في الجو طب ال outlook ال outlookhuman
+
+448
+00:35:28,340 --> 00:35:33,560
+human بيه مصبوط لازم الإنسان يشوف و هو اللي بيقدر
+
+449
+00:35:33,560 --> 00:35:35,960
+طبعا هاي ال data set بدها كمان ال data عشان احنا
+
+450
+00:35:35,960 --> 00:35:40,140
+اياش التاريخ عشان تصير في عندي unique identifiers
+
+451
+00:35:40,140 --> 00:35:46,340
+لكل role طيب نرجع لل temperature هل في مجال أنا ك
+
+452
+00:35:46,340 --> 00:35:51,960
+human أقدر أو أقرأ درجة الحرارة الحقيقية بدون أي
+
+453
+00:35:51,960 --> 00:35:57,190
+equipment لأمفروغ منها سواء كان الـ equipment هذا
+
+454
+00:35:57,190 --> 00:36:00,950
+مشبوك على الحيط وأنا بدأ أطلع فيه وأقرأ أخد منه
+
+455
+00:36:00,950 --> 00:36:04,790
+درجة الحرارة أو هذا مشبوك الـ equipment مشبوك على
+
+456
+00:36:04,790 --> 00:36:07,930
+ال laptop أو على الجهاز والجهاز هو اللي بياخد منه
+
+457
+00:36:07,930 --> 00:36:12,870
+القراءة ولا لأ في الآخر في الآخر هو أو الجهاز هذا
+
+458
+00:36:12,870 --> 00:36:17,530
+أو ال sensor هذا قرأ القيمة الحقيقية الموجودة
+
+459
+00:36:17,530 --> 00:36:21,370
+وزودني فيها ماعملهاش prediction ماعملهاش
+
+460
+00:36:21,370 --> 00:36:28,700
+generation مصبوط؟ تمامنجي وكذلك في الـ Humidity
+
+461
+00:36:28,700 --> 00:36:32,940
+معناته أن أنا الآن هي في عندي equipment أو بين
+
+462
+00:36:32,940 --> 00:36:40,180
+جسين data تم إدخالها على ال data set بشكل صناعي بس
+
+463
+00:36:40,180 --> 00:36:44,560
+مش بشكل .. مش بذكاء صناعي أنا قاعد بسألك
+
+464
+00:36:44,560 --> 00:36:51,880
+artificial data data مصنعة أو data مصطنعة تمام؟
+
+465
+00:36:51,880 --> 00:36:55,520
+ملاحظ .. ملاحظ الفرق؟ نجي هلأ ال equipment أو عفوا
+
+466
+00:36:55,520 --> 00:37:00,850
+لل outlookواحد قال okay يا دكتور ال outlook كمان
+
+467
+00:37:00,850 --> 00:37:03,110
+إيش اللي أنت عندك؟ قلت بدي أقوله والله هنا في عندي
+
+468
+00:37:03,110 --> 00:37:08,030
+إما الجو هيكون مشمس أو بدي يكون غائم أو غائم جزئيا
+
+469
+00:37:08,030 --> 00:37:15,470
+صحيح cloudy أو sunny partial cloudy و cloudy طب ما
+
+470
+00:37:15,470 --> 00:37:19,230
+أنا بقدر أجيب كاميرا و أصلبها على السماء كده و
+
+471
+00:37:19,230 --> 00:37:26,170
+بتلتقط صورة و بتقوللي إيش الوضع إيش الجو الآنبينفع
+
+472
+00:37:26,170 --> 00:37:32,450
+صح؟ بينفع بس ال value هذه المدخلة ال .. مين اللي
+
+473
+00:37:32,450 --> 00:37:38,850
+أخد decision بناء على الصورة ال AI فصارت هذه
+
+474
+00:37:38,850 --> 00:37:46,510
+artificial data هذه صارت artificial data تخيل أنه
+
+475
+00:37:46,510 --> 00:37:51,830
+أنا في ال data set تبعتي كان عندها ألف record
+
+476
+00:37:51,830 --> 00:37:56,560
+اشتغل عليهم ال humanالف ريكورد اشتغل عليهم ال
+
+477
+00:37:56,560 --> 00:38:05,200
+human لو أنا سألتك في ال outlook قداش نسبة خطأه هو
+
+478
+00:38:05,200 --> 00:38:13,240
+بيقول الجو مشمس غائم .. غائم جزئيا Zero لو أخدنا
+
+479
+00:38:13,240 --> 00:38:19,780
+أي إنسان سوي طلعنا برا هيك في الفضاء كيف الجو يا
+
+480
+00:38:19,780 --> 00:38:24,380
+فلان الله ما شاء الله الشمس اليوم مظبطةولا لأ؟ هو
+
+481
+00:38:24,380 --> 00:38:27,380
+عمل Prediction؟ لأ، بينما الـ Artificial
+
+482
+00:38:27,380 --> 00:38:29,980
+Intelligence أو الـ Machine Learning أو النظام
+
+483
+00:38:29,980 --> 00:38:36,120
+اللي انت عملته بالكاميرا تنبأ بحالة الشمس أو الجو
+
+484
+00:38:36,120 --> 00:38:39,620
+بناءً على الصورة إيش طب تخيل إنه في اللحظة اللي
+
+485
+00:38:39,620 --> 00:38:44,300
+تقلط فيها الصورة كان فيه سحابة صيف مارجة إيش
+
+486
+00:38:44,300 --> 00:38:49,140
+هيقوللي؟ ملاحظ؟ فهنا صار في عندي Prediction هذه
+
+487
+00:38:49,140 --> 00:38:55,240
+Artificial Data نيجي لموضوعالريني الآن بعد كل هذه
+
+488
+00:38:55,240 --> 00:38:59,200
+ال data هذه مدخلة من خلال human أو من خلال أو
+
+489
+00:38:59,200 --> 00:39:03,420
+مدخلة تحت supervision of a human تحت متابعة
+
+490
+00:39:03,420 --> 00:39:09,160
+ومراقبة الإنسان يعني real data نيجي لكمية اليوم
+
+491
+00:39:09,160 --> 00:39:15,000
+هذا كان ماطر أو غير ماطر الآن مين اللي يكتب لي yes
+
+492
+00:39:15,000 --> 00:39:15,280
+و no
+
+493
+00:39:24,100 --> 00:39:29,260
+برضه في عندى حساس للمطار لسه
+
+494
+00:39:29,260 --> 00:39:33,040
+أنا باتكلمش على تنبأ باتكلمش على تنبؤ شوف فى
+
+495
+00:39:33,040 --> 00:39:37,740
+اللحظة اللى انت بتكتب فيها او بتدكر كلمة يتنبأ
+
+496
+00:39:37,740 --> 00:39:43,180
+معناته Artificial Data تمام؟
+
+497
+00:39:43,180 --> 00:39:48,240
+انا قاعد بتكلم على Historical Data Real Data الان
+
+498
+00:39:48,240 --> 00:39:51,540
+هدولة ال الف ريكورد كان ال expert أو خبير الأرصاد
+
+499
+00:39:51,540 --> 00:39:58,370
+الجوية بعينالجو و هو اللي بيسجل الجو كان ماطر أو
+
+500
+00:39:58,370 --> 00:40:06,610
+لأ بعد فترة من الزمن يعني ألف قراءة على تسعين يوم
+
+501
+00:40:06,610 --> 00:40:10,290
+فترة الشتاء مثلا قداش بيطلعوا ع كام سنة جمع ال
+
+502
+00:40:10,290 --> 00:40:16,590
+data هاي ألف على تسعين يا شباب حوالي عشر سنوات
+
+503
+00:40:16,590 --> 00:40:21,330
+تقريبا تقريبا عشر سنوات عشرة ماشي الحال على مدار
+
+504
+00:40:21,330 --> 00:40:26,910
+عشر سنوات هو بيجمع بال result هايإجا واحد شاطر زي
+
+505
+00:40:26,910 --> 00:40:30,830
+كهيك قال له إيش رأيك يا بفلان بناء على ال data
+
+506
+00:40:30,830 --> 00:40:39,190
+اللي عندك أبنيلك نظام .. نظام يتنبأ بحالك الطقس هل
+
+507
+00:40:39,190 --> 00:40:45,010
+الجو هيكون ماطر أو لأ؟ قالك okay زودك بال الف
+
+508
+00:40:45,010 --> 00:40:50,130
+record فدخلت على ال data mining project وصار ال
+
+509
+00:40:50,130 --> 00:40:55,000
+mining project تبعك لما تقوله درجة الحرارة كذاالـ
+
+510
+00:40:55,000 --> 00:41:00,160
+Outlook كذا الـ Humidity كذا يرد عليك يقولك هذا
+
+511
+00:41:00,160 --> 00:41:05,320
+الجو Rainy or not الآن فصار ال system بعد هيك هو
+
+512
+00:41:05,320 --> 00:41:08,040
+اللي يقولك بناءً على الموضوع يتحدده أنت المدخلات
+
+513
+00:41:08,040 --> 00:41:12,720
+من خلال ال sensors وال expert الموجود أو موظف
+
+514
+00:41:12,720 --> 00:41:16,060
+الأرصاد الجوية عشان يقيم الجو ويقولك هذا اليوم بدي
+
+515
+00:41:16,060 --> 00:41:20,420
+يكون ماطر أو لا وصارت ال data ستة بعتك فيها خمس
+
+516
+00:41:20,420 --> 00:41:30,100
+تلاف record يعني قداش ضاف عليهمأربعة آلاف بس
+
+517
+00:41:30,100 --> 00:41:36,220
+الأربعة آلاف دول إيش وصلنا فوق Artificial Data إذا
+
+518
+00:41:36,220 --> 00:41:41,100
+ال data هذه اتاخدت على علّاتها ال data set كلها
+
+519
+00:41:41,100 --> 00:41:43,460
+تترفض ليش؟
+
+520
+00:41:45,190 --> 00:41:49,830
+مش reliable ماقدرش أثق فيها لكن لو كان موظف
+
+521
+00:41:49,830 --> 00:41:55,430
+الأرصاد أو expert هذا بيختبر النظام باستمرار بين
+
+522
+00:41:55,430 --> 00:42:00,430
+قوسين كل مثلا مع نهاية كل أسبوع هو بيسجل ملاحظاته
+
+523
+00:42:00,430 --> 00:42:04,130
+على ورقته ومع نهاية كل أسبوع بياخد عينتين أو تلاتة
+
+524
+00:42:04,130 --> 00:42:08,670
+عشوائيات وبيفحص ال result تبعت ال system أو بيشيك
+
+525
+00:42:08,670 --> 00:42:12,870
+عليها مع كل يوم بيومه وبيتأكد إن ال data هذه صحيحة
+
+526
+00:42:12,870 --> 00:42:18,880
+أو لأبتصير ال data مش artificial بتبطل artificial
+
+527
+00:42:18,880 --> 00:42:26,680
+لأن الناس اللي أقرت وجودها في ال system من ال
+
+528
+00:42:26,680 --> 00:42:30,980
+human وبالتالي أصبحت جزء من ال data اللي موجودة
+
+529
+00:42:30,980 --> 00:42:35,200
+لكن عادة للأسف بعد ما بيصير في عند ناس ال system
+
+530
+00:42:35,200 --> 00:42:39,640
+الناس بتركن و بتبطل التبع السؤال اللي بيطرح نفسك
+
+531
+00:42:39,640 --> 00:42:45,410
+أنا لما بدي أجي أشتغل لاحقاعلى أي منهم أشتغل؟ على
+
+532
+00:42:45,410 --> 00:42:49,890
+الـ 1000 أسأل نفسك إيش الإضافة جابني أتفكر تشتغل
+
+533
+00:42:49,890 --> 00:42:53,230
+إيش الإضافة اللي أنا بدي أقدّمله إياها إذا ال
+
+534
+00:42:53,230 --> 00:42:56,870
+system اللي عنده بيعمل prediction لحالة المقرر نعم
+
+535
+00:42:56,870 --> 00:43:05,130
+أو لا بنسبة 100% عمدار السنوات الماضية كلها،
+
+536
+00:43:05,130 --> 00:43:08,670
+الأربع سنوات الماضية أو الأربعين، إيش حد في اللي
+
+537
+00:43:08,670 --> 00:43:11,610
+وانت؟ولا شيء، وبالتالي أنت مش لازم تشتغل في المجال
+
+538
+00:43:11,610 --> 00:43:16,230
+هذا لأن الـ domain هذا أو المنطقة هذه closed،
+
+539
+00:43:16,230 --> 00:43:20,010
+شبعت، تمام يا شباب؟ وبالتالي لما أنا بتكلم على
+
+540
+00:43:20,010 --> 00:43:27,550
+artificial data إن الـ data كان القرار فيها يعود
+
+541
+00:43:27,550 --> 00:43:33,850
+أو لبنائها لآلة، تمام؟ والآلة هذه unreliable، مش
+
+542
+00:43:33,850 --> 00:43:38,080
+موثوق فيها لك من اليوم كلنا بنفق بال sensorsولا لأ
+
+543
+00:43:38,080 --> 00:43:41,700
+بس ال sensors مابتاخدش قرار ال sensor بتديني value
+
+544
+00:43:41,700 --> 00:43:45,280
+بتعمل collection والقرار برجع لل human أو لل
+
+545
+00:43:45,280 --> 00:43:52,440
+system الموجود تمام يا جماعة الخير؟ واضحة الأمور؟
+
+546
+00:43:52,440 --> 00:43:57,700
+كذلك من ال generic question المفروض اللي أنا
+
+547
+00:43:57,700 --> 00:44:03,780
+أطرحها على نفسي هل في أي unique identifier للروز؟
+
+548
+00:44:06,150 --> 00:44:09,830
+يعني الصفوف اللي عندي هذه فيه لها معرف أساسي
+
+549
+00:44:09,830 --> 00:44:12,930
+primary
+
+550
+00:44:12,930 --> 00:44:17,050
+key يعني بينجو سين في primary key الأصل يكون في ال
+
+551
+00:44:17,050 --> 00:44:22,430
+database هاي في عند مين ال date زي ما كتبنا هنا
+
+552
+00:44:22,430 --> 00:44:30,290
+للطالب في المدرسةرقم الهوية للطالب في وزارة ال ..
+
+553
+00:44:30,290 --> 00:44:34,390
+للولد في وزارة الصحة رقم الهوية طب ليش أنا محتاج
+
+554
+00:44:34,390 --> 00:44:39,150
+الـ Identifier هذا؟ عشان شغلتين الأولى .. الأولى
+
+555
+00:44:39,150 --> 00:44:45,330
+عشان أتأكد إن الـ data هذه مش duplicate ال data
+
+556
+00:44:45,330 --> 00:44:50,990
+يعني قد تتشابه الظروف يجيني يوم درجة الحرارة سبعة
+
+557
+00:44:50,990 --> 00:44:59,800
+و cloudyتمام؟ ولو humanity ومافيش مضر ممكن يجيني
+
+558
+00:44:59,800 --> 00:45:03,160
+يومين في السنة زي بعض زي هيك لكن إيش اللي بيضمنني
+
+559
+00:45:03,160 --> 00:45:08,560
+إن هدولة rows يومين مختلفين التاريخ اللي هو ال
+
+560
+00:45:08,560 --> 00:45:13,500
+identifier ال field اللي موجود عندها الشغل التاني
+
+561
+00:45:13,500 --> 00:45:17,080
+اللي بتلزمني ليش أنا محتاج ال identifier لما بحتاج
+
+562
+00:45:17,080 --> 00:45:21,740
+أعمل integration عشان أعمل integration بدي أعمل
+
+563
+00:45:21,740 --> 00:45:25,550
+integration between two sourcesعندي رقم الطالب في
+
+564
+00:45:25,550 --> 00:45:28,190
+المدرسة رقم .. عفوا رقم هويت الطالب في المدرسة
+
+565
+00:45:28,190 --> 00:45:32,410
+وعندي رقم هويته في وزارة الصحة في التربية والتعليم
+
+566
+00:45:32,410 --> 00:45:36,450
+ووزارة الصحة عشان باعتمادي على رقم الهوية بقدر
+
+567
+00:45:36,450 --> 00:45:39,310
+أعمل match و أعمل integration ما بين ال two
+
+568
+00:45:39,310 --> 00:45:44,550
+records اللي موجودين هنا ولا لأ؟ لو مافيش عندي ال
+
+569
+00:45:44,550 --> 00:45:49,230
+identifier هذا أو المعرف هذا مش هقدر أجمع البيانات
+
+570
+00:45:49,230 --> 00:45:51,410
+صح وبالتالي بيانة بيكون فيها مشكلة
+
+571
+00:45:54,130 --> 00:45:59,570
+الـ unique identifier فعليًا هو unique موجود بـ
+
+572
+00:45:59,570 --> 00:46:03,350
+unique و لا .. لو تكرر .. ممكن يصير فيه تكرار لازم
+
+573
+00:46:03,350 --> 00:46:09,530
+يكون unique طب لو صار فيه تكرار شو يعني؟ يعني بهمش
+
+574
+00:46:09,530 --> 00:46:12,130
+.. الآن .. هذه الفكرة .. هذا الأسئلة بتقرح يعني
+
+575
+00:46:12,130 --> 00:46:16,110
+الآن بينفع .. هيك هتاجي أقول بينفع أنا ألاقي طالب
+
+576
+00:46:16,110 --> 00:46:18,990
+في المدرسة أو طالبين اثنين اثنين في المدرسة اللي
+
+577
+00:46:18,990 --> 00:46:23,930
+هم نفس الرقملأ، الآن لجيت نفس رقم الهوية و لجيت
+
+578
+00:46:23,930 --> 00:46:28,710
+واحد تسعين والتاني خمسة و تمانين لأ، في مشكلة هان،
+
+579
+00:46:28,710 --> 00:46:32,510
+بدي أحلها، فعشان هي كان لازم أفهم أن المفروض ال
+
+580
+00:46:32,510 --> 00:46:35,070
+identifier اللي يكون unique فعليًا، هل هو actually
+
+581
+00:46:35,070 --> 00:46:39,830
+unique؟ و لو لجيت فيه تكرار، شو يعني التكرار هذا؟
+
+582
+00:46:39,830 --> 00:46:43,130
+يعني على سبيل المثال، على سبيل المثال، نيجي نقول
+
+583
+00:46:43,130 --> 00:46:47,690
+والله الطالب، رقم هويت الطالب، مثلا هيك أنا مش
+
+584
+00:46:47,690 --> 00:46:53,530
+قولت، قولت رقم هويت الطالبتمام؟ لكن هل هو كافي
+
+585
+00:46:53,530 --> 00:46:56,810
+فعليًا يكون ك unique identifier في سجله المدرسي؟
+
+586
+00:46:56,810 --> 00:47:00,730
+قالك لا يا عمي رقم الطالب والمستوى الدراسي هدولة
+
+587
+00:47:00,730 --> 00:47:03,990
+مع بعض لأن الطالب هذا موجود عندنا في المدرسة لمدة
+
+588
+00:47:03,990 --> 00:47:11,630
+عشر سنوات وعلى كل سنة فيه إله record جديد اه ..
+
+589
+00:47:11,630 --> 00:47:16,610
+معناته صار عند ال key هذا مش بس رقم الهوية صار في
+
+590
+00:47:16,610 --> 00:47:22,680
+عنده رقم الهوية والمستوى تبع الطالببينما في
+
+591
+00:47:22,680 --> 00:47:27,900
+المزارة الصحية فقط رقم الهوية وبالتالي أنا بدي
+
+592
+00:47:27,900 --> 00:47:31,620
+أنتبه و أفهم شو يعني لو صار فيه تكرار أو القيمة
+
+593
+00:47:31,620 --> 00:47:36,320
+المفروض اللي تكون مكررة لو .. لو ظهرت بتكرار ليش
+
+594
+00:47:36,320 --> 00:47:42,660
+ظهرت؟ حكينا في الموضوع الـ Join إنه فعليا لو كان
+
+595
+00:47:42,660 --> 00:47:46,680
+في عندي Two Data Sets والمفروض أنا بدي أروح أجمعهم
+
+596
+00:47:46,680 --> 00:47:50,200
+مع بعض لازم يكون في عندي Unique Identifier طيب
+
+597
+00:47:51,090 --> 00:47:55,330
+لاجيب طالب اللي له سجل في المدرسة وما لاجيبلهش سجل
+
+598
+00:47:55,330 --> 00:48:00,370
+في وزارة الترابي أو في الصحة شو يعني؟ شو بدي أساوي
+
+599
+00:48:00,370 --> 00:48:03,370
+في ال record هذا؟ هل ممكن أروح أعبي زي ما يقول
+
+600
+00:48:03,370 --> 00:48:09,830
+محمد هان؟ اه ولا أروح أحذف ال record كله؟ كمان؟
+
+601
+00:48:09,830 --> 00:48:13,240
+طيب الشغل التانيOkay البيانات اللي أنا أخدتها من
+
+602
+00:48:13,240 --> 00:48:16,120
+وزارة التربي والتعليم لطلاب المرحلة الإبتدائية أو
+
+603
+00:48:16,120 --> 00:48:19,560
+المرحلة الأساسية كانت عشر تلاف record بناء على رقم
+
+604
+00:48:19,560 --> 00:48:24,360
+الهوية ولمّا روحت على وزارة الصحة راحت دوني اتناشر
+
+605
+00:48:24,360 --> 00:48:29,240
+.. اتناشر الف record اتدوني .. بالضبط فلازم أنا
+
+606
+00:48:29,240 --> 00:48:32,880
+أكون فاهم أنه فيه ناس ممكن تكون إيش مادخلتش مدرسة
+
+607
+00:48:32,880 --> 00:48:38,060
+و هدول غالبا عددهم الفين وروحت لما بدأت أفدور لأ
+
+608
+00:48:38,060 --> 00:48:41,920
+يا عم اللي جيته أنه فيه كمان بياناتفي بيانات كمان
+
+609
+00:48:41,920 --> 00:48:47,420
+أنه فعليًا مش بس الألف اللي مش رايح المدرسة والألف
+
+610
+00:48:47,420 --> 00:48:50,540
+التاني ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب
+
+611
+00:48:50,540 --> 00:48:50,720
+.. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب
+
+612
+00:48:50,720 --> 00:48:50,840
+.. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب
+
+613
+00:48:50,840 --> 00:48:51,400
+.. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب
+
+614
+00:48:51,400 --> 00:48:51,700
+.. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب
+
+615
+00:48:51,700 --> 00:48:53,840
+.. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب .. ب
+
+616
+00:48:53,840 --> 00:49:01,940
+.. ب .. ب .. ب .. ب ..
+
+617
+00:49:01,940 --> 00:49:06,680
+ب
+
+618
+00:49:07,820 --> 00:49:11,080
+طب شو الحل؟ شو بدي أسوي مع هيك record؟ أنت بدك
+
+619
+00:49:11,080 --> 00:49:15,800
+تاخد قرار في حينها إن إيش بدي أخلي وإيش بدي أحدث
+
+620
+00:49:15,800 --> 00:49:24,320
+وهل الحدث هو الحل عندي وجديش نسبته، تمام؟
+
+621
+00:49:24,320 --> 00:49:31,140
+وزي ما قلنا جديش نسبة الشغلات من الأسئلة المهمة
+
+622
+00:49:31,140 --> 00:49:37,130
+اللي تترحى على نفسك كمانإيش الـ data الـ available
+
+623
+00:49:37,130 --> 00:49:39,850
+لل task؟ روحت أنا و الله يا وزارة الصحة قالتلي في
+
+624
+00:49:39,850 --> 00:49:45,710
+عند meeting instance للمرض الفلاني، مش كافية، هل
+
+625
+00:49:45,710 --> 00:49:51,290
+في مجال أدور على مصادر بديلة أو ممكن أعمل
+
+626
+00:49:51,290 --> 00:49:54,690
+integration؟ باجي على سبيل المثال، نقول مثلا مرض
+
+627
+00:49:54,690 --> 00:50:01,390
+الثلاثيمية مرض وراثي يصيب فقط سكان منطقة الحوض
+
+628
+00:50:01,390 --> 00:50:05,960
+البحر الأبيض المتوسطعندي فى فلسطين مالجتش مثلا
+
+629
+00:50:05,960 --> 00:50:10,120
+data set وانا حابب اشتغل على المرض هذا فممكن أطرق
+
+630
+00:50:10,120 --> 00:50:13,020
+أبواب تانية فى المنطقة بس بينفعش أروح على جنيوب
+
+631
+00:50:13,020 --> 00:50:16,700
+أفريقيا أسألهم في عنكوا data set عن المرض هذا ليش؟
+
+632
+00:50:16,700 --> 00:50:20,680
+لأنه مش شائع فانا بدور على مصادر البيانات المختلفة
+
+633
+00:50:20,680 --> 00:50:26,060
+أنا بدي أعمل diagnosis ل certain virusومش ملاقي
+
+634
+00:50:26,060 --> 00:50:29,260
+dataset في بلدي طب ما أنت ممكن تلاقي dataset موجود
+
+635
+00:50:29,260 --> 00:50:32,820
+available من خلال مختبرات عالمية أو إلى آخره ممكن
+
+636
+00:50:32,820 --> 00:50:37,580
+تكون مجانية أو ممكن تكون مدفوعة فحسب ال task اللي
+
+637
+00:50:37,580 --> 00:50:43,240
+أنت إيش بدك تشتغل عليها زي ما قلنا جداش ال data
+
+638
+00:50:43,240 --> 00:50:46,160
+هذي relevant طبعا المصادر التانية جداش ممكن تكون
+
+639
+00:50:46,160 --> 00:50:50,700
+relevant و جداش ال additional relevant available
+
+640
+00:50:50,700 --> 00:50:55,180
+جداش حجمهمفانت فعلياً بلزمك في مرحلة إعداد
+
+641
+00:50:55,180 --> 00:50:57,320
+البيانات أو فهم البيانات وال system وتجميع
+
+642
+00:50:57,320 --> 00:51:03,660
+البيانات شغل كتير قداش حجم ال data المتاحة عندك
+
+643
+00:51:03,660 --> 00:51:09,120
+وذكرنا سابقاً ال expert ماصار expert إلا من واقع
+
+644
+00:51:09,120 --> 00:51:14,460
+تجربة سابقة أو قوية فتيجي تقولي والله أنا إلي مثلا
+
+645
+00:51:14,460 --> 00:51:17,860
+عشر تجاربالـ 10 تجارب هدول بيختلفوا عن المية
+
+646
+00:51:17,860 --> 00:51:21,820
+والمية هدول بيختلفوا تماما عن الألف طبعا بتكلم
+
+647
+00:51:21,820 --> 00:51:24,300
+اختلافهمين في حجم ال knowledge العائد على ال
+
+648
+00:51:24,300 --> 00:51:32,220
+expert تمام؟ وبالتالي كل ما كانت عفوا كل ما كانت
+
+649
+00:51:32,220 --> 00:51:38,200
+ال data historical أكبر كل ما كانت أفضل السؤال هل
+
+650
+00:51:38,200 --> 00:51:45,080
+في علاقة بين ال history و ال size؟ الأصل أهالأصل
+
+651
+00:51:45,080 --> 00:51:49,220
+أه لأن ال instances هدول أو ال rows هاي ما تراكمت
+
+652
+00:51:49,220 --> 00:51:54,960
+إلا مع مرور الوقت بس طبعا ممكن الوقت يكون قصير زي
+
+653
+00:51:54,960 --> 00:51:58,280
+ما في ال time series أو في ال temporal data ولا
+
+654
+00:51:58,280 --> 00:52:01,880
+لأ، ممكن الوقت يكون قصير أو يكون طويل، حسب ففعليا
+
+655
+00:52:01,880 --> 00:52:06,180
+في ارتباط، في عناصر لكن السؤال اللي بيطرح نفسه
+
+656
+00:52:06,180 --> 00:52:11,140
+الآن هل بينفع التعامل مع مرض ال influenza قبل
+
+657
+00:52:11,140 --> 00:52:15,500
+خمسين سنة مثل اليوم؟هذه برضه سؤال مهم أطرحه في الـ
+
+658
+00:52:15,500 --> 00:52:19,380
+Historical data عندي بيانات عن مرضى الـ influenza
+
+659
+00:52:19,380 --> 00:52:24,520
+أو مرضى الكوليرة قبل 100 سنة أروح أقول والله أنا
+
+660
+00:52:24,520 --> 00:52:27,280
+بدي أعمل system كذا كذا بناء على ال data قبل 100
+
+661
+00:52:27,280 --> 00:52:32,040
+أو 150 سنة غالبا .. غالبا هذه ممكن تكون useless
+
+662
+00:52:32,040 --> 00:52:36,040
+فأنا بدي يكون ال history تبعتي ال data مفيد
+
+663
+00:52:36,040 --> 00:52:42,500
+بالنسبة لي مش بس بالحجم لأ كمان إيش في واقعحسب إذا
+
+664
+00:52:42,500 --> 00:52:45,360
+أنا والله بدأ أقول والله اللي كان يأثر عليهم في ال
+
+665
+00:52:45,360 --> 00:52:48,300
+.. في الفترة الزمنية الفلانية اللي كانوا عندهم
+
+666
+00:52:48,300 --> 00:52:50,920
+ماكانوش بيعرفوا اللقاح مثلا كذا أو مابيعرفوش
+
+667
+00:52:50,920 --> 00:52:54,800
+التغذية الفلانية فكان بيأثر okay بصير هذا بتفرج بس
+
+668
+00:52:54,800 --> 00:52:59,280
+بيقولوا هاي دراسة بأثر رجع عشان تعرف ليش .. إيش
+
+669
+00:52:59,280 --> 00:53:03,480
+اللي كان يصير هناك دراسة تحليلية تمام أكثر منها
+
+670
+00:53:03,480 --> 00:53:05,580
+دراسة تنبؤية بيش بالمستقبل
+
+671
+00:53:08,500 --> 00:53:11,720
+ممكن أصير أدور على تاريخ المرض هذا بس هي مش بس في
+
+672
+00:53:11,720 --> 00:53:15,560
+المرض كمان حتى في الحروب وفي الاقتصاد وفي السياسة
+
+673
+00:53:15,560 --> 00:53:19,440
+ممكن أنا أدرس أو أعمل شغلات كتيرة لكن زي ما قلتلك
+
+674
+00:53:19,440 --> 00:53:25,620
+هذه عادة ما بنسميها احنا دراسات تحليلية تمام؟ أكثر
+
+675
+00:53:25,620 --> 00:53:32,980
+منها من أجل التنبؤ لاحقا آخر سؤال تقريبا هنا في ال
+
+676
+00:53:32,980 --> 00:53:37,420
+question أو ال general question مين هو ال expert؟
+
+677
+00:53:38,090 --> 00:53:42,350
+في الـ domain إيش
+
+678
+00:53:42,350 --> 00:53:45,170
+ال data expert؟ who is the data expert and the
+
+679
+00:53:45,170 --> 00:53:50,770
+domain expert؟ الآن لما أنت روحت على وزارة الصحة
+
+680
+00:53:50,770 --> 00:53:58,270
+وطلبت أعينات لل CT ولا صورة مقطعية أو كده حضرتك مش
+
+681
+00:53:58,270 --> 00:54:03,410
+خبير وبنفعش تفتي تقول الصورة هذه مصاب وهذا غير
+
+682
+00:54:03,410 --> 00:54:09,360
+مصاب هذا مصاب وهذا سليم، بنفع؟ مافعشبدك .. بدك
+
+683
+00:54:09,360 --> 00:54:14,820
+اتنين يكونوا معاك expert في التعامل مع ال data لبن
+
+684
+00:54:14,820 --> 00:54:18,580
+النوع هذا و هلا يتحارجيك أنواع البيانات اللي فعلا
+
+685
+00:54:18,580 --> 00:54:21,540
+احنا هنشتغل عليها مع ال course هذا تبعنا و بدك
+
+686
+00:54:21,540 --> 00:54:24,280
+expert في ال domain عشان ال expert في ال domain
+
+687
+00:54:24,280 --> 00:54:28,800
+دوره يقيملي .. يقيم أداء ال system اللي هاطلعه
+
+688
+00:54:28,800 --> 00:54:31,640
+يقيم ال knowledge اللي انا بده أطلعها يقول لأ يا
+
+689
+00:54:31,640 --> 00:54:35,220
+عم لأ في مشكلة في غلط في ال system هذه و هذه و هذه
+
+690
+00:54:35,220 --> 00:54:40,700
+ال system شخصهم غلطتمام؟ فبدنا نحاول نعيد تدريب
+
+691
+00:54:40,700 --> 00:54:44,480
+الـ system مرة تانية بزيادة ال data أو الأخرين ال
+
+692
+00:54:44,480 --> 00:54:49,240
+expert في ال data اللي انت بدأت تشتغل عليها برأيك
+
+693
+00:54:49,240 --> 00:54:53,740
+في فهم البيانات ممكن هذا مايتوفرش ويتوفر التاني
+
+694
+00:54:55,470 --> 00:54:59,470
+تمام؟ عادة في عليك جهد كبير في فهم البيانات عشان
+
+695
+00:54:59,470 --> 00:55:03,510
+هيك بقولك كل ما كان في عندك expert في ال data اللي
+
+696
+00:55:03,510 --> 00:55:06,830
+انت بتشتغل فيها مهم وكل ما كان في عندك expert في
+
+697
+00:55:06,830 --> 00:55:09,330
+ال domain أهم لأن هو ده بده يعمل evaluation معاك
+
+698
+00:55:09,330 --> 00:55:17,650
+لاحقا لكن برضه هذه تكلفة عالية بعد
+
+699
+00:55:17,650 --> 00:55:23,530
+المقدمة هاي بديك تاخد دقيقة من الآن تفكر ان ال
+
+700
+00:55:23,530 --> 00:55:35,840
+data اللي عندنا هناكم نوع؟ ال data كم نوع؟ لسه
+
+701
+00:55:35,840 --> 00:55:39,520
+في ال data preparation في ال data collection قبل
+
+702
+00:55:39,520 --> 00:55:43,460
+ما أقول بسم الله المفروض في ال mining أبدأ ايش؟
+
+703
+00:55:43,460 --> 00:55:47,300
+أسأل نفس الأسئلة هذه عشان أقدر أفهم ال data لأن
+
+704
+00:55:47,300 --> 00:55:49,540
+الموجودات كلهم تحت عنوان ال data understanding
+
+705
+00:55:52,930 --> 00:55:55,650
+فكر بضيقك يا جدش أنواع البيانات المختلفة اللي
+
+706
+00:55:55,650 --> 00:55:59,910
+عندنا أنواع
+
+707
+00:55:59,910 --> 00:56:05,710
+البيانات أربع أنواع dynamic structured وهي ال data
+
+708
+00:56:05,710 --> 00:56:10,950
+ال organized in tables أو relation ده تم رتبه
+
+709
+00:56:10,950 --> 00:56:15,650
+ولمّا بتكلم structured البيانات مش هتطلع عن النمط
+
+710
+00:56:15,650 --> 00:56:16,010
+هذا
+
+711
+00:56:18,950 --> 00:56:24,030
+الها schema معينة السؤال بيطرح نفسه هل ال json
+
+712
+00:56:24,030 --> 00:56:30,490
+object structured؟ لأ، هناك ناس قالت هنا لأ مين
+
+713
+00:56:30,490 --> 00:56:36,290
+بيقول ان ال json object structured data؟ ممكن يكون
+
+714
+00:56:36,290 --> 00:56:40,390
+ممكن أحولها و ممكن أحول ال structure ل json
+
+715
+00:56:40,390 --> 00:56:44,430
+structured
+
+716
+00:56:44,430 --> 00:56:49,490
+بس مش ملزم يعني مانفهاش زيك مطلقابدون قيود بين
+
+717
+00:56:49,490 --> 00:56:52,210
+جسين الجيسون object .. في حد الشباب بيعرفش إيش
+
+718
+00:56:52,210 --> 00:56:57,170
+يعني جيسون object؟ في حد بيعرفش إيش يعني جيسون
+
+719
+00:56:57,170 --> 00:57:06,170
+object؟ آه يا ياسر، ليوسف عفوا، إيش يعني جيسون؟
+
+720
+00:57:06,170 --> 00:57:14,420
+نظام ترميز لل data، آه محمدjson object الان ال
+
+721
+00:57:14,420 --> 00:57:17,760
+json object هي عبارة عن اول شي json اختصار ل
+
+722
+00:57:17,760 --> 00:57:22,540
+object او ل java عفوا notation object java
+
+723
+00:57:22,540 --> 00:57:26,120
+notation ماهي javascript notation object okay
+
+724
+00:57:26,120 --> 00:57:33,960
+javascript notation object object notation عشان
+
+725
+00:57:33,960 --> 00:57:34,740
+ترتيب الحروف
+
+726
+00:57:45,890 --> 00:57:52,070
+Json عشان تتضحلك الصورة افترض المثال التالي عند ال
+
+727
+00:57:52,070 --> 00:58:02,890
+student ID 123 name Hashem
+
+728
+00:58:02,890 --> 00:58:06,250
+نجلنا
+
+729
+00:58:06,250 --> 00:58:11,730
+معدلك يا Hashem كمل 95
+
+730
+00:58:13,380 --> 00:58:19,340
+يا فرحتك يا أستاذنا خمسة وتسعين الان ال json أو ال
+
+731
+00:58:19,340 --> 00:58:23,120
+javascript ال json object بياخد الشكل هذا هو عبارة
+
+732
+00:58:23,120 --> 00:58:28,200
+عن مجموعة من ال key و ال values مجموعة من ال key و
+
+733
+00:58:28,200 --> 00:58:32,980
+ال values الان ال json object هو عبارة عن semi
+
+734
+00:58:32,980 --> 00:58:33,600
+structured
+
+735
+00:58:41,340 --> 00:58:45,740
+ليش semi-structured؟ لأنه ممكن أنا قاعد يقوله عند
+
+736
+00:58:45,740 --> 00:58:54,220
+ال student name أو ال name سامح
+
+737
+00:58:54,220 --> 00:59:00,460
+ال ID 124
+
+738
+00:59:00,460 --> 00:59:07,490
+وماعنديش ال GPA لاحظ اختلف في الترتيب؟تمام؟ ومافيش
+
+739
+00:59:07,490 --> 00:59:12,530
+عندياش الـ GPA وعدد ال .. في عدد ال .. ال bears
+
+740
+00:59:12,530 --> 00:59:16,350
+عدد الأزواج مختلف الموجودة لأن كل واحد بنسميه احنا
+
+741
+00:59:16,350 --> 00:59:21,270
+key و value بنسميه bear عدد الأزواج مختلف وبالتالي
+
+742
+00:59:21,270 --> 00:59:26,670
+هو structured لأنه مكون من bears but semi
+
+743
+00:59:26,670 --> 00:59:31,250
+-structured لأنه عدد ال bears وترتيبهم مش ثابت
+
+744
+00:59:32,450 --> 00:59:35,950
+وعادة ما بينعملش عليه validation إلا غير manual
+
+745
+00:59:35,950 --> 00:59:44,670
+تمام؟ لكن تخيل في الجدول الجدول لما بيجيك جدول أو
+
+746
+00:59:44,670 --> 00:59:48,760
+باجي بقولك هاي في instance من الجدول الفلانيفيش
+
+747
+00:59:48,760 --> 00:59:51,820
+مجال يعني العمود الأول يعني العمود الأول العمود
+
+748
+00:59:51,820 --> 00:59:55,180
+التالت يعني التالت الخامس يعني الخامس ممكن يكون
+
+749
+00:59:55,180 --> 00:59:58,000
+فيه missing value ممكن يكون مكتوب لـ null و لا لأ
+
+750
+00:59:58,000 --> 01:00:01,040
+وبالتالي هذه الفرق بين الـ semi-structured و ال
+
+751
+01:00:01,040 --> 01:00:05,660
+unstructured ال data unstructured هي عبارة عن كل
+
+752
+01:00:05,660 --> 01:00:09,740
+البيانات اللي فيها أو ال files اللي بتحتوي على
+
+753
+01:00:09,740 --> 01:00:14,340
+binary سواء كانت text audio video image image
+
+754
+01:00:14,340 --> 01:00:24,310
+unstructuredالـ image unstructured؟ الـ matrix من
+
+755
+01:00:24,310 --> 01:00:31,830
+كام بعض؟ إذا كنت بتكلم black and white من بعدين
+
+756
+01:00:31,830 --> 01:00:38,610
+إذا كنت بتكلم grey scale بتكلم من تلاتة بصرف بتكلم
+
+757
+01:00:38,610 --> 01:00:46,030
+RGB بتكلم على أربعة أربعة dimension مصبوط؟طب أتكلم
+
+758
+01:00:46,030 --> 01:00:51,910
+على Full HD؟ هذا لسه جداش حجم المصفوفة؟ بدي أرجع
+
+759
+01:00:51,910 --> 01:00:55,250
+معاك للبداية خالص الـ Colored Image أو عفوا الـ
+
+760
+01:00:55,250 --> 01:01:00,850
+Black and White Image جداش حجمها؟ 2×2؟ 10×10؟ هو
+
+761
+01:01:00,850 --> 01:01:04,490
+Two Dimension؟ 2D؟ مختفقين حجم الصورة أو عدد
+
+762
+01:01:04,490 --> 01:01:09,890
+الـPixels جداش؟ فهذا unstructured يعني اقصد إنه
+
+763
+01:01:09,890 --> 01:01:15,730
+مافيش شغلة ثابتة أسقطها على كل الـData Type هايلكن
+
+764
+01:01:15,730 --> 01:01:20,410
+لما باجي بتكلم أنا جدول الطلاب جدول الطلاب جدول
+
+765
+01:01:20,410 --> 01:01:23,450
+الطلاب مافيش مجال بدي أكون كل البيانات اللي موجودة
+
+766
+01:01:23,450 --> 01:01:28,050
+فيه كذلك في عندي التصنيفين التانين اللي هي الـ
+
+767
+01:01:28,050 --> 01:01:33,690
+Dynamic وفي عندي الـ Static في عندي Dynamic وعندي
+
+768
+01:01:33,690 --> 01:01:38,670
+Static الـ Dynamic هي عبارة عن ال data اللي بتتغير
+
+769
+01:01:38,670 --> 01:01:44,290
+باستمرار ال content تبعتها بتتغير باستمرار الصورة
+
+770
+01:01:44,290 --> 01:01:49,140
+Dynamic يا شبابالـ Audio Dynamic تسجيل المحاضرة
+
+771
+01:01:49,140 --> 01:01:53,720
+تبعتنا هذا Dynamic لأ لأنه خلاص الملف متى ما اتصدر
+
+772
+01:01:53,720 --> 01:02:00,820
+الملف هيبقى الملف كما هو لو شهدناه مليون مرة هيبقى
+
+773
+01:02:00,820 --> 01:02:06,300
+ثابت مش هيتغير حسب جودة الـ Net، ماشي الحال لكن
+
+774
+01:02:06,300 --> 01:02:12,080
+تخيل ملفات ال word أو ملفات ال text اللي عندكأو
+
+775
+01:02:12,080 --> 01:02:15,360
+الـ Text المحطوط على الـ Blogs أو على الشبكات
+
+776
+01:02:15,360 --> 01:02:20,560
+التواصل الإجتماعي Dynamic ولا Static؟ Dynamic بين
+
+777
+01:02:20,560 --> 01:02:24,720
+كل لحظة والتانية ممكن فلان حط Post حذفه، لأ عدل
+
+778
+01:02:24,720 --> 01:02:28,420
+على ال Post اللي أضافه أجيه Comment جديدة، مصبوط؟
+
+779
+01:02:28,420 --> 01:02:31,480
+بس هاي، لأ كمان الـ Financial الـ Time Series Data
+
+780
+01:02:31,480 --> 01:02:36,280
+الـ Stock Market Data هذه كل دقيقة أو كل ثانية
+
+781
+01:02:36,280 --> 01:02:39,520
+ممكن تصير عليه إيش Update، فبسميها Dynamic Data
+
+782
+01:02:39,520 --> 01:02:44,570
+وين ما بيصير فيه Ending؟تغيير frequently فبسميها
+
+783
+01:02:44,570 --> 01:02:49,110
+dynamic و ال static data عكسها تماما اللي هي في ال
+
+784
+01:02:49,110 --> 01:02:52,950
+images و ال audio و ال video إلى آخرها هذه
+
+785
+01:02:52,950 --> 01:02:56,810
+المربعات اللي احنا شوفناها فعليا في المقدمة في
+
+786
+01:02:56,810 --> 01:03:01,350
+اللقاء الأول هي أنواع البيانات طبعا و علاقتها مع
+
+787
+01:03:01,350 --> 01:03:04,710
+بعض ممكن يكون في عندي structured و dynamic و في
+
+788
+01:03:04,710 --> 01:03:08,540
+عندي unstructuredو Dynamic ممكن يكون في عندي
+
+789
+01:03:08,540 --> 01:03:12,880
+Structured و Static و في عندي Structured و
+
+790
+01:03:12,880 --> 01:03:16,440
+Unstructured و Static احنا في ال data mining في ال
+
+791
+01:03:16,440 --> 01:03:22,720
+course هذا هنشتغل وين؟ Structured و Static هان
+
+792
+01:03:22,720 --> 01:03:27,880
+ليش؟ لأنه أسهل له و أنا لسه عمالي بدي أتعلم كيه
+
+793
+01:03:27,880 --> 01:03:31,020
+بدي أتعامل مع ال data لأنه يا جماعة الخير أنا هاخد
+
+794
+01:03:31,020 --> 01:03:35,470
+algorithm ال machine learning بده يبني خبرةتمام؟
+
+795
+01:03:35,470 --> 01:03:37,970
+عشان ياخد decision أو يديني معرفة بناءً على الـ
+
+796
+01:03:37,970 --> 01:03:43,290
+data طب ال data لو بدها تتغير باستمرار معناته أنا
+
+797
+01:03:43,290 --> 01:03:47,950
+بحاجة أن ال knowledge هذه اللي بدها تتصدر بدأ
+
+798
+01:03:47,950 --> 01:03:50,830
+باستمرار وعمليات ال learning في ال machine
+
+799
+01:03:50,830 --> 01:03:54,710
+learning مختلفة في batch وفي online وتقنيات هذه
+
+800
+01:03:54,710 --> 01:03:59,830
+غير عن هذه و ال performance تبعت هذه غير عن هذه
+
+801
+01:03:59,830 --> 01:04:03,530
+فاحنا الآن لسه بدنا نتعلم data mining فأنسب حاجة
+
+802
+01:04:03,530 --> 01:04:08,120
+إلنا وين؟أتعلم مع مين؟ مع الـ Static Data اللي
+
+803
+01:04:08,120 --> 01:04:11,480
+عادة بتكون ناتج الـ Business Intelligence Systems
+
+804
+01:04:11,480 --> 01:04:15,040
+أو في الـ Data Warehousing يعني بين جثين الـ Data
+
+805
+01:04:15,040 --> 01:04:20,500
+Structured و Static ليش الـ ERP هذا Structured؟
+
+806
+01:04:20,500 --> 01:04:25,480
+كيف كان؟ وين؟ هذه الـ ERP اختصار للـ Environmental
+
+807
+01:04:27,730 --> 01:04:31,450
+لأ لأ، فإنها علاقة بالبيئة ففي الآخر لما أنا بدأ
+
+808
+01:04:31,450 --> 01:04:36,710
+أتكلم في الـ .. في الـ system إذا بدك ال .. ال ..
+
+809
+01:04:36,710 --> 01:04:39,650
+environmental resource management مالهاش .. مالهاش
+
+810
+01:04:39,650 --> 01:04:43,830
+داخل يعني فبالبيئة هي dynamic كل فكرة بتتغير
+
+811
+01:04:43,830 --> 01:04:49,910
+الشيء؟ ال business intelligence آه، الآن هل كل شيء
+
+812
+01:04:49,910 --> 01:04:53,470
+هيتغير؟ ال rule اللي انبنت يا صاحبي ثابتة بس
+
+813
+01:04:53,470 --> 01:04:58,220
+النتائج لازم تتغير مين قال إنها بتتغير؟الـ rule
+
+814
+01:04:58,220 --> 01:05:02,100
+الآن إذا الـ rule بيقول واحد زائد واحد يساوي تلاتة
+
+815
+01:05:02,100 --> 01:05:08,080
+فالنتائج تبع ال system هذا تلاتة كل ما تجي input
+
+816
+01:05:08,080 --> 01:05:14,280
+واحد وواحد مش هيتغير، مصبوط؟ إلا لو أنا روحتش قعدت
+
+817
+01:05:14,280 --> 01:05:19,250
+تعليمه، قعدت تعليمه، في الآخر staticليش؟ لأنه
+
+818
+01:05:19,250 --> 01:05:21,530
+عبارة كمان مرة شباب في ال business intelligence
+
+819
+01:05:21,530 --> 01:05:24,750
+أنا عندي عبارة عن مجموعة من ال rules اللي انبنت
+
+820
+01:05:24,750 --> 01:05:30,350
+بناء على ال knowledge السابقة هضلني أستخدمها لحد
+
+821
+01:05:30,350 --> 01:05:33,110
+ما يصير في عندي knowledge جديدة وهذه لن تكون إلا
+
+822
+01:05:33,110 --> 01:05:36,410
+في واحد من اتنين إما أعمل retraining أو إعادة
+
+823
+01:05:36,410 --> 01:05:41,330
+تعليم لل model تبعي أو ال system تبعي يكون بتعلم
+
+824
+01:05:41,330 --> 01:05:44,550
+لوحده self learning model نعم
+
+825
+01:05:47,450 --> 01:05:52,730
+اه إيش .. إيش نقحة؟ الآن المؤمن بيسأل الـ data
+
+826
+01:05:52,730 --> 01:05:56,250
+اللي collecting by web scraper اللي .. اللي خلنا
+
+827
+01:05:56,250 --> 01:06:01,150
+نقول المتجمعين أو .. اللي إيش بيسموه متصيدين؟ لأ
+
+828
+01:06:01,150 --> 01:06:04,390
+مش كلها ضد القانون في مثلا الـ Twitter بتزودك ببعض
+
+829
+01:06:04,390 --> 01:06:07,830
+ال .. ال APIs اللي تبدأ تتجرد فكلها .. في بعضها
+
+830
+01:06:07,830 --> 01:06:10,610
+legal وفي illegal مش قضيتنا الآن لكن السؤال اللي
+
+831
+01:06:10,610 --> 01:06:15,130
+بيطرح نفسه إيش البيانات اللي أنا باخدها منه؟ إذا
+
+832
+01:06:15,130 --> 01:06:20,650
+أنا باخد textفباخد unstructured data طبعا أخدت ال
+
+833
+01:06:20,650 --> 01:06:24,330
+data set الكوربوس هذه و رميتها عندي على جهازي و
+
+834
+01:06:24,330 --> 01:06:28,530
+علمت النظام أول مرة و رجعت علمته بعد شهرين على نفس
+
+835
+01:06:28,530 --> 01:06:32,730
+ال data set و علمته بعد تلت أشهر هذه أصبحت في نطاق
+
+836
+01:06:32,730 --> 01:06:38,770
+.. في نطاق ال static data ما تغيرش جديد عنديتمام؟
+
+837
+01:06:38,770 --> 01:06:43,630
+لكن لو هذا ال document مع كل عملية learning أو بين
+
+838
+01:06:43,630 --> 01:06:46,310
+كل فترة والتانية بيصير عليه تغيير حتى لو كان عندي
+
+839
+01:06:46,310 --> 01:06:50,350
+على جهازي هذا بسميه dynamic تمام؟
+
+840
+01:06:52,750 --> 01:06:56,390
+في كل مجال بيصير في mining الآن يا جماعة الخير لو
+
+841
+01:06:56,390 --> 01:06:59,010
+احنا و ال course تبعنا اسمه data science أو علوم
+
+842
+01:06:59,010 --> 01:07:03,850
+بيانات المفروض بدي أتعامل مع كل هذه الأنواع لأن
+
+843
+01:07:03,850 --> 01:07:07,190
+عملية ال data collection و ال data preparation لكل
+
+844
+01:07:07,190 --> 01:07:12,690
+نوع مختلفة الآن بدي أعمل بدي أبني features من
+
+845
+01:07:12,690 --> 01:07:16,050
+الصورة غير عن ال features اللي بدي أبنيها من ال
+
+846
+01:07:16,050 --> 01:07:21,610
+text طب ما هي واحدة dynamic و واحدةstatic ولا لأ
+
+847
+01:07:21,610 --> 01:07:26,750
+بتفرج تماما عن ال audio بتفرج معايا عن ال video
+
+848
+01:07:26,750 --> 01:07:31,450
+streaming ال life فكل واحدة إلها processing خاصة
+
+849
+01:07:31,450 --> 01:07:35,210
+في جمع البيانات وفي محضير البيانات لعملية ال
+
+850
+01:07:35,210 --> 01:07:40,030
+mining تمام؟تي اي سؤال يا جماعة الخير؟ احنا اليوم
+
+851
+01:07:40,030 --> 01:07:43,710
+هيك .. هنحنجف والمحاضرة ان شاء الله تعالى هنبدأ
+
+852
+01:07:43,710 --> 01:07:47,170
+نتكلم عن ال data set بس إيه الشغلة أخرى قبل ما
+
+853
+01:07:47,170 --> 01:07:50,830
+تطلع الشباب؟ الآن اليوم ان شاء الله تعالى هحط على
+
+854
+01:07:50,830 --> 01:07:54,190
+ال model أول ما تدخل على صفحتنا فيه المنتدى،
+
+855
+01:07:54,190 --> 01:07:58,070
+المنتدى التنقيب البيانات هتكون فيه مجموعة أو فيه
+
+856
+01:07:58,070 --> 01:08:03,130
+زي boss محطوط في أسماء المجموعات الآن وزعوا نفسكوا
+
+857
+01:08:03,130 --> 01:08:07,820
+الأربعاتتلاتة أو أربعة تلاتة الحد الأدنى أربعة
+
+858
+01:08:07,820 --> 01:08:14,640
+الحد الأقصى كمجموعة وواحد منكوا بيعمل reply على ال
+
+859
+01:08:14,640 --> 01:08:17,740
+boss تبعي باسم المجموعة يعني هو اللي بيعمل reply
+
+860
+01:08:17,740 --> 01:08:20,760
+وبيقول احنا مجموعتنا مكوّنة فلان وفلان وفلان بذكر
+
+861
+01:08:20,760 --> 01:08:24,720
+الأسام الأشخاص التلاتة أو التانين اللي معاه شرايك
+
+862
+01:08:24,720 --> 01:08:28,520
+بدهم يعملوا مش like لأنه ماعناش ال like بس بدهم
+
+863
+01:08:28,520 --> 01:08:31,220
+يأكدوا له ان okay تمام احنا في المجموعة مع فلان
+
+864
+01:08:32,470 --> 01:08:36,990
+Okay بعد ما تخلص الأمور لو لقيت واحد لحاله هحطه في
+
+865
+01:08:36,990 --> 01:08:41,170
+مجموعة من المجموعات اللي أنا بأرتقيها بشكل مناسب
+
+866
+01:08:41,170 --> 01:08:42,250
+الله عطيكم العافية
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/dY2Slj6BExM_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/dY2Slj6BExM_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..952a512e1e24ed7e3da2e59462ae38934e75d3b7
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/dY2Slj6BExM_raw.json
@@ -0,0 +1 @@
+{"segments": [{"id": 1, "seek": 3477, "start": 5.01, "end": 34.77, "text": "بسم الله والحمد لله والصلاة والسلام على رسول الله اليوم إن شاء الله تعالى هنبدأ بالفعل بالفصل التاني أو بال chapter التاني من مساق تنقيب البيانات واللي هو عنوانه data understanding and preparation أو البعض بيسميه data processing data preprocessing فعليا ال chapter كله يتوحي محور حوالين فهم البيانات وكيف ممكن أنا أجهزها لعملية ال mining وما تنساش أنه لما ذكرنا وطبعا يعني بذكرك في ما مضى", "tokens": [3555, 38251, 21984, 16070, 35571, 3215, 24976, 3224, 16070, 9381, 15040, 3660, 16070, 3794, 37440, 15844, 12602, 3794, 12610, 21984, 45595, 20498, 36145, 13412, 16606, 21984, 37279, 6027, 7578, 8032, 1863, 44510, 10721, 20666, 5172, 30241, 20666, 5172, 36520, 16712, 7649, 1829, 34051, 20666, 7187, 16712, 7649, 1829, 9154, 47524, 995, 4587, 6055, 1863, 38436, 3555, 2423, 21292, 7649, 9307, 4032, 6027, 20292, 31439, 18871, 2407, 7649, 3224, 1412, 3701, 293, 13081, 34051, 29739, 3615, 11242, 4724, 1829, 38251, 1829, 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ال data set بشكل صناعي بس مش بشكل .. مش بذكاء صناعي أنا قاعد بسألك artificial data data مصنعة أو data مصطنعة تمام؟ ملاحظ .. ملاحظ الفرق؟ نجي هلأ ال equipment أو عفوا لل outlook", "tokens": [1863, 7435, 1829, 4032, 4117, 8848, 23275, 8978, 2423, 39184, 12877, 17711, 20449, 8315, 47395, 14739, 41850, 6024, 48506, 39896, 8978, 18871, 16254, 5927, 34051, 4724, 9957, 10874, 3794, 9957, 1412, 46811, 11933, 3215, 9778, 6027, 11296, 15844, 2423, 1412, 992, 4724, 8592, 28820, 20328, 8315, 3615, 1829, 4724, 3794, 37893, 4724, 8592, 28820, 4386, 37893, 4724, 8848, 4117, 16606, 20328, 8315, 3615, 1829, 41850, 12174, 995, 22488, 4724, 3794, 10721, 23275, 11677, 1412, 1412, 3714, 9381, 1863, 27884, 34051, 1412, 3714, 9381, 9566, 1863, 27884, 46811, 10943, 22807, 3714, 15040, 5016, 19913, 4386, 3714, 15040, 5016, 19913, 27188, 2288, 4587, 22807, 8717, 7435, 1829, 8032, 1211, 10721, 2423, 5927, 34051, 6225, 5172, 14407, 24976, 484, 752, 453], "avg_logprob": -0.2364758350769011, "compression_ratio": 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3352.93, "end": 3376.01, "text": "فكر بضيقك يا جدش أنواع البيانات المختلفة اللي عندنا أنواع البيانات أربع أنواع dynamic structured وهي ال data ال organized in tables أو relation ده تم رتبه ولمّا بتكلم structured البيانات مش هتطلع عن النمط هذا", "tokens": [5172, 37983, 4724, 11242, 1829, 4587, 4117, 35186, 10874, 3215, 8592, 14739, 14407, 3615, 2423, 21292, 7649, 9307, 9673, 46456, 46538, 3660, 13672, 1829, 43242, 8315, 14739, 14407, 3615, 2423, 21292, 7649, 9307, 5551, 25513, 3615, 14739, 14407, 3615, 8546, 18519, 37037, 1829, 2423, 1412, 2423, 9983, 294, 8020, 34051, 9721, 11778, 3224, 46811, 12602, 2655, 3555, 3224, 4032, 19528, 11703, 995, 39894, 4117, 19528, 18519, 2423, 21292, 7649, 9307, 37893, 8032, 2655, 9566, 1211, 3615, 18871, 28239, 2304, 9566, 23758], "avg_logprob": -0.24542683017690006, "compression_ratio": 1.6331658291457287, "no_speech_prob": 0.0, "words": [{"start": 3352.93, "end": 3353.35, "word": "فكر", "probability": 0.87158203125}, {"start": 3353.35, "end": 3353.79, 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notation", "probability": 0.98046875}, {"start": 3447.76, "end": 3448.42, "word": " object", "probability": 0.98828125}, {"start": 3448.42, "end": 3451.12, "word": " object", "probability": 0.93359375}, {"start": 3451.12, "end": 3451.78, "word": " notation", "probability": 0.984375}, {"start": 3451.78, "end": 3453.96, "word": " عشان", "probability": 0.9847005208333334}, {"start": 3453.96, "end": 3454.28, "word": " ترتيب", "probability": 0.976806640625}, {"start": 3454.28, "end": 3454.74, "word": " الحروف", "probability": 0.98876953125}], "temperature": 1.0}, {"id": 127, "seek": 349173, "start": 3465.89, "end": 3491.73, "text": "Json عشان تتضحلك الصورة افترض المثال التالي عند ال student ID 123 name Hashem نجلنا معدلك يا Hashem كمل 95", "tokens": [41, 3015, 6225, 8592, 7649, 6055, 2655, 11242, 5016, 23275, 31767, 13063, 3660, 1975, 5172, 2655, 43042, 9673, 12984, 6027, 16712, 6027, 1829, 43242, 2423, 3107, 7348, 34466, 1315, 30775, 443, 8717, 7435, 1211, 8315, 20449, 3215, 23275, 35186, 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الان ال json أو ال javascript ال json object بياخد الشكل هذا هو عبارة عن مجموعة من ال key و ال values مجموعة من ال key و ال values الان ال json object هو عبارة عن semi structured", "tokens": [25528, 6156, 2288, 33753, 4117, 35186, 5551, 14851, 45636, 8315, 16490, 2304, 3794, 3660, 34683, 3794, 3615, 9957, 2423, 7649, 2423, 361, 3015, 34051, 2423, 361, 37331, 5944, 2423, 361, 3015, 2657, 4724, 1829, 47283, 3215, 25124, 28820, 23758, 31439, 6225, 3555, 9640, 3660, 18871, 3714, 7435, 2304, 2407, 27884, 9154, 2423, 2141, 4032, 2423, 4190, 3714, 7435, 2304, 2407, 27884, 9154, 2423, 2141, 4032, 2423, 4190, 2423, 7649, 2423, 361, 3015, 2657, 31439, 6225, 3555, 9640, 3660, 18871, 12909, 18519], "avg_logprob": -0.16530107434202984, "compression_ratio": 1.7976878612716762, "no_speech_prob": 3.516674041748047e-06, "words": [{"start": 3493.38, "end": 3493.58, "word": "يا", "probability": 0.86474609375}, {"start": 3493.58, "end": 3494.02, "word": " فرحتك", "probability": 0.955810546875}, {"start": 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0.49267578125}, {"start": 3505.52, "end": 3505.6, "word": " ال", "probability": 0.9658203125}, {"start": 3505.6, "end": 3506.04, "word": " values", "probability": 0.97021484375}, {"start": 3506.04, "end": 3507.14, "word": " مجموعة", "probability": 0.92939453125}, {"start": 3507.14, "end": 3507.72, "word": " من", "probability": 0.99462890625}, {"start": 3507.72, "end": 3507.88, "word": " ال", "probability": 0.986328125}, {"start": 3507.88, "end": 3508.06, "word": " key", "probability": 0.9609375}, {"start": 3508.06, "end": 3508.2, "word": " و", "probability": 0.9482421875}, {"start": 3508.2, "end": 3508.3, "word": " ال", "probability": 0.95947265625}, {"start": 3508.3, "end": 3508.76, "word": " values", "probability": 0.98681640625}, {"start": 3508.76, "end": 3510.44, "word": " الان", "probability": 0.77099609375}, {"start": 3510.44, "end": 3510.98, "word": " ال", "probability": 0.97802734375}, {"start": 3510.98, "end": 3511.34, "word": " json", "probability": 0.981201171875}, {"start": 3511.34, "end": 3511.76, "word": " object", "probability": 0.9833984375}, {"start": 3511.76, "end": 3511.98, "word": " هو", "probability": 0.7958984375}, {"start": 3511.98, "end": 3512.42, "word": " عبارة", "probability": 0.997314453125}, {"start": 3512.42, "end": 3512.62, "word": " عن", "probability": 0.9912109375}, {"start": 3512.62, "end": 3512.98, "word": " semi", "probability": 0.7646484375}, {"start": 3512.98, "end": 3513.6, "word": " structured", "probability": 0.482177734375}], "temperature": 1.0}, {"id": 129, "seek": 354518, "start": 3521.34, "end": 3545.18, "text": "ليش semi-structured؟ لأنه ممكن أنا قاعد يقوله عند ال student name أو ال name سامح ال ID 124 وماعنديش ال GPA لاحظ اختلف في الترتيب؟", "tokens": [20292, 8592, 12909, 12, 372, 46847, 22807, 5296, 33456, 3224, 3714, 43020, 41850, 12174, 995, 22488, 7251, 39648, 3224, 43242, 2423, 3107, 1315, 34051, 2423, 1315, 8608, 10943, 5016, 2423, 7348, 2272, 19, 4032, 15042, 3615, 1863, 16254, 8592, 2423, 41321, 20193, 5016, 19913, 1975, 46456, 46538, 8978, 16712, 2288, 31371, 3555, 22807], "avg_logprob": -0.19791667052993067, "compression_ratio": 1.2298136645962734, "no_speech_prob": 0.0, "words": [{"start": 3521.34, "end": 3521.78, "word": "ليش", "probability": 0.893310546875}, {"start": 3521.78, "end": 3522.02, "word": " semi", "probability": 0.5322265625}, {"start": 3522.02, "end": 3522.7, "word": "-structured؟", "probability": 0.7288818359375}, {"start": 3522.7, "end": 3523.04, "word": " لأنه", "probability": 0.8974609375}, {"start": 3523.04, "end": 3523.4, "word": " ممكن", "probability": 0.984619140625}, {"start": 3523.4, "end": 3523.74, "word": " أنا", "probability": 0.77880859375}, {"start": 3523.74, "end": 3524.04, "word": " قاعد", "probability": 0.6648763020833334}, {"start": 3524.04, "end": 3524.62, "word": " يقوله", "probability": 0.6715494791666666}, {"start": 3524.62, "end": 3525.74, "word": " عند", "probability": 0.51416015625}, {"start": 3525.74, "end": 3525.88, "word": " ال", 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"probability": 0.3955078125}, {"start": 3541.64, "end": 3543.86, "word": " لاحظ", "probability": 0.94189453125}, {"start": 3543.86, "end": 3544.24, "word": " اختلف", "probability": 0.9441731770833334}, {"start": 3544.24, "end": 3544.4, "word": " في", "probability": 0.95263671875}, {"start": 3544.4, "end": 3545.18, "word": " الترتيب؟", "probability": 0.96904296875}], "temperature": 1.0}, {"id": 130, "seek": 357125, "start": 3545.93, "end": 3571.25, "text": "تمام؟ ومافيش عندياش الـ GPA وعدد ال .. في عدد ال .. ال bears عدد الأزواج مختلف الموجودة لأن كل واحد بنسميه احنا key و value بنسميه bear عدد الأزواج مختلف وبالتالي هو structured لأنه مكون من bears but semi-structured لأنه عدد ال bears وترتيبهم مش ثابت", "tokens": [39237, 10943, 22807, 4032, 15042, 41185, 8592, 43242, 25528, 8592, 2423, 39184, 41321, 4032, 22488, 3215, 2423, 4386, 8978, 6225, 3215, 3215, 2423, 4386, 2423, 17276, 6225, 3215, 3215, 16247, 11622, 2407, 26108, 3714, 46456, 46538, 9673, 29245, 23328, 3660, 5296, 33456, 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370509, "start": 3675.47, "end": 3705.09, "text": "لكن لما باجي بتكلم أنا جدول الطلاب جدول الطلاب جدول الطلاب مافيش مجال بدي أكون كل البيانات اللي موجودة فيه كذلك في عندي التصنيفين التانين اللي هي الـ Dynamic وفي عندي الـ Static في عندي Dynamic وعندي Static الـ Dynamic هي عبارة عن ال data اللي بتتغير باستمرار ال content تبعتها بتتغير باستمرار الصورة Dynamic يا شباب", "tokens": [1211, 19452, 5296, 15042, 4724, 26108, 1829, 39894, 4117, 19528, 41850, 10874, 3215, 12610, 41950, 15040, 3555, 10874, 3215, 12610, 41950, 15040, 3555, 10874, 3215, 12610, 41950, 15040, 3555, 19446, 41185, 8592, 3714, 7435, 6027, 4724, 16254, 5551, 30544, 28242, 2423, 21292, 7649, 9307, 13672, 1829, 3714, 29245, 23328, 3660, 8978, 3224, 9122, 8848, 23275, 8978, 18871, 16254, 16712, 9381, 22653, 5172, 9957, 16712, 7649, 9957, 13672, 1829, 39896, 2423, 39184, 45440, 4032, 41185, 18871, 16254, 2423, 39184, 745, 2399, 8978, 18871, 16254, 45440, 4032, 3615, 1863, 16254, 745, 2399, 2423, 39184, 45440, 39896, 6225, 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0.9641927083333334}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 4122.5404375, "duration_after_vad": 3945.060624999987}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/hrMDIeuEJkQ.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/hrMDIeuEJkQ.srt
new file mode 100644
index 0000000000000000000000000000000000000000..8ec68282a05c57ecee6b9535f513f794420a0c40
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/hrMDIeuEJkQ.srt
@@ -0,0 +1,2867 @@
+1
+00:00:04,840 --> 00:00:07,380
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:07,380 --> 00:00:11,680
+أهلا وسهلا بكم يا شباب، إن شاء الله، نحن اليوم نكمل
+
+3
+00:00:11,680 --> 00:00:14,360
+مع الـ chapter data understanding and data
+
+4
+00:00:14,360 --> 00:00:16,700
+preparation، وهذا الـ chapter، المحاضرة هي التي
+
+5
+00:00:16,700 --> 00:00:20,200
+ستكون المحاضرة الأخيرة في الـ chapter الموجود
+
+6
+00:00:20,200 --> 00:00:23,200
+بين أيدينا. كنا قد تكلمنا أن فعلياً، عشان أنا أعمل أي
+
+7
+00:00:23,200 --> 00:00:27,100
+data mining project، يلزمُني data cleaning، data
+
+8
+00:00:27,100 --> 00:00:32,500
+integration، data transformation، data selection،
+
+9
+00:00:32,500 --> 00:00:36,130
+data mining pattern evaluation، وknowledge
+
+10
+00:00:36,130 --> 00:00:39,150
+presentation. وقلنا هذه الخطوات السبعة التي أنا
+
+11
+00:00:39,150 --> 00:00:43,310
+فعلياً أمر بها في أي مشروع له علاقة بـ data mining.
+
+12
+00:00:43,310 --> 00:00:47,290
+وكنا قد حكينا في المحاضرة الأخيرة، بدأنا نتكلم عن الـ
+
+13
+00:00:47,290 --> 00:00:49,910
+data transformation، وقلنا هدف الـ data
+
+14
+00:00:49,910 --> 00:00:55,030
+transformation أن أضع البيانات في صورة جديدة تتناسب
+
+15
+00:00:55,030 --> 00:00:58,970
+مع عملية الـ mining التي أنا أريد أن أقوم بها، وذكرنا
+
+16
+00:00:58,970 --> 00:01:01,230
+أن من الممكن أن أطبق smoothing أو aggregation،
+
+17
+00:01:01,230 --> 00:01:04,770
+generalization، و الـ normalization. ومحاضرتنا الأخيرة
+
+18
+00:01:04,770 --> 00:01:08,190
+شغلة في المحاضرة الماضية، بدأنا مع الـ normalization،
+
+19
+00:01:08,190 --> 00:01:11,870
+وقلنا الـ normalization أنه أنا فعلياً أذهب وأعمل
+
+20
+00:01:11,870 --> 00:01:15,850
+scaling للـ data set الموجودة عندي، أو عفواً للـ
+
+21
+00:01:15,850 --> 00:01:19,030
+attributes، أو للـ data التي عندي، بحيث أن تتناسب مع
+
+22
+00:01:19,990 --> 00:01:23,850
+طبيعة الـ mining task التي عندي، وقلنا أبسط الأمور
+
+23
+00:01:23,850 --> 00:01:27,110
+لو كان في عندي two attributes، و الـ range أو الـ
+
+24
+00:01:27,110 --> 00:01:30,290
+gap بين الـ ranges التابعة لهما عالية جداً أو عالية كثيراً،
+
+25
+00:01:30,290 --> 00:01:34,210
+مثل ما قلنا، واحد من صفر لواحد، والـ attribute
+
+26
+00:01:34,210 --> 00:01:38,240
+الثاني من مئة لألف، هذين الاثنين، لو أنا أردت أن أجمعهما
+
+27
+00:01:38,240 --> 00:01:42,400
+معاً على رسمة واحدة، من المستحيل أن أقدر أُطبقهما.
+
+28
+00:01:42,400 --> 00:01:45,400
+فبالتالي، لازم أنا أعمل scaling، أحطّهُما في
+
+29
+00:01:45,400 --> 00:01:49,600
+نفس الـ range، يُسهل عليّ رسمهما، والشغل الثاني أيضاً، الـ
+
+30
+00:01:49,600 --> 00:01:52,620
+computation التابعة للـ algorithm تصبح أبسط عندما تكون
+
+31
+00:01:52,620 --> 00:01:56,600
+أعطيتها كلها من نفس المستوى. وكنا قد تكلمنا عن الـ
+
+32
+00:01:56,600 --> 00:01:59,800
+zero score، أو الـ z score normalization، أو الـ
+
+33
+00:01:59,800 --> 00:02:04,180
+standard normalization. قلنا الفكرة بالـ normal بالـ
+
+34
+00:02:04,180 --> 00:02:07,480
+standard، أو بالـ zero score، أنه أنا فعلياً للـ
+
+35
+00:02:07,480 --> 00:02:11,500
+attributes التي عندي، أحتاج أن أحسب المتوسط الحسابي
+
+36
+00:02:11,500 --> 00:02:17,380
+الـ mean، وأحسب الـ variance أو الانحراف المعياري للـ
+
+37
+00:02:17,380 --> 00:02:21,400
+attributes الموجودة عندي. والانحراف المعياري هو
+
+38
+00:02:21,400 --> 00:02:28,200
+عبارة عن حاصل مجموع تربيع الفروقات ما بين النقاط و
+
+39
+00:02:28,200 --> 00:02:32,020
+المتوسط الحسابي، على العدد، تحت الجذر التربيعي،
+
+40
+00:02:32,020 --> 00:02:38,090
+وشفنا المرة الماضية تأثيره فعلياً بالشكل هذا، عندما
+
+41
+00:02:38,090 --> 00:02:40,970
+ذهبتُ وأطبقتُ الـ zero mean، كان مفهومها أن عندما
+
+42
+00:02:40,970 --> 00:02:45,110
+أبدأُ أطبق الـ normalization هذه، أو الـ scaling،
+
+43
+00:02:45,110 --> 00:02:47,770
+هذا، المتوسط الحسابي الذي سيظهر مع الـ attribute
+
+44
+00:02:47,770 --> 00:02:51,630
+الجديد، أو مع الـ value الجديد، قيمته صفر، وبالتالي
+
+45
+00:02:51,630 --> 00:02:57,870
+ستكون عندي الـ variance قيمتها واحد. وطبعاً قلنا هذه
+
+46
+00:02:57,870 --> 00:03:02,560
+واضحة في الرسمة. لاحظ أن هذه الـ data، الـ original، طبيعية.
+
+47
+00:03:02,560 --> 00:03:06,300
+الآن، هيها موزعة على two classes، عندما عملت لها
+
+48
+00:03:06,300 --> 00:03:11,760
+scaling بالـ standard scalar، أو بالـ zero score. لاحظ
+
+49
+00:03:11,760 --> 00:03:16,000
+توزعت على الأربع أرباع التي في الـ Cartesian plane،
+
+50
+00:03:16,000 --> 00:03:19,320
+وبالتالي، أنا أقدر أتكلم أن فعلياً، في قيم تلغي
+
+51
+00:03:19,320 --> 00:03:22,660
+البعض عندما أجمع متوسطهما، أو عندما أبحث عن متوسطهما
+
+52
+00:03:22,660 --> 00:03:27,020
+الحسابي. اليوم، إن شاء الله، سنكمل، أو كنا قد حكينا أيضاً في
+
+53
+00:03:27,020 --> 00:03:29,380
+الموضوع، لأن هذه آخر الشغلات التي أنهينا بها محاضرتنا
+
+54
+00:03:29,380 --> 00:03:32,340
+الماضية، الـ robust scalar، هي عبارة عن special
+
+55
+00:03:32,340 --> 00:03:38,240
+scalar من الـ zero score، لكن بدلاً من أن يعتمد على
+
+56
+00:03:38,240 --> 00:03:43,200
+الـ mean، يعتمد على الـ median، والـ quartile، بدلاً من
+
+57
+00:03:43,200 --> 00:03:46,440
+الـ mean، الـ median، والـ variance، الـ min max score.
+
+58
+00:03:46,440 --> 00:03:50,750
+قلنا الـ min max score، مفهومها أن أنا فعلياً أحاول أن
+
+59
+00:03:50,750 --> 00:03:54,130
+أحصر الـ attributes هذه، أو الـ values هذه، ضمن فترة أنا
+
+60
+00:03:54,130 --> 00:03:58,830
+أحددها، ضمن مجموعة من العناصر التي أنا أريدها.
+
+61
+00:03:58,830 --> 00:04:03,850
+وليكن على سبيل المثال، أنا كان عندي الـ values: 12،
+
+62
+00:04:03,850 --> 00:04:12,170
+15، 10، 11، 20. هذه القيم الموجودة عندي، وأبدأ أذهب
+
+63
+00:04:12,170 --> 00:04:17,210
+وأضعها في فترة من صفر لواحد، أبسط، لكي تكون معي الآن
+
+64
+00:04:17,210 --> 00:04:22,510
+أسهل في الحل. الآن حسب الـ Min Max Normalization هذه،
+
+65
+00:04:22,510 --> 00:04:25,770
+كل ما أنا أفعله، أقوم بعمل Shift، وتقليص للـ
+
+66
+00:04:25,770 --> 00:04:28,610
+interval، الـ interval الحقيقي الذي عندي، من عشرة
+
+67
+00:04:28,610 --> 00:04:34,090
+لعشرين.  الـ data موجودة، الـ data موجودة
+
+68
+00:04:34,090 --> 00:04:37,850
+من عشرة لعشرين. الآن أنا أريد أن أذهب وأجعلَها كلها
+
+69
+00:04:37,850 --> 00:04:43,330
+محصورة ما بين صفر وواحد. يعني الـ minimum التابعة لي
+
+70
+00:04:43,330 --> 00:04:51,310
+جديداً قيمتها عشرة، والعشرون هذه هي الـ max.  طب الـ new
+
+71
+00:04:51,310 --> 00:04:59,650
+minimum التي أنا أريدها صفر، والـ new max واحد.
+
+72
+00:04:59,650 --> 00:05:03,550
+أنا قاعد بقول، بيُخليها من صفر لواحد. كل الأرقام
+
+73
+00:05:03,550 --> 00:05:07,170
+ستصبح من صفر لواحد. الآن بكل بساطة، أي قيمة من القيم
+
+74
+00:05:07,170 --> 00:05:10,710
+هذه، تُطبق عليها هذا القانون البسيط الموجود
+
+75
+00:05:10,710 --> 00:05:14,610
+عندنا. طبعاً قوانينه يا شباب مطلوبة بالحفظ، تمام؟ لأن
+
+76
+00:05:14,610 --> 00:05:19,290
+لن أزيدك بالقانون وأنت تحلم. الآن نأتي نأخذ على
+
+77
+00:05:19,290 --> 00:05:23,630
+سبيل المثال، المفروض العشرة هذه، بعد القانون، ستطابق
+
+78
+00:05:23,630 --> 00:05:28,650
+من؟ الصفر. تعال نأخذ العشرة، القيمة الجديدة للعشرة
+
+79
+00:05:28,650 --> 00:05:35,950
+تساوي العشرة ناقص الـ minimum التابعة للـ attribute، الـ
+
+80
+00:05:35,950 --> 00:05:42,330
+minimum التابعة للـ attribute كم؟ عشرة، على الـ
+
+81
+00:05:42,330 --> 00:05:46,700
+maximum ناقص الـ minimum التابعة للـ attribute، عشرون
+
+82
+00:05:46,700 --> 00:05:52,640
+ناقص عشرة، مضروبة في الـ new maximum، ناقص الـ new
+
+83
+00:05:52,640 --> 00:06:01,260
+minimum. الـ new maximum واحد، ناقص صفر، زائد الـ
+
+84
+00:06:01,260 --> 00:06:08,000
+minimum. الـ new minimum للـ attribute صفر، صفر على
+
+85
+00:06:08,000 --> 00:06:15,310
+عشرة، مضروب في واحد، زائد صفر، صفر.  بصفر؟ وبهكذا أنا
+
+86
+00:06:15,310 --> 00:06:19,770
+أحصل على الـ values، وأطبقها. تعالوا نشوف الخمسة عشر أين
+
+87
+00:06:19,770 --> 00:06:28,810
+ستصبح. نفس الكلام يا أصدقائي. الآن، خمسة عشر ناقص عشرة، على
+
+88
+00:06:28,810 --> 00:06:37,410
+عشرين ناقص عشرة، مضروبة في واحد ناقص صفر، زائد الصفر.
+
+89
+00:06:39,330 --> 00:06:43,130
+لا، ليست صفر، حرام عليك! خمسة عشر ناقص عشرة، خمسة، خمسة على
+
+90
+00:06:43,130 --> 00:06:49,010
+عشرة في واحد زائد صفر، نصف.
+
+91
+00:06:49,010 --> 00:06:52,790
+فعلاً، هي تقع في نصف الـ interval ما بين العشرة
+
+92
+00:06:52,790 --> 00:06:57,410
+والعشرين، الخمسة عشر تقع في الوسط، تمام؟  مفهوم يا شباب؟
+
+93
+00:06:57,410 --> 00:07:01,290
+طيب، وبهذا نكون قد أنهينا من الـ normalization،
+
+94
+00:07:01,290 --> 00:07:04,610
+بإعتمادنا على الـ min max.
+
+95
+00:07:08,350 --> 00:07:11,010
+Normalization أو Scalar. طبعاً هنا أنا أتكلم عن
+
+96
+00:07:11,010 --> 00:07:15,810
+Linear Transformation، مجرد معادلة خطية، نقلت الـ
+
+97
+00:07:15,810 --> 00:07:24,550
+data إلى range جديد. هذا مثال فقط، أنا أُزوّدك بالـ
+
+98
+00:07:24,550 --> 00:07:29,150
+minimum، والـ maximum في الأصل، وأسألك، الـ 73600
+
+99
+00:07:29,150 --> 00:07:34,910
+هذه، ستصبح أسهل.  أسهل scalar يمكن أن أطبقه أنا، وهو الـ
+
+100
+00:07:34,910 --> 00:07:39,910
+decimal scalar. Decimal Scalar، الـ Decimal Scalar، أو
+
+101
+00:07:39,910 --> 00:07:42,970
+الـ Decimal Scaling. أنا عندي قيم، كما قلنا، بعض
+
+102
+00:07:42,970 --> 00:07:51,710
+العملات تُقاس بالملايين، 170 مليون في
+
+103
+00:07:51,710 --> 00:07:54,550
+الحساب، أو في الـ computation التابعة للـ system، سيُرهقني
+
+104
+00:07:54,550 --> 00:07:57,370
+كثيراً هذا الرقم، وسيُرهق الـ computer أيضاً يا أصدقائي.
+
+105
+00:07:57,370 --> 00:08:01,470
+فما هو الحل؟ أريد أن أغير هذه الأرقام. كل الـ
+
+106
+00:08:01,470 --> 00:08:05,330
+attribute يكون لها هذه الصفة. مفهوم الـ scaling أنه أنا
+
+107
+00:08:05,330 --> 00:08:10,710
+ممكن أن أصغر له قيم معينة، أحجمه، كيف أحجمه؟  أقسمه على
+
+108
+00:08:10,710 --> 00:08:14,630
+عشرة أس عشرة.
+
+109
+00:08:14,630 --> 00:08:18,310
+أس. الآن أنا أريد أن أتخلص من كل الأصفار، معناته هي سبعة،
+
+110
+00:08:18,310 --> 00:08:24,490
+و هذا الثامن. معناته، نقسم الـ X على عشرة أس
+
+111
+00:08:24,490 --> 00:08:28,910
+ثمانية، على سبيل المثال. ما هي القيمة التي ستظهر عندي؟
+
+112
+00:08:28,910 --> 00:08:34,690
+واحد فاصلة سبعة، وكل الأرقام بنفس النظام الموجود عند
+
+113
+00:08:34,690 --> 00:08:38,450
+هنا، وبالتالي هذا أسهل واحد.  طب هل من الـ decimal
+
+114
+00:08:38,450 --> 00:08:44,130
+scaling هذا، أو ضمن الـ scalars السابقة، أقدر أُغير
+
+115
+00:08:44,130 --> 00:08:51,430
+أو أكبّر الـ range؟ كيف أفعل يا أصدقائي؟  نضرب
+
+116
+00:08:51,430 --> 00:08:57,030
+في ماذا؟ نضرب في عشرة، نضرب في عشرة، تمام؟ أو نترك نفس
+
+117
+00:08:57,030 --> 00:08:58,910
+المعادلة ونجعل الـ K سالبة.
+
+118
+00:09:01,480 --> 00:09:05,840
+فتتحول العملية مباشرة إلى ضرب.  طيب، في الـ min max،
+
+119
+00:09:05,840 --> 00:09:10,540
+أقدر أكبّر الـ range.  كانت أساساً عندي من صفر لـ
+
+120
+00:09:10,540 --> 00:09:16,560
+واحد، أنا أريد أن أجعلها من واحد لعشرة. ينفع نفس
+
+121
+00:09:16,560 --> 00:09:21,600
+القانون، نفس المعادلة، لكن مع تطبيق معاملات جديدة
+
+122
+00:09:21,600 --> 00:09:25,180
+في المعادلة الجديدة. ستكون الـ old minimum، أو الـ
+
+123
+00:09:25,180 --> 00:09:28,280
+attribute minimum،  لـ الـ new minimum، و للـ new
+
+124
+00:09:28,280 --> 00:09:33,180
+maximum.  وخلصنا. طب هل ممكن هذا
+
+125
+00:09:33,180 --> 00:09:41,240
+الكلام يصير مع الـ Standard Scalar؟  أكبر الـ .. ماذا؟
+
+126
+00:09:41,240 --> 00:09:44,780
+الـ .. ماذا؟ الـ Standard Scalar؟ الذي يحسب المتوسط
+
+127
+00:09:44,780 --> 00:09:52,320
+الحسابي، والانحراف المعياري. أولاً، هذا لا يُمكن،
+
+128
+00:09:52,320 --> 00:09:56,400
+لأن المتغيرات تابعة، تابعة لكل الـ attributes،
+
+129
+00:09:56,400 --> 00:10:00,620
+الـ variance تابعة لكل الـ attributes، وبالتالي، لا
+
+130
+00:10:00,620 --> 00:10:04,650
+يوجد مجال. اسمه Standard، مافيش فيه لعب.
+
+131
+00:10:04,650 --> 00:10:14,470
+تمام. سنتنقل الآن إلى موضوع data reduction.  نحن كنا
+
+132
+00:10:14,470 --> 00:10:18,010
+نتكلم عن من؟ عن الـ data transformation، وكان
+
+133
+00:10:18,010 --> 00:10:20,650
+نتكلم بالتحديد في الـ transformation، الـ scaling.
+
+134
+00:10:20,650 --> 00:10:24,590
+الآن أريد أن أتكلم في الـ data، في الـ transformation، أريد
+
+135
+00:10:24,590 --> 00:10:27,710
+أن أتكلم عن الـ data reduction. الآن، مفهوم الـ
+
+136
+00:10:27,710 --> 00:10:33,360
+transformation، أن صورة الـ data كانت في صورة، و أصبحت
+
+137
+00:10:33,360 --> 00:10:37,480
+في صورة مختلفة.  ممكن هذه الصورة فعلياً كانت تأثير
+
+138
+00:10:37,480 --> 00:10:41,820
+فقط في البيانات، كما عملت بالـ Scaling. نفس الـ
+
+139
+00:10:41,820 --> 00:10:45,620
+attributes بقيت كما هي، والـ rows بقيت كما هي،
+
+140
+00:10:45,620 --> 00:10:48,840
+من ناحية العدد، لكن الـ data الموجودة في الـ
+
+141
+00:10:48,840 --> 00:10:53,220
+attributes هي التي أخذت صورة جديدة، وبهذا أصبحت كل
+
+142
+00:10:53,220 --> 00:10:57,360
+الـ data's لها صورة جديدة، أو form جديدة. لكن
+
+143
+00:10:57,360 --> 00:11:01,860
+الآن، في الـ data reduction، هو عبارة عن تحوير للـ data
+
+144
+00:11:01,860 --> 00:11:07,360
+أنني أريد أن أقلل حجم البيانات. يا دكتور، أنت منذ البداية
+
+145
+00:11:07,360 --> 00:11:09,760
+الـ chapter، و تقول لنا، اكبروا البيانات، ومصادر بنا
+
+146
+00:11:09,760 --> 00:11:12,960
+البيانات أخرى، وعزز، و integration، و هكذا.  وتقول لي أريد
+
+147
+00:11:12,960 --> 00:11:15,860
+أن أفعل reduction؟  آه، أنت بحاجة أن تعمل reduction
+
+148
+00:11:15,860 --> 00:11:21,180
+أحياناً، الـ data set  already كبيرة عندك، فيها مليون
+
+149
+00:11:21,180 --> 00:11:21,600
+record.
+
+150
+00:11:24,360 --> 00:11:28,360
+آخذ المليون record، وأتعلم عليهم؟  جيد، لكن سيكلفك كثيراً
+
+151
+00:11:28,360 --> 00:11:32,040
+وقتاً، وتقوم بالـ analysis.  لو أنا جئتُ وسألتك، أن تعمل
+
+152
+00:11:32,040 --> 00:11:35,700
+analysis لخمسة attributes، وعشرة rows، يعني خمسون
+
+153
+00:11:35,700 --> 00:11:41,040
+value، أو أزيد الـ rows، وأقول مئة، يصبح خمسمائة
+
+154
+00:11:41,040 --> 00:11:43,800
+خمسون، أم خمسمائة؟  أيٌّ منها تستخدم في الـ analysis؟
+
+155
+00:11:44,390 --> 00:11:47,750
+الخمسون، بكل تأكيد.  قلنا، هو الكمبيوتر يختلف معي يا
+
+156
+00:11:47,750 --> 00:11:50,470
+أستاذ؟ آه، يختلف معك عندما يتعلق الأمر بالشغل بالملايين، كما
+
+157
+00:11:50,470 --> 00:11:54,030
+نحن نتكلم. جالسين، ليست قيمة واحدة، وليست معادلة واحدة
+
+158
+00:11:54,030 --> 00:11:57,970
+التي تُحسب، لكن تصبح تختلف معك.  فعشان هيك، أنا
+
+159
+00:11:57,970 --> 00:12:02,590
+أحتاج أحياناً أن أعمل reduction. لكن الشرط الأساسي، الـ
+
+160
+00:12:02,590 --> 00:12:08,090
+reduction هذا، ليس على حساب جودة الـ data. يعني، بين
+
+161
+00:12:08,090 --> 00:12:11,010
+الجيدين، عندما أقول، والله، أنني أريد أن آخذ مثلاً من
+
+162
+00:12:11,010 --> 00:12:15,370
+المئة ألف، أريد أن آخذ خمسين ألف فقط، أريد أن أضمن أن الـ 50
+
+163
+00:12:15,370 --> 00:12:18,870
+ألف هؤلاء يمثلون كل الـ data الحقيقية،
+
+164
+00:12:18,870 --> 00:12:22,490
+representative لكل الـ data.  أجي أقول، إن في عندي
+
+165
+00:12:22,490 --> 00:12:25,870
+مجموعة من الـ attributes، أنا لا أريدها فعلياً، أنا
+
+166
+00:12:25,870 --> 00:12:31,510
+لا أريدها، لأنها إما useless، غير مفيدة عندي، أو
+
+167
+00:12:31,510 --> 00:12:35,850
+فعلياً، الـ effect التابعة لها بسيط جداً، لا يؤثر،
+
+168
+00:12:35,850 --> 00:12:41,690
+وبالتالي أنا جالس أتكلم عن reduction، هدفها أن أجعل
+
+169
+00:12:41,690 --> 00:12:48,250
+الـ data set تصبح عندي much smaller من الأول، جبتها
+
+170
+00:12:48,250 --> 00:12:51,070
+صغيرة في الأول، أنت الـ data ما كنت تعرفها أساساً،
+
+171
+
+223
+00:16:33,890 --> 00:16:37,990
+discretization بتكلم على reduction على مستوى ال values
+
+224
+00:16:37,990 --> 00:16:42,830
+عدد ال distinct values في ال attribute و خلينا
+
+225
+00:16:42,830 --> 00:16:48,340
+الآن نبدأ مع الأولى كمان مرة، جماعة الخير، بعيد و
+
+226
+00:16:48,340 --> 00:16:53,140
+بأكد أنا بدي أعمل reduction لل data set بحيث أنها
+
+227
+00:16:53,140 --> 00:16:57,700
+تكون أصغر ما يمكن بنفس الخصائص أو نفس النتائج
+
+228
+00:16:57,700 --> 00:17:02,100
+التحليلية اللي تطلع فيها، كل الـ database الكبيرة، هل
+
+229
+00:17:02,100 --> 00:17:05,400
+الكلام هذا متاح؟ آه، متاح بعد ما أطبق المجموعة
+
+230
+00:17:05,400 --> 00:17:08,820
+من العناصر التالية. نبدأ مع الـ data reduction و الـ
+
+231
+00:17:08,820 --> 00:17:14,600
+feature selection. احنا متفقين أنه الـ data relevant
+
+232
+00:17:14,600 --> 00:17:18,480
+للـ task. سألنا نفسنا من البداية: هل الـ data هذه
+
+233
+00:17:18,480 --> 00:17:22,520
+relevant؟ مناسبة للـ task؟ آه، مناسبة... مناسبة
+
+234
+00:17:22,520 --> 00:17:27,380
+تماماً. الآن بدي أبدأ أسأل نفسي: هل الـ feature هاي
+
+235
+00:17:27,380 --> 00:17:32,700
+relevant ولا irrelevant للـ task؟ مثلاً، كنا متفقين
+
+236
+00:17:32,700 --> 00:17:36,940
+سابقا، أن الـ ID و الـ names مالهاش علاقة بأي شيء
+
+237
+00:17:36,940 --> 00:17:39,720
+فهذه الـ attributes لو كانت موجودة، شو بدي أسوي
+
+238
+00:17:39,720 --> 00:17:45,050
+فيها؟ بدي أشيلها. الآن، تخيل أن الـ data  بتاعتي
+
+239
+00:17:45,050 --> 00:17:48,310
+بتتكلم على تشخيص مرض معين: positive or negative.
+
+240
+00:17:48,310 --> 00:17:53,790
+تمام؟ و من ضمن الـ attribute، اسم الـ physical، اسم
+
+241
+00:17:53,790 --> 00:17:59,330
+الطبيب اللي قرر الحالة هاي أو عمل التشخيص هذا. هل
+
+242
+00:17:59,330 --> 00:18:03,790
+اسم الطبيب هذا، الاسم مش اسم المريض، اسم الطبيب الـ
+
+243
+00:18:03,790 --> 00:18:07,510
+expert اللي قال فعلياً أن الحالة هذه positive أو
+
+244
+00:18:07,510 --> 00:18:11,710
+قال عنها negative. هل اسم الطبيب بالوزن في الـ
+
+245
+00:18:11,710 --> 00:18:17,650
+mining؟ أكيد لا، irrelevant. بدي أشيله. واحد يقول: لما
+
+246
+00:18:17,650 --> 00:18:20,530
+أنت رجعتي يا دكتور لنفس المثال بالأسماء، كل الأسماء
+
+247
+00:18:20,530 --> 00:18:25,030
+و الـ IDs، كلها بدنا نشيلها. حتى أفق معك: تحصيل
+
+248
+00:18:25,030 --> 00:18:33,150
+الطالب في المدرسة اللي له علاقة براتب والده؟ آه،
+
+249
+00:18:33,150 --> 00:18:35,910
+شوف، في الأول معظمنا قال لا، بس بعدين شوية صرنا نقول
+
+250
+00:18:35,910 --> 00:18:41,990
+قد يكون okay. هذه القد إيش مقدارها؟ لا، ممكن نحسبها
+
+251
+00:18:42,740 --> 00:18:45,280
+بناء على الـ data set اللي عندي. واحد بيقول خمسين،
+
+252
+00:18:45,280 --> 00:18:49,000
+وهنا واحد بيقوله أقل. أنا ممكن أحسبها وأقول لك فعلياً
+
+253
+00:18:49,000 --> 00:18:53,140
+تأثير الـ attribute هذا بمقدار كذا على النتيجة. لسه
+
+254
+00:18:53,140 --> 00:18:57,460
+دي بلاش، لأن هذا احنا مختلفين في الموضوع هذا. هل
+
+255
+00:18:57,460 --> 00:19:06,600
+تحصيل الطالب له علاقة بعمر والده؟ هتقول لي طبعاً؟ وين
+
+256
+00:19:06,600 --> 00:19:10,620
+هو اللي بيقوله. أنا صراحة هشوف، بسأل، طبعاً لا، بس في
+
+257
+00:19:10,620 --> 00:19:17,340
+واحد قال: آه صحيح، بصراحة لا، آه، يمكن ننزل من العلامة
+
+258
+00:19:17,340 --> 00:19:17,680
+يعني
+
+259
+00:19:21,300 --> 00:19:26,040
+بس شوف، أنت مع كل واحدة صرت تقول: إيش؟ يمكن، يمكن
+
+260
+00:19:26,040 --> 00:19:30,400
+لأنه فعلياً الأقرب بالنسبة لك لا، مالوش علاقة
+
+261
+00:19:30,400 --> 00:19:33,720
+بسلوك والده في متابعته، بغض النظر عن عمره، كان شاب
+
+262
+00:19:33,720 --> 00:19:36,880
+صغير أو كهل، ولا لا. إذا طول ما هو حامل العصاية فوق
+
+263
+00:19:36,880 --> 00:19:42,800
+رأسه و بنجر على رأسه، بيدرس، بيدرس، بتحس إن في ناس
+
+264
+00:19:42,800 --> 00:19:44,560
+بيظلوا موجودين أكثر من الشباب. نعم.
+
+265
+00:19:48,990 --> 00:19:52,730
+صار... صار هذا له... له تأثير، بس أنا قاعد بتكلم
+
+266
+00:19:52,730 --> 00:19:56,390
+بأطرح معك إنه ممكن ألاقي attributes شكلها بيوحي
+
+267
+00:19:56,390 --> 00:20:02,030
+أنه ممكن يكون تمام؟ لكنه فعلياً مالوش علاقة. تمام.
+
+268
+00:20:02,030 --> 00:20:04,590
+دكتور، جهدك للتصك باسم اللي أنت جاي تتكلم عنه؟
+
+269
+00:20:04,590 --> 00:20:07,270
+معليش، قاعد بقول لك: الآن قاعد بتكلم، التصنيف بتاع
+
+270
+00:20:07,270 --> 00:20:11,530
+تحصيل الطالب في المدرسة وعمر والده. الآن، متوفر
+
+271
+00:20:11,530 --> 00:20:18,760
+attribute اسمه الـ father age. بتتوقع هيك... by sins
+
+272
+00:20:18,760 --> 00:20:22,360
+هل father age مؤثر؟ أنا بقول لك من واقع خبرتي؟ لا،
+
+273
+00:20:22,360 --> 00:20:26,880
+لا، ليش؟ لأنه كمان مرة، إلها علاقة بالـ attitude تبع
+
+274
+00:20:26,880 --> 00:20:31,680
+الأب. إذا هو متابع، هتظل متابع لآخر نفس، وإذا هو
+
+275
+00:20:31,680 --> 00:20:40,180
+مهم من البداية، هتظل نفس العنصر. الآن وبالتالي،
+
+276
+00:20:40,180 --> 00:20:42,900
+أنا عشان أطلع من الجدل اللي ما يمكن وما يمكنش وجدش
+
+277
+00:20:42,900 --> 00:20:47,190
+تأثيره، أنا فيه عندي بعض الـ formal methods، بعض الطرق
+
+278
+00:20:47,190 --> 00:20:50,610
+الرسمية، الـ Practical اللي ممكن أنا أستخدمها وأصل
+
+279
+00:20:50,610 --> 00:20:55,270
+لنتيجة. طيب، لما أنا بقلل عدد الـ attributes، جماعة
+
+280
+00:20:55,270 --> 00:21:00,510
+الخير، واحد، اثنين، ثلاثة، أربعة، كانوا عشرة attributes.
+
+281
+00:21:00,510 --> 00:21:04,650
+محمد، قد إيش عدد الـ attributes عندك في الـ data set؟ 87
+
+282
+00:21:04,650 --> 00:21:09,710
+attribute. قد إيش حجم الـ data set اللي عندك أنت؟ أيوة،
+
+283
+00:21:09,710 --> 00:21:19,260
+آه، آه، 13 attribute و أربعة عشر row؟ أربعة عشر
+
+284
+00:21:19,260 --> 00:21:24,720
+attributes. آه، و الـ rows؟ الآن، الـ attributes هذه
+
+285
+00:21:24,720 --> 00:21:27,800
+ستة وثمانين أو أربعة عشر. ممكن غيره يقول لي عشرة و
+
+286
+00:21:27,800 --> 00:21:32,740
+الناس يقول لي سبعة، و واحد يقول لي خمسة. المهم أحافظ...
+
+287
+00:21:32,740 --> 00:21:38,920
+لا... احنا حكينا مئة مرة، أجلش يبدأ خمسة آلاف row
+
+288
+00:21:38,920 --> 00:21:40,540
+بتعيده؟
+
+289
+00:21:44,740 --> 00:21:51,580
+لما أراجعها إن شاء الله، برد عليك. آه،
+
+290
+00:21:51,580 --> 00:21:59,640
+أنت بقى كتناسبها. آه، بقى، دوّارت
+
+291
+00:21:59,640 --> 00:22:05,700
+على الجليل مش ضروري يديك knowledge كويسة. نشوف، نشوف.
+
+292
+00:22:05,700 --> 00:22:12,600
+ماشي، ماشي. طيب خلينا نرجع، خلينا نرجع لمحاضرتنا. الهدف
+
+293
+00:22:12,600 --> 00:22:17,480
+من الـ Feature Selection، أن أحتفظ فقط بالـ Most
+
+294
+00:22:17,480 --> 00:22:22,120
+Relevant Attributes، بالـ Most Effective Attributes.
+
+295
+00:22:22,120 --> 00:22:28,900
+والباقي بدي أخلص منه. وهذا عشان يديني زيادة في كفاءة
+
+296
+00:22:28,900 --> 00:22:35,720
+الـ System بتاعتي. ولما أنا فعلياً أتكلم Feature
+
+297
+00:22:35,720 --> 00:22:39,080
+Selection أو data reduction، لما أنا زي ما قلت لك
+
+298
+00:22:39,080 --> 00:22:42,360
+بحدث attribute، يعني بحدث variable من المعادلة اللي
+
+299
+00:22:42,360 --> 00:22:45,620
+بدها تصير، وبالتالي أنا بقلل الـ computation اللي
+
+300
+00:22:45,620 --> 00:22:50,760
+بدها تصير عندي لاحقاً. عادة يا جماعة الخير لو قلت لك
+
+301
+00:22:50,760 --> 00:22:57,720
+أنا ما بعرف أي مجموعة هي اللي بتأثر، أي مجموعة من
+
+302
+00:22:57,720 --> 00:23:01,260
+الـ features هي صاحبة التأثير الأكبر، لكن بدي أجرب،
+
+303
+00:23:01,260 --> 00:23:05,500
+وهذا فعلياً هذا اللي بيصير: try and measure. هذا الـ
+
+304
+00:23:05,500 --> 00:23:08,800
+concept موجود جداً في الـ machine learning، و مطبق و
+
+305
+00:23:08,800 --> 00:23:15,680
+effective، بس مكلف. الآن، لو أنا أجيت وقلت لك عندي
+
+306
+00:23:15,680 --> 00:23:20,840
+three attributes، إيش
+
+307
+00:23:20,840 --> 00:23:23,980
+هي الـ data set أو إيش هي الـ subsets من الـ
+
+308
+00:23:23,980 --> 00:23:27,690
+attributes هذه اللي ممكن أجرب عليها؟ ما بعرف يعني إيش
+
+309
+00:23:27,690 --> 00:23:32,750
+تجرب عليها؟ يعني تطبق الـ mining task بتاعتك على الـ
+
+310
+00:23:32,750 --> 00:23:35,910
+attributes هي. ممكن واحد، الـ label و كمان variable،
+
+311
+00:23:35,910 --> 00:23:39,730
+one dependent أو one independent و one dependent
+
+312
+00:23:39,730 --> 00:23:42,570
+variable، هي الـ target بتاعتي. إلا لو كانت عندي three
+
+313
+00:23:42,570 --> 00:23:46,570
+classes، أي three attributes، عفواً. أي واحد، وأي
+
+314
+00:23:46,570 --> 00:23:52,370
+اثنين، وأي ثلاثة، بالإضافة للـ target، هي الـ data set
+
+315
+00:23:52,370 --> 00:23:57,710
+بتاعتي، مكونة من four attributes، وأنا بدي أجرب الآن
+
+316
+00:23:57,710 --> 00:24:03,850
+آخذ قرار: مين الأكثر أهمية فيهم؟ وبدي أجرب وأجيب
+
+317
+00:24:03,850 --> 00:24:08,290
+كل مرة، كيف كان الـ performance؟ لأن ممكن أنا أشغل
+
+318
+00:24:08,290 --> 00:24:12,150
+على الـ attribute الأول لحاله مع الـ target، و الـ
+
+319
+00:24:12,150 --> 00:24:15,390
+attribute الثاني مع الـ target، و الـ attribute
+
+320
+00:24:15,390 --> 00:24:20,330
+الثالث مع الـ target. بعدين الأول والثاني مع الـ
+
+321
+00:24:20,330 --> 00:24:26,830
+target، الأول والثالث مع الـ target، الثاني والثالث
+
+322
+00:24:26,830 --> 00:24:32,690
+مع الـ target، وكلهم مع الـ target. عادةً، عمال
+
+323
+00:24:32,690 --> 00:24:36,410
+بذكرنا هون، بقول لي: معناته إن أنت عندك عدد احتمالات
+
+324
+00:24:36,410 --> 00:24:42,330
+اثنين أس اثنين. إذا ترجع للرياضيات المنفصلة في الـ
+
+325
+00:24:42,330 --> 00:24:48,520
+subset، الـ power set. الـ power set بتحتوي على كل
+
+326
+00:24:48,520 --> 00:24:52,280
+المجموعات الجزئية من المجموعة A اللي هي عددهم 2
+
+327
+00:24:52,280 --> 00:24:55,620
+أس الـ cardinality للمجموعة A، باستثناء طبعاً، ما
+
+328
+00:24:55,620 --> 00:24:59,620
+راح منا منهم واحد. فاحنا مش قضية اثنين أس n، تمام؟
+
+329
+00:24:59,620 --> 00:25:07,480
+هذا العدد. إذا أنا بدي أجرب كويس على خمسة، على عشرة،
+
+330
+00:25:07,480 --> 00:25:12,600
+الآن أنا اثنين أس عشرة، نتكلم عن ألف وأربع وعشرين
+
+331
+00:25:12,600 --> 00:25:16,570
+محاولة عندي. بدي أغير منهم واحدة: ألف وثلاثة وعشر
+
+332
+00:25:16,570 --> 00:25:24,090
+محاولة. بس مع سبعة وثمانين، قضية... و
+
+333
+00:25:24,090 --> 00:25:27,650
+أنا هريحك في العلمات، إن شاء الله تعالى، ولا يهمك، مش
+
+334
+00:25:27,650 --> 00:25:32,850
+هخليك تتعب من حملها بالمرة، هشيل منهم قدر ما أقدر.
+
+335
+00:25:32,850 --> 00:25:38,510
+الآن، وبالتالي الـ feature selection اللي هتصير عندي
+
+336
+00:25:38,510 --> 00:25:45,560
+الآن، واحدة من اثنين: supervised و unsupervised. لو
+
+337
+00:25:45,560 --> 00:25:54,700
+أنا أجيت قلت لك: كـ test، شو يعني supervised؟ يعني
+
+338
+00:25:54,700 --> 00:25:59,940
+الـ human exist فيه supervision، فيه إشراف. وين
+
+339
+00:25:59,940 --> 00:26:04,920
+الإشراف بتاع الـ human؟ لا، مش في الـ data collection،
+
+340
+00:26:04,920 --> 00:26:10,480
+في الـ test، في الـ target، في تحديد الـ target. ممكن
+
+341
+00:26:10,480 --> 00:26:13,580
+الآن يكون الـ selection بتاعي للـ features بناء على
+
+342
+00:26:14,450 --> 00:26:17,590
+علاقة الـ Feature بالـ Target، وهدي بنسميها
+
+343
+00:26:17,590 --> 00:26:22,350
+Supervised. يعني لما أنا فعلياً بدي أقرر أتخلص من
+
+344
+00:26:22,350 --> 00:26:26,810
+Attribute أو أبقي، بدي أفحص علاقة الـ Attribute هذا
+
+345
+00:26:26,810 --> 00:26:32,650
+بالـ Target، وهدي بسميها Supervised، بسميها
+
+346
+00:26:32,650 --> 00:26:38,330
+Supervised. لما بأشتغل على أنه أنا بدي أقرر بين Two
+
+347
+00:26:38,330 --> 00:26:42,690
+Attributes جانب بعض، هل هما dependent أو redundant
+
+348
+00:26:42,690 --> 00:26:47,210
+attributes أو لا؟ هذي بسميها unsupervised. ما دخلتش
+
+349
+00:26:47,210 --> 00:26:54,170
+الـ target في حسبتي. الآن بشكل عام... بشكل عام الآن،
+
+350
+00:26:54,170 --> 00:26:57,510
+بدي أشيل الـ redundant attributes أو redundant
+
+351
+00:26:57,510 --> 00:27:02,130
+features. redundant عند الـ age، وعند الـ date of
+
+352
+00:27:02,130 --> 00:27:07,910
+birth، وعند الـ age category. شو رأيكم في الـ three
+
+353
+00:27:07,910 --> 00:27:12,690
+attributes هدول؟ كلهم زي بعض، بيحملوا نفس المعلومة
+
+354
+00:27:12,690 --> 00:27:19,990
+بس بصور مختلفة. تماماً مثل: يقول في عند الراتب، وعند
+
+355
+00:27:19,990 --> 00:27:25,630
+الراتب السنوي، أو صافي الراتب، وعند الراتب السنوي. بما
+
+356
+00:27:25,630 --> 00:27:28,610
+أن كلهم بيحملوا نفس المعلومة. هذه redundant attributes.
+
+357
+00:27:28,610 --> 00:27:33,690
+فأنت بدك تشيل اثنين من الثلاثة هدول، وتحتفظ بواحد
+
+358
+00:27:33,690 --> 00:27:36,890
+فقط، اللي بتناسب مع الـ task بتاعتك.
+
+359
+00:27:40,720 --> 00:27:44,200
+بدك ترجع للخلف سطرين وتعمل data cleaning
+
+360
+00:27:44,200 --> 00:27:48,660
+عشان تعالج الـ consistency. احنا خلصنا، أنا خلصت من
+
+361
+00:27:48,660 --> 00:27:52,300
+الـ missing، عملت لها handling، عبيتها، خلصت الـ noise
+
+362
+00:27:52,300 --> 00:27:56,840
+data، وحليت الـ inconsistency اللي موجودة. الآن
+
+363
+00:27:56,840 --> 00:28:00,720
+انتقلت لمرحلة الـ data selection. تمام يا مؤمن.
+
+364
+00:28:00,720 --> 00:28:03,560
+ففعلياً أنا يا شباب، أنا خلصت المرحلة اللي لها كل
+
+365
+00:28:03,560 --> 00:28:07,320
+علاقة بالـ preparation. الشيء الثاني زي ما قلنا، بدنا
+
+366
+00:28:07,320 --> 00:28:10,730
+نشيل الـ irrelevant attributes. أي attribute
+
+367
+00:28:10,730 --> 00:28:16,210
+irrelevant، تمام؟ irrelevant attribute بدي أخلص منه
+
+368
+00:28:16,210 --> 00:28:22,730
+في
+
+369
+00:28:22,730 --> 00:28:26,510
+شغل مهم جداً، لأول مرة هنقولها، إن أنا بدي أحذف الـ
+
+370
+00:28:26,510 --> 00:28:30,830
+attribute اللي مش فيها قيم مختلفة أو فيها تغيير
+
+371
+00:28:30,830 --> 00:28:38,630
+بسيط في الاختلاف. يعني كان في عندنا ملف طبي بيتكلم
+
+372
+00:28:38,630 --> 00:28:46,800
+عن النساء الحوامل. آه، أحسن، بدي أتنبأ بوزن المولود
+
+373
+00:28:46,800 --> 00:28:53,880
+لما ينولد، ولا جئت فيه attribute اسمه الـ gender. ليش
+
+374
+00:28:53,880 --> 00:28:59,320
+نشيل يا كريم؟ بالعجل، بالعجل، نشيل. ليش نشيل؟ بالعجل،
+
+375
+00:28:59,320 --> 00:29:04,880
+لأن كل الحوامل female، وبالتالي أنا ما فيش داعي لـ
+
+376
+00:29:04,880 --> 00:29:06,060
+attribute هذه يظل موجود.
+
+377
+00:29:08,960 --> 00:29:12,060
+لا، لا، بتكلم... بتكلم على الأم... عن الأم... جنس
+
+378
+00:29:12,060 --> 00:29:16,080
+الأم... بتكلم... أنا بدي أتنبأ بوزن المولود، أو بدي
+
+379
+00:29:16,080 --> 00:29:20,440
+أعمل regression لوزن المولود، تمام؟ الآن، وراجعت
+
+380
+00:29:20,440 --> 00:29:22,860
+البيانات... من بيانات الأم، موجود عندي الـ gender،
+
+381
+00:29:22,860 --> 00:29:28,160
+ما يلزمش... الآن، واحد يقول لي: هذا الـ attribute مهم؟
+
+382
+00:29:28,160 --> 00:29:31,800
+لا، مش مهم. ليش؟ لأن كل الـ attributes أو... عفواً...
+
+383
+00:29:31,800 --> 00:29:36,320
+كل الـ rows بتتشارك نفس الـ value، وبالتالي هذا
+
+384
+00:29:36,320 --> 00:29:40,880
+useless. تضحكوا، ماشي الحال، الله يهنيكم يا رب. زي
+
+385
+00:29:40,880 --> 00:29:46,120
+العمر في مثال المدرسة،
+
+386
+00:29:46,120 --> 00:29:50,360
+شكراً لك يا أحمد. الآن، العمر في مثال المدرسة،
+
+387
+00:29:50,360 --> 00:29:52,680
+الابتدائي، المرحلة الابتدائية، كلهم موجودين في نفس الـ
+
+388
+00:29:52,680 --> 00:29:56,600
+range. إلا إذا كان ما أنا بدي فعلياً، أنا معناته أشوف
+
+389
+00:29:56,600 --> 00:30:05,240
+تأثيره: العمر، أو فرق السنين، على تحصيله. عملية
+
+390
+00:30:05,240 --> 00:30:09,160
+الفحص أو المشاهدة أو شوف مين الـ attributes الأحسن، و
+
+391
+00:30:09,160 --> 00:30:15,900
+كذا مكلف أكثر. الحل الآن وبالتالي، موضوع إن أنا أجرب
+
+392
+00:30:15,900 --> 00:30:21,080
+الـ subset اللي موجود عندي زي
+
+445
+00:34:20,420 --> 00:34:25,500
+التنتين أنه بالـ forward ببدأ مع single attribute و
+
+446
+00:34:25,500 --> 00:34:28,180
+ببدأ أضيف الثاني والثالث والرابع وهكذا والـ
+
+447
+00:34:28,180 --> 00:34:32,540
+attribute اللي ما بأثرش في الـ result النهائي أو
+
+448
+00:34:32,540 --> 00:34:38,590
+تأثيره قليل بقى أشيله، بقى أشيله من اللي بعدين بينما
+
+449
+00:34:38,590 --> 00:34:43,470
+الـ Backward بقى أبدأ معاهم كلهم وببدأ أغيرهم
+
+450
+00:34:43,470 --> 00:34:46,730
+واحد وراء الثاني والـ Attribute اللي بقى أحس أنه
+
+451
+00:34:46,730 --> 00:34:49,770
+الـ Accuracy أو الـ performance تبع الـ
+
+452
+00:34:49,770 --> 00:34:53,250
+knowledge rule تبعها Down، صارت الـ Accuracy
+
+453
+00:34:53,250 --> 00:34:58,010
+نزلت لتحت بقى أشيله وأشوف اللي بعده وهكذا
+
+454
+00:34:58,010 --> 00:35:02,430
+بعض الناس بتروح بتطبق Machine Learning Algorithm
+
+455
+00:35:02,430 --> 00:35:09,230
+على الـ data set، فبتروح بتبني Decision Tree للـ data
+
+456
+00:35:09,230 --> 00:35:13,530
+set مكونة من six attributes عشان توصلنا للـ class
+
+457
+00:35:13,530 --> 00:35:18,270
+الـ Decision Tree لما بنوها لقوا إن الـ rules تبع الـ
+
+458
+00:35:18,270 --> 00:35:22,850
+Decision Tree فقط معتمدة على three attributes: a1 و
+
+459
+00:35:22,850 --> 00:35:33,290
+a4 و a6. هذا يعني أن a2 و a3 و a5 are useless. فراح
+
+460
+00:35:33,290 --> 00:35:36,130
+هدفهم يقول لك خلاص أنا بقدر أبني النظام تبعي على
+
+461
+00:35:36,130 --> 00:35:42,970
+الـ data set اللي موجودة عندها الآن
+
+462
+00:35:42,970 --> 00:35:48,750
+الـ data set هيها، اه بتتكون من six attributes، فلما
+
+463
+00:35:48,750 --> 00:35:50,810
+احنا أخدنا الـ six attributes هدول وبنينا عليهم
+
+464
+00:35:50,810 --> 00:35:54,170
+Decision Tree، الـ Decision Tree  عاليه واضحة جداً
+
+465
+00:35:54,170 --> 00:35:58,330
+لما رسمتها بتتكون من ايش؟ فقط من الـ three attributes
+
+466
+00:35:58,330 --> 00:36:07,350
+A1 و A4 و A6، ولسه بيقول لي A4 هو الأكثر أهمية، وراء
+
+467
+00:36:07,350 --> 00:36:13,050
+بيجي A1 و A6 بنفس المنزلة في ناحية الأهمية، يعني أن
+
+468
+00:36:13,050 --> 00:36:17,950
+2 و 3 و 5 مالهمش معنى، مالهمش لازمة، فإيش بروح أنا؟
+
+469
+00:36:17,950 --> 00:36:21,250
+بحذفهم وببني نظامي من جديد فقط على الـ three
+
+470
+00:36:21,250 --> 00:36:25,870
+attributes الموجودة، اه اه اه، هنشوفه مع بعض إن شاء
+
+471
+00:36:25,870 --> 00:36:30,050
+الله لاحقاً، طيب الآن
+
+472
+00:36:32,550 --> 00:36:37,790
+بما إنه مبدأ إنه والله أنا أطبق وأجرب على كلهم مزعج،
+
+473
+00:36:37,790 --> 00:36:40,650
+خصوصاً في ناس حيصير في عندها ألف وأربع مئة محاولة،
+
+474
+00:36:40,650 --> 00:36:44,170
+و ناس الله يعينهم، مش عارف قد ايش، اثنين مليون تقريباً،
+
+475
+00:36:44,170 --> 00:36:49,150
+مصبوط؟ فالكلام حيصير in a sense، فهو مش منطقي، الآن
+
+476
+00:36:49,150 --> 00:36:54,550
+في بعض الـ correlation algorithms بتفحص العلاقة ما
+
+477
+00:36:54,550 --> 00:36:58,470
+بين الـ attributes سواء كانت العلاقة بين الـ
+
+478
+00:36:58,470 --> 00:37:01,830
+attribute والـ label عشان يقول لي والله قد ايش هذا
+
+479
+00:37:01,830 --> 00:37:06,620
+effect أو قد ايش correlated أو بين الـ attributes
+
+480
+00:37:06,620 --> 00:37:11,960
+نفسها عشان يتكلم من ناحية redundancy، الآن إبعاد
+
+481
+00:37:11,960 --> 00:37:15,700
+الخير في موضوع الـ correlation، عادة كل ما كان الـ
+
+482
+00:37:15,700 --> 00:37:19,340
+value ناتج التحصيل تبع الـ correlation analysis
+
+483
+00:37:19,340 --> 00:37:23,760
+عالية أو قريبة من الواحد، إن هدول الـ two attributes
+
+484
+00:37:23,760 --> 00:37:28,240
+هدول mostly dependent، بيعتمدوا على بعض، وممكن
+
+485
+00:37:28,240 --> 00:37:32,590
+يكونوا completely duplicated، طيب في الحالة هذه بدي
+
+486
+00:37:32,590 --> 00:37:37,490
+أخلص من واحد منهم، كل ما كانت القيمة قريبة للصفر
+
+487
+00:37:37,490 --> 00:37:41,950
+بقول إن الـ two attributes هدول independent، ما فيش
+
+488
+00:37:41,950 --> 00:37:45,910
+بينهم علاقة، وبالتالي أنا مضطر أبقي اثنين، يعني
+
+489
+00:37:45,910 --> 00:37:49,550
+فعلياً أنا المطلوب مني الآن واحدة، هنشوفه كمان شوية
+
+490
+00:37:49,550 --> 00:37:53,790
+لأنه في أول واجب جاينى الآن، هنشوفه فعلياً مطلوب مني
+
+491
+00:37:53,790 --> 00:37:57,250
+من مجموعة الـ features هدول أعمل دراسة بالـ
+
+492
+00:37:57,250 --> 00:38:01,770
+coefficient عشان أُحدد قياس الـ dependency اللي
+
+493
+00:38:01,770 --> 00:38:05,190
+موجودة من الـ ... من الـ attributes، أو عفواً من الـ
+
+494
+00:38:05,190 --> 00:38:09,010
+algorithm المستخدم عند الـ person وهي بيستخدمها لما
+
+495
+00:38:09,010 --> 00:38:12,450
+يكون في عندي numerical attributes وفي عندي الـ chi-
+
+496
+00:38:12,450 --> 00:38:15,110
+square لما تكون الـ attributes عبارة عن nominal
+
+497
+00:38:15,110 --> 00:38:19,350
+attributes، وفي عندي الـ spearman والـ kendall tau
+
+498
+00:38:19,350 --> 00:38:21,790
+برضه مجموعة ... في مجموعة كتير من الـ algorithms
+
+499
+00:38:21,790 --> 00:38:26,410
+ممكن تطبق، خلينا احنا نتكلم على الـ pearson والـ chi-
+
+500
+00:38:26,410 --> 00:38:30,830
+square، كونوا واحدة للـ numerical، واحدة للـ nominal
+
+501
+00:38:30,830 --> 00:38:34,370
+في
+
+502
+00:38:34,370 --> 00:38:36,810
+الـ pearson coefficient أنا فيه عندي two attributes
+
+503
+00:38:36,810 --> 00:38:46,290
+الآن a1 و a2، a1
+
+504
+00:38:46,290 --> 00:38:51,470
+و a2 numeric
+
+505
+00:38:51,470 --> 00:38:55,830
+attributes، لها description، مديني إجابته، إيش
+
+506
+00:38:55,830 --> 00:39:00,070
+العلاقة اللي بينهم، ولا الأسماء جادرة من خلالها أحدد
+
+507
+00:39:00,070 --> 00:39:03,930
+إيش اللي موجود، أو شو علاقة الـ two attributes مع
+
+508
+00:39:03,930 --> 00:39:08,410
+بعضهم، والاثنين بما إنه الاثنين الـ numeric فبقدر أطبق
+
+509
+00:39:08,410 --> 00:39:12,770
+بينهم الـ Pearson correlation، إيش الـ Pearson
+
+510
+00:39:12,770 --> 00:39:17,830
+بقول؟ بقول كالتالي، القانون تبعنا هو عبارة عن مجموع
+
+511
+00:39:17,830 --> 00:39:23,250
+حاصل ضرب الفروقات، كل value في الـ attribute ناقص
+
+512
+00:39:23,250 --> 00:39:27,070
+المتوسط الحسابي تبعته، يعني
+
+513
+00:39:28,590 --> 00:39:33,650
+لو كان هذا واحد ... اثنين ... ثلاثة ... وهنا مثلاً
+
+514
+00:39:33,650 --> 00:39:42,270
+سبعة ... خمسة ... عشرة، أو  عشرة، المتوسط الحسابي
+
+515
+00:39:42,270 --> 00:39:46,830
+الـ summation، يا معظم الخير الـ μ للـ A1، للـ A1
+
+516
+00:39:46,830 --> 00:39:54,270
+واحد زائد ستة على ثلاثة ... ثلاثة ... اثنين، والمجموع
+
+517
+00:39:55,400 --> 00:40:00,560
+المتوسط الحسابي 7.7257
+
+518
+00:40:00,560 --> 00:40:15,380
+.512 و 10.22، 22 على 3، 7.380، 33 من 100، مصبوط؟ الآن
+
+519
+00:40:15,380 --> 00:40:20,640
+عشان أنا أحسب طيب الانحراف المعياري، أو الـ variance
+
+520
+00:40:20,640 --> 00:40:22,500
+إيش قانون الـ variance؟
+
+521
+00:40:26,440 --> 00:40:32,460
+الـ Standard Deviation، سيجما
+
+522
+00:40:32,460 --> 00:40:35,460
+... أيوة، الجذر يساوي الجذر التربيعي لـ summation
+
+523
+00:40:35,460 --> 00:40:42,640
+الـ xi ناقص μ تربيع على عددهم، تحت الجذر، برجع بأكد
+
+524
+00:40:42,640 --> 00:40:45,980
+عليك القوانين هذه كلها للحفظ يا شباب، وهذا زيهم
+
+525
+00:40:45,980 --> 00:40:51,920
+أكيد، وهذا ... هذا الانحراف المعياري، المعادلة مكتوبة بشكلين
+
+526
+00:40:51,920 --> 00:40:59,090
+هي ... فأنت احفظ هذه أو هذه، الأسهل لك، لأ مش كتير
+
+527
+00:40:59,090 --> 00:41:05,350
+يا مؤمن، مش كتير يا مؤمن، الآن، فهذه المعلومات بدي
+
+528
+00:41:05,350 --> 00:41:10,230
+أحسبها على الـ attributes اللي موجودة عندي، وبالتالي
+
+529
+00:41:10,230 --> 00:41:15,770
+بصير وبقوله واحد ناقص اثنين مضروبة في سبعة ناقص
+
+530
+00:41:15,770 --> 00:41:23,350
+سبعة فاصلة ثلاثة، زائد اثنين ناقص اثنين مضروبة في
+
+531
+00:41:23,350 --> 00:41:30,460
+خمسة ناقص سبعة فاصلة ثلاثة، زائد ثلاثة ناقص اثنين مضروبة
+
+532
+00:41:30,460 --> 00:41:35,020
+في عشرة ناقص سبعة فاصلة ثلاثة، هذا المجموع على
+
+533
+00:41:35,020 --> 00:41:40,060
+عددهم، ثلاثة، في الانحراف المعياري، الـ variance للـ
+
+534
+00:41:40,060 --> 00:41:43,480
+attribute الأول، والـ variance للـ attribute الثاني
+
+535
+00:41:43,480 --> 00:41:50,680
+تمام، الآن الـ
+
+536
+00:41:50,680 --> 00:41:57,220
+value اللي هتطلعه، بيطلع من سالب واحد، أكبر أو يساوي
+
+537
+00:41:57,220 --> 00:42:05,200
+سالب واحد، وأقل أو يساوي موجب واحد، صفر يعني
+
+538
+00:42:05,200 --> 00:42:09,040
+independent attributes، ما فيش بينهم علاقة، إشارة
+
+539
+00:42:09,040 --> 00:42:13,740
+سالبة، يعني العلاقة عكسية، في علاقة، بس عكسية، الإشارة
+
+540
+00:42:13,740 --> 00:42:17,960
+موجبة، بقى في علاقة، لكن علاقة طردية بين الأرقام اللي
+
+541
+00:42:17,960 --> 00:42:18,700
+موجودة
+
+542
+00:42:23,010 --> 00:42:26,390
+وين؟ للاتنين، علاقة الاثنين مع بعض، وإذا كان الاثنين
+
+543
+00:42:26,390 --> 00:42:29,890
+بيختلفوا في الـ ... في إيش؟ في الـ rows، بيختلفوا ...
+
+544
+00:42:29,890 --> 00:42:32,810
+two attributes بيختلفوا ... بيختلفوا بعدد الـ rows؟
+
+545
+00:42:32,810 --> 00:42:35,370
+كيف هذا الكلام بده يصير؟ مش الاثنين موجودين في نفس
+
+546
+00:42:35,370 --> 00:42:40,430
+الـ data set؟ طيب، وخلصت أنا مرحلة الـ data
+
+547
+00:42:40,430 --> 00:42:46,750
+preparation،  عبيت المسألة الآن، positive correlation
+
+548
+00:42:46,750 --> 00:42:50,370
+يعني
+
+549
+00:42:50,370 --> 00:42:55,690
+الاثنين الـ value أكبر من صفر، يعني الاثنين dependent
+
+550
+00:42:55,690 --> 00:42:59,610
+أو في علاقة ... في علاقة قوية ما بينهم، وبالتالي
+
+551
+00:42:59,610 --> 00:43:05,970
+بقدر أستغني عن واحد فيهم، وكذلك لو كانت القيمة
+
+552
+00:43:05,970 --> 00:43:10,450
+قريبة للسالب واحد، في علاقة، لكن علاقة عكسية
+
+553
+00:43:10,450 --> 00:43:15,050
+وبالتالي بقدر أستغني عن واحد منهم، بإيش أنا ...
+
+554
+00:43:15,050 --> 00:43:17,690
+الصفر هو الـ perfect، يعني الـ two attributes هدول
+
+555
+00:43:17,690 --> 00:43:21,710
+لازم يظلوا، بس مش دائماً  حدّيني صفر ولا حدّيني واحد
+
+556
+00:43:21,710 --> 00:43:26,010
+ولا حدّيني سالب واحد، فحدّيني قيم في الـ range هذا
+
+557
+00:43:26,010 --> 00:43:32,850
+قيم حقيقية، يعني سالب خمسة من عشرة في
+
+558
+00:43:32,850 --> 00:43:39,250
+علاقة عكسية في خمسين في المئة، فأنت بتاخد قرار بناء
+
+559
+00:43:39,250 --> 00:43:43,770
+على إيش؟ بدي أقيّمها، مثلاً بتقول كل الـ relation أو كل
+
+560
+00:43:43,770 --> 00:43:49,860
+coefficient relation اللي بتكون فوق الـ 70% هي اللي
+
+561
+00:43:49,860 --> 00:43:54,420
+بدي أحذفها، بدون ذلك بدي أحتفظ فيها، فهذا بيظل عندك
+
+562
+00:43:54,420 --> 00:44:00,940
+قرار أنت بدك تطبقه، بس بتأثر في الجودة اللي هي ...
+
+563
+00:44:00,940 --> 00:44:05,640
+إذا اخترت 50 أو 70 أو ... أكيد أنت شوف إن الأصل
+
+564
+00:44:05,640 --> 00:44:10,560
+أنا بدي أخلص من الـ dependent attribute، الـ full
+
+565
+00:44:10,560 --> 00:44:13,880
+dependent اللي بينهم، هي عبارة عن الـ redundant
+
+566
+00:44:13,880 --> 00:44:18,660
+data، لأنه مسموح لي أعمل Transformation، مصبوط؟ يعني
+
+567
+00:44:18,660 --> 00:44:21,840
+الأصل إنه لما يكون Attribute A و Attribute B لما
+
+568
+00:44:21,840 --> 00:44:25,280
+يكون في بينهم Linear Equation، بقدر أرجّح الـ A للـ
+
+569
+00:44:25,280 --> 00:44:30,160
+B أو أودي الـ A للـ B، مصبوط؟ والعكس صحيح، الآن
+
+570
+00:44:30,160 --> 00:44:34,440
+واحد من الاثنين دول لازم ينشال، بس هل كل الـ data
+
+571
+00:44:34,440 --> 00:44:37,660
+اللي عندي هذه بتمثل الـ relation هذه؟ إذا كل الـ
+
+572
+00:44:37,660 --> 00:44:40,780
+data بتمثل الـ relation هذه، أنا بقول لك لازم تشيله،
+
+573
+00:44:40,780 --> 00:44:46,960
+استخدامه useless، لكن والله الارتباط 80%، في إما آخذ
+
+574
+00:44:46,960 --> 00:44:50,160
+قرار، إما أضحي، ما بدي الـ knowledge اللي بتيجي من
+
+575
+00:44:50,160 --> 00:44:53,540
+وراء الـ 80% هذه، لأن الـ correlation عالية، أو فعلياً
+
+576
+00:44:53,540 --> 00:44:56,100
+بدي أبقي وأتحمل التابعات عشان الـ knowledge
+
+577
+00:44:56,100 --> 00:45:02,900
+تأثيرها، الله أعلم، وقد يكون هذا الجدول في three
+
+578
+00:45:02,900 --> 00:45:17,200
+attributes: 1، 3، 4، 5، 6، 4، 6، 6، 8، 9، C، 5، 5، 10، 1، 8، هدول
+
+579
+00:45:17,200 --> 00:45:24,640
+two attributes،  بيساوي a زائد ثلاثة، linear
+
+580
+00:45:24,640 --> 00:45:29,800
+transformation عملت، ومش بس هيك، روحت عملت، غيرت
+
+581
+00:45:29,800 --> 00:45:34,340
+واحد وهذا
+
+582
+00:45:34,340 --> 00:45:41,660
+الـ attribute عملت له generate randomly من واحد لعشرة، حسبت
+
+583
+00:45:41,660 --> 00:45:46,050
+المتوسط الحسابي لكل واحد فيهم، حسبت الانحراف
+
+584
+00:45:46,050 --> 00:45:49,310
+المعياري لكل واحد فيهم، من هنا على المعادلة اللي
+
+585
+00:45:49,310 --> 00:45:54,850
+شفناها قبل شوية، ضل أطبق main في المعادلة السابقة
+
+586
+00:45:54,850 --> 00:46:02,370
+أو روحت حسبت المعادلة اللي عندي هان، a في b، اه بقى
+
+587
+00:46:02,370 --> 00:46:08,930
+إنك تحفظها، أنا قاعد بقول لك حفظها سهل جداً، واحد
+
+588
+00:46:08,930 --> 00:46:13,830
+ناقص المتوسط الحسابي زائد
+
+589
+00:46:15,210 --> 00:46:20,330
+مضروبة في، مضروبة في أربعة ناقص المتوسط الحسابي
+
+590
+00:46:20,330 --> 00:46:23,550
+ستة
+
+591
+00:46:23,550 --> 00:46:28,670
+فاصلة ستة، زائد، وبدك تكررها مع كل الـ values اللي موجودة
+
+592
+00:46:28,670 --> 00:46:32,510
+عندك، البرمجة طبعاً بتريحني في موضوع الـ function زي
+
+593
+00:46:32,510 --> 00:46:38,950
+هيك ولا لأ؟ لكن لاحظ أنت الفرق، أو المتوسط الحسابي
+
+594
+00:46:38,950 --> 00:46:42,310
+قد ايش بيفرق، لكن عند الـ variance
+
+595
+00:46:45,820 --> 00:46:50,120
+تقريباً متساوي، والفرق اللي صار إنه لو ضلت هذه
+
+596
+00:46:50,120 --> 00:46:57,000
+سبعة كانت نفسها، وهذه إشارة ممكن تديني لو أنا بدي
+
+597
+00:46:57,000 --> 00:47:00,360
+أعمل برنامج من بدري، أقول الـ attribute اللي بتديني
+
+598
+00:47:00,360 --> 00:47:06,580
+نفس الـ variance، بديش إياها، بس بظل في عندي حالة إن
+
+599
+00:47:06,580 --> 00:47:09,420
+بعض الأحيان الـ values، اختلاف الـ values فعلاً جاي
+
+600
+00:47:09,420 --> 00:47:13,650
+random، مش جاي ضمن الـ linear equation، فمش دائماً الـ
+
+601
+00:47:13,650 --> 00:47:17,490
+variance لوحده كافي إن أنا أحكم على الـ dependency
+
+602
+00:47:17,490 --> 00:47:21,710
+بين الـ two attributes، بالمجمل روحنا حسبنا الـ
+
+603
+00:47:21,710 --> 00:47:24,710
+Pearson correlation coefficient، أو coefficient
+
+604
+00:47:24,710 --> 00:47:33,510
+correlation بين a و b كان فاصلة 779، يعني 78 من 100
+
+605
+00:47:33,510 --> 00:47:41,730
+والـ dependency تبع الـ a والـ c فاصلة 085، شو
+
+606
+00:47:41,730 --> 00:47:42,150
+يعني؟
+
+607
+00:47:45,000 --> 00:47:52,200
+يعني أنا الآن، إني الخيار أشيل واحد a أو b، والـ c
+
+608
+00:47:52,200 --> 00:47:56,480
+لازم يظل، ليش
+
+609
+00:47:56,480 --> 00:48:01,620
+الـ c لازم يظل؟ قريبة من الصفر القيمة، مصبوط؟
+
+610
+00:48:01,620 --> 00:48:05,220
+قريبة من الصفر، كل ما كانت القيمة قريبة للصفر، فهذا
+
+611
+00:48:05,220 --> 00:48:08,800
+الـ attribute يُعد independent، مستقل، مالوش علاقة
+
+612
+00:48:08,800 --> 00:48:11,800
+بالـ attribute اللي في جنبه، وكل ما كبرت الـ value
+
+613
+00:48:11,800 --> 00:48:15,640
+باتجاه الواحد، معنى فيهُ  dependence عالية ما بين الـ
+
+614
+00:48:15,640 --> 00:48:20,420
+two attributes، وبالتالي لازم أخلص بواحد منهم، تمام
+
+615
+00:48:20,420 --> 00:48:28,940
+يا شباب؟ هذا الـ Python code بسيط عملته الصبح مع
+
+616
+00:48:28,940 --> 00:48:
+
+667
+00:52:32,410 --> 00:52:35,130
+أو قصص علمية أو حقيقية سمّها زي ما بدّك
+
+668
+00:52:37,850 --> 00:52:43,990
+الـ data set مكوّنة من 1500 row تمام؟ يعني في عندي
+
+669
+00:52:43,990 --> 00:52:50,550
+two attributes في الـ data set الـ gender preferred
+
+670
+00:52:50,550 --> 00:52:56,830
+reading male
+
+671
+00:52:56,830 --> 00:53:08,500
+fiction male nonfiction female fiction female nonfiction
+
+672
+00:53:08,500 --> 00:53:14,720
+وهكذا هذه
+
+673
+00:53:14,720 --> 00:53:19,280
+الـ variables لاحظوا أن الـ data اللي عندي في كل الـ
+
+674
+00:53:19,280 --> 00:53:25,300
+attributes فقط قيمتين عشان هيك الجدول اللي طلع عندي
+
+675
+00:53:25,300 --> 00:53:30,060
+اثنين في اثنين الجدول اللي طلع عندي هنا اثنين في
+
+676
+00:53:30,060 --> 00:53:30,400
+اثنين
+
+677
+00:53:34,140 --> 00:53:39,700
+في الـ preferred reading لأ في أكثر بقول لك أدب.. أدب
+
+678
+00:53:39,700 --> 00:53:44,220
+.. آه فيش.. فيش هنا فيش هنا okay بس هذا كمثال بدي
+
+679
+00:53:44,220 --> 00:53:47,240
+أجيب لك هنا في الـ preferred reading راح يقول لي
+
+680
+00:53:47,240 --> 00:53:52,320
+والله أنا بدي الأدب literature في politics في
+
+681
+00:53:52,320 --> 00:53:57,860
+economics في sport هاي صارت أربعة fantasy fantasy
+
+682
+00:53:57,860 --> 00:54:04,390
+هاي خمسة فانت ممكن تعد قد ما بدك في الآخر جدع
+
+683
+00:54:04,390 --> 00:54:09,230
+هتصير حجم هذا على جد الـ data اللي عندك يعني بين
+
+684
+00:54:09,230 --> 00:54:14,070
+جسين أربعة values لأن فعلياً two two two values في
+
+685
+00:54:14,070 --> 00:54:15,890
+الـ attribute الأول و two values في الـ attribute
+
+686
+00:54:15,890 --> 00:54:18,790
+الثاني لكن في الحالة اللي أنا جاي أتكلم أنه
+
+687
+00:54:18,790 --> 00:54:24,090
+القراءة بتاعتي السياسة و اقتصاد و أدب و علوم و.. و
+
+688
+00:54:24,090 --> 00:54:30,730
+..و فن 102 في 5 هتزيد أكيد الآن
+
+689
+00:54:32,090 --> 00:54:35,510
+الـ values الـ 250 سيبك من اللي في الأحمر هذه بس
+
+690
+00:54:35,510 --> 00:54:37,630
+أنا عشان احنا قاعدين نتعلم نقول لك أن هنا فيه
+
+691
+00:54:37,630 --> 00:54:40,650
+values بده أحسبه الآن الـ values اللي باللون الأسود
+
+692
+00:54:40,650 --> 00:54:45,690
+هذه هي عبارة عن computation للي موجود يعني بين
+
+693
+00:54:45,690 --> 00:54:48,250
+جثيم هين بيقول لي في الـ data set أو في الـ two
+
+694
+00:54:48,250 --> 00:54:51,790
+attributes 250 واحد من الـ male بيحبوا يقرأوا الـ
+
+695
+00:54:51,790 --> 00:54:59,400
+fiction stories 200 من الـ female بيقرأوا fiction لو
+
+696
+00:54:59,400 --> 00:55:02,280
+أنا قرأت الصفوف اللي هي الـ value summation اللي
+
+697
+00:55:02,280 --> 00:55:06,200
+موجود عندي 450 هي عبارة عن عدد الناس اللي بتقرأ
+
+698
+00:55:06,200 --> 00:55:10,120
+fiction في 1500 تمام؟
+
+699
+00:55:10,120 --> 00:55:17,360
+العمود 300 male 1200 female تمام؟ واضحة الـ values
+
+700
+00:55:17,360 --> 00:55:20,700
+اللي بلون الأسود؟ هذه اللي احنا بنسميها سميناها قبل
+
+701
+00:55:20,700 --> 00:55:26,940
+شوية هي الـ actual أو الـ observation O الـ actual
+
+702
+00:55:26,940 --> 00:55:27,520
+values
+
+703
+00:55:30,330 --> 00:55:35,630
+الـ actual count الآن الـ expected اللي هي باللون
+
+704
+00:55:35,630 --> 00:55:38,650
+الأحمر هذه لازم تكون عندك عشان تظبط عملية الـ
+
+705
+00:55:38,650 --> 00:55:43,970
+coordination فكرتها كالتالي يا جماعة الخير الآن في
+
+706
+00:55:43,970 --> 00:55:49,070
+الصف والعمود اللي أنا بدي اشتغل عليه بدي الـ
+
+707
+00:55:49,070 --> 00:55:55,420
+expected اللي هنا expect لمين؟ عدد الرجال أو الـ
+
+708
+00:55:55,420 --> 00:55:59,640
+male اللي بيقرأ fiction قيمة المتوقعة بناء على الـ
+
+709
+00:55:59,640 --> 00:56:06,500
+1500 اللي موجودين الـ expected value هذه تساوي في
+
+710
+00:56:06,500 --> 00:56:12,160
+المقام 1500 الـ total number وفوق مضروبة بقيمتين
+
+711
+00:56:12,160 --> 00:56:15,280
+عدد
+
+712
+00:56:15,280 --> 00:56:19,080
+الرجال في
+
+713
+00:56:19,080 --> 00:56:28,670
+عدد الـ fiction تمام؟ على 1500 250 عفواً 300 العدد
+
+714
+00:56:28,670 --> 00:56:42,090
+الرجال ضرب 450 بالـ fiction على 1500 ولاحظ
+
+715
+00:56:42,090 --> 00:56:45,330
+هو هاني حط لك في القانون حط لك الـ I والـ J عشان
+
+716
+00:56:45,330 --> 00:56:50,700
+يُسهّل عليك الصف والعمود اللي بتشتغل معه لكن كمان
+
+717
+00:56:50,700 --> 00:56:54,980
+مرة أنت افهمها كالتالي في أي attribute أو في أي
+
+718
+00:56:54,980 --> 00:57:00,400
+cell.. في أي cell عشان أحسب الـ expected value هي
+
+719
+00:57:00,400 --> 00:57:06,080
+عبارة عن حاصل ضرب المجموع بتاع الصف في مجموع العمود
+
+720
+00:57:06,080 --> 00:57:12,360
+على العدد الكل 1500 يعني الـ expected بتاع هنا
+
+721
+00:57:12,360 --> 00:57:20,310
+هتكون عبارة عن 1200 في 1050 على 1500 الـ Expected
+
+722
+00:57:20,310 --> 00:57:26,610
+اللي هنا 300 في 1050 على 1500 وهيك بتصير عندك أسهل
+
+723
+00:57:26,610 --> 00:57:33,810
+أنك تتذكر الـ Expected Value جدع قيمته يا مؤمن؟
+
+724
+00:57:33,810 --> 00:57:41,770
+15؟ آه بدك آلة حاسبة هذه
+
+725
+00:57:41,770 --> 00:57:43,670
+آلة حاسبة 90 على كل
+
+726
+00:57:48,570 --> 00:57:59,090
+300 ضرب 450 تقسيم 1500 300 ضرب 450 على 1500 تسعين
+
+727
+00:57:59,090 --> 00:58:03,450
+تسعين تسعين تسعين تسعين تسعين تسعين تسعين تسعين
+
+728
+00:58:03,450 --> 00:58:14,470
+تسعين تسعين تسعين تسعين تسعين تسعين تسعين
+
+729
+00:58:14,470 --> 00:58:15,930
+تسعين
+
+730
+00:58:18,440 --> 00:58:24,260
+اللي بعدها ثلاثمئة في ألف وخمسين ثلاثمئة ضرب ألف
+
+731
+00:58:24,260 --> 00:58:34,720
+وخمسين تقسيم ألف وخمسمائة اللي
+
+732
+00:58:34,720 --> 00:58:37,980
+هتستفيد من الرقم أن هو الرقم هذا بيَلْزَمُك في
+
+733
+00:58:37,980 --> 00:58:44,980
+المعادلة عشان تجيب قيمة الـ correlation expected
+
+734
+00:58:44,980 --> 00:58:47,940
+هاي الأرقام اللي موجودة عندنا
+
+735
+00:58:50,970 --> 00:58:58,290
+إحصاء شغل إحصاء أكيد بدي أجيب لك إياه ونلزّمك فيه
+
+736
+00:58:58,290 --> 00:59:01,110
+الاتباع الرياضي بتاعه احنا عاملين بيقول لك احفظ
+
+737
+00:59:01,110 --> 00:59:06,290
+القانون أيوة
+
+738
+00:59:06,290 --> 00:59:10,190
+جلبك مادة إيش إحصاء احنا قلنا من الأول
+
+739
+00:59:10,190 --> 00:59:14,210
+multidisciplinary مهمّين بدك تعرف إحصاء وبدك تعرف
+
+740
+00:59:14,210 --> 00:59:17,790
+database وبدك تعرف برمجة وبدك تعرف machine
+
+741
+00:59:17,790 --> 00:59:21,690
+learning وبدك تعرف knowledge presentation وبدك تعرف
+
+742
+00:59:21,690 --> 00:59:28,130
+ترسم كل حاجة نعم الـ course مكسب للي بدوا يشتغلوا
+
+743
+00:59:28,130 --> 00:59:32,670
+وللي ما بدواش طيب
+
+744
+00:59:32,670 --> 00:59:37,870
+الآن عبّينا الجدول هاي عبّينا الجدول هذا جماعة
+
+745
+00:59:37,870 --> 00:59:40,830
+الخير في الامتحان إذا أنا بدي أسألك في الموضوع هذا
+
+746
+00:59:40,830 --> 00:59:47,590
+لازم أزوّدك بالـ data أما هزوّدك بالـ data as two rows
+
+747
+00:59:47,590 --> 00:59:54,610
+جدول مكوّن من two rows أو هديك الجدول بدون الـ
+
+748
+00:59:54,610 --> 00:59:58,410
+expected الآن
+
+749
+00:59:58,410 --> 01:00:03,810
+حسبت للـ chi-square بناء على المعادلة الـ actual
+
+750
+01:00:03,810 --> 01:00:07,850
+ناقص الـ expected تربيع على الـ expected على كل
+
+751
+01:00:07,850 --> 01:00:11,550
+الخلايا الأربع اللي موجودة في الجدول المحصلة كانت
+
+752
+01:00:11,550 --> 01:00:13,730
+خمسمائة وسبعة
+
+753
+01:00:16,280 --> 01:00:20,860
+بما أن عدد الأعمدة اللي عندي هنا والصفوف اثنين
+
+754
+01:00:20,860 --> 01:00:25,000
+اثنين ناقص واحد وناقص واحد معناته أنا بتكلم one
+
+755
+01:00:25,000 --> 01:00:29,820
+degree of freedom الـ
+
+756
+01:00:29,820 --> 01:00:33,440
+hypothesis بتاعتي one degree of freedom هتكون
+
+757
+01:00:33,440 --> 01:00:37,900
+المفروض عندي هنا عشرة بناء على الـ values اللي
+
+758
+01:00:37,900 --> 01:00:44,400
+موجودة لو أنا جيت للجدول هذا و
+
+759
+01:00:44,400 --> 01:00:51,980
+أين القيمة بتاعتنا؟ خمسمائة وجدع طلعت احنا
+
+760
+01:00:51,980 --> 01:00:54,460
+ليه بندور هيك one degree of freedom المفروض في
+
+761
+01:00:54,460 --> 01:00:59,160
+الصف الأول الآن
+
+762
+01:00:59,160 --> 01:01:02,820
+بناء على القيمة اللي موجودة عندك بناء على القيمة
+
+763
+01:01:02,820 --> 01:01:08,880
+اللي موجودة هنا هيكون القرار أن أنا فعلياً أقبل أو
+
+764
+01:01:08,880 --> 01:01:14,300
+أرفض الـ
+
+765
+01:01:14,300 --> 01:01:15,560
+value اللي موجودة عندي هنا
+
+766
+01:01:21,160 --> 01:01:26,300
+We need to reject بنرفض القيمة هذه وين؟ point zero
+
+767
+01:01:26,300 --> 01:01:31,900
+zero واحد إذا كانت القيمة اللي طالعة يعني بالعقل
+
+768
+01:01:31,900 --> 01:01:34,700
+الإمام علي رضي الله عنه قال لو كان ال.. لو كان
+
+769
+01:01:34,700 --> 01:01:37,640
+الدين بالعقل ما كان مسحه باطل الخفي أو لا من
+
+770
+01:01:37,640 --> 01:01:42,780
+ظاهر صح؟ لما.. لما نمسح على الجربان في الشتاء
+
+771
+01:01:42,780 --> 01:01:47,020
+نمسح من فوق بينما الوسخ من أين بيجي؟ يعني من من
+
+772
+01:01:47,020 --> 01:01:51,330
+تحت بس الدين مش بالعقل مش كل شيء بالعقل بيجي ماشي
+
+773
+01:01:51,330 --> 01:01:58,530
+أحمد؟ فأنت بدك تروح تحسب عشان تثبت كلامك طيب الـ
+
+774
+01:01:58,530 --> 01:02:02,710
+reduction الأخيرة اللي عندنا الـ data reduction
+
+775
+01:02:02,710 --> 01:02:05,330
+اللي بتمتّع من الـ reduction خلصنا من الـ attributes
+
+776
+01:02:05,330 --> 01:02:08,670
+احنا وقلت بقى أخلص من الـ irrelevant attributes أو
+
+777
+01:02:08,670 --> 01:02:12,230
+الـ dependent attributes الآن بدي أعمل sampling
+
+778
+01:02:12,230 --> 01:02:15,870
+sampling يعني أنا بدي أتكلم على الـ rows جماعة الخير
+
+779
+01:02:15,870 --> 01:02:20,090
+أنا خلصت خلصت عدد الـ attributes الآن بدي أقلّص عدد
+
+780
+01:02:21,080 --> 01:02:24,780
+الـ rows افترض
+
+781
+01:02:24,780 --> 01:02:29,540
+أن أنا عندي الصندوق هذا وفيه
+
+782
+01:02:29,540 --> 01:02:43,100
+عشر كرات وقلت لك
+
+783
+01:02:43,100 --> 01:02:53,290
+بدي أسحب كرتين متتاليتين كل واحدة بشكل مستقل تمام؟
+
+784
+01:02:53,290 --> 01:02:59,910
+احتمال أن الكرتين هدول يطلعوا حمر جدع؟ خلط
+
+785
+01:02:59,910 --> 01:03:08,590
+السحب الأولى أربعة على عشرة من جلك؟
+
+786
+01:03:08,590 --> 01:03:13,850
+حسب الـ random sample بتاعتي with replacement أو
+
+787
+01:03:13,850 --> 01:03:17,670
+without هذا اللي أنا بدي أوصلك إياه الآن أنا في الـ
+
+788
+01:03:17,670 --> 01:03:28,030
+sampling أو في الـ Random Sample في
+
+789
+01:03:28,030 --> 01:03:34,190
+عندي With Replacement و
+
+790
+01:03:34,190 --> 01:03:40,630
+Without Replacement مع
+
+791
+01:03:40,630 --> 01:03:44,870
+الإرجاع وبدون الإرجاع الآن احتمال أن أسحب كرتين
+
+792
+01:03:44,870 --> 01:03:56,610
+حمر مع الإرجاع 4 على 10 ضرب 4 على 10 بدون
+
+793
+01:03:56,610 --> 01:04:06,250
+إرجاع 4 على 10 ضرب 3 على 9 لأن الآن اتغيّرت الـ
+
+794
+01:04:06,250 --> 01:04:09,890
+sample بتاعتي أو الـ population بتاعتي اتغيّرت
+
+795
+01:04:09,890 --> 01:04:17,120
+وبالتالي قلت وقيمتين تمام الآن احنا معظم شغلنا لما
+
+796
+01:04:17,120 --> 01:04:21,300
+بنعمل sampling معظمُه نتكلم sampling without
+
+797
+01:04:21,300 --> 01:04:26,180
+replacement لأن أنا ما بديش تكرار فأحنا بنشتغل
+
+798
+01:04:26,180 --> 01:04:32,280
+هنا without replacement ليش؟ لأن كمان مرة عاملة
+
+799
+01:04:32,280 --> 01:04:35,060
+بقول أنا بدي أخلص من التكرار أخلص من الـ rows
+
+800
+01:04:35,060 --> 01:04:38,560
+المكرّرة أخلص من الـ attributes المكرّرة فلو أنا
+
+801
+01:04:38,560 --> 01:04:43,920
+الصاحب بتاعي أو الـ random sample مع الإرجاع ممكن الـ
+
+802
+01:04:43,920 --> 01:04:48,660
+record نفسه يظل يطلع عندي الشغل الثاني اللي أنا
+
+803
+01:04:48,660 --> 01:04:54,260
+بدي إياه لأن في الـ random sampling تخيّل أنا جيت و
+
+804
+01:04:54,260 --> 01:05:01,620
+قلت لك بدي 70 أو عفواً بدي خمسين أربعين في المئة من
+
+805
+01:05:01,620 --> 01:05:07,400
+الـ data set هاي بدي تاخد لي أربعين في المئة من الـ
+
+806
+01:05:07,400 --> 01:05:07,960
+data set
+
+807
+01:05:13,280 --> 01:05:19,680
+كم كرة بقى تحطها أنت؟ أربع كرات بدك تسحب أربع كرات
+
+808
+01:05:19,680 --> 01:05:27,300
+عشوائي شو
+
+809
+01:05:27,300 --> 01:05:32,240
+وراك بهيك؟ sample صح من ناحية sample without
+
+810
+01:05:32,240 --> 01:05:39,000
+replacement صح بس هي مشكلة أن الـ data set ها دي لا
+
+811
+01:05:39,000 --> 01:05:42,560
+تمثّل البيانات does not representative أنا قلت بدي
+
+812
+01:05:42,560 --> 01:05:47,540
+أجل حجم الـ data 6 نعم لكن بدي أضل أتمثّل الوضع
+
+813
+01:05:47,540 --> 01:05:54,520
+العام بتاعتها ما بضبط الحل كيف أنا بدي أضمن نسبة نسبة
+
+814
+01:05:54,520 --> 01:06:00,380
+وتناسب 40% من الأحمر و40% من الأسود وبهيك بكون
+
+815
+01:06:00,380 --> 01:06:04,640
+حصلت على الـ 40% وهذه الـ 40% بنسميها stratified
+
+816
+01:06:05,470 --> 01:06:10,590
+Sampling أو بين جثيم Supervised Sampling بروح على
+
+817
+01:06:10,590 --> 01:06:16,530
+كل class وبأخذ منه 40% الـ data set موجودة حقيقة
+
+818
+01:06:16,530 --> 01:06:20,470
+نعم موزّعة على two classes three classes four
+
+819
+01:06:20,470 --> 01:06:26,310
+classes أنا بدي 40% منها بأخذهم يا شي stratified
+
+820
+01:06:26,310 --> 01:06:30,270
+Sampling مباشرة بتجيب لي 30% من كل أو 40% من كل
+
+821
+01:06:30,270 --> 01:06:34,400
+class ضايل عندنا نقطة واحدة في موضوع الـ
+
+822
+01:06:34,400 --> 01:06:37,740
+Discretization في موضوع الـ Discretization يا شباب
+
+823
+01:06:37,740 --> 01:06:44,840
+الفكرة أنا قلّلت عدد الـ attributes قلّلت عدد الـ rows
+
+824
+01:06:44,840 --> 01:06:51,520
+بالـ sampling والآن بدي أَقلّل عدد الـ distinct values
+
+825
+01:06:51,520 --> 01:06:55,060
+في الـ attribute الـ attribute نفسه موجود مش هقص منه
+
+826
+01:06:55,060 --> 01:06:58,860
+على مستوى الـ rows والـ attribute هيبقى بدي أقلّل
+
+827
+01:06:58,860 --> 01:07:03,430
+العدد الـ Variable.. Variant أو العدد الـ Values
+
+828
+01:07:03,430 --> 01:07:06,810
+أقل العدد الـ Values أو أقل الـ Variety الـ Variety
+
+829
+01:07:06,810 --> 01:07:11,550
+بين الـ Values اللي موجودة بتفرج معايا؟ آه بتفرج
+
+830
+01:07:11,550 --> 01:07:17,970
+أنا عندي الـ Age من عشر لخمسين نتكلم على تسعة و
+
+831
+01:07:17,970 --> 01:07:20,830
+أربعين distinct value واحد وأربعين.. واحد و
+
+832
+01:07:20,830 --> 01:07:24,090
+أربعين، صح؟ لأن الصفر موجود معناته واحد وأربعين
+
+833
+01:07:24,090 --> 01:07:27,490
+واحد وأربعين distinct value يعني الـ rule بتاعي بدي
+
+834
+01:07:27,490 --> 01:07:32,780
+يحتوي على واحد وأربعين F41 condition هذا الكلام
+
+835
+01:07:32,780 --> 01:07:38,400
+مشكلة ما بضبط الحل اعمل discretization أقلّل الـ values
+
+836
+01:07:38,400 --> 01:07:43,280
+اللي موجودة كيف لاحظ هي number number continuous
+
+837
+01:07:43,280 --> 01:07:47,820
+وأنت بقى بتحوّلها discrete discretization بتعملهم
+
+838
+01:07:47,820 --> 01:07:52,500
+قيم يعني بنجمع بقى بتعملهم فئات بس بده تحافظ
+
+839
+01:07:52,500 --> 01:07:57,850
+على الأرقام اللي موجودة الآن ممكن أنت تستخدم طرق
+
+840
+01:07:57,850 --> 01:08:02,170
+سواء بالاعتماد على الـ Label أو بدونه Supervised و
+
+841
+01:08:02,170 --> 01:08:05,570
+Unsupervised بالـ Unsupervised بدي أطبّق مفهوم الـ
+
+842
+01:08:05,570 --> 01:08:09,650
+Binning وأستبدل القيم بالـ Mean أو بالـ Median زي
+
+843
+01:08:09,650 --> 01:08:13,530
+ما شفنا وين في الـ Data Transformation يعني بيجي
+
+844
+01:08:13,530 --> 01
+
+889
+01:12:04,190 --> 01:12:10,240
+باستخدام python تقرأ الـ data set
+
+890
+01:12:10,240 --> 01:12:14,340
+وتطبق عليها عمليات الـ cleaning التالية بناءً على
+
+891
+01:12:14,340 --> 01:12:18,720
+الحاجة: إزالة الـ missing values، الـ noise، الـ duplicate records، و
+
+892
+01:12:18,720 --> 01:12:22,960
+إزالة الـ correlated attributes واختيار الـ relevant attributes
+
+893
+01:12:22,960 --> 01:12:28,940
+كيف تتعامل مع الـ correlated attributes؟ الآن، إذا كانت
+
+894
+01:12:28,940 --> 01:12:34,560
+معاملات الـ correlation بين الـ attributes أكبر من أو تساوي 80%،
+
+895
+01:12:34,560 --> 01:12:41,490
+فإنك تحذف جميعها ماعدا واحد منها.
+
+896
+01:12:41,490 --> 01:12:44,410
+فقط، وهكذا تكرر العملية وتطبقها على الجميع.
+
+897
+01:12:44,410 --> 01:12:51,910
+بعد ذلك، قم بتقسيم الـ data set بنسبة 70% للتدريب (training) و
+
+898
+01:12:51,910 --> 01:12:57,630
+30% للاختبار (testing) باستخدام stratified sampling، و
+
+899
+01:12:57,630 --> 01:13:00,290
+أضف تعليقات (comments) كافية على الـ code.
+
+900
+01:13:01,090 --> 01:13:05,730
+بعد ذلك، يرجى رفع ملف بايثون (Python) منفرداً لكل واحد.
+
+901
+01:13:05,730 --> 01:13:09,570
+من المهم أن يكون عمل كل شخص مختلفاً عن عمل زملائه، حتى على نفس الـ data set.
+
+902
+01:13:09,570 --> 01:13:12,990
+التعليقات، الطرق التي تستخدمها، كل هذا يجب أن يكون مختلفاً.
+
+903
+01:13:12,990 --> 01:13:16,770
+ستناقشون عمل كل منكم مع مجموعتكم، لكن العمل بالبايثون يجب أن يكون فردياً.
+
+904
+01:13:16,770 --> 01:13:20,970
+الآن، يوجد بعض الأكواد في
+
+905
+01:13:20,970 --> 01:13:24,050
+الشرائح (slides) ستساعدكم على العديد من التفاصيل.
+
+906
+01:13:25,420 --> 01:13:28,560
+منذ بداية الشهر الماضي وأنا أقول
+
+907
+01:13:28,560 --> 01:13:31,720
+للطلاب أن يقوموا بعملية الـ install. إذا لم تقم
+
+908
+01:13:31,720 --> 01:13:34,440
+بعملية الـ install، فأنت جاهز للعمل غداً أو الآن.
+
+909
+01:13:34,440 --> 01:13:40,100
+أما إذا لم تقم بعملية الـ install، فسيتوجب عليك البدء الآن.
+
+910
+01:13:40,100 --> 01:13:43,720
+ستعملون بشكل فردي، وترفعون ملف الـ python الخاص بكم على
+
+911
+01:13:43,720 --> 01:13:48,640
+الـ model بشكل مستقل، وبعد ذلك ستناقشون مع مجموعاتكم.
+
+912
+01:13:48,640 --> 01:13:52,420
+لاحقاً، كما سنشرح لكم.  
+
+913
+01:13:52,420 --> 01:13:54,820
+سأغادر الآن إن شاء الله، وسأرفع لكم
+
+914
+01:13:54,820 --> 01:13:59,360
+على الـ model. لا تقلقوا، إن شاء الله سيكون كل شيء على ما يرام.
+
+915
+01:13:59,360 --> 01:14:01,840
+شكراً لكم، وأتمنى لكم نهاية أسبوع سعيدة إن شاء الله.
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/hrMDIeuEJkQ_postprocess.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/hrMDIeuEJkQ_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..2464e16e7d050d9e150e54111e3ebf9f65766291
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/hrMDIeuEJkQ_postprocess.srt
@@ -0,0 +1,3660 @@
+1
+00:00:04,840 --> 00:00:07,380
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:07,380 --> 00:00:11,680
+أهلا وسهلا بكم يا شباب ان شاء الله احنا اليوم نكمل
+
+3
+00:00:11,680 --> 00:00:14,360
+مع ال chapter data understanding and data
+
+4
+00:00:14,360 --> 00:00:16,700
+preparation و هذا ال chapter المحاضرة هي اللي
+
+5
+00:00:16,700 --> 00:00:20,200
+هتكون المحاضرة الأخيرة في ال chapter اللي موجود
+
+6
+00:00:20,200 --> 00:00:23,200
+بين ايدينا كنا اتكلمنا انه فعليا عشان انا اعمل اي
+
+7
+00:00:23,200 --> 00:00:27,100
+data mining project بيلزمني من data cleaning data
+
+8
+00:00:27,100 --> 00:00:32,500
+integration data transformation data selection
+
+9
+00:00:32,500 --> 00:00:36,130
+data miningpattern evaluation و knowledge
+
+10
+00:00:36,130 --> 00:00:39,150
+presentation وقلنا هذه الخطوات السبعة اللي انا
+
+11
+00:00:39,150 --> 00:00:43,310
+فعليا بمر فيها اي مشروع اللي علاقة بال data mining
+
+12
+00:00:43,310 --> 00:00:47,290
+وكنا حكينا اخر محاضرة الأخيرة بدأنا نتكلم عن ال
+
+13
+00:00:47,290 --> 00:00:49,910
+data transformation وقلنا هدف ال data
+
+14
+00:00:49,910 --> 00:00:55,030
+transformation ان احط البيانات في صورة جديدةتتناسب
+
+15
+00:00:55,030 --> 00:00:58,970
+مع عملية ال mining اللي انا بدي اقوم فيها وذكرنا
+
+16
+00:00:58,970 --> 00:01:01,230
+انه ممكن اطبق smoothing او aggregation
+
+17
+00:01:01,230 --> 00:01:04,770
+generalization و ال normalization ومحاضرتنا اخر
+
+18
+00:01:04,770 --> 00:01:08,190
+شغلة في المحاضرة الماضية بدينا مع ال normalization
+
+19
+00:01:08,190 --> 00:01:11,870
+وقلنا ال normalization انه انا فعليا اروح اعمل
+
+20
+00:01:11,870 --> 00:01:15,850
+scaling لل data set اللي موجودة عندى او عفوا لل
+
+21
+00:01:15,850 --> 00:01:19,030
+attributes او لل data اللي عندى بحيث انه تتناسب مع
+
+22
+00:01:19,990 --> 00:01:23,850
+طبيعة ال mining task اللي عندى وقولنا أبسط الأمور
+
+23
+00:01:23,850 --> 00:01:27,110
+لو كان في عندى ال two attributes و ال range أو ال
+
+24
+00:01:27,110 --> 00:01:30,290
+gap بين ال ranges تبعتهم عالية كبيرة أو عالية كتير
+
+25
+00:01:30,290 --> 00:01:34,210
+مثل ما قولنا واحد من صفر لواحد وال attribute
+
+26
+00:01:34,210 --> 00:01:38,240
+التاني من مية لألفهدول التانية لو انا بدى اجمعهم
+
+27
+00:01:38,240 --> 00:01:42,400
+مع بعض على رسمة واحدة من المستحيل اقدر ايش اطبقهم
+
+28
+00:01:42,400 --> 00:01:45,400
+فبالتالي لازم انا اعمل scaling احطهم التانية في
+
+29
+00:01:45,400 --> 00:01:49,600
+نفس ال range بيسهل علي رسمهم والشغل التاني كمان ال
+
+30
+00:01:49,600 --> 00:01:52,620
+computation تبعت ال algorithm بتكون أبسط لما بتكون
+
+31
+00:01:52,620 --> 00:01:56,600
+اديتها كلها أيش من نفس المستوى وكنا اتكلمنا عن ال
+
+32
+00:01:56,600 --> 00:01:59,800
+zero score او ال z score normalization او ال
+
+33
+00:01:59,800 --> 00:02:04,180
+standard normalization قولنا الفكرة بال normalبال
+
+34
+00:02:04,180 --> 00:02:07,480
+stand أو بال zero score انه انا فعليا لل
+
+35
+00:02:07,480 --> 00:02:11,500
+attributes اللى عندى بحاجة ان احسب المتوسط الحسابى
+
+36
+00:02:11,500 --> 00:02:17,380
+ال main و احسب ال variance او الانحراف المعيارى لل
+
+37
+00:02:17,380 --> 00:02:21,400
+attributes اللى موجود عندى و الانحراف المعيارى هي
+
+38
+00:02:21,400 --> 00:02:28,200
+عبارة عن حاصل مجموع تربيع الفروقات ما بين النقاط و
+
+39
+00:02:28,200 --> 00:02:32,020
+المتوسط الحسابى على العدد تحت الجدر التربيعى
+
+40
+00:02:32,020 --> 00:02:38,090
+وشوفناالمرة الماضية تأثيره فعليا بالشكل هذا لما
+
+41
+00:02:38,090 --> 00:02:40,970
+روحت انا طبقت الـ zero mean كان مفهومها انه لما
+
+42
+00:02:40,970 --> 00:02:45,110
+انا بقى اطبق ال normalization هاي او ال scaling
+
+43
+00:02:45,110 --> 00:02:47,770
+هذه المتوسط الحساب اللي هيطلع مع ال attribute
+
+44
+00:02:47,770 --> 00:02:51,630
+الجديد او مع ال value جديد قيمته صفر وبالتالي
+
+45
+00:02:51,630 --> 00:02:57,870
+هتكون عندى ال variance قيمتها واحد وطبعا قولنا هاي
+
+46
+00:02:57,870 --> 00:03:02,560
+واضحة الرسمةلاحظ ان هذه ال data ال original طبيعية
+
+47
+00:03:02,560 --> 00:03:06,300
+الان هيها مزاية على two classes لما عملت لها
+
+48
+00:03:06,300 --> 00:03:11,760
+scaling بال standard scalar او بال zero score لاحظ
+
+49
+00:03:11,760 --> 00:03:16,000
+توزعت على الأربع الأربع اللي في ال Cartesian plane
+
+50
+00:03:16,000 --> 00:03:19,320
+وبالتالي انا بقدر اتكلم انه فعليا في قيم تلغي
+
+51
+00:03:19,320 --> 00:03:22,660
+التانية لما اجمع متوسطهم او لما بدور على متوسطهم
+
+52
+00:03:22,660 --> 00:03:27,020
+الحساب اليوم ان شاء الله هنكملأو كنا حكينا برضه في
+
+53
+00:03:27,020 --> 00:03:29,380
+الموضوع عشان هذه أخر شغلات نهينا فيها محاضرتنا
+
+54
+00:03:29,380 --> 00:03:32,340
+الماضية ال robust scalar هي عبارة عن ال special
+
+55
+00:03:32,340 --> 00:03:38,240
+scalar من ال zero score لكن بدل ما يروح يعتمد لي
+
+56
+00:03:38,240 --> 00:03:43,200
+على ال mean بيعتمد على ال median و ال quartile بدل
+
+57
+00:03:43,200 --> 00:03:46,440
+ال median ال mean و ال variance ال min max score
+
+58
+00:03:46,440 --> 00:03:50,750
+قلنا ال min max score مفهومها ان انا فعليا أحبالـ
+
+59
+00:03:50,750 --> 00:03:54,130
+attributes هذه أو ال values هذه ضمن فترة أنا
+
+60
+00:03:54,130 --> 00:03:58,830
+بحددها ضمن مجموعة من العناصر اللي أنا بدي إيها
+
+61
+00:03:58,830 --> 00:04:03,850
+وليكن على سبيل المثال أنا كان في عند ال values 12
+
+62
+00:04:03,850 --> 00:04:12,170
+15 10 11 20 هذه القيم اللي موجودة عندى وبدأ أروح
+
+63
+00:04:12,170 --> 00:04:17,210
+أحطها في فترة من 0 ل1 أبسط عشان تكون معايا الآن
+
+64
+00:04:17,210 --> 00:04:22,510
+أسهل في الحلالآن حسب الـ Min Max Normalization هذه
+
+65
+00:04:22,510 --> 00:04:25,770
+كل اللي أنا بسويه قاعد بعمل Shift و تقليص لل
+
+66
+00:04:25,770 --> 00:04:28,610
+Interval ال Interval الحقيقية اللي عندي من عشرة
+
+67
+00:04:28,610 --> 00:04:34,090
+لعشرين مش هدرد هيك ال data موجودة ال data موجودة
+
+68
+00:04:34,090 --> 00:04:37,850
+من عشرة لعشرين الآن أنا بدي أروح أخليها كلها
+
+69
+00:04:37,850 --> 00:04:43,330
+محصورة ما بين صفر و واحد يعني ال minimum تبعتي
+
+70
+00:04:43,330 --> 00:04:51,310
+جداش قيمتها عشرة والعشرينهذه الـ max طب ال new
+
+71
+00:04:51,310 --> 00:04:59,650
+minimum اللي أنا بدي إياها zero و ال new max واحد
+
+72
+00:04:59,650 --> 00:05:03,550
+أنا قاعد بتقول بيخليها من صفر ل واحد كل الأرقام
+
+73
+00:05:03,550 --> 00:05:07,170
+تصير من صفر ل واحد الآن بكل بساطة أي قيمة من القيم
+
+74
+00:05:07,170 --> 00:05:10,710
+هدول بتطبق عليها مين القانون البسيط اللي موجود
+
+75
+00:05:10,710 --> 00:05:14,610
+عندها طبعا قوانينها يا شباب مطلوب بحفظ تمام؟ لإن
+
+76
+00:05:14,610 --> 00:05:19,290
+مش هزودك بالقانون و أنت بتحلمالان نيجي ناخد على
+
+77
+00:05:19,290 --> 00:05:23,630
+سبيل المثال المفروض العشرة هذه بعد القانون هيتطابق
+
+78
+00:05:23,630 --> 00:05:28,650
+مين؟ الصفر تعالي ناخد العشرة القيمة الجديدة للعشرة
+
+79
+00:05:28,650 --> 00:05:35,950
+تساوي العشرة ناقص ال minimum تبعت ال attribute ال
+
+80
+00:05:35,950 --> 00:05:42,330
+minimum تبعت ال attribute قداش؟ عشرة على ال
+
+81
+00:05:42,330 --> 00:05:46,700
+maximum ناقص ال minimum تبعت ال attributeعشرين
+
+82
+00:05:46,700 --> 00:05:52,640
+ناقص عشرة مضروبة فيه لـ new maximum ناقص لـ new
+
+83
+00:05:52,640 --> 00:06:01,260
+minimum لـ new maximum واحد ناقص صفر زائد ال
+
+84
+00:06:01,260 --> 00:06:08,000
+minimum لـ new minimum لل attribute صفر صفر على
+
+85
+00:06:08,000 --> 00:06:15,310
+عشرة مضروب في واحد زائد صفر صفربصبوت؟ وبهيك انا
+
+86
+00:06:15,310 --> 00:06:19,770
+هايل ال Values و هطبقها تعالى نشوف الخمستعش وين
+
+87
+00:06:19,770 --> 00:06:28,810
+هتصير نفس الكلام يا مؤمن الان خمستعش ناقص عشرة على
+
+88
+00:06:28,810 --> 00:06:37,410
+عشرين ناقص عشرة مضروبة فيه واحد ناقص صفر زاد الصفر
+
+89
+00:06:39,330 --> 00:06:43,130
+لا مش صفر حرام عليك خمس عشر نقص عشرة خمسة خمسة على
+
+90
+00:06:43,130 --> 00:06:49,010
+عشرة في واحد زائد صفر نص
+
+91
+00:06:49,010 --> 00:06:52,790
+فعلا هي جاي في نص ال interval ما بين العشرة
+
+92
+00:06:52,790 --> 00:06:57,410
+والعشرين الخمس عشر جاي بالوسط تمام مظلوط الشباب؟
+
+93
+00:06:57,410 --> 00:07:01,290
+طيب و هيك بنكون خلصنا من ال normalization
+
+94
+00:07:01,290 --> 00:07:04,610
+باعتمادنا على ال min max
+
+95
+00:07:08,350 --> 00:07:11,010
+Normalization أو Scalar طبعا هنا أنا بتكلم على
+
+96
+00:07:11,010 --> 00:07:15,810
+Linear Transformation مجرد معادلة خطية نقلت ال
+
+97
+00:07:15,810 --> 00:07:24,550
+data على range جديد هاي مثال بس أنا مزودك بال
+
+98
+00:07:24,550 --> 00:07:29,150
+minimum و ال maximum بالاصل و بسألك كده ال 73600
+
+99
+00:07:29,150 --> 00:07:34,910
+كده هتصير أسهل scalar ممكن أطبقه أنا اللي هو ال
+
+100
+00:07:34,910 --> 00:07:39,910
+decimal scalarDecimal Scalar الـ Decimal Scalar أو
+
+101
+00:07:39,910 --> 00:07:42,970
+الـ Decimal Scaling أنا عند القيم زي ما قولنا بعض
+
+102
+00:07:42,970 --> 00:07:51,710
+العملات تقاس بالملايين 170 مليون في
+
+103
+00:07:51,710 --> 00:07:54,550
+الحساب أو في ال computation تبعت ال system هيغلبني
+
+104
+00:07:54,550 --> 00:07:57,370
+كتير الرقم هذا و هيغلب ال computer كمان يا أهد
+
+105
+00:07:57,370 --> 00:08:01,470
+فإيش الحل؟ بدي أروح أغير الأرقام هذا كل ال
+
+106
+00:08:01,470 --> 00:08:05,330
+attribute بيكون هاي صفتهفمفهوم ال scaling انه انا
+
+107
+00:08:05,330 --> 00:08:10,710
+ممكن اصغرله قيم معينة احجمه كيف احجمه جسمه على
+
+108
+00:08:10,710 --> 00:08:14,630
+عشرة أُس عشرة
+
+109
+00:08:14,630 --> 00:08:18,310
+أُس الان انا بدي اخلص من كل الأصفار معناته هي سبعة
+
+110
+00:08:18,310 --> 00:08:24,490
+و هاد التامن معناته الحاجوله ال X على عشرة أُس
+
+111
+00:08:24,490 --> 00:08:28,910
+تمانية على سبيل المثال ايش القيمة اللي هتطلع عندى
+
+112
+00:08:28,910 --> 00:08:34,690
+واحد point7 وكل الأقام بنفس النظام اللي موجود عند
+
+113
+00:08:34,690 --> 00:08:38,450
+هيكل وبالتالي هذا أسهل واحد طب هل من ال decimal
+
+114
+00:08:38,450 --> 00:08:44,130
+scaling هذا او ضمن ال scalars السابقات بقدر اغير
+
+115
+00:08:44,130 --> 00:08:51,430
+او اكبر ال range كيف أسوي يا مؤمن يا راني هان اضرب
+
+116
+00:08:51,430 --> 00:08:57,030
+في ايش اضرب في عشرة اضرب في عشرة تمام او بتخلي نفس
+
+117
+00:08:57,030 --> 00:08:58,910
+المعادلة وخلي ال K بالسالب
+
+118
+00:09:01,480 --> 00:09:05,840
+فتتحول المباشرة العملية لضرب طيب في ال min max
+
+119
+00:09:05,840 --> 00:09:10,540
+بقدر اكبر ال range هي كانت أساسا عندى من صفر ل
+
+120
+00:09:10,540 --> 00:09:16,560
+واحد انا بدي اعملها من واحد لعشرة بينفع نفس
+
+121
+00:09:16,560 --> 00:09:21,600
+القانون لنفس المعادلة بس بكي اتطبق معاملات جديدة
+
+122
+00:09:21,600 --> 00:09:25,180
+في المعادلة الجديدة حتكون ال old minimum او ال
+
+123
+00:09:25,180 --> 00:09:28,280
+attribute minimum ال attribute maximum ل ال new
+
+124
+00:09:28,280 --> 00:09:33,180
+minimum و ل ال new maximum و خلصناطب هل ممكن هذا
+
+125
+00:09:33,180 --> 00:09:41,240
+الكلام يصير مع الـ Standard Scalar؟ أكبر ال .. إيش
+
+126
+00:09:41,240 --> 00:09:44,780
+ال .. إيش ال Standard Scalar؟ اللي بيحسب المتوسط
+
+127
+00:09:44,780 --> 00:09:52,320
+الحساب و الحراف المعياري أول واحد هذا بقدرش
+
+128
+00:09:52,320 --> 00:09:56,400
+لأن المتغيرات تابعة لميو تابعة لكل ال attributes
+
+129
+00:09:56,400 --> 00:10:00,620
+ال variance تابعة لكل ال attributes وبالتالي لا
+
+130
+00:10:00,620 --> 00:10:04,650
+مافيش مجالStandard اسمه standard مافيش فيه لعب
+
+131
+00:10:04,650 --> 00:10:14,470
+تمام هنمتقل الآن لموضوع data reduction احنا كنا
+
+132
+00:10:14,470 --> 00:10:18,010
+بنتكلم على مين على ال data transformation وكان
+
+133
+00:10:18,010 --> 00:10:20,650
+نتكلم بالتحديد في ال transformation ال scaling
+
+134
+00:10:20,650 --> 00:10:24,590
+الان بدي اتكلم في ال data في ال transformation بدي
+
+135
+00:10:24,590 --> 00:10:27,710
+اتكلم على ال data reduction الان مفهوم ال
+
+136
+00:10:27,710 --> 00:10:33,360
+transformation ان الصورة ال data كانت في صورةوصارت
+
+137
+00:10:33,360 --> 00:10:37,480
+في صورة مختلفة ممكن الصورة هذه فعلياً كانت تأثير
+
+138
+00:10:37,480 --> 00:10:41,820
+فقط في البيانات زي ما عملت بالـ Scaling نفس ال
+
+139
+00:10:41,820 --> 00:10:45,620
+attributes ضالوا زي ما هم و ال rows ضالوا زي ما هم
+
+140
+00:10:45,620 --> 00:10:48,840
+بالناحية عدد لكن ال data اللي موجودة في ال
+
+141
+00:10:48,840 --> 00:10:53,220
+attributes هي اللي أخدت صورة جديدة وبهيك بصرت كل
+
+142
+00:10:53,220 --> 00:10:57,360
+ال data's صارت لها صورة جديدة أو form جديدة لكن
+
+143
+00:10:57,360 --> 00:11:01,860
+الآنفي ال data reduction هو عبارة عن تحوير لل data
+
+144
+00:11:01,860 --> 00:11:07,360
+أنه أنا بدي أقلص حجم البيانات يا دكتور انت من أول
+
+145
+00:11:07,360 --> 00:11:09,760
+ال chapter و بتقولنا كبروا البيانات و مصادر بنا
+
+146
+00:11:09,760 --> 00:11:12,960
+البيانات أخرى وعزز و integration و هلاك تقولي بدي
+
+147
+00:11:12,960 --> 00:11:15,860
+أعمل reduction أه انت بحاجة أنك تعمل reduction
+
+148
+00:11:15,860 --> 00:11:21,180
+أحيانا ال data set already كبيرة عندك فيها مليون
+
+149
+00:11:21,180 --> 00:11:21,600
+record
+
+150
+00:11:24,360 --> 00:11:28,360
+أخد المليون record أتعلم عليهم؟ كويس بس هكلفك كتير
+
+151
+00:11:28,360 --> 00:11:32,040
+وقته و بتعمل analysis لو أنا اتيت سألتك تعمل
+
+152
+00:11:32,040 --> 00:11:35,700
+analysis ل five attributes و ten rows يعني خمسين
+
+153
+00:11:35,700 --> 00:11:41,040
+value ولا بس أزيد ال rows أقول metro بصيروا خمسمية
+
+154
+00:11:41,040 --> 00:11:43,800
+خمسين ولا خمسمية؟ مين يستخدم في ال analysis؟
+
+155
+00:11:44,390 --> 00:11:47,750
+الخمسين بكل تأكيد قولي هو الكمبيوتر فارق معايا يا
+
+156
+00:11:47,750 --> 00:11:50,470
+أستاذ أه بتفرج معاه لما تشير الشغل بالملايين زي ما
+
+157
+00:11:50,470 --> 00:11:54,030
+احنا بتتكلم جاعدين ومش قيمة واحدة ومش معادلة واحدة
+
+158
+00:11:54,030 --> 00:11:57,970
+اللي بتنحسب لأ بتصير تفرج معايا فعشان هيك أنا
+
+159
+00:11:57,970 --> 00:12:02,590
+بحتاج أحيانًا أعمل reduction لكن شرب أساسي ال
+
+160
+00:12:02,590 --> 00:12:08,090
+reduction هذا مش على حساب جودة ال data يعني بين
+
+161
+00:12:08,090 --> 00:12:11,010
+جسين لما أنا بقول والله أني بدي أخد مثلًا من
+
+162
+00:12:11,010 --> 00:12:15,370
+المائة ألف بدي أخد خمسين الف فقطبدي أضمن إن الـ 50
+
+163
+00:12:15,370 --> 00:12:18,870
+ألف هدول بيمثلوا كل ال data الحقيقية
+
+164
+00:12:18,870 --> 00:12:22,490
+representative لكل ال data باجي أقول إن في عندي
+
+165
+00:12:22,490 --> 00:12:25,870
+مجموعة من ال attributes أنا مابديش إياها فعليا أنا
+
+166
+00:12:25,870 --> 00:12:31,510
+مابديش إياها لأنها إما useless غير مفيدة عندي أو
+
+167
+00:12:31,510 --> 00:12:35,850
+فعليا ال effect تبعتها بسيط وبسيط جدا مابأثرش
+
+168
+00:12:35,850 --> 00:12:41,690
+وبالتالي أنا جاعة بتكلم علىReduction هدفها ان اخلي
+
+169
+00:12:41,690 --> 00:12:48,250
+ال data set تصير عندى much smaller من الأول جبتها
+
+170
+00:12:48,250 --> 00:12:51,070
+صغيرة في الأول انت ال data ماكنتش بتعرفها أساسا
+
+171
+00:12:51,070 --> 00:12:55,650
+بتعرفش ان هي representative ولا لأ بس الان وقعت
+
+172
+00:12:55,650 --> 00:12:59,150
+بين ايديك data set حجمها كبير احنا في الأول قولات
+
+173
+00:12:59,150 --> 00:13:02,310
+جيبنا data set شايفينها صغيرة بدنا نكبرها عشان
+
+174
+00:13:02,310 --> 00:13:05,790
+نعزز ال knowledge اللى موجودة فيها بس الان already
+
+175
+00:13:05,790 --> 00:13:09,330
+ال data set اللى موجودة بين ايدياضخمة لو انا سألتك
+
+176
+00:13:09,330 --> 00:13:14,310
+محمد جداش حجم ال data set اللي انت رفعتليها على ال
+
+177
+00:13:14,310 --> 00:13:20,190
+model تلاتة مليون record مش
+
+178
+00:13:20,190 --> 00:13:24,210
+قضية تلاتة مليون record بالمنطق .. بالمنطق انا
+
+179
+00:13:24,210 --> 00:13:26,630
+هاخد التلاتة مليون record و اقول ال system اتعلم
+
+180
+00:13:26,630 --> 00:13:31,150
+عليهم لازم اعمل reduction لأن ممكن من التلاتة
+
+181
+00:13:31,150 --> 00:13:33,290
+مليون record انه بس تلات تلاف record يكونوا كافيات
+
+182
+00:13:33,290 --> 00:13:37,580
+ممكنالـ 3 مليون record ممكن فيه بينهم redundant
+
+183
+00:13:37,580 --> 00:13:41,440
+attributes أو عفوا redundant rows فلمّا أنا أروح
+
+184
+00:13:41,440 --> 00:13:47,200
+أشيلهم يصيروا 500 ألف فهذا الكلام لازم يصير عشان
+
+185
+00:13:47,200 --> 00:13:51,100
+كمان مرة قلتلك أسرع عملية ال analysis و في نفس
+
+186
+00:13:51,100 --> 00:13:54,620
+الوقت أن ال data تظل بتحمل نفس .. بتديني نفس
+
+187
+00:13:54,620 --> 00:14:01,480
+النتيجة وهذا أحيانا بيفعلني فيهأحياناً بألجأ له ..
+
+188
+00:14:01,480 --> 00:14:04,160
+بأحياناً بألجأ له لأنه أنا فعلياً بدي action
+
+189
+00:14:04,160 --> 00:14:08,620
+سريعة، بدي أشوف result تلاتة مليون ممكن بدهم
+
+190
+00:14:08,620 --> 00:14:11,400
+ياخدوا مني نهار أو اتنين، ساعة أو تنتين، بينما أنا
+
+191
+00:14:11,400 --> 00:14:14,680
+محتاج أشوف result خلال نص ساعة، فإيش بدي أضطر
+
+192
+00:14:14,680 --> 00:14:19,400
+أساوي؟ لازم أقل الحجم ال data، هذي واحد، اتنين
+
+193
+00:14:19,400 --> 00:14:22,440
+الأجهزة
+
+194
+00:14:22,440 --> 00:14:25,970
+اللي أنا عادة بعمل عليها analysis بتكلفيعني أنا
+
+195
+00:14:25,970 --> 00:14:29,570
+بعرف طالب ماجستير من قريبنا عشان فعليا كان النص
+
+196
+00:14:29,570 --> 00:14:34,390
+ساعة بيدفع عليها مبلغ محترم وفعليا احتاج اتناشر
+
+197
+00:14:34,390 --> 00:14:38,530
+ساعة دفع عليهم وكان في بعض اشتغل على بعض ال ال ال
+
+198
+00:14:38,530 --> 00:14:43,530
+free ال clusters بالمجان بس ماكنتش يتكفي كان بعد
+
+199
+00:14:43,530 --> 00:14:46,290
+مثلا ست ساعات تفصل ال session يقولوا خلاص اكتر من
+
+200
+00:14:46,290 --> 00:14:52,880
+ست ساعات بنشغل cashفكان لازم يروح يدفع عشان .. لكن
+
+201
+00:14:52,880 --> 00:14:57,760
+بالآخر أنا قاعد بقولك ال reduction هذه علشان أسرع
+
+202
+00:14:57,760 --> 00:15:01,320
+عملية ال analysis مع الضمان اللي لها نفس النتيجة
+
+203
+00:15:01,320 --> 00:15:04,280
+طب كيف بدي أضمن نفس النتيجة؟ إذا أنت كنت expert
+
+204
+00:15:04,280 --> 00:15:08,320
+بتفهم لحالك من وقع الخبرة اللي صارت زي حالتنا،
+
+205
+00:15:08,320 --> 00:15:13,040
+بنتدرب، بنتعلم، بدك تجرب مرة خليتهم 100 ألف تلاتة
+
+206
+00:15:13,040 --> 00:15:18,350
+مليون نزلتهم لخمسين ألفنزلتهم لعشرة ألف و في كل
+
+207
+00:15:18,350 --> 00:15:22,430
+مرة بقال إن ال result إذا ال result ضلت بنفس
+
+208
+00:15:22,430 --> 00:15:25,610
+المستوى ما تلاقى ال reduction أولى بالنسبة لي
+
+209
+00:15:25,610 --> 00:15:31,870
+تمام؟ نعم جايينها .. جايينها بالتفصيل الآن يا مؤمن
+
+210
+00:15:31,870 --> 00:15:35,590
+ان شاء الله تعالى و لا يهمك الآن لاحظ أنا بتكلم
+
+211
+00:15:35,590 --> 00:15:40,230
+قاعد reduction ماتكلمتش بأي dimension لا اتكلمت
+
+212
+00:15:40,230 --> 00:15:43,490
+على صفوف ولا اتكلمت على أعمدة بس في الآخر بدي أعمل
+
+213
+00:15:43,490 --> 00:15:47,350
+reductionالفكرة كمان مرة بدي أصغر حجم ال data set
+
+214
+00:15:47,350 --> 00:15:53,650
+بدي أصغر عدد ال computation اللي بدها تصير و أحافظ
+
+215
+00:15:53,650 --> 00:15:55,870
+على نفس ال analytic result نفس النتيجة اللي بدها
+
+216
+00:15:55,870 --> 00:16:01,770
+تطلع معايا قدر المستطاع ليه أشهد الكلام؟ عشان أقلل
+
+217
+00:16:01,770 --> 00:16:07,410
+ال analysis time عشان أقلل ال analysis time الآن
+
+218
+00:16:07,410 --> 00:16:11,310
+في ال reduction أنا فيه عندي تلت خطوات أو three
+
+219
+00:16:11,310 --> 00:16:17,430
+operations ممكن أنا أسويهمreduction على مستوى ال
+
+220
+00:16:17,430 --> 00:16:23,050
+attributes وهنا نسميها feature selection اختيار ال
+
+221
+00:16:23,050 --> 00:16:29,430
+attributes المميزة لل data set sampling وهنا بتكلم
+
+222
+00:16:29,430 --> 00:16:33,890
+على reduction على مستوى ال rows او بتكلم
+
+223
+00:16:33,890 --> 00:16:37,990
+discretization بتكلم reduction على مستوى ال values
+
+224
+00:16:37,990 --> 00:16:42,830
+عدد ال distinct values في ال attribute وخلّينا
+
+225
+00:16:42,830 --> 00:16:48,340
+الآن نبدأ معالأولى كمان مرة جماعة الخير بعيد و
+
+226
+00:16:48,340 --> 00:16:53,140
+بأكد أنا بدي أعمل reduction لل data set بحيث أنها
+
+227
+00:16:53,140 --> 00:16:57,700
+تكون أصغر ما يمكن بنفس الخصائص أو نفس النتائج
+
+228
+00:16:57,700 --> 00:17:02,100
+التحليلية اللي تطلع فيها كل ال database الكبيرة هل
+
+229
+00:17:02,100 --> 00:17:05,400
+الكلام هذا متاح؟ أه متاح بعد ما أطبق المجموعة
+
+230
+00:17:05,400 --> 00:17:08,820
+العناصر التالية نبدأ مع ال data reduction و ال
+
+231
+00:17:08,820 --> 00:17:14,600
+feature selection احنا متفقينإنه ال data relevant
+
+232
+00:17:14,600 --> 00:17:18,480
+لل task سألنا نفسنا من البداية هل ال data هذه
+
+233
+00:17:18,480 --> 00:17:22,520
+relevant؟ مناسبة لل task؟ أه مناسبة .. مناسبة
+
+234
+00:17:22,520 --> 00:17:27,380
+تماما الان بدأ أبدأ أسأل نفسي هل ال feature هاي
+
+235
+00:17:27,380 --> 00:17:32,700
+relevant ولا irrelevant لل task مثلا كنا متفقين
+
+236
+00:17:32,700 --> 00:17:36,940
+سابقا إن ال ID و ال names مالهاش علاقة بأي شيء
+
+237
+00:17:36,940 --> 00:17:39,720
+فهذه ال attributes لو كانت موجودة شو بدي أسوي
+
+238
+00:17:39,720 --> 00:17:45,050
+فيها؟ بدي أشيلهاالان تخيل ان ال data 6 تبعتي
+
+239
+00:17:45,050 --> 00:17:48,310
+بتتكلم على تشخيص مرض معين positive or negative
+
+240
+00:17:48,310 --> 00:17:53,790
+تمام؟ و من ضمن ال attribute اسم ال physical اسم
+
+241
+00:17:53,790 --> 00:17:59,330
+الطبيب اللي قرر الحالة هاي او عمل التشخيص هذا هل
+
+242
+00:17:59,330 --> 00:18:03,790
+اسم الطبيب هذا الاسم مش اسم المريض اسم الطبيب ال
+
+243
+00:18:03,790 --> 00:18:07,510
+expert اللي قال فعليا ان الحالة هذه positive او
+
+244
+00:18:07,510 --> 00:18:11,710
+قال عنها negative هل اسم الطبيب بالزمن في ال
+
+245
+00:18:11,710 --> 00:18:17,650
+mining؟أكيد لأ irrelevant بدي أشيله واحد يقول لما
+
+246
+00:18:17,650 --> 00:18:20,530
+انت رجعتي يا دكتور لنفس المثال بالاسماء كل الأسماء
+
+247
+00:18:20,530 --> 00:18:25,030
+و ال IDs كلها بدنا نشيلها حتى أفق معاك تحصيل
+
+248
+00:18:25,030 --> 00:18:33,150
+الطالب في المدرسة اللي له علاقة براتب والده اه
+
+249
+00:18:33,150 --> 00:18:35,910
+شوف في الأول معظمنا قال لأ بس بعدين شوية صرنا نقول
+
+250
+00:18:35,910 --> 00:18:41,990
+قد يكون okay القد هذه قداش مقدارها لأ ممكن نحسبها
+
+251
+00:18:42,740 --> 00:18:45,280
+بناء على ال data set اللي عندي واحد بيقول خمسين
+
+252
+00:18:45,280 --> 00:18:49,000
+وهنا واحد بيقوله أقل أنا ممكن أحسبها و أقولك فعليا
+
+253
+00:18:49,000 --> 00:18:53,140
+تأثير ال attribute هذا بمقدار كذا على النتيجة لسه
+
+254
+00:18:53,140 --> 00:18:57,460
+دي بلاش لأن هذا احنا مختلفين في الموضوع هذا هل
+
+255
+00:18:57,460 --> 00:19:06,600
+تحصيل الطالب له علاقة بعمر والده؟ هتقولي طبعا؟ وين
+
+256
+00:19:06,600 --> 00:19:10,620
+هو اللي بيقوله انا صحيه هشوفه بسلأ طبعا لأ بس في
+
+257
+00:19:10,620 --> 00:19:17,340
+واحد قال اه صحيح بصبوط لأ اه يمكن ننزل من العلامة
+
+258
+00:19:17,340 --> 00:19:17,680
+يعنى
+
+259
+00:19:21,300 --> 00:19:26,040
+بس شوف انت مع كل واحدة صيرتي تقول إيش يمكن يمكن
+
+260
+00:19:26,040 --> 00:19:30,400
+لأنه فعليا الأقرب بالنسبة إلك لأ مالوش اللي علاقة
+
+261
+00:19:30,400 --> 00:19:33,720
+بسلوك والده في متابعته بغض النظر عن عمره كان شاب
+
+262
+00:19:33,720 --> 00:19:36,880
+صغير أو كهل ولا لأ إذا طول ما هو حامل العصاية فوق
+
+263
+00:19:36,880 --> 00:19:42,800
+راسه وبنجر على راسه أدرس أدرس بيدرس بتهيألك في ناس
+
+264
+00:19:42,800 --> 00:19:44,560
+بيظلوا موجودين أكتر من الشباب نعم
+
+265
+00:19:48,990 --> 00:19:52,730
+صار .. صار هذا إله .. إله تأثير بس أنا قاعد بتكلم
+
+266
+00:19:52,730 --> 00:19:56,390
+باطرح معاك إنه ممكن ألاقي attributes شكلها بيوحي
+
+267
+00:19:56,390 --> 00:20:02,030
+إنه ممكن يكون تمام؟ لكنه فعلياً مالوش علاقة تمام
+
+268
+00:20:02,030 --> 00:20:04,590
+دكتور جهدك للتصك باسم اللي إنت جاي تتكلم عنه؟
+
+269
+00:20:04,590 --> 00:20:07,270
+ماعليش قاعد بقولك الآن قاعد بتكلم التصك تبعت من
+
+270
+00:20:07,270 --> 00:20:11,530
+تحصيل الطالب في المدرسة وعمر والده الآن متوفر
+
+271
+00:20:11,530 --> 00:20:18,760
+attribute اسمه ال father age بتتوقع هيك ..by sins
+
+272
+00:20:18,760 --> 00:20:22,360
+هل father age مؤثر؟ أنا بقولك من واقع خطب برا؟ لأ
+
+273
+00:20:22,360 --> 00:20:26,880
+لأ، ليش؟ لأنه كمان مرة إلها علاقة بال attitude تبع
+
+274
+00:20:26,880 --> 00:20:31,680
+الأب إذا هو متابع، هو هتظل متابع لآخر نفس وإذا هو
+
+275
+00:20:31,680 --> 00:20:40,180
+مهم من البداية، هتظل نفس العنصر الآن وبالتالي،
+
+276
+00:20:40,180 --> 00:20:42,900
+أنا عشان أطلع من الجدل اللي مايمكن ومايمكنش وجدش
+
+277
+00:20:42,900 --> 00:20:47,190
+تأثيره أنا فيه عند بعض ال formal methodsبعض الطرق
+
+278
+00:20:47,190 --> 00:20:50,610
+الرسمية الـ Practical اللي ممكن أنا أستخدمها و أصل
+
+279
+00:20:50,610 --> 00:20:55,270
+لنتيجة طيب لما أنا بجلل عدد ال attributes جماعة
+
+280
+00:20:55,270 --> 00:21:00,510
+الخير واحد اتنين تلاتة اربع كانوا عشر attributes
+
+281
+00:21:00,510 --> 00:21:04,650
+محمد جدش عدد ال attributes عندك في ال data set 87
+
+282
+00:21:04,650 --> 00:21:09,710
+attribute جدش حجم ال data set اللي عندك انت ايوة
+
+283
+00:21:09,710 --> 00:21:19,260
+اه اه 13 attributeو اربع عشر روه؟ اربع عشر
+
+284
+00:21:19,260 --> 00:21:24,720
+attributes اه و ال rows؟ الان ال attributes هذه
+
+285
+00:21:24,720 --> 00:21:27,800
+ستة و تمانين او اربع عشر ممكن غيره يقولي عشرة و
+
+286
+00:21:27,800 --> 00:21:32,740
+الناس يقولي سبعة و واحد يقولي خمسة المهم احافظ ..
+
+287
+00:21:32,740 --> 00:21:38,920
+لأ .. احنا حكينا مائة مرة أجلش يبدأ خمس تلاف روه
+
+288
+00:21:38,920 --> 00:21:40,540
+بتعيده؟
+
+289
+00:21:44,740 --> 00:21:51,580
+لما ادوجها ان شاء الله برد عليك اه
+
+290
+00:21:51,580 --> 00:21:59,640
+انت بقى كتناسبها اه بقى دوارت
+
+291
+00:21:59,640 --> 00:22:05,700
+على الجليل مش ضرور يديك knowledge كويسة نشوف نشوف
+
+292
+00:22:05,700 --> 00:22:12,600
+ماشي ماشي طيب خلينا نرجع خلينا نرجع لمحاضرتناالهدف
+
+293
+00:22:12,600 --> 00:22:17,480
+من الـ Feature Selection إن أحتفظ فقط بالـ Most
+
+294
+00:22:17,480 --> 00:22:22,120
+Relevant Attributes بالـ Most Effective Attributes
+
+295
+00:22:22,120 --> 00:22:28,900
+والباقي بدي أخلص منه وهذا عشان يديني أزيد من كفاءة
+
+296
+00:22:28,900 --> 00:22:35,720
+الـ System تبعتي ولمّا أنا فعليًا أتكلم Feature
+
+297
+00:22:35,720 --> 00:22:39,080
+Selectionأو data reduction لما انا زي ما قلتلك
+
+298
+00:22:39,080 --> 00:22:42,360
+بحدث attribute يعني بحدث variable من المعادلة اللي
+
+299
+00:22:42,360 --> 00:22:45,620
+بدها تصير وبالتالي انا بقلل ال computation اللي
+
+300
+00:22:45,620 --> 00:22:50,760
+بدها تصير عندي لاحقا عادة يا جماعة الخير لو قلتلك
+
+301
+00:22:50,760 --> 00:22:57,720
+انا ما بعرف اي مجموعة هي اللي بتأثر اي مجموعة من
+
+302
+00:22:57,720 --> 00:23:01,260
+ال features هي صاحبة التأثير الاكبر لكن بدي اجرب
+
+303
+00:23:01,260 --> 00:23:05,500
+وهذا فعليا هذا اللي بصير try and measureهذا ال
+
+304
+00:23:05,500 --> 00:23:08,800
+concept موجود جدا في ال machine learning و مطبق و
+
+305
+00:23:08,800 --> 00:23:15,680
+effective بس مكلف الان لو انا اجيت و قلتلك عندي
+
+306
+00:23:15,680 --> 00:23:20,840
+three attributes ايش
+
+307
+00:23:20,840 --> 00:23:23,980
+هي ال data set او ايش هي ال subsets من ال
+
+308
+00:23:23,980 --> 00:23:27,690
+attributes هذه اللي ممكن اجرب عليهاعارفش يعني ايش
+
+309
+00:23:27,690 --> 00:23:32,750
+تجرب عليها؟ يعني تطبق ال mining task تبعتك على ال
+
+310
+00:23:32,750 --> 00:23:35,910
+attributes هي ممكن واحد ال label و كمان variable
+
+311
+00:23:35,910 --> 00:23:39,730
+one dependent او one independent و one dependent
+
+312
+00:23:39,730 --> 00:23:42,570
+variable هي ال target تبعتي الا لو كانت عندي three
+
+313
+00:23:42,570 --> 00:23:46,570
+classes اي three attributes عفوا اي واحد و اي
+
+314
+00:23:46,570 --> 00:23:52,370
+اتنين و اي تلاتة بالاضافة لل target هي ال data set
+
+315
+00:23:52,370 --> 00:23:57,710
+تبعتي مكونة من four attributesو أنا بدي أجرب الآن
+
+316
+00:23:57,710 --> 00:24:03,850
+أخد قرار مين الأكتر أهمية فيهم و بدي أجرب و أجيس
+
+317
+00:24:03,850 --> 00:24:08,290
+كل مرة كيف كان ال performance لأن ممكن أنا أشغل
+
+318
+00:24:08,290 --> 00:24:12,150
+على ال attribute الأول لحاله مع ال target و ال
+
+319
+00:24:12,150 --> 00:24:15,390
+attribute التاني مع ال target و ال attribute
+
+320
+00:24:15,390 --> 00:24:20,330
+التالت مع ال target بعدين الأول و التاني مع ال
+
+321
+00:24:20,330 --> 00:24:26,830
+target الأول و التالت مع ال targetالثاني والتالت
+
+322
+00:24:26,830 --> 00:24:32,690
+مع ال target و كلهم مع ال target عادة و عماله
+
+323
+00:24:32,690 --> 00:24:36,410
+بذكرنا هان بقول لي معناته ان انت عندك عدد احتمالات
+
+324
+00:24:36,410 --> 00:24:42,330
+اتنين اثنان اذا ترجع للرياضيات المنفصلة في ال
+
+325
+00:24:42,330 --> 00:24:48,520
+subset ال power set ال power set بتحتوي علىكل
+
+326
+00:24:48,520 --> 00:24:52,280
+المجموعات الجزئية من المجموعة A اللي هي عددهم 2
+
+327
+00:24:52,280 --> 00:24:55,620
+أُس ال cardinality للمجموعة A باستثناء طبعا ما
+
+328
+00:24:55,620 --> 00:24:59,620
+راحنا منهم واحد في فاحنا مش قضية اتنين أُس ان تمام
+
+329
+00:24:59,620 --> 00:25:07,480
+هذا العدد إذا أنا بدي أجرب كويس على خمسة على عشرة
+
+330
+00:25:07,480 --> 00:25:12,600
+الان انا اتنين أُس عشرة نتكلم عن ألف و أربع عشرين
+
+331
+00:25:12,600 --> 00:25:16,570
+محاولة عندهبدي أغير منهم واحدة ألف و تلات و عشر
+
+332
+00:25:16,570 --> 00:25:24,090
+محاولة بس مع سبعة و تمانين قضية و
+
+333
+00:25:24,090 --> 00:25:27,650
+أنا هريحت في العلمات ان شاء الله تعالى ولا يهمك مش
+
+334
+00:25:27,650 --> 00:25:32,850
+هخليك تتعب من حملهم بالمرة هشيل منهم جدر ما بقدر
+
+335
+00:25:32,850 --> 00:25:38,510
+الآن وبالتالي ال feature selection اللي هتصير عندي
+
+336
+00:25:38,510 --> 00:25:45,560
+الآن واحدة من تنتين supervised و unsupervisedلو
+
+337
+00:25:45,560 --> 00:25:54,700
+أنا جيت قلتلك ك test شو يعني supervised؟ يعني
+
+338
+00:25:54,700 --> 00:25:59,940
+ال human exist فيه supervision فيه إشراف وين
+
+339
+00:25:59,940 --> 00:26:04,920
+الإشراف تبعت ال human؟ لا مش في ال data collection
+
+340
+00:26:04,920 --> 00:26:10,480
+في ال test في ال target في تحديد ال target ممكن
+
+341
+00:26:10,480 --> 00:26:13,580
+الآن يكون ال selection تبعي لل features بناء على
+
+342
+00:26:14,450 --> 00:26:17,590
+علاقة الـ Feature بالـ Target وهدي بنسميها
+
+343
+00:26:17,590 --> 00:26:22,350
+Supervised يعني لما أنا فعليا بدي أقرر أتخلص من
+
+344
+00:26:22,350 --> 00:26:26,810
+Attribute أو أبقي بدي أفحص علاقة الـ Attribute هذا
+
+345
+00:26:26,810 --> 00:26:32,650
+بالـ Target وهدي بسميها Supervised بسميها
+
+346
+00:26:32,650 --> 00:26:38,330
+Supervised لما بأشتغل على أنه أنا بدي أقرر بين Two
+
+347
+00:26:38,330 --> 00:26:42,690
+Attributes جانب بعضهل هما dependent او redundant
+
+348
+00:26:42,690 --> 00:26:47,210
+attributes او لا هذي بسميها unsupervised مادخلتش
+
+349
+00:26:47,210 --> 00:26:54,170
+ال target في حسبتي الان بشكل عام .. بشكل عام الان
+
+350
+00:26:54,170 --> 00:26:57,510
+بدي اشيل ال redundant attributes او redundant
+
+351
+00:26:57,510 --> 00:27:02,130
+features redundant عند ال age و عند ال date of
+
+352
+00:27:02,130 --> 00:27:07,910
+birth و عند ال age category شو رايكوا في ال three
+
+353
+00:27:07,910 --> 00:27:12,690
+attributes هدول؟كلهم زي بعض بيحملوا نفس المعلومة
+
+354
+00:27:12,690 --> 00:27:19,990
+بس بصور مختلفة تماما مثل يقول في عند الراتب وعند
+
+355
+00:27:19,990 --> 00:27:25,630
+الراتب السنوي أو صاف الراتب وعند الراتب السنوي بما
+
+356
+00:27:25,630 --> 00:27:28,610
+كلهم بيحملوا نفس المعلومة هذه redundant attributes
+
+357
+00:27:28,610 --> 00:27:33,690
+فانت بدك تشيل اتنين من التلاتة هدول و تحتفظ بواحد
+
+358
+00:27:33,690 --> 00:27:36,890
+فقط اللي بتناسب مع ال task تبعتك
+
+359
+00:27:40,720 --> 00:27:44,200
+بدك تبقى ترجع للخلف خطوطين وتعمل data cleaning
+
+360
+00:27:44,200 --> 00:27:48,660
+عشان تعالج ال consistency احنا خلصنا انا خلصت من
+
+361
+00:27:48,660 --> 00:27:52,300
+ال missing عملت لها handling عبيتها خلصت ال noise
+
+362
+00:27:52,300 --> 00:27:56,840
+data وحليت ال inconsistency اللي موجودة فالان
+
+363
+00:27:56,840 --> 00:28:00,720
+انتقلت في مرحلة ال data selection تمام يا مؤمن
+
+364
+00:28:00,720 --> 00:28:03,560
+ففعليا انا يا شباب انا خلصت المرحلة اللي لها كل
+
+365
+00:28:03,560 --> 00:28:07,320
+علاقة بال preparation الشيء الثاني زي ما قلنا بدنا
+
+366
+00:28:07,320 --> 00:28:10,730
+نشيل ال irrelevant attributesأي attribute
+
+367
+00:28:10,730 --> 00:28:16,210
+irrelevant تمام؟ irrelevant attribute بدي أخلص منه
+
+368
+00:28:16,210 --> 00:28:22,730
+في
+
+369
+00:28:22,730 --> 00:28:26,510
+شغل مهم جدا لأول مرة هنقولها ان انا بدي احذف ال
+
+370
+00:28:26,510 --> 00:28:30,830
+attribute اللي مش فيها قيم مختلفة او فيها تغيير
+
+371
+00:28:30,830 --> 00:28:38,630
+بسيط في الاختلاف يعني كان في عندنا ملف صحي بيتكلم
+
+372
+00:28:38,630 --> 00:28:46,800
+عنالنساء الحوامل اه احسن بدي اتنبأ بوزن المولود
+
+373
+00:28:46,800 --> 00:28:53,880
+لما ينولد و لاجئت فيه attribute اسمه ال gender ليش
+
+374
+00:28:53,880 --> 00:28:59,320
+انشال يا كريم بالعجل بالعجل انشال ليش انشال بالعجل
+
+375
+00:28:59,320 --> 00:29:04,880
+لأن كل الحوامل female وبالتالي انا مافيش داعي ال
+
+376
+00:29:04,880 --> 00:29:06,060
+attribute هذي يظل موجود
+
+377
+00:29:08,960 --> 00:29:12,060
+لأ لأ بتكلمش .. بتكلم على الأم .. عن الأم .. جنس
+
+378
+00:29:12,060 --> 00:29:16,080
+الأم .. بتكلم .. أنا بدي أتنبأ بوزن المولود أو بدي
+
+379
+00:29:16,080 --> 00:29:20,440
+أعمل regression لوزن المولود تمام؟ الآن و راجعت
+
+380
+00:29:20,440 --> 00:29:22,860
+البيانات .. من بيانات الأم موجود عند ال gender
+
+381
+00:29:22,860 --> 00:29:28,160
+مابيلزمش .. الآن واحد يقوللي هذا ال attribute مهم؟
+
+382
+00:29:28,160 --> 00:29:31,800
+لأ مش مهم ليش؟ لأن كل ال attributes أو .. عفوا ..
+
+383
+00:29:31,800 --> 00:29:36,320
+كل ال rows بتتشارك نفس ال value وبالتالي هذا
+
+384
+00:29:36,320 --> 00:29:40,880
+uselessتضحكوا، ماشي الحال، الله يهنيكم يا رب زي
+
+385
+00:29:40,880 --> 00:29:46,120
+العمر في مثال المدرسة،
+
+386
+00:29:46,120 --> 00:29:50,360
+شكرا لك يا أحمد الآن، العمر في مثال المدرسة،
+
+387
+00:29:50,360 --> 00:29:52,680
+الابتدائي، المرحلة الابتدائية، كلهم لورد في نفس ال
+
+388
+00:29:52,680 --> 00:29:56,600
+range إلا إذا كان ما أنا بدي فعليًا أنا معنى أشوف
+
+389
+00:29:56,600 --> 00:30:05,240
+تأثيره العمر أو فرق السنين على تحصيله عملية
+
+390
+00:30:05,240 --> 00:30:09,160
+الفحصأو مشاهد او شوف مين ال attributes الأحسن و
+
+391
+00:30:09,160 --> 00:30:15,900
+كذا مكلف أكتر الحل الان وبالتالي موضوع ان انا اجرب
+
+392
+00:30:15,900 --> 00:30:21,080
+ال subset اللي موجود عندى زى ما قلنا hosted مكلفة
+
+393
+00:30:21,080 --> 00:30:24,900
+مرحيقة وبالتالي انا هتجنبها و هشوف بعض ال methods
+
+394
+00:30:24,900 --> 00:30:28,780
+اللى بتساعدني فيه استكشف مين هي ال attributes
+
+395
+00:30:28,780 --> 00:30:34,880
+المهمة بأقل تكلفة الان هذه اللى اتكلمنا عليها
+
+396
+00:30:34,880 --> 00:30:39,940
+الخطوة الأولىTry and measure ايش يعني خد ال data
+
+397
+00:30:39,940 --> 00:30:43,820
+set كلها و ابني عليها ال mining task تبعتك و شوف
+
+398
+00:30:43,820 --> 00:30:48,280
+ال result تمام ال result كانت 80% خلصت من ال
+
+399
+00:30:48,280 --> 00:30:51,020
+attribute الأخير و بدأت أبدا أخلص منهم واحد ورا
+
+400
+00:30:51,020 --> 00:30:55,580
+التاني و جربت دلت النتيجة مثل ما هي معاتو ال
+
+401
+00:30:55,580 --> 00:30:59,460
+attribute الأخير هذا uses عارف انا بتكلم معاك كيف
+
+402
+00:30:59,460 --> 00:31:03,000
+ان ال description تبعت ال data set مش موجودهو
+
+403
+00:31:03,000 --> 00:31:07,400
+أسماء ال attributes مافيش فيها معنى meaningless
+
+404
+00:31:07,400 --> 00:31:11,080
+كتب لي A1, A2, A3, A4, A5 هاي أسماء ال attributes
+
+405
+00:31:11,080 --> 00:31:14,060
+أو feature 1, feature 2, feature 3 فصرت أنا مش
+
+406
+00:31:14,060 --> 00:31:19,820
+عارف شو كنه ال attribute هذاعن إيش بتكلم؟ ماعنديش
+
+407
+00:31:19,820 --> 00:31:23,760
+لكن أنا واثق شويه يا كريم أنا واثق بمصدر البيانات
+
+408
+00:31:23,760 --> 00:31:28,700
+أخدتها من شخص خبير في المجال وال data موثوقة لكن
+
+409
+00:31:28,700 --> 00:31:31,900
+مدانيش الأوصاف هذه كيف ممكن أشتغل؟ مافيش قدام اللي
+
+410
+00:31:31,900 --> 00:31:35,760
+قارر try and test okay هي الفكرة وين يا كريم؟ انه
+
+411
+00:31:35,760 --> 00:31:38,980
+انا فعليا كريم بيقول انا استخلصت ال knowledge
+
+412
+00:31:38,980 --> 00:31:44,300
+وخلصت صحيح وصلت ل rule لكن ال rule اللي انبنى
+
+413
+00:31:44,300 --> 00:31:52,100
+بيعتمد على86 attributes يعني لما انا بده اروح اعمل
+
+414
+00:31:52,100 --> 00:31:57,620
+test او افحص او اقولك اعمل estimation تمام انت
+
+415
+00:31:57,620 --> 00:32:02,240
+مجبر توفرلي الـ 86 value تمثل ال attributes هاي
+
+416
+00:32:02,240 --> 00:32:07,700
+دول يعني انا هدفي استخراج knowledge نعم لكن الأهم
+
+417
+00:32:07,700 --> 00:32:10,400
+منها من ال knowledge ذاتها ال role اللي انا
+
+418
+00:32:10,400 --> 00:32:14,640
+هستخدمه لاحقاالرول اللي مبني على three أو four
+
+419
+00:32:14,640 --> 00:32:21,420
+attributes أو عشرة في ال execution أسرع من ال 86
+
+420
+00:32:21,420 --> 00:32:25,360
+عشان هيك أنا بحاول أقللهم مش بس لمرحلة ال mining
+
+421
+00:32:25,360 --> 00:32:28,540
+لأنه فعلا أنا حصلت على لكن أنا في الآخر هذا ال
+
+422
+00:32:28,540 --> 00:32:31,580
+mining بده ينحق في application ال rule بده ينحق في
+
+423
+00:32:31,580 --> 00:32:34,600
+application على mobile جداش حجم ال computation
+
+424
+00:32:34,600 --> 00:32:38,620
+اللي بيحصل لأ هذه لازم يعملها reduction وبحث الشيء
+
+425
+00:32:38,620 --> 00:32:39,040
+آخر مهم
+
+426
+00:32:58,730 --> 00:33:04,890
+لما تصير ال data set بين إيديك وتفهمها كويس بتصير
+
+427
+00:33:04,890 --> 00:33:07,290
+أنت صاحب القرار هذا ال attribute relevant ولا
+
+428
+00:33:07,290 --> 00:33:11,400
+irrelevantبيفرج و لا بيأثر و لا بيأثرش بقاشر بيفرج
+
+429
+00:33:11,400 --> 00:33:14,240
+عن ال attribute التاني وبناء عليه ممكن ان انت بعد
+
+430
+00:33:14,240 --> 00:33:19,180
+مجموعة من التفكير بعد فترة من التفكير و بعض
+
+431
+00:33:19,180 --> 00:33:21,980
+الحسابات احيانا زي ما هنشوف الآن تاخد decision هذا
+
+432
+00:33:21,980 --> 00:33:24,500
+ال attribute و serious this فبدي احدفه تبع ال
+
+433
+00:33:24,500 --> 00:33:29,700
+feather تمام؟ كمان مرة يا شباب انا برجع و بأكد ان
+
+434
+00:33:29,700 --> 00:33:32,140
+انا ال feature selection بس مش ال knowledge mining
+
+435
+00:33:32,140 --> 00:33:35,940
+ال extraction لأ في خطوة لسه بعدها موضوع ال
+
+436
+00:33:35,940 --> 00:33:40,200
+deploymentللـ role هذه أو للـ knowledge هذه هو أنا
+
+437
+00:33:40,200 --> 00:33:46,500
+لان اللي بده يتنبأ بالاتفاع السهم مش برنامج بدي
+
+438
+00:33:46,500 --> 00:33:51,380
+يقرأ حالة السوق ويقول لي لان مش هيستنقل .. كل مكان
+
+439
+00:33:51,380 --> 00:33:54,680
+ال attributes أو ال variables اللي أنا باعتمد
+
+440
+00:33:54,680 --> 00:33:59,920
+عليها في ال prediction أقل بيكون أفضل لأن هذا ..
+
+441
+00:33:59,920 --> 00:34:04,260
+تخيل أنت في الـ real-time systems كل ال attributes
+
+442
+00:34:04,260 --> 00:34:08,860
+بصير بيفرج معاه في ال computationفالان الطريقة
+
+443
+00:34:08,860 --> 00:34:11,840
+الأولى زى ما قلنا try and measure انا باخد كل ال
+
+444
+00:34:11,840 --> 00:34:20,420
+data set او عفوا اما forward او backward الفرق بين
+
+445
+00:34:20,420 --> 00:34:25,500
+التنتين انه بال forward ببدأ مع single attribute و
+
+446
+00:34:25,500 --> 00:34:28,180
+ببدأ اضيف التاني و التالت و الرابع و كده و ال
+
+447
+00:34:28,180 --> 00:34:32,540
+attribute اللى مابأثرش فى ال result النهائى او
+
+448
+00:34:32,540 --> 00:34:38,590
+تأثيره قليل بقى شيلهبقى أشيله من اللي بعدين بينما
+
+449
+00:34:38,590 --> 00:34:43,470
+الـ Backward بقى أبدأ معاهم كلهم و ببدأ أغيرهم
+
+450
+00:34:43,470 --> 00:34:46,730
+واحد ورا التاني و الـ Attribute اللي بقى أحس أنه
+
+451
+00:34:46,730 --> 00:34:49,770
+الـ Accuracy أو ال .. ال .. ال performance تبع ال
+
+452
+00:34:49,770 --> 00:34:53,250
+knowledge rule تبع تهاني Down صارت ال accuracy
+
+453
+00:34:53,250 --> 00:34:58,010
+نزلت لتحت بقى خليه و بشوف بحدث اللي بعده و هكذا
+
+454
+00:34:58,010 --> 00:35:02,430
+بعض الناس بتروح بتطبق Machine Learning Algorithm
+
+455
+00:35:02,430 --> 00:35:09,230
+على ال data setفبروح ببني decision tree ال data
+
+456
+00:35:09,230 --> 00:35:13,530
+set مكونة من six attributes عشان توصلنا لل class
+
+457
+00:35:13,530 --> 00:35:18,270
+ال decision tree لما بناها لجأ ان ال rules بعت ال
+
+458
+00:35:18,270 --> 00:35:22,850
+decision tree فقط معتمد على three attributes a1 و
+
+459
+00:35:22,850 --> 00:35:33,290
+a4 و a6 هذا يعني ان a2 و a3 و a5 are uselessفرح
+
+460
+00:35:33,290 --> 00:35:36,130
+هدفهم يقولك خلاص أنا بقدر أبني النظام تبع عالمين
+
+461
+00:35:36,130 --> 00:35:42,970
+على ال data set اللي موجود عندها الان
+
+462
+00:35:42,970 --> 00:35:48,750
+ال data set هيها اه بتتكون من six attributes فلما
+
+463
+00:35:48,750 --> 00:35:50,810
+احنا أخدنا ال six attributes هدول بنينا عليهم
+
+464
+00:35:50,810 --> 00:35:54,170
+decision tree ال decision tree عامالها واضحة جداني
+
+465
+00:35:54,170 --> 00:35:58,330
+لما رسمتها بتكون من ايش فقط من ال three attributes
+
+466
+00:35:58,330 --> 00:36:07,350
+A1 و A4و A6 و لسه بيقولي A4 هو الأكتر أهمية ورا
+
+467
+00:36:07,350 --> 00:36:13,050
+بيجي A1 و A6 بنفس المنزلة في ناحية أهمية يعني انه
+
+468
+00:36:13,050 --> 00:36:17,950
+2 و 3 و 5 مالهمش معنى مالهمش لازمة فإيش بروح أنا
+
+469
+00:36:17,950 --> 00:36:21,250
+بحذفهم و ببني نظامي من جديد فقط على ال three
+
+470
+00:36:21,250 --> 00:36:25,870
+attributes الموجودة اه اه اه هنشوفه مع بعض ان شاء
+
+471
+00:36:25,870 --> 00:36:30,050
+الله لاحقا طيب الآن
+
+472
+00:36:32,550 --> 00:36:37,790
+بما انه مبدأ انه والله انا اطبق وجرب على كلهم مزعج
+
+473
+00:36:37,790 --> 00:36:40,650
+خصوصا في ناس حيصير في عندها ألف و أربع عشر محاولة
+
+474
+00:36:40,650 --> 00:36:44,170
+و ناس الله يعينهم مش عارف جديش اتنين أسمية تقريبا،
+
+475
+00:36:44,170 --> 00:36:49,150
+مصبوط؟ فالكلام حيصير in sense فهو مش منطقي، الآن
+
+476
+00:36:49,150 --> 00:36:54,550
+في بعض ال correlation algorithms بتفحص العلاقة ما
+
+477
+00:36:54,550 --> 00:36:58,470
+بين ال attributes سواء كانت العلاقة بين ال
+
+478
+00:36:58,470 --> 00:37:01,830
+attribute و ال label عشان يقولي والله جديش هذا
+
+479
+00:37:01,830 --> 00:37:06,620
+effectأو جدّاش correlated أو بين ال attributes
+
+480
+00:37:06,620 --> 00:37:11,960
+نفسها عشان يتكلم من ناحية redundancy الانش إبعاد
+
+481
+00:37:11,960 --> 00:37:15,700
+الخير في موضوع ال correlation عادة كل ما كان ال
+
+482
+00:37:15,700 --> 00:37:19,340
+value ناتج التحصيل تبع ال correlation analysis
+
+483
+00:37:19,340 --> 00:37:23,760
+عالية أو قريبة من الواحد ان هدول ال two attributes
+
+484
+00:37:23,760 --> 00:37:28,240
+هدوله mostly dependent بيعتمدوا على بعض وممكن
+
+485
+00:37:28,240 --> 00:37:32,590
+يكونوا completely duplicatedطب في الحالة هذه بدي
+
+486
+00:37:32,590 --> 00:37:37,490
+أخلص من واحد منهم كل ما كانت القيمة قريبة للصفر
+
+487
+00:37:37,490 --> 00:37:41,950
+بقول ان ال two attributes هدول independent مافيش
+
+488
+00:37:41,950 --> 00:37:45,910
+بينهم علاقة وبالتالي أنا مضطر أبقي اتنين يعني
+
+489
+00:37:45,910 --> 00:37:49,550
+فعليا انا المطلوب مني الآن وحده هنشوفه كمان شوية
+
+490
+00:37:49,550 --> 00:37:53,790
+لأنه في أول واجب جاينا الآن هنشوفه فعليا مطلوب مني
+
+491
+00:37:53,790 --> 00:37:57,250
+من مجموعة ال features هدول أعمل دراسة بال
+
+492
+00:37:57,250 --> 00:38:01,770
+coefficient عشان أحددمقاش الـ dependency اللي
+
+493
+00:38:01,770 --> 00:38:05,190
+موجودة من ال .. من ال attributes أو عفوا من ال
+
+494
+00:38:05,190 --> 00:38:09,010
+algorithm المستخدم عند ال person وهي بيستخدمها لما
+
+495
+00:38:09,010 --> 00:38:12,450
+يكون في عند ال numerical attributes وفي عند ال chi
+
+496
+00:38:12,450 --> 00:38:15,110
+-square لما تكون ال attributes عبارة عن nominal
+
+497
+00:38:15,110 --> 00:38:19,350
+attributes وفي عند ال spearman و ال kindle تاو
+
+498
+00:38:19,350 --> 00:38:21,790
+برضه مجموعة .. في مجموعة كتير من ال algorithms
+
+499
+00:38:21,790 --> 00:38:26,410
+ممكن تطبق خلينا احنا نتكلم على ال person و ال chi
+
+500
+00:38:26,410 --> 00:38:30,830
+-square كونوا واحدة لل numerical واحدةللـ nominal
+
+501
+00:38:30,830 --> 00:38:34,370
+في
+
+502
+00:38:34,370 --> 00:38:36,810
+ال person coefficient انا فيه عندي two attributes
+
+503
+00:38:36,810 --> 00:38:46,290
+الان a1 و a2 a1
+
+504
+00:38:46,290 --> 00:38:51,470
+و a2 numeric
+
+505
+00:38:51,470 --> 00:38:55,830
+attributes لها ال description مديني اجيبوا لي ايش
+
+506
+00:38:55,830 --> 00:39:00,070
+العلاقة اللي بينهمولا الأسماء جادر من خلالها أحدد
+
+507
+00:39:00,070 --> 00:39:03,930
+ايش اللي موجود او شو علاقة ال two attributes مع
+
+508
+00:39:03,930 --> 00:39:08,410
+بعضهم والتنين بما انه التنين ال numeric فبقدر اطبق
+
+509
+00:39:08,410 --> 00:39:12,770
+بينهمين ال Pearson correlation ايش ال Pearson
+
+510
+00:39:12,770 --> 00:39:17,830
+بقول؟ بقول كتالي القانون تبعتنا هي عبارة عن مجموع
+
+511
+00:39:17,830 --> 00:39:23,250
+حاصل ضرب الفروقات كل value في ال attribute ناقص
+
+512
+00:39:23,250 --> 00:39:27,070
+المتوسط الحسابي تبعته يعني
+
+513
+00:39:28,590 --> 00:39:33,650
+لو كان هذا واحد .. اتنين .. تلاتة .. وهنا مثلا
+
+514
+00:39:33,650 --> 00:39:42,270
+سبعة .. خمسة .. تلات عشر او عشرة المتوسط الحساب
+
+515
+00:39:42,270 --> 00:39:46,830
+hand gradation يا معظم الخير الـ Mu للـ A لـ A
+
+516
+00:39:46,830 --> 00:39:54,270
+واحد ستة على ثلاثة .. ثلاثة .. اتنين والميوهان
+
+517
+00:39:55,400 --> 00:40:00,560
+متوسط الحسابي 7.7257
+
+518
+00:40:00,560 --> 00:40:15,380
+.512 و 10.22 22 على 3 7.380 33 من 100 مصبوط الآن
+
+519
+00:40:15,380 --> 00:40:20,640
+عشان انا احسب طب الحراف المعياري او ال variance
+
+520
+00:40:20,640 --> 00:40:22,500
+ايش قانون ال variance
+
+521
+00:40:26,440 --> 00:40:32,460
+الـ Standard Deviation سيجما
+
+522
+00:40:32,460 --> 00:40:35,460
+.. أيوة الجدر يساوي الجدر التربيعي لـ summation
+
+523
+00:40:35,460 --> 00:40:42,640
+الـ xi نقص ميو تربيع على عددهم تحت الجدر برجع بأكد
+
+524
+00:40:42,640 --> 00:40:45,980
+عليك القوانين هاي كلها للحفظ يا شباب و هذا زيهم
+
+525
+00:40:45,980 --> 00:40:51,920
+أكيد و هذا .. هذا الدرباك المعادلة مكتوبة بشكلين
+
+526
+00:40:51,920 --> 00:40:59,090
+هي .. فانت احفظ هذه أو هذه الأسهل إلكلأ لأ مش كتير
+
+527
+00:40:59,090 --> 00:41:05,350
+يا مؤمن مش كتير يا مؤمن الان فهذه المعلومات بدي
+
+528
+00:41:05,350 --> 00:41:10,230
+احسبها عن ال attributes اللي موجودة عندى وبالتالي
+
+529
+00:41:10,230 --> 00:41:15,770
+بصير و بقوله واحد ناقص اتنين مضروبة في سبعة ناقص
+
+530
+00:41:15,770 --> 00:41:23,350
+سبعة point تلاتة زائد اتنين ناقص اتنين مضروبة في
+
+531
+00:41:23,350 --> 00:41:30,460
+خمسة ناقص سبعة تلاتةزائد تلاتة ناقص اتنين مضروبة
+
+532
+00:41:30,460 --> 00:41:35,020
+في عشرة ناقص سبعة point تلاتة هذا المجموع على
+
+533
+00:41:35,020 --> 00:41:40,060
+عددهم تلاتة في الانحراف المعياري ال variance لل
+
+534
+00:41:40,060 --> 00:41:43,480
+attribute الأول وال variance لل attribute التاني
+
+535
+00:41:43,480 --> 00:41:50,680
+تمام الآن ال
+
+536
+00:41:50,680 --> 00:41:57,220
+value اللي هتطلعهتطلع من سالب واحد أكبر أو تساوي
+
+537
+00:41:57,220 --> 00:42:05,200
+سالب واحد وأقل أو تساوي موجة بواحد صفر يعني
+
+538
+00:42:05,200 --> 00:42:09,040
+independent attributes مافيش بينهم علاقة إشارة
+
+539
+00:42:09,040 --> 00:42:13,740
+سالبة يعني العلاقة عكسية في علاقة بس عكسية الإشارة
+
+540
+00:42:13,740 --> 00:42:17,960
+موجة بقى في علاقة لكن علاقة طردية بين الأرقام اللي
+
+541
+00:42:17,960 --> 00:42:18,700
+موجودة
+
+542
+00:42:23,010 --> 00:42:26,390
+وين؟ للتنين، علاقة التنين مع بعض وإذا كان التنين
+
+543
+00:42:26,390 --> 00:42:29,890
+بيختلفوا في ال .. في إيش؟ في ال rows بيختلفوا ..
+
+544
+00:42:29,890 --> 00:42:32,810
+two attributes بيختلفوا .. بيختلفوا ببعدد ال rows؟
+
+545
+00:42:32,810 --> 00:42:35,370
+كيف هذا الكلام بده يصير؟ مش التنين موجودين في نفس
+
+546
+00:42:35,370 --> 00:42:40,430
+ال data set؟ طيب، وخلصت أنا مرحلة ال data
+
+547
+00:42:40,430 --> 00:42:46,750
+preparation، عبيت المسن الآن positive correlation
+
+548
+00:42:46,750 --> 00:42:50,370
+يعني
+
+549
+00:42:50,370 --> 00:42:55,690
+التنينالـ value أكبر من صفر يعني التنين dependent
+
+550
+00:42:55,690 --> 00:42:59,610
+أو في علاقة .. في علاقة قوية ما بينهم وبالتالي
+
+551
+00:42:59,610 --> 00:43:05,970
+بقدر أستغني عن واحد فيهم وكذلك لو كانت القيمة
+
+552
+00:43:05,970 --> 00:43:10,450
+قريبة للسالب واحد في علاقة لكن علاقة عكسية
+
+553
+00:43:10,450 --> 00:43:15,050
+وبالتالي بقدر أستغني عن واحد منهم بإيش أنا ..
+
+554
+00:43:15,050 --> 00:43:17,690
+الصفر هو ال perfect يعني ال two attributes هدولة
+
+555
+00:43:17,690 --> 00:43:21,710
+لازم يظلوابس مش دائما حدّيني صفر ولا حدّيني واحد
+
+556
+00:43:21,710 --> 00:43:26,010
+ولا حدّيني سلب واحد فحدّيني قيم في ال range هذا
+
+557
+00:43:26,010 --> 00:43:32,850
+قيم حقيقية يعني سالب خمسة من عشرة في
+
+558
+00:43:32,850 --> 00:43:39,250
+علاقة عكسية في خمسين في المية فانت بتاخد قرار بناء
+
+559
+00:43:39,250 --> 00:43:43,770
+على إيش بدي أقيها مثلا بتقول كل ال relation أو كل
+
+560
+00:43:43,770 --> 00:43:49,860
+coefficient relation اللي بتكون فوقالـ 70% هي اللي
+
+561
+00:43:49,860 --> 00:43:54,420
+بده احذفها مدون ذلك بده احتفظ فيها فهذا بيظل عندك
+
+562
+00:43:54,420 --> 00:44:00,940
+كارول انت بده تطبقه بس بتأثر في الجودة اللي هي ..
+
+563
+00:44:00,940 --> 00:44:05,640
+اذا اختارت 50 او 70 او .. اكيد انت شوف ان الاصل
+
+564
+00:44:05,640 --> 00:44:10,560
+انا بده اخلص من ال dependent attribute ال full
+
+565
+00:44:10,560 --> 00:44:13,880
+dependent اللي بين جثينه هي عبارة عن ال redundant
+
+566
+00:44:13,880 --> 00:44:18,660
+dataلأنه مسموح لعمل Transformation، مصبوط؟ يعني
+
+567
+00:44:18,660 --> 00:44:21,840
+الأصل أنه لما يكون Attribute A و Attribute B لما
+
+568
+00:44:21,840 --> 00:44:25,280
+يكون في بينهم Linear Equation بقدر أرجح الـ A للـ
+
+569
+00:44:25,280 --> 00:44:30,160
+B أو أودّي الـ A للـ B، مصبوط؟ والعكس صحيح، الآن
+
+570
+00:44:30,160 --> 00:44:34,440
+واحد من التانيه دول لازم ينشل، بس هل كل ال data
+
+571
+00:44:34,440 --> 00:44:37,660
+اللي عندي هاي بتمثل ال relation هذه؟ إذا كل ال
+
+572
+00:44:37,660 --> 00:44:40,780
+data بتمثل ال relation هذه أنا بقولك لازم تشيله،
+
+573
+00:44:40,780 --> 00:44:46,960
+استخدامه useless، لكن والله الارتباط 80%في اما اخد
+
+574
+00:44:46,960 --> 00:44:50,160
+قرار اما اضحى مابديش ال knowledge اللى بتتيجى من
+
+575
+00:44:50,160 --> 00:44:53,540
+ورا ال 80% هاي لان ال correlation عالية او فعليا
+
+576
+00:44:53,540 --> 00:44:56,100
+بدي ابقي و اتحمل التابعات عشان ال knowledge
+
+577
+00:44:56,100 --> 00:45:02,900
+تأثيرها الله وعلا ماقدش يكون هذا الجدول في three
+
+578
+00:45:02,900 --> 00:45:17,200
+attributes 1 3 4 5 6 4 6 6 8 9 C 5 5 10 1 8هدولة
+
+579
+00:45:17,200 --> 00:45:24,640
+two attributes بي تساوي a زائد تلاتة linear
+
+580
+00:45:24,640 --> 00:45:29,800
+transformation عملت ومش بس هيك روحت اندهان غيرت
+
+581
+00:45:29,800 --> 00:45:34,340
+واحد وهذا
+
+582
+00:45:34,340 --> 00:45:41,660
+الاتسي عملتله generate randomly من واحد لعشرة حسبت
+
+583
+00:45:41,660 --> 00:45:46,050
+المتوسط الحسابي لكل واحد فيهمحسبت الانحراف
+
+584
+00:45:46,050 --> 00:45:49,310
+المعياري لكل واحد فيهم من هنا على المعادلة اللي
+
+585
+00:45:49,310 --> 00:45:54,850
+شفناها قبل شوية ضل اطبق main في المعادلة السابقة
+
+586
+00:45:54,850 --> 00:46:02,370
+او روحت حسب المعادلة اللي عندي هان a في b اه بقى
+
+587
+00:46:02,370 --> 00:46:08,930
+انك تحفظها انا قاعد بقولك حفظها سهل جدا واحد
+
+588
+00:46:08,930 --> 00:46:13,830
+ناقص المتوسط الحسابي زائد
+
+589
+00:46:15,210 --> 00:46:20,330
+مضروبة ع الفان مضروبة في اربع نقص المتوسط الحسابي
+
+590
+00:46:20,330 --> 00:46:23,550
+6
+
+591
+00:46:23,550 --> 00:46:28,670
+.6 زائد و بدك تكررها مع كل ال values اللي موجود
+
+592
+00:46:28,670 --> 00:46:32,510
+عندك البرمجة طبعا بتريحني في موضوع ال function زي
+
+593
+00:46:32,510 --> 00:46:38,950
+هيك ولا لأ؟ لكن لاحظ انت الفرق او المتوسط الحسابي
+
+594
+00:46:38,950 --> 00:46:42,310
+جديش بيفرج لكن عند ال variance
+
+595
+00:46:45,820 --> 00:46:50,120
+متقريبا متساوي و الفرق اللي صار انه لو ضلت هذه
+
+596
+00:46:50,120 --> 00:46:57,000
+سبعة كان نفسها و هذه إشارة ممكن تديني لو أنا بدي
+
+597
+00:46:57,000 --> 00:47:00,360
+أعمل برنامج من بدري أقول ال attribute اللي بتديني
+
+598
+00:47:00,360 --> 00:47:06,580
+نفس ال variance بديش إياها بس بظل في عندي حالة ان
+
+599
+00:47:06,580 --> 00:47:09,420
+بعض الأحيان ال values اختلاف ال values فعلا جاي
+
+600
+00:47:09,420 --> 00:47:13,650
+random مش جاي ضمن ال linear equationفمش دايما ال
+
+601
+00:47:13,650 --> 00:47:17,490
+variance لوحده كافي ان انا احكم على ال dependency
+
+602
+00:47:17,490 --> 00:47:21,710
+بين ال two attributes بالمجمل روحنا حسبنا ال
+
+603
+00:47:21,710 --> 00:47:24,710
+Pearson correlation coefficient او coefficient
+
+604
+00:47:24,710 --> 00:47:33,510
+correlation بين a و b كان point 779 يعني 78 من 100
+
+605
+00:47:33,510 --> 00:47:41,730
+و ال dependency تبعت ال a و ال c point 085 شو
+
+606
+00:47:41,730 --> 00:47:42,150
+يعني؟
+
+607
+00:47:45,000 --> 00:47:52,200
+يعني أنا الآن إني الخيار أشيل واحد A أو B والـ C
+
+608
+00:47:52,200 --> 00:47:56,480
+لازم يظل ليش
+
+609
+00:47:56,480 --> 00:48:01,620
+الـ C لازم يظل؟ قريبة من الصفر القيمة، مصبوط؟
+
+610
+00:48:01,620 --> 00:48:05,220
+قريبة من الصفر، كل ما كانت القيمة قريبة للصفر فهذا
+
+611
+00:48:05,220 --> 00:48:08,800
+ال attribute يعد independent مستقل، مالوش علاقة
+
+612
+00:48:08,800 --> 00:48:11,800
+بال attribute اللي في جنبه وكل ما كبرت ال value
+
+613
+00:48:11,800 --> 00:48:15,640
+باتجاه الواحدمعنى تفيدي من دنسة عالية ما بين ال
+
+614
+00:48:15,640 --> 00:48:20,420
+two attributes وبالتالي لازم أخلص بواحد منهم تمام
+
+615
+00:48:20,420 --> 00:48:28,940
+يا شباب؟ هذا ال python code بسيط عملته الصبح مع
+
+616
+00:48:28,940 --> 00:48:31,940
+المثال عشان اورديك كيف ممكن انا بدي استدعي ال
+
+617
+00:48:31,940 --> 00:48:34,080
+correlation انا مش حابن ال function ال function
+
+618
+00:48:34,080 --> 00:48:40,080
+موجودة بس استخدم ال
+
+619
+00:48:40,080 --> 00:48:44,310
+attributes هاي ال data set تبعتي ال iris قرأتهاو
+
+620
+00:48:44,310 --> 00:48:46,450
+هاي ال data قلتله ال correlation واحد ال data
+
+621
+00:48:46,450 --> 00:48:50,690
+frame ال data اسم ال attribute ضغط ال correlation
+
+622
+00:48:50,690 --> 00:48:54,450
+مع ال attribute التاني فبتداني القيمة مع مو اذا
+
+623
+00:48:54,450 --> 00:48:58,610
+انا بطبق by default و بطبق ال person لانه numeric
+
+624
+00:48:58,610 --> 00:49:03,130
+اذا انا بطبق مثلا ال sparse، sparse man فاروح
+
+625
+00:49:03,130 --> 00:49:06,730
+اقوله هنا ال method equal عشان يديني الممكنية نغير
+
+626
+00:49:06,730 --> 00:49:10,830
+ال coefficient measurement او metric اللي انا بدي
+
+627
+00:49:10,830 --> 00:49:16,220
+استخدمهاالان هذا علاقة بين two attributes انت عندك
+
+628
+00:49:16,220 --> 00:49:20,440
+81 او 86 attributes او 14 attributes بدك تفكر كيف
+
+629
+00:49:20,440 --> 00:49:24,460
+ممكن انا اشتغل او اظبط ال code تبعي بحيث انه يشتغل
+
+630
+00:49:24,460 --> 00:49:33,340
+قائمة يقولي هاي هدولة ضعيف و هدولة القوية اكيد
+
+631
+00:49:33,340 --> 00:49:38,900
+لانه اتنين اتنين التاني مع كل اللي بعده مع كل اللي
+
+632
+00:49:38,900 --> 00:49:43,650
+بعدهو بناء على هيك .. بناء على هيك انت بتحتفظ
+
+633
+00:49:43,650 --> 00:49:48,410
+بمجموعة ال attributes بناء على ال value اللي بتطلع
+
+634
+00:49:48,410 --> 00:49:54,630
+اكيد
+
+635
+00:49:54,630 --> 00:49:58,370
+انا اول ما بدينا استخدم ال sense تبعتك و اروح شوف
+
+636
+00:49:58,370 --> 00:50:03,290
+ال irrelevant attribute و احذفها بناء على خبرتك
+
+637
+00:50:03,290 --> 00:50:09,250
+مالكاش خبرة؟ بدك تتعب اما بيطلعي and majorأو بدك
+
+638
+00:50:09,250 --> 00:50:12,150
+تتعب في ال coefficient أو في ال correlation
+
+639
+00:50:12,150 --> 00:50:15,310
+coefficients و أنت بتحسب فيها في كل الأحوال بدك
+
+640
+00:50:15,310 --> 00:50:21,610
+تشتغل مافيش مجال انك تبقى قاعد لازم تتعب الآن في
+
+641
+00:50:21,610 --> 00:50:26,290
+حالة إذا كانت عندي nominal data nominal data يعني
+
+642
+00:50:26,290 --> 00:50:31,810
+البيانات اللي عندي مش أرقام البيانات اللي عندي مش
+
+643
+00:50:31,810 --> 00:50:35,390
+أرقام ال
+
+644
+00:50:35,390 --> 00:50:36,110
+choice square
+
+645
+00:50:41,310 --> 00:50:48,490
+ساوي مجموع من 1 ل C C لإيه الشباب Columns Columns
+
+646
+00:50:48,490 --> 00:50:52,890
+و من 1 ل R Rows صحوف لإن أنا في عندى two
+
+647
+00:50:52,890 --> 00:50:56,030
+attributes برضه هاخدهم و ال two attributes هدول
+
+648
+00:50:56,030 --> 00:51:02,770
+موجودين فانا بدي عد كل قيمة فيهم في عند ال OIG ال
+
+649
+00:51:02,770 --> 00:51:05,590
+observed أو ال actual values اللى موجودة عندى في
+
+650
+00:51:05,590 --> 00:51:11,680
+الجدولناقص الـ expected value وهذا سأحسبه الآن حسب
+
+651
+00:51:11,680 --> 00:51:16,040
+القانون اللي سنشاهده في الإصلاح القادم على 2 أو
+
+652
+00:51:16,040 --> 00:51:21,720
+عفوا التربيع على الـ expected value وبحصل على قيمة
+
+653
+00:51:21,720 --> 00:51:28,860
+وبدي أرجع لجدول تبع الـ significant level degree
+
+654
+00:51:28,860 --> 00:51:33,760
+of freedom هذا
+
+655
+00:51:33,760 --> 00:51:34,260
+الجدول
+
+656
+00:51:37,670 --> 00:51:43,210
+بيتكلم على degree of freedom اللي هي عبارة عن حاصل
+
+657
+00:51:43,210 --> 00:51:49,250
+ضرب الصفوف ناقص واحد والأعمد ناقص واحد عشان عدد ال
+
+658
+00:51:49,250 --> 00:51:52,430
+rows و ال attributes اللي انت بتشتغل عليها و مع
+
+659
+00:51:52,430 --> 00:51:54,570
+قيمة من القيم يعني هتيجي في لحظة من لحظة تقولي انا
+
+660
+00:51:54,570 --> 00:51:59,110
+بدي القيمة هذه بناء ل chi-square مع degree of
+
+661
+00:51:59,110 --> 00:52:04,190
+freedom level of significance مع degree of freedom
+
+662
+00:52:04,190 --> 00:52:09,770
+الأن برجليك تطبيقهاالان في ال example اللي موجود
+
+663
+00:52:09,770 --> 00:52:15,430
+عندي في عندي two attributes في ال data set ال
+
+664
+00:52:15,430 --> 00:52:22,410
+gender ال gender و ال preferred reading ال gender
+
+665
+00:52:22,410 --> 00:52:27,170
+male و female و ال preferred reading يعني الناس
+
+666
+00:52:27,170 --> 00:52:32,410
+بحبوا يقراوا روايات اما رواية خيالية او قصص خيالية
+
+667
+00:52:32,410 --> 00:52:35,130
+او قصص علمية او حقيقية سميها زي ما بدك
+
+668
+00:52:37,850 --> 00:52:43,990
+ال data set مكوّنة من 1500 row تمام؟ يعني في عندي
+
+669
+00:52:43,990 --> 00:52:50,550
+two attributes في ال data set ال gender preferred
+
+670
+00:52:50,550 --> 00:52:56,830
+reading male
+
+671
+00:52:56,830 --> 00:53:08,500
+fiction male nonfiction female fiction femalenon
+
+672
+00:53:08,500 --> 00:53:14,720
+-fiction وهكذا هذه
+
+673
+00:53:14,720 --> 00:53:19,280
+ال variables لاحظوا ان ال data اللي عندي في كل ال
+
+674
+00:53:19,280 --> 00:53:25,300
+attributes فقط قمتين عشان هيك الجدول اللي طلع عندي
+
+675
+00:53:25,300 --> 00:53:30,060
+اتنين في اتنين الجدول اللي طلع عندي هنا اتنين في
+
+676
+00:53:30,060 --> 00:53:30,400
+اتنين
+
+677
+00:53:34,140 --> 00:53:39,700
+في ال prefered reading لأ في أكتر بقولك أدب .. أدب
+
+678
+00:53:39,700 --> 00:53:44,220
+.. أه فيش .. فيش هان فيش هان okay بس هذا كمثال بدي
+
+679
+00:53:44,220 --> 00:53:47,240
+أجيبلك هان في ال preferred reading راح يقوللي
+
+680
+00:53:47,240 --> 00:53:52,320
+والله أنا بد الأدب literature في politics في
+
+681
+00:53:52,320 --> 00:53:57,860
+economics في sport هاي صار أربعة Fantasia Fantasia
+
+682
+00:53:57,860 --> 00:54:04,390
+هاي خمسة فانت بممكن تعد قد ما بدكفي الآخر جداش
+
+683
+00:54:04,390 --> 00:54:09,230
+هصير حجم هذا على جد ال data اللي عندك يعني بين
+
+684
+00:54:09,230 --> 00:54:14,070
+جسين أربعة values لأنه فعليا two two two values في
+
+685
+00:54:14,070 --> 00:54:15,890
+ال attribute الأول و two values في ال attribute
+
+686
+00:54:15,890 --> 00:54:18,790
+التاني لكن في الحالة اللي أنا جاعل بتكلم أنه
+
+687
+00:54:18,790 --> 00:54:24,090
+القراءة تبعتي السياسة و اقتصاد و أدب و علوم و .. و
+
+688
+00:54:24,090 --> 00:54:30,730
+.. و فن 102 في 5 هتزيد أكيد الآن
+
+689
+00:54:32,090 --> 00:54:35,510
+الـ values الـ 250 سيبك من اللي في الأحمر هذه بس
+
+690
+00:54:35,510 --> 00:54:37,630
+أنا عشان احنا قاعدين نتعلمك نقولك انه هنا فيه
+
+691
+00:54:37,630 --> 00:54:40,650
+values بده أحسبه الآن ال values اللي باللون الأسود
+
+692
+00:54:40,650 --> 00:54:45,690
+هذه هي عبارة عن computation للي موجود يعني بين
+
+693
+00:54:45,690 --> 00:54:48,250
+جثيم هين بيقوللي في ال data set أو في ال two
+
+694
+00:54:48,250 --> 00:54:51,790
+attributes 250 واحد من ال male بيحبوا يقرأوا ال
+
+695
+00:54:51,790 --> 00:54:59,400
+fiction stories 200 من ال female بيقرأوا fictionلو
+
+696
+00:54:59,400 --> 00:55:02,280
+أنا قرأت الصفوف اللي هي ال value الصماشن اللي
+
+697
+00:55:02,280 --> 00:55:06,200
+موجود عندى 450 هي عبارة عن عدد الناس اللي بتقرأ
+
+698
+00:55:06,200 --> 00:55:10,120
+fiction في 1500 تمام؟
+
+699
+00:55:10,120 --> 00:55:17,360
+العمود 300 male 1200 female تمام؟ واضحة ال values
+
+700
+00:55:17,360 --> 00:55:20,700
+اللي بلون الأسود؟ هذه اللي احنا بنسميها سمناها قبل
+
+701
+00:55:20,700 --> 00:55:26,940
+شوية هي ال actual أو ال observation O ال actual
+
+702
+00:55:26,940 --> 00:55:27,520
+values
+
+703
+00:55:30,330 --> 00:55:35,630
+الـ actual count الان الـ expected اللي هي باللون
+
+704
+00:55:35,630 --> 00:55:38,650
+الأحمر هذه لازم تكون عندك عشان تظبط عملية ال
+
+705
+00:55:38,650 --> 00:55:43,970
+coordination فكرتها كالتالي يا جماعة الخير الآن في
+
+706
+00:55:43,970 --> 00:55:49,070
+الصف و العمود اللي انا بدي اشتغل عليه بدي ال
+
+707
+00:55:49,070 --> 00:55:55,420
+expected اللي هانExpect لمين؟ عدد الرجال أو الـ
+
+708
+00:55:55,420 --> 00:55:59,640
+mail اللي بيقرأه fiction قيمة المتوقعة بناء على ال
+
+709
+00:55:59,640 --> 00:56:06,500
+1500 اللي موجودين ال expected value هذه تساوي في
+
+710
+00:56:06,500 --> 00:56:12,160
+المقام 1500 ال total number و فوق مضروبة بقيمتين
+
+711
+00:56:12,160 --> 00:56:15,280
+عدد
+
+712
+00:56:15,280 --> 00:56:19,080
+الرجال في
+
+713
+00:56:19,080 --> 00:56:28,670
+عدد ال fictionتمام؟ على 1500 250 عفواً 300 العدد
+
+714
+00:56:28,670 --> 00:56:42,090
+الرجال ضرب 450 بال fiction على 1500 ولاحظ
+
+715
+00:56:42,090 --> 00:56:45,330
+هو هاني حطتلك في القانون حطتلك ال I و ال J عشان
+
+716
+00:56:45,330 --> 00:56:50,700
+تسهل عليه الصف و العمود اللي بتشتغل معاهلكن كمان
+
+717
+00:56:50,700 --> 00:56:54,980
+مرة انت افهمها كالتالي في اي attribute او في اي
+
+718
+00:56:54,980 --> 00:57:00,400
+cell .. في اي cell عشان احسب ال expected value هي
+
+719
+00:57:00,400 --> 00:57:06,080
+عبارة عن حاصل ضرب المجموع تبع الصف في مجموع العمود
+
+720
+00:57:06,080 --> 00:57:12,360
+على العدد الكل 1500 يعني ال expected تبع الهان
+
+721
+00:57:12,360 --> 00:57:20,310
+هتكون عبارة عن 1200 في 1050 على 1500الـ Expected
+
+722
+00:57:20,310 --> 00:57:26,610
+اللي هان 300 في 1050 على 1500 وهيك بتصير عندك أسهل
+
+723
+00:57:26,610 --> 00:57:33,810
+انك تتذكر الـ Expected Value جداش قيمته يا مؤمن؟
+
+724
+00:57:33,810 --> 00:57:41,770
+15؟ اه بدك قلة حاسبة هذه
+
+725
+00:57:41,770 --> 00:57:43,670
+قلة حاسبة 90 على كل
+
+726
+00:57:48,570 --> 00:57:59,090
+300 ضرب 450 تقسيم 1500 300 ضرب 450 عال 1500 تسعين
+
+727
+00:57:59,090 --> 00:58:03,450
+تسعين تسعين تسعين تسعين تسعين تسعين تسعين تسعين
+
+728
+00:58:03,450 --> 00:58:14,470
+تسعين تسعين تسعين تسعين تسعين تسعين تسعين
+
+729
+00:58:14,470 --> 00:58:15,930
+تسعين
+
+730
+00:58:18,440 --> 00:58:24,260
+اللي بعدها تلاتمية في الف و خمسين تلاتمية ضارب الف
+
+731
+00:58:24,260 --> 00:58:34,720
+و خمسين تقسيم الف و خمسمية اللي
+
+732
+00:58:34,720 --> 00:58:37,980
+هتستفيد من الرقم انه هيه الرقم هذا بيلزمك في
+
+733
+00:58:37,980 --> 00:58:44,980
+المعادلة عشان تجيب قيمة ال correlation expected
+
+734
+00:58:44,980 --> 00:58:47,940
+هاي الأرقام اللي موجودة عندنا
+
+735
+00:58:50,970 --> 00:58:58,290
+احصة شغل احصة اكيد بدك اجيب لك اياه و نلزمك فيه
+
+736
+00:58:58,290 --> 00:59:01,110
+الاتباع الرياضي تبعه احنا عاملا بيقولك احفظ
+
+737
+00:59:01,110 --> 00:59:06,290
+القانون ايوة
+
+738
+00:59:06,290 --> 00:59:10,190
+جلبك مادة ايش احصة احنا قولنا من الأول
+
+739
+00:59:10,190 --> 00:59:14,210
+multidisciplinary متمينين بدك تعرف احصة و بدك تعرف
+
+740
+00:59:14,210 --> 00:59:17,790
+database و بدك تعرف برمجة و بدك تعرف machine
+
+741
+00:59:17,790 --> 00:59:21,690
+learningوبدك تعرف knowledge presentation وبدك تعرف
+
+742
+00:59:21,690 --> 00:59:28,130
+ترسم كل حاجة نعم ال course ماكسب للي بدوا يشتغل
+
+743
+00:59:28,130 --> 00:59:32,670
+ولي بدواش طيب
+
+744
+00:59:32,670 --> 00:59:37,870
+الآن عبّينا الجدول هاي عبّينا الجدول هذا جماعة
+
+745
+00:59:37,870 --> 00:59:40,830
+الخير في الامتحان اذا انا بدي اسألك في الموضوع هذا
+
+746
+00:59:40,830 --> 00:59:47,590
+لازم ازودك بال data اما هزودك بال dataas two rows
+
+747
+00:59:47,590 --> 00:59:54,610
+جدول مكوّن من two rows او هديك الجدول بدون ال
+
+748
+00:59:54,610 --> 00:59:58,410
+expected الآن
+
+749
+00:59:58,410 --> 01:00:03,810
+حسبت لل chi-square بناء على المعادلة ال actual
+
+750
+01:00:03,810 --> 01:00:07,850
+ناقص ال expected تربيع على ال expected على كل
+
+751
+01:00:07,850 --> 01:00:11,550
+الخلايا الأربع اللي موجودة في الجدول المحصلة كانت
+
+752
+01:00:11,550 --> 01:00:13,730
+خمسمية وسبعة
+
+753
+01:00:16,280 --> 01:00:20,860
+بما انه عدد الأعمد اللي عندي هان و الصفوف اتنين
+
+754
+01:00:20,860 --> 01:00:25,000
+اتنين ناقص واحد و ناقص واحد معناته انا بتكلم one
+
+755
+01:00:25,000 --> 01:00:29,820
+degree of freedom ال
+
+756
+01:00:29,820 --> 01:00:33,440
+hypothesis تبعتي one degree of freedom هتكون
+
+757
+01:00:33,440 --> 01:00:37,900
+المفروض عندي هان عشرة بناء على ال values اللي
+
+758
+01:00:37,900 --> 01:00:44,400
+موجودة لو انا اجيت للجدول هذا و
+
+759
+01:00:44,400 --> 01:00:51,980
+اين القيمة تبعتنا؟خمسمية و جدشي طلعت احنا
+
+760
+01:00:51,980 --> 01:00:54,460
+ليش بندور هيك one degree of freedom المفروض في
+
+761
+01:00:54,460 --> 01:00:59,160
+الصف الأول الآن
+
+762
+01:00:59,160 --> 01:01:02,820
+بناء على القيمة اللي موجودة عندك بناء على القيمة
+
+763
+01:01:02,820 --> 01:01:08,880
+اللي موجودة هان هيكون القرار ان انا فعليا اقبل او
+
+764
+01:01:08,880 --> 01:01:14,300
+ارفض ال
+
+765
+01:01:14,300 --> 01:01:15,560
+value اللي موجودة عندى هان
+
+766
+01:01:21,160 --> 01:01:26,300
+We need to reject بنرفض القيمة هذه وين؟ point zero
+
+767
+01:01:26,300 --> 01:01:31,900
+zero واحد إذا كانت القيمة اللي طالع يعني بالعقل
+
+768
+01:01:31,900 --> 01:01:34,700
+الإمام علي رضي الله عنه قال لو كان ال .. لو كان
+
+769
+01:01:34,700 --> 01:01:37,640
+الدينه بالعقل لا كان مسحه باطل الخفي أو لا من
+
+770
+01:01:37,640 --> 01:01:42,780
+ظاهرة صح؟ لما .. لما نمسح على الجربان في الشتاء
+
+771
+01:01:42,780 --> 01:01:47,020
+نمسح من فوق بينما الوسخ من أين بيجي؟ يعني من من
+
+772
+01:01:47,020 --> 01:01:51,330
+تحت بس الدين مش بالعقل مش كل شي بالعقل بيجيماشي
+
+773
+01:01:51,330 --> 01:01:58,530
+احمد؟ فانت بدك تروح تحسب عشان تثبت كلامك طيب ال
+
+774
+01:01:58,530 --> 01:02:02,710
+reduction الأخيرة اللي عندنا ال data reduction
+
+775
+01:02:02,710 --> 01:02:05,330
+اللي بتمتع من ال reduction خلصنا من ال attributes
+
+776
+01:02:05,330 --> 01:02:08,670
+احنا و قلت بقى أخلص من ال irrelevant attributes او
+
+777
+01:02:08,670 --> 01:02:12,230
+ال dependent attributes الآن بدي أعمل sampling
+
+778
+01:02:12,230 --> 01:02:15,870
+sampling يعني أنا بدي أتكلم على الروزة جماعة الخير
+
+779
+01:02:15,870 --> 01:02:20,090
+أنا خلصت غلصت عدد ال attributes الآن بدي أقلص عدد
+
+780
+01:02:21,080 --> 01:02:24,780
+الروز افترض
+
+781
+01:02:24,780 --> 01:02:29,540
+ان انا عندى الصندوق هذا وفيه
+
+782
+01:02:29,540 --> 01:02:43,100
+عشر كورات وقلتلك
+
+783
+01:02:43,100 --> 01:02:53,290
+بدي اسحب كورتين متتابعة كل واحدة بشكل مستقلتمام؟
+
+784
+01:02:53,290 --> 01:02:59,910
+احتمال ان الكورتين هدول يطلعوا حمر جداش؟ خلط
+
+785
+01:02:59,910 --> 01:03:08,590
+السحب الأولى اربعة على عشرة من جلك؟
+
+786
+01:03:08,590 --> 01:03:13,850
+حسب ال random sample تبعتي with replacement او
+
+787
+01:03:13,850 --> 01:03:17,670
+without هذا اللي انا بدو أوصلك إياه الآن انا في ال
+
+788
+01:03:17,670 --> 01:03:28,030
+samplingأو في الـ Random Sample في
+
+789
+01:03:28,030 --> 01:03:34,190
+عندي With Replacement و
+
+790
+01:03:34,190 --> 01:03:40,630
+Without Replacement مع
+
+791
+01:03:40,630 --> 01:03:44,870
+الإرجاع و بدون الإرجاع الآن احتمال أن أسحب كورتين
+
+792
+01:03:44,870 --> 01:03:56,610
+حمر مع الإرجاع4 على 10 ضرب 4 على 10 بدون
+
+793
+01:03:56,610 --> 01:04:06,250
+ارجع 4 على 10 ضرب 3 على 9 لأنه الآن اتغيرت ال
+
+794
+01:04:06,250 --> 01:04:09,890
+sample تبعتي او ال population تبعتي اتغيرت
+
+795
+01:04:09,890 --> 01:04:17,120
+وبالتالي جلت وقمتين تمامالان احنا معظم شغلنا لما
+
+796
+01:04:17,120 --> 01:04:21,300
+بنعمل sampling معظمه نتكلم sampling without
+
+797
+01:04:21,300 --> 01:04:26,180
+replacement لان انا مابديش تكرار انا فاحنا بنشتغل
+
+798
+01:04:26,180 --> 01:04:32,280
+هان without replacement ليش؟ لان كمان مرة عامالة
+
+799
+01:04:32,280 --> 01:04:35,060
+بقول انا بدي اخلص من التكرار اخلص من ال rows
+
+800
+01:04:35,060 --> 01:04:38,560
+المكررة اخلص من ال attributes المكررة فلو انا
+
+801
+01:04:38,560 --> 01:04:43,920
+الصاحب تبعي او ال random sample مع الارجاعممكن ال
+
+802
+01:04:43,920 --> 01:04:48,660
+record نفسه يظل يطلع عندى الشغل التانى اللى انا
+
+803
+01:04:48,660 --> 01:04:54,260
+بديهاها لان في ال random sampling تخيل انا اجيت و
+
+804
+01:04:54,260 --> 01:05:01,620
+قلتلك بدي 70 او عفوا بدي خمسين اربعين في المية من
+
+805
+01:05:01,620 --> 01:05:07,400
+ال data set هاي بدي تاخدلي اربعين في المية من ال
+
+806
+01:05:07,400 --> 01:05:07,960
+data set
+
+807
+01:05:13,280 --> 01:05:19,680
+كم كورة بقى تحطها انت؟ اربع كور بدك تسحب اربع كور
+
+808
+01:05:19,680 --> 01:05:27,300
+عشوائي شو
+
+809
+01:05:27,300 --> 01:05:32,240
+وراك بهيك؟ sample صح من ناحية sample without
+
+810
+01:05:32,240 --> 01:05:39,000
+replacement صح بس هي مشكلة ان ال data set ها ديلا
+
+811
+01:05:39,000 --> 01:05:42,560
+تمثل البيانات does not representative أنا قلت بدي
+
+812
+01:05:42,560 --> 01:05:47,540
+أجلل حجم ال data 6 نعم لكن بدي أبضل اتمثل الوضع
+
+813
+01:05:47,540 --> 01:05:54,520
+العام تبعتها مابيش الحل كيف أنا بدي أضمن نسبة نسبة
+
+814
+01:05:54,520 --> 01:06:00,380
+و تناسب 40% من الأحمر و 40% من الأسود وبهك بكون
+
+815
+01:06:00,380 --> 01:06:04,640
+حصلت على ال 40% و هذه ال 40% بنسميها stratified
+
+816
+01:06:05,470 --> 01:06:10,590
+Sampling أو بين جثين Supervised Sampling بروح على
+
+817
+01:06:10,590 --> 01:06:16,530
+كل class و باخد منه 40% ال data set موجودة حقيقة
+
+818
+01:06:16,530 --> 01:06:20,470
+نعم موزع على two classes three classes four
+
+819
+01:06:20,470 --> 01:06:26,310
+classes انا بدي 40% منها باخدهم ياشي Stratified
+
+820
+01:06:26,310 --> 01:06:30,270
+Sampling مباشرة بتجيبلي 30% من كل او 40% من كل
+
+821
+01:06:30,270 --> 01:06:34,400
+class ضايل عندنا نقطة واحدةفي موضوع الـ
+
+822
+01:06:34,400 --> 01:06:37,740
+Discretization في موضوع الـ Discretization يا شباب
+
+823
+01:06:37,740 --> 01:06:44,840
+الفكرة أنا قللت عدد ال attributes قللت عدد ال rows
+
+824
+01:06:44,840 --> 01:06:51,520
+بال sampling والآن بدي أقلل عدد ال distinct values
+
+825
+01:06:51,520 --> 01:06:55,060
+في ال attribute ال attribute نفسه موجود مش هقص منه
+
+826
+01:06:55,060 --> 01:06:58,860
+على مستوى ال rows وال attribute هيبقى بدي أجلل
+
+827
+01:06:58,860 --> 01:07:03,430
+العددالـ Variable .. Variant أو العدد الـ Values
+
+828
+01:07:03,430 --> 01:07:06,810
+أقل العدد الـ Values أو أقل ال Variety ال Variety
+
+829
+01:07:06,810 --> 01:07:11,550
+بين ال Values اللي موجودة بتفرج معايا؟ أه بتفرج
+
+830
+01:07:11,550 --> 01:07:17,970
+أنا عندي ال Age من عشر لخمسين نتكلم على تسعة و
+
+831
+01:07:17,970 --> 01:07:20,830
+أربعين distinct value واحد و أربعين .. واحد و
+
+832
+01:07:20,830 --> 01:07:24,090
+أربعين، صح؟ لأن الصفر موجود معناه واحد و أربعين
+
+833
+01:07:24,090 --> 01:07:27,490
+واحد و أربعين distinct value يعني ال rule تبعي بدي
+
+834
+01:07:27,490 --> 01:07:32,780
+احتوي على واحد و أربعين F41 condition هذا الكلام
+
+835
+01:07:32,780 --> 01:07:38,400
+مشكلة مابيش الحل اعمل discretization جلل ال values
+
+836
+01:07:38,400 --> 01:07:43,280
+اللي موجودة كيف لاحظ هي number number continuous
+
+837
+01:07:43,280 --> 01:07:47,820
+وانت بقى بتحولها discrete discretization بتعملهم
+
+838
+01:07:47,820 --> 01:07:52,500
+قيم يعني بينجوسين بقى بتعملهم فئات بس بده تحافظ
+
+839
+01:07:52,500 --> 01:07:57,850
+على الأرقام اللي موجودة الآن ممكن انت تستخدمطرق
+
+840
+01:07:57,850 --> 01:08:02,170
+سواء بالاعتماد على الـ Label أو بدونه Supervised و
+
+841
+01:08:02,170 --> 01:08:05,570
+Unsupervised بالـ Unsupervised بدي أطبق مفهوم الـ
+
+842
+01:08:05,570 --> 01:08:09,650
+Binning و أستبدل القيم بالـ Mean أو بالـ Medium زي
+
+843
+01:08:09,650 --> 01:08:13,530
+ما شوفنا وين في الـ Data Transformation يعني بيجي
+
+844
+01:08:13,530 --> 01:08:18,510
+هاي ال data set هاي ال data set two attributes ال
+
+845
+01:08:18,510 --> 01:08:22,070
+label مش هغير عليه درجة الحرارة اللي موجودة عندهان
+
+846
+01:08:22,070 --> 01:08:27,530
+بدي أعملها Discretization أجسمها Binningجالي اشتغل
+
+847
+01:08:27,530 --> 01:08:32,830
+على frequent او equal frequency مع تلت عناصر equal
+
+848
+01:08:32,830 --> 01:08:35,870
+frequency مع تلت عناصر رتبت ال attribute في الأول
+
+849
+01:08:35,870 --> 01:08:43,450
+ترتيب تصعدي وجسمتهم بعد هي تلتات وحطيت ال median
+
+850
+01:08:43,450 --> 01:08:47,150
+بتاعة كل واحد فيهم هاي discretization بنسميها
+
+851
+01:08:47,150 --> 01:08:51,970
+unsupervised discretization ال label ماتدخلش في
+
+852
+01:08:51,970 --> 01:08:56,920
+الموضوعالان في عندي بال supervised لأ بدي اعمل
+
+853
+01:08:56,920 --> 01:09:01,380
+حساب لل label نفس ال data set .. نفس ال data set
+
+854
+01:09:01,380 --> 01:09:07,180
+كل ما بيتغير ال label بدي اعتبر انه هادي bin او
+
+855
+01:09:07,180 --> 01:09:11,300
+هادي مجموعة 81
+
+856
+01:09:11,300 --> 01:09:16,580
+طبعا باجترطب ال data في البداية لازم كون بدي اجسم
+
+857
+01:09:16,580 --> 01:09:22,280
+بدي اجترطب ال data هاي لاحظ ال 64 هادي هتكون لحالة
+
+858
+01:09:23,310 --> 01:09:31,590
+الآن الـ 65 لحالها الـ 69 .. الـ 68 و69 و70 هدولة
+
+859
+01:09:31,590 --> 01:09:35,710
+one pen لأن كل ما بتغير ال label بيصير فيه pen
+
+860
+01:09:35,710 --> 01:09:43,730
+جديدة عفوا لأ وصل لأخر طب و كل pen حطله المين أو
+
+861
+01:09:43,730 --> 01:09:48,450
+ال media مش قضيتنا كتير في نوع تاني بس شكل الناس
+
+862
+01:09:48,450 --> 01:09:52,810
+اللي slide أضيفها أو في موضوع ال supervisedانه مش
+
+863
+01:09:52,810 --> 01:09:57,870
+كل ما بيتغير ال bin احط minimum لعدد ال bins قبل
+
+864
+01:09:57,870 --> 01:10:02,210
+التغير يعني ان ال class يظهر بعدد معين قبل ما يغير
+
+865
+01:10:02,210 --> 01:10:05,970
+لو اجينا جولنهان على نفسها ال data sorted بكل ما
+
+866
+01:10:05,970 --> 01:10:14,010
+يتغير او بعد اقل عدد تلت مرات من الظهور هحسب
+
+867
+01:10:14,010 --> 01:10:19,160
+التغير يعني انا بن جوسين بدي اروح ادور علىيعني مش
+
+868
+01:10:19,160 --> 01:10:23,440
+هبدل لل next pen إلا لما يكون واحد من ال classes
+
+869
+01:10:23,440 --> 01:10:30,340
+ظهر على الأقل عدد مرات تابعة وليكن تلاتة حاجة أن
+
+870
+01:10:30,340 --> 01:10:36,820
+هي data sorted yes مرة no مرة هيتغير ال class لكن
+
+871
+01:10:36,820 --> 01:10:43,380
+مش هعمل pen yes صاروا مرتين yes و no مرة تلاتة yes
+
+872
+01:10:43,380 --> 01:10:47,980
+وراها yes ماتغيرش لسه ماتغيرش الآن عند التغيير هنا
+
+873
+01:10:50,070 --> 01:10:55,470
+صار نو هذه كلها عبارة عن one pin ليش؟ لأن ال yes
+
+874
+01:10:55,470 --> 01:10:59,190
+ظهرت على الأقل تلت مرات و هي فعليا ظهرت واحدة
+
+875
+01:10:59,190 --> 01:11:03,310
+تنتين تلات أربع طب ال no مالاش داخل فيها موجودة
+
+876
+01:11:03,310 --> 01:11:08,330
+الآن هحسب المتوسط الحساب اللي هدول كلهم و أحطه هنا
+
+877
+01:11:08,330 --> 01:11:15,130
+اللي بعدها واحد واحد واحد نين تلاتة ال pin اللي
+
+878
+01:11:15,130 --> 01:11:20,700
+بعده لأنه صار في عندي تلاتة yesو بعدين انتقل لـ No
+
+879
+01:11:20,700 --> 01:11:24,760
+برضه نفس الكلام بجيب المتوسط الحسابي لهدول و هدول
+
+880
+01:11:24,760 --> 01:11:31,900
+الأخرانيات مع بعضهم البن الأخيرة تمام؟ وهكذا بكون
+
+881
+01:11:31,900 --> 01:11:35,240
+اننا خلصنا من ال discretization او خلصنا من ال
+
+882
+01:11:35,240 --> 01:11:38,440
+data reduction data reduction يعني في عندي feature
+
+883
+01:11:38,440 --> 01:11:42,160
+selection و في عندي sampling و في عندي
+
+884
+01:11:42,160 --> 01:11:46,580
+discretization وبهكذا احنا خلصنا ال chapter فعليا
+
+885
+01:11:46,580 --> 01:11:50,710
+دل عند ال assignment هذاال assignment هذا بقى
+
+886
+01:11:50,710 --> 01:11:54,150
+هتسلمني إياه يوم السبت الجاي .. اه يوم التنين
+
+887
+01:11:54,150 --> 01:11:57,910
+الجاي يوم التنين محاضرتنا التلاتة قبل ما تيجي على
+
+888
+01:11:57,910 --> 01:12:04,190
+المحاضرة يوم التنين بتكون سلم الان المطلوب منك
+
+889
+01:12:04,190 --> 01:12:10,240
+python باعتمادك على ال pythonتقرا ال data set
+
+890
+01:12:10,240 --> 01:12:14,340
+تبعتك و تطبق عليها ال cleaning التالي بناء على
+
+891
+01:12:14,340 --> 01:12:18,720
+الحاجة ال missing ال noise ال duplicate records ال
+
+892
+01:12:18,720 --> 01:12:22,960
+relevant attributes تشيل ال correlated attributes
+
+893
+01:12:22,960 --> 01:12:28,940
+كيف تشتغل على ال correlated attributes الان كل ال
+
+894
+01:12:28,940 --> 01:12:34,560
+attributes ال correlation تبعتهم بتزيد
+
+895
+01:12:34,560 --> 01:12:41,490
+عن ال 80% اكبر او تساوي 80%بدك تحذف تبقى واحد منهم
+
+896
+01:12:41,490 --> 01:12:44,410
+فقط و هيك انا اعدي التكرول و بدك تطبقه على الجميع
+
+897
+01:12:44,410 --> 01:12:51,910
+خلصنا تجسم ال data set ل سبعين و تلاتين training و
+
+898
+01:12:51,910 --> 01:12:57,630
+testing باعتمادك على stratified sampling و
+
+899
+01:12:57,630 --> 01:13:00,290
+تضيف enough comments على ال code اللي موجود عندك
+
+900
+01:13:01,090 --> 01:13:05,730
+جبل ما ترفعلي ملف بايثون individual كل واحد لحاله
+
+901
+01:13:05,730 --> 01:13:09,570
+اللي بده يشتغل صح نفسي ب data set بس شغلك انت غير
+
+902
+01:13:09,570 --> 01:13:12,990
+عن شغل زميلك ال comments تبعتك الطرق اللي انت حر
+
+903
+01:13:12,990 --> 01:13:16,770
+بدك تشتغل فيه بعدين هتتناقش انت و مجموعتك بس الشغل
+
+904
+01:13:16,770 --> 01:13:20,970
+بال بايثون individual بشكل فردي الآن في بعض
+
+905
+01:13:20,970 --> 01:13:24,050
+الأكواد موجودة في ال slide هتريحك في جزئيات كبيرة
+
+906
+01:13:25,420 --> 01:13:28,560
+كنت من أول السنة .. من أول الشهر الماضي و أنا بقول
+
+907
+01:13:28,560 --> 01:13:31,720
+لك الشباب اللي أنا كنت اعمل install ازا انت عملي
+
+908
+01:13:31,720 --> 01:13:34,440
+install انت ready تشتغل البكرة او تشتغل ان الآن
+
+909
+01:13:34,440 --> 01:13:40,100
+ماعملتش install اصلا بدك .. هتاخد وجهت .. الآن ده
+
+910
+01:13:40,100 --> 01:13:43,720
+هتشتغل individual ترفعلي شغل ملف ال python هذا على
+
+911
+01:13:43,720 --> 01:13:48,640
+ال model بشكل مستقل و بعدين بتتناقش انت و مجموعتك
+
+912
+01:13:48,640 --> 01:13:52,420
+لاحقا زي ما هنقول لك .. اه يا هب .. اه هذا الآن
+
+913
+01:13:52,420 --> 01:13:54,820
+بطلع من هنا ان شاء الله تعالى هروح نرفعلكي على ال
+
+914
+01:13:54,820 --> 01:13:59,360
+modelولا أي همك ان شاء الله تمام الشباب يعطيكم
+
+915
+01:13:59,360 --> 01:14:01,840
+العافية و نهاية أسبوع سعيدة ان شاء الله
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/j7QLNeXbOs4_postprocess.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/j7QLNeXbOs4_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..4b98d704eaa447e65762423557c46b84e03c7bf6
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/j7QLNeXbOs4_postprocess.srt
@@ -0,0 +1,1592 @@
+1
+00:00:00,910 --> 00:00:04,730
+بسم الله و الحمد لله و الصلاة والسلام على رسول
+
+2
+00:00:04,730 --> 00:00:08,090
+الله اليوم ان شاء الله تعالى في التسجيل اللي محاضر
+
+3
+00:00:08,090 --> 00:00:13,910
+عليه هنشغل عملي فيه مع موضوع ال .. ال clustering و
+
+4
+00:00:13,910 --> 00:00:17,550
+هنبدأ في .. مع ال k means ال data set اللي هنشغل
+
+5
+00:00:17,550 --> 00:00:21,170
+عليها مؤقتا او هنشغل عليها انا هي عبارة عن جزء
+
+6
+00:00:21,170 --> 00:00:27,430
+صغير من ال iris المكونة من 30 rowاللي هو مع كل
+
+7
+00:00:27,430 --> 00:00:33,310
+عشرة row بتخضع ل class معين sitosa و versicolor و
+
+8
+00:00:33,310 --> 00:00:37,170
+virginica هذه ال data set اللي موجودة او انا هشغل
+
+9
+00:00:37,170 --> 00:00:42,150
+عليها خلينا بداية طبعا كالعادة مع اي مشروع احنا او
+
+10
+00:00:42,150 --> 00:00:44,950
+معايا بال python و program في ال data science او
+
+11
+00:00:44,950 --> 00:00:50,570
+في ال data mining بيلزمني انيأحمل البيانات اللي
+
+12
+00:00:50,570 --> 00:00:55,510
+موجودة عندي فخلينا نبدأ انه هي comment انا هى بدي
+
+13
+00:00:55,510 --> 00:01:05,610
+اعمل import ال data set طبعا بيلزمني استخدم ال
+
+14
+00:01:05,610 --> 00:01:12,150
+banders import banders
+
+15
+00:01:12,150 --> 00:01:13,670
+as pd
+
+16
+00:01:26,850 --> 00:01:32,410
+الان بدي اسم ال data set iris="bandas
+
+17
+00:01:32,410 --> 00:01:36,530
+.read
+
+18
+00:01:36,530 --> 00:01:49,870
+-csv">اسم الملف الموجود في نفس ال folder iris-mini
+
+19
+00:01:49,870 --> 00:01:52,990
+.csv
+
+20
+00:02:00,180 --> 00:02:03,400
+أذا انا بدى اتأكد ان عملية ال loading كباعة صحيحة
+
+21
+00:02:03,400 --> 00:02:12,140
+او لأ ممكن اتأكد ان والله اقوله ال iris.head
+
+22
+00:02:12,140 --> 00:02:15,660
+اقولنا ال head هي بتتكلم على by default خمس صفوف
+
+23
+00:02:15,660 --> 00:02:18,760
+لكن ممكن اخليها تلاتة او اربعة
+
+24
+00:02:34,600 --> 00:02:51,360
+بداية موثقة إن شاء الله قرأنا
+
+25
+00:02:51,360 --> 00:02:54,970
+ال data setهذه المفروضة الطريقة أو هذا الخطوة يعني
+
+26
+00:02:54,970 --> 00:03:00,670
+مافيش فيها خطأ مطلقا طيب الان بما ان انا بدي اشتغل
+
+27
+00:03:00,670 --> 00:03:11,130
+unsupervised learning task فانا بدي افصل عفوا
+
+28
+00:03:11,130 --> 00:03:15,430
+ال label لا ال label attribute عن ال data set فانا
+
+29
+00:03:15,430 --> 00:03:18,530
+هروح اقول ان في عندى ال attribute
+
+30
+00:03:20,420 --> 00:03:34,540
+أوكي خلّيني أقوم بالإعادة split data attribute and
+
+31
+00:03:34,540 --> 00:03:44,680
+label الان
+
+32
+00:03:44,680 --> 00:03:51,670
+سأقوم بالإعادة attribute equalالـ iris أنا بدي كل
+
+33
+00:03:51,670 --> 00:03:55,290
+ال data set .drop طبعا هذه اللي اتعلمناها في موضوع
+
+34
+00:03:55,290 --> 00:03:59,050
+ال processing
+
+35
+00:03:59,050 --> 00:04:05,750
+اسم ال attribute ال variety اذا انا مش غلطان
+
+36
+00:04:05,750 --> 00:04:09,150
+variety
+
+37
+00:04:16,110 --> 00:04:23,610
+Okay طبعا هذا الكلب موجود لان انا على axis equal
+
+38
+00:04:23,610 --> 00:04:42,270
+واحد ومن دي ال labels attributes
+
+39
+00:04:42,270 --> 00:04:51,740
+وال labelsequal to iris of
+
+40
+00:04:51,740 --> 00:04:55,460
+الوريدة
+
+41
+00:04:55,460 --> 00:05:04,940
+تمام هيك انا ال data فصلت
+
+42
+00:05:04,940 --> 00:05:09,800
+تمام معايا من
+
+43
+00:05:09,800 --> 00:05:15,000
+و بينكم هو مش متحمل انا بكتب نص الاسمو ال label
+
+44
+00:05:15,000 --> 00:05:17,760
+فانا فصلت ال data attributes هيك و ال label
+
+45
+00:05:17,760 --> 00:05:28,020
+attribute تمام
+
+46
+00:05:28,020 --> 00:05:36,540
+اصبح لدي الان ال data set متوفرة لكن انا فيه مشكلة
+
+47
+00:05:36,540 --> 00:05:42,850
+حقيقية انه لما انا بدى اعمل clusterالـ data set
+
+48
+00:05:42,850 --> 00:05:46,870
+تبعتي هتظهر .. هيديني أرقام clusters ال lizard
+
+49
+00:05:46,870 --> 00:05:50,730
+هيديني أرقام clusters والأرقام اللي عندي أنا فعليا
+
+50
+00:05:50,730 --> 00:05:55,490
+هي عبارة عن .. الله مصلى على سيدنا محمد عن nominal
+
+51
+00:05:55,490 --> 00:06:00,030
+class وبالتالي انا لازم اشكون في عنده طريقة معينة
+
+52
+00:06:00,030 --> 00:06:02,710
+عشان اقدر اقارن بيهم .. اذا انا بدي اتكلم في موضوع
+
+53
+00:06:02,710 --> 00:06:06,910
+ال majority لو انا بدي اتجاه الخطوة هاي و هرجعلها
+
+54
+00:06:06,910 --> 00:06:13,320
+بعد هي كانتمباشرة الآن خلّينا نروح على الـ
+
+55
+00:06:13,320 --> 00:06:17,600
+SKLAYER.CLUSTER
+
+56
+00:06:17,600 --> 00:06:20,620
+IMPORT
+
+57
+00:06:20,620 --> 00:06:26,460
+K-MEANS IMPORT K-MEANS
+
+58
+00:06:37,490 --> 00:06:41,430
+الان بدي أبني model مثل ما كنت بشغل معاه في ال
+
+59
+00:06:41,430 --> 00:06:51,610
+classification من ال key means و
+
+60
+00:06:51,610 --> 00:06:56,270
+number of clusters ال argument كام cluster اللي هي
+
+61
+00:06:56,270 --> 00:07:05,870
+ال key تبعتنا أنا هروح أقوله تلاتة model dot
+
+62
+00:07:07,920 --> 00:07:13,640
+فت عشان يدرس ال data set وقلنا بدي أتعامل مع ال
+
+63
+00:07:13,640 --> 00:07:25,220
+attributes فقط okay هاي import okay
+
+64
+00:07:25,220 --> 00:07:33,480
+means from sk learn
+
+65
+00:07:36,700 --> 00:07:42,660
+بورد و build و create كميز object
+
+66
+00:07:47,690 --> 00:07:52,070
+تمام عملنا لوفيت وهي كانت الأمور تمام الخطوة اللي
+
+67
+00:07:52,070 --> 00:07:56,690
+بعد هيك ايش بتتوقع ان انا بدي اسوي فيه بدي اتعرف
+
+68
+00:07:56,690 --> 00:08:00,310
+على ال classes اللي موجودة عندها طبعا ال method
+
+69
+00:08:00,310 --> 00:08:02,910
+اللي كنا نشوفها مع ال class مع ال classification
+
+70
+00:08:02,910 --> 00:08:09,050
+اللي هي method الخاصة بال prediction
+
+71
+00:08:09,050 --> 00:08:13,470
+مع ال classification هي نفسها مازالت متاحة اما ان
+
+72
+00:08:13,470 --> 00:08:14,850
+انا هروح و اقول له why
+
+73
+00:08:20,450 --> 00:08:31,910
+wire predict equal model.predict
+
+74
+00:08:31,910 --> 00:08:38,210
+طبعا و ال predict هاي كالعقب بده تاخد برضه من
+
+75
+00:08:41,820 --> 00:08:45,500
+الـ attributes اللي هي ال data set هو راح درسهم
+
+76
+00:08:45,500 --> 00:08:49,460
+هان في ال fit راح ادرس ال attributes و اعمل
+
+77
+00:08:49,460 --> 00:08:52,860
+computation حسب ال means الان في ال predicts بدي
+
+78
+00:08:52,860 --> 00:08:57,920
+يديني قائمة بال classes اللي بتنتمي لها كل
+
+79
+00:08:57,920 --> 00:09:03,270
+instance او قائمة بال classes نعمبحيث انك .. يعني
+
+80
+00:09:03,270 --> 00:09:06,370
+هيبدين قائمة من 30 element بنفس عدد ال data set
+
+81
+00:09:06,370 --> 00:09:09,890
+لكن هذه ال value اللي فيها بتمثل ال class number
+
+82
+00:09:09,890 --> 00:09:13,510
+اللي .. عفوا ال cluster number اللي بتتميله ال
+
+83
+00:09:13,510 --> 00:09:18,710
+instance اللي موجودة عندها لو انا حبيت انا اطبع
+
+84
+00:09:18,710 --> 00:09:24,910
+print ypredict وهي
+
+85
+00:09:24,910 --> 00:09:25,130
+run
+
+86
+00:09:30,860 --> 00:09:36,000
+أي data set اللي طلعت عندي هنا أي هدول عشرة لو
+
+87
+00:09:36,000 --> 00:09:43,830
+عدناهموهي كمان عشرة وهي كمان عشرين لاحظوا معايا ان
+
+88
+00:09:43,830 --> 00:09:46,410
+العشرين اللي في الآخر هدول يعني هاي هذه ال
+
+89
+00:09:46,410 --> 00:09:49,570
+instance تنتمى لل class الأول هذه ال instance عفوا
+
+90
+00:09:49,570 --> 00:09:53,190
+لل cluster الأول ال instance هي لل cluster التالد
+
+91
+00:09:53,190 --> 00:09:56,950
+ال instance هي لل cluster التاني ليش؟ لأنه أخد
+
+92
+00:09:56,950 --> 00:10:01,350
+الأرقام ل clusters بنفس الترتيب اللي موجود بيبدأ
+
+93
+00:10:01,350 --> 00:10:06,530
+صفر واحد اتنين تلاتة اربعة بحسب العدد اللي انالو
+
+94
+00:10:06,530 --> 00:10:09,310
+انا ايدي اتغيرت هنا و قلت له عدد ال cluster تبعت 2
+
+95
+00:10:09,310 --> 00:10:14,710
+و عملت run هاي
+
+96
+00:10:14,710 --> 00:10:18,870
+بس 01 تمام؟ لو انا قلت له 4
+
+97
+00:10:26,090 --> 00:10:30,990
+هي دهر الرقم تلاتة في ال cluster فهو دائما مجبر ان
+
+98
+00:10:30,990 --> 00:10:35,550
+يوزع حسب العناصر الموجودة لو قلت له خمسة في
+
+99
+00:10:35,550 --> 00:10:39,490
+التجربة الأخيرة مع ال K زي ما قلنا سابقا مافيش
+
+100
+00:10:39,490 --> 00:10:42,710
+لازم يكون كل العناصر موجودة استحالة ألا يجي
+
+101
+00:10:42,710 --> 00:10:47,850
+cluster فاضيليش؟ لأنه بألزمه بألزمه أن ال data set
+
+102
+00:10:47,850 --> 00:10:51,370
+تتوزع على عدد معين من ال clusters وقولنا هذه هي
+
+103
+00:10:51,370 --> 00:10:54,470
+التحدي الأساسي الموجود في ال K-Means أو في ال
+
+104
+00:10:54,470 --> 00:10:57,590
+partitional clustering إن أنا أكون فعليا عارف عدد
+
+105
+00:10:57,590 --> 00:11:00,950
+ال clusters مسبقا أنا فعليا ال data set تبعتي
+
+106
+00:11:00,950 --> 00:11:03,370
+مكونة من ال three clusters ف already هي من ال
+
+107
+00:11:03,370 --> 00:11:07,590
+three clusters الآن
+
+108
+00:11:07,590 --> 00:11:12,230
+لو أنا بده أروح أعمل metric بده أسأل الآن هي بده
+
+109
+00:11:12,230 --> 00:11:12,750
+أروح ال
+
+110
+00:11:15,990 --> 00:11:27,230
+بس هنحطها ن comment find the clusters list
+
+111
+00:11:27,230 --> 00:11:38,190
+for the data set find او predict لإن في الآخر
+
+112
+00:11:38,190 --> 00:11:42,110
+عملية prediction اللي احنا بنتكلم
+
+113
+00:11:49,020 --> 00:11:53,000
+التي في الآخر عملية prediction تمام الآن مثلها مثل
+
+114
+00:11:53,000 --> 00:11:57,840
+ال classification task او ال .. انا في عندي ال
+
+115
+00:11:57,840 --> 00:12:00,400
+matrix فممكن انا بدي اروح لمرحلة ال evaluation
+
+116
+00:12:00,400 --> 00:12:07,960
+الان لو
+
+117
+00:12:07,960 --> 00:12:12,780
+انا روحت طبعا from a
+
+118
+00:12:12,780 --> 00:12:18,340
+scalar dot
+
+119
+00:12:24,970 --> 00:12:32,430
+بارد الـ matrix الـ
+
+120
+00:12:32,430 --> 00:12:40,990
+contingency الـ
+
+121
+00:12:40,990 --> 00:12:47,190
+contingency matrix
+
+122
+00:12:47,190 --> 00:12:49,110
+equal
+
+123
+00:13:03,230 --> 00:13:05,590
+metric.clusterscontingencymatrix وإيش ال
+
+124
+00:13:05,590 --> 00:13:10,150
+contingency matrix هيها حسب ال help بتاخد مني two
+
+125
+00:13:10,150 --> 00:13:14,030
+parameters بتاخد مني ال true label وبتاخد مني اللي
+
+126
+00:13:14,030 --> 00:13:16,710
+بدك label لأن ال label السابعة اللي موجودة في ال
+
+127
+00:13:16,710 --> 00:13:22,560
+label صحعشان اريكم انه الاستحاق ال labels وهيها
+
+128
+00:13:22,560 --> 00:13:30,920
+وهي كومة وهي ال y predict لو
+
+129
+00:13:30,920 --> 00:13:37,680
+انا قلت له print ال contingency matrix وعملت
+
+130
+00:13:37,680 --> 00:13:37,940
+run
+
+131
+00:13:47,130 --> 00:13:55,510
+اللي صار انه اخد هو فعليا ال .. الصحيح دائما العمل
+
+132
+00:13:55,510 --> 00:14:04,630
+بيحمل مفاجأات جديدة انا ال .. okay اللي
+
+133
+00:14:04,630 --> 00:14:09,670
+صار عندي هان انه هي ال data setتوزعت قال لي ان ال
+
+134
+00:14:09,670 --> 00:14:13,670
+class هي contingency ان ال attribute او ال cluster
+
+135
+00:14:13,670 --> 00:14:17,190
+الأول pure العشرة اللي فيه و هي .. لو الصفر هدولة
+
+136
+00:14:17,190 --> 00:14:22,410
+عشرة تمام ال class التاني اللي هو واحد فيه عشرة
+
+137
+00:14:22,410 --> 00:14:25,930
+كذلك مافيش فيه pure بناء على المقارنة اللي موجودة
+
+138
+00:14:25,930 --> 00:14:33,230
+لو عديت هدولة انا اتنين
+
+139
+00:14:33,230 --> 00:14:34,450
+ستة
+
+140
+00:14:36,250 --> 00:14:42,110
+عشرة أو عشرة تمام لكن جال ليه ان في عندي مشكلة انا
+
+141
+00:14:42,110 --> 00:14:46,970
+انه في ال class التالت موزع ما بين فعليا مش pure
+
+142
+00:14:46,970 --> 00:14:52,070
+بالاساس ان القيم تبعته مختلفة من العناصر اللي
+
+143
+00:14:52,070 --> 00:14:58,220
+موجودة وبالتالي قيمة ال contingency matrix هييعني
+
+144
+00:14:58,220 --> 00:15:01,740
+انا فعليا هو في عنده مشكلة مع ال cluster التالت في
+
+145
+00:15:01,740 --> 00:15:06,640
+موضوع التقييم لو انا روحت هان و قلتله اربعة ايش
+
+146
+00:15:06,640 --> 00:15:14,220
+حيصير عندي هان جاب
+
+147
+00:15:14,220 --> 00:15:18,760
+لي مصفوفة اربعة في اربعة و حاول يتعرف على ال data
+
+148
+00:15:18,760 --> 00:15:25,630
+set اللي موجودةعندي طيب ليش تلاتة في أربعة مش
+
+149
+00:15:25,630 --> 00:15:28,650
+أربعة في أربعة الأصل أنا أكون أربعة في أربعة لأن
+
+150
+00:15:28,650 --> 00:15:33,130
+ال labels اللي عندي أنا فعليا هم تلاتة اللي في ال
+
+151
+00:15:33,130 --> 00:15:36,790
+true label فدولة تريد وبالتالي المقارنة بدها تكون
+
+152
+00:15:36,790 --> 00:15:46,450
+دائما صحيحة طبعا
+
+153
+00:15:46,450 --> 00:15:46,810
+كذلك
+
+154
+00:15:50,590 --> 00:15:54,970
+في عندى من ال matrix اللى حكينا عليها سابقا اللى
+
+155
+00:15:54,970 --> 00:16:01,030
+هي adjusted rent score و ال purity ال purity طبعا
+
+156
+00:16:01,030 --> 00:16:04,070
+اللى بنحسبها حنا منها ال maximum مع كل row في
+
+157
+00:16:04,070 --> 00:16:08,490
+المصفوفة عشرة عشرة تمانية تمانية و عشرين على
+
+158
+00:16:08,490 --> 00:16:11,550
+تلاتين هي ال purity تبعت ال algorithm اللى موجود
+
+159
+00:16:11,550 --> 00:16:15,270
+عندى لكن لو انا بدى اتكلم على ال adjusted rent
+
+160
+00:16:15,270 --> 00:16:20,500
+index هروح اقوله من ال matrixاللي هي عندى ال
+
+161
+00:16:20,500 --> 00:16:28,620
+cluster dot اللى هي ال adjusted score
+
+162
+00:16:28,620 --> 00:16:36,130
+نفس الكلام بتاخد منى ال labels اللى موجودةخلّينا
+
+163
+00:16:36,130 --> 00:16:42,210
+نعمل رن نحنا هنا بس إداني أنها رقم أيها point 8
+
+164
+00:16:42,210 --> 00:16:46,410
+وكنا متفقين أن ال adjusted rand index كل ما قربت
+
+165
+00:16:46,410 --> 00:16:50,610
+للواحد يكون الأداء ال cluster ال algorithm تبعتي
+
+166
+00:16:50,610 --> 00:16:51,970
+أفضل فهي قيمتها هنا
+
+167
+00:16:57,350 --> 00:17:02,150
+بنفس النظام ممكن انا اجيبها وهذه عبارة عن مجموعة
+
+168
+00:17:02,150 --> 00:17:09,150
+من ال matrix كذلك خلنا نسميها mi equal نفس الكلام
+
+169
+00:17:09,150 --> 00:17:17,210
+السابق matrix dot cluster dot
+
+170
+00:17:19,300 --> 00:17:23,340
+نقوم باستخدام البرنامج InfoScore نقوم باستخدام
+
+171
+00:17:23,340 --> 00:17:30,920
+البرنامج InfoScore نقوم باستخدام البرنامج
+
+172
+00:17:30,920 --> 00:17:36,960
+InfoScore نقوم باستخدام البرنامج InfoScore
+
+173
+00:17:41,330 --> 00:17:49,990
+هذه هي قيمة الان ام اي نوعا ما عندي تمام الخطأ
+
+174
+00:17:49,990 --> 00:17:56,570
+اللي كان warning مش خطأ warning
+
+175
+00:17:56,570 --> 00:18:02,690
+future warning the behavior will not changeأنا
+
+176
+00:18:02,690 --> 00:18:07,110
+بتتكلم إن ال NMI حسب ال version أنا صحيح عملت
+
+177
+00:18:07,110 --> 00:18:11,930
+update قريب وهي المفاجأات اللي موجودة عندها تمام
+
+178
+00:18:11,930 --> 00:18:16,170
+هدفي ما يتعلق في ال partitional clustering نعمل
+
+179
+00:18:16,170 --> 00:18:19,410
+review على السريع إيش اللي سوناه طبعا زي ما تشوفين
+
+180
+00:18:19,410 --> 00:18:24,170
+جامعة الخيار ال python سهل مش بحاجة ل .. مافيش
+
+181
+00:18:24,170 --> 00:18:27,690
+فيها تعقيدات دي functions تبعت جاهزة و ممكن أنا
+
+182
+00:18:27,690 --> 00:18:30,450
+أشتغل عليها بكل سهولة
+
+183
+00:18:42,150 --> 00:18:48,390
+الان بدي أنتقل معاكم لجزئية ال hierarchical
+
+184
+00:18:48,390 --> 00:18:53,190
+clustering في
+
+185
+00:18:53,190 --> 00:19:04,350
+ال hierarchical clustering نعمل
+
+186
+00:19:04,350 --> 00:19:07,450
+ال data set بنفس الكلام خلّينا في الأول أنشئ ملف
+
+187
+00:19:07,450 --> 00:19:09,150
+جديد file
+
+188
+00:19:15,560 --> 00:19:26,460
+my new python file اخرى
+
+189
+00:19:26,460 --> 00:19:31,540
+كلمة
+
+190
+00:19:31,540 --> 00:19:39,140
+cluster
+
+191
+00:19:39,140 --> 00:19:42,420
+class
+
+192
+00:19:47,320 --> 00:19:52,220
+عن طريق الـ Clustering طبعا انا هاختصر و هاخد نفس
+
+193
+00:19:52,220 --> 00:20:02,760
+الفكرة و هعمل نفس ال split لبعض ال data هاي
+
+194
+00:20:02,760 --> 00:20:03,700
+ال clustering
+
+195
+00:20:15,390 --> 00:20:28,770
+من مكتبة مختلفة اتمنى استدعي الموديل from scipy
+
+196
+00:20:28,770 --> 00:20:33,610
+.cluster
+
+197
+00:20:33,610 --> 00:20:35,950
+.hierarical
+
+198
+00:20:38,670 --> 00:20:44,290
+emport بدي اعمل emport لشيء اتين الشغل الأولى لل
+
+199
+00:20:44,290 --> 00:20:51,210
+linkage اللى هى
+
+200
+00:20:51,210 --> 00:20:55,610
+ال
+
+201
+00:20:55,610 --> 00:20:59,810
+linkage و ال dendogram اللى هى بتمثل عشان لو انا
+
+202
+00:20:59,810 --> 00:21:05,730
+فكرت ارسمها طيب الخطوة
+
+203
+00:21:07,060 --> 00:21:09,920
+التالية ان انا بدي استد الـ Hierarchical Cluster
+
+204
+00:21:16,860 --> 00:21:23,900
+HC Hierarchical Clustering Equal Linkage و ال
+
+205
+00:21:23,900 --> 00:21:28,140
+linkage هذا بده ياخد مني ال attributes ال data set
+
+206
+00:21:28,140 --> 00:21:33,200
+تبعتي و بده يحددله ال linkage criteria اللي موجودة
+
+207
+00:21:33,200 --> 00:21:37,200
+عندنا احنا قولنا في عندنا single و في عندنا ال
+
+208
+00:21:37,200 --> 00:21:41,120
+complete و في عندنا ال average و في عندنا ال word
+
+209
+00:21:41,120 --> 00:21:43,960
+تمام
+
+210
+00:21:46,240 --> 00:21:50,820
+هيك ال algorithm تبعي تم التقسيمة تمت من ناحية
+
+211
+00:21:50,820 --> 00:21:57,940
+hierarchical و بدأ معاهم خطوة خطوة لكن فعليا انا
+
+212
+00:21:57,940 --> 00:22:02,040
+كيف ال cluster كيف بدى اشوفها يعني لو انا راح
+
+213
+00:22:02,040 --> 00:22:06,960
+قلتله هنا print at c ايش بده يعطيني؟
+
+214
+00:22:14,290 --> 00:22:25,250
+sorry هذا ملف HD لازم اعمله run داني
+
+215
+00:22:25,250 --> 00:22:37,750
+قائمة من تلاتين أو list من تلاتين element فيها
+
+216
+00:22:37,750 --> 00:22:40,170
+أرقام العناصر اللي موجودة عندى
+
+217
+00:22:42,940 --> 00:22:47,220
+ومين أقرب عنصر كان لها العملية محتاجة تتجمع
+
+218
+00:22:47,220 --> 00:23:00,840
+انستانس انستانس انستانس
+
+219
+00:23:00,840 --> 00:23:01,320
+انستانس انستانس انستانس انستانس انستانس انستانس
+
+220
+00:23:06,600 --> 00:23:10,320
+وهي ال distance أو قيمة ال linkage أو ال distance
+
+221
+00:23:10,320 --> 00:23:16,220
+اللي نشتغل عليها وكيف تحت أي cluster بنضمن يعني ال
+
+222
+00:23:16,220 --> 00:23:20,060
+points صفر و أربعة المسافة بينهم وهي ال cluster
+
+223
+00:23:20,060 --> 00:23:24,040
+اللي بعده طبعا كل نقطة زي ما قلنا سابقا هي بدأتبع
+
+224
+00:23:24,040 --> 00:23:27,560
+بعضهم كل cluster بدأ يشتغل كل نقطة كانت cluster
+
+225
+00:23:27,560 --> 00:23:31,980
+لكن النص اللي زي هذا غير مفهوم عشان انا استوعبه صح
+
+226
+00:23:31,980 --> 00:23:37,760
+يلزمني ان ارسمه يلزمني ان ارسمه طيب عشان انا ارسمه
+
+227
+00:23:37,760 --> 00:23:51,160
+بس خليني هنا نحط comment and import and build
+
+228
+00:24:05,560 --> 00:24:11,260
+Hierarchical cluster model
+
+229
+00:24:16,260 --> 00:24:21,000
+خلّينا من جزئية الرسم انتهينا منها الان او عفوًا
+
+230
+00:24:21,000 --> 00:24:23,980
+الطباعة بدي اروح على جزئية الرسم عشان في عند
+
+231
+00:24:23,980 --> 00:24:30,900
+المكتب المشهورة اللي هي ال math plot library ال
+
+232
+00:24:30,900 --> 00:24:34,700
+math اختصار ل math plot library تحتمل للرسم هبقى
+
+233
+00:24:34,700 --> 00:24:45,930
+بقوله import by plot python plotواختصرها بلت بيثون
+
+234
+00:24:45,930 --> 00:24:51,230
+بروفيشنال الان الخطوة اللى هشتغل عليها
+
+235
+00:24:53,810 --> 00:24:57,570
+لأن أنا لن أتعامل مع ال labels اللي موجودة عندي
+
+236
+00:24:57,570 --> 00:25:02,650
+فانا بدي اضع ال range و اعمل index للنقاط اللي
+
+237
+00:25:02,650 --> 00:25:08,190
+موجودة عندي هان هروح انا في عندي الخطوة اللي
+
+238
+00:25:08,190 --> 00:25:11,430
+استدعيناها تبع الترسم مافيها مشكلة انتهينا هروح
+
+239
+00:25:11,430 --> 00:25:20,170
+اقول له انا ال label list تبعتي تساوي
+
+240
+00:25:20,170 --> 00:25:20,810
+ال range
+
+241
+00:25:29,390 --> 00:25:33,110
+عند تلاتين element تبدأ نقاط تأخذ واحد واحدة لان
+
+242
+00:25:33,110 --> 00:25:37,530
+انا بدي ارسمهم على شكل ديندوجرام ليس حد من نقطة
+
+243
+00:25:37,530 --> 00:25:37,810
+صفر
+
+244
+00:25:40,690 --> 00:25:47,390
+فمش هارسمه على ال X axis و ال Y في ال 2D plane في
+
+245
+00:25:47,390 --> 00:25:50,190
+ال X و Y فمش هبدأ من عند النقطة صفر هبدأ من عند
+
+246
+00:25:50,190 --> 00:25:54,010
+النقطة واحد و ال range تبعتي ال واحد و التلاتين
+
+247
+00:25:54,010 --> 00:26:00,310
+هذا غير متضمن فيهم فهيكون عندي ال list تبعتي هان
+
+248
+00:26:00,310 --> 00:26:05,090
+تلاتين element تلاتين element بناء على ال list
+
+249
+00:26:05,090 --> 00:26:09,620
+اللي موجودة على ال range اللي موجود عنديطيب هذه مش
+
+250
+00:26:09,620 --> 00:26:13,700
+كتير لها علاقة بالرسم يعني ممكن انا احطها فوق لكن
+
+251
+00:26:13,700 --> 00:26:19,160
+هتلزمني فعليا جزئية الرسم بشكل كبير طيب الان بدي
+
+252
+00:26:19,160 --> 00:26:24,980
+.. بس انا عشان اقول انه الان انا بدت احضر لل
+
+253
+00:26:24,980 --> 00:26:37,400
+dendrogram بدي ارسم plot the dendrogram
+
+254
+00:26:47,630 --> 00:26:58,430
+make list list for labels for هي المفروض ال
+
+255
+00:26:58,430 --> 00:27:02,750
+instance list instance
+
+256
+00:27:02,750 --> 00:27:12,730
+list instance
+
+257
+00:27:12,730 --> 00:27:16,650
+list او ساهم بال list ساهم بالاسهل
+
+258
+00:27:19,200 --> 00:27:25,260
+sample list for data
+
+259
+00:27:25,260 --> 00:27:31,460
+samples تمام
+
+260
+00:27:31,460 --> 00:27:34,980
+الآن
+
+261
+00:27:34,980 --> 00:27:42,520
+عملت import import
+
+262
+00:27:42,520 --> 00:27:48,440
+لل by blot library
+
+263
+00:27:55,150 --> 00:28:01,110
+خطوة اللي بعد هيك في داخل ال plt بدي اجهز للصورة
+
+264
+00:28:01,110 --> 00:28:08,310
+هي figure figure
+
+265
+00:28:08,310 --> 00:28:15,050
+حجم الصورة جداش بدي احددله يا ال f size fig size
+
+266
+00:28:15,050 --> 00:28:24,730
+equal ولي اكون مثلا عشرة عرض وسبعةأنا فعليا الارض
+
+267
+00:28:24,730 --> 00:28:30,950
+عندي هتكون تلاتين و بخلي الارتفاع خمستاشر خليني
+
+268
+00:28:30,950 --> 00:28:33,470
+أشوف كيف نتيجتها هنا بس في الآخر يعني في الآخر هي
+
+269
+00:28:33,470 --> 00:28:38,190
+حصورة هتظهر في ال area الخاصة بال plot اللي موجودة
+
+270
+00:28:38,190 --> 00:28:43,810
+عندها هتشوفها لما نعند الرد طيب تمام ال figure هذه
+
+271
+00:28:43,810 --> 00:28:48,450
+خلاص أنا عشان أضيف ال .. بدي أسبع الآن ال
+
+272
+00:28:48,450 --> 00:28:52,650
+dendrogram ال dendrogram بتاخد مني مجموعةعناصر
+
+273
+00:28:52,650 --> 00:28:57,730
+بدأت أخد مني ال model هذه ال axis ال model تبعي
+
+274
+00:28:57,730 --> 00:29:03,330
+بدأ أخد مني ال orientation ال orientation انا ..
+
+275
+00:29:03,330 --> 00:29:07,030
+ال .. ال .. ال .. الاتجاه تبع الرسم تبعه بيكون عمو
+
+276
+00:29:07,030 --> 00:29:14,890
+.. أفقي ولا عمودي ولا كيف انا هروح أقوله ال top ال
+
+277
+00:29:14,890 --> 00:29:20,470
+labels تبعت ال x axis انا
+
+278
+00:29:20,470 --> 00:29:21,570
+في عندي ال sample list
+
+279
+00:29:25,360 --> 00:29:31,140
+الترتيب الـ distance distance
+
+280
+00:29:31,140 --> 00:29:37,820
+source الان احنا متفقين ان ال element موجودة
+
+281
+00:29:37,820 --> 00:29:42,580
+sequential 1 2 3 4 5 6 هذا ال sample data لكن مش
+
+282
+00:29:42,580 --> 00:29:49,780
+بالضرورة ال instance الأولى هي الأول عملية الدمج
+
+283
+00:29:49,780 --> 00:29:55,080
+هتتم بين اقصر two distances لما انا بقول رتب ليهم
+
+284
+00:29:55,080 --> 00:29:57,140
+تساعدي او تنازلي
+
+285
+00:30:10,640 --> 00:30:14,480
+descending فانا ركبتهم ترتيب تنازلي عشان فعليا
+
+286
+00:30:14,480 --> 00:30:18,640
+تسائق descending تنازلي عشان يبدأ يقول من المسافة
+
+287
+00:30:18,640 --> 00:30:23,980
+الأكبر بين من تم عملية الدمج طب أنا جماعة الخير لو
+
+288
+00:30:23,980 --> 00:30:26,840
+انتوا بتستخدموا ال bython ال by chart المفروض في
+
+289
+00:30:26,840 --> 00:30:31,400
+عندك library هان بتوضحلك كل ال arguments بتديك
+
+290
+00:30:31,400 --> 00:30:35,540
+تفاصيل كاملة او بتديكوا تفاصيل كاملة عن العناصر او
+
+291
+00:30:35,540 --> 00:30:39,500
+اللي انتوا بتشتغلوها على سبيل المثال احنا شغالين
+
+292
+00:30:39,500 --> 00:30:46,760
+وينهي الـ descending الـ
+
+293
+00:30:46,760 --> 00:30:49,720
+distance for each node and order
+
+294
+00:30:59,460 --> 00:31:04,880
+أقصر أو أكبر مسافات هيبدأ يرتب ليهم بالترتيب
+
+295
+00:31:04,880 --> 00:31:08,540
+التنازل اللي موجود عندي يعني اقصر او اكبر مسافات
+
+296
+00:31:08,540 --> 00:31:09,360
+اقصر او اكبر مسافات هيبدأ يرتب ليهم بالترتيب
+
+297
+00:31:09,360 --> 00:31:09,980
+التنازل اللي موجود عندي اقصر اقصر او اكبر مسافات
+
+298
+00:31:09,980 --> 00:31:15,740
+هيبدأ يرتب ليهم بالترتيب
+
+299
+00:31:15,740 --> 00:31:19,300
+التنازل اللي موجود عندي اقصر اقصر اقصر اقصر اقصر
+
+300
+00:31:19,300 --> 00:31:22,690
+اقصر اقصر اقصر اقصأفضهر الـ leaf و العدد ال
+
+301
+00:31:22,690 --> 00:31:30,250
+elements اللي فيها I show leaf count و الخيار true
+
+302
+00:31:30,250 --> 00:31:36,050
+هى كده اندغرام جهز المفروض بقى اللى عندي انا اروح
+
+303
+00:31:36,050 --> 00:31:44,450
+اقوله ال plot blt.show
+
+304
+00:31:57,450 --> 00:32:02,690
+على السريع، اش اللي انا سويته استدعيت الـ
+
+305
+00:32:02,690 --> 00:32:08,430
+Hierarchical Cluster من الـ Science Python استخدمت
+
+306
+00:32:08,430 --> 00:32:13,600
+الـ linkage والددومجرامالان الـ hierarchical الـ
+
+307
+00:32:13,600 --> 00:32:16,740
+cage قلت له هى ال data set و هى ال attributes اللى
+
+308
+00:32:16,740 --> 00:32:20,620
+موجودة عندى حضرت list أو قائمة للعناصر اللى موجودة
+
+309
+00:32:20,620 --> 00:32:23,680
+هجرب الآن عدى استخدم ال labels بدل ال label list
+
+310
+00:32:23,680 --> 00:32:28,160
+أشوف تظهر أسماءها اللى موجودة عندى ولا لأ بس مش
+
+311
+00:32:28,160 --> 00:32:31,340
+هتسفيد منها لأن كلهم هيظهروا نفس القائمة خلينا
+
+312
+00:32:31,340 --> 00:32:35,480
+نعمل بعد هيك رسمتهم استدعيت المكتب تبع ال python
+
+313
+00:32:35,480 --> 00:32:40,360
+ال matlab plot libraryعملت فيها figure حددت لها ال
+
+314
+00:32:40,360 --> 00:32:44,760
+size وانشأت في داخلها ديندو جرام الديندو جرام هذا
+
+315
+00:32:44,760 --> 00:32:51,920
+بيحتوي على مجموعة العناصر التالية ال cluster و ال
+
+316
+00:32:51,920 --> 00:32:54,960
+orientation اللي بدرسون فيها و ال labels و ال
+
+317
+00:32:54,960 --> 00:32:59,260
+distance إلى أخره الأمور بتهيألي تمام خلينا نعمل
+
+318
+00:32:59,260 --> 00:32:59,500
+run
+
+319
+00:33:04,350 --> 00:33:09,090
+حيّر رسمة ظهرت لو انا فكرت ان اكبر الرسمة بالشكل
+
+320
+00:33:09,090 --> 00:33:12,810
+هذا او
+
+321
+00:33:12,810 --> 00:33:16,090
+اذا بدي انا اكبرها هيك كمان لان انا فعليا انا
+
+322
+00:33:16,090 --> 00:33:19,670
+عملها تلاتين في خمستاشر فارتفاعها خمستاشر و عرضها
+
+323
+00:33:19,670 --> 00:33:26,170
+تلاتين لاحظوا ان هاي بقول هان هاي جسملي فعليا بقول
+
+324
+00:33:26,170 --> 00:33:29,870
+التقسيمة تبعتك هذي انسب عبارة عن two clusters اذا
+
+325
+00:33:29,870 --> 00:33:33,800
+انت بتجسمهم في المستوى هذا في two clustersالأخضر
+
+326
+00:33:33,800 --> 00:33:38,180
+والأحمر لكن كذلك ان في عندي cluster هان ال
+
+327
+00:33:38,180 --> 00:33:42,020
+variation بينهم قليلة جدا هيها فممكن انا اخد هذه
+
+328
+00:33:42,020 --> 00:33:44,980
+في cluster لحالي وهذه في cluster لحالي ايش ال
+
+329
+00:33:44,980 --> 00:33:49,120
+elements هيهم ال instances ال instances بدي اعيد
+
+330
+00:33:49,120 --> 00:33:51,840
+الرسم يا جماعة الخير بدي اعيد الرسم على السريع او
+
+331
+00:33:51,840 --> 00:33:55,960
+بدي اعيد ال code على السريع واروح استبدل بدل ال
+
+332
+00:33:55,960 --> 00:34:00,220
+sample list هان بدي اروح استخدم ال labels اللي هي
+
+333
+00:34:00,220 --> 00:34:09,130
+الحقيقية اللي موجودة عندي هانوهي run ما
+
+334
+00:34:09,130 --> 00:34:15,750
+زبطتش ليش؟ لأن الـ x-axis بدى يتعامل مع number فهو
+
+335
+00:34:15,750 --> 00:34:18,230
+بتعامل مع number فعشان هيك كان ال sample list
+
+336
+00:34:18,230 --> 00:34:25,670
+ضروري جدا بالنسبة لنا ان نتعامل معاه وبهيك الرسمة
+
+337
+00:34:25,670 --> 00:34:27,350
+بتكون صحيحة
+
+338
+00:34:39,030 --> 00:34:44,390
+هذه الرسمة output
+
+339
+00:34:44,390 --> 00:34:59,310
+يهان ال instances او
+
+340
+00:34:59,310 --> 00:35:03,310
+بدلت لو جبت له ascending و run
+
+341
+00:35:07,960 --> 00:35:18,480
+هذه الرسومتين أصبحوا موجودات تمام،
+
+342
+00:35:18,480 --> 00:35:28,060
+لو أنا شريتها بالمرة run
+
+343
+00:35:36,610 --> 00:35:40,190
+ما تغيرش عندى ولا حاجة بالتالي انا ممكن استجنى
+
+344
+00:35:40,190 --> 00:35:46,530
+عنها عفوا اللى المفروض خلّيتها انا كهيران انا
+
+345
+00:35:46,530 --> 00:35:52,010
+بحتفظ باخر الصورة موجودة عشان اقارن لو انا هان
+
+346
+00:35:52,010 --> 00:35:59,990
+قلتله false run
+
+347
+00:36:07,320 --> 00:36:10,520
+الخيارات هي الـ default اللي موجودة عندي يعني هذه
+
+348
+00:36:10,520 --> 00:36:17,000
+وهذه هي
+
+349
+00:36:17,000 --> 00:36:20,520
+عبارة عن مجموعة الخيارات ال default اللي موجودة
+
+350
+00:36:20,520 --> 00:36:24,380
+عندي باستثناء ال algorithm المفروض و تكون ال data
+
+351
+00:36:24,380 --> 00:36:28,360
+set اللي موجودة عندى نفسي اه في شغل مهم جدا لو انا
+
+352
+00:36:28,360 --> 00:36:30,020
+بدى اقارن مثلا بين ال
+
+353
+00:36:34,310 --> 00:36:38,130
+عفوا اللهم صلى الله عليه و سلم يا محمد بين ال
+
+354
+00:36:38,130 --> 00:36:42,970
+clusters بال word و بال single هعيد ال code هذا
+
+355
+00:36:42,970 --> 00:36:48,570
+نفسه تمام لو انا اخدت ال code هذا حتى بما في الرسم
+
+356
+00:36:48,570 --> 00:36:54,870
+يعني okay هان
+
+357
+00:36:54,870 --> 00:36:57,970
+ال code لو انا قلت له هنا ال complete
+
+358
+00:37:03,650 --> 00:37:08,090
+lead أو عشان اقدر اميز بين الرسمتين بدي اضيف title
+
+359
+00:37:08,090 --> 00:37:16,370
+للرسمة هروح اقول له هنا ال blt.title
+
+360
+00:37:16,370 --> 00:37:22,390
+ال title تبع هنا اللي هي single linkage
+
+361
+00:37:31,250 --> 00:37:37,090
+عند الرسم فقط هذا الشغل الوحيد اللي هتتغير عندي
+
+362
+00:37:37,090 --> 00:37:52,610
+complete linkage
+
+363
+00:37:52,610 --> 00:37:58,050
+اللي انا عملت الان two modelsبنعمل ال two models
+
+364
+00:37:58,050 --> 00:38:02,310
+هذه مافيش داعي ان اعملها الان import مجرد ان انا
+
+365
+00:38:02,310 --> 00:38:09,330
+اعمل complete in case جديد عشان هيسميته h1 و هبقى
+
+366
+00:38:09,330 --> 00:38:16,430
+بيسميه h1 فبغض النظر عن التسميات وهيبقى اعمل run
+
+367
+00:38:16,430 --> 00:38:21,750
+هذا المفروض ال algorithm يديني رسمتين الأولى و هي
+
+368
+00:38:21,750 --> 00:38:28,550
+التانية لو انا بدي اكبر بس الصفحه هنا شويةهذا ال
+
+369
+00:38:28,550 --> 00:38:33,730
+complete linkage وهذا ال single linkage لاحظوا
+
+370
+00:38:33,730 --> 00:38:37,770
+معايا اختلفت الترتيبة مع ال single linkage اول ما
+
+371
+00:38:37,770 --> 00:38:41,970
+عمل merge عمل بين ال 26 وال28 هذا في ال complete
+
+372
+00:38:41,970 --> 00:38:48,240
+بينما ال single linkage عمل بين ال 6 وال8في الآخر
+
+373
+00:38:48,240 --> 00:38:51,400
+التوزيعة نعم هي عبارة عن three different clusters
+
+374
+00:38:51,400 --> 00:38:54,660
+او two different clusters واضحة هان يعني هي بحسب
+
+375
+00:38:54,660 --> 00:38:57,480
+الهيراريك اللي بيقول أفضل شغلة هنا هي عبارة عن two
+
+376
+00:38:57,480 --> 00:39:00,180
+clusters اللي انت بدك يعني لكن لو انت بدك تلاتة
+
+377
+00:39:00,180 --> 00:39:03,320
+ممكن تحصل زي ما قلنا سابقا على هان وهذه الفروقات
+
+378
+00:39:03,320 --> 00:39:07,360
+واضحة بالاتلقال لاحظوا انه هان قال لأ مع ال
+
+379
+00:39:07,360 --> 00:39:10,480
+complete قال ممكن تحصل على أربعة كمان different
+
+380
+00:39:10,480 --> 00:39:15,400
+clusters لو نزلت للمستوى هذاهي هدول واحدة تنتين
+
+381
+00:39:15,400 --> 00:39:19,320
+تلاتة اربعة وبهي كده اصبح لدي اجلوميراتيف او
+
+382
+00:39:19,320 --> 00:39:22,640
+Hierarchical Clustering ممكن تديني معلومات عن ال
+
+383
+00:39:22,640 --> 00:39:30,800
+data set اكتر من ان انا موجود اكتر
+
+384
+00:39:30,800 --> 00:39:33,640
+من ال partition ال cluster زي ما قلنا وهي مزيتها
+
+385
+00:39:33,640 --> 00:39:38,240
+لكن تبقى و هده هتركها لإيكوا تعلموها لوحدكوا ان
+
+386
+00:39:38,240 --> 00:39:44,320
+كيف انا ممكن احصلعند اي مستوى انا بدي اجفه انا
+
+387
+00:39:44,320 --> 00:39:47,880
+الآن هو بقول هي ال data set تبعتك وهي رسمتها لو
+
+388
+00:39:47,880 --> 00:39:50,800
+انا بدي افصل ال data set تروح على ال model هذا
+
+389
+00:39:50,800 --> 00:39:57,760
+وتبدأ تجمع فيه لحد مستوى معين يعني ان انا هي 26 26
+
+390
+00:39:57,760 --> 00:40:03,640
+28 21 23 30 هدول اقرب ما يمكن لبعضهم ازوان cluster
+
+391
+00:40:03,640 --> 00:40:10,170
+بعدين 11 13 15 19 12 17تمام؟ لو انت بقى تنزل كمان
+
+392
+00:40:10,170 --> 00:40:14,590
+مستوى هذا اكتر فحسب حاجتك و زي ما قلتلكوا هذه اللي
+
+393
+00:40:14,590 --> 00:40:20,070
+هتركها لإلكوا تشوفوا كيف ممكن انا احصل على ال data
+
+394
+00:40:20,070 --> 00:40:22,630
+set في different clusters لما انا اعتمديت ال
+
+395
+00:40:22,630 --> 00:40:26,730
+hierarchical clustering هذا اللي بديه في الجزء
+
+396
+00:40:26,730 --> 00:40:28,750
+العملي هرفعلكم إياه الآن ان شاء الله تعالى
+
+397
+00:40:28,750 --> 00:40:34,550
+بالاضافة لل python code هذا للي حابب يشتغل اتمنى
+
+398
+00:40:34,550 --> 00:40:36,570
+لكوا فايدة دائما والسلام عليكم ورحمة الله
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/j7QLNeXbOs4_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/j7QLNeXbOs4_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..f8cbb22b06db62fba29567df1b974b5af2619e75
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/j7QLNeXbOs4_raw.json
@@ -0,0 +1 @@
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قرأنا ال data set", "tokens": [3555, 28259, 10632, 3714, 2407, 12984, 4587, 3660, 36145, 13412, 16606, 21984, 12174, 2288, 10721, 8315, 2423, 1412, 992], "avg_logprob": -0.39863280653953553, "compression_ratio": 0.9571428571428572, "no_speech_prob": 6.556510925292969e-07, "words": [{"start": 154.60000000000002, "end": 155.52, "word": "بداية", "probability": 0.76416015625}, {"start": 155.52, "end": 156.0, "word": " موثقة", "probability": 0.771826171875}, {"start": 156.0, "end": 156.06, "word": " إن", "probability": 0.400146484375}, {"start": 156.06, "end": 156.24, "word": " شاء", "probability": 0.968017578125}, {"start": 156.24, "end": 156.7, "word": " الله", "probability": 0.962890625}, {"start": 156.7, "end": 171.36, "word": " قرأنا", "probability": 0.638519287109375}, {"start": 171.36, "end": 171.46, "word": " ال", "probability": 0.8134765625}, {"start": 171.46, "end": 171.64, "word": " data", "probability": 0.5830078125}, {"start": 171.64, "end": 172.14, "word": " set", 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جديدة انا ال .. okay اللي صار عندي هان انه هي ال data set", "tokens": [6027, 20292, 20328, 9640, 16472, 3224, 1975, 9778, 3215, 31439, 6156, 3615, 20292, 995, 2423, 4386, 31767, 5016, 1829, 5016, 11778, 16373, 15042, 18863, 42213, 4724, 1829, 5016, 42213, 3714, 5172, 26108, 10721, 9307, 10874, 16254, 41891, 1975, 8315, 2423, 4386, 1392, 13672, 1829, 20328, 9640, 18871, 16254, 8032, 7649, 16472, 3224, 39896, 2423, 1412, 992], "avg_logprob": -0.2897478070175439, "compression_ratio": 1.4710144927536233, "no_speech_prob": 0.0, "words": [{"start": 827.13, "end": 827.53, "word": "اللي", "probability": 0.751220703125}, {"start": 827.53, "end": 827.87, "word": " صار", "probability": 0.880859375}, {"start": 827.87, "end": 828.25, "word": " انه", "probability": 0.6339111328125}, {"start": 828.25, "end": 828.51, "word": " اخد", "probability": 0.7776692708333334}, {"start": 828.51, "end": 828.67, "word": " هو", "probability": 0.796875}, {"start": 828.67, "end": 829.23, "word": " فعليا", 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على المقارنة اللي موجودة لو عديت هدولة انا اتنين ستة", "tokens": [2655, 2407, 11622, 34268, 50239, 32239, 16472, 2423, 1508, 39896, 27820, 3020, 16472, 2423, 19667, 1975, 2407, 2423, 13630, 16247, 12610, 6075, 18863, 8592, 25720, 13672, 1829, 8978, 3224, 4032, 39896, 4386, 45164, 31767, 5172, 2288, 8032, 3215, 12610, 3660, 6225, 8592, 25720, 46811, 10943, 2423, 1508, 16712, 7649, 1829, 13672, 1829, 31439, 36764, 24401, 8978, 3224, 6225, 8592, 25720, 9122, 8848, 23275, 19446, 41185, 8592, 8978, 3224, 6075, 44945, 16606, 15844, 9673, 4587, 9640, 1863, 3660, 13672, 1829, 3714, 29245, 23328, 3660, 45164, 6225, 16254, 2655, 8032, 3215, 12610, 3660, 1975, 8315, 1975, 2655, 1863, 9957, 8608, 2655, 3660], "avg_logprob": -0.22586634253511334, "compression_ratio": 1.7668161434977578, "no_speech_prob": 3.0994415283203125e-06, "words": [{"start": 847.29, "end": 848.01, "word": "توزعت", "probability": 0.790283203125}, {"start": 848.01, "end": 848.95, "word": " قال", "probability": 0.4814453125}, 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"end": 897.17, "text": "عشرة أو عشرة تمام لكن جال ليه ان في عندي مشكلة انا انه في ال class التالت موزع ما بين فعليا مش pure بالاساس ان القيم تبعته مختلفة من العناصر اللي موجودة وبالتالي قيمة ال contingency matrix هي", "tokens": [3615, 8592, 25720, 34051, 6225, 8592, 25720, 46811, 10943, 44381, 10874, 6027, 32239, 3224, 16472, 8978, 18871, 16254, 37893, 28820, 3660, 1975, 8315, 16472, 3224, 8978, 2423, 1508, 16712, 6027, 2655, 3714, 2407, 11622, 3615, 19446, 49374, 6156, 3615, 20292, 995, 37893, 6075, 20666, 32277, 32277, 16472, 25062, 32640, 6055, 3555, 34268, 3224, 3714, 46456, 46538, 3660, 9154, 18863, 1863, 33546, 2288, 13672, 1829, 3714, 29245, 23328, 3660, 46599, 6027, 2655, 6027, 1829, 12174, 32640, 3660, 2423, 27820, 3020, 8141, 39896], "avg_logprob": -0.24504572916321637, "compression_ratio": 1.619289340101523, "no_speech_prob": 2.9802322387695312e-06, "words": [{"start": 876.25, "end": 876.77, "word": "عشرة", "probability": 0.6328938802083334}, {"start": 876.77, "end": 876.91, 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979.56, "end": 993.68, "text": "اللي هي عندى ال cluster dot اللى هي ال adjusted score نفس الكلام بتاخد منى ال labels اللى موجودة", "tokens": [6027, 20292, 39896, 43242, 7578, 2423, 13630, 5893, 13672, 7578, 39896, 2423, 19871, 6175, 8717, 36178, 2423, 28820, 10943, 39894, 47283, 3215, 9154, 7578, 2423, 16949, 13672, 7578, 3714, 29245, 23328, 3660], "avg_logprob": -0.3181818181818182, "compression_ratio": 1.2608695652173914, "no_speech_prob": 2.980232238769531e-07, "words": [{"start": 979.56, "end": 979.86, "word": "اللي", "probability": 0.36572265625}, {"start": 979.86, "end": 980.0, "word": " هي", "probability": 0.62841796875}, {"start": 980.0, "end": 980.38, "word": " عندى", "probability": 0.5771484375}, {"start": 980.38, "end": 980.5, "word": " ال", "probability": 0.91064453125}, {"start": 980.5, "end": 980.96, "word": " cluster", "probability": 0.62353515625}, {"start": 980.96, "end": 983.44, "word": " dot", "probability": 0.398681640625}, {"start": 983.44, "end": 984.06, "word": " 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1489.43, "end": 1489.97, "word": " الخطوة", "probability": 0.8785400390625}, {"start": 1489.97, "end": 1490.09, "word": " اللى", "probability": 0.705322265625}, {"start": 1490.09, "end": 1490.63, "word": " هشتغل", "probability": 0.8505859375}, {"start": 1490.63, "end": 1491.23, "word": " عليها", "probability": 0.97998046875}], "temperature": 1.0}, {"id": 59, "seek": 152081, "start": 1493.81, "end": 1520.81, "text": "لأن أنا لن أتعامل مع ال labels اللي موجودة عندي فانا بدي اضع ال range و اعمل index للنقاط اللي موجودة عندي هان هروح انا في عندي الخطوة اللي استدعيناها تبع الترسم مافيها مشكلة انتهينا هروح اقول له انا ال label list تبعتي تساوي ال range", "tokens": [1211, 33456, 41850, 5296, 1863, 5551, 2655, 3615, 10943, 1211, 20449, 2423, 16949, 13672, 1829, 3714, 29245, 23328, 3660, 18871, 16254, 6156, 7649, 995, 4724, 16254, 1975, 11242, 3615, 2423, 3613, 4032, 1975, 25957, 1211, 8186, 5296, 1211, 1863, 4587, 41193, 13672, 1829, 3714, 29245, 23328, 3660, 18871, 16254, 8032, 7649, 8032, 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0.6852620442708334}, {"start": 1508.85, "end": 1508.99, "word": " تبع", "probability": 0.6420084635416666}, {"start": 1508.99, "end": 1509.39, "word": " الترسم", "probability": 0.635986328125}, {"start": 1509.39, "end": 1509.81, "word": " مافيها", "probability": 0.81884765625}, {"start": 1509.81, "end": 1510.21, "word": " مشكلة", "probability": 0.974609375}, {"start": 1510.21, "end": 1510.73, "word": " انتهينا", "probability": 0.823974609375}, {"start": 1510.73, "end": 1511.43, "word": " هروح", "probability": 0.888671875}, {"start": 1511.43, "end": 1511.63, "word": " اقول", "probability": 0.796142578125}, {"start": 1511.63, "end": 1511.73, "word": " له", "probability": 0.51123046875}, {"start": 1511.73, "end": 1511.91, "word": " انا", "probability": 0.7193603515625}, {"start": 1511.91, "end": 1512.17, "word": " ال", "probability": 0.4482421875}, {"start": 1512.17, "end": 1512.69, "word": " label", "probability": 0.984375}, {"start": 1512.69, "end": 1514.41, "word": " list", "probability": 0.732421875}, {"start": 1514.41, "end": 1517.03, "word": " تبعتي", "probability": 0.9161376953125}, {"start": 1517.03, "end": 1520.17, "word": " تساوي", "probability": 0.8895263671875}, {"start": 1520.17, "end": 1520.41, "word": " ال", "probability": 0.94873046875}, {"start": 1520.41, "end": 1520.81, "word": " range", "probability": 0.953125}], "temperature": 1.0}, {"id": 60, "seek": 153781, "start": 1529.39, "end": 1537.81, "text": "عند تلاتين element تبدأ نقاط تأخذ واحد واحدة لان انا بدي ارسمهم على شكل ديندوجرام ليس حد من نقطة صفر", "tokens": [3615, 41260, 6055, 1211, 9307, 9957, 4478, 6055, 44510, 10721, 8717, 4587, 41193, 6055, 10721, 9778, 8848, 36764, 24401, 36764, 24401, 3660, 5296, 7649, 1975, 8315, 4724, 16254, 1975, 2288, 38251, 16095, 15844, 13412, 28820, 11778, 9957, 3215, 29245, 2288, 10943, 32239, 3794, 11331, 3215, 9154, 8717, 47432, 3660, 20328, 5172, 2288], "avg_logprob": -0.5421579963756058, "compression_ratio": 1.3488372093023255, "no_speech_prob": 1.8477439880371094e-06, "words": [{"start": 1529.39, "end": 1529.99, "word": "عند", "probability": 0.3143310546875}, {"start": 1529.99, "end": 1530.59, "word": " تلاتين", "probability": 0.74908447265625}, {"start": 1530.59, "end": 1530.95, "word": " element", "probability": 0.416015625}, {"start": 1530.95, "end": 1531.87, "word": " تبدأ", "probability": 0.5142008463541666}, {"start": 1531.87, "end": 1532.19, "word": " نقاط", "probability": 0.74951171875}, {"start": 1532.19, "end": 1532.49, "word": " تأخذ", "probability": 0.66339111328125}, {"start": 1532.49, "end": 1532.71, "word": " واحد", "probability": 0.95458984375}, {"start": 1532.71, "end": 1532.99, "word": " واحدة", "probability": 0.7770182291666666}, {"start": 1532.99, "end": 1533.11, "word": " لان", "probability": 0.259033203125}, {"start": 1533.11, "end": 1533.21, "word": " انا", "probability": 0.62939453125}, {"start": 1533.21, "end": 1533.47, "word": " بدي", "probability": 0.36083984375}, {"start": 1533.47, "end": 1533.99, 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plane", "probability": 0.892578125}, {"start": 1547.11, "end": 1547.39, "word": " في", "probability": 0.3154296875}, {"start": 1547.39, "end": 1547.49, "word": " ال", "probability": 0.77880859375}, {"start": 1547.49, "end": 1547.65, "word": " X", "probability": 0.8173828125}, {"start": 1547.65, "end": 1547.81, "word": " و", "probability": 0.91015625}, {"start": 1547.81, "end": 1548.03, "word": " Y", "probability": 0.81982421875}, {"start": 1548.03, "end": 1548.55, "word": " فمش", "probability": 0.8790690104166666}, {"start": 1548.55, "end": 1548.81, "word": " هبدأ", "probability": 0.7872721354166666}, {"start": 1548.81, "end": 1548.91, "word": " من", "probability": 0.9541015625}, {"start": 1548.91, "end": 1549.05, "word": " عند", "probability": 0.91357421875}, {"start": 1549.05, "end": 1549.45, "word": " النقطة", "probability": 0.8502604166666666}, {"start": 1549.45, "end": 1549.65, "word": " صفر", "probability": 0.77294921875}, {"start": 1549.65, "end": 1549.93, "word": " هبدأ", 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element", "probability": 0.8466796875}, {"start": 1562.67, "end": 1563.31, "word": " تلاتين", "probability": 0.950927734375}, {"start": 1563.31, "end": 1563.69, "word": " element", "probability": 0.9580078125}, {"start": 1563.69, "end": 1564.03, "word": " بناء", "probability": 0.955078125}, {"start": 1564.03, "end": 1564.35, "word": " على", "probability": 0.71826171875}, {"start": 1564.35, "end": 1564.77, "word": " ال", "probability": 0.85400390625}, {"start": 1564.77, "end": 1565.09, "word": " list", "probability": 0.97265625}, {"start": 1565.09, "end": 1565.51, "word": " اللي", "probability": 0.865478515625}, {"start": 1565.51, "end": 1566.05, "word": " موجودة", "probability": 0.9796142578125}, {"start": 1566.05, "end": 1566.27, "word": " على", "probability": 0.740234375}, {"start": 1566.27, "end": 1566.37, "word": " ال", "probability": 0.96630859375}, {"start": 1566.37, "end": 1566.57, "word": " range", "probability": 0.94482421875}, {"start": 1566.57, "end": 1566.71, "word": " 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code", "probability": 0.96630859375}, {"start": 2033.12, "end": 2033.28, "word": " على", "probability": 0.919921875}, {"start": 2033.28, "end": 2033.7, "word": " السريع", "probability": 0.99365234375}, {"start": 2033.7, "end": 2034.32, "word": " واروح", "probability": 0.8675537109375}, {"start": 2034.32, "end": 2035.3, "word": " استبدل", "probability": 0.93994140625}, {"start": 2035.3, "end": 2035.82, "word": " بدل", "probability": 0.982421875}, {"start": 2035.82, "end": 2035.96, "word": " ال", "probability": 0.86572265625}, {"start": 2035.96, "end": 2036.46, "word": " sample", "probability": 0.68310546875}, {"start": 2036.46, "end": 2037.02, "word": " list", "probability": 0.88818359375}, {"start": 2037.02, "end": 2037.3, "word": " هان", "probability": 0.765625}, {"start": 2037.3, "end": 2037.5, "word": " بدي", "probability": 0.91943359375}, {"start": 2037.5, "end": 2037.64, "word": " اروح", "probability": 0.8561197916666666}, {"start": 2037.64, "end": 2038.14, "word": " استخدم", 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بالنسبة لنا ان نتعامل معاه وبهيك الرسمة بتكون صحيحة", "tokens": [2407, 3224, 1829, 1190, 19446, 30767, 3555, 9566, 2655, 8592, 32239, 8592, 22807, 5296, 33456, 2423, 39184, 2031, 12, 24633, 47525, 7578, 7251, 2655, 3615, 10943, 1211, 20449, 1230, 6156, 3224, 2407, 39894, 3615, 10943, 1211, 20449, 1230, 6156, 3615, 8592, 7649, 39896, 4117, 25961, 2423, 6889, 1329, 48812, 2288, 13063, 1829, 10874, 28259, 20666, 1863, 35457, 3660, 5296, 8315, 16472, 8717, 2655, 3615, 10943, 1211, 20449, 40294, 46599, 3224, 1829, 4117, 34892, 38251, 3660, 39894, 30544, 20328, 5016, 1829, 5016, 3660], "avg_logprob": -0.2748494004628744, "compression_ratio": 1.5193370165745856, "no_speech_prob": 1.1920928955078125e-07, "words": [{"start": 2044.27, "end": 2044.59, "word": "وهي", "probability": 0.5358072916666666}, {"start": 2044.59, "end": 2044.81, "word": " run", "probability": 0.31982421875}, {"start": 2044.81, "end": 2049.13, "word": " ما", "probability": 0.1875}, {"start": 2049.13, "end": 2049.81, "word": " زبطتش", "probability": 0.816796875}, {"start": 2049.81, "end": 2050.39, "word": " ليش؟", "probability": 0.70263671875}, {"start": 2050.39, "end": 2050.81, "word": " لأن", "probability": 0.869140625}, {"start": 2050.81, "end": 2051.49, "word": " الـ", "probability": 0.603515625}, {"start": 2051.49, "end": 2051.95, "word": " x", "probability": 0.389404296875}, {"start": 2051.95, "end": 2052.79, "word": "-axis", "probability": 0.809326171875}, {"start": 2052.79, "end": 2053.77, "word": " بدى", "probability": 0.44976806640625}, {"start": 2053.77, "end": 2054.17, "word": " يتعامل", "probability": 0.95537109375}, {"start": 2054.17, "end": 2054.33, "word": " مع", "probability": 0.9833984375}, {"start": 2054.33, "end": 2054.85, "word": " number", "probability": 0.55322265625}, {"start": 2054.85, "end": 2055.75, "word": " فهو", "probability": 0.8935546875}, {"start": 2055.75, "end": 2056.13, "word": " بتعامل", "probability": 0.8934326171875}, {"start": 2056.13, "end": 2056.23, "word": " مع", "probability": 0.9892578125}, {"start": 2056.23, "end": 2056.49, "word": " number", "probability": 0.830078125}, {"start": 2056.49, "end": 2057.11, "word": " فعشان", "probability": 0.8326416015625}, {"start": 2057.11, "end": 2057.29, "word": " هيك", "probability": 0.5445556640625}, {"start": 2057.29, "end": 2057.47, "word": " كان", "probability": 0.86767578125}, {"start": 2057.47, "end": 2057.59, "word": " ال", "probability": 0.7431640625}, {"start": 2057.59, "end": 2057.83, "word": " sample", "probability": 0.87939453125}, {"start": 2057.83, "end": 2058.23, "word": " list", "probability": 0.88232421875}, {"start": 2058.23, "end": 2059.05, "word": " ضروري", "probability": 0.8868408203125}, {"start": 2059.05, "end": 2060.65, "word": " جدا", "probability": 0.77099609375}, {"start": 2060.65, "end": 2061.11, "word": " بالنسبة", "probability": 0.9888916015625}, {"start": 2061.11, "end": 2061.39, "word": " لنا", "probability": 0.704345703125}, {"start": 2061.39, "end": 2061.59, "word": " ان", "probability": 0.484130859375}, {"start": 2061.59, "end": 2062.15, "word": " نتعامل", "probability": 0.9669921875}, {"start": 2062.15, "end": 2062.99, "word": " معاه", "probability": 0.87060546875}, {"start": 2062.99, "end": 2065.31, "word": " وبهيك", "probability": 0.845947265625}, {"start": 2065.31, "end": 2065.67, "word": " الرسمة", "probability": 0.9573567708333334}, {"start": 2065.67, "end": 2066.57, "word": " بتكون", "probability": 0.82958984375}, {"start": 2066.57, "end": 2067.35, "word": " صحيحة", "probability": 0.97041015625}], "temperature": 1.0}, {"id": 80, "seek": 210331, "start": 2079.03, "end": 2103.31, "text": "هذه الرسمة output يهان ال instances او بدلت لو جبت له ascending و run", "tokens": [3224, 24192, 34892, 38251, 3660, 5598, 7251, 3224, 7649, 2423, 14519, 1975, 2407, 47525, 1211, 2655, 45164, 10874, 3555, 2655, 46740, 15526, 2029, 4032, 1190], "avg_logprob": -0.5970553136788882, "compression_ratio": 1.0769230769230769, "no_speech_prob": 0.0, "words": 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العملي هرفعلكم إياه الآن ان شاء الله تعالى بالاضافة لل python code هذا للي حابب يشتغل اتمنى لكوا فايدة دائما والسلام عليكم ورحمة الله", "tokens": [39237, 10943, 22807, 45164, 16472, 2655, 4724, 4587, 7578, 6055, 1863, 11622, 1211, 9122, 2304, 7649, 3714, 14851, 2407, 7578, 23758, 1975, 4117, 2655, 2288, 6156, 5016, 35457, 11331, 26108, 2655, 4117, 4032, 30767, 1829, 19446, 12174, 1211, 2655, 23275, 14407, 29538, 13672, 1829, 8032, 2655, 31747, 11296, 5296, 28814, 23275, 14407, 6055, 8592, 38688, 14407, 9122, 33911, 3714, 43020, 1975, 8315, 1975, 5016, 36520, 15844, 2423, 1412, 992, 8978, 819, 23313, 5296, 15042, 1975, 8315, 1975, 34268, 2304, 16254, 2655, 2423, 35250, 804, 596, 48673, 23758, 13672, 1829, 4724, 16254, 3224, 8978, 25724, 11622, 38207, 18863, 2304, 20292, 8032, 28480, 3615, 23275, 2304, 11933, 25528, 3224, 6024, 48506, 16472, 13412, 16606, 21984, 37279, 6027, 7578, 20666, 46958, 31845, 3660, 24976, 38797, 3089, 23758, 5296, 20292, 11331, 16758, 3555, 7251, 8592, 2655, 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2411.73, "word": " اكتر", "probability": 0.8662109375}, {"start": 2411.73, "end": 2412.83, "word": " فحسب", "probability": 0.6514485677083334}, {"start": 2412.83, "end": 2413.15, "word": " حاجتك", "probability": 0.848876953125}, {"start": 2413.15, "end": 2413.25, "word": " و", "probability": 0.8212890625}, {"start": 2413.25, "end": 2413.39, "word": " زي", "probability": 0.645751953125}, {"start": 2413.39, "end": 2413.49, "word": " ما", "probability": 0.95849609375}, {"start": 2413.49, "end": 2414.05, "word": " قلتلكوا", "probability": 0.90078125}, {"start": 2414.05, "end": 2414.43, "word": " هذه", "probability": 0.427978515625}, {"start": 2414.43, "end": 2414.59, "word": " اللي", "probability": 0.611328125}, {"start": 2414.59, "end": 2414.99, "word": " هتركها", "probability": 0.9078369140625}, {"start": 2414.99, "end": 2415.43, "word": " لإلكوا", "probability": 0.78155517578125}, {"start": 2415.43, "end": 2415.87, "word": " تشوفوا", "probability": 0.9749755859375}, {"start": 2415.87, "end": 2416.09, "word": " كيف", "probability": 0.9609375}, {"start": 2416.09, "end": 2416.49, "word": " ممكن", "probability": 0.963134765625}, {"start": 2416.49, "end": 2417.15, "word": " انا", "probability": 0.736572265625}, {"start": 2417.15, "end": 2418.49, "word": " احصل", "probability": 0.9041341145833334}, {"start": 2418.49, "end": 2419.01, "word": " على", "probability": 0.90478515625}, {"start": 2419.01, "end": 2419.79, "word": " ال", "probability": 0.95751953125}, {"start": 2419.79, "end": 2420.07, "word": " data", "probability": 0.81494140625}, {"start": 2420.07, "end": 2420.47, "word": " set", "probability": 0.9423828125}, {"start": 2420.47, "end": 2420.61, "word": " في", "probability": 0.77587890625}, {"start": 2420.61, "end": 2420.93, "word": " different", "probability": 0.921875}, {"start": 2420.93, "end": 2421.55, "word": " clusters", "probability": 0.9404296875}, {"start": 2421.55, "end": 2421.87, "word": " لما", "probability": 0.760986328125}, {"start": 2421.87, "end": 2422.07, "word": " انا", "probability": 0.83056640625}, {"start": 2422.07, "end": 2422.53, "word": " اعتمديت", "probability": 0.86328125}, {"start": 2422.53, "end": 2422.63, "word": " ال", "probability": 0.98095703125}, {"start": 2422.63, "end": 2423.11, "word": " hierarchical", "probability": 0.5567626953125}, {"start": 2423.11, "end": 2423.61, "word": " clustering", "probability": 0.6929931640625}, {"start": 2423.61, "end": 2424.89, "word": " هذا", "probability": 0.8427734375}, {"start": 2424.89, "end": 2425.25, "word": " اللي", "probability": 0.981201171875}, {"start": 2425.25, "end": 2425.97, "word": " بديه", "probability": 0.5782877604166666}, {"start": 2425.97, "end": 2426.29, "word": " في", "probability": 0.66259765625}, {"start": 2426.29, "end": 2426.73, "word": " الجزء", "probability": 0.9793294270833334}, {"start": 2426.73, "end": 2427.15, "word": " العملي", "probability": 0.9449869791666666}, {"start": 2427.15, "end": 2427.71, "word": " هرفعلكم", "probability": 0.83427734375}, {"start": 2427.71, "end": 2427.93, "word": " إياه", "probability": 0.6172688802083334}, {"start": 2427.93, "end": 2428.15, "word": " الآن", "probability": 0.830078125}, {"start": 2428.15, "end": 2428.29, "word": " ان", "probability": 0.61376953125}, {"start": 2428.29, "end": 2428.43, "word": " شاء", "probability": 0.967529296875}, {"start": 2428.43, "end": 2428.45, "word": " الله", "probability": 0.94384765625}, {"start": 2428.45, "end": 2428.75, "word": " تعالى", "probability": 0.8330078125}, {"start": 2428.75, "end": 2429.31, "word": " بالاضافة", "probability": 0.927001953125}, {"start": 2429.31, "end": 2430.33, "word": " لل", "probability": 0.63916015625}, {"start": 2430.33, "end": 2431.01, "word": " python", "probability": 0.46923828125}, {"start": 2431.01, "end": 2431.41, "word": " code", "probability": 0.966796875}, {"start": 2431.41, "end": 2431.77, "word": " هذا", "probability": 0.9052734375}, {"start": 2431.77, "end": 2432.39, "word": " للي", "probability": 0.740478515625}, {"start": 2432.39, "end": 2432.93, "word": " حابب", "probability": 0.9749348958333334}, {"start": 2432.93, "end": 2433.59, "word": " يشتغل", "probability": 0.97646484375}, {"start": 2433.59, "end": 2434.55, "word": " اتمنى", "probability": 0.83062744140625}, {"start": 2434.55, "end": 2434.75, "word": " لكوا", "probability": 0.77490234375}, {"start": 2434.75, "end": 2435.11, "word": " فايدة", "probability": 0.928955078125}, {"start": 2435.11, "end": 2435.37, "word": " دائما", "probability": 0.8024088541666666}, {"start": 2435.37, "end": 2435.73, "word": " والسلام", "probability": 0.7864583333333334}, {"start": 2435.73, "end": 2436.01, "word": " عليكم", "probability": 0.92138671875}, {"start": 2436.01, "end": 2436.37, "word": " ورحمة", "probability": 0.962890625}, {"start": 2436.37, "end": 2436.57, "word": " الله", "probability": 0.9619140625}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 2437.8398125, "duration_after_vad": 2167.442499999992}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/mLZ1tevgxvs.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/mLZ1tevgxvs.srt
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@@ -0,0 +1,3001 @@
+1
+00:00:05,300 --> 00:00:07,540
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:07,540 --> 00:00:12,300
+اليوم إن شاء الله.. إن شاء الله تعالى، هنكمل في الـ
+
+3
+00:00:12,300 --> 00:00:14,680
+introduction على الـ data mining، نتعرف على الـ data
+
+4
+00:00:14,680 --> 00:00:19,000
+mining tasks، ونشوف الـ tools اللي هنشتغل عليها خلال
+
+5
+00:00:19,000 --> 00:00:26,950
+الفصل الـ.. لكن الـ.. بدنا نعمل review سريعة لما تم
+
+6
+00:00:26,950 --> 00:00:30,170
+عرضه الأسبوع الماضي، بدي واحد منكم على السريع الآن
+
+7
+00:00:30,170 --> 00:00:33,270
+يذكرني سواء كان من الدفتر، من الـ slides، من دماغه،
+
+8
+00:00:33,270 --> 00:00:36,690
+طبعًا لو كان من دماغه أفضل، ما هو، ما هي الـ data
+
+9
+00:00:36,690 --> 00:00:41,270
+mining؟ عرف لي الـ data mining، أه
+
+10
+00:00:41,270 --> 00:00:44,990
+محمد: عملية
+
+11
+00:00:44,990 --> 00:00:47,650
+cleaning و analyzing  الـ data عشان أطلع منها
+
+12
+00:00:47,650 --> 00:00:51,250
+knowledge، more professional definition؟ أعطيني
+
+13
+00:00:51,250 --> 00:00:55,800
+التعريف professional أكتر، كلامك صح لكن إحنا بدنا
+
+14
+00:00:55,800 --> 00:01:02,300
+الآن تعريف رسمي، محمد أحمد فروخ: knowledge discovery
+
+15
+00:01:02,300 --> 00:01:15,800
+كمان non trivial، implicit، useful،
+
+16
+00:01:21,930 --> 00:01:28,370
+أيوة، novel، طيب
+
+17
+00:01:28,370 --> 00:01:32,690
+عرفنا الـ data mining على إنها عبارة عن الـ process
+
+18
+00:01:32,690 --> 00:01:38,270
+for extracting interesting patterns، اللي هي
+
+19
+00:01:38,270 --> 00:01:42,690
+الأنماط المهمة أو المثيرة أو أو إلى آخره، مصبوط؟
+
+20
+00:01:42,690 --> 00:01:47,620
+وقلنا كلمة interesting pattern تعني novel، إنه الـ
+
+21
+00:01:47,620 --> 00:01:50,600
+pattern هذا أو النمط هذا جديد، ما حد شافه قبل هيك
+
+22
+00:01:50,600 --> 00:01:55,640
+previously unseen، non-trivial، مش تقليدي، وطبعًا
+
+23
+00:01:55,640 --> 00:02:00,000
+متكافئات تقريبًا، لكن إذا كنت أنا بتكلم إنه
+
+24
+00:02:00,000 --> 00:02:03,460
+الـ process نفسها non-trivial، إنه العملية مش عملية
+
+25
+00:02:03,460 --> 00:02:06,360
+تقليدية، مش عملية سهلة، مش كل الناس هتقوم فيها،
+
+26
+00:02:06,360 --> 00:02:09,060
+implicit، فهو حقيقي أو valid،
+
+27
+00:02:11,940 --> 00:02:16,100
+نطق Simplest، يعني بين جثتين، مش fake، فده حقيقي موجود
+
+28
+00:02:16,100 --> 00:02:21,160
+في الـ data، و useful عشان يبقى بني عليه action، مفيد
+
+29
+00:02:21,160 --> 00:02:26,200
+للناس، وطبعًا understandable،
+
+30
+00:02:26,200 --> 00:02:32,180
+مفهوم، عشان الناس تقدر تبني عليه action، previously
+
+31
+00:02:32,180 --> 00:02:38,380
+unknown أو unseen، اللي هي novel، تمام، قلنا بعد هيك
+
+32
+00:02:38,380 --> 00:02:43,050
+أن الـ data mining تمر بـ.. أو أي data mining
+
+33
+00:02:43,050 --> 00:02:48,110
+project فيه له سبع مراحل، سبع مراحل بتبدأ من
+
+34
+00:02:48,110 --> 00:02:54,570
+cleaning، integration،
+
+35
+00:02:54,570 --> 00:02:59,910
+selection،
+
+36
+00:02:59,910 --> 00:03:05,630
+transformation،
+
+37
+00:03:05,630 --> 00:03:08,830
+mining،
+
+38
+00:03:14,020 --> 00:03:21,740
+evaluation، و presentation، وعشان
+
+39
+00:03:21,740 --> 00:03:26,160
+ما تنساش من الـ cleaning لحد الـ mining، مرتبط
+
+40
+00:03:26,160 --> 00:03:30,320
+بمصطلح data،
+
+41
+00:03:30,320 --> 00:03:36,000
+cleaning، data integration، data selection، data
+
+42
+00:03:36,000 --> 00:03:40,570
+transformation، data mining، أنا على السريع، cleaning
+
+43
+00:03:40,570 --> 00:03:44,790
+كانت تقتضي مني أن أعالج incomplete data أو الـ
+
+44
+00:03:44,790 --> 00:03:52,270
+missing data، أعمل handling للـ missing data، noisy
+
+45
+00:03:52,270 --> 00:04:00,610
+data، inconsistent data، شو
+
+46
+00:04:00,610 --> 00:04:04,050
+يعني missing data، أن في عندي field ما فيش فيه value،
+
+47
+00:04:04,050 --> 00:04:08,330
+null، والـ field هذا أنا محتاجه، فبالتالي بدي أشوف كيف
+
+48
+00:04:08,330 --> 00:04:12,470
+بدي أعبي الـ value المناسبة أو الحقيقية أو الصحيحة أو
+
+49
+00:04:12,470 --> 00:04:16,750
+القريبة من الصحيحة للـ attributes هذا، noisy إنه
+
+50
+00:04:16,750 --> 00:04:20,010
+فيها خطأ، الـ value واضح فيها خطأ، مثل الراتب بالـ
+
+51
+00:04:20,010 --> 00:04:26,030
+salary أو الراتب بالـ salary، الـ salary بالسالب أو
+
+52
+00:04:26,030 --> 00:04:31,190
+الراتب بالسالب، وبالتالي أنا بدي أنتبه لهذه الشغلة،
+
+53
+00:04:31,190 --> 00:04:32,530
+inconsistent،
+
+54
+00:04:35,480 --> 00:04:40,460
+في two fields متناقضين مع بعض، عمره تلاتين سنة وهو
+
+55
+00:04:40,460 --> 00:04:44,700
+مولوده الألفين، تمام؟ أو mail و pregnant زي ما قلنا
+
+56
+00:04:44,700 --> 00:04:50,440
+سابقا، الـ integration، data integration، أن الـ data
+
+57
+00:04:50,440 --> 00:04:54,700
+source تبعتي أو مصادر البيانات تبعتي مختلفة، فبدي
+
+58
+00:04:54,700 --> 00:04:58,560
+أكون عندي المقدرة على أني أقدر أجمع البيانات هذه
+
+59
+00:04:58,560 --> 00:05:02,020
+عشان تكمل بعضها، وضربنا المثال إنه أنا بدي أشتغل
+
+60
+00:05:02,020 --> 00:05:06,400
+على مشروع يقيم أو يتنبأ لي بتحصيل الطالب في
+
+61
+00:05:06,400 --> 00:05:08,600
+المدرسة بناءً على الحالة الصحية تبعته أو الأرشيف
+
+62
+00:05:08,600 --> 00:05:12,140
+الصحي تبعه، وزارة التربية والتعليم ووزارة الصحة
+
+63
+00:05:12,140 --> 00:05:15,220
+مصدرين مختلفين للبيانات، فبالتالي أنا لازم أقدر
+
+64
+00:05:15,220 --> 00:05:17,740
+أكون عندي التعامل معاهم، وهنا بلزمك تعامل مع
+
+65
+00:05:17,740 --> 00:05:23,620
+البيانات، بلزمك database وبرمجة غالبًا في الـ data
+
+66
+00:05:23,620 --> 00:05:27,670
+selection، اختيار البيانات، بعد ما جمعت البيانات وصارت
+
+67
+00:05:27,670 --> 00:05:32,170
+في عندي huge data أو many attributes، مين اللي بده
+
+68
+00:05:32,170 --> 00:05:34,970
+يظل ومين اللي بده يبقى؟ مين الـ relevant attribute
+
+69
+00:05:34,970 --> 00:05:39,110
+ومين الـ irrelevant؟ وبالتالي أنا مطلوب مني أحذف الـ
+
+70
+00:05:39,110 --> 00:05:42,510
+irrelevant، أحذف الـ redundant attribute وأحذف فقط
+
+71
+00:05:42,510 --> 00:05:47,890
+بالـ relevant attributes، الـ data transformation، الـ
+
+72
+00:05:47,890 --> 00:05:52,070
+rules أو الـ knowledge أو الـ pattern، إحنا اتفقنا
+
+73
+00:05:52,070 --> 00:05:58,170
+أنه في تعريفنا للـ pattern هو عبارة عن group أو
+
+74
+00:05:58,170 --> 00:06:02,930
+ordering parts، repeated parts، مصبوط؟ يعني هذه
+
+75
+00:06:02,930 --> 00:06:07,410
+العناصر أو هذه الـ parts ظهرت بترتيب معين وبنسبة
+
+76
+00:06:07,410 --> 00:06:12,990
+تكرار معينة، في الـ transformation لو كان عندي الـ
+
+77
+00:06:12,990 --> 00:06:18,770
+date of birth، قلنا عدد الـ values اللي عندي كبير
+
+78
+00:06:18,770 --> 00:06:25,450
+جداً وبالتالي بيصير التكرار، الـ pattern، تكرار البتر
+
+79
+00:06:25,450 --> 00:06:31,550
+قليل جدًا، طيب، بهمش أبسط الأمور، يعني كل الناس اللي
+
+80
+00:06:31,550 --> 00:06:35,970
+مولودين في نفس السنة، ممكن أنا أستغني عن الشهر وأستغني
+
+81
+00:06:35,970 --> 00:06:39,090
+عن اليوم، لأنه في الآخر لو سألت أي واحد فيهم
+
+82
+00:06:39,090 --> 00:06:43,390
+مثلًا للناس اللي ولدت في الألفين، قد ايش عمرك يا فلان؟
+
+83
+00:06:44,810 --> 00:06:48,750
+عشرين، مباشرة عشرين أو تسعة عشر، بغض النظر، ليش؟
+
+84
+00:06:48,750 --> 00:06:52,750
+لأن كله مولود في سنة.. فهذه أسهل، وفعليًا ما أبعد
+
+85
+00:06:52,750 --> 00:06:56,130
+عن الحقيقة، بالعكس هي الحقيقة بذاتها، إنه هو مولود
+
+86
+00:06:56,130 --> 00:07:01,490
+الألفين للآن، فنحن نتكلم عن عشرين سنة، طيب، لاحظ أن
+
+87
+00:07:01,490 --> 00:07:08,570
+أنا فعليًا قللت الـ variant data، الاختلاف الكثير في
+
+88
+00:07:08,570 --> 00:07:12,090
+الـ data، قللته، وصار بإمكاني الآن أعتمد على الـ year
+
+89
+00:07:12,090 --> 00:07:16,590
+فقط، أو الأفضل من الـ year كمان أن أروح أعمل الـ age
+
+90
+00:07:16,590 --> 00:07:19,970
+لـ category، بيصير مثلًا والله بتكلم على فئة أطفال،
+
+91
+00:07:19,970 --> 00:07:26,910
+شباب، يافعين، كبار، مثلًا، عجزاء، هذه خمس فئات بدل ما
+
+92
+00:07:26,910 --> 00:07:33,070
+كنت بتعامل مع خمسين، ستين، رقم مختلف، لأ صار عندي
+
+93
+00:07:33,070 --> 00:07:38,710
+هان، وهيك أنا بأضمن أن الـ pattern تبعي صار فيه
+
+94
+00:07:38,710 --> 00:07:42,290
+frequent أكتر، وبالتالي في الـ data transformation،
+
+95
+00:07:42,290 --> 00:07:46,750
+تصير، صحيح، الـ data mining هي عبارة عن الـ task، هو الـ
+
+96
+00:07:46,750 --> 00:07:49,950
+prediction task، اللي أنا بدور فيها فعليًا هي البحث
+
+97
+00:07:49,950 --> 00:07:54,570
+عن المعرفة أو knowledge extraction، اللي بديها الـ
+
+98
+00:07:54,570 --> 00:07:55,770
+selection قبل الـ cleaning
+
+99
+00:08:02,610 --> 00:08:06,110
+أجازك عشان تخفف العدد، أنت اللي عندك، okay، الآن..
+
+100
+00:08:06,110 --> 00:08:12,630
+الآن أنت عندك الـ data set، عندك الـ data set للاجئات
+
+101
+00:08:12,630 --> 00:08:15,870
+فيها value ناقصة أو مفقودة أو فيها value غير صحيحة،
+
+102
+00:08:15,870 --> 00:08:21,250
+ممكن فعليًا تروح تقدر تروح تدور برا أنت عشان تجيبها،
+
+103
+00:08:21,250 --> 00:08:26,850
+الآن بعدين أنا في الـ selection غالبًا ما عنديش.. أنا
+
+104
+00:08:26,850 --> 00:08:29,930
+بقدر أحكم على الأسماء والأرقام، يعني رقم تليفون
+
+105
+00:08:29,930 --> 00:08:34,230
+الشخص مش مهم لصحته، رقم هويته مش مهم لمستوى حالته
+
+106
+00:08:34,230 --> 00:08:38,570
+اجتماعيًا، مصبوط؟ اسمه مش متعلق بتحصيله الدراسي،
+
+107
+00:08:38,570 --> 00:08:40,650
+هذه كلها الـ irrelevant attribute، أنا بقدر أعتمد
+
+108
+00:08:40,650 --> 00:08:44,410
+عليها، مصبوط، وأحذفهم، لكن في عندي مجموعة
+
+109
+00:08:44,410 --> 00:08:46,190
+هتلاقي فيه مجموعة عن الـ attributes أنا ما أقدرش
+
+110
+00:08:46,190 --> 00:08:50,370
+أتكلم عليها، فإيش أحضر؟ أحضر بعد الـ integration، بعد
+
+111
+00:08:50,370 --> 00:08:54,090
+الـ integration، أروح أبدأ أستخدم بعض الـ algorithm
+
+112
+00:08:54,090 --> 00:08:57,370
+اللي تروح تحسب الـ correlation أو الـ dependency بين
+
+113
+00:08:57,370 --> 00:09:01,650
+الـ attributes عشان أقرر مين أشيل ومين أبقى،
+
+114
+00:09:01,650 --> 00:09:06,310
+فبالتالي لأ، لازم تكون فعليًا الـ cleaning number one،
+
+115
+00:09:06,310 --> 00:09:10,470
+لأنه بعد أنت الآن الـ cleaning للـ source الأول، الـ
+
+116
+00:09:10,470 --> 00:09:14,340
+cleaning للـ source الثاني، وبعدين بتيجي لمرحلة الـ
+
+117
+00:09:14,340 --> 00:09:17,500
+integration، لأنه كمان مرة الـ cleaning هذه بتتم
+
+118
+00:09:17,500 --> 00:09:21,420
+بمعرفة الـ source، يعني الآن مصدر بيانات وزارة الصحة،
+
+119
+00:09:21,420 --> 00:09:26,980
+أنا والله في السنة 2005 لـ 2007 مش لاقي حاجة أو في
+
+120
+00:09:26,980 --> 00:09:31,640
+عندي بعض الـ missing values للطفل هذا، زودوني فيهم،
+
+121
+00:09:31,640 --> 00:09:37,440
+قبل ما أفكر في موضوع الـ integration، الآن زي ما
+
+122
+00:09:37,440 --> 00:09:41,350
+قلنا الـ mining هي عبارة عن الـ task اللي أنا فعليًا
+
+123
+00:09:41,350 --> 00:09:44,710
+بدي من خلالها أعمل extract للـ knowledge، بعد هيك
+
+124
+00:09:44,710 --> 00:09:46,410
+الـ knowledge اللي أنا حصلت عليها بدي أعملها
+
+125
+00:09:46,410 --> 00:09:50,550
+evaluation وأعملها presentation، هذا اللي هيكون
+
+126
+00:09:50,550 --> 00:09:55,610
+محطة حضرتنا اليوم في موضوع الـ data mining tasks،
+
+127
+00:09:55,610 --> 00:10:00,790
+لكن كنا سألناكم سؤال أو كنا أعطيناكم شبه واجب للـ
+
+128
+00:10:00,790 --> 00:10:08,660
+discussion، time series data، temporal data، special
+
+129
+00:10:08,660 --> 00:10:18,860
+data، و series، الـ sequence data، أيوة، من يبدأ يسمعنا
+
+130
+00:10:18,860 --> 00:10:23,480
+بالأول، بس اللي حضروا الواجب أو حضروا الكلام ده
+
+131
+00:10:23,480 --> 00:10:29,160
+يرفعوا أيديهم، الشباب، طيب، الآن يعني في عندنا واحد،
+
+132
+00:10:29,160 --> 00:10:38,260
+اثنين، ثلاثة، أربعة، خمسة، ستة، مش جايبين، سبعة، ليش؟ أول
+
+133
+00:10:38,260 --> 00:10:43,240
+محاضرة؟ أول محاضرة.. مش أول محاضرة.. okay، ماشي،
+
+134
+00:10:43,240 --> 00:10:47,500
+الحالة okay.. نرد.. نتمنى من الجميع يكون التزام
+
+135
+00:10:47,500 --> 00:10:50,400
+حديد في الشغلات اللي إحنا بنعطيها.. آه،
+
+136
+00:10:50,400 --> 00:10:55,320
+مؤمن: series.. time series data، بصوت عالي بس،
+
+137
+00:10:55,320 --> 00:10:58,020
+عشان كلنا نسمع، والكاميرا تقدر، ارفع صوتك.. أيوة،
+
+138
+00:10:58,020 --> 00:10:59,400
+it's a series of data،
+
+139
+00:11:02,930 --> 00:11:06,910
+يعني هي عبارة عن مجموعة من البيانات مؤرشفة تبعًا
+
+140
+00:11:06,910 --> 00:11:11,010
+لظهورها الزمني، تمام؟ في حد حصل على شغل غير هيك،
+
+141
+00:11:11,010 --> 00:11:14,150
+شباب، أيوة؟ هو الوصول للبيانات التي اتصل الزمن مع
+
+142
+00:11:14,150 --> 00:11:17,410
+بعضها ببعض، و الوصول لنمط معين يمكن من خلال
+
+143
+00:11:17,410 --> 00:11:21,650
+التنبؤ بالقيم المُتوقعة، هيك أنت بتتكلم على الـ Time
+
+144
+00:11:21,650 --> 00:11:26,270
+Series Mining، تمام؟ لكن إحنا بنتكلم على الـ Time
+
+145
+00:11:26,270 --> 00:11:29,750
+Series Data، أيوة، حسن؟ Data connected to look at
+
+146
+00:11:31,670 --> 00:11:37,190
+data، بيانات بناءً على تغييراتها تبعًا للتسلسل
+
+147
+00:11:37,190 --> 00:11:40,970
+الزمني، يعني بنقول للشباب، كل الـ data اللي
+
+148
+00:11:40,970 --> 00:11:47,510
+مرتبطة بعامل الزمن بنصنفها على إنها إيش؟ الـ Time
+
+149
+00:11:47,510 --> 00:11:50,630
+Series Data، أمثلة، مين بقدر يديني مثال؟ آه، رامي،
+
+150
+00:11:50,630 --> 00:11:53,650
+مثلًا،
+
+151
+00:11:53,650 --> 00:11:58,250
+الأمراض، تطور الأمراض، الـ Time Series،
+
+152
+00:12:02,050 --> 00:12:06,150
+درجات الحرارة والرطوبة، القياسات الطقس بشكل عام،
+
+153
+00:12:06,150 --> 00:12:16,570
+غيره، عدد مثلًا المسافرين خارج البلاد، زيادة الكثافة،
+
+154
+00:12:16,570 --> 00:12:21,210
+السكانية، الكثوف والكسوف، الظاهر الطبيعي، السؤال يا
+
+155
+00:12:21,210 --> 00:12:25,190
+شباب، الفترة الزمنية هذه هل لها better معين؟ يعني كل
+
+156
+00:12:25,190 --> 00:12:29,680
+دقيقة، كل ثانية، كل ساعة، كل يوم، كل.. كده، في الآخر
+
+157
+00:12:29,680 --> 00:12:33,360
+أنت فعليًا جمعت الـ data كيف؟ يعني الآن، تعوضت
+
+158
+00:12:33,360 --> 00:12:37,440
+الأرصاد، تعوضت، الأرصاد بيحاولوا يجمعوا الـ data
+
+159
+00:12:37,440 --> 00:12:41,500
+مثلًا على مدار الأيام، لكن الـ sensor بيزودهم،
+
+160
+00:12:41,500 --> 00:12:47,540
+بيزودهم بالقراءات على مدار الساعة، وبالتالي كل ثانية
+
+161
+00:12:47,540 --> 00:12:52,140
+عنده قراءة، لكن هو متى، بإيش بيحتفظ؟ بالقراءات اللي
+
+162
+00:12:52,140 --> 00:12:57,630
+بيصير فيها تغيير، وبيجي يقولك والله هاي تبع للزمن
+
+163
+00:12:57,630 --> 00:13:00,490
+كان كذا، يعني دائمًا الـ data مرتبط أو تجمع بعامل
+
+164
+00:13:00,490 --> 00:13:11,770
+الزمن، temporal data، temporal data، هاني، الـ temporal
+
+165
+00:13:11,770 --> 00:13:16,750
+.. هاني، هاني، بقول أن الـ temporal data هي عبارة عن
+
+166
+00:13:16,750 --> 00:13:24,080
+data، كنا معنين شغلتين، الـ state، الحالة، والفترة
+
+167
+00:13:24,080 --> 00:13:27,760
+الزمنية اللي ظهرت فيها الحالة هاي، غيره، أنا عبدالله
+
+168
+00:13:27,760 --> 00:13:34,940
+كريم: temporal يعني
+
+169
+00:13:34,940 --> 00:13:38,920
+أنت حصرتها لي في وقت، جبت لي مثال عليها، temporal، شو
+
+170
+00:13:38,920 --> 00:13:43,620
+تعريف الـ temporal data؟
+
+171
+00:13:43,620 --> 00:13:46,300
+طيب، related to time and instance،
+
+172
+00:13:51,130 --> 00:13:57,290
+ما زلت بتتكلم عن الـ time series، الـ state.. الحالة..
+
+173
+00:13:57,290 --> 00:14:00,670
+شو.. التغير اللي في الحالة.. كيف كانت.. يعني
+
+174
+00:14:00,670 --> 00:14:08,190
+أو كأن الآن.. هذا الزمن.. هذا الزمن.. هذا
+
+175
+00:14:08,190 --> 00:14:12,430
+العامل الزمني.. كيف الحالة كانت هان، والحالة كانت
+
+176
+00:14:12,430 --> 00:14:13,330
+هان، والحالة كانت هان،
+
+177
+00:14:22,460 --> 00:14:28,
+
+223
+00:17:36,770 --> 00:17:41,990
+حضرت يا هاشم؟ ماشي، الحل تمام. يعني فعليًا أنا في
+
+224
+00:17:41,990 --> 00:17:45,510
+الـ Data Mining بقدر أشتغل في كل الاتجاهات، سواء في
+
+225
+00:17:45,510 --> 00:17:50,730
+الأرقام؟ طيب، بدي أسأل في الـ Biology، في الـ
+
+226
+00:17:50,730 --> 00:17:55,450
+Geography، في الـ Geology، في كل المجالات أنا ممكن
+
+227
+00:17:55,450 --> 00:17:59,290
+أشتغل بناءً على الـ data اللي موجودة. سؤال اللي بيطرح
+
+228
+00:17:59,290 --> 00:18:05,270
+نفسه الآن: أنا بدي أروح أدرس سوق أو حالة سوق فلسطين
+
+229
+00:18:05,270 --> 00:18:11,430
+للأوراق المالية (يعني بين قوسين بورصة فلسطين). تحت أي
+
+230
+00:18:11,430 --> 00:18:17,040
+نوع من أنواع الـ data؟  time series. في حد بيقول
+
+231
+00:18:17,040 --> 00:18:22,320
+غير الكلام هذا؟ special .. special .. special ..
+
+232
+00:18:22,320 --> 00:18:26,140
+special .. special .. special .. special ..
+
+233
+00:18:26,140 --> 00:18:27,200
+special .. special .. special .. special ..
+
+234
+00:18:27,200 --> 00:18:28,440
+special .. special .. special .. special ..
+
+235
+00:18:28,440 --> 00:18:29,840
+special .. special .. special .. special ..
+
+236
+00:18:29,840 --> 00:18:29,860
+special .. special .. special .. special ..
+
+237
+00:18:29,860 --> 00:18:29,880
+special .. special .. special .. special ..
+
+238
+00:18:29,880 --> 00:18:30,120
+special .. special .. special .. special ..
+
+239
+00:18:30,120 --> 00:18:30,180
+special .. special .. special .. special ..
+
+240
+00:18:30,180 --> 00:18:31,320
+special .. special .. special .. special ..
+
+241
+00:18:31,320 --> 00:18:31,620
+special .. special .. special .. special ..
+
+242
+00:18:31,620 --> 00:18:31,880
+special .. special .. special .. special ..
+
+243
+00:18:31,880 --> 00:18:34,940
+special .. special .. special ..
+
+244
+00:18:34,940 --> 00:18:41,320
+special
+
+245
+00:18:41,320 --> 00:18:43,570
+.. special .. special .. لكن الـ location الـ
+
+246
+00:18:43,570 --> 00:18:47,850
+location هو بيكون في صميم العملية، ودائمًا بأثر
+
+247
+00:18:47,850 --> 00:18:52,650
+تمام؟ مثل الناس اللي بتشتغل في التنقيب عن النفط و
+
+248
+00:18:52,650 --> 00:18:57,910
+الذهب. الآن الـ special data جزء من شغلها، جزء من الـ
+
+249
+00:18:57,910 --> 00:19:03,410
+data تبعتهم. يعني أنا بدي أروح أجيب البيانات
+
+250
+00:19:03,410 --> 00:19:07,750
+عن أنواع التربة، وأنَبُؤ على طول
+
+251
+00:19:07,750 --> 00:19:12,950
+فلسطين، تمام؟ أي منطقة ممكن ألاقي فيها .. أفحر فيها
+
+252
+00:19:12,950 --> 00:19:18,810
+منجم ذهب مثلًا. هاي special .. هاي special. تمام؟ لكن
+
+253
+00:19:18,810 --> 00:19:21,550
+سوق أوراق فلسطين .. الأوراق الفلسطينية .. أو سوق
+
+254
+00:19:21,550 --> 00:19:25,510
+الفلسطيني للأوراق المالية. أنا بتكلم على time series
+
+255
+00:19:25,510 --> 00:19:32,810
+data. هل ممكن تكون هذه temporal data؟ هل
+
+256
+00:19:32,810 --> 00:19:38,920
+في الـ state؟ يعني بين قوسين؟ ماشي، بحكي: ما هو أنا
+
+257
+00:19:38,920 --> 00:19:42,200
+كنت مبارح مرتفع، اليوم ممكن أنخفض، ممكن في الساعة
+
+258
+00:19:42,200 --> 00:19:45,500
+الـحادية بقى أنخفض شوية، بعد نص ساعة أرتفع. هل فعليًا
+
+259
+00:19:45,500 --> 00:19:48,560
+أنا بدور على state؟ يعني بين قوسين، هل في عندي
+
+260
+00:19:48,560 --> 00:19:51,880
+السوق كله اللي بيرتفع وبينخفض مرة واحدة؟ ولا شغلات
+
+261
+00:19:51,880 --> 00:19:55,500
+بسيطة؟ إذا كان السوق كله، مجموعة القيم كلها مع بعضها
+
+262
+00:19:55,500 --> 00:20:00,750
+ممكن أتكلم عليها temporarily، لكن إذا كنت بتكلم إنه
+
+263
+00:20:00,750 --> 00:20:03,230
+لأ، السوق هو عبارة عن مجموعة من الأسهم. إيش من
+
+264
+00:20:03,230 --> 00:20:05,610
+الأسهم بتطلع، وإيش بنزل، وإيش ثابت. معناته أنا
+
+265
+00:20:05,610 --> 00:20:09,070
+بتتكلم على time series، وما فيه dependency ما بين
+
+266
+00:20:09,070 --> 00:20:16,170
+الأسهم اللي موجودة بشكل عام. تمام يا شباب، على
+
+267
+00:20:16,170 --> 00:20:19,270
+الأسهم، على تداول الأسهم اللي موجودة: أسهم
+
+268
+00:20:19,270 --> 00:20:23,970
+الاتصالات، أسهم الجوال، أسهم شركات التأمين ..
+
+269
+00:20:28,570 --> 00:20:32,950
+أكيد أكيد أكيد. احنا مش مختلفين معك، لكن هل الآن
+
+270
+00:20:32,950 --> 00:20:37,110
+هذا لما أنا بدي أروح أجيب الـ data تبعتي وبدي
+
+271
+00:20:37,110 --> 00:20:39,910
+أشتغل عندهم، هيكون الوضع السياسي: اليوم كان في عندنا
+
+272
+00:20:39,910 --> 00:20:43,170
+قصف في المنطقة الفلانية. هذا لا يُذكر في الـ data
+
+273
+00:20:43,170 --> 00:20:46,150
+اللي موجودة. وبناءً على هيك احنا بنفترض دائمًا أن
+
+274
+00:20:46,150 --> 00:20:49,130
+احنا شغالين في الـ ideal case، أن الحياة ماشية تمام
+
+275
+00:20:49,130 --> 00:20:52,670
+مش فيها مشاكل، وبدنا نعمل دراسة للموضوع لأن
+
+276
+00:20:52,670 --> 00:20:56,370
+بالمناسبة، لحظة الحروب كل الدراسات هذه مالهاش معنى
+
+277
+00:20:56,370 --> 00:21:01,320
+بتصير، لأن بتصير الأولوية للحياة، الأولوية من أجل
+
+278
+00:21:01,320 --> 00:21:05,980
+الحياة. تمام، ندخل في موضوع محاضرتنا اليوم. نص ساعة
+
+279
+00:21:05,980 --> 00:21:08,460
+هنا عملنا refresh كويسة. تلت ساعة فعليًا بعد ما أنتم
+
+280
+00:21:08,460 --> 00:21:12,460
+اتأخرتم. خليني أروح باتجاه نتعرف على الـ data mining
+
+281
+00:21:12,460 --> 00:21:15,860
+tasks اللي بدنا نشتغل عليها. لما أنا بتكلم على الـ
+
+282
+00:21:15,860 --> 00:21:20,940
+data mining tasks، معناته أنا قاعد بدور على النمط
+
+283
+00:21:20,940 --> 00:21:25,850
+اللي أنا بدي إياه، الـ knowledge اللي أنا بدي أشوفها،
+
+284
+00:21:25,850 --> 00:21:30,350
+اللي بدي أستخرجها. الآن الناس اللي بتنقب على الذهب
+
+285
+00:21:30,350 --> 00:21:34,530
+عاملة حسابها، بتدور على كل شغلة صفراء بتلمع. وهذه
+
+286
+00:21:34,530 --> 00:21:39,230
+عينها دائمًا اللي بتغسل في التربة وبتصفّي فيها. عينها
+
+287
+00:21:39,230 --> 00:21:42,450
+على هي الشغلة. بينما الناس اللي بتنقب على الأحجار
+
+288
+00:21:42,450 --> 00:21:47,250
+الكريمة، بتدور على الألوان الجذابة. أثناء البحث.  مولا
+
+289
+00:21:47,250 --> 00:21:50,670
+لأ؟ يعني ممكن، عفوًا، أن الذهب يكون أشبه بالرمل،
+
+290
+00:21:50,670 --> 00:21:54,390
+بالتراب. لكن الأحجار الكريمة لأ، هي فعليًا نوع من
+
+291
+00:21:54,390 --> 00:21:57,810
+أنواع الحجر، هيكون وموجود عندنا. اللي بده ينقب على
+
+292
+00:21:57,810 --> 00:22:02,110
+البترول، كل الكلام هذا ما بيعنيهوش لحد ما فعليًا يصل
+
+293
+00:22:02,110 --> 00:22:06,010
+للنفط الخام، ويبدأ يظهر في التربة بشكل جلي، ويقول
+
+294
+00:22:06,010 --> 00:22:10,370
+أنا أصلًا .. فإحنا فعليًا الـ data mining task هي عبارة
+
+295
+00:22:10,370 --> 00:22:15,510
+عن أنواع الـ patterns اللي أنا بدي أدور عليها،
+
+296
+00:22:15,510 --> 00:22:18,250
+أنواع الـ knowledge، المعرفة اللي أنا بدي أدور
+
+297
+00:22:18,250 --> 00:22:22,630
+عليها. وبالتالي أنا قاعد أتكلم على مجموعة الـ
+
+298
+00:22:22,630 --> 00:22:30,430
+functions اللي تمثل الـ task هاي. عادة أو بشكل أساسي،
+
+299
+00:22:30,430 --> 00:22:35,090
+الـ data mining task بتأخد واحد من الـ two trends: إما
+
+300
+00:22:35,090 --> 00:22:43,130
+descriptive (وصفية) أو predictive (تنبؤية). بالوصفية،
+
+301
+00:22:43,130 --> 00:22:49,070
+الهدف منها بيكون إن أنا أقدر أوصف الـ data أو أقدم
+
+302
+00:22:49,070 --> 00:22:54,350
+وصف جديد للـ data، تمام؟ وهلأ رح أشوف معاكم مثال
+
+303
+00:22:54,350 --> 00:22:59,330
+برضه،  بشارككم كويس معايا، وبخلينا نفرّق بين اتنين
+
+304
+00:22:59,330 --> 00:23:05,820
+بشكل واضح. بينما الـ predictive task هي: بدي أنفذ تقصي
+
+305
+00:23:05,820 --> 00:23:11,600
+أو تحقيق، أو دراسة، أو تحليل للـ data عشان أقدر أتنبأ
+
+306
+00:23:11,600 --> 00:23:17,140
+مستقبلًا لـ instance معينة. يعني أنا بروح بأدرس وضع
+
+307
+00:23:17,140 --> 00:23:23,360
+السوق الحالي عشان أتنبأ إن قيمة السوق هترتفع ولا
+
+308
+00:23:23,360 --> 00:23:28,320
+تنخفض. طيب، متى أنا بدي أتنبأ؟ في اليوم؟ لأ، الأصل
+
+309
+00:23:28,320 --> 00:23:31,200
+لكمان ساعة مثلًا، لأن السوق مثلًا بتغير كل ساعة مثلًا،
+
+310
+00:23:31,200 --> 00:23:34,620
+كمان ساعة. بتعرفش هو وضع السوق بكرا، بتعرفش هو وضع
+
+311
+00:23:34,620 --> 00:23:38,900
+السوق بعد أسبوع، بعد شهر، بعد سنة. هذه مفهوم التنبؤ.
+
+312
+00:23:38,900 --> 00:23:43,840
+لكن كله بناءً على إيش؟ على الـ current data، البيانات
+
+313
+00:23:43,840 --> 00:23:50,200
+الحالية اللي موجودة عندي. طيب، الآن رح أروح معاكم
+
+314
+00:23:50,200 --> 00:23:56,800
+على الصورة. هاي مش واضحة كتير. رح أساعدكم في الصورة، لأن
+
+315
+00:23:56,800 --> 00:24:00,220
+الإضاءة شوية، وحتى والصورة تبعت كمان بلورة باهتة، مش
+
+316
+00:24:00,220 --> 00:24:05,400
+كتير. الصف الأول طبعًا هدول مئة صورة. الصف الأول
+
+317
+00:24:05,400 --> 00:24:11,780
+مجموعة من الطائرات. الصف الثاني: مجموعة من السيارات.
+
+318
+00:24:11,780 --> 00:24:16,740
+الثالث: مجموعة من الطيور. كلها طيور منزلية بالمناسبة.
+
+319
+00:24:16,740 --> 00:24:21,000
+الرابع: مجموعة من القطط، الغزلان.
+
+320
+00:24:23,650 --> 00:24:30,330
+الـ Dogs، الكلاب. Frogs، ضفادع. Horses، خيول. Boots،
+
+321
+00:24:30,330 --> 00:24:36,410
+أحذية. Trucks أو شاحنات. هدول عشرة، أو هدول مئة صورة.
+
+322
+00:24:36,410 --> 00:24:41,510
+هدول مئة صورة. الآن، افترض إن هدول هما الـ data set
+
+323
+00:24:41,510 --> 00:24:45,730
+اللي موجودين عندك. هذه الـ data set ممكن تكون هيك
+
+324
+00:24:45,730 --> 00:24:50,430
+مئة صورة. الآن خلينا نروح باتجاه الـ descriptive
+
+325
+00:24:50,430 --> 00:24:55,900
+mining tasks. بدي أديك مثال على واحد منها. لو أنا
+
+326
+00:24:55,900 --> 00:25:02,800
+إجيت سألتك، قلت لك،  ذكرت لك الصور، إيش هما،
+
+327
+00:25:02,800 --> 00:25:07,320
+بناءً على معرفتك السابقة اللي أنت تراكمت عليها مدار
+
+328
+00:25:07,320 --> 00:25:13,160
+تسعة عشر أو عشرين سنة بالـ objects هدول، جسملي إياها
+
+329
+00:25:13,160 --> 00:25:16,180
+لمجموعتين،
+
+330
+00:25:16,180 --> 00:25:21,380
+لاحظ؟ بدك تجسملي إياها لمجموعتين، وبدك تديلي وصف مقنع
+
+331
+00:25:22,880 --> 00:25:26,940
+للـ إيه؟ للعناصر أو للمجموعتين هدول؟ آه محمد: شويّة، ده
+
+332
+00:25:26,940 --> 00:25:30,120
+.. جمادات وكائنات حية .. جمادات وكائنات حية .. مين
+
+333
+00:25:30,120 --> 00:25:32,660
+بيشارك محمد في التقسيمة هاي؟ أو بيوافق على
+
+334
+00:25:32,660 --> 00:25:38,320
+التقسيمة؟ كلها .. منطقية؟ جدًا .. جدًا .. الآن مين
+
+335
+00:25:38,320 --> 00:25:43,520
+الجمادات؟ السيارات .. طائرات .. السيارات ..
+
+336
+00:25:43,520 --> 00:25:50,590
+والقوارب .. والشاحنات. فعليًا هدول واحد، اتنين،
+
+337
+00:25:50,590 --> 00:25:56,130
+ثلاثة، أربعة. بمثل 40% من الـ data set. مضبوط. والستين
+
+338
+00:25:56,130 --> 00:25:59,490
+في المئة اللي ضلّوا في الكائنات الحية. تصنيف تمام،
+
+339
+00:25:59,490 --> 00:26:03,590
+وجميل. مئة في المئة، وما عليه أي غبار. معقدة
+
+340
+00:26:03,590 --> 00:26:08,630
+المسألة .. آه يا محمد: وسائل نقل، حيوانات. سماها
+
+341
+00:26:08,630 --> 00:26:12,790
+تسمية مختلفة. صحيحة مئة في المئة. ما فيش مشكلة فيها
+
+342
+00:26:12,790 --> 00:26:19,540
+غيره يا شباب. حد في عنده أي تسمية ثانية؟ طيب، الآن يا
+
+343
+00:26:19,540 --> 00:26:24,380
+سيدي العزيز، هدول المجموعتين بديش إياها مجموعتين،
+
+344
+00:26:24,380 --> 00:26:28,160
+بدي إياها أربع،
+
+345
+00:26:28,160 --> 00:26:32,920
+بدي تلاحظ .. خد وجهة نظرك وأنت بتفكر في الموضوع و
+
+346
+00:26:32,920 --> 00:26:36,440
+تشاور أنت وجارك، ما فيش مشكلة عندك. بدي تلاحظ أنه
+
+347
+00:26:36,440 --> 00:26:44,040
+الآن بدك .. دماغك هيعصر أكثر. لأ، أنت الآن مش على كيفك
+
+348
+00:26:44,040 --> 00:26:48,480
+زي ما أنا ألزمتك بالاثنتين. الآن جسملي إياها لأربع
+
+349
+00:26:48,480 --> 00:26:52,260
+مجموعات، بديش ثلاثة، بدي أربع مجموعات.
+
+350
+00:26:55,310 --> 00:27:03,210
+اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+351
+00:27:03,210 --> 00:27:04,850
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+352
+00:27:04,850 --> 00:27:05,010
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+353
+00:27:05,010 --> 00:27:05,050
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+354
+00:27:05,050 --> 00:27:07,670
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+355
+00:27:07,670 --> 00:27:08,050
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+356
+00:27:08,050 --> 00:27:08,410
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+357
+00:27:08,410 --> 00:27:11,050
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+358
+00:27:24,450 --> 00:27:28,910
+وسائل نقل جوية، وسائل نقل برية، وسائل نقل برية،
+
+359
+00:27:28,910 --> 00:27:36,630
+طيور، وحيوانات. طيور، وحيوانات. طيب،
+
+360
+00:27:36,630 --> 00:27:42,370
+ما قلت لك قوارب؟ أنا معناته الآن لاحظ إن أنت ضيعت 10
+
+361
+00:27:42,370 --> 00:27:46,750
+% من الـ data. أنت ما استفدت منها. معناته ذكرت لك إياها
+
+362
+00:27:46,750 --> 00:27:50,610
+قوارب. قلنا عددهم هدول. عشر فئات مختلفات. بدنا
+
+363
+00:27:50,610 --> 00:27:51,750
+نجسمهم على أربع. آه، هاشم:
+
+364
+00:27:55,230 --> 00:28:05,710
+وسائل المواصلات، برمائيات، طيور، ثدييات. الضفادع ..
+
+365
+00:28:05,710 --> 00:28:12,790
+برمائية، مش مشكلة. أنا رح أكتب على اللوح يا شباب. طيب،
+
+366
+00:28:12,790 --> 00:28:16,010
+مش مشكلة. طائرات،
+
+367
+00:28:58,530 --> 00:29:03,210
+يلا يا هاشم، أربع تصنيفات بدنا منك. صنفهم
+
+368
+00:29:03,210 --> 00:29:07,850
+عيدهم ثاني بعد ما كتبنا برمائيات. هاشم بصنف لي إياها.
+
+369
+00:29:07,850 --> 00:29:16,650
+الآن: برمائيات، طيور .. طيور ..
+
+370
+00:29:16,650 --> 00:29:21,510
+أربعة.
+
+371
+00:29:21,510 --> 00:29:25,770
+غيره: وسائل نقل جوية .. وسائل نقل جوية
+
+372
+00:29:29,950 --> 00:29:39,330
+وحيوانات. okay، نوقف. خلاص.
+
+373
+00:29:39,330 --> 00:29:46,450
+الوصف بيكون مُبرر في
+
+374
+00:29:46,450 --> 00:29:56,130
+الآخر. هذا اسم المجموعة. يعني صنف. شوف جامعة الخير
+
+375
+00:29:56,130 --> 00:30:00,040
+كمان مرة. يعني إيش .. إيش الـ .. إيش الـ data mining؟
+
+376
+00:30:00,040 --> 00:30:03,120
+إنّه كل واحد بدي يشوف الـ .. الـ analyst بدي يطلع بـ
+
+377
+00:30:03,120 --> 00:30:11,360
+pattern ما شافهوش سابقًا. تفضل: مجموعة جوية، وبتضم ..
+
+378
+00:30:11,360 --> 00:30:20,240
+بتضم مين؟ آه الطائرات والطيور. بس الـ judge ما بيطيرش،
+
+379
+00:30:20,240 --> 00:30:20,900
+بنطيّره.
+
+380
+00:30:31,000 --> 00:30:38,600
+مش هتقدر تصنفه في المجموعة الجوية. أيوة، وإنما تصنفه
+
+381
+00:30:38,600 --> 00:30:47,640
+في البرية. آه، التصنيف اللي أنا فعليًا اجتهدت وشفته
+
+382
+00:30:47,640 --> 00:30:49,460
+التالي: قلت أنا أنا أنا أنا أنا أنا أنا أنا أنا أنا
+
+383
+00:30:49,460 --> 00:30:52,230
+أنا أنا أنا أنا أنا أنا أنا الـ Living objects
+
+384
+00:30:52,230 --> 00:30:56,010
+هدول، و Non-living objects الثاني. مش مختلفين عليهم
+
+385
+00:30:56,010 --> 00:31:00,410
+بالـ Non-living objects، في منهم بيسير على عجلات، وفي
+
+386
+00:31:00,410 --> 00:31:05,870
+منهم بدون: طائرات وقوارب بدون عجلات، سيارات و
+
+387
+00:31:05,870 --> 00:31:14,150
+شاحنات بعجلات، بتمشي على العجلات. الطائرة هاش
+
+388
+00:31:14,150 --> 00:31:20,520
+الحالة، في طائرة مسيرة فيهم. ها هان برضه برضه بعجلات. فيه
+
+389
+00:31:20,520 --> 00:31:25,960
+في الآخر العجل مش هو الأساس، الحركة تبعتها اللي أنا
+
+390
+00:31:25,960 --> 00:31:30,100
+بدي أقوله. فالآن: على عجلات، وبدون عجلات. هذا الـ non
+
+391
+00:31:30,100 --> 00:31:36,920
+-living objects. طيب، والـ living objects؟ مثلًا؟
+
+392
+00:31:36,92
+
+445
+00:35:56,570 --> 00:36:00,570
+جديش مثلاً التدخين مرتبط بسرطان الرئة، جديش فقر الدم
+
+446
+00:36:00,570 --> 00:36:03,790
+مرتبط بسرطان الرئة أو الشغلات اللي زي هيك كانت جديش
+
+447
+00:36:03,790 --> 00:36:07,850
+الحالة الاجتماعية بتأثر على الطالب تماماً على تحصيله
+
+448
+00:36:07,850 --> 00:36:12,850
+العلمي، إلى آخره في الـ predictive، في عندنا
+
+449
+00:36:12,850 --> 00:36:16,090
+classification، وفي الـ classification بدي أعمل
+
+450
+00:36:16,090 --> 00:36:20,550
+predict لمين؟ للفئة، الـ category، الفئة هذه بتكون محددة
+
+451
+00:36:20,550 --> 00:36:26,890
+ومسبقاً في الـ regression بدي أعمل prediction لقيمة، لـ value
+
+452
+00:36:26,890 --> 00:36:30,630
+certain value، قيمة بذاتها، وفي الـ recommendation
+
+453
+00:36:30,630 --> 00:36:35,030
+بدي أحاول أعمل predict للـ preference، للشغلات اللي
+
+454
+00:36:35,030 --> 00:36:39,330
+ممكن تكون مفيدة للشخص هذا، نبدأ بنوع من التفصيل
+
+455
+00:36:39,330 --> 00:36:42,870
+للعناصر اللي موجودة هنا، في الـ classification زي ما
+
+456
+00:36:42,870 --> 00:36:45,970
+قلنا هي عبارة عن predictive data mining task
+
+457
+00:36:45,970 --> 00:36:52,310
+classification، predictive data mining task، بدي
+
+458
+00:36:52,310 --> 00:36:58,880
+أتنبأ في الـ data set، عادةً بتكون تحتوي على شغلتين، يا
+
+459
+00:36:58,880 --> 00:37:03,060
+جماعة الخير، أو نوعين من الـ variables، نوعين من الـ
+
+460
+00:37:03,060 --> 00:37:09,620
+attributes، النوع الأول اللي هو مجموعة الـ
+
+461
+00:37:09,620 --> 00:37:15,420
+explanatory variables، أو المجموعة الاستكشافية
+
+462
+00:37:15,420 --> 00:37:19,340
+المجموعة المميزة، سميها زي ما بدك، الفكرة فيها هذه
+
+463
+00:37:19,340 --> 00:37:24,560
+عبارة عن مجموعة الـ attributes اللي بتحمل خصائص الـ
+
+464
+00:37:24,560 --> 00:37:31,900
+object، خصائص الـ raw اللي أنا بتكلم عليه، والتاني هي
+
+465
+00:37:31,900 --> 00:37:38,480
+عبارة عن الـ target variable، يعني بقي لي أقول أنه
+
+466
+00:37:38,480 --> 00:37:48,020
+أنا عندي data set فيها كالتالي، هاي الـ target
+
+467
+00:37:51,340 --> 00:37:56,120
+وهان مجموعة الـ fields اللي موجودة، مجموعة الـ fields
+
+468
+00:37:56,120 --> 00:38:01,840
+كالتالي
+
+469
+00:38:01,840 --> 00:38:06,320
+brief
+
+470
+00:38:06,320 --> 00:38:13,500
+نفس eat، fly
+
+471
+00:38:13,500 --> 00:38:16,900
+whales
+
+472
+00:38:25,410 --> 00:38:33,490
+feather، مثلاً، هي هدول الآن: التنفس، يأكل، يطير، عجلات،
+
+473
+00:38:33,490 --> 00:38:43,970
+ريش، والـ target، الـ role، أولاً breathe
+
+474
+00:38:43,970 --> 00:38:48,650
+no، eat، no، yes، بحط X
+
+475
+00:38:51,580 --> 00:39:01,160
+wheel، yes، no، وأنا في عندي plane، في المقابل في عندي
+
+476
+00:39:01,160 --> 00:39:10,740
+أنا breathe، eat، fly، no، weather، ريش، هيبرد
+
+477
+00:39:10,740 --> 00:39:15,220
+الآن لاحظ، أنا جاهز، بجهز الـ data set، طبعاً هذا بيكون
+
+478
+00:39:15,220 --> 00:39:18,420
+وصف للعناصر اللي موجودة عندنا
+
+479
+00:39:28,840 --> 00:39:31,660
+الآن يا جماعة الخير، المفروض أنه كل row من الـ rows
+
+480
+00:39:31,660 --> 00:39:36,760
+هي تختلف، تستوفي لما رح نتكلم عليها، لأ، ممنوع يتكرر، تكرار
+
+481
+00:39:36,760 --> 00:39:40,180
+الـ rows لا يضيف شيء في المعرفة، عشان هي class، كل
+
+482
+00:39:40,180 --> 00:39:43,360
+row يكون مختلف عن الثاني، عشان يقدر الـ system وهو
+
+483
+00:39:43,360 --> 00:39:47,740
+بيتعلم، يقدر يجمع أكثر قدر ممكن من الـ different
+
+484
+00:39:47,740 --> 00:39:53,480
+properties، لمين؟ لكل class، بنجي بنقول هان breathe
+
+485
+00:39:53,480 --> 00:40:03,880
+بالخطأ yes، no، wheels، feather، وهنا
+
+486
+00:40:03,880 --> 00:40:14,580
+plane، الآن شو رأيك بالـ breath؟ شو يعني بدها؟ بدها
+
+487
+00:40:14,580 --> 00:40:19,560
+cleaning، هان بيجي جزء للـ cleaning، الآن أنا في عندي
+
+488
+00:40:19,560 --> 00:40:26,790
+بأبحث عن errors، inconsistent، ولا missing، ولا noise
+
+489
+00:40:26,790 --> 00:40:31,230
+inconsistent يعني
+
+490
+00:40:31,230 --> 00:40:35,170
+في تعارض ما بين الـ two attributes، غالباً هذه noise
+
+491
+00:40:35,170 --> 00:40:43,310
+data، خطأ في الإدخال، طبعاً ما فيش...ما فيش...لا في
+
+492
+00:40:48,950 --> 00:40:53,230
+تمام؟ الآن...هذه الآن، ده الـ  مقصد من في الـ
+
+493
+00:40:53,230 --> 00:41:00,570
+classification، هذه كلها الـ attributes هدول، صححتها
+
+494
+00:41:00,570 --> 00:41:07,330
+و...وصححتها، تمام؟
+
+495
+00:41:07,330 --> 00:41:11,570
+explanatory variables، اللي أنا فعلياً بدي أستكشف
+
+496
+00:41:11,570 --> 00:41:16,130
+من خلالهم الـ properties، الـ different properties
+
+497
+00:41:16,130 --> 00:41:20,790
+عشان أربطها أو أشوف إيش بيميز الـ target، بيان جوسين
+
+498
+00:41:20,790 --> 00:41:24,350
+بدي أستكشف زي ما أنتم بتفضلوا الـ target من خلال
+
+499
+00:41:24,350 --> 00:41:28,990
+الـ attributes هاي، ببدأ بأدرس العلاقات، ملاحظين أنا
+
+500
+00:41:28,990 --> 00:41:36,790
+في عندنا تلت شغلات أساسية مرتبطة بالـ bird، الأكل
+
+501
+00:41:36,790 --> 00:41:44,730
+والشرب، والريش، والـ feather، مضبوط؟ عفواً، الأكل، والتنفس
+
+502
+00:41:44,730 --> 00:41:51,230
+والأكل، والريش، الـ flying مرتبطة بالطائر؟ لأ، لأن
+
+503
+00:41:51,230 --> 00:41:54,550
+العنصر الثاني، أو الـ class الثاني، بيشترك بالطائر
+
+504
+00:41:54,550 --> 00:41:59,430
+طبعاً ما هيش الشغلات المرتبطة بالطائرة، الـ
+
+505
+00:41:59,430 --> 00:42:04,800
+discriminative attribute اللي عندي، الـ wheel، الـ
+
+506
+00:42:04,800 --> 00:42:09,200
+wheels، تمام؟ والـ fly، يعني مع بعضهم، إذا الـ fly و
+
+507
+00:42:09,200 --> 00:42:12,460
+الـ wheel، فخلاص على المضمون، فهيك أنا صار في عندي
+
+508
+00:42:12,460 --> 00:42:15,800
+knowledge، بقدر أقول أنا general knowledge، وهذه
+
+509
+00:42:15,800 --> 00:42:21,680
+valid، والأصل هي تكون novel، أن أي object عنده
+
+510
+00:42:21,680 --> 00:42:30,700
+المقدرة أنه يطير وله عجلات، فهو طائرة، تمام؟
+
+511
+00:42:32,580 --> 00:42:35,980
+محمد أبو حاسم يقول لك: كل قاعدة شوية بناءً على الـ
+
+512
+00:42:35,980 --> 00:42:38,480
+data set اللي موجود عندنا، هنا كمان مرة يا جماعة
+
+513
+00:42:38,480 --> 00:42:43,320
+الخير، لما أنا بأتعامل، بأتعامل ضمن الـ data set اللي
+
+514
+00:42:43,320 --> 00:42:50,120
+موجودة، لاحظ سابقاً في الصور، مسألة cash والدبابات
+
+515
+00:42:50,120 --> 00:42:54,900
+وين صنفتها؟ أو وين ضمنتها؟ ليش؟ لأنها مش موجودة
+
+516
+00:42:54,900 --> 00:43:00,300
+وبالتالي أنا بأشتغل ضمن حدود الـ data set تبعتي، و
+
+517
+00:43:00,300 --> 00:43:04,340
+بعدين لما تكلمنا عن الـ validity تبعت الـ pattern
+
+518
+00:43:04,340 --> 00:43:09,500
+تبعي، ما قلتش ضروري يكون one hundred percent، ما قلتش
+
+519
+00:43:09,500 --> 00:43:13,080
+أنه لازم يكون مئة في المئة دقيق، لكن قلت لك with
+
+520
+00:43:13,080 --> 00:43:18,280
+some degree of certainty، مع نسبة معينة من الدقة
+
+521
+00:43:18,280 --> 00:43:22,720
+النسبة هاي عشان يكون في مجال لقبول أو رفض البيانات
+
+522
+00:43:22,720 --> 00:43:24,700
+ملك؟ لأ، نعم
+
+523
+00:43:29,430 --> 00:43:33,750
+هو الـ data set لازم تكون التنين موجودات عندك أنت
+
+524
+00:43:33,750 --> 00:43:37,230
+الآن الـ data mining task تعمل analysis للـ
+
+525
+00:43:37,230 --> 00:43:42,410
+explanatory، تمام؟ عشان تعمل prediction لاحقاً للـ
+
+526
+00:43:42,410 --> 00:43:50,350
+target هذا
+
+527
+00:43:50,350 --> 00:43:53,810
+اللي عند الطائرة وتتنفس، تمام، الآن إحنا عرفنا
+
+528
+00:43:53,810 --> 00:44:02,290
+لأنه عندنا كم؟ أربعة، أو أربعة rows، 100%، عادة الـ
+
+529
+00:44:02,290 --> 00:44:05,870
+missing data أو الـ noise data مش بسهولة الكشف
+
+530
+00:44:05,870 --> 00:44:09,270
+عنها، وإلا كان ما قال cash، إنه فعلياً أنت بدك تجد
+
+531
+00:44:09,270 --> 00:44:12,210
+وجد، وأنت بتدرس البيانات اللي موجودة، إيش أنت بتروح
+
+532
+00:44:12,210 --> 00:44:17,370
+بتساوي؟ بتروح بتقول له مثلاً إيش ممكن أساوي الـ
+
+533
+00:44:17,370 --> 00:44:20,630
+attribute هذه؟ دور، أعمل الـ maximum والـ minimum، و
+
+534
+00:44:20,630 --> 00:44:23,250
+أعمل association ما بين الـ attribute والـ
+
+535
+00:44:23,250 --> 00:44:26,030
+attribute الثاني، زي الـ association مع الـ attribute
+
+536
+00:44:26,030 --> 00:44:31,320
+والـ target، لحد ما تصل لارتباط، لكن برضه بتظهر
+
+537
+00:44:31,320 --> 00:44:34,900
+الفرصة أن هذه تبقى مثل ما هي، لأن من اللي ممكن هذي
+
+538
+00:44:34,900 --> 00:44:39,820
+يعملها bridge، لو أنت ما شفتهاش، حجم البيانات الآن
+
+539
+00:44:39,820 --> 00:44:45,380
+هذه واحدة، تمام، خطأ واحد في مئة ألف record، جديش
+
+540
+00:44:45,380 --> 00:44:51,630
+تأثيره؟ يكاد يكون صفر، يكاد يكون له تأثير، لكن يكاد
+
+541
+00:44:51,630 --> 00:44:55,910
+يكون صفر، لكن لو هذا العنصر واحد من عشرة أو واحد من
+
+542
+00:44:55,910 --> 00:44:59,650
+أربعة زي هيك، صار تأثيره 25% على الـ decision تبعتي
+
+543
+00:44:59,650 --> 00:45:01,070
+في الموضوع، إيه رأيك؟
+
+544
+00:45:06,320 --> 00:45:10,220
+تمام، بس أنا الآن...الآن هذا تماماً مثل المثال
+
+545
+00:45:10,220 --> 00:45:13,660
+السابق اللي عرضت لك مجموعة الصور، قلت لك هي...أنا بس
+
+546
+00:45:13,660 --> 00:45:16,940
+حاول تكتب الـ data set قدامك، المفروض أنا عرضت الـ
+
+547
+00:45:16,940 --> 00:45:20,040
+data set سابقاً، جهزت الـ data set سابقاً، زي ما
+
+548
+00:45:20,040 --> 00:45:23,340
+اشتغلنا بالمثال تبع المحاضرة الماضية، الجدول اللي
+
+549
+00:45:23,340 --> 00:45:27,220
+فيه الصناديق الحمراء وال...ال...والكون اللي هي
+
+550
+00:45:27,220 --> 00:45:31,160
+القمع وال...والكرة الزرقاء، تمام؟ وربطنا
+
+551
+00:45:31,160 --> 00:45:35,240
+بالأوزان، قلت لك هي الـ data set، وشوف الـ pattern، لأن
+
+552
+00:45:35,240 --> 00:45:39,080
+أنا بس كتبتها قدامك، وأنت معيّ واحد بواحد، لو جئت
+
+553
+00:45:39,080 --> 00:45:42,000
+عرضت لك إياها بالشكل هذا، وقلت لك يا رامي شوف لي الـ
+
+554
+00:45:42,000 --> 00:45:45,840
+patterns، اعطيني pattern للطائرة، واعطيني pattern
+
+555
+00:45:45,840 --> 00:45:51,820
+للطائر، إيش رح تروح تقول؟ رح تاخد مني وقت بسيط أو طويل
+
+556
+00:45:51,820 --> 00:45:57,840
+حسب حجم الـ data set، وتبدأ تدرس العناصر، if bird to
+
+557
+00:45:57,840 --> 00:46:03,420
+feather، معناته bird، otherwise
+
+558
+00:46:05,030 --> 00:46:08,830
+وعادة هدف الـ binary classification يا شباب، دائماً
+
+559
+00:46:08,830 --> 00:46:14,750
+بصير بدور على الـ more strongest rule
+
+560
+00:46:14,750 --> 00:46:24,810
+أو value، باجي بقول مين أقوى عندي؟ تنفس، وأكل، وريش
+
+561
+00:46:24,810 --> 00:46:33,100
+مع البرد، ولا عجلات وطيران مع الطائرة، حسب الـ data
+
+562
+00:46:33,100 --> 00:46:38,920
+set اللي عندنا هنا، مين أقوى؟ يعني هيك
+
+563
+00:46:38,920 --> 00:46:42,220
+أنا قلت يا عزيزي، اتبعت أنه برد، توصف الليلة بعدها
+
+564
+00:46:42,220 --> 00:46:45,060
+...لا لا لا، ما هو أنا هيك جاي لك، أنا جاي لك لاحقاً
+
+565
+00:46:45,060 --> 00:46:48,200
+أجي أقول لك التالي، أنت ما خلينا...ما خلينا نخصص
+
+566
+00:46:48,200 --> 00:46:52,000
+إحنا، الآن هي الـ data set اللي عندك، وجئت قلت لك أن
+
+567
+00:46:52,000 --> 00:46:56,840
+الآن أنا في عندي object، عندي object واضح أنه
+
+568
+00:46:56,840 --> 00:47:05,420
+بيتنفس، والمعلومات اللي عندي بتقول أنه بيأكلش وبيطير
+
+569
+00:47:05,420 --> 00:47:16,740
+وما لوش عجلات، وإله ريش، عصفور
+
+570
+00:47:16,740 --> 00:47:22,780
+عيّان، أه؟ لأ، مرت حردانة منه بس دو ده نفسه مضرب
+
+571
+00:47:22,780 --> 00:47:26,960
+عن الطعام، الآن إيش التصنيف هذا للـ object هذا يا
+
+572
+00:47:26,960 --> 00:47:33,450
+رامي؟ كيف أشيله؟ مش كيفك، هذا واحد من الاثنين اللي
+
+573
+00:47:33,450 --> 00:47:38,910
+عندك، حسب الـ role، لازم الـ algorithm تديني قرار bird
+
+574
+00:47:38,910 --> 00:47:47,430
+ولا plane؟ ليش bird؟ لأنه بتنفس وإله ريش، فهو 90%
+
+575
+00:47:47,430 --> 00:47:53,190
+من الـ role تبعت الـ bird تنطبق عليه، بتنفس وبيطير
+
+576
+00:47:53,190 --> 00:47:58,330
+وإله ريش وما لوش عجلات، وبالتالي أنا قاعد أتكلم على
+
+577
+00:47:58,330 --> 00:48:07,050
+80% من خصائص الطائر موجودة عنده، فهو طائر، تمام؟
+
+578
+00:48:07,050 --> 00:48:10,890
+هذه الـ prediction، هذه البيانات بتلزم في مرحلة الـ
+
+579
+00:48:10,890 --> 00:48:17,430
+learning، مرحلة الـ analysis، عشان أبدأ أبني rules في
+
+580
+00:48:17,430 --> 00:48:21,430
+تحديد الـ object هذه، في مرحلة الـ prediction باجي
+
+581
+00:48:21,430 --> 00:48:26,770
+بسأل، بقول: والله okay، الـ...في سوق أوراق فلسطين
+
+582
+00:48:26,770 --> 00:48:31,390
+المالية، سهم شركة الاتصالات على مدار عشر سنوات
+
+583
+00:48:31,390 --> 00:48:38,790
+بيطلع وبينزل، تمام؟ بكرة كيف وضع السهم؟ بناءً...
+
+584
+00:48:38,790 --> 00:48:44,690
+رح نتكلم، المفروض منه، كيف وضع السهم بكرة؟ بده يرتفع ولا
+
+585
+00:48:44,690 --> 00:48:46,310
+بده ينزل...بده ينخفض؟
+
+586
+00:48:49,530 --> 00:48:53,730
+حسب الـ data تبعتنا، الآن مثلاً كان واضح في الـ
+
+587
+00:48:53,730 --> 00:48:56,950
+pattern...واضح في الـ pattern أنه في الأيام...في
+
+588
+00:48:56,950 --> 00:49:01,270
+الأيام اللي بيكون، أو مثلاً في فصل الشتاء، واللي
+
+589
+00:49:01,270 --> 00:49:08,050
+بيكون فيها مطر غزير، تمام، السهم بينزل، بكرة...هذا
+
+590
+00:49:08,050 --> 00:49:10,210
+الـ pattern هيك بيقول لي، الـ historical data هيك
+
+591
+00:49:10,210 --> 00:49:16,580
+بتقول لي بكرة...بكرة واضح أنه في عندنا منخفض برياح
+
+592
+00:49:16,580 --> 00:49:21,340
+شديدة، تمام، وكتير من المدارس، أو عفواً من الوزارات
+
+593
+00:49:21,340 --> 00:49:28,600
+أعلنت عن عدم انتظام الدوام في الغد، اعطيني حالة تسهم
+
+594
+00:49:28,600 --> 00:49:34,680
+بكرة، ما بتقوليش لأ لأ لأ، مش...مش معروفة الزمن، لأ أنا
+
+595
+00:49:34,680 --> 00:49:37,920
+متعلق بالزمن، أما أنت حاجة أساسية موجودة، التنتين
+
+596
+00:49:37,920 --> 00:49:41,800
+نفس الشغل يا رامي، أنا ما قلت لكش الطائر بدون ريش
+
+597
+00:49:46,050 --> 00:49:49,530
+ها، الآن أنا ما قلت لكش أنا طائر بدون ريش، تمام؟
+
+598
+00:49:49,530 --> 00:49:54,090
+لكن افترض إنه طائرة مسيرة أو طائرة صغيرة للتمويه
+
+599
+00:49:54,090 --> 00:50:00,850
+كسوها بالريش، تخيل، شو رح تقول لي عليه؟ الآن إجاك،
+
+600
+00:50:00,850 --> 00:50:05,290
+قال لك في عندك object، لأ شباب، أنت الآن، ماشي
+
+601
+00:50:05,290 --> 00:50:07,930
+الحالة، ممكن تضحك، خد راحتك، لكن فعلياً إيه هيك
+
+602
+00:50:07,930 --> 00:50:13,330
+السؤال المطروح عندك؟ وجوابك من هون، يا رح تقول لي
+
+603
+00:50:13,330 --> 00:50:19,490
+plane؟ يا رح تقول لي bird، وما لكش خيار ثاني، الآن
+
+604
+00:50:19,490 --> 00:50:23,330
+اصبر شوية...الآن قلت لك أنه أنا في عندي object
+
+605
+00:50:23,330 --> 00:50:31,350
+object لا يأكل ولا يتنفس، بيطير وله عجلات، ومغطى
+
+606
+00:50:31,350 --> 00:50:36,650
+بالريش، جاوبني
+
+607
+00:50:36,650 --> 00:50:38,590
+ليش؟
+
+608
+00:50:40,420 --> 00:50:43,040
+مئه بالمئة، انتهى الأمر، إذا كنت تقول لي ما فيش عنصر
+
+609
+00:50:43,040 --> 00:50:47,740
+أو ما فيش وجود للعنصر هذا، بقول لك أنت غلطان، ممكن
+
+610
+00:50:47,740 --> 00:50:50,280
+يصير زي لما قعدوا يدوروا على الـ bigfoot، ولّاقوا
+
+611
+00:50:50,280 --> 00:50:54,540
+عينات وشعر أسود وقجز وزي...الآن أنا بدي أجيب لك
+
+612
+00:50:54,540 --> 00:51:00,780
+مثال على طائرات فعلياً...فعلياً مغطاة بالريش، الطائرات
+
+613
+00:51:00,780 --> 00:51:04,240
+اللي بيحطوها ضمن أسراب الطيور ويصورهم، أنت بتحتاج
+
+614
+00:51:04,240 --> 00:51:06,460
+حساب على National Geographic لما بيصوروهم
+
+615
+00:51:06,460 --> 00:51:11,480
+بيبعتوا لهم drone أو بيبعتوا لهم طائرة عادية؟ لأ
+
+667
+00:55:14,020 --> 00:55:18,480
+.. «أو ما تخدعش معين الأدبار» خلاص، هذا الـ «Raw»
+
+668
+00:55:18,480 --> 00:55:21,340
+بده ينشال مش لازم يظل موجود عندي أو الـ
+
+669
+00:55:21,340 --> 00:55:25,140
+«Attribute» هذا عفواً، بطل القيمة لأنه كمان مرة يا
+
+670
+00:55:25,140 --> 00:55:29,560
+جماعة الخير، الأصل... الأصل أنه أنا بأدور على
+
+671
+00:55:29,560 --> 00:55:33,100
+«Discriminative Attributes» صفات مميزة، آجي أقول
+
+672
+00:55:33,100 --> 00:55:37,580
+على سبيل المثال، آجي أقول والله الـ «Gender» بدي
+
+673
+00:55:37,580 --> 00:55:43,100
+أحطه من ضمن الـ «Attribute»، فيه تأثير الحالة الصحية
+
+674
+00:55:43,100 --> 00:55:48,220
+تأثير الحالة الصحية لطلاب مدرسة الشجاعية
+
+675
+00:55:48,220 --> 00:55:53,720
+الإبتدائية للذكور، إنت ملاحظ؟ لأن هذا الـ attribute
+
+676
+00:55:53,720 --> 00:56:00,340
+useless، لأن الـ society تبعتك اللي إنت مستهدفها
+
+677
+00:56:00,340 --> 00:56:06,160
+كلها نفس الفئة، فبالتالي هذا الـ attribute مش مميز
+
+678
+00:56:06,160 --> 00:56:07,120
+نعم
+
+679
+00:56:10,800 --> 00:56:13,700
+ما هي اللي أنا قلته، عشان هيك ما كانت الـ Fly هي
+
+680
+00:56:13,700 --> 00:56:19,720
+المؤثرة، كنت بتكلم على النفس والأكل والريش، هدول
+
+681
+00:56:19,720 --> 00:56:24,480
+اللي طائر، وكانت النفس والأكل أقوى، ليش؟ لأنه زي ما
+
+682
+00:56:24,480 --> 00:56:28,580
+قلنا، ممكن يكون في عندي طائر مغطى، مغطى بريش الآن
+
+683
+00:56:28,580 --> 00:56:32,940
+هذا مثال آخر، جاله هي الـ data set، هذا مثال شركة
+
+684
+00:56:32,940 --> 00:56:38,410
+تأمين، بدها تأمين السيارات، شركات التأمين بتفتح عشان
+
+685
+00:56:38,410 --> 00:56:40,930
+تكسب من المصاري اللي بتاخدها، حجب بوليست التأمين
+
+686
+00:56:40,930 --> 00:56:44,690
+الآن، إذا كل واحد بده يسجل عندي أو بده يأمن عندي
+
+687
+00:56:44,690 --> 00:56:48,410
+بده يعمل حادث وأنا بدي أدفع له، وأنا هاخسر، فالآن
+
+688
+00:56:48,410 --> 00:56:52,890
+قالوا بده نعمل دراسة نقدر الـ risk تبع بوليست
+
+689
+00:56:52,890 --> 00:56:57,930
+التأمين، high high ولا low، جابوا له الـ circle data
+
+690
+00:56:57,930 --> 00:57:04,430
+عندهم، هيها فيها الـ age وفيها الـ type، وفعلياً الـ
+
+691
+00:57:04,430 --> 00:57:08,150
+risk في الـ reality، هذه الأحداث كانت موجودة عندهم
+
+692
+00:57:08,150 --> 00:57:12,010
+كانت الـ risk high ولا low، الآن مفهوم الـ
+
+693
+00:57:12,010 --> 00:57:16,490
+classification أنه يجب أن يبني أو يدرس الـ data set
+
+694
+00:57:16,490 --> 00:57:21,510
+high، ويبني لي predictor أو يديني classifier عشان
+
+695
+00:57:21,510 --> 00:57:26,850
+لما أنا آجي أقول له والله أنا فيه عندي راجل عمره
+
+696
+00:57:26,850 --> 00:57:30,690
+ستين سنة وبيودي سوق sport car
+
+697
+00:57:36,030 --> 00:57:39,910
+الـ Risk High ولا Low؟ إنت بقى بتقول High، وغيرك
+
+698
+00:57:39,910 --> 00:57:43,630
+بده يقول Low، بس الآن مش على كيفك، الـ system بعد ما
+
+699
+00:57:43,630 --> 00:57:50,490
+بيعمل Analysis، تمام؟ هيروح يديني Specific Rule، وهو
+
+700
+00:57:50,490 --> 00:57:54,110
+اللي بدي يقول لي، الـ system هذا استخدمنا فيه
+
+701
+00:57:54,110 --> 00:57:59,650
+decision tree، فقال لي إذا كان العمر أقل من 25 فالـ
+
+702
+00:57:59,650 --> 00:58:07,660
+Risk High مباشرة، إذا الـ age أكبر من 25، تمام؟ العامل
+
+703
+00:58:07,660 --> 00:58:11,540
+الثاني اللي في الـ risk، نوع السيارة، إذا كانت sport
+
+704
+00:58:11,540 --> 00:58:18,620
+car فهي الـ risk high، otherwise الـ risk low، بالتالي
+
+705
+00:58:18,620 --> 00:58:25,540
+الـ prediction تبعت هذه high، تمام؟
+
+706
+00:58:25,540 --> 00:58:30,080
+هي المطلوب مني إن الـ system أو الـ Machine Learning
+
+707
+00:58:30,080 --> 00:58:34,560
+Algorithm كـ classifier ياخد الـ data set، يحللها،
+
+708
+00:58:34,560 --> 00:58:40,940
+يبني decisions، قرارات، عشان يقول في الآخر الـ risk
+
+709
+00:58:40,940 --> 00:58:43,540
+high ولا low، بينفعش يقول intermediate
+
+710
+00:58:46,030 --> 00:58:50,150
+ولا بيقوله نسبة معينة، الآن هو تعلم عشان ياخد
+
+711
+00:58:50,150 --> 00:58:54,930
+قرار إما بـ high أو low، مافيش... مافيش له خيار غير
+
+712
+00:58:54,930 --> 00:58:57,950
+هيك، الآن يا جماعة، الخيار... وهذه الميزة اللي
+
+713
+00:58:57,950 --> 00:59:01,810
+بتميز فيها الإنسان عن الآلة، الآلة بتعلم... الآلة
+
+714
+00:59:01,810 --> 00:59:05,390
+بتعلم high و low بس، فبيصير جوابك high و low،
+
+715
+00:59:05,390 --> 00:59:07,730
+مافيش... مافيش عندها غير هيك، بتع... لكن
+
+716
+00:59:07,730 --> 00:59:11,550
+الإنسان بيجي يقول لك يا عم، يصبر شوية، هذا ستين سنة
+
+717
+00:59:12,370 --> 00:59:16,810
+راجل، عاجز وراكز، ومش عارف... وربنا، ومنعم عليه
+
+718
+00:59:16,810 --> 00:59:22,610
+بالفلوس، وين المشكلة الـ Mercedes Sport Car؟ هيمشي
+
+719
+00:59:22,610 --> 00:59:26,910
+فيها بالراحة، جامد الراجل، بخاف عليها لا تنخدش،
+
+720
+00:59:26,910 --> 00:59:30,470
+فهيمشي فيها بالراحة، فهذه المعايير بتصير عند الـ
+
+721
+00:59:30,470 --> 00:59:34,410
+human بتلعب دور، لكن عند الآلة strict، واحد زائد
+
+722
+00:59:34,410 --> 00:59:37,500
+واحد يساوي اثنين، وبالتالي الـ prediction يا رامي
+
+723
+00:59:37,500 --> 00:59:41,420
+تبقى على الـ data set، ما تقول لي أنت الـ case، طبعاً
+
+724
+00:59:41,420 --> 00:59:45,180
+برجع وبأكد يا جماعة الخير اللي كانت المشكلة أنه
+
+725
+00:59:45,180 --> 00:59:48,440
+أنا رسمت الـ data set قدامك أو حاولت أبنيها قدامك
+
+726
+00:59:48,440 --> 00:59:52,580
+بالتشاور معاك، لكن لو حاططها لك إياها فجأة، هتختلف
+
+727
+00:59:52,580 --> 00:59:56,980
+نظرتك تماماً، إلا الـ mining task الثاني اللي في
+
+728
+00:59:56,980 --> 01:00:01,420
+الـ prediction، الـ regression وحكينا فيها كتير
+
+729
+01:00:01,420 --> 01:00:05,920
+قيمة الأسس، قيمة السهم، الآن لما أنا بتكلم في الـ
+
+730
+01:00:05,920 --> 01:00:10,160
+regression يا شباب، إنه أنا فعلياً بتكلم إنه بدي
+
+731
+01:00:10,160 --> 01:00:17,580
+أعمل prediction لـ value، كمية المبيعات، قيمة السهم،
+
+732
+01:00:17,580 --> 01:00:25,080
+كمية المطر المتساقطة، سرعة الرياح، درجة الحرارة، لاحظ
+
+733
+01:00:25,080 --> 01:00:29,420
+ولا مرة من المرات قلت لك بده يرتفع ولا ينخفض ولا
+
+734
+01:00:29,420 --> 01:00:33,740
+يبقى ثابت، قلت لك اديني value، وغالباً بندور على
+
+735
+01:00:33,740 --> 01:00:39,640
+continuous value، تمام؟ وهكذا... هكذا أنا بتكلم على
+
+736
+01:00:39,640 --> 01:00:44,120
+regression... regression task، باجي بقول والله
+
+737
+01:00:44,120 --> 01:00:49,060
+أسعار المنازل في المنطقة الفلانية بعد ثلاث سنوات
+
+738
+01:00:49,060 --> 01:00:55,030
+كده هتتصير، بناء على مواصفات المنزل، 200 متر، مكون من
+
+739
+01:00:55,030 --> 01:00:58,830
+أربع غرف مثلاً، وشرفة وإلى آخره، وحديقة من هالكلام
+
+740
+01:00:58,830 --> 01:01:02,830
+هذا، هذه المواصفات كلها بتقول إن البيت بعد هيك
+
+741
+01:01:02,830 --> 01:01:07,490
+هيكون هذا الحاجة مثلاً 600 ألف دولار بعد ثلاث سنوات
+
+742
+01:01:07,490 --> 01:01:12,610
+هذه regression، ليش؟ لأن فعلياً أنا بتكلم على value
+
+743
+01:01:19,930 --> 01:01:22,330
+الـ Clustering في الـ Descriptive Data Mining
+
+744
+01:01:22,330 --> 01:01:27,730
+Tasks، في الـ Descriptive، البيانات الوصفية، إحنا
+
+745
+01:01:27,730 --> 01:01:31,170
+شفنا واشتغلنا مع بعض بالمثال الأول لما قلت لك
+
+746
+01:01:31,170 --> 01:01:37,040
+وزّعناهم لمجموعتين، وزّعناهم لأربع مجموعات، إنت
+
+747
+01:01:37,040 --> 01:01:40,200
+فعلياً كنت بتوزّع الـ data points اللي هو الصور
+
+748
+01:01:40,200 --> 01:01:43,220
+كانوا عندنا أو الـ rows اللي في الـ data set اللي
+
+749
+01:01:43,220 --> 01:01:48,720
+عندي بناءً على الـ similarity تبعتها في المجموعة
+
+750
+01:01:48,720 --> 01:01:55,200
+ليش ما حطّيتش الطير أو العصفور مع الطيارة؟ لأن فيه
+
+751
+01:01:55,200 --> 01:01:57,480
+إيه الـ characteristics أو attributes خاصة عن
+
+752
+01:01:57,480 --> 01:02:02,060
+الطيارة، فكان في مجموعة ثانية، لكن لو إحنا مثلاً
+
+753
+01:02:04,060 --> 01:02:07,300
+بقولوا والله إنهم بيكونوا هدول في مجموعتين، وبناء
+
+754
+01:02:07,300 --> 01:02:13,980
+على سرعة التنقل الموجودة كمان، ممكن الطيارة والعصفور
+
+755
+01:02:13,980 --> 01:02:16,700
+يكونوا في نفس المكان ولا لأ؟ بناء على الـ
+
+756
+01:02:16,700 --> 01:02:19,480
+properties أو الـ characteristics، لكن الـ data... الـ
+
+757
+01:02:19,480 --> 01:02:24,780
+system كل اللي بياخده منك عدد الـ clusters اللي أنت
+
+758
+01:02:24,780 --> 01:02:28,780
+محتاجها، قد إيش... كام cluster أنت محتاجه؟ اثنين،
+
+759
+01:02:28,780 --> 01:02:33,490
+ثلاثة، أربعة؟ وبروح بصنّف لك إياهم أو عفواً، بجسم لك
+
+760
+01:02:33,490 --> 01:02:37,270
+إياهم وبقول لك العناصر كذا في المجموعة الفلانية،
+
+761
+01:02:37,270 --> 01:02:39,910
+العناصر كذا في المجموعة التالية، العناصر كذا في
+
+762
+01:02:39,910 --> 01:02:43,050
+المجموعة الثالثة، في الرابعة، وبعد هيك وبيقف لحد
+
+763
+01:02:43,050 --> 01:02:48,050
+الأربعة، لا بيزيد خمسة ولا بيوقف عن ثلاثة بناء على
+
+764
+01:02:48,050 --> 01:02:52,110
+الـ similarity الموجودة، هذه العناصر الآن اللي هي
+
+765
+01:02:52,110 --> 01:02:56,250
+دوائر اللون اللي باللون الأصفر، فعلياً هي الـ data
+
+766
+01:02:56,250 --> 01:03:02,450
+set تبعتنا، هي مجموعة الصور تبعتنا، الآن واضح أنه في
+
+767
+01:03:02,450 --> 01:03:07,130
+توزيع، ما بينهم، أبعاد عن بعض في الرسم، يعني فعلياً
+
+768
+01:03:07,130 --> 01:03:13,830
+مجموعاتهم، مقسمات، مصنّفات، فكانت هذه واحدة، هذه اثنتين،
+
+769
+01:03:13,830 --> 01:03:17,850
+هذه ثلاثة، وهذا هو التجميع، فبيجي دور الـ cluster
+
+770
+01:03:17,850 --> 01:03:22,470
+algorithm، بيجي يقول لي هذه العناصر من كذا لكذا في
+
+771
+01:03:22,470 --> 01:03:25,730
+المجموعة الأولى، كذا لكذا لمجموعة ثانية، كذا وكذا
+
+772
+01:03:25,730 --> 01:03:30,790
+للمجموعة اللي بعدها، من الـ Outer، طبعاً فيه هنا مثال
+
+773
+01:03:30,790 --> 01:03:33,850
+على الـ document clustering، تجميع المستندات أو
+
+774
+01:03:33,850 --> 01:03:37,170
+تصنيف المستندات، المستندات اللي موجودة على الـ web
+
+775
+01:03:37,170 --> 01:03:42,680
+أو في الـ Wikipedia، ممكن تصنف؟ أه، ممكن تصنف، بناء
+
+776
+01:03:42,680 --> 01:03:46,120
+على إيش؟ بناء على المحتوى، معناته أنا ببدأ أروح
+
+777
+01:03:46,120 --> 01:03:49,400
+أدور، آخد الـ frequent term أو الـ frequent words
+
+778
+01:03:49,400 --> 01:03:52,660
+اللي في كل document، تمام؟ وأحاول أعرف الـ
+
+779
+01:03:52,660 --> 01:03:55,800
+categories اللي موجودة، وأجسمهم بدون ما أعرف الـ
+
+780
+01:03:55,800 --> 01:03:58,200
+categories، اللي أنا بصير classification، هجسمهم
+
+781
+01:03:58,200 --> 01:04:01,780
+على مجموعات بناء على قربهم لبعضهم، حسب بديهم
+
+782
+01:04:01,780 --> 01:04:07,330
+مجموعتين، ثلاثة، أربعة، في الـ Outlier Detection
+
+783
+01:04:07,330 --> 01:04:11,830
+كذلك هي Descriptive Task، Descriptive Task، الآن
+
+784
+01:04:11,830 --> 01:04:17,710
+بتفرق شوية عن الـ Clustering، إنه أنا بدي أصير أدور
+
+785
+01:04:17,710 --> 01:04:22,630
+على النقاط البعيدة اللي مافيش شغلات بتشبهها، لو أنا
+
+786
+01:04:22,630 --> 01:04:26,030
+أجيب، وقلت لك هذا الرسم في الـ 2D لكل الـ data، 6
+
+787
+01:04:26,030 --> 01:04:31,720
+نقطة، الآن واضح إن هي هذه النقطة outlier، لأنه مافيش
+
+788
+01:04:31,720 --> 01:04:36,100
+شغلة حواليها، مافيش إشي بيشابهها، بعيدة عن
+
+789
+01:04:36,100 --> 01:04:39,940
+الجيران، نفس
+
+790
+01:04:39,940 --> 01:04:42,920
+الكلام، النقطة هاي... نفس الكلام، النقطة هاي، طب
+
+791
+01:04:42,920 --> 01:04:46,840
+الثلاث هدول، آه، بنقدر نعتبرهم outlier، الثلاث، لأنه
+
+792
+01:04:46,840 --> 01:04:51,020
+لم يصلوا إلى الحد الأدنى من التجمع، يعني أقول
+
+793
+01:04:51,020 --> 01:04:54,640
+والله مثلاً أقل عدد... أقل تجمع بدي أعتبره أربعة
+
+794
+01:04:54,640 --> 01:04:58,360
+عناصر، خمس عناصر، عشر عناصر، مائة عنصر، وبيتلاحظ
+
+795
+01:04:58,360 --> 01:05:03,360
+شغلة ثانية كمان، هدول كلياتهم جايات مع بعض as one
+
+796
+01:05:03,360 --> 01:05:08,560
+cluster، على الرغم إن النقاط نوعاً ما متباعدة، وهنا
+
+797
+01:05:08,560 --> 01:05:13,460
+بيصير إنه ماحد بيقول إن الـ density تبعت الـ
+
+798
+01:05:13,460 --> 01:05:18,280
+cluster اللي عندي تكون متساوية، المجموعات اللي عندي
+
+799
+01:05:18,280 --> 01:05:22,700
+مش بالضرورة تكون بتحتوي نفس الأعداد، ومش بالضرورة
+
+800
+01:05:22,700 --> 01:05:27,400
+كلها نفس الكثافة، واضح هذا أكثر كثافة من كل الـ
+
+801
+01:05:27,400 --> 01:05:30,380
+clusters اللي موجودة عندي ولا لأ؟ بينما هذا هو
+
+802
+01:05:30,380 --> 01:05:34,520
+الأقل كثافة، هذا الأكثر انتظاماً، هذا وهذا، بينما هذا
+
+803
+01:05:34,520 --> 01:05:38,460
+لأ، شوية في بعض، لكن في الآخر بالـ outlier detection
+
+804
+01:05:38,460 --> 01:05:44,130
+أنا بكون بهمني فقط التعامل مع النقاط اللي هي
+
+805
+01:05:44,130 --> 01:05:48,290
+المنفردة أو المعزولة عن التجمعات اللي موجودة، اللي
+
+806
+01:05:48,290 --> 01:05:55,650
+أنا عمالاً بحاول أحددها، ممكن
+
+807
+01:05:55,650 --> 01:06:00,910
+...ممكن... إنت مش ممكن تختصر تساوي تتحقق... تتحقق
+
+808
+01:06:00,910 --> 01:06:04,910
+الـ value هذه... هذه صارت out، ليش؟ بسبب إيش؟
+
+809
+01:06:04,910 --> 01:06:10,290
+مثلاً في طائر ومش مسجّل إنه بينفس، ممكن أراح...
+
+810
+01:06:10,290 --> 01:06:13,050
+أراح سجّل الحالة تبعتة بعد ما مات
+
+811
+01:06:16,070 --> 01:06:19,230
+طبعاً؟ فهيبدأ تصير تسأل هذه الـ outlier، ليش كانت
+
+812
+01:06:19,230 --> 01:06:22,650
+موجودة؟
+
+813
+01:06:22,650 --> 01:06:28,250
+الآن
+
+814
+01:06:28,250 --> 01:06:31,370
+بيصير في عندك مشكلة في data، يعني الآن تخيّل النقاط
+
+815
+01:06:31,370 --> 01:06:32,710
+موزعة هيك، مؤمن بيقول
+
+816
+01:06:46,680 --> 01:06:52,300
+لا، حتماً في عندك مشكلة في الـ data، آه
+
+817
+01:06:52,300 --> 01:06:56,040
+آه، الـ outlier، ليش أنا بدي أعمل عليها detection، إذا
+
+818
+01:06:56,040 --> 01:06:58,620
+هدفها جابت لي، طبعاً واحدة من الـ learn، من الـ
+
+819
+01:06:58,620 --> 01:07:05,570
+preprocessing، تَحْيِيْض الـ outlier، لأنه بيأثر على قرار
+
+820
+01:07:05,570 --> 01:07:08,530
+النظام أو على تعليم الـ system اللي موجود عندك
+
+821
+01:07:08,530 --> 01:07:12,610
+فإنت data set بالشكل هذا، data set غير منظم، فيها
+
+822
+01:07:12,610 --> 01:07:17,750
+مشكلة، بدك تشوف الآن إيه سبب المشكلة هذه، وتحاول
+
+823
+01:07:17,750 --> 01:07:21,890
+تتجنبها أو بتروح تحذف كل out layers point هاي اللي
+
+824
+01:07:21,890 --> 01:07:26,230
+موجودة عندك، حتى لو بيخسر data كتير، ما حد بيقول إنه
+
+825
+01:07:26,230 --> 01:07:34,360
+data، الآن يعني تخيّل... الأصل الـ data تكون ملائمة
+
+826
+01:07:34,360 --> 01:07:38,220
+وتكون ذات جودة عالية للـ task اللي إنت بتنفذها،
+
+827
+01:07:38,220 --> 01:07:42,720
+وإلا مش هتحصل على قرار سليم، لأنه كمان مرة، إذا هذه
+
+828
+01:07:42,720 --> 01:07:46,160
+النقاط بدها تدخل في الحسبة لاحقاً، في حسبة القرار
+
+829
+01:07:46,160 --> 01:07:50,200
+بتصير تحرف القرار عن الصحة، وبالتالي مافيش قدامك
+
+830
+01:07:50,200 --> 01:07:53,080
+إلّا إنك إنت إيش؟ تخلص منها
+
+831
+01:08:01,120 --> 01:08:06,140
+مش هني مشكلة، لأن أنا فعلياً بدور هل في عندي outlier
+
+832
+01:08:06,140 --> 01:08:10,460
+ولا لأ، أديك حالة إن الـ outlier هيصير بحد ذاته هو
+
+833
+01:08:10,460 --> 01:08:14,680
+المطلوب، الآن إياد الشامي بيستخدم بطاقة ائتمان
+
+834
+01:08:14,680 --> 01:08:22,160
+وبيشتري، معدل الشهر 250 دولار، تمام؟ وهذا الكلام للـ
+
+835
+01:08:22,160 --> 01:08:25,020
+trend تبعه، له خمس أو ست سنوات من يوم ما أخد
+
+836
+01:08:25,020 --> 01:08:32,470
+البطاقة، الشهر هذا، شهر اثنين 2020، مشتريات
+
+837
+01:08:32,470 --> 01:08:36,330
+إياد الشامي تجاوزت الستمائة
+
+889
+01:12:20,930 --> 01:12:26,990
+نعم، بصير ممكن أوفر، على قد ما بعرف هدول جديش هم من حجم
+
+890
+01:12:26,990 --> 01:12:30,190
+الزبائن اللي عندي، وبصير أنا بجيب الكمية اللي
+
+891
+01:12:30,190 --> 01:12:34,250
+تتناسب مع احتياجاتهم بدون ما أتضرر أنا من خسارة
+
+892
+01:12:34,250 --> 01:12:37,850
+فالـ Association Rules مهمة، وتطبيقاتها واسعة جداً
+
+893
+01:12:37,850 --> 01:12:44,170
+جديش الناس اللي بتستخدم Android و IOS، مقابلًا في
+
+894
+01:12:44,170 --> 01:12:47,190
+الـ Accessories وارتباطهم في... مع البرامج اللي
+
+895
+01:12:47,190 --> 01:12:52,090
+موجودة، وإلى آخره. فعلياً أنه أنا بأدور... بحاول
+
+896
+01:12:52,090 --> 01:12:58,230
+أدور على set of rules، أبني مجموعة من القوانين توصف
+
+897
+01:12:58,230 --> 01:13:06,310
+ارتباط العناصر مع بعضها، وهذا عادة يكون ضمن قوانين
+
+898
+01:13:06,310 --> 01:13:08,450
+محددة، مثلاً، جالي هذه في عندي transaction
+
+899
+01:13:08,450 --> 01:13:12,070
+لسوبرماركت، Beef و chicken و milk، في عندي سبعة
+
+900
+01:13:12,070 --> 01:13:18,550
+transactions الآن، لو أنا سألت: قداش عدد الناس اللي
+
+901
+01:13:18,550 --> 01:13:25,690
+اشترت حليب ولحمة مع بعض؟ آه، أخدت حليب ولحمة Beef و
+
+902
+01:13:25,690 --> 01:13:32,830
+milk واحد... اثنين... اثنين. هل أنا لو أنا سألت
+
+903
+01:13:32,830 --> 01:13:35,730
+هدول، لو قرفت راطون هي ال data 6 بقعت يا رايمي بس
+
+904
+01:13:35,730 --> 01:13:40,250
+عشان أنا أقدر أتخيل الموضوع، قديش أقول والله لأن
+
+905
+01:13:40,250 --> 01:13:44,620
+في ارتباط بين اللحمة والحليب مثلاً. Okay، جديش هذا
+
+906
+01:13:44,620 --> 01:13:49,080
+الكلام مدعوم من ال data set؟ جديش حقيقة ما موجود؟
+
+907
+01:13:49,080 --> 01:13:53,300
+اثنين على سبعة، اثنين على سبعة نسبة متدنية، وصلتش
+
+908
+01:13:53,300 --> 01:13:57,120
+لخمسين في المئة، ولا لأ؟ ولو أتينا مثلاً، جديش
+
+909
+01:13:57,120 --> 01:14:02,320
+الناس اللي أخدت مثلاً ال chicken و beef مع بعض؟
+
+910
+01:14:02,320 --> 01:14:11,710
+واحد، اثنين، واحد، اثنين، ثلاثة. ال beef والـ
+
+911
+01:14:11,710 --> 01:14:15,110
+chicken، ال beef والـ chicken واحدة... اثنين...
+
+912
+01:14:15,110 --> 01:14:19,070
+ثلاثة... وين الرابع يا أخو؟ ال cheese... ال cheese
+
+913
+01:14:19,070 --> 01:14:23,110
+...جبنة... جبنة... تمام؟ الآن ال beef والـ chicken
+
+914
+01:14:23,110 --> 01:14:28,350
+هذا ثلاثة... هذا الارتباط أكثر، بس برضه ما وصلش...
+
+915
+01:14:28,350 --> 01:14:31,710
+بس لكن أفضل من الأولاني، على الأقل ممكن يصير فيه
+
+916
+01:14:31,710 --> 01:14:35,250
+توجه أن والله أن الناس... يعني مش كلها بتاكل لحمة
+
+917
+01:14:35,250 --> 01:14:38,490
+حمراء، فبياخدوا اللحمة وبياخدوا الدجاج لأنهم هم في
+
+918
+01:14:38,490 --> 01:14:44,820
+البيت. الناس مقسمين على موضوع الأكل، ففي الآخر ممكن
+
+919
+01:14:44,820 --> 01:14:47,940
+أحسب ال support وأحسب ال confidence، حنشوف جديش
+
+920
+01:14:47,940 --> 01:14:51,540
+دقة الكلام، الرول اللي أنا بقول عليه هذا بشكل
+
+921
+01:14:51,540 --> 01:14:56,300
+صحيح. وزن التكرار... اه، التكرار مهم... وزنه... كل
+
+922
+01:14:56,300 --> 01:15:01,380
+موقف... مثلاً اثنين تكرر تسعة، أربع مرات الملك لحاله
+
+923
+01:15:01,380 --> 01:15:06,060
+يعني بكون frequent item. لأ، المقصد أنه لو قسمنا كل
+
+924
+01:15:06,060 --> 01:15:10,990
+...لأ لأ، هو الأنش كمان، الفكرة وين إذا بتكلم عن
+
+925
+01:15:10,990 --> 01:15:15,070
+الملك لحاله، هذا attribute، إذا ال beef لحالها دي
+
+926
+01:15:15,070 --> 01:15:19,630
+attribute، الآن باجي بتكلم: هذا جديش ال frequent،
+
+927
+01:15:19,630 --> 01:15:22,730
+جديش الطلب عليه، okay، لكن مش association،
+
+928
+01:15:22,730 --> 01:15:24,930
+association لازم يكون في عندي two different
+
+929
+01:15:24,930 --> 01:15:29,690
+attributes على الأقل متلازمين مع بعضهم، هدول اللي
+
+930
+01:15:29,690 --> 01:15:34,340
+أنا ببدأ أورّي عليهم. ال Minimum Support والـ Minimum
+
+931
+01:15:34,340 --> 01:15:37,700
+Confidence، حنتكلم عليهم لاحقاً لما نروح على ال
+
+932
+01:15:37,700 --> 01:15:42,500
+cluster، على ال association rule بالتفصيل. الآن، آخر
+
+933
+01:15:42,500 --> 01:15:47,800
+شغلة بدنا إياها في محاضرة اليوم، قبل ما نتكلم في ال
+
+934
+01:15:47,800 --> 01:15:54,260
+tools، يعني إحنا فعلياً... فعلياً قدرنا نلخص اليوم الـ
+
+935
+01:15:54,260 --> 01:15:58,320
+mining tasks الخمسة اللي إحنا بدنا إياهم، اللي هم
+
+936
+01:16:02,200 --> 01:16:05,940
+classification، regression، as predictive tasks، بعد
+
+937
+01:16:05,940 --> 01:16:10,520
+هيك، clustering و association rules و outlier
+
+938
+01:16:10,520 --> 01:16:14,440
+detection، as descriptive tasks. بالنسبة للـ tools
+
+939
+01:16:14,440 --> 01:16:16,820
+اللي بدنا نشتغل عليها، طبعاً بإمكانك تشتغل بالـ data
+
+940
+01:16:16,820 --> 01:16:20,800
+mining، أي شغلة programming languages، ممكن Python والـ
+
+941
+01:16:20,800 --> 01:16:23,580
+R والـ Java، و software packages، في عندنا الـ
+
+942
+01:16:23,580 --> 01:16:26,720
+RapidMiner والـ Weka والـ Orange، هذه أساس الـ
+
+943
+01:16:26,720 --> 01:16:32,260
+software packages. إحنا بالنسبة لنا، حنشتغل Python و
+
+944
+01:16:32,260 --> 01:16:36,180
+RapidMiner، فبدي منك تنزل على جهازك الآن، تنزل على
+
+945
+01:16:36,180 --> 01:16:41,160
+جهازك RapidMiner، point 9، RapidMiner Studio، والـ
+
+946
+01:16:41,160 --> 01:16:48,700
+Python، بدي تنزل لي الـ Anaconda Spider distribution
+
+947
+01:16:51,730 --> 01:16:56,050
+ما هو؟ عشان أنا أريحك من تنزيل المكتبات هاي، نزل الـ
+
+948
+01:16:56,050 --> 01:16:58,890
+Anaconda Spider Distribution تبع الـ Python، هذه
+
+949
+01:16:58,890 --> 01:17:03,690
+فيها كل الـ libraries اللي أنت محتاجها، تمام؟ الله
+
+950
+01:17:03,690 --> 01:17:06,390
+يعطيكم العافية، ونشوفكم إن شاء الله لمحاضرة الجاية
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/mLZ1tevgxvs_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/mLZ1tevgxvs_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..d775b84c237f53b85d8f371a4f0b5cb317d60b06
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/mLZ1tevgxvs_raw.srt
@@ -0,0 +1,3884 @@
+1
+00:00:05,300 --> 00:00:07,540
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:07,540 --> 00:00:12,300
+اليوم ان شاء الله .. ان شاء الله تعالى هنكمل في ال
+
+3
+00:00:12,300 --> 00:00:14,680
+introduction على ال data mining نتعرف على ال data
+
+4
+00:00:14,680 --> 00:00:19,000
+mining tasks ونشوف ال tools اللي هنشغل عليها خلال
+
+5
+00:00:19,000 --> 00:00:26,950
+الفصل ال .. لكن ال .. بدنا نعمل review سريعةلما تم
+
+6
+00:00:26,950 --> 00:00:30,170
+عرضه الأسبوع الماضي بدي واحد منكم على السريع الآن
+
+7
+00:00:30,170 --> 00:00:33,270
+ذكرني سواء كان من الدفتر، من ال slides، من دماغه،
+
+8
+00:00:33,270 --> 00:00:36,690
+طبعا لو كان من دماغه أفضل، ما هو، ما هي ال data
+
+9
+00:00:36,690 --> 00:00:41,270
+mining، عرفلي ال data mining أه
+
+10
+00:00:41,270 --> 00:00:44,990
+محمد عملية
+
+11
+00:00:44,990 --> 00:00:47,650
+cleaning و analyzing ال data عشان أطلع منها
+
+12
+00:00:47,650 --> 00:00:51,250
+knowledge more professional definition، اعطيني
+
+13
+00:00:51,250 --> 00:00:55,800
+التعريفprofessional أكتر كلامك صح لكن احنا بدنا
+
+14
+00:00:55,800 --> 00:01:02,300
+الآن تعريف رسم محمد أحمد فروخ knowledge discovery
+
+15
+00:01:02,300 --> 00:01:15,800
+كمان non trivial implicit useful
+
+16
+00:01:21,930 --> 00:01:28,370
+أيوة novel طيب
+
+17
+00:01:28,370 --> 00:01:32,690
+عرفنا ال data mining على إن هي عبارة عن ال process
+
+18
+00:01:32,690 --> 00:01:38,270
+for extracting interesting patterns اللي هي
+
+19
+00:01:38,270 --> 00:01:42,690
+الأنماط المهمة أو المثيرة أو أو إلى آخرها، مصبوط؟
+
+20
+00:01:42,690 --> 00:01:47,620
+وقلنا كلمة interesting pattern تعني novelإنه ال
+
+21
+00:01:47,620 --> 00:01:50,600
+pattern هذا أو النمط هذا جديد ما حد شافه قبل هيك
+
+22
+00:01:50,600 --> 00:01:55,640
+previously unseen non-trivial مش تقليدي وطبعا
+
+23
+00:01:55,640 --> 00:02:00,000
+تنتهي متكافئات تقريبا لكن إذا كنت أنا بتتكلم إنه
+
+24
+00:02:00,000 --> 00:02:03,460
+ال process نفسها non-trivial إنه العملية مش عملية
+
+25
+00:02:03,460 --> 00:02:06,360
+تقليدية مش عملية سهلة مش كل الناس هتقوم فيها K
+
+26
+00:02:06,360 --> 00:02:09,060
+implicit فهو حقيقي أو valid
+
+27
+00:02:11,940 --> 00:02:16,100
+نطق Simplest يعني بين جثين مش Fake فده حقيقي موجود
+
+28
+00:02:16,100 --> 00:02:21,160
+في ال data و useful عشان يبقى بنى عليه action مفيد
+
+29
+00:02:21,160 --> 00:02:26,200
+للناس وطبعا Understandable
+
+30
+00:02:26,200 --> 00:02:32,180
+مفهوم عشان الناس تقدر تبني عليه action previously
+
+31
+00:02:32,180 --> 00:02:38,380
+unknown أو unseen اللي هي novel تمام قلنا بعد هيك
+
+32
+00:02:38,380 --> 00:02:43,050
+أن ال data miningتمر ب .. او اي data mining
+
+33
+00:02:43,050 --> 00:02:48,110
+project فيه له سبع مراحل سبع مراحل بتبدأ من
+
+34
+00:02:48,110 --> 00:02:54,570
+cleaning integration
+
+35
+00:02:54,570 --> 00:02:59,910
+selection
+
+36
+00:02:59,910 --> 00:03:05,630
+transformation
+
+37
+00:03:05,630 --> 00:03:08,830
+mining
+
+38
+00:03:14,020 --> 00:03:21,740
+Evaluation وPresentation وعشان
+
+39
+00:03:21,740 --> 00:03:26,160
+ما تنساش من الـ Cleaning لحد الـ Mining مرتبط
+
+40
+00:03:26,160 --> 00:03:30,320
+بمصطلح Data
+
+41
+00:03:30,320 --> 00:03:36,000
+Cleaning Data Integration Data Selection Data
+
+42
+00:03:36,000 --> 00:03:40,570
+Transformationdata mining أنا على السريع cleaning
+
+43
+00:03:40,570 --> 00:03:44,790
+كانت تقتضي مني ان اعبّل incomplete data او ال
+
+44
+00:03:44,790 --> 00:03:52,270
+missing data اعمل handling للمissing data noisy
+
+45
+00:03:52,270 --> 00:04:00,610
+data inconsistent data شو
+
+46
+00:04:00,610 --> 00:04:04,050
+يعني missing data ان في عندى field مافيش فيه value
+
+47
+00:04:04,050 --> 00:04:08,330
+nullوال field هذا أنا محتاجه فبالتالي بدي أشوف كيف
+
+48
+00:04:08,330 --> 00:04:12,470
+بدي أعب ال value المناسب أو الحقيقية أو الصحيحة أو
+
+49
+00:04:12,470 --> 00:04:16,750
+القريبة من الصحيحة لل attributes هذا noisy إنه
+
+50
+00:04:16,750 --> 00:04:20,010
+فيها خطأ ال value واضح فيها خطأ مثل الراتب بال
+
+51
+00:04:20,010 --> 00:04:26,030
+salary أو الراتب بال salary ال salary بالسالب أو
+
+52
+00:04:26,030 --> 00:04:31,190
+الراتب بالسالب وبالتالي أنا بدي أنتبه لهذه الشغلة
+
+53
+00:04:31,190 --> 00:04:32,530
+inconsistent
+
+54
+00:04:35,480 --> 00:04:40,460
+في two fields متناقضين مع بعض عمره تلاتين سنة وهو
+
+55
+00:04:40,460 --> 00:04:44,700
+موليدي الألفين تمام؟ أو mail و pregnant زي ما قلنا
+
+56
+00:04:44,700 --> 00:04:50,440
+سابقا ال integration data integration أن ال data
+
+57
+00:04:50,440 --> 00:04:54,700
+source تبعتي أو مصادر البيانات تبعتي مختلفة فبدي
+
+58
+00:04:54,700 --> 00:04:58,560
+أكون عندي المقدرة على أني أقدر أجمعالبيانات هذه
+
+59
+00:04:58,560 --> 00:05:02,020
+عشان تكمل بعضها وضربنا المثال إنه أنا بدي أشتغل
+
+60
+00:05:02,020 --> 00:05:06,400
+على مشروع يقيم لأو يتنبأ لي بتحصيل الطالب في
+
+61
+00:05:06,400 --> 00:05:08,600
+المدرسة بناء على الحالة الصحية تبعته أو الأرشيف
+
+62
+00:05:08,600 --> 00:05:12,140
+الصحي تبعه وزارة التربية والتعليم ووزارة الصحة
+
+63
+00:05:12,140 --> 00:05:15,220
+مصدرين مختلفين للبيانات فبالتالي أنا لازم أقدر
+
+64
+00:05:15,220 --> 00:05:17,740
+أكون عند التعامل معاهم وهنا بلزمك تعامل مع
+
+65
+00:05:17,740 --> 00:05:23,620
+البيانات بلزمك database وبرمجة غالبا في ال data
+
+66
+00:05:23,620 --> 00:05:27,670
+selectionاختيار البيانات بعدما جمعت البيانات وصارت
+
+67
+00:05:27,670 --> 00:05:32,170
+في عندي huge data أو many attributes مين اللي بده
+
+68
+00:05:32,170 --> 00:05:34,970
+يظل ومين اللي بده يبقى؟ مين ال relevant attribute
+
+69
+00:05:34,970 --> 00:05:39,110
+ومين ال irrelevant؟ وبالتالي أنا مطلوب مني أحذف ال
+
+70
+00:05:39,110 --> 00:05:42,510
+irrelevant أحذف ال redundant attribute وأحذف فقط
+
+71
+00:05:42,510 --> 00:05:47,890
+بال relevant attributes ال data transformation ال
+
+72
+00:05:47,890 --> 00:05:52,070
+rules أو ال knowledge أو ال pattern احنا اتفقنا
+
+73
+00:05:52,070 --> 00:05:58,170
+أنه في تعريفنا لل patternهو عبارة عن group أو
+
+74
+00:05:58,170 --> 00:06:02,930
+ordering parts repeated parts، مصبوط؟ يعني هذه
+
+75
+00:06:02,930 --> 00:06:07,410
+العناصر أو هذه الـ parts ظهرت بترتيب معين وبنسبة
+
+76
+00:06:07,410 --> 00:06:12,990
+تكرار معينة في الـ transformation لو كان عندي الـ
+
+77
+00:06:12,990 --> 00:06:18,770
+date of birth قلنا عدد ال values اللي عندي كبير
+
+78
+00:06:18,770 --> 00:06:25,450
+جداً وبالتالي بيصير التكرار الـ patternتكرار البتر
+
+79
+00:06:25,450 --> 00:06:31,550
+قليل جدا طيب بهمش أبسط الأمور يعني كل الناس اللي
+
+80
+00:06:31,550 --> 00:06:35,970
+مولودين في نفس السنة ممكن أنا أستغني عن الشهر و
+
+81
+00:06:35,970 --> 00:06:39,090
+أستغني عن اليوم لأنه في الآخر لو سألت أي واحد فيهم
+
+82
+00:06:39,090 --> 00:06:43,390
+مثلا للناس اللي ولدت في الألفين جديش عمرك يا فلان؟
+
+83
+00:06:44,810 --> 00:06:48,750
+عشرين، مباشرة عشرين أو تسعة عشر، بغض النظر، ليش؟
+
+84
+00:06:48,750 --> 00:06:52,750
+لأن كله مولود في سنة .. فهذه أسهل، وفعليا ما أبعد
+
+85
+00:06:52,750 --> 00:06:56,130
+عن الحقيقة، بالعكس هي الحقيقة بذاتها، إن هو موليد
+
+86
+00:06:56,130 --> 00:07:01,490
+الألفين للآن، فنحن نتكلم عن عشرين سنة طيب، لاحظ إن
+
+87
+00:07:01,490 --> 00:07:08,570
+أنا فعليا قللت ال variant dataالاختلاف الكتير في
+
+88
+00:07:08,570 --> 00:07:12,090
+ال data قللته وصار بإمكاني الآن اعتمد على ال year
+
+89
+00:07:12,090 --> 00:07:16,590
+فقط أو الأفضل من ال year كمان أن أروح أعمل ال age
+
+90
+00:07:16,590 --> 00:07:19,970
+ل category بيصير مثلا و الله بتكلم على فئة أطفال
+
+91
+00:07:19,970 --> 00:07:26,910
+شباب، يافعين، كبار مثلا عجزاء، هذه خمس فئات بدل ما
+
+92
+00:07:26,910 --> 00:07:33,070
+كنت بتعامل مع خمسين، ستين، رقم مختلف لأ صار عندي
+
+93
+00:07:33,070 --> 00:07:38,710
+هان و هيك أنا بأضمن أن ال pattern تبعيصار فيه
+
+94
+00:07:38,710 --> 00:07:42,290
+frequent أكثر وبالتالي في ال data transformation
+
+95
+00:07:42,290 --> 00:07:46,750
+تصير صحيح ال data mining هي عبارة عن ال task هو ال
+
+96
+00:07:46,750 --> 00:07:49,950
+prediction task اللي أنا بدغوم فيها فعليا هي البحث
+
+97
+00:07:49,950 --> 00:07:54,570
+عن المعرفة أو knowledge extraction اللي بديها ال
+
+98
+00:07:54,570 --> 00:07:55,770
+selection قبل ال cleaning
+
+99
+00:08:02,610 --> 00:08:06,110
+أجازك عشان تخفف العدد أنت اللي عندك okay الآن ..
+
+100
+00:08:06,110 --> 00:08:12,630
+الآن أنت عندك ال data set عندك ال data set لاجئات
+
+101
+00:08:12,630 --> 00:08:15,870
+فيها value ناقصة أو مفقودة أو فيها value غير صحيحة
+
+102
+00:08:15,870 --> 00:08:21,250
+ممكن فعليا تروح تقضر تروح تدور برا أنت عشان تجيبها
+
+103
+00:08:21,250 --> 00:08:26,850
+الآن بعدين أنا في ال selectionغالبا ماعنديش .. أنا
+
+104
+00:08:26,850 --> 00:08:29,930
+بقدر أحكم على الأسماء والأرقام، يعني رقم تليفون
+
+105
+00:08:29,930 --> 00:08:34,230
+الشخص مش مهم لصحته، رقم هويته مش مهم لمستوى حالته
+
+106
+00:08:34,230 --> 00:08:38,570
+إجتماعيا، مصبوط؟ اسمه مش متعلق بتحصيله الدراسي،
+
+107
+00:08:38,570 --> 00:08:40,650
+هذه كلها الـrelevant attribute أنا بقدر أعتمد
+
+108
+00:08:40,650 --> 00:08:44,410
+عليها مصبوط، وأحذفهم الجبللكن في عندى مجموعه
+
+109
+00:08:44,410 --> 00:08:46,190
+هتلاقي فيه مجموعه عن الـ attributes أنا ماقدرش
+
+110
+00:08:46,190 --> 00:08:50,370
+أتكلم عليها فإيش حضر؟ حضر بعد ال integration بعد
+
+111
+00:08:50,370 --> 00:08:54,090
+ال integration أروح أبدأ أستخدم بعض ال algorithm
+
+112
+00:08:54,090 --> 00:08:57,370
+اللى تروح تحسب ال correlation أو ال dependency بين
+
+113
+00:08:57,370 --> 00:09:01,650
+ال attributes عشان أقرر مين أشيل و مين أبقى
+
+114
+00:09:01,650 --> 00:09:06,310
+فبالتالي لأ لازم تكون فعليا ال cleaning number one
+
+115
+00:09:06,310 --> 00:09:10,470
+لأنه بعد أنت الآن ال cleaning لل source الأول ال
+
+116
+00:09:10,470 --> 00:09:14,340
+cleaning لل source التاني و بعدين بتيجي لمرحلاتالـ
+
+117
+00:09:14,340 --> 00:09:17,500
+integration لأنه كمان مرة الـ cleaning هذه بتتم
+
+118
+00:09:17,500 --> 00:09:21,420
+بمعرفة ال source يعني الآن مصدر بيانات وزارة الصحة
+
+119
+00:09:21,420 --> 00:09:26,980
+أنا والله في السنة 2005 ل 2007 مش ملاقي حاجة أو في
+
+120
+00:09:26,980 --> 00:09:31,640
+عندي بعض ال missing values للطفل هذا زودولي فيهم
+
+121
+00:09:31,640 --> 00:09:37,440
+قبل ما أفكر في الموضوع ال integration الآن زي ما
+
+122
+00:09:37,440 --> 00:09:41,350
+قلنا ال mining هي عبارة عن ال taskاللي أنا فعلياً
+
+123
+00:09:41,350 --> 00:09:44,710
+بدي من خلالها أعمل extract للـ knowledge بعد هيك
+
+124
+00:09:44,710 --> 00:09:46,410
+الـ knowledge اللي أنا حصلت عليها بدي أعملها
+
+125
+00:09:46,410 --> 00:09:50,550
+evaluation وأعمللها presentation هذا اللي هيكون
+
+126
+00:09:50,550 --> 00:09:55,610
+محطة حضرتنا اليوم في موضوع الـ data mining task
+
+127
+00:09:55,610 --> 00:10:00,790
+لكن كنا سألناكوا سؤال أو كنا أعطاناكوا شبه واجب لل
+
+128
+00:10:00,790 --> 00:10:08,660
+discussion time series datatemporal data special
+
+129
+00:10:08,660 --> 00:10:18,860
+data و series ال sequence data أيوة من يبدأ يسمعنا
+
+130
+00:10:18,860 --> 00:10:23,480
+بالأول بس اللي حضروا الواجب أو حضروا الكلام ده
+
+131
+00:10:23,480 --> 00:10:29,160
+يرفعوا إيديهم الشباب طيب الآن يعني في عندنا واحد
+
+132
+00:10:29,160 --> 00:10:38,260
+اتنين تلاتة أربعة خمسة ستة مش مجايبين سبعةليش؟ أول
+
+133
+00:10:38,260 --> 00:10:43,240
+محاضرة؟ أول محاضرة .. مش أول محاضرة .. okay ماشي
+
+134
+00:10:43,240 --> 00:10:47,500
+الحالة okay .. نرد .. نتمنى من الجميع يكون التزام
+
+135
+00:10:47,500 --> 00:10:50,400
+حديدي في الشغلات اللي إحنا عايش بنقض بها .. آه
+
+136
+00:10:50,400 --> 00:10:55,320
+مؤمن .. series .. time series data بصوت عالي بس
+
+137
+00:10:55,320 --> 00:10:58,020
+عشان كلنا نسمع و الكاميرا تقدر تربيت صوتك .. أيوة
+
+138
+00:10:58,020 --> 00:10:59,400
+it's a series of data
+
+139
+00:11:02,930 --> 00:11:06,910
+يعني هي عبارة عن مجموعة من البيانات مؤرشفة تبعًا
+
+140
+00:11:06,910 --> 00:11:11,010
+لظهورها الزمني، تمام؟ في حد حصل على شغل غير هيك
+
+141
+00:11:11,010 --> 00:11:14,150
+شباب، أيوة؟ هو الوصول للبيانات التي اتصل الزمن مع
+
+142
+00:11:14,150 --> 00:11:17,410
+بعضها لبعض ووصول إلى رمضان معين يمكن من خلال
+
+143
+00:11:17,410 --> 00:11:21,650
+التنبؤ بالقيم المتقبلة هيك أنت بتتكلم على الـTime
+
+144
+00:11:21,650 --> 00:11:26,270
+Series Mining، تمام؟ لكن احنا بتتكلم على الـTime
+
+145
+00:11:26,270 --> 00:11:29,750
+Series Data أيوة، حسن؟ Data connected to look at
+
+146
+00:11:31,670 --> 00:11:37,190
+Data جميعات بناءً على تغييراتها تبعًا للتسلسل
+
+147
+00:11:37,190 --> 00:11:40,970
+الزمني يعني بينجو سينا الشباب كل ال data اللي
+
+148
+00:11:40,970 --> 00:11:47,510
+مرتبطة بعامل الزمن بصيصنها على إنها إيش؟ الـ Time
+
+149
+00:11:47,510 --> 00:11:50,630
+Series Data، أمثلة مين بقدر يديني مثال؟ آه رامي
+
+150
+00:11:50,630 --> 00:11:53,650
+مثلًا
+
+151
+00:11:53,650 --> 00:11:58,250
+الأمراض، تطور الأمراض الـ Time Series
+
+152
+00:12:02,050 --> 00:12:06,150
+درجات الحرارة والرطوبة القياسات الطقس بشكل عام
+
+153
+00:12:06,150 --> 00:12:16,570
+غيره عدد مثلا المسافرين خارج البلاد زيادة الكثافة
+
+154
+00:12:16,570 --> 00:12:21,210
+السكانية الكثوف والخصوف الظاهر الطبيعي السؤال يا
+
+155
+00:12:21,210 --> 00:12:25,190
+شباب الفترة الزمنية هذه هل لها better معين يعني كل
+
+156
+00:12:25,190 --> 00:12:29,680
+دقيقة كل ثانية كل ساعة كل يوم كل .. كدهففي الآخر
+
+157
+00:12:29,680 --> 00:12:33,360
+أنت فعليًا جمعتي ال data كيف؟ يعني الآن تعوضت
+
+158
+00:12:33,360 --> 00:12:37,440
+الأرصاد، تعوضت الأرصاد بيحاولوا يجمعوا ال data
+
+159
+00:12:37,440 --> 00:12:41,500
+مثلًا على مدار الأيام لكن ال sensor بيزودهم،
+
+160
+00:12:41,500 --> 00:12:47,540
+بيزودهم بالقراءات على مدار الساعة وبالتالي كل ثاني
+
+161
+00:12:47,540 --> 00:12:52,140
+عنده قراءة لكن هو متى، بإيش بيحتفظ؟ بالقراءات اللي
+
+162
+00:12:52,140 --> 00:12:57,630
+بيصير فيهاتغيير وبيجي يقولك والله هاي تبع للزمن
+
+163
+00:12:57,630 --> 00:13:00,490
+كان كذا يعني دائما ال data مرتبط أو تجمع بعامل
+
+164
+00:13:00,490 --> 00:13:11,770
+الزمن temporal data temporal data هاني ال temporal
+
+165
+00:13:11,770 --> 00:13:16,750
+.. هاني هاني بقول ان ال temporal data هي عبارة عن
+
+166
+00:13:16,750 --> 00:13:24,080
+dataكنا معنين شغلتين الـ state الحالة والفترة
+
+167
+00:13:24,080 --> 00:13:27,760
+الزمنية اللي ظهرت فيها الحالة هاي غيره انا عبدالله
+
+168
+00:13:27,760 --> 00:13:34,940
+كريم temporal يعني
+
+169
+00:13:34,940 --> 00:13:38,920
+انت حصرتليها في الوثر جبتلي مثال عليها temporal شو
+
+170
+00:13:38,920 --> 00:13:43,620
+تعريف ال temporal data؟
+
+171
+00:13:43,620 --> 00:13:46,300
+طيب، related to time and instance
+
+172
+00:13:51,130 --> 00:13:57,290
+ما زلت بتتكلم عن ال time series ال state .. الحالة
+
+173
+00:13:57,290 --> 00:14:00,670
+.. شو .. التغير اللي في الحالة .. كيف كانت .. يعني
+
+174
+00:14:00,670 --> 00:14:08,190
+أو كأن الآن .. هذا الزمن .. هذا الزمن .. هذا
+
+175
+00:14:08,190 --> 00:14:12,430
+العامل الزمني .. كيف الحالة كانت هان و الحالة كانت
+
+176
+00:14:12,430 --> 00:14:13,330
+هان و الحالة كانت هان
+
+177
+00:14:22,460 --> 00:14:28,320
+بين الـ time series و ال temporal وجود الحالة تبع
+
+178
+00:14:28,320 --> 00:14:31,800
+ال object يعني لاحظ أنه أنا قاعد بقى أتدور على
+
+179
+00:14:31,800 --> 00:14:35,960
+حالة ال object بدورش على specific valuesعلى value
+
+180
+00:14:35,960 --> 00:14:38,540
+يعني لما أتكلم على حالة أو ال state غالبًا لما
+
+181
+00:14:38,540 --> 00:14:42,520
+أتكلم على table of values مجموعة من القيمة عشان
+
+182
+00:14:42,520 --> 00:14:45,500
+تصل تمامًا يعني أسقطها على ال object oriented ال
+
+183
+00:14:45,500 --> 00:14:49,120
+state هي عبارة عن مجموعة ال values اللي حملتها ال
+
+184
+00:14:49,120 --> 00:14:54,580
+attributes اللي عندي ممتاز ال special data special
+
+185
+00:14:54,580 --> 00:15:00,760
+data يا رهنصبر ايه يا أهب special ماكتبتش
+
+186
+00:15:00,760 --> 00:15:02,440
+عدها مؤمن special
+
+187
+00:15:09,660 --> 00:15:13,340
+ماذا رأيك يا عمر؟ انه مع المطحون كأثمان دي هتفيلوا
+
+188
+00:15:13,340 --> 00:15:17,720
+قيمة رقمية في نصات ال .. ال .. ال .. الاحتياطات ده
+
+189
+00:15:17,720 --> 00:15:22,180
+100% الان الشغلة الجديدة اللي هتدخل على الموضوع في
+
+190
+00:15:22,180 --> 00:15:27,240
+الـ Special Data ان الموقع الجغرافي او الاحداثات
+
+191
+00:15:27,240 --> 00:15:32,040
+الجغرافية مهمة جدا تمام؟ ان انا فعليا بدي اشوف ايش
+
+192
+00:15:32,040 --> 00:15:36,150
+القيم او ايش ال estate او ايش التغييراتواخد
+
+193
+00:15:36,150 --> 00:15:40,830
+بالمعيار أو بعين الحسبان المكان الجغرافي اللى
+
+194
+00:15:40,830 --> 00:15:43,970
+موجود فيه ال object أو الشغلة أو ال event اللى أنا
+
+195
+00:15:43,970 --> 00:15:50,180
+بدي أشتغل عليهاكل العلاقة لها علاقة بالـ GIS لأنه
+
+196
+00:15:50,180 --> 00:15:52,820
+فعليًا كل الشغل بدور وين .. هان .. الآن لما يجي
+
+197
+00:15:52,820 --> 00:15:57,240
+بتتكلم بتنبؤ بالزلازل و الشغلات هاي كلها داتها على
+
+198
+00:15:57,240 --> 00:16:00,800
+special data بناءً على الـ historical data اللي
+
+199
+00:16:00,800 --> 00:16:04,120
+موجودة و المعرفة الحالية و اللي بيصير على وجه
+
+200
+00:16:04,120 --> 00:16:07,020
+الأرض بيصير يقولك و الله ممكن يصير زلزال في المطر
+
+201
+00:16:07,020 --> 00:16:10,420
+هم كيف هيتعرف يقولك زلزال متوقع يصير زلزال في عرض
+
+202
+00:16:10,420 --> 00:16:15,380
+.. في العرض البحر على بعد مش عارف جداش، قوة كده
+
+203
+00:16:15,380 --> 00:16:20,170
+بناءً على ..Special data اللي موجودة عندنا إيش
+
+204
+00:16:20,170 --> 00:16:25,570
+الأخيرة؟ كانت الـ sequence إيش الـ sequence data؟
+
+205
+00:16:25,570 --> 00:16:31,050
+فرخ؟ statistically relevant patterns between data
+
+206
+00:16:31,050 --> 00:16:33,670
+و values طب أنا حرم لو قلتها بالعربي يعني نفهم
+
+207
+00:16:33,670 --> 00:16:38,150
+إحنا منك أسهل هيك على السريع أيوة اللي هو data
+
+208
+00:16:38,150 --> 00:16:44,870
+مرتبطة بعض إلى مفتوح مثلًا فيه طب إيش الفرق بينها
+
+209
+00:16:44,870 --> 00:16:49,880
+و بين ال time series؟أيوة أحمد وممكن تستعيني
+
+210
+00:16:49,880 --> 00:16:59,800
+بتايمر لأنه ساكت يعني مالهاش
+
+211
+00:16:59,800 --> 00:17:02,400
+علاقة بالزمن؟ مالهاش علاقة بالزمن؟ مالهاش علاقة
+
+212
+00:17:02,400 --> 00:17:05,860
+بالزمن؟ مالهاش علاقة بالزمن؟ مالهاش علاقة بالزمن؟
+
+213
+00:17:05,860 --> 00:17:08,400
+مالهاش علاقة بالزمن؟ مالهاش علاقة بالزمن؟ مالهاش
+
+214
+00:17:08,400 --> 00:17:10,780
+علاقة بالزمن؟ مالهاش علاقة بالزمن؟ مالهاش علاقة
+
+215
+00:17:10,780 --> 00:17:11,820
+بالزمن؟ مالهاش علاقة بالزمن؟ مالهاش علاقة بالزمن؟
+
+216
+00:17:11,820 --> 00:17:12,380
+مالهاش علاقة بالزمن؟ مالهاش علاقة بالزمن؟ مالهاش
+
+217
+00:17:12,380 --> 00:17:13,260
+علاقة بالزمن؟ مالهاش علاقة بالزمن؟ مالهاش علاقة
+
+218
+00:17:13,260 --> 00:17:19,750
+بالزمن؟ مالهاش علاقة بالزالتغييرات لاحقا، هو هذا
+
+219
+00:17:19,750 --> 00:17:23,490
+هو محط الدراسة وأكثر مثال إليها اللي هو الـ DNA
+
+220
+00:17:23,490 --> 00:17:28,030
+Sequence في أمثلة تانية الـ Web Serving الـ Web
+
+221
+00:17:28,030 --> 00:17:31,970
+Serving الـ Web Serving، Ok اللي هو تصفح الإنترنت
+
+222
+00:17:31,970 --> 00:17:36,770
+للأشخاص آه يا هاشم، إيش فيه عندك؟ نفس ما قالوا،
+
+223
+00:17:36,770 --> 00:17:41,990
+حضرت يا هاشم؟ ماشي الحل تمام، يعني فعليا أنا في
+
+224
+00:17:41,990 --> 00:17:45,510
+الـ Data Mining بقدر أشتغل في كل الإتجاهات سواء في
+
+225
+00:17:45,510 --> 00:17:50,730
+الـأرقام؟ طيب، بدي أسأل في الـ Biology في الـ
+
+226
+00:17:50,730 --> 00:17:55,450
+Geography في الـ Geology في كل المجالات أنا ممكن
+
+227
+00:17:55,450 --> 00:17:59,290
+أشغل بناءً على ال data اللي موجودة سؤال اللي بيطرح
+
+228
+00:17:59,290 --> 00:18:05,270
+نفسه الآن أنا بدي أروح أدرس سوق أو حالة سوق فلسطين
+
+229
+00:18:05,270 --> 00:18:11,430
+للأوراق المالية يعني بين قوسين بورصة فلسطين تحت أي
+
+230
+00:18:11,430 --> 00:18:17,040
+نوع من أنواع ال data تبيجعtime series في حد بيقول
+
+231
+00:18:17,040 --> 00:18:22,320
+غير الكلام هذا special .. special .. special ..
+
+232
+00:18:22,320 --> 00:18:26,140
+special .. special .. special .. special ..
+
+233
+00:18:26,140 --> 00:18:26,140
+special .. special .. special .. special ..
+
+234
+00:18:26,140 --> 00:18:26,140
+special .. special .. special .. special ..
+
+235
+00:18:26,140 --> 00:18:26,140
+special .. special .. special .. special ..
+
+236
+00:18:26,140 --> 00:18:26,140
+special .. special .. special .. special ..
+
+237
+00:18:26,140 --> 00:18:27,200
+special .. special .. special .. special ..
+
+238
+00:18:27,200 --> 00:18:28,440
+special .. special .. special .. special ..
+
+239
+00:18:28,440 --> 00:18:29,840
+special .. special .. special .. special ..
+
+240
+00:18:29,840 --> 00:18:29,840
+special .. special .. special .. special ..
+
+241
+00:18:29,840 --> 00:18:29,860
+special .. special .. special .. special ..
+
+242
+00:18:29,860 --> 00:18:29,880
+special .. special .. special .. special ..
+
+243
+00:18:29,880 --> 00:18:30,120
+special .. special .. special .. special ..
+
+244
+00:18:30,120 --> 00:18:30,120
+special .. special .. special .. special ..
+
+245
+00:18:30,120 --> 00:18:30,180
+special .. special .. special .. special ..
+
+246
+00:18:30,180 --> 00:18:31,320
+special .. special .. special .. special ..
+
+247
+00:18:31,320 --> 00:18:31,620
+special .. special .. special .. special ..
+
+248
+00:18:31,620 --> 00:18:31,620
+special .. special .. special .. special ..
+
+249
+00:18:31,620 --> 00:18:31,620
+special .. special .. special .. special ..
+
+250
+00:18:31,620 --> 00:18:31,620
+special .. special .. special .. special ..
+
+251
+00:18:31,620 --> 00:18:31,880
+special .. special .. special .. special ..
+
+252
+00:18:31,880 --> 00:18:31,880
+special .. special .. special .. special ..
+
+253
+00:18:31,880 --> 00:18:31,880
+special .. special .. special .. special ..
+
+254
+00:18:31,880 --> 00:18:31,880
+special .. special .. special .. special ..
+
+255
+00:18:31,880 --> 00:18:31,880
+special .. special .. special .. special ..
+
+256
+00:18:31,880 --> 00:18:34,940
+special .. special .. special ..
+
+257
+00:18:34,940 --> 00:18:41,320
+special
+
+258
+00:18:41,320 --> 00:18:43,570
+.. special .. special ..لكن الـ location الـ
+
+259
+00:18:43,570 --> 00:18:47,850
+location هو بيكون في صميم العملية و دائما بأثر
+
+260
+00:18:47,850 --> 00:18:52,650
+تمام؟ مثل الناس اللي بتشتغل في التنقيب عن النفط و
+
+261
+00:18:52,650 --> 00:18:57,910
+الدهب الآن الـ special data جزء من شغلها جزء من ال
+
+262
+00:18:57,910 --> 00:19:03,410
+data تبعتهم يعني أنا بدي أروح أجيب الله البيانات
+
+263
+00:19:03,410 --> 00:19:07,750
+عن أنواع التربة أنواع التربة و اتنبأ على طول
+
+264
+00:19:07,750 --> 00:19:12,950
+فلسطينتمام؟ أي منطقة ممكن ألاقي فيها .. أفحر فيها
+
+265
+00:19:12,950 --> 00:19:18,810
+منجم دهب مثلا هاي special .. هاي special تمام؟ لكن
+
+266
+00:19:18,810 --> 00:19:21,550
+سوق أوراق الفلسطين .. الأوراق الفلسطين .. أو سوق
+
+267
+00:19:21,550 --> 00:19:25,510
+الفلسطين الأوراق المالية أنا بتكلم على time series
+
+268
+00:19:25,510 --> 00:19:32,810
+data هل ممكن تكون هذه temporal data؟ هل
+
+269
+00:19:32,810 --> 00:19:38,920
+في الها state؟ يعني بين جوسين؟ماشي بحكي ما هو أنا
+
+270
+00:19:38,920 --> 00:19:42,200
+كنت مبارح مرتفع اليوم ممكن أنخفض ممكن في الساعة
+
+271
+00:19:42,200 --> 00:19:45,500
+هادية بقى أنخفض شوية بعد نص ساعة أرتفع هل فعليا
+
+272
+00:19:45,500 --> 00:19:48,560
+أنا بدور على state يعني بين بوسينة هل في عندي
+
+273
+00:19:48,560 --> 00:19:51,880
+السوق كله اللي بيرتفع و بينخفض مرة واحدة ولا شغلات
+
+274
+00:19:51,880 --> 00:19:55,500
+بسيطة إذا كان السوق كله مجموعة القيم كلها مع بعضها
+
+275
+00:19:55,500 --> 00:20:00,750
+ممكن أتكلم عليها temporarily لكن إذا كنت بتكلمإنه
+
+276
+00:20:00,750 --> 00:20:03,230
+لأ، السوق هو عبارة عن مجموعة من الأسهم إيش من
+
+277
+00:20:03,230 --> 00:20:05,610
+الأسهم بتطلع و إيش بنزل و إيش ثابت معناته أنا
+
+278
+00:20:05,610 --> 00:20:09,070
+بتتكلم على time series و مافيه dependency ما بين
+
+279
+00:20:09,070 --> 00:20:16,170
+الأسهم اللي موجودة بشكل عام تمام يا شباب على
+
+280
+00:20:16,170 --> 00:20:19,270
+الأسهم، على تداول الأسهم اللي موجودة أسهم
+
+281
+00:20:19,270 --> 00:20:23,970
+الإتصالات، أسهم الجوال، أسهم شركات التأمين ..
+
+282
+00:20:28,570 --> 00:20:32,950
+أكيد أكيد أكيد أحنا مش مختلفين معاك لكن هل الآن
+
+283
+00:20:32,950 --> 00:20:37,110
+هذا لما أنا بدي أروح أجيب ال data تبعتي و بدي
+
+284
+00:20:37,110 --> 00:20:39,910
+أشتغل عندهم هيكون الوضع السياسي اليوم كان في عنده
+
+285
+00:20:39,910 --> 00:20:43,170
+قصف في المنطقة الفلانية هذا لا يذكر في ال data
+
+286
+00:20:43,170 --> 00:20:46,150
+اللي موجودة وبناء على هيك احنا بنفترض دائما أن
+
+287
+00:20:46,150 --> 00:20:49,130
+أحنا شغالين في ال ideal case أن الحياة ماشية تمام
+
+288
+00:20:49,130 --> 00:20:52,670
+مش فيها مشاكل وبدنا نعمل دراسة للموضوحة لأن
+
+289
+00:20:52,670 --> 00:20:56,370
+بالمناسبة لحظة الحروب كل الدراسات هذه مالهاش معنى
+
+290
+00:20:56,370 --> 00:21:01,320
+بتصير لأنه بتصير الأولويةللحياة الأولوية من أجل
+
+291
+00:21:01,320 --> 00:21:05,980
+الحياة تمام ندخل في موضوع محاضرتنا اليوم نص ساعة
+
+292
+00:21:05,980 --> 00:21:08,460
+هنا عملنا refresh كويسة تلت ساعة فعليا بعد ما انتم
+
+293
+00:21:08,460 --> 00:21:12,460
+اتأخرتم خليني أروح باتجاه نتعرف على ال data mining
+
+294
+00:21:12,460 --> 00:21:15,860
+task اللي بدأ نشتغل عليها لما أنا بتكلم على ال
+
+295
+00:21:15,860 --> 00:21:20,940
+data mining task معناته أنا قاعد بدور على النمط
+
+296
+00:21:20,940 --> 00:21:25,850
+اللي انا بديأو الـ knowledge اللي أنا بدي أشوفها
+
+297
+00:21:25,850 --> 00:21:30,350
+اللي بدي أستخرجها الآن الناس اللي بتنقب على الدهب
+
+298
+00:21:30,350 --> 00:21:34,530
+عاملة حسابها بتدور على كل شغلة صفرة بتلمع وهذه
+
+299
+00:21:34,530 --> 00:21:39,230
+عينها دائما اللي بتغسل في التربة و بتصف فيها عينها
+
+300
+00:21:39,230 --> 00:21:42,450
+على هي شغلة بينما الناس اللي بتنقب على الحجار
+
+301
+00:21:42,450 --> 00:21:47,250
+الكريمة بتدور على الألوان الجذابة أثناء البحث مولا
+
+302
+00:21:47,250 --> 00:21:50,670
+لأ؟ يعني ممكن عفوا أن الدهب يكون أشبه بالرمل
+
+303
+00:21:50,670 --> 00:21:54,390
+بالترابلكن الحجار الكريم لأ، هي فعليًا نوع من
+
+304
+00:21:54,390 --> 00:21:57,810
+أنواع الحصة هيكون وموجود عندنا اللي بده ينقب على
+
+305
+00:21:57,810 --> 00:22:02,110
+البترول، كل الكلام هذا مابيعنهوش لحد ما فعليًا يصل
+
+306
+00:22:02,110 --> 00:22:06,010
+للبترول الخام ويبدأ يظهر في التربة بشكل جليب ويقول
+
+307
+00:22:06,010 --> 00:22:10,370
+أنا أصلت فإحنا فعليًا ال data mining task هي عبارة
+
+308
+00:22:10,370 --> 00:22:15,510
+عن أنواع ال patterns اللي أنا بدي أدور عليها،
+
+309
+00:22:15,510 --> 00:22:18,250
+أنواع ال knowledge، المعرفة اللي أنا بدي أدور
+
+310
+00:22:18,250 --> 00:22:22,630
+عليهاوبالتالي أنا قاعد أتكلم على مجموعة الـ
+
+311
+00:22:22,630 --> 00:22:30,430
+functions اللي تمثل ال task هاي عادة أو بشكل أساسي
+
+312
+00:22:30,430 --> 00:22:35,090
+ال data mining task تاخد واحد من ال two trends إما
+
+313
+00:22:35,090 --> 00:22:43,130
+descriptive وصفية أو predictiveتنبؤية بالوصفية
+
+314
+00:22:43,130 --> 00:22:49,070
+الهدف منها بتكون ان انا اقدر اوصف ال data او اقدم
+
+315
+00:22:49,070 --> 00:22:54,350
+وصف جديد لل data تمام؟ و هلاقد هشوف معاكم مثال
+
+316
+00:22:54,350 --> 00:22:59,330
+برضه بشارككم كويس معايا و بخلينا نفرج بين اتنين
+
+317
+00:22:59,330 --> 00:23:05,820
+بشكل واضح بينما ال predictive taskهي بدي أنفذ تقصي
+
+318
+00:23:05,820 --> 00:23:11,600
+أو تحقيق أو دراسة أو تحليل لل data عشان أقدر أتنبأ
+
+319
+00:23:11,600 --> 00:23:17,140
+مستقبلا ل instance معينة يعني أنا بروح بأدرس وضع
+
+320
+00:23:17,140 --> 00:23:23,360
+السوق الحالي عشان أتنبأ إن قيمة السوق هترتفع ولا
+
+321
+00:23:23,360 --> 00:23:28,320
+تنخفضطب، متى أنا بدي أتنبأ؟ في اليوم؟ لأ، الأصل
+
+322
+00:23:28,320 --> 00:23:31,200
+لكمان ساعة مثلا لإن السوق مثلا بتغير كل ساعة مثلا
+
+323
+00:23:31,200 --> 00:23:34,620
+كمان ساعة، بتعرفش هو وضع السوق بكرا، بتعرفش هو وضع
+
+324
+00:23:34,620 --> 00:23:38,900
+السوق بعد أسبوع، بعد شهر، بعد سنة هذه مفهوم التنبؤ
+
+325
+00:23:38,900 --> 00:23:43,840
+لكن كله بناء على إيش؟ على ال current data البيانات
+
+326
+00:23:43,840 --> 00:23:50,200
+الحالية اللي موجودة عندى طيب، الآن هاروح معاكوا
+
+327
+00:23:50,200 --> 00:23:56,800
+على الصورة هايمش واضحة كتير هساعدك في الصورة لأن
+
+328
+00:23:56,800 --> 00:24:00,220
+الإضاءة شوية وحتى و الصورة تبعت كمان بلور باهتة مش
+
+329
+00:24:00,220 --> 00:24:05,400
+كتير الصف الأول طبعا هدولة ميت صورة الصف الأول
+
+330
+00:24:05,400 --> 00:24:11,780
+مجموعة من الطائرات الصف التاني مجموعة من السيارات
+
+331
+00:24:11,780 --> 00:24:16,740
+التالت مجموعة من الطيور كلها طيور منزلية بالمناسبة
+
+332
+00:24:16,740 --> 00:24:21,000
+الرابع مجموعة من القطط الغزلان
+
+333
+00:24:23,650 --> 00:24:30,330
+الـ Dogs، الكلاب Frogs، ضفاضع Horses، حصن Boots،
+
+334
+00:24:30,330 --> 00:24:36,410
+نوارب Trucks أو شاحنات هدولة عشر أو هدولة ميت صورة
+
+335
+00:24:36,410 --> 00:24:41,510
+هدولة ميت صورة الآن افترض إن هدولة هما ال data set
+
+336
+00:24:41,510 --> 00:24:45,730
+اللي موجودين عندك هذه ال data set ممكن تكون هيك
+
+337
+00:24:45,730 --> 00:24:50,430
+ميت صورة الآن خلينا نروح باتجاه ال descriptive
+
+338
+00:24:50,430 --> 00:24:55,900
+mining tasksبدي أديك مثال على واحد منها، لو أنا
+
+339
+00:24:55,900 --> 00:25:02,800
+إجيت سألتك، قولتلك، هين ذكرتلك الصور، إيش هما،
+
+340
+00:25:02,800 --> 00:25:07,320
+بناءً على معرفتك السابقة اللي انت اتراكمت على مدار
+
+341
+00:25:07,320 --> 00:25:13,160
+تسعة عشر أو عشرين سنة بال object هدول، جسملياهم
+
+342
+00:25:13,160 --> 00:25:16,180
+لمجمعتين،
+
+343
+00:25:16,180 --> 00:25:21,380
+لاحظ؟، بدك تجسملياهم لمجمعتين و بدك تديلي وصف مقنع
+
+344
+00:25:22,880 --> 00:25:26,940
+للإيه؟ للعناصر أو للمجموعتين لهدول؟ آه محمد شوي ده
+
+345
+00:25:26,940 --> 00:25:30,120
+.. جمادات وكائنات حية .. جمادات وكائنات حية .. مين
+
+346
+00:25:30,120 --> 00:25:32,660
+بيشارك محمد في التقسيمة هاي؟ أو بوافق على
+
+347
+00:25:32,660 --> 00:25:38,320
+التقسيمة؟ كلها .. منطقية؟ جدا .. جدا .. الآن مين
+
+348
+00:25:38,320 --> 00:25:43,520
+الجمادات؟ السيارات .. طيارات .. السيارات ..
+
+349
+00:25:43,520 --> 00:25:50,590
+والقوارب ..والشاحنات فعلياً هدول واحد، اتنين،
+
+350
+00:25:50,590 --> 00:25:56,130
+تلاتة، أربعة بمثل 40% من ال data set مصبوط والستين
+
+351
+00:25:56,130 --> 00:25:59,490
+في المية اللي ضالوا في الكائنات الحية تصنيف تمام
+
+352
+00:25:59,490 --> 00:26:03,590
+وجميل مائة في المائة ومافي عليه أي غبار معقد
+
+353
+00:26:03,590 --> 00:26:08,630
+المسألة .. آه يا محمد وسائل نقل حيوانات سماها
+
+354
+00:26:08,630 --> 00:26:12,790
+تسمية مختلفة صحيحة مئة في المية مافيش مشكلة فيها
+
+355
+00:26:12,790 --> 00:26:19,540
+غيره يا شباب حد في عنده أي تسمية تانيةطيب، الآن يا
+
+356
+00:26:19,540 --> 00:26:24,380
+سيد العزيز هدولة المجموعات بديش يهم مجموعتين،
+
+357
+00:26:24,380 --> 00:26:28,160
+بديهم أربعة،
+
+358
+00:26:28,160 --> 00:26:32,920
+بدي تلاحظ .. خد وجهتك و أنت بتفكر في الموضوع و
+
+359
+00:26:32,920 --> 00:26:36,440
+تشوّر أنت و جارك، مافيش مشكلة عندك، بدي تلاحظ أنه
+
+360
+00:26:36,440 --> 00:26:44,040
+الآن بدك .. دماغك هيعصر أكثرلأ انت الأن مش ع كيفك
+
+361
+00:26:44,040 --> 00:26:48,480
+زي ما أنا ألزمتك بالتنتين، الآن جسمليهم لأربع
+
+362
+00:26:48,480 --> 00:26:52,260
+مجموعات، بديش تلاتة، بدي أربع مجموعات
+
+363
+00:26:55,310 --> 00:27:03,210
+اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+364
+00:27:03,210 --> 00:27:04,850
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+365
+00:27:04,850 --> 00:27:05,010
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+366
+00:27:05,010 --> 00:27:05,050
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+367
+00:27:05,050 --> 00:27:07,670
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+368
+00:27:07,670 --> 00:27:08,050
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+369
+00:27:08,050 --> 00:27:08,410
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+370
+00:27:08,410 --> 00:27:08,410
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+371
+00:27:08,410 --> 00:27:08,410
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+372
+00:27:08,410 --> 00:27:08,410
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+373
+00:27:08,410 --> 00:27:11,050
+..اصبر ..اصبر ..اصبر ..اصبر ..اصبر
+
+374
+00:27:24,450 --> 00:27:28,910
+وسائل لقى الجوية وسائل لقى البرية وسائل لقى البرية
+
+375
+00:27:28,910 --> 00:27:36,630
+طيور وحيوانات طيور وحيوانات طب
+
+376
+00:27:36,630 --> 00:27:42,370
+ما قلتلك قوارب انا معناته الان لاحظ ان انت ضيعت 10
+
+377
+00:27:42,370 --> 00:27:46,750
+% من الداتة انت مااستفدتش منها معناه ذكرتلك إياها
+
+378
+00:27:46,750 --> 00:27:50,610
+قوارب قلنا عدناهم هدولة عشر فئات مختلفات بدنا
+
+379
+00:27:50,610 --> 00:27:51,750
+نجسمهم على أربع أه هاشم
+
+380
+00:27:55,230 --> 00:28:05,710
+وسائل المواصلات برمائيات وقيور وثدييات الدفاضع ..
+
+381
+00:28:05,710 --> 00:28:12,790
+برمائي مش مشكلة .. انا راح اكتب على اللوح شباب طيب
+
+382
+00:28:12,790 --> 00:28:16,010
+مش مشكلة طائرات
+
+383
+00:28:58,530 --> 00:29:03,210
+يلّا يا هاشم أربعة أربعة تصنيفات بدنا منك صنفهم
+
+384
+00:29:03,210 --> 00:29:07,850
+عيدهم تاني بعد ما كتبنا برمئيات هاشم بصنفني لياهم
+
+385
+00:29:07,850 --> 00:29:16,650
+الآن برمئيات طيور .. طيور ..
+
+386
+00:29:16,650 --> 00:29:21,510
+أربعة
+
+387
+00:29:21,510 --> 00:29:25,770
+غيره وسائل نقل جوية .. وسائل نقل جوية
+
+388
+00:29:29,950 --> 00:29:39,330
+وحيوانات okay نيرو خلاص
+
+389
+00:29:39,330 --> 00:29:46,450
+الوصف بيكون مبرر في
+
+390
+00:29:46,450 --> 00:29:56,130
+الأخر هذا اسم المجموعة يعني صنف شوف جامعة الخير
+
+391
+00:29:56,130 --> 00:30:00,040
+كمان مرةيعني إيش .. إيش ال .. إيش ال data mining؟
+
+392
+00:30:00,040 --> 00:30:03,120
+إنه كل واحد بدي يشوف ال .. ال analyst بدي يطلع ب
+
+393
+00:30:03,120 --> 00:30:11,360
+pattern ماشوفهوش سابقا، تفضل مجموعة جوية و بتضم ..
+
+394
+00:30:11,360 --> 00:30:20,240
+بتضم مين؟ أه الطائرات والطيور، بس ال judge بطيرش،
+
+395
+00:30:20,240 --> 00:30:20,900
+بنطيره
+
+396
+00:30:31,000 --> 00:30:38,600
+مش هتقدر تصنفه في المجموعة الجوية ايوة وانبك تصنفه
+
+397
+00:30:38,600 --> 00:30:47,640
+في البرية اه التصنيف اللي انا فعليا اجتهدت شفته
+
+398
+00:30:47,640 --> 00:30:49,460
+كتالي قلت انا انا انا انا انا انا انا انا انا انا
+
+399
+00:30:49,460 --> 00:30:49,460
+انا انا انا انا انا انا انا انا انا انا انا انا
+
+400
+00:30:49,460 --> 00:30:49,460
+انا انا انا انا انا انا انا انا انا انا انا انا
+
+401
+00:30:49,460 --> 00:30:49,460
+انا انا انا انا انا انا انا انا انا انا انا انا
+
+402
+00:30:49,460 --> 00:30:49,460
+انا انا انا انا انا انا انا انا انا انا انا انا
+
+403
+00:30:49,460 --> 00:30:49,460
+انا انا انا انا انا انا انا انا انا انا انا انا
+
+404
+00:30:49,460 --> 00:30:52,230
+انا انا انا انا انا انا انا اناالـ Living objects
+
+405
+00:30:52,230 --> 00:30:56,010
+هدول و Non-living objects التاني مش مختلفين عليهم
+
+406
+00:30:56,010 --> 00:31:00,410
+بالـ Non-living objects في منهم بيسير على عجلات و
+
+407
+00:31:00,410 --> 00:31:05,870
+في منهم بدون طائرات و قوارب بدون عجلات سيارات و
+
+408
+00:31:05,870 --> 00:31:14,150
+شاحنات بالعجلات تمشي على العجلات الطائرة هاش
+
+409
+00:31:14,150 --> 00:31:20,520
+الحالة في طيارة مسيرة فيهم هان برضه برضه عجلاتفيه
+
+410
+00:31:20,520 --> 00:31:25,960
+في الآخر العجل مش هو الأساس الحركة تبعتها اللي أنا
+
+411
+00:31:25,960 --> 00:31:30,100
+بدي أقوله فالآن على عجلات و بدون عجلات هذا ال non
+
+412
+00:31:30,100 --> 00:31:36,920
+-living object طب و ال living object؟ مثلا؟
+
+413
+00:31:36,920 --> 00:31:43,460
+ليش؟ ال judge أليف و غير أليف؟ أليف و غير أليف؟
+
+414
+00:31:43,460 --> 00:31:52,360
+الآن لمن قال لك الغزلان أليفة؟ حرام عليكولا تضفضع
+
+415
+00:31:52,360 --> 00:31:56,560
+ولا تضفضع أليفة كمان الشباب مقصود بال ألف
+
+416
+00:31:56,560 --> 00:32:01,620
+الاستئناس هل لما تجرب من الغزالة بتقولك اتفضل تشرد
+
+417
+00:32:01,620 --> 00:32:06,840
+دليل إلا غير لو ربيتلك أسد يعني زي ما بتربيها زي
+
+418
+00:32:06,840 --> 00:32:11,090
+ما تربي الأسد عندك بتصير أليفةبس يعني خارج المنغ
+
+419
+00:32:11,090 --> 00:32:14,350
+انت الآن ماحناش تقولنا understandable أو
+
+420
+00:32:14,350 --> 00:32:18,210
+actionable ولا لأ بيترتب عليها معناه هذه التصنيفات
+
+421
+00:32:18,210 --> 00:32:23,910
+لاحظ إنه أنا عمالي بحاول أخد منك وصف جدمتلك طلب
+
+422
+00:32:23,910 --> 00:32:27,790
+بدي منك أربع مجموعات وزودني بالوصف لكل مجموعة
+
+423
+00:32:27,790 --> 00:32:31,630
+descriptive من وين جبت الوصف؟ من ال data set اللي
+
+424
+00:32:31,630 --> 00:32:36,650
+موجودة من ال data set اللي موجودةطيب .. قولنا
+
+425
+00:32:36,650 --> 00:32:42,070
+descriptive و predictive descriptive زي ما شوفنا
+
+426
+00:32:42,070 --> 00:32:46,010
+في ال .. في ال predictive قولتلك أنا عندي object
+
+427
+00:32:46,010 --> 00:32:54,090
+بيمشي على رجلتين دسمه مغطى .. بتنفس وبياكل مغطى
+
+428
+00:32:54,090 --> 00:32:58,010
+بالريش تمام؟
+
+429
+00:32:58,010 --> 00:33:05,720
+وين بقت صنفه؟ غزال في الحيوانات الغير قليفةالآن
+
+430
+00:33:05,720 --> 00:33:08,960
+سابقًا قبل ما أقولك هذا أنا باشر بقولك أنا في عندى
+
+431
+00:33:08,960 --> 00:33:13,200
+جامعة الخير تلت تصنيفات أو أربع تصنيفات أربع أقسام
+
+432
+00:33:13,200 --> 00:33:18,560
+معروفات كائنات حية أو كائنات غير حية كائنات الحية
+
+433
+00:33:18,560 --> 00:33:24,220
+فيها قسمين إشي الآن فيها طيور و حيوانات و فيها ..
+
+434
+00:33:24,220 --> 00:33:29,060
+و الغير حية فيها مثلًا عجلات و بدون عجلاتصنفلي
+
+435
+00:33:29,060 --> 00:33:32,900
+الآن الكائن اللي أنا ذكرتلكي إياه بيأكل وبيتنفس
+
+436
+00:33:32,900 --> 00:33:39,300
+وبيمشي على قدمين وإله ريش مباشرة هتروح تقولي هذا
+
+437
+00:33:39,300 --> 00:33:43,300
+فئة الطيور بناءًا عليش أنت حكمت بناءًا على ال
+
+438
+00:33:43,300 --> 00:33:47,260
+knowledge اللي أنا فعليًا أخدتها و بعرفها عن كل
+
+439
+00:33:47,260 --> 00:33:51,080
+صنف من الصخفات أو الأصناف التالية وهذا هو ال
+
+440
+00:33:51,080 --> 00:33:55,380
+predictive بارك
+
+441
+00:33:55,380 --> 00:34:01,790
+يا مؤمنماشي الحق، بلاش، طيب، الآن من
+
+442
+00:34:01,790 --> 00:34:05,570
+الـdescriptive task اللي عندي ال clustering اللي
+
+443
+00:34:05,570 --> 00:34:08,050
+احنا اشتغلناها مع بعض لما قلتلك جسم ال data set
+
+444
+00:34:08,050 --> 00:34:14,770
+لمجمعتين لأربع مجموعات ال outlier detection لو أنا
+
+445
+00:34:14,770 --> 00:34:19,150
+اجيت قلتلك في الطيور إيش كان ال outlier عند محمد
+
+446
+00:34:19,150 --> 00:34:24,370
+غنيم؟الجاج كل العناصر أو كل الصور اللي موجودة تمان
+
+447
+00:34:24,370 --> 00:34:34,310
+صور فيها عصافير أو كأو طيور تطير تمام flying معدد
+
+448
+00:34:34,310 --> 00:34:40,560
+دجاج هم صورتين فكانوا هدول بالنسبة لمحمدمثابة ال
+
+449
+00:34:40,560 --> 00:34:43,600
+outlier هم اللي بت .. يعني لو .. لو طريق .. لو
+
+450
+00:34:43,600 --> 00:34:46,700
+الاص .. لو هدولة الصورتين مش موجودات كان قولنا
+
+451
+00:34:46,700 --> 00:34:49,900
+لامحمد والله تصنيفك تمام بس ايه قولنا هدولة
+
+452
+00:34:49,900 --> 00:34:54,660
+outlier الان تخيل ان هدولة فعليا كانوا مش اتنين ل
+
+453
+00:34:54,660 --> 00:35:00,890
+تمانية اتنين ل تمانية وتسعينفعليًا بقول هدولة
+
+454
+00:35:00,890 --> 00:35:05,210
+outlier شواذة يعني كل اللي عندي فعليًا real birds
+
+455
+00:35:05,210 --> 00:35:08,170
+بصير أسميهم birds ممكن أقول لأ قيور خلاص لأنه
+
+456
+00:35:08,170 --> 00:35:15,590
+فعليًا بستخدم الجناحين كوسيلة حركة الآن عادة ال
+
+457
+00:35:15,590 --> 00:35:20,610
+outlier كم ذلك في الصحة الآن الصحة هي الأساس المرض
+
+458
+00:35:20,610 --> 00:35:25,150
+هو ال outlier اللي موجود عندي أنا عادة بروح بقى
+
+459
+00:35:25,150 --> 00:35:30,490
+أشتري من الدكان اللي في جنبيمعدلي في الشهر مثلا
+
+460
+00:35:30,490 --> 00:35:35,070
+باخد منه 400 شكل وهذا الكلام معروف يعني 400 plus
+
+461
+00:35:35,070 --> 00:35:38,110
+or minus عشرة عشرين مش قضية plus or minus عشرين
+
+462
+00:35:38,110 --> 00:35:44,150
+رحت في الأشهر من الأشهر لجته 700 outlier في ال
+
+463
+00:35:44,150 --> 00:35:48,510
+history اللي موجود عندك هان، تمام؟ وبالتالي ال
+
+464
+00:35:48,510 --> 00:35:51,430
+affinity analysis أو اللي احنا بنسميه ال
+
+465
+00:35:51,430 --> 00:35:55,470
+association rules معامل ارتباط الأشياء مع بعضها
+
+466
+00:35:56,570 --> 00:36:00,570
+جديش مثلا التدخين مرتبط بسرطان الرئة جديش فقر الدم
+
+467
+00:36:00,570 --> 00:36:03,790
+مرتبط بسرطان الرئة أو الشغلات اللي زي هي كانت جديش
+
+468
+00:36:03,790 --> 00:36:07,850
+الحالة الاجتماعية بتأثر على الطالب تمام على تحصيله
+
+469
+00:36:07,850 --> 00:36:12,850
+العلمي إلى آخرين في ال predictive في عند
+
+470
+00:36:12,850 --> 00:36:16,090
+classification وفي ال classification بدي أعمل
+
+471
+00:36:16,090 --> 00:36:20,550
+predict لمين ل category لفئة الفئة هذه بتكون محددة
+
+472
+00:36:20,550 --> 00:36:26,890
+ومسبقا في ال regression بدي أعمل prediction لvalue
+
+473
+00:36:26,890 --> 00:36:30,630
+certain value قيمة بذاتها وفي ال recommendation
+
+474
+00:36:30,630 --> 00:36:35,030
+بدي أحاول أعمل predict لل preference للشغلات اللي
+
+475
+00:36:35,030 --> 00:36:39,330
+ممكن تكون مفيدة للشخص هذا نبدأ بنوع من التفصيل
+
+476
+00:36:39,330 --> 00:36:42,870
+للعناصر اللي موجودة هنا في ال classification زي ما
+
+477
+00:36:42,870 --> 00:36:45,970
+قلنا هي عبارة عن predictive data mining task
+
+478
+00:36:45,970 --> 00:36:52,310
+classification predictive data mining task بدي
+
+479
+00:36:52,310 --> 00:36:58,880
+أتنبأ في ال data set عادةبتكون تحتوي على شغلتين يا
+
+480
+00:36:58,880 --> 00:37:03,060
+جماعة الخير أو نوعين من ال variables نوعين من ال
+
+481
+00:37:03,060 --> 00:37:09,620
+attributes النوع الأول اللي هو مجموعة ال
+
+482
+00:37:09,620 --> 00:37:15,420
+explanatory variables أو المجموعة الاستكشافية
+
+483
+00:37:15,420 --> 00:37:19,340
+المجموعة المميزة سميها زي ما بدك الفكرة فيها هذه
+
+484
+00:37:19,340 --> 00:37:24,560
+عبارة عن مجموعة ال attributes اللي بتحمل خصائصالـ
+
+485
+00:37:24,560 --> 00:37:31,900
+object خصائص ال raw اللي أنا بتكلم عليه والتاني هي
+
+486
+00:37:31,900 --> 00:37:38,480
+عبارة عن ال target variable يعني بقاجي أقول أنه
+
+487
+00:37:38,480 --> 00:37:48,020
+أنا عندي data set فيها كتالي هاي ال target
+
+488
+00:37:51,340 --> 00:37:56,120
+وهان مجموعة ال fields اللي موجودة مجموعة ال fields
+
+489
+00:37:56,120 --> 00:38:01,840
+كالتالي
+
+490
+00:38:01,840 --> 00:38:06,320
+brief
+
+491
+00:38:06,320 --> 00:38:13,500
+نفس eat fly
+
+492
+00:38:13,500 --> 00:38:16,900
+whales
+
+493
+00:38:25,410 --> 00:38:33,490
+feather مثلا هي هدول الآن التنفس يأكل يطير عجلات
+
+494
+00:38:33,490 --> 00:38:43,970
+ريش و ال target ال role أول breathe
+
+495
+00:38:43,970 --> 00:38:48,650
+no eat no yes بحط X
+
+496
+00:38:51,580 --> 00:39:01,160
+wheel yes no وانا في عندي plane في المقابل في عندي
+
+497
+00:39:01,160 --> 00:39:10,740
+أنا breathe eat fly no weather ريش هيبرد
+
+498
+00:39:10,740 --> 00:39:15,220
+الآن لاحظ أنا جاهز بجهز ال data set طبعا هذا بيكون
+
+499
+00:39:15,220 --> 00:39:18,420
+وصف للعناصر اللي موجودة عندها
+
+500
+00:39:28,840 --> 00:39:31,660
+الآن يا جماعة الخير المفروض أنه كل row من ال rows
+
+501
+00:39:31,660 --> 00:39:36,760
+هي تتبيه تست لما هنتكلم عليها لأ ممنوع يتكرر تكرار
+
+502
+00:39:36,760 --> 00:39:40,180
+ال rows لا يضيف شيء في المعرفة عشان هي class كل
+
+503
+00:39:40,180 --> 00:39:43,360
+row يكون مختلف عن التاني عشان يقدر ال system و هو
+
+504
+00:39:43,360 --> 00:39:47,740
+بيتعلم يقدر يجمع أكثر قدر ممكن من ال different
+
+505
+00:39:47,740 --> 00:39:53,480
+properties لمين؟ لكل class بنجي بنقول هان breathe
+
+506
+00:39:53,480 --> 00:40:03,880
+بالخطأ yesno wheels feather وهنا
+
+507
+00:40:03,880 --> 00:40:14,580
+plain الآن شو رايك بال breath؟ شو يعني بدها؟ بدها
+
+508
+00:40:14,580 --> 00:40:19,560
+cleaning هانا بيجي جزء ل cleaning الآن أنا في عندى
+
+509
+00:40:19,560 --> 00:40:26,790
+باك تعدى error inconsistentو لا missing و لا noise
+
+510
+00:40:26,790 --> 00:40:31,230
+inconsistent يعني
+
+511
+00:40:31,230 --> 00:40:35,170
+في تعارض ما بين ال two attributes غالبا هذه noise
+
+512
+00:40:35,170 --> 00:40:43,310
+data خطأ في الإدخال طبعا مافيش .. مافيش .. لا في
+
+513
+00:40:48,950 --> 00:40:53,230
+تمام؟ الآن .. هذه الآن ده المقضوب من في ال
+
+514
+00:40:53,230 --> 00:41:00,570
+classification هذه كلها ال attribute هدول صححتها
+
+515
+00:41:00,570 --> 00:41:07,330
+و .. وصححتاش تمام؟
+
+516
+00:41:07,330 --> 00:41:11,570
+explanatory و variables اللي أنا فعليا بدي أستكشف
+
+517
+00:41:11,570 --> 00:41:16,130
+من خلالهمالـ properties الـ different properties
+
+518
+00:41:16,130 --> 00:41:20,790
+عشان أربطها أو أشوف إيش بتميز ال target بيان جوسين
+
+519
+00:41:20,790 --> 00:41:24,350
+بدي أستكشف زي ما انتوا بتفضلوا ال target من خلال
+
+520
+00:41:24,350 --> 00:41:28,990
+ال attribute هاي ببدأ بأدرس العلاصر املاحظين أنا
+
+521
+00:41:28,990 --> 00:41:36,790
+في عنده تلت شغلات أساسية مرتبطة بال bird الأكل
+
+522
+00:41:36,790 --> 00:41:44,730
+والشرب والريش وال featherمصبوط؟ عفوًا الأكل والنفس
+
+523
+00:41:44,730 --> 00:41:51,230
+والأكل والريش ال flying مرتبطة بالطائر؟ لأ لأن
+
+524
+00:41:51,230 --> 00:41:54,550
+العنصر التاني أو ال class التاني بيشاركي الطائر
+
+525
+00:41:54,550 --> 00:41:59,430
+طبعا ماهيش الشغلات المرتبطة بالطائرة ال
+
+526
+00:41:59,430 --> 00:42:04,800
+discriminative attribute اللي عندي ال wheelالـ
+
+527
+00:42:04,800 --> 00:42:09,200
+Wheels تمام؟ و الـ Fly يعني مع بعضهم إذا الـ Fly و
+
+528
+00:42:09,200 --> 00:42:12,460
+الـ Wheel فخلاص على المضمون فهيك أنا صار في عندي
+
+529
+00:42:12,460 --> 00:42:15,800
+knowledge بقدر أقول أنا general knowledge و هذه
+
+530
+00:42:15,800 --> 00:42:21,680
+valid و الأصل هي تكون novel أن أي object عنده
+
+531
+00:42:21,680 --> 00:42:30,700
+المقدرة أن يطير وله عجلات فهو دائرة تمام؟
+
+532
+00:42:32,580 --> 00:42:35,980
+محمد أبو حاسم يقول لك كل قاعدة شوية بناء على ال
+
+533
+00:42:35,980 --> 00:42:38,480
+data set اللي موجود عندنا هنا كمان مرة يا جماعة
+
+534
+00:42:38,480 --> 00:42:43,320
+الخير لما أنا بأتعامل بأتعامل ضمن ال data set اللي
+
+535
+00:42:43,320 --> 00:42:50,120
+موجودة لاحظ سابقا في الصور مسألة cash و الدبابات
+
+536
+00:42:50,120 --> 00:42:54,900
+وين صنفتها أو وين جسمتها ليش؟ لأنها مش موجودة
+
+537
+00:42:54,900 --> 00:43:00,300
+وبالتالي أنا بأشتغل ضمنحدود ال data 6 تبعتي و
+
+538
+00:43:00,300 --> 00:43:04,340
+بعدين لما اتكلمنا عن ال validity تبعت ال pattern
+
+539
+00:43:04,340 --> 00:43:09,500
+تبعي ماقلتش ضروري يكون one hundred percent ماقلتش
+
+540
+00:43:09,500 --> 00:43:13,080
+انه لازم يكون مية في المية دقيق لكن قلتلك with
+
+541
+00:43:13,080 --> 00:43:18,280
+some degree of certainty مع نسبة معينة من الدقة
+
+542
+00:43:18,280 --> 00:43:22,720
+النسبة هاي عشان يكون في مجال لقبول او رفض البيانات
+
+543
+00:43:22,720 --> 00:43:24,700
+ملك لأ نعم
+
+544
+00:43:29,430 --> 00:43:33,750
+هو الـ data set لازم تكون التنين موجودات عندك انت
+
+545
+00:43:33,750 --> 00:43:37,230
+الآن ال data mining task تعمل analysis للـ
+
+546
+00:43:37,230 --> 00:43:42,410
+explanatory تمام؟ عشان تعمل prediction لاحقا لل
+
+547
+00:43:42,410 --> 00:43:50,350
+target هذا
+
+548
+00:43:50,350 --> 00:43:53,810
+اللي عند الطائرة و تتنفس تمام، الان احنا عرفنا
+
+549
+00:43:53,810 --> 00:44:02,290
+لأنه عندنا كم؟ أربعة أو أربعة روز100% عادة الـ
+
+550
+00:44:02,290 --> 00:44:05,870
+missing data أو الـ noise data مش بسهولة الكشف
+
+551
+00:44:05,870 --> 00:44:09,270
+عنها وإلا كان ما جال cash إنه فعليا أنت بدك تجد
+
+552
+00:44:09,270 --> 00:44:12,210
+وجد وانت بتدرس البيانات اللي موجودة إيش أنت بتروح
+
+553
+00:44:12,210 --> 00:44:17,370
+بتساوي؟ بتروح بتقوله مثلا إيش ممكن أساوي ال
+
+554
+00:44:17,370 --> 00:44:20,630
+attribute هذه؟ دور أعمل ال maximum و ال minimum و
+
+555
+00:44:20,630 --> 00:44:23,250
+أعمل association ما بين ال attribute و ال
+
+556
+00:44:23,250 --> 00:44:26,030
+attribute التاني زي ال association مع ال attribute
+
+557
+00:44:26,030 --> 00:44:31,320
+و ال targetلحد ما تصل لارتباط لكن برضه بتظهر
+
+558
+00:44:31,320 --> 00:44:34,900
+الفرصة أن هذه تبقى مثل ما هي لأن من اللي ممكن هذي
+
+559
+00:44:34,900 --> 00:44:39,820
+يعملها bridge لو أنت ماشوفتهاش حجم البيانات الآن
+
+560
+00:44:39,820 --> 00:44:45,380
+هذه واحدة تمام خطأ واحد في مائة ألف record قدش
+
+561
+00:44:45,380 --> 00:44:51,630
+تأثيره يكاد يكون صفر يكاد يكون له تأثيرلكن يكاد
+
+562
+00:44:51,630 --> 00:44:55,910
+يكون صفر لكن لو هذا العنصر واحد من عشرة أو واحد من
+
+563
+00:44:55,910 --> 00:44:59,650
+أربعة زي هيك صار تأثير و 25% على ال decision تبعتي
+
+564
+00:44:59,650 --> 00:45:01,070
+في الموضوع أيه رأيك؟
+
+565
+00:45:06,320 --> 00:45:10,220
+تمام، بس أنا الآن .. الآن هذا تماما مثل المثال
+
+566
+00:45:10,220 --> 00:45:13,660
+السابق اللي عرضتلك مجموعة الصور قلتلك هي .. أنا بس
+
+567
+00:45:13,660 --> 00:45:16,940
+حاول تكتب ال data set قدامك المفروض أنا عرضت ال
+
+568
+00:45:16,940 --> 00:45:20,040
+data set سابقا جهزت ال data set سابقا زي ما
+
+569
+00:45:20,040 --> 00:45:23,340
+اشتغلنا بالمثال تبع المحاضرة الماضية الجدول اللي
+
+570
+00:45:23,340 --> 00:45:27,220
+فيه الصناديق الحمرة و ال .. ال .. و الكون اللي هي
+
+571
+00:45:27,220 --> 00:45:31,160
+القمع و ال .. و الكورة الزرق تمام؟ و ربطنا
+
+572
+00:45:31,160 --> 00:45:35,240
+بالأوزان قلتلك هي ال data set و شوف ال patternلأن
+
+573
+00:45:35,240 --> 00:45:39,080
+أنا بس كتبتك قدامك و أنت معايا واحدة بواحدة لو جيت
+
+574
+00:45:39,080 --> 00:45:42,000
+عرضتلك إياها بالشكل هذا و قولتلك يا رامي شوف لي ال
+
+575
+00:45:42,000 --> 00:45:45,840
+patterns اديني pattern للطائرة و اديني pattern
+
+576
+00:45:45,840 --> 00:45:51,820
+للطائر إيش هتروح تقولي؟ هتاخد مني وقت بسيط أو طويل
+
+577
+00:45:51,820 --> 00:45:57,840
+حسب حجم ال data set و تبدأ تدرس العناصر E to bird
+
+578
+00:45:57,840 --> 00:46:03,420
+to feather معناته bird otherwise
+
+579
+00:46:05,030 --> 00:46:08,830
+وعادة هدف ال binary classification يا شباب دائما
+
+580
+00:46:08,830 --> 00:46:14,750
+بصير بدور على ال more strongest rule
+
+581
+00:46:14,750 --> 00:46:24,810
+أو value باجي بقول مين أجوى عندي تنفس و أكل و ريش
+
+582
+00:46:24,810 --> 00:46:33,100
+مع البارد ولا عجلات و طيران مع الطائرةحسب ال data
+
+583
+00:46:33,100 --> 00:46:38,920
+set اللي عندنا هنا، مين أقوى؟ يعني هيك
+
+584
+00:46:38,920 --> 00:46:42,220
+أنا قلت يا عزيزي اتبعت انه برد توصف الليلة بعدها
+
+585
+00:46:42,220 --> 00:46:45,060
+.. لا لا لا، ما هو انا هيك جايك، انا جايك لاحقا
+
+586
+00:46:45,060 --> 00:46:48,200
+أجي أقولك التالي، انت ما خلنا .. ما خلنا نخصناش
+
+587
+00:46:48,200 --> 00:46:52,000
+احنا، الآن هي ال data set اللي عندك وجيت قلتلك أن
+
+588
+00:46:52,000 --> 00:46:56,840
+الآن أنا في عندي object، عندي object واضح أنه
+
+589
+00:46:56,840 --> 00:47:05,420
+بيتنفس، والمعلومات اللي عندييقول إنه بيأكلش وبيطير
+
+590
+00:47:05,420 --> 00:47:16,740
+ومالوش عجلات وإله ريش عصفور
+
+591
+00:47:16,740 --> 00:47:22,780
+عيّان، أه؟ لأ، مرت حردانة منه بس دو ده نفسه مضرب
+
+592
+00:47:22,780 --> 00:47:26,960
+عن الطعام الآن إيش التصنيف هذا لل object هذا يا
+
+593
+00:47:26,960 --> 00:47:33,450
+راني؟كيف أشيله؟ مش عكيفك هذا واحد من التنين اللي
+
+594
+00:47:33,450 --> 00:47:38,910
+عندك حسب ال role لازم ال algorithm تديني قرار bird
+
+595
+00:47:38,910 --> 00:47:47,430
+ولا plane؟ ليش bird؟ لأنه بتنفس ويله ريش فهو 90%
+
+596
+00:47:47,430 --> 00:47:53,190
+من ال role تبعت ال bird تنطبق عليه بتنفس و بطير
+
+597
+00:47:53,190 --> 00:47:58,330
+ويله ريشومالوش عجلات وبالتالي أنا قاعد أتكلم على
+
+598
+00:47:58,330 --> 00:48:07,050
+80% من خصائص الطائر موجودة عنده فهو طائر تمام؟
+
+599
+00:48:07,050 --> 00:48:10,890
+هذه ال prediction هذه البيانات بتلزم في مرحلة ال
+
+600
+00:48:10,890 --> 00:48:17,430
+learning مرحلة ال analysis عشان أبدأ أبني rules في
+
+601
+00:48:17,430 --> 00:48:21,430
+تحديد ال object هذه في مرحلة ال prediction باجي
+
+602
+00:48:21,430 --> 00:48:26,770
+بسأل بقول والله okayالـ .. في سوق أوراق فلسطين
+
+603
+00:48:26,770 --> 00:48:31,390
+المالية ساهم شركة الاتصالات على مدار عشر سنوات
+
+604
+00:48:31,390 --> 00:48:38,790
+بيطلع و بينزل تمام؟ بكرا كيف وضع السهم؟ بناء ..
+
+605
+00:48:38,790 --> 00:48:44,690
+هتكلم مفروض منه كيف وضع السهم بكرا؟ بده يرتفع ولا
+
+606
+00:48:44,690 --> 00:48:46,310
+بده ينزل .. بده ينخفض؟
+
+607
+00:48:49,530 --> 00:48:53,730
+حسب ال data تبعتنا الآن مثلا كان واضح في ال
+
+608
+00:48:53,730 --> 00:48:56,950
+pattern .. واضح في ال pattern أنه في الأيام .. في
+
+609
+00:48:56,950 --> 00:49:01,270
+الأيام اللي بيكون أو مثلا في فصل الشتاء و اللي
+
+610
+00:49:01,270 --> 00:49:08,050
+بيكون فيها مطر غزير تمام السهمي بينزل بكرة .. هذا
+
+611
+00:49:08,050 --> 00:49:10,210
+ال pattern هيك بيقوللي ال historical data هيك
+
+612
+00:49:10,210 --> 00:49:16,580
+بتقوللي بكرة .. بكرة واضح أنه في عندنا منخفضبرياح
+
+613
+00:49:16,580 --> 00:49:21,340
+شديدة تمام وكتير من المدارس أو عفوًا من الوزارات
+
+614
+00:49:21,340 --> 00:49:28,600
+أعلنت عن عدم انتظام الدوام في الغد ديني حالة تتسهم
+
+615
+00:49:28,600 --> 00:49:34,680
+بكرة ما بتقوليش لأ لأ لأ مش مش معروفة الزمن لأ أنا
+
+616
+00:49:34,680 --> 00:49:37,920
+متعلق بالزمن أما أنت حاجة أساسية موجودة التنتين
+
+617
+00:49:37,920 --> 00:49:41,800
+نفس الشغل يا رامي أنا ماقلتكاش الطائر بدون ريش
+
+618
+00:49:46,050 --> 00:49:49,530
+ها، الآن أنا ما قلتلكاش أنا طائر بدون ريش، تمام؟
+
+619
+00:49:49,530 --> 00:49:54,090
+لكن افترض إنه طائرة مسيرة أو طائرة صغيرة للتمويه
+
+620
+00:49:54,090 --> 00:50:00,850
+كسوها بالريش، تخيل، شو بقى كتقولليه؟ الآن إيجاك،
+
+621
+00:50:00,850 --> 00:50:05,290
+قالك في عندك object، لأ شباب أنت الآن، ماشي
+
+622
+00:50:05,290 --> 00:50:07,930
+الحالة، ممكن تضحك خدراحتك، لكن فعليا إيه هيك
+
+623
+00:50:07,930 --> 00:50:13,330
+السؤال المطروح عندك؟ وجوابك من هنا، يا بقى كتقوللي
+
+624
+00:50:13,330 --> 00:50:19,490
+بلين؟يا بقى تقوللي بيرت ومالكاش خيار تاني الآن
+
+625
+00:50:19,490 --> 00:50:23,330
+اصصبر شوية ..الآن قولتلك انه أنا في عندي object
+
+626
+00:50:23,330 --> 00:50:31,350
+object لا يأكل ولا يتنفس يطير وله عجلات ومغطى
+
+627
+00:50:31,350 --> 00:50:36,650
+بالريش جاوبني
+
+628
+00:50:36,650 --> 00:50:38,590
+ليش؟
+
+629
+00:50:40,420 --> 00:50:43,040
+مية لمية انتهى الأمر، إذا كنت تقول لي مافيش عنصر
+
+630
+00:50:43,040 --> 00:50:47,740
+أو مافيش وجود للعنصر هذا، بقولك أنت غلطان، ممكن
+
+631
+00:50:47,740 --> 00:50:50,280
+يصير زي لما قعدوا يدوروا ع ال bigfoot و لاجوا
+
+632
+00:50:50,280 --> 00:50:54,540
+عينات و شعر أسوذ و قجز و زي .. الآن أنا بدي أجيبلك
+
+633
+00:50:54,540 --> 00:51:00,780
+مثال على طائرات فعليا .. فعليا تغطى بالرشالطائرات
+
+634
+00:51:00,780 --> 00:51:04,240
+اللي بيحطوها ضمن أسراب الطيور و تصورهم انت بتحتاج
+
+635
+00:51:04,240 --> 00:51:06,460
+حساب على national geographic لما بيصوروهم
+
+636
+00:51:06,460 --> 00:51:11,480
+بيبعتولهم drone او بيبعتولهم طيارة عادية؟ لأ
+
+637
+00:51:11,480 --> 00:51:16,720
+الطيارة هذه بيكون او بيكون الكاميرا على طائر الآن
+
+638
+00:51:16,720 --> 00:51:21,760
+بيروح بيجيبله مجسم الطائر و بطيرله ضمن السرب عشان
+
+639
+00:51:21,760 --> 00:51:25,740
+ماينفرش منهالآن ضمن المواصفات هذا، أجل قلتلك، هي
+
+640
+00:51:25,740 --> 00:51:30,040
+في عندي واحد من العناصر هدول في كل السمات، سمات
+
+641
+00:51:30,040 --> 00:51:37,060
+الطير، لكنه لا يأكل ولا يتنفس، مباشرة، طيارة Spy
+
+642
+00:51:37,060 --> 00:51:41,840
+Bird، أنتوا أكيد مولعين بـ NBC2 Action يعني
+
+643
+00:51:44,640 --> 00:51:47,520
+أنا شفت في ال .. في ال document .. كل ال
+
+644
+00:51:47,520 --> 00:51:50,960
+documentary films اللي بيصور ل groups تبعت
+
+645
+00:51:50,960 --> 00:51:53,920
+الحيوانات و الطيور و الشغلات اللي زي هاي حل من
+
+646
+00:51:53,920 --> 00:51:59,300
+اتنين إما فعليا بركب الكاميرا على الطير وللأسف هذا
+
+647
+00:51:59,300 --> 00:52:03,780
+الكلام كان مرفوض تماما على الأقل مع الغربان لأنه
+
+648
+00:52:03,780 --> 00:52:06,400
+جتلوا الغراب أكثر من مرة اللي كانوا بيودوا يحطوا
+
+649
+00:52:06,400 --> 00:52:10,740
+عليه الكاميرا فكان البديل أن يحطوا شكل مجسم الغراب
+
+650
+00:52:11,290 --> 00:52:15,170
+تمام؟ والعيون هي بمثابة الكاميرا كذلك فشلت التجربة
+
+651
+00:52:15,170 --> 00:52:23,470
+مع البقاريق أن الطير اللي كان بيرحط على رأسه أو
+
+652
+00:52:23,470 --> 00:52:30,130
+على عنق الكاميرا تمام؟ كان بينتحر أو بينفر منه
+
+653
+00:52:30,130 --> 00:52:35,490
+القطيع تبعه أو المئسر المفروض
+
+654
+00:52:35,490 --> 00:52:39,090
+أعدمه في الساحة هم الخيانة وطنية عظمة
+
+655
+00:52:42,470 --> 00:52:46,070
+ماشي ماشي نشوف الردود الجميلة في الامتحانات ان شاء
+
+656
+00:52:46,070 --> 00:52:49,450
+الله نذكر
+
+657
+00:52:49,450 --> 00:52:52,530
+ناشي في ال classification أنا عمال بحاول معاك
+
+658
+00:52:52,530 --> 00:52:59,490
+أوصلك لل task إيش هي وكيف أنت بدك تبنيها الآن من
+
+659
+00:52:59,490 --> 00:53:02,710
+ال classification المعروف اللي بدي أوصلك إياه أنه
+
+660
+00:53:02,710 --> 00:53:07,250
+لازم ال class أو ال target predefined يكون معرف
+
+661
+00:53:07,250 --> 00:53:11,940
+مسبقا مش أنت اللي بدك تشتهي تتحطهبدي أكون معرف
+
+662
+00:53:11,940 --> 00:53:15,160
+مسبقًا مثل قال لي و الله في عالم الحيوانات في عندي
+
+663
+00:53:15,160 --> 00:53:19,820
+فقاريات و لا فقاريات في الفقاريات في عندي ذوات
+
+664
+00:53:19,820 --> 00:53:24,800
+الدم الحار و ذوات الدم البارد و هذا مرتبط بأرجل و
+
+665
+00:53:24,800 --> 00:53:29,340
+هذا مالوش أرجل في اللي في اللي لا فقاريات و إيه
+
+666
+00:53:29,340 --> 00:53:32,160
+جرح قال لي قال لي و الله عندي كائن حي يأكل و يتنفس
+
+667
+00:53:32,160 --> 00:53:34,340
+ما هو كله الآن يأكل و يتنفس و لا شراهك لأنه كائن
+
+668
+00:53:34,340 --> 00:53:43,510
+حي في الآخر قال لك الآن لا يحتوي على عظاملا فقريات
+
+669
+00:53:43,510 --> 00:53:52,270
+وليس له أرجل تمام؟ واتخذ الشكل الطولي حصرته يعني
+
+670
+00:53:52,270 --> 00:53:56,410
+انت لحظة ردتك مواصفاته وانت بناء على الكلام اللي
+
+671
+00:53:56,410 --> 00:54:01,120
+أنا بقوله انت وصلت لمين؟يعني مثلًا لواحد من الـ
+
+672
+00:54:01,120 --> 00:54:04,360
+two objects هدولة اللي موجودة عندي وبالتالي هي ال
+
+673
+00:54:04,360 --> 00:54:08,400
+classification أنت عندك معرفة بدك تبنيها من ال
+
+674
+00:54:08,400 --> 00:54:13,400
+data set عشان تتنبأ لو أعرضتلك حالة مشابهة ما
+
+675
+00:54:13,400 --> 00:54:16,940
+جُلتلك .. ما جُلتلكاش حالة منهم الحالة اللي منهم
+
+676
+00:54:16,940 --> 00:54:19,620
+الأصل أنت تديني one hundred percent وما تخطأيش
+
+677
+00:54:19,620 --> 00:54:23,540
+فيهم بس أنا بعلم cash عشان أختبرك في ال إيه؟ في ال
+
+678
+00:54:23,540 --> 00:54:28,100
+.. في الموجود اللي أنا بجهزك عشان تقدر تتعامل مع
+
+679
+00:54:28,100 --> 00:54:29,000
+ال case الجديدة
+
+680
+00:54:40,450 --> 00:54:43,290
+كيف يعني؟ مش فاهم يعني مثلا بالجانات الحياة
+
+681
+00:54:43,290 --> 00:54:48,270
+بتتنفسر .. أه هو الآن .. هسير لاحقا إذا الآن ..
+
+682
+00:54:48,270 --> 00:54:51,670
+الآن .. لما نتكلم في ال .. ال attribute أو في ال
+
+683
+00:54:51,670 --> 00:54:56,710
+selection إذا الآن ال attribute هذا كله فيه
+
+684
+00:54:56,710 --> 00:55:00,870
+constant value أو ال variation فيه قليلة فهذا ال
+
+685
+00:55:00,870 --> 00:55:04,930
+attribute useless فبحثوا فهم ممكن يديني إيش مش ..
+
+686
+00:55:04,930 --> 00:55:08,590
+ما .. ما بتنفس مثلا هم كل اللي عندك .. يقولوا كله
+
+687
+00:55:08,590 --> 00:55:14,020
+شرط يعني معناته بيكون outlierالفكرة كمان مرة، الآن
+
+688
+00:55:14,020 --> 00:55:18,480
+.. «أو ما تخدعش معين الأدبار» خلاص، هذا الـ «Raw»
+
+689
+00:55:18,480 --> 00:55:21,340
+بده ينشال مش لازم يظل موجود عندى أو الـ
+
+690
+00:55:21,340 --> 00:55:25,140
+«Attribute» هذا عفواً ببطل القيمة لأنه كمان مرة يا
+
+691
+00:55:25,140 --> 00:55:29,560
+جماعة الخير الأصل .. الأصل أنه أنا بأدور على
+
+692
+00:55:29,560 --> 00:55:33,100
+«Discriminative Attributes» صفات مميزة آجي أقول
+
+693
+00:55:33,100 --> 00:55:37,580
+على سبيل المثال آجي أقول والله الـ «Gender» بدي
+
+694
+00:55:37,580 --> 00:55:43,100
+أحطه من ضمن الـ «Attribute» فيهتأثير الحالة الصحية
+
+695
+00:55:43,100 --> 00:55:48,220
+تأثير الحالة الصحية لقلاب مدرسة الشجاعية
+
+696
+00:55:48,220 --> 00:55:53,720
+الإبتدائية للذكور انت ملاحظ؟ لأن هذا ال attribute
+
+697
+00:55:53,720 --> 00:56:00,340
+useless لأن ال society تبعتك اللي انت مستهدفها
+
+698
+00:56:00,340 --> 00:56:06,160
+كلها نفس الفئة فبالتالي هذا ال attribute مش مميز
+
+699
+00:56:06,160 --> 00:56:07,120
+نعم
+
+700
+00:56:10,800 --> 00:56:13,700
+ما هي اللي أنا قلته، عشان هيك ماكنتش الـFly هي
+
+701
+00:56:13,700 --> 00:56:19,720
+المؤثرة كنت بتكلم على النفس والأكل والريش، هدول
+
+702
+00:56:19,720 --> 00:56:24,480
+اللي طائر وكانت النفس والأكل أجوى، ليش؟ لأنه زي ما
+
+703
+00:56:24,480 --> 00:56:28,580
+قلنا ممكن يكون في عندي طائرة مغطا، مغطا بريش الآن
+
+704
+00:56:28,580 --> 00:56:32,940
+هذا مثال آخر، جاله هي ال data set هذا مثال شركة
+
+705
+00:56:32,940 --> 00:56:38,410
+تأمين، بدها تأمين السياراتشركات التأمين بتفتح عشان
+
+706
+00:56:38,410 --> 00:56:40,930
+تكسب من المصارى اللى بتاخدها حجب بوليست التأمين
+
+707
+00:56:40,930 --> 00:56:44,690
+الآن إذا كل واحد بده يسجل عندى أو بده يأمن عندى
+
+708
+00:56:44,690 --> 00:56:48,410
+بده يعمل حادث وانا بده أدفعله مات وانا هاخسر فالآن
+
+709
+00:56:48,410 --> 00:56:52,890
+قالوا بده نعمل دراسة نقدر ال risk تبع بوليست
+
+710
+00:56:52,890 --> 00:56:57,930
+التأمين high high ولا low جابونله ال circle data
+
+711
+00:56:57,930 --> 00:57:04,430
+عندهم هيها فيها ال age وفيها ال typeوفعلياً ال
+
+712
+00:57:04,430 --> 00:57:08,150
+risk في ال reality هذه الأحداث كانت موجودة عندهم
+
+713
+00:57:08,150 --> 00:57:12,010
+كانت ال risk high ولا low الآن مفهوم ال
+
+714
+00:57:12,010 --> 00:57:16,490
+classification أنه يجب أن يبني أو يدرس ال data set
+
+715
+00:57:16,490 --> 00:57:21,510
+high ويبني لي predictor أو يديني classifier عشان
+
+716
+00:57:21,510 --> 00:57:26,850
+لما أنا آجي أقوله والله أنا فيه عندي راجل عمره
+
+717
+00:57:26,850 --> 00:57:30,690
+ستين سنة وبيدو سوق sport car
+
+718
+00:57:36,030 --> 00:57:39,910
+الـ Risk High و لا Low؟ انت بقى بتقول High و غيرك
+
+719
+00:57:39,910 --> 00:57:43,630
+بدي يقول Low بس الآن مش على كيفك ال system بعد ما
+
+720
+00:57:43,630 --> 00:57:50,490
+بيعمل Analysis تمام؟ هيروح يديني Specific Rule وهو
+
+721
+00:57:50,490 --> 00:57:54,110
+اللي بدي يقوللي ال system هذا استخدمنا فيه
+
+722
+00:57:54,110 --> 00:57:59,650
+decision tree فقاللي إذا كان العمر أقل من 25 فال
+
+723
+00:57:59,650 --> 00:58:07,660
+Risk High مباشرة إذا ال age أكبر من 25تمام؟ العامل
+
+724
+00:58:07,660 --> 00:58:11,540
+التاني اللي في ال risk نوع السيارة إذا كانت sport
+
+725
+00:58:11,540 --> 00:58:18,620
+car فهي ال risk high otherwise ال risk low بالتالي
+
+726
+00:58:18,620 --> 00:58:25,540
+ال prediction تبعت هذه high تمام؟
+
+727
+00:58:25,540 --> 00:58:30,080
+هي المطلوب مني إن ال systemأو الـ Machine Learning
+
+728
+00:58:30,080 --> 00:58:34,560
+Algorithm كـ classifier ياخد ال data set يحللها
+
+729
+00:58:34,560 --> 00:58:40,940
+يبني decisions قرارات عشان يقول في الآخر ال risk
+
+730
+00:58:40,940 --> 00:58:43,540
+high ولا low بينفعش يقول intermediate
+
+731
+00:58:46,030 --> 00:58:50,150
+ولا بيقوله بالنسبة معينة، الآن هو تعلم عشان ياخد
+
+732
+00:58:50,150 --> 00:58:54,930
+قرار إما بـhigh أو low مافيش .. مافيش إله خيار غير
+
+733
+00:58:54,930 --> 00:58:57,950
+هيكده، الآن يا جماعة الخيار .. و هذه الميزة اللي
+
+734
+00:58:57,950 --> 00:59:01,810
+بتميز فيها الإنسان عن الآلة، الآلة بتعلم .. الآلة
+
+735
+00:59:01,810 --> 00:59:05,390
+بتعلمه high و low بس، فبيصير جوابك high و low،
+
+736
+00:59:05,390 --> 00:59:07,730
+مافيش .. مافيش عنده جماعة غير هيك، بتع .. لكن
+
+737
+00:59:07,730 --> 00:59:11,550
+الإنسان بيجي يقولك يا عم يصبر شوية، هذا ستين سنة
+
+738
+00:59:12,370 --> 00:59:16,810
+راجل عاجل وراكز ومش عارف .. وربنا ومنعم عليه
+
+739
+00:59:16,810 --> 00:59:22,610
+بالفلوس وين المشكلة الـ Mercedes Sport Car؟ هيمشي
+
+740
+00:59:22,610 --> 00:59:26,910
+فيها بالراحة، جماد أول الراجل، بخاف عليا لا تنخدش،
+
+741
+00:59:26,910 --> 00:59:30,470
+فهيمشي فيها بالراحة، فهذه المعايير بتصير عند الـ
+
+742
+00:59:30,470 --> 00:59:34,410
+human بتلعب دور، لكن عند الآلة strict، واحد زائد
+
+743
+00:59:34,410 --> 00:59:37,500
+واحد يساوي اتنينوبالتالي ال prediction يا رامي
+
+744
+00:59:37,500 --> 00:59:41,420
+تبقى على ال data set ما تقولليش أنت ال case طبعا
+
+745
+00:59:41,420 --> 00:59:45,180
+برجع و بأكد يا جماعة الخير اللي كانت المشكلة أنه
+
+746
+00:59:45,180 --> 00:59:48,440
+أنا رسمت ال data set قدامك أو حاولت أبنيها قدامك
+
+747
+00:59:48,440 --> 00:59:52,580
+بالتشاور معاك لكن لو حاطيتك إياها فجأة هتختلف
+
+748
+00:59:52,580 --> 00:59:56,980
+نظرتك تماما لا إلاالـ mining task التاني اللي في
+
+749
+00:59:56,980 --> 01:00:01,420
+الـ prediction الـ regression وحكينا فيها كتير
+
+750
+01:00:01,420 --> 01:00:05,920
+قيمة الأسس، قيمة السهم الآن لما أنا بتكلم في الـ
+
+751
+01:00:05,920 --> 01:00:10,160
+regression يا شباب إنه أنا فعلياً بتكلم إنه بدي
+
+752
+01:00:10,160 --> 01:00:17,580
+أعمل prediction ل value كمية المبيعات قيمة السهم
+
+753
+01:00:17,580 --> 01:00:25,080
+كمية المطر المتساقطة سرعة الرياح درجة الحرارةلاحظ
+
+754
+01:00:25,080 --> 01:00:29,420
+ولا مرة من المرات قلتلك بده يرتفع ولا ينخفض ولا
+
+755
+01:00:29,420 --> 01:00:33,740
+يبقى ثابت قلتلك اتديني value وغالبا بندور على
+
+756
+01:00:33,740 --> 01:00:39,640
+continuous value تمام؟ وهكذا .. هكذا أنا بتكلم على
+
+757
+01:00:39,640 --> 01:00:44,120
+regression .. regression task باجي بقول والله
+
+758
+01:00:44,120 --> 01:00:49,060
+أسعار المنازل في المنطقة الفلانية بعد تلت سنوات
+
+759
+01:00:49,060 --> 01:00:55,030
+كده هيتصيربناء على مواصفات المنزل 200 متر مكوّن من
+
+760
+01:00:55,030 --> 01:00:58,830
+أربع غرف مثلا وشرفة وإلى آخره وحديقة من هالكلام
+
+761
+01:00:58,830 --> 01:01:02,830
+هذا هذه المواصفات كلها بتقول إن البيت بعد هيكد
+
+762
+01:01:02,830 --> 01:01:07,490
+هيكون هذا حاجه مثلا 600 ألف دولار بعد تلت سنوات
+
+763
+01:01:07,490 --> 01:01:12,610
+هذه regression ليش؟ لأن فعليا أنا بتكلم على value
+
+764
+01:01:19,930 --> 01:01:22,330
+الـ Clustering في الـ Descriptive Data Mining
+
+765
+01:01:22,330 --> 01:01:27,730
+Tasks في الـ Descriptive البيانات الوصفية احنا
+
+766
+01:01:27,730 --> 01:01:31,170
+شفنا واشتغلنا مع بعض بالمثال الأول لما قلتلك
+
+767
+01:01:31,170 --> 01:01:37,040
+وزعلياهم لمجمعتين وزعلياهم لأربع مجموعاتفانت
+
+768
+01:01:37,040 --> 01:01:40,200
+فعليًا كنت بتوزع ال data points اللي هو الصور
+
+769
+01:01:40,200 --> 01:01:43,220
+كانوا عندنا أو ال rows اللي في ال data set اللي
+
+770
+01:01:43,220 --> 01:01:48,720
+عندي بناءً على ال similarity تبعتها في المجموعة
+
+771
+01:01:48,720 --> 01:01:55,200
+ليش ماحطتش الطير أو العصفور مع الطيارة؟ لأن فيه
+
+772
+01:01:55,200 --> 01:01:57,480
+إيه ال characteristics أو attributes خاصة عن
+
+773
+01:01:57,480 --> 01:02:02,060
+الطيارة فكان في مجموعة تانية لكن لو احنا مثلًا
+
+774
+01:02:04,060 --> 01:02:07,300
+بقولنا والله إنهم بيكونوا هدولة في مجموعتين وبناء
+
+775
+01:02:07,300 --> 01:02:13,980
+على سلوب التنقل الموجود كمان ممكن الطيارة والعصفر
+
+776
+01:02:13,980 --> 01:02:16,700
+يكونوا في نفس المكان ولا لأ؟ بناء على ال
+
+777
+01:02:16,700 --> 01:02:19,480
+properties أو ال characteristics لكن ال data .. ال
+
+778
+01:02:19,480 --> 01:02:24,780
+system كل اللي بياخده منك عدد ال clusters اللي أنت
+
+779
+01:02:24,780 --> 01:02:28,780
+محتاجها جداش .. كام cluster أنت محتاجه؟ اتنين،
+
+780
+01:02:28,780 --> 01:02:33,490
+تلاتة، أربعة؟ وبروح بصنفلك إياهمأو بعفوًا بجسملك
+
+781
+01:02:33,490 --> 01:02:37,270
+إياهم و بقولك العناصر كذا في المجموعة الفلانية
+
+782
+01:02:37,270 --> 01:02:39,910
+العناصر كذا في المجموعة التالية العناصر كذا في
+
+783
+01:02:39,910 --> 01:02:43,050
+المجموعة الثالثة في الرابعة و بعد هيك و بيقف لحد
+
+784
+01:02:43,050 --> 01:02:48,050
+الأربعة لا بيزيد خمسة ولا بيوقف عن تلاتة بناء على
+
+785
+01:02:48,050 --> 01:02:52,110
+ال similarity الموجودة هذه العناصر الآن اللي هي
+
+786
+01:02:52,110 --> 01:02:56,250
+دوائر اللون اللي باللون الأصفرفعلياً هي الـ data
+
+787
+01:02:56,250 --> 01:03:02,450
+set تبعتنا هي مجموعة الصور تبعتنا الآن واضح أنه في
+
+788
+01:03:02,450 --> 01:03:07,130
+توزيع ما بينهم إبعاد عن بعض في الرسم يعني فعلياً
+
+789
+01:03:07,130 --> 01:03:13,830
+قبيعتهم مقسمات مصنفات فكانت هذه واحدة هذه اتنتين
+
+790
+01:03:13,830 --> 01:03:17,850
+هذه تلاتة وهذا هو التجميع فبيجي دور ال cluster
+
+791
+01:03:17,850 --> 01:03:22,470
+algorithm بيجي يقول لي هذه العناصرمن كذا لكذا في
+
+792
+01:03:22,470 --> 01:03:25,730
+المجموعة الأولى، كذا لكذا لمجموعة تانية، كذا وكذا
+
+793
+01:03:25,730 --> 01:03:30,790
+للمجموعة اللي بعدها من الـ Outer طبعا فيه هنا مثال
+
+794
+01:03:30,790 --> 01:03:33,850
+على ال document clustering تجميع المستندات أو
+
+795
+01:03:33,850 --> 01:03:37,170
+تصنيف المستندات المستندات اللي موجودة على ال web
+
+796
+01:03:37,170 --> 01:03:42,680
+أو في ال Wikipediaممكن تصنف؟ أه ممكن تصنف، بناء
+
+797
+01:03:42,680 --> 01:03:46,120
+على إيش؟ بناء على المحتوى، معناته أنا بدأ أروح
+
+798
+01:03:46,120 --> 01:03:49,400
+أدور أخد ال frequent term أو ال frequent words
+
+799
+01:03:49,400 --> 01:03:52,660
+اللي في كل document تمام؟ و أحاول أعرف ال
+
+800
+01:03:52,660 --> 01:03:55,800
+categories اللي موجودة و أجسمهم بدون ما أعرف ال
+
+801
+01:03:55,800 --> 01:03:58,200
+categories اللي أنا بصير classification، هجسمهم
+
+802
+01:03:58,200 --> 01:04:01,780
+على مجموعات بناء على قربهم أو بعضهم، حسب بديهم
+
+803
+01:04:01,780 --> 01:04:07,330
+مجموعتين، تلاتة، أربعةفي الـ Outlier Detection
+
+804
+01:04:07,330 --> 01:04:11,830
+كذلك هي Descriptive Task Descriptive Task الآن
+
+805
+01:04:11,830 --> 01:04:17,710
+بتفرق شوية عن ال Clustering إنه أنا بدي أصير أدور
+
+806
+01:04:17,710 --> 01:04:22,630
+على النقاط البعيدة اللي مافيش شغلات بتشبهها لو أنا
+
+807
+01:04:22,630 --> 01:04:26,030
+أجيب و قلتلك هذا الرسم في الـ 2D لكل ال data 6
+
+808
+01:04:26,030 --> 01:04:31,720
+ببعتي الآن واضح إن هي هذه النقطةoutlier لأنه مافيش
+
+809
+01:04:31,720 --> 01:04:36,100
+شغلة حواليها مافيش إشي بشابهها مافيش بعيدة عن
+
+810
+01:04:36,100 --> 01:04:39,940
+الجيران نفس
+
+811
+01:04:39,940 --> 01:04:42,920
+الكلام النقطة هاي .. نفس الكلام النقطة هاي طب
+
+812
+01:04:42,920 --> 01:04:46,840
+التلاتة هدول أه بنقر يكونوا outlier التلاتة لأنه
+
+813
+01:04:46,840 --> 01:04:51,020
+لم يصلوا إلى الحد الأدنى من التجمع يعني أشيقول
+
+814
+01:04:51,020 --> 01:04:54,640
+والله مثلا أقل عدد .. أقل تجمع بدي اعتبره أربع
+
+815
+01:04:54,640 --> 01:04:58,360
+عناصر، خمس عناصر، عشر عناصر، مائة عنصر وبيتلاحظ
+
+816
+01:04:58,360 --> 01:05:03,360
+شغلة تانية كمانهدول كلياتهم جايات مع بعض as one
+
+817
+01:05:03,360 --> 01:05:08,560
+cluster على الرغم إن النقاط نوعا ما متباعدة وهنا
+
+818
+01:05:08,560 --> 01:05:13,460
+بيصير إنه ماحدش بيقول إن ال density تبعت ال
+
+819
+01:05:13,460 --> 01:05:18,280
+cluster اللي عندي تكون متساويةالمجموعات اللي عندي
+
+820
+01:05:18,280 --> 01:05:22,700
+مش بالضرورة تكون بتحتوي نفس الأعداد ومش بالضرورة
+
+821
+01:05:22,700 --> 01:05:27,400
+كلها نفس الكثافة واضح هذا أكثر كثافة من كل ال
+
+822
+01:05:27,400 --> 01:05:30,380
+clusters اللي موجودة عندي ولا لأ؟ بينما هذا هو
+
+823
+01:05:30,380 --> 01:05:34,520
+الأقل كثافة هذا الأكثر انتظاما هذا وهذا بينما هذا
+
+824
+01:05:34,520 --> 01:05:38,460
+لأ شوية في بعض لكن في الآخر بال outlier detection
+
+825
+01:05:38,460 --> 01:05:44,130
+أنا بكون بهمني فقط التعامل مع النقاطاللي هي
+
+826
+01:05:44,130 --> 01:05:48,290
+المنفردة أو المعزولة عن التجمعات اللي موجودة اللي
+
+827
+01:05:48,290 --> 01:05:55,650
+أنا عمالًا بحاول أحددها ممكن
+
+828
+01:05:55,650 --> 01:06:00,910
+.. ممكن .. انت مش ممكن تختصير تساوي تتحقق .. تتحقق
+
+829
+01:06:00,910 --> 01:06:04,910
+ال value هذه .. هذه صارت out لا يعني بسبب إيش؟
+
+830
+01:06:04,910 --> 01:06:10,290
+مثلًا في طائر و مش محطول إنه يتنفس ممكن أراح ..
+
+831
+01:06:10,290 --> 01:06:13,050
+أراح سجل الحالة تبعته بعد ما مات
+
+832
+01:06:16,070 --> 01:06:19,230
+طبعا؟ فهيبدأ تصير تسأل هذي ال outlier ليش كانت
+
+833
+01:06:19,230 --> 01:06:22,650
+موجودة
+
+834
+01:06:22,650 --> 01:06:28,250
+الان
+
+835
+01:06:28,250 --> 01:06:31,370
+بيصير في عندك مشكلة في ده يعني الان تخيل النقاط
+
+836
+01:06:31,370 --> 01:06:32,710
+موزعة هيك مؤمن بيقول
+
+837
+01:06:46,680 --> 01:06:52,300
+لا حتمًا في عندك مشكلة في ال data آه
+
+838
+01:06:52,300 --> 01:06:56,040
+آه ال outlier ليش أنا بدي أعمل عليها detection إذا
+
+839
+01:06:56,040 --> 01:06:58,620
+بهدف جابتلي طبعًا واحدة من ال learn من ال
+
+840
+01:06:58,620 --> 01:07:05,570
+preprocessing تحييض ال outlier لأنه بيأثر علىقرار
+
+841
+01:07:05,570 --> 01:07:08,530
+النظام أو على تعليم الـ system اللي موجود عندك
+
+842
+01:07:08,530 --> 01:07:12,610
+فانت data set بالشكل هذا data set غير منظمة فيها
+
+843
+01:07:12,610 --> 01:07:17,750
+مشكلة بدك تشوف الآن إيه السبب المشكلة هذه و تحاول
+
+844
+01:07:17,750 --> 01:07:21,890
+تتجنبها أو بتروح تحذف كل out layers point هاي اللي
+
+845
+01:07:21,890 --> 01:07:26,230
+موجودة عندك حتى لو بيخسر data كتير ماحدش بيقول إنه
+
+846
+01:07:26,230 --> 01:07:34,360
+data الآن يعني تخ ..الأصل الـ data بتكون ملائمة
+
+847
+01:07:34,360 --> 01:07:38,220
+وتكون ذات جودة عالية لل task اللي أنت بتتنفذها
+
+848
+01:07:38,220 --> 01:07:42,720
+وإلا مش هتحصل على قرار سليم لأنه كمان مرة إذا هذه
+
+849
+01:07:42,720 --> 01:07:46,160
+النقاط بدها تدخل في الحسبة لاحقا في حسبة القرار
+
+850
+01:07:46,160 --> 01:07:50,200
+بتصير تحرف القرار عن الصحة وبالتالي مافيش قدامك
+
+851
+01:07:50,200 --> 01:07:53,080
+اللي جار انت إيش تخلص منها
+
+852
+01:08:01,120 --> 01:08:06,140
+مش هني مشكلة لإن أنا فعليا بدور هل في عندي outlier
+
+853
+01:08:06,140 --> 01:08:10,460
+ولا لأ أديك حالة إن ال outlier هيصير بحد ذاته هو
+
+854
+01:08:10,460 --> 01:08:14,680
+المطلوب الآن إياد الشام بيستخدم بطاقة لإتمان
+
+855
+01:08:14,680 --> 01:08:22,160
+وبشتري معدل الشهر 250 دولار تمام؟ وهذا الكلام لل
+
+856
+01:08:22,160 --> 01:08:25,020
+trend تبعه له خمس أو ست سنوات من يوم ما أخد
+
+857
+01:08:25,020 --> 01:08:32,470
+البطاقةالشهر هذا شهر اتنين الفين وعشرين مشتريات
+
+858
+01:08:32,470 --> 01:08:36,330
+إياد الشامي تجاوزت الست مائة دولار على البطاقة و
+
+859
+01:08:36,330 --> 01:08:42,830
+احنا لسه على الشهر ماخلصش شو رأيك؟ outlier و هذا
+
+860
+01:08:42,830 --> 01:08:46,130
+اللي أنا بدي .. اللي بدي أتحقق خلاص بدي أوقف عشان
+
+861
+01:08:46,130 --> 01:08:51,570
+أتحقق من الحالة اللي موجودة عندي وبالتاليأنا قاعد
+
+862
+01:08:51,570 --> 01:08:54,750
+بقى أشتغل إن والله ال data set اللي عندي أو ال
+
+863
+01:08:54,750 --> 01:08:58,510
+outlier هي بحد ذاتها هي المطلوبة فممكن زي ما بنقول
+
+864
+01:08:58,510 --> 01:09:02,050
+للشباب إنه فعليا ال outlier هذه هي بحد ذاتها
+
+865
+01:09:02,050 --> 01:09:06,170
+المطلوبة ممكن تكون مطلوبة بسبب الحماية إنه أنا
+
+866
+01:09:06,170 --> 01:09:09,610
+فعليا الحركة هذه صارت .. مش هي الحركة الحقيقية على
+
+867
+01:09:09,610 --> 01:09:14,820
+حركة إياد الشامي ومن ثمالإحتمال الأكبر أنه في
+
+868
+01:09:14,820 --> 01:09:19,240
+البطاقة صُرِقت وبالتالي أنا إيش؟ بدي أوقف البطاقة
+
+869
+01:09:19,240 --> 01:09:21,820
+لحد ما أتأكد إنه فعليا هو صاحبها اللي عمال بيشتري
+
+870
+01:09:21,820 --> 01:09:25,480
+ولا لأ فزي ما قلتلك أحيانا الـ outlier بيلزمني في
+
+871
+01:09:25,480 --> 01:09:28,600
+الـ network traffic أنا الآن في الـ server الجامعة
+
+872
+01:09:28,600 --> 01:09:34,100
+كل طلاب الجامعة القدامة والجداد يعدوبهم خمسين ألف
+
+873
+01:09:34,100 --> 01:09:36,860
+قدامة وجداد بدي أقول كتالة اللي هم ال active واللي
+
+874
+01:09:36,860 --> 01:09:40,260
+ممكن يزوروا صفحتي الجامعة في لحظة من اللحظات ال
+
+875
+01:09:40,260 --> 01:09:46,730
+request خطأت الميت ألفمرة واحدة لأ واجه شوية في ..
+
+876
+01:09:46,730 --> 01:09:49,710
+في عمال يعمل .. عمال بتتعرض لهجوم معين أنا بدي
+
+877
+01:09:49,710 --> 01:09:53,710
+أنتبهله فبتصير ال outlier بحد ذاتها معرفتها أو
+
+878
+01:09:53,710 --> 01:09:58,090
+تحقيق .. تحقيق أو تأكيدها هي المطلوبة هي الغاية
+
+879
+01:09:58,090 --> 01:10:02,030
+بذاتها مش لإنه أنا بدي أبعد أستبعدها لأ لإنه أنا
+
+880
+01:10:02,030 --> 01:10:07,300
+هتعالج المشكلة هتترتب عليهاهذه صورة برضه مثالة للـ
+
+881
+01:10:07,300 --> 01:10:09,800
+Ozone، لطابقة الـ Ozone و للـ Outer Air Detection
+
+882
+01:10:09,800 --> 01:10:12,400
+آخر حاجة عندنا في الـ Mining Task اللي هي الـ
+
+883
+01:10:12,400 --> 01:10:16,160
+Association Rule، الارتباط، معاملات الارتباط أو
+
+884
+01:10:16,160 --> 01:10:21,240
+العناصر، قوانين ارتباط العناصر مع بطن، هان أنا
+
+885
+01:10:21,240 --> 01:10:26,790
+فعليا بأدور على Interesting Relationshipعلاقات بين
+
+886
+01:10:26,790 --> 01:10:30,910
+مين؟ بين الـ Variables لاحظ ما اتكلمتش على الـ
+
+887
+01:10:30,910 --> 01:10:34,970
+Target في كل الـ Descriptive Outlier و Clustering
+
+888
+01:10:34,970 --> 01:10:38,990
+ما اتكلمتش على الـ Target الـ Target فقط موجود في
+
+889
+01:10:38,990 --> 01:10:42,870
+الـ Predictive في الـ Descriptive مافيش وكأنه كل
+
+890
+01:10:42,870 --> 01:10:46,770
+ال data set هي عبارة عن explanatory variables وانا
+
+891
+01:10:46,770 --> 01:10:50,850
+بنصير أتعامل معاها فقط و أدرس العلاقة ما بين ال
+
+892
+01:10:50,850 --> 01:10:56,820
+attributes هاي من أكثر الأمثلة المشهورة جداًارتباط
+
+893
+01:10:56,820 --> 01:11:01,800
+الأمراض بعادات أو بتصرفات مثلًا سرطان الرقب
+
+894
+01:11:01,800 --> 01:11:09,100
+التدغين مثلًا فقر الدم بالسوق التخزية مثلًا
+
+895
+01:11:09,100 --> 01:11:13,540
+البدانة بعد ممارسة الرياضة والإفراط في الأكل هذه
+
+896
+01:11:13,540 --> 01:11:17,420
+الـ Association ليست على حالة وتنتين وتلاتة هذه
+
+897
+01:11:17,420 --> 01:11:22,000
+أصلحت حقائق لأن كل الـ datasetبتقولّي والله الوزن
+
+898
+01:11:22,000 --> 01:11:25,920
+الزائد مع سوق تغذية وتدخين أو إفراط في التغذية
+
+899
+01:11:25,920 --> 01:11:30,500
+والتدخين ومافيش رياضة موجودين، تمام؟ فهذه عبارة عن
+
+900
+01:11:30,500 --> 01:11:36,020
+ارتباط بيجي بقولّي في ال transaction في المبيعات
+
+901
+01:11:36,020 --> 01:11:40,760
+الناس اللي بتشتري الأصناف الفلانية هي دايما اللي
+
+902
+01:11:40,760 --> 01:11:44,900
+بتدور على الأصناف كذا يعني مثلا بروح والله أسين من
+
+903
+01:11:44,900 --> 01:11:49,880
+الناس بروح بشتري السمن حيواني من ال supermarket
+
+904
+01:11:51,210 --> 01:11:58,610
+بروح بيشتري مثلا بيشتري المكسرات
+
+905
+01:11:58,610 --> 01:12:03,750
+لدرجة معينة فالآن هذا ال trend تبعه هيه هيك و
+
+906
+01:12:03,750 --> 01:12:08,690
+بيصير و بيصير عند ال supermarket قناعة تمة إن فئة
+
+907
+01:12:08,690 --> 01:12:12,950
+الناس هدول اللي بتروح على السمن الحيواني هذاهم نفس
+
+908
+01:12:12,950 --> 01:12:15,970
+الفئة اللي بتدور على الشغلات هدول فبصير إيش ممكن
+
+909
+01:12:15,970 --> 01:12:20,930
+يعيد ترتيب العناصر عشان يسهل عليهم موضوع الشراء
+
+910
+01:12:20,930 --> 01:12:26,990
+نعمبصير ممكن أوفر عقدر باعرف هدول جديش هم من حجم
+
+911
+01:12:26,990 --> 01:12:30,190
+الزبائن اللي عندي و بصير أنا بجيب الكيمية اللي
+
+912
+01:12:30,190 --> 01:12:34,250
+تتناسب مع احتياجاتهم بدون ما أتضرر أنا من خسارة
+
+913
+01:12:34,250 --> 01:12:37,850
+فالـ Association Rules مهمة و تطبيقاتها واسعة جدا
+
+914
+01:12:37,850 --> 01:12:44,170
+جديش الناس اللي بتستخدم Android و IOS مقابلًا في
+
+915
+01:12:44,170 --> 01:12:47,190
+الـ Accessories و ارتباطهم في .. مع البرامج اللي
+
+916
+01:12:47,190 --> 01:12:52,090
+موجودة و إلى آخرهمففعليًا أنه أنا بأدور .. بحاول
+
+917
+01:12:52,090 --> 01:12:58,230
+أدور على set of rules أبني مجموعة من القوانين توصف
+
+918
+01:12:58,230 --> 01:13:06,310
+ارتباط العناصر مع بعضها وهذا عادة يكون ضمن قوانين
+
+919
+01:13:06,310 --> 01:13:08,450
+محددة مثلًا، جالي هذه في عندي transaction
+
+920
+01:13:08,450 --> 01:13:12,070
+لسوبرماركت بيف و chicken و milk، في عندي سبعة
+
+921
+01:13:12,070 --> 01:13:18,550
+transactions الآن، لو أنا سألت قداش عدد الناساللي
+
+922
+01:13:18,550 --> 01:13:25,690
+اشترت حليب و لحمة مع بعض آه أخدت حليب و لحمة بيف و
+
+923
+01:13:25,690 --> 01:13:32,830
+milk واحد .. اتنين .. اتنين هل انا لو انا سألت
+
+924
+01:13:32,830 --> 01:13:35,730
+هدول لو قرفت راطون هي ال data 6 بقعت يا رايمي بس
+
+925
+01:13:35,730 --> 01:13:40,250
+عشان انا اقدر اتخيل الموضوع مدي اش اقول والله لان
+
+926
+01:13:40,250 --> 01:13:44,620
+في ارتباط بين اللحمة و الحليب مثلاOkay، جديش هذا
+
+927
+01:13:44,620 --> 01:13:49,080
+الكلام مدعوم من ال data set؟ جديش حقيقة ما موجود؟
+
+928
+01:13:49,080 --> 01:13:53,300
+اتنين على سبعة، اتنين على سبعة نسمة متدنية، وصلتش
+
+929
+01:13:53,300 --> 01:13:57,120
+لخمسين في المية، ولا لأ؟ ولو أتينا مثلا، جديش
+
+930
+01:13:57,120 --> 01:14:02,320
+الناس اللي أخدت مثلا ال chicken و beef مع بعض؟
+
+931
+01:14:02,320 --> 01:14:11,710
+واحد، اتنين، واحد، اتنين،تلاتة ال beef و ال
+
+932
+01:14:11,710 --> 01:14:15,110
+chicken ال beef و ال chicken واحدة .. اتنين ..
+
+933
+01:14:15,110 --> 01:14:19,070
+تلاتة .. وين الرابع يا أخو؟ ال cheese .. ال cheese
+
+934
+01:14:19,070 --> 01:14:23,110
+.. جبنة .. جبنة .. تمام؟ الآن ال beef و ال chicken
+
+935
+01:14:23,110 --> 01:14:28,350
+هذا تلاتة .. هذا الارتباط أكثر بس برضه ماوصلش ..
+
+936
+01:14:28,350 --> 01:14:31,710
+بس لكن أفضل من الأولاني على الأقل ممكن يصير فيه
+
+937
+01:14:31,710 --> 01:14:35,250
+توجه أن والله أن الناس .. يعني مش كلها بتاكل لحمة
+
+938
+01:14:35,250 --> 01:14:38,490
+حمراء فبياخدوا اللحمة وبياخدوا الدجاج لأنهم هم في
+
+939
+01:14:38,490 --> 01:14:44,820
+البيتالناس مقسمين على موضوع الأكل ففي الآخر ممكن
+
+940
+01:14:44,820 --> 01:14:47,940
+أحسب ال support و أحسب ال confidence حنشوف ينجدش
+
+941
+01:14:47,940 --> 01:14:51,540
+دقة الكلام الرولي اللي أنا بتقول عليه هذا بشكل
+
+942
+01:14:51,540 --> 01:14:56,300
+صحيح فوزن التكرار .. اه التكرار مهم .. وزنه .. كل
+
+943
+01:14:56,300 --> 01:15:01,380
+موقف .. مثلا اتنين تكرر تسعة أربع مرات الملك لحاله
+
+944
+01:15:01,380 --> 01:15:06,060
+يعني بكون frequent item لأ المقصد أنه لو قسمنا كل
+
+945
+01:15:06,060 --> 01:15:10,990
+..لأ لأ هو الأنش كمان الفكرة وين إذا بتكلم عن
+
+946
+01:15:10,990 --> 01:15:15,070
+الملك لحاله هذا attribute إذا البيف لحالها دي
+
+947
+01:15:15,070 --> 01:15:19,630
+attribute، الآن باجي بتكلم هذا جداش ال frequent،
+
+948
+01:15:19,630 --> 01:15:22,730
+جداش الطلب عليه، okay لكن مش association،
+
+949
+01:15:22,730 --> 01:15:24,930
+association لازم يكون في عندي two different
+
+950
+01:15:24,930 --> 01:15:29,690
+attributes على الأقل متلازمين مع بعضهم، هدول اللي
+
+951
+01:15:29,690 --> 01:15:34,340
+أنا بدأ أور عليهمالـ Minimum Support والـ Minimum
+
+952
+01:15:34,340 --> 01:15:37,700
+Confidence هنتكلم عليهم لاحقا لما نروح على ال
+
+953
+01:15:37,700 --> 01:15:42,500
+cluster على ال association rule بالتفصيل الآن أخر
+
+954
+01:15:42,500 --> 01:15:47,800
+شغلة بدنا إياها في محاضرة اليوم جبل ما نتكلم في ال
+
+955
+01:15:47,800 --> 01:15:54,260
+tools يعني إحنا فعليا .. فعليا قدرنا نلخص اليوم ال
+
+956
+01:15:54,260 --> 01:15:58,320
+miling task الخمسة اللي إحنا بدنا إياهم اللي هم
+
+957
+01:16:02,200 --> 01:16:05,940
+classification regression as predictive tasks بعد
+
+958
+01:16:05,940 --> 01:16:10,520
+هيك clustering و association rules وoutlier
+
+959
+01:16:10,520 --> 01:16:14,440
+detection as descriptive tasks بالنسبة لل tools
+
+960
+01:16:14,440 --> 01:16:16,820
+اللي بدنا نشتغل عليها طبعا بإمكانك تشتغل بال data
+
+961
+01:16:16,820 --> 01:16:20,800
+mining أي شغلة programming languages ممكن python و
+
+962
+01:16:20,800 --> 01:16:23,580
+ال R و ال Java و software packages في عندنا ال
+
+963
+01:16:23,580 --> 01:16:26,720
+RapidMiner و ال Weka و ال Orange هذه أساس ال
+
+964
+01:16:26,720 --> 01:16:32,260
+software package احنا بالنسبة لناهنشتغل python و
+
+965
+01:16:32,260 --> 01:16:36,180
+RapidMiner فبدي اياك نزل على جهازك الان نزل على
+
+966
+01:16:36,180 --> 01:16:41,160
+جهازك RapidMiner point 9 RapidMiner studio و ال
+
+967
+01:16:41,160 --> 01:16:48,700
+python بدي تنزللي ال spider Anaconda distribution
+
+968
+01:16:51,730 --> 01:16:56,050
+ما هو عشان انا اريحك من تنزيل المكتبات هاي نزل الـ
+
+969
+01:16:56,050 --> 01:16:58,890
+Spider Anaconda Distribution تبع الـ Python هذه
+
+970
+01:16:58,890 --> 01:17:03,690
+فيها كل ال libraries اللي انت محتاجها، تمام؟ الله
+
+971
+01:17:03,690 --> 01:17:06,390
+عطيكم العافية ونشوفكم ان شاء الله لمحاضرة الجاية
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/oxlQUhGi7Cg_postprocess.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/oxlQUhGi7Cg_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..439d02a5c10ac7b5a86755b4478ffdd77f2ef7de
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/oxlQUhGi7Cg_postprocess.srt
@@ -0,0 +1,1764 @@
+1
+00:00:03,310 --> 00:00:06,250
+السلام عليكم .. طبعا احنا جلنا .. كنا و جفنا هان
+
+2
+00:00:06,250 --> 00:00:09,790
+اللي في قطاعنا التسجيل لأنه تجاوز ال 30 دقيقة و
+
+3
+00:00:09,790 --> 00:00:12,390
+ماقلناش يكون التسجيل كبير بالنسبة لكم أو وقت طويل
+
+4
+00:00:12,390 --> 00:00:16,610
+.. بترتبوا معرفتكم ان شاء الله تعالى، مع أن لو كان
+
+5
+00:00:16,610 --> 00:00:20,990
+متواصل ممكن يكون أفضل، مايبقى عرفتالان هنتكلم عن
+
+6
+00:00:20,990 --> 00:00:27,030
+الـ Appropriate Algorithm قلنا سابقا أن البحث عن
+
+7
+00:00:27,030 --> 00:00:30,510
+ال association rules بيعتمد على شغلتين أساسيتين أو
+
+8
+00:00:30,510 --> 00:00:33,410
+خطواتين أساسيتين أي ألجوريثم مكوّن من خطواتين
+
+9
+00:00:33,410 --> 00:00:40,150
+الخطوة الأولى أن أنا فعليا أدور على كل frequent
+
+10
+00:00:40,150 --> 00:00:41,170
+item set
+
+11
+00:00:44,140 --> 00:00:46,780
+وطبعا عندما أتكلم على frequent يعني أنها تتجاوز ال
+
+12
+00:00:46,780 --> 00:00:49,480
+support ال minimum support اللي معروف عندها او ال
+
+13
+00:00:49,480 --> 00:00:53,340
+threshold الخاص بيه وبعدين اروح اعمل generate ل
+
+14
+00:00:53,340 --> 00:00:57,140
+strong association rules بناء على ال minimum أو ال
+
+15
+00:00:57,140 --> 00:01:00,720
+frequent item sets اللي موجودة عندها وعندما أتكلم
+
+16
+00:01:00,720 --> 00:01:03,380
+على strong association rules يعني أن ال rules يجب
+
+17
+00:01:03,380 --> 00:01:07,930
+أن يحققوا ال minimum support وال minimumconfidence
+
+18
+00:01:07,930 --> 00:01:11,510
+condition هذا شرمالة الـ association role القوي
+
+19
+00:01:11,510 --> 00:01:17,750
+الابريري بيستخدم او يستخدم من أجل الحصول على كل
+
+20
+00:01:17,750 --> 00:01:22,190
+frequent item set تمام it computes the frequent
+
+21
+00:01:22,190 --> 00:01:25,430
+item set in a data set through several iterations
+
+22
+00:01:25,430 --> 00:01:31,830
+من خلال دورات متعددة بيصل اياش ال case iteration
+
+23
+00:01:31,830 --> 00:01:40,050
+compute all the frequent item setالان يا جماعة
+
+24
+00:01:40,050 --> 00:01:43,970
+الخير احنا متفقين ان ال data set او ال attributes
+
+25
+00:01:43,970 --> 00:01:47,370
+او ال transactional data set اللي انا بده اشتغل
+
+26
+00:01:47,370 --> 00:01:54,470
+عليها مكونة of element elements اللي هو عددهم M من
+
+27
+00:01:54,470 --> 00:01:59,950
+I واحد زي ما قلنا ل I M items فهي M من ال items
+
+28
+00:01:59,950 --> 00:02:05,250
+معناته ال K تبعته تتراوحمن الـ 1 to M هذه
+
+29
+00:02:05,250 --> 00:02:09,070
+المجموعات اللي موجودة عندى وبالتالي هي عبارة عدد
+
+30
+00:02:09,070 --> 00:02:12,930
+الـ iteration بعدد ال elements اللي موجودة عندى او
+
+31
+00:02:12,930 --> 00:02:16,010
+عفوا بعدد ال items اللي موجودة عندى في ال data set
+
+32
+00:02:16,010 --> 00:02:20,330
+اللي موجودة هناEach iteration has two steps
+
+33
+00:02:20,330 --> 00:02:24,670
+Candidate generation بتحدد ال candidates و بعدين
+
+34
+00:02:24,670 --> 00:02:27,810
+ال candidates counting and selection بتاخد ال
+
+35
+00:02:27,810 --> 00:02:31,090
+candidate اللي هو المرشح ال element المرشح او ال
+
+36
+00:02:31,090 --> 00:02:35,690
+item 6 المرشحة وبتروح بتعدلها تمام وبناء على العدد
+
+37
+00:02:35,690 --> 00:02:40,890
+بتختارها او مابتختارهاش في
+
+38
+00:02:40,890 --> 00:02:43,010
+المثال اللي موجود عندنا هنا جماعة الخير
+
+39
+00:02:46,520 --> 00:02:51,000
+أنا بأتكلم على ال minimum support with count equal
+
+40
+00:02:51,000 --> 00:02:54,800
+to with count equal to ال minimum support with
+
+41
+00:02:54,800 --> 00:02:59,400
+count equal to with count equal to with count
+
+42
+00:02:59,400 --> 00:02:59,600
+equal to with count equal to with count equal to
+
+43
+00:02:59,600 --> 00:03:00,800
+with count equal to with count equal to with count
+
+44
+00:03:00,800 --> 00:03:01,380
+equal to with count equal to with count equal to
+
+45
+00:03:01,380 --> 00:03:01,720
+with count equal to with count equal to with count
+
+46
+00:03:01,720 --> 00:03:03,220
+equal to with count equal to with count equal to
+
+47
+00:03:03,220 --> 00:03:04,120
+with count equal to with count equal to with count
+
+48
+00:03:04,120 --> 00:03:04,780
+equal to with count equal to with count equal to
+
+49
+00:03:04,780 --> 00:03:05,920
+with count equal to with count equal to with count
+
+50
+00:03:05,920 --> 00:03:08,320
+equal to with count equal to with count equal to
+
+51
+00:03:08,320 --> 00:03:14,250
+with countالـ data set تبعت في الهام لكن لو انا
+
+52
+00:03:14,250 --> 00:03:17,610
+اتيت و اتطلعت في ال database او ال data sets اللي
+
+53
+00:03:17,610 --> 00:03:23,710
+موجودة عندى اقصى شغلة عندى خمس elements او اربع
+
+54
+00:03:23,710 --> 00:03:29,830
+items موجودين في كل transactionهذا يجعلني أتوقف
+
+55
+00:03:29,830 --> 00:03:36,030
+مبكرا لأنه لن يكون لدي اي item set في ال database
+
+56
+00:03:36,030 --> 00:03:40,350
+الموجودة فيها خمس عناصر وبالتالي لا يوجد لدي أي
+
+57
+00:03:40,350 --> 00:03:44,890
+rules تحتوي على خمس عناصر هكذا يبدو بالنسبة لنا
+
+58
+00:03:44,890 --> 00:03:49,190
+تمام، دعنا نرى ماذا سيحدث الآن
+
+59
+00:03:58,360 --> 00:04:04,340
+ماشي الحال خلّيني أنا أوقف التسجيل للحظة عشان أعدل
+
+60
+00:04:04,340 --> 00:04:08,300
+شغلة في ال slide هذه في طريقة عرض ال slide ممكن
+
+61
+00:04:08,300 --> 00:04:23,640
+تكون أريح لإينا في الفهم طيب
+
+62
+00:04:23,640 --> 00:04:26,200
+جماعة الخير أرجو المثال نعرضه بشكل أفضل إن شاء
+
+63
+00:04:26,200 --> 00:04:31,930
+الله تعالىالان كما قلنا سابقا ان ال algorithm كله
+
+64
+00:04:31,930 --> 00:04:35,470
+يبحث عن ال item frequent set في الأول و بعدين
+
+65
+00:04:35,470 --> 00:04:39,490
+بيعمل generate و قلنا ان ال app priori هان في كل
+
+66
+00:04:39,490 --> 00:04:43,230
+step في كل iteration بيشتغل جيش بروح بساوي بيعمل
+
+67
+00:04:43,230 --> 00:04:44,590
+generate ل
+
+68
+00:04:47,090 --> 00:04:50,450
+للـ group بالـ candidates و بعدين بيعدلوا ال
+
+69
+00:04:50,450 --> 00:04:53,550
+elements تبعته و بعدين بيعملوا منه selection فاحنا
+
+70
+00:04:53,550 --> 00:04:56,630
+الآن هذا مع ال algorithm اللي حاسسه الآن معناته
+
+71
+00:04:56,630 --> 00:05:02,930
+حبدأ انا مع شغل بسميها C1 C1 هي عبارة عن ال
+
+72
+00:05:02,930 --> 00:05:10,210
+candidates of item set with one element اللي هم I1
+
+73
+00:05:10,210 --> 00:05:15,770
+I2 I3 I4
+
+74
+00:05:17,700 --> 00:05:21,560
+I5 مش هم ال elements اللي عندي هاي هم خمسة هدول و
+
+75
+00:05:21,560 --> 00:05:27,840
+بدى أروح أحسب ال support لكل واحدة فيهم نيجي لل I1
+
+76
+00:05:27,840 --> 00:05:31,300
+طبعا انا الآن هيك المفروض انا اساوي ارسم رسمة زي
+
+77
+00:05:31,300 --> 00:05:36,260
+هذه اقول هي C1 ال candidates تعوتي بنعملهم
+
+78
+00:05:36,260 --> 00:05:44,380
+generation generate الان I1 I2
+
+79
+00:05:49,900 --> 00:05:57,880
+I3 I4 I5 الخطوة اللي بعد هيك انا بدروح احسب لهم
+
+80
+00:05:57,880 --> 00:06:03,080
+جماعة الخير ال support لما انا بده احسب ال support
+
+81
+00:06:03,080 --> 00:06:09,900
+لل C2 لل C1 يعني ما زلت candidate واحد الان I1
+
+82
+00:06:09,900 --> 00:06:14,460
+جديش هي واحدة تلاتة
+
+83
+00:06:14,460 --> 00:06:21,050
+اربعة خمسة ستةبقدر اكتبهم مع بعض انا هاي ستة
+
+84
+00:06:21,050 --> 00:06:26,490
+support لان
+
+85
+00:06:26,490 --> 00:06:34,930
+الخطوة التانية هي عبارة هاي I1 equal 6 I2 واحدة
+
+86
+00:06:34,930 --> 00:06:45,510
+اتنين تلاتة اربعة خمسة ستة سبعة I2 equal 7 I3
+
+87
+00:06:48,370 --> 00:06:55,430
+1,2,3,4,5,6 I4
+
+88
+00:06:55,430 --> 00:07:09,550
+1,2,3,4,5,6 I5 1,2,3,4,5,6 I5 I5 I5
+
+89
+00:07:09,550 --> 00:07:12,590
+I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5
+
+90
+00:07:12,590 --> 00:07:12,790
+I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5
+
+91
+00:07:17,500 --> 00:07:27,780
+I1 I2 I3 I4 I5 I5
+
+92
+00:07:27,780 --> 00:07:27,800
+I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5
+
+93
+00:07:27,800 --> 00:07:28,640
+I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5
+
+94
+00:07:28,640 --> 00:07:28,700
+I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5
+
+95
+00:07:28,700 --> 00:07:36,340
+I5 I5 I5 I5الخطوة الأولى رحت عملت لهم generation و
+
+96
+00:07:36,340 --> 00:07:40,740
+حسبت ال candidate وهي روحت أخدتهم لأن ال minimum
+
+97
+00:07:40,740 --> 00:07:45,240
+support بتحقق ال minimum support اللي موجودة عندي
+
+98
+00:07:45,240 --> 00:07:49,860
+تمام الخطوة التالية أنا الآن خلصت من ال candidate
+
+99
+00:07:49,860 --> 00:07:54,180
+C1 بدأ أروح أعمل candidate من C2 و لازم تكون ال
+
+100
+00:07:54,180 --> 00:08:00,940
+element هذا موجود عندي يعني أنا بدأ أقول I1 I2
+
+101
+00:08:02,300 --> 00:08:09,700
+لازم يكون موجود في ال database I1 I3
+
+102
+00:08:09,700 --> 00:08:23,920
+I1 I4 I1 I5 هد ايش هدول ال candidates of C2 لان هم
+
+103
+00:08:23,920 --> 00:08:29,460
+مجموعات من اتنين بعد هيك ببدأ ب I2أكتب I1 لأ
+
+104
+00:08:29,460 --> 00:08:36,720
+already هي موجودة عندي انا كتبتها I2 و I3 I3 I2 و
+
+105
+00:08:36,720 --> 00:08:53,680
+I4 I2 و I5 as groups بعد هي I3 و I4 I3
+
+106
+00:08:53,680 --> 00:08:55,020
+و I5
+
+107
+00:08:58,450 --> 00:09:06,210
+و بعد هي I4 و I5 و هك انا بأضمن ان انا جيبت كل ال
+
+108
+00:09:06,210 --> 00:09:11,370
+items اللي شغالة اللي موجودة بال element 2 ليش في
+
+109
+00:09:11,370 --> 00:09:17,150
+جامعة الخير انا ماروحتش كتابة I2 و I1 كمان مرة لان
+
+110
+00:09:17,150 --> 00:09:20,870
+حسب المجموعات او ما درسنا من discrete mathematics
+
+111
+00:09:20,870 --> 00:09:26,810
+انه فعليا ترتيب العناصر كمجموعة A و B
+
+112
+00:09:32,860 --> 00:09:35,720
+بالتالي ترتيب العناصر في المجموع لايعني شيء و
+
+113
+00:09:35,720 --> 00:09:39,200
+تكرار العنصر في المجموع لايعني شيء فانا ضمانة هيك
+
+114
+00:09:39,200 --> 00:09:42,800
+بأضمن ان انا جيبت كل ال elements و مافوتش ولا واحد
+
+115
+00:09:42,800 --> 00:09:46,440
+منهم و بنفس الكلام بروح بحسب ال support لكل واحد
+
+116
+00:09:46,440 --> 00:09:51,950
+فيهمأي واحد مع اي اتنين مع اتنين مع اتنين مع اتنين
+
+117
+00:09:51,950 --> 00:10:00,630
+مع اتنين مع اتنين مع اتنين مع اتنين مع اتنين مع
+
+118
+00:10:00,630 --> 00:10:03,050
+اتنين مع اتنين مع اتنين مع اتنين مع اتنين مع اتنين
+
+119
+00:10:03,050 --> 00:10:03,210
+مع اتنين مع اتنين مع اتنين مع اتنين مع اتنين مع
+
+120
+00:10:03,210 --> 00:10:03,730
+اتنين مع اتنين مع اتنين مع اتنين مع اتنين مع اتنين
+
+121
+00:10:03,730 --> 00:10:05,750
+مع اتنين مع اتنين مع اتنين مع اتنين مع اتنين مع
+
+122
+00:10:05,750 --> 00:10:09,490
+مع اتنين مع اتنين مع اتنين مع اتنين مع اتنين
+
+123
+00:10:09,490 --> 00:10:15,050
+مع اتنين مع اتبتحتوي فقط على العناصر اللي ال
+
+124
+00:10:15,050 --> 00:10:18,710
+support تبعتها أكبر من اتنين وبالتالي هي صغرة
+
+125
+00:10:18,710 --> 00:10:24,510
+المجموعة طيب الخطوة اللي بعد هيك بروح أنشئ انا كل
+
+126
+00:10:24,510 --> 00:10:28,770
+المجموعات اللي مبنية على تلت عناصر كل المجموعات
+
+127
+00:10:28,770 --> 00:10:32,910
+اللي مبنية على تلت عناصر من اين؟ من خلال ال data
+
+128
+00:10:32,910 --> 00:10:38,920
+set اللي موجودة عندها طيب سؤال مهم جداI1 I2 I3 I4
+
+129
+00:10:38,920 --> 00:10:42,260
+I5 لو افترضنا انه في عنده I6 وهي مش مبينة اروح
+
+130
+00:10:42,260 --> 00:10:45,460
+استخدمها لأ ليش لأن هو كل ال subset لازم يكون
+
+131
+00:10:45,460 --> 00:10:49,380
+frequent و بما انه I6 مش في الحسبة ما هي مرض فانا
+
+132
+00:10:49,380 --> 00:10:53,120
+بادر اجيب ال item تلاتة اللي من تلت عناصر جدش هم
+
+133
+00:10:53,120 --> 00:10:57,540
+جامعة الخيار هيكونوا خليني بس انا ارجع للخطوة هاي
+
+134
+00:10:57,540 --> 00:11:05,740
+من تلت عناصر في عندي I1 I2 I3
+
+135
+00:11:07,470 --> 00:11:19,790
+مع I1 و I2 و I4 I1 و I2 و I5 هدول يا جماعة الخير
+
+136
+00:11:19,790 --> 00:11:28,130
+مين فيهم ينتمي لل data set هذه هي في أول سطر و I2
+
+137
+00:11:28,130 --> 00:11:38,670
+و I4 و هذه ينتمي لأول سطرI1, I2 و I3 كانت تتم
+
+138
+00:11:38,670 --> 00:11:44,250
+الأول سطر لآخر سطر طيب الان لو انا روحت و قلت I2
+
+139
+00:11:44,250 --> 00:11:52,450
+I3 I4 لها
+
+140
+00:11:52,450 --> 00:11:59,230
+وجود في ال data set اللي موجود عندى مالهاش وجود
+
+141
+00:12:03,300 --> 00:12:11,400
+I2 I3 I5 I5
+
+142
+00:12:11,400 --> 00:12:11,620
+I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5
+
+143
+00:12:11,620 --> 00:12:11,820
+I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5
+
+144
+00:12:11,820 --> 00:12:12,160
+I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5
+
+145
+00:12:12,160 --> 00:12:13,320
+I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5 I5
+
+146
+00:12:43,780 --> 00:12:46,920
+طيب جمعة الخير الآن بدنا ناخد اللي نعمل candidate
+
+147
+00:12:46,920 --> 00:12:53,300
+ل ال C3 الألمة بتكلم على C3 ايش أنا بتكلم .. ايش
+
+148
+00:12:53,300 --> 00:12:55,760
+.. ايش صفات المجموعات هاي؟ هي عبارة عن كل
+
+149
+00:12:55,760 --> 00:12:58,960
+المجموعات اللي فيها تلت عناصر بس بشرط ان ال
+
+150
+00:12:58,960 --> 00:13:02,720
+element تبعتهم يكون frequent item frequent item
+
+151
+00:13:02,720 --> 00:13:07,540
+ممتاز طيب الألمة أنا بدأش اقول على سبيل المثال بدأ
+
+152
+00:13:07,540 --> 00:13:09,440
+بدأ اصنف I1
+
+153
+00:13:11,420 --> 00:13:18,940
+و I2 و I3 لأن هذه المجموعة عشان انا اخدها لازم
+
+154
+00:13:18,940 --> 00:13:25,500
+لازم لازم ال I1 و I2 و I3 تكون frequent يعني كل
+
+155
+00:13:25,500 --> 00:13:29,640
+subset منها تكون frequent يعني I1 و I2 مع بعض و I2
+
+156
+00:13:29,640 --> 00:13:36,420
+و I3 و I1 و I3 مع بعض لان عفوا لما انا بدي اجي
+
+157
+00:13:36,420 --> 00:13:41,560
+اطلع لهدول مع بعض هل هدولة frequentI1 و I2 عادية
+
+158
+00:13:41,560 --> 00:13:51,160
+I1 و I3 عادية I2 و I3 عادية I1 و
+
+159
+00:13:51,160 --> 00:13:55,020
+I4 عادية
+
+160
+00:13:55,020 --> 00:13:59,940
+I1 و I2 عادية I1 و I4 عادية I1 و I4 عادية I1 و I4
+
+161
+00:13:59,940 --> 00:14:04,260
+عادية I1 و I4 عادية I1 و I4 عادية I1 و I4 عادية I1
+
+162
+00:14:04,260 --> 00:14:09,300
+و I4 عادية I1 و I4 عادية I1 و I4 عادية I1 و I4
+
+163
+00:14:09,300 --> 00:14:09,460
+عادية I1 و I4 عادية I1 و I4 عادية I1 و I4 عادية I1
+
+164
+00:14:09,460 --> 00:14:09,480
+و I4 عادية I1 و I4 عادية I1 و I4 عادية I1 و I4
+
+165
+00:14:09,480 --> 00:14:09,500
+عادية I1 و I4 عادية I1 و I4 عادية I1 و I4 عادية I1
+
+166
+00:14:09,500 --> 00:14:13,870
+و I4 عادية I1 و I4 عادية I1 و I4 عاديةI5 I1 I2
+
+167
+00:14:13,870 --> 00:14:17,930
+frequent I1 I5 I1 I5 هي الموجودة بيبقى الـ 2 و 5
+
+168
+00:14:17,930 --> 00:14:21,550
+I2 I5 frequent معناته okay accepted بنيجي للي
+
+169
+00:14:21,550 --> 00:14:27,130
+بعديها I2
+
+170
+00:14:27,130 --> 00:14:34,530
+I3 I4 I2
+
+171
+00:14:34,530 --> 00:14:36,650
+I4 not frequent بتسقط
+
+172
+00:14:39,050 --> 00:14:46,530
+I2 I3 I5 I3
+
+173
+00:14:46,530 --> 00:14:52,830
+و I5 ليسوا مستخدمين I2 و I5 مستخدمين I3 و I5 ليسوا
+
+174
+00:14:52,830 --> 00:14:57,490
+مستخدمين I3
+
+175
+00:14:57,490 --> 00:15:00,430
+I4 I5
+
+176
+00:15:03,220 --> 00:15:06,240
+أي تلاتة او اي اربعة او اي تلاتة او اي تلاتة او اي
+
+177
+00:15:06,240 --> 00:15:08,280
+تلاتة او اي تلاتة او اي تلاتة او اي تلاتة او اي
+
+178
+00:15:08,280 --> 00:15:08,760
+تلاتة او اي تلاتة او اي تلاتة او اي تلاتة او اي
+
+179
+00:15:08,760 --> 00:15:11,520
+تلاتة او اي تلاتة او اي تلاتة او اي تلاتة او اي
+
+180
+00:15:11,520 --> 00:15:13,740
+تلاتة او اي تلاتة او اي تلاتة او اي تلاتة او اي
+
+181
+00:15:13,740 --> 00:15:17,900
+تلاتة او اي تلاتة او اي تلاتة او اي تلاتة او اي
+
+182
+00:15:17,900 --> 00:15:24,080
+تلاتة او اي تلاتة او اي تلاتة او اي تلاتة او اI1
+
+183
+00:15:24,080 --> 00:15:27,640
+I2 I5 هدول ال candidates بروح بحسب اللهم ال
+
+184
+00:15:27,640 --> 00:15:31,080
+support كم مرة ظهروا فال data set اللي موجودة مع
+
+185
+00:15:31,080 --> 00:15:39,120
+بعض ال support I1 I2 I5 I مرة و I مرة تمام معناته
+
+186
+00:15:39,120 --> 00:15:43,560
+هذه مرتين مرتين
+
+187
+00:15:43,560 --> 00:15:46,820
+و
+
+188
+00:15:46,820 --> 00:15:53,170
+I1 I3 I1 I2 I3هي واحدة هيتنتين معناته هذا كمان
+
+189
+00:15:53,170 --> 00:15:57,150
+مرتين ممتاز معناته باخد من هدول انا ال candidates
+
+190
+00:15:57,150 --> 00:16:03,610
+او ال .. ال .. اللي حققوا ال minimum support عشان
+
+191
+00:16:03,610 --> 00:16:06,230
+اروح على اربعة هل هاروح على اربعة انا فعليا يا
+
+192
+00:16:06,230 --> 00:16:12,330
+جماعة الخير على items من اربع عناصر لأ لان انا
+
+193
+00:16:12,330 --> 00:16:16,810
+فعليا ماعنديش وبالتالي انا هنا وقفتلأن انا ال
+
+194
+00:16:16,810 --> 00:16:20,050
+maximum تبعتي من اربع عناصر خلنا لو انا الاصل اللي
+
+195
+00:16:20,050 --> 00:16:25,170
+انا بدي اروح فيها فبدي اخد من هنا يعني انا هاخد ال
+
+196
+00:16:25,170 --> 00:16:28,970
+association من هنا I1 عادة انا باخد ال association
+
+197
+00:16:28,970 --> 00:16:35,210
+من هنا برجعش لورا I1 I2 I3 I4 بعمل union ما بينهم
+
+198
+00:16:35,210 --> 00:16:40,950
+هيه فش غير هيك عفوا I5 جديش ال support لإلها
+
+199
+00:16:44,580 --> 00:16:49,620
+وحد تسجل في غيرها لا مفيش غيرها لأن هذا هو العبارة
+
+200
+00:16:49,620 --> 00:16:52,220
+عن ال association انا باخد منها زي ما انا كنت اخد
+
+201
+00:16:52,220 --> 00:16:56,780
+منها الآن اخدت I1 و I2 و حطيت لهم I3 I1 و I2 و I5
+
+202
+00:16:56,780 --> 00:17:03,960
+خلصنا I2 و I3 حطيت لهم I4 اخدت I2 و I3 و حطيت لهم
+
+203
+00:17:03,960 --> 00:17:11,500
+I4 I2 و I3 و I5 و هكذاعن كل الـ creation تبعتي
+
+204
+00:17:11,500 --> 00:17:16,780
+عندي هتكون من الـ element اللي موجود هنا ففعليا في
+
+205
+00:17:16,780 --> 00:17:19,200
+ال candidate generation هو بيبدأ من ال k equal
+
+206
+00:17:19,200 --> 00:17:25,540
+واحد وبياخد كل ال item set من ال one item set تمام
+
+207
+00:17:25,540 --> 00:17:29,660
+و بروح بجيب ليهم بعد هيك بيبدأ يروح يجمع العناصر
+
+208
+00:17:29,660 --> 00:17:35,180
+بعد ما يروح يحسب ال support لكل واحدة فيهم for k
+
+209
+00:17:35,180 --> 00:17:43,050
+equal k نقص اتنينjoin of الـ k ناقص واحد with
+
+210
+00:17:43,050 --> 00:17:49,830
+itself نقل العناصر هدول مع بعضهم if ال both a لحد
+
+211
+00:17:49,830 --> 00:17:56,030
+اك ناقص واحد are in ال k لو كان هدولة موجودين في
+
+212
+00:17:56,030 --> 00:18:01,790
+ال list اللي جابل ال list of candidates اللي حققوا
+
+213
+00:18:01,790 --> 00:18:05,230
+ال minimum support روح ضيفلي عليهم ال k فقط طبعا
+
+214
+00:18:05,230 --> 00:18:08,350
+مين المختلفة جامعة الخير انا فعليا هايم هدول
+
+215
+00:18:08,350 --> 00:18:14,320
+كلاتهم موجوداتمن A1 ل A .. من A ل K نقص واحد وانا
+
+216
+00:18:14,320 --> 00:18:18,160
+انضاف عند مين في ال elements في المجموعة ال K فانا
+
+217
+00:18:18,160 --> 00:18:23,300
+اضاف ال .. ايش ال K على المجموعة اللي موجودة عندي
+
+218
+00:18:23,300 --> 00:18:27,040
+وبهيكد انا ال algorithm بيشتغل و بجيبليها بعد هيكد
+
+219
+00:18:27,040 --> 00:18:29,820
+اللي .. اللي ممكن يلزم ال prone set ان انا فعليا
+
+220
+00:18:29,820 --> 00:18:35,840
+اروح ادور على ال non frequent item فبروح باخد ال K
+
+221
+00:18:35,840 --> 00:18:40,830
+نقص واحد اللي هي ال L تبعتي هايو بروح بحسب ال
+
+222
+00:18:40,830 --> 00:18:44,110
+support لإيه لهم عشان اعمل drop لمن؟ لل element
+
+223
+00:18:44,110 --> 00:18:47,810
+اللي
+
+224
+00:18:47,810 --> 00:18:53,570
+موجودة عندي اللي هي بلات حقق من ما بصبر ال
+
+225
+00:18:53,570 --> 00:18:55,730
+pseudocode بياخد ck
+
+226
+00:18:58,390 --> 00:19:03,490
+K item set frequent item set اللي هي ال list اللي
+
+227
+00:19:03,490 --> 00:19:06,830
+موجودة عندى list of frequent item set او size K
+
+228
+00:19:06,830 --> 00:19:15,150
+بيبدأ من L1 for K equal 1 ال K لا تساوي 5 K plus
+
+229
+00:19:15,150 --> 00:19:21,950
+plus begin ال candidate CK زائد واحد candidate
+
+230
+00:19:21,950 --> 00:19:27,060
+generate ال Kطبعا انا انا زي ما اقول من هنا انا
+
+231
+00:19:27,060 --> 00:19:29,840
+بحب اعمل generate for each transaction تيه ال
+
+232
+00:19:29,840 --> 00:19:33,480
+database database to increment the count of
+
+233
+00:19:33,480 --> 00:19:36,840
+candidates اللي انا هدول ال candidates هدول انا
+
+234
+00:19:36,840 --> 00:19:43,020
+بحسب ال minimum support و ال candidates with ال
+
+235
+00:19:43,020 --> 00:19:46,280
+minimum support اللي موجودين عندها و بنتهيأ لحق و
+
+236
+00:19:46,280 --> 00:19:50,020
+في الآخر ايش بروح بيساوي بيعمل union ل ال case
+
+237
+00:19:50,020 --> 00:19:54,660
+اللي موجودة يعنيطبعاً يا جماعة الخير لازم احنا
+
+238
+00:19:54,660 --> 00:19:59,300
+نأكد على نقطة مهمة جدا انه ال .. طبعا ال code او
+
+239
+00:19:59,300 --> 00:20:02,480
+حفظ ال code هذا مش .. مش مطلوب انه بقدر ما انا
+
+240
+00:20:02,480 --> 00:20:06,960
+مطلوب ان انا فهمته من خلال الخطوات وهي ال .. ال بي
+
+241
+00:20:06,960 --> 00:20:13,880
+سيدو code اللي موجود عندى كذلك ال .. ماما صلي علي
+
+242
+00:20:13,880 --> 00:20:18,760
+سيدنا محمد .. مش .. لازم ابدأ أكد على نقطة هان انه
+
+243
+00:20:18,760 --> 00:20:19,900
+انا فعليا
+
+244
+00:20:22,210 --> 00:20:25,910
+حصولي على ال frequent item set لا يعني حصولي على
+
+245
+00:20:25,910 --> 00:20:28,570
+ال association rules انا في الآخر اللي عايش وصلت
+
+246
+00:20:28,570 --> 00:20:33,050
+هنا ووصلت هايه ال frequent item set اللي موجودة من
+
+247
+00:20:33,050 --> 00:20:38,170
+عندي ال تلاتة الخطوة اللي بعد هيك اللي بعد هيك ان
+
+248
+00:20:38,170 --> 00:20:43,930
+انا بدي اروح انشئ
+
+249
+00:20:43,930 --> 00:20:47,790
+frequent item set بدي اروح انشئ association rules
+
+250
+00:20:48,800 --> 00:20:51,100
+معناته ان انا لازم ان انا عندى خطوة ان اروح انش ال
+
+251
+00:20:51,100 --> 00:20:55,280
+association ال implication هذا كيف احصل عليها for
+
+252
+00:20:55,280 --> 00:20:59,820
+each frequent item setلكل مجموعة من ال item set
+
+253
+00:20:59,820 --> 00:21:07,540
+اللي حصلتها for each non-proper non-empty set A
+
+254
+00:21:07,540 --> 00:21:13,820
+المفروض ان ال B تكون من المكملات ال X والتقاطع
+
+255
+00:21:13,820 --> 00:21:17,460
+بينهم Phi بين ال A والB ال association rule بده
+
+256
+00:21:17,460 --> 00:21:19,680
+ينبنى بالشكل هذا
+
+257
+00:21:22,060 --> 00:21:28,180
+طيب الان انا جيت هنا هذه العناصر اللي موجودة عندى
+
+258
+00:21:28,180 --> 00:21:34,280
+انا مين ايش اللي عندى العناصر I1
+
+259
+00:21:34,280 --> 00:21:43,560
+I2 I3 I5 هدولة هم ال frequent items I4 مش frequent
+
+260
+00:21:43,560 --> 00:21:47,180
+وبالتالي هيسقط من كل حسبة تماما طيب ايش اللي انا
+
+261
+00:21:47,180 --> 00:22:01,510
+باجب اقول I1 ل I2هك اللي بده يصير I1 إلى I3 I1
+
+262
+00:22:01,510 --> 00:22:13,730
+I5 بعد هيك I1 إلى I2 و I3 مع بعضهذه كل الـ
+
+263
+00:22:13,730 --> 00:22:16,690
+association rules اللي ممكن تكون عندي هان ارتباط
+
+264
+00:22:16,690 --> 00:22:23,750
+عنصر مع مجموعة او مع مجموعة مع عنصر و هان ببدأ ايه
+
+265
+00:22:23,750 --> 00:22:32,290
+و بروح بقى احسب انا لكل واحدة فيهم جداش ال support
+
+266
+00:22:32,290 --> 00:22:36,490
+و ال .. طيب خلينا نشوف المثال اللي موجود عندنا هان
+
+267
+00:22:37,740 --> 00:22:42,080
+لما انا بنقول هاي ال item set اللي موجودة عندى في
+
+268
+00:22:42,080 --> 00:22:46,000
+ال data set ده افترض ان هاي كل items اللي عندى
+
+269
+00:22:46,000 --> 00:22:48,740
+هاني frequent لأنه فعليا واحد و اتنين و تلاتة
+
+270
+00:22:48,740 --> 00:22:52,960
+عبارة عن frequent items و هم صفوا معايا للاخر فأي
+
+271
+00:22:52,960 --> 00:22:56,400
+subset هتكون موجودة لو انا افترضت ان هدولة كلهم
+
+272
+00:22:56,400 --> 00:22:58,800
+بيحققوا ال minimum support دلوقت دوري افحص ال
+
+273
+00:22:58,800 --> 00:23:04,860
+confidenceالترانزكشن الأول قيمته كم يا شباب ال
+
+274
+00:23:04,860 --> 00:23:12,740
+confidence تبعته احنا قلنا الواحد اتنين
+
+275
+00:23:12,740 --> 00:23:18,980
+تلاتة اربعة هذه قيمة ال support تبعت ال a و ال b
+
+276
+00:23:20,300 --> 00:23:25,820
+أربعة على تسعة، لا أريد أن أكتب التسعة وهنا على
+
+277
+00:23:25,820 --> 00:23:30,340
+الواحد، واحد اتنين تلاتة أربعة خمسة ستة أربعة على
+
+278
+00:23:30,340 --> 00:23:35,540
+ستة أربعة على ستة تجاوزت الخمسة الخمسة وخمسين في
+
+279
+00:23:35,540 --> 00:23:40,660
+المية معناته هذا ال rule عبارة عن strong rule أخد
+
+280
+00:23:40,660 --> 00:23:47,980
+على سبيل المثال ال rule الموجود عندهااو اي واحد او
+
+281
+00:23:47,980 --> 00:23:52,120
+اي اتنين او اي تلاتة ك support هي واحد هي اتنين
+
+282
+00:23:52,120 --> 00:24:00,100
+ممتاز اتنين على ال frequent التابعة للتنين واحدة
+
+283
+00:24:00,100 --> 00:24:06,160
+تنتين تلاتة اربعة خمسة ستة سبعة اتنين على سبعة is
+
+284
+00:24:06,160 --> 00:24:08,020
+not a strong rule وهكذا
+
+285
+00:24:14,930 --> 00:24:17,730
+هو بتتم الحسبة معايا في كل ال rules اللي موجودة
+
+286
+00:24:17,730 --> 00:24:21,530
+عندي هان وانا بقرر بناء عيني كذلك لو انا افترض ان
+
+287
+00:24:21,530 --> 00:24:26,410
+هي عندي هان مجموعة من ال rules ال minimum support
+
+288
+00:24:26,410 --> 00:24:30,350
+تبعتي اتنين وفي عندي ال minimum confidence خمسين
+
+289
+00:24:30,350 --> 00:24:33,350
+في المية وبدأ اعمل نفس الحسبة وليشوف اللي ال
+
+290
+00:24:33,350 --> 00:24:39,330
+transaction هذا مين فيهم strong ومين فيهم منحقق
+
+291
+00:24:39,330 --> 00:24:44,070
+ال minimum support يعني مين منهم strong ومين لأالـ
+
+292
+00:24:44,070 --> 00:24:48,710
+mean هذا ال support تبعت هذا الأول واحد اتنين
+
+293
+00:24:48,710 --> 00:24:57,090
+تلاتة هي واحد اتنين اتنين على a و b واحد اتنين
+
+294
+00:24:57,090 --> 00:25:02,690
+تلاتة اربعة اربعة خمسين في المية okay accepted
+
+295
+00:25:02,690 --> 00:25:11,250
+ناخد هذا على سبيل المثال برضه نفس الكلام اتنين على
+
+296
+00:25:11,250 --> 00:25:16,630
+ال aالإي واحد اتنين اتنين على اتنين معناته مية في
+
+297
+00:25:16,630 --> 00:25:21,530
+المية هنا كان خمسين في المية خمسين في المية هنا
+
+298
+00:25:21,530 --> 00:25:27,610
+مية في المية فهو accepted تمام بينما ناخد على سبيل
+
+299
+00:25:27,610 --> 00:25:38,670
+المثال هذا2 على ال بيز 1 2 3 4 5 6 7 2 على 7 اقل
+
+300
+00:25:38,670 --> 00:25:44,150
+من 50% rejected وبالتالي انا عندى هاي مجموعة ال
+
+301
+00:25:44,150 --> 00:25:47,410
+confidence انا حسبتهم الشكل هذا لكل واحد فيهم
+
+302
+00:25:47,410 --> 00:25:54,850
+وبالتالي بقدر اقول ان هدول qualified بينما
+
+303
+00:25:54,850 --> 00:26:00,400
+هدول not qualified roles يعني هدول رول قويةممكن
+
+304
+00:26:00,400 --> 00:26:05,720
+اعتمد عليها بينما هذه ليست قوية طبعا هذا كله
+
+305
+00:26:05,720 --> 00:26:10,080
+بتنبعد الحسبة ال association rules طيب نفس الكلام
+
+306
+00:26:10,080 --> 00:26:13,060
+لو انا بدى اشتغل .. بتشوف .. بنشوف المثال هذا
+
+307
+00:26:13,060 --> 00:26:17,840
+لوحدكم عشان احاول اكسب من الوقت الفكرة فيه بقولك
+
+308
+00:26:17,840 --> 00:26:21,520
+انه انا في عندى مجموعة هي عبارة عن frequent هذه
+
+309
+00:26:21,520 --> 00:26:26,240
+المجموعة frequent وال support with support خمسين
+
+310
+00:26:26,240 --> 00:26:31,240
+في المينةتمام؟ لأنه في الأخر عدد بيجي بعد خير ال
+
+311
+00:26:31,240 --> 00:26:33,700
+program empty subset هدولة ال subset وهي ال
+
+312
+00:26:33,700 --> 00:26:38,340
+support تبعت كل واحدة فيهم الان بيقولك find the
+
+313
+00:26:38,340 --> 00:26:42,680
+confidence of ال rule هذاالان ال rules اللي موجود
+
+314
+00:26:42,680 --> 00:26:45,240
+عندى هن هي عبارة عن ال support تبعته كدهش يا جماعة
+
+315
+00:26:45,240 --> 00:26:48,740
+الخير واحد اتنين تلاتة احنا قولنا اي subset منها
+
+316
+00:26:48,740 --> 00:26:51,660
+هي عبارة عن subset هتكون frequent اي بما ان هذا
+
+317
+00:26:51,660 --> 00:26:54,880
+frequent فاي subset هتكون frequent ممتاز طب ال
+
+318
+00:26:54,880 --> 00:26:59,200
+frequent اللي عندى هن عبارة عن كدهش عبارة عن خمسين
+
+319
+00:26:59,200 --> 00:27:03,100
+صح ال support تبعته خمسين هيا خمسين في المية اقولك
+
+320
+00:27:03,100 --> 00:27:06,260
+طيب
+
+321
+00:27:06,260 --> 00:27:10,470
+معناته هى خمسين في الميةاللي هم الـ A اتنين و
+
+322
+00:27:10,470 --> 00:27:13,490
+تلاتة و أربع مع بعض على اتنين و تلاتة الاتنين و
+
+323
+00:27:13,490 --> 00:27:18,830
+التلاتة هي ال support تبعتهم جداش هيها خمسين في
+
+324
+00:27:18,830 --> 00:27:23,410
+المية خمسين في المية على خمسين في المية معناته مية
+
+325
+00:27:23,410 --> 00:27:26,790
+في المية تح؟ وبالتالي هي حسبة ال confidence
+
+326
+00:27:26,790 --> 00:27:31,610
+الموجودة وكملوا البثال لأن المثال بسيط مش محتاج ال
+
+327
+00:27:31,610 --> 00:27:35,610
+a priori drawbacks اللي في عند ال major drawbacks
+
+328
+00:27:35,610 --> 00:27:41,470
+في ال a priori بحتاجالـ computational عالي طبعاً
+
+329
+00:27:41,470 --> 00:27:44,790
+لأنه انا في عندى multiple scan لل data set بضلني
+
+330
+00:27:44,790 --> 00:27:50,150
+ارجع لل data set عشان دائما افحص اعدل ال support
+
+331
+00:27:50,150 --> 00:27:53,330
+المعنى هو ان انا في عندى huge number of candidates
+
+332
+00:27:53,330 --> 00:28:01,990
+كذلك لازم تندس workload العمل ممل لانه دائما بده
+
+333
+00:28:01,990 --> 00:28:06,310
+يعد ال support مرة و تنتين و تلاتة أو عشرة للموجود
+
+334
+00:28:06,310 --> 00:28:13,630
+كيف ممكن احنا نحسنمن أداء الـ .. من
+
+335
+00:28:13,630 --> 00:28:19,290
+أداء الـ priority improving بشكل عام لو أنا قللت
+
+336
+00:28:19,290 --> 00:28:26,350
+عدد المرات للـ scanning تبع ال databaseبحس ان اجسم
+
+337
+00:28:26,350 --> 00:28:33,510
+ال database ل 2 partitions على سبيل المثال اشتغل
+
+338
+00:28:33,510 --> 00:28:38,090
+مع ال partitions من الاتنين اللي موجودين عندها اقل
+
+339
+00:28:38,090 --> 00:28:43,170
+العدد ال candidates اللي موجودين عندى
+
+340
+00:28:45,440 --> 00:28:49,160
+Facilitate support counting of candidates انه كيف
+
+341
+00:28:49,160 --> 00:28:54,160
+ممكن احسن او اشوف طريقة احتفظ فيها بالعدد تبعت ال
+
+342
+00:28:54,160 --> 00:29:00,080
+candidates او اروح استخدم تكنيقى يسرع من العملية
+
+343
+00:29:00,080 --> 00:29:04,860
+كلها و باعتماد على سبيل مثال على ال processing او
+
+344
+00:29:04,860 --> 00:29:05,920
+ال parallel computing
+
+345
+00:29:09,970 --> 00:29:14,350
+لو انا اللي بدي اجسم ال database تبعتي ل two
+
+346
+00:29:14,350 --> 00:29:20,070
+partitions و امر عليهم فقط مرتين فقط مرتين an item
+
+347
+00:29:20,070 --> 00:29:24,390
+set that potentially frequent in the database must
+
+348
+00:29:24,390 --> 00:29:28,450
+frequent at least one of the partitions يعني اذا
+
+349
+00:29:28,450 --> 00:29:31,390
+جالك الله اذا انا باجسم ال database تبعتي ل two
+
+350
+00:29:31,390 --> 00:29:36,750
+partitions و بمرها ال frequent اللي هنا هي
+
+351
+00:29:36,750 --> 00:29:37,450
+frequent هنا
+
+352
+00:29:43,250 --> 00:29:50,150
+هذا مبدأه في الحسبة اللي موجودة عندها ال any items
+
+353
+00:29:50,150 --> 00:29:54,590
+that potentially frequent in database عفوا ال
+
+354
+00:29:54,590 --> 00:29:57,010
+frequently في ال database فهي هتكون frequent في
+
+355
+00:29:57,010 --> 00:30:02,110
+واحدة منهم وبالتالي
+
+356
+00:30:02,110 --> 00:30:06,490
+خلاص انا يعني مروري لأول لأول مرة انا مريت فعشان
+
+357
+00:30:06,490 --> 00:30:09,090
+اتعرف على ال frequent items فهيكون عندي دايما
+
+358
+00:30:09,090 --> 00:30:13,650
+frequent itemsالسكان الأول هو partition the
+
+359
+00:30:13,650 --> 00:30:16,850
+database partition database and find local
+
+360
+00:30:16,850 --> 00:30:19,870
+frequent patterns في ال partition الأول
+
+361
+00:30:19,870 --> 00:30:23,610
+consolidate global frequent patterns وشوف ايش ال
+
+362
+00:30:23,610 --> 00:30:26,510
+global patterns اللي موجودة في التنتين عشان هدول
+
+363
+00:30:26,510 --> 00:30:33,670
+هم اللي هيكونوا العناصر اللي موجودين عندنا reduce
+
+364
+00:30:33,670 --> 00:30:38,070
+the number of candidates ممكن انا اشتغل
+
+365
+00:30:41,590 --> 00:30:47,930
+الـ hashing bucket count الـ item k .. k item set
+
+366
+00:30:47,930 --> 00:30:56,270
+و ان انا اروح ادور على ال .. ال .. اقل من العدد
+
+367
+00:30:56,270 --> 00:30:59,510
+المطلوب انا اروح ا .. ا .. ا .. اسيبهم مابديش
+
+368
+00:30:59,510 --> 00:31:07,670
+اياهم عفوا
+
+369
+00:31:07,670 --> 00:31:10,930
+يا شباب ال .. ال .. الان فكرة ال .. ال hash bucket
+
+370
+00:31:10,930 --> 00:31:16,460
+هانان انا بدي اخد ال data تبعتي حزمة هاي ال
+
+371
+00:31:16,460 --> 00:31:19,920
+candidates اللي موجودين عندي a والb والc والd ال
+
+372
+00:31:19,920 --> 00:31:23,320
+hash entries تبعتي عبارة عن subset او sets من
+
+373
+00:31:23,320 --> 00:31:28,060
+pairs من ازواج a والb a والc الاخرين الان وكل
+
+374
+00:31:28,060 --> 00:31:34,990
+واحدة مكونة من ال item set مكونة من تلاتةالان اذا
+
+375
+00:31:34,990 --> 00:31:40,530
+من ال frequency تبعت المجموعة كلها كانت اقل من ال
+
+376
+00:31:40,530 --> 00:31:43,730
+threshold معين انا مابديش اياهم يعني فيهم على
+
+377
+00:31:43,730 --> 00:31:50,390
+الاقل element كان وزنه ضعيف وبالتالي لم يكن على
+
+378
+00:31:50,390 --> 00:31:57,590
+القدر المعين او نزلمن حجم أو نزل من مجموع الـ
+
+379
+00:31:57,590 --> 00:32:01,110
+element set لأن لو كانوا هدول كلهم frequent items
+
+380
+00:32:01,110 --> 00:32:05,550
+معناته العدد تبعهم هتتجاوز ال frequent item
+
+381
+00:32:05,550 --> 00:32:08,210
+الموجود يعني هيك لو اتكلمت انا و قولت ان ال
+
+382
+00:32:08,210 --> 00:32:12,170
+frequency تبعت كل pair ال minimum frequency خمسة
+
+383
+00:32:12,170 --> 00:32:17,570
+تمام ال minimum support تبعت كل واحد خمسة خمسة و
+
+384
+00:32:17,570 --> 00:32:18,910
+خمسة و خمسة و خمسة و خمسة و خمسة و خمسة و خمسة و
+
+385
+00:32:18,910 --> 00:32:19,410
+خمسة و خمسة و خمسة و خمسة و خمسة و خمسة و خمسة و
+
+386
+00:32:19,410 --> 00:32:20,470
+خمسة و خمسة و خمسة و خمسة و خمسة و خمسة و خمسة و
+
+387
+00:32:20,470 --> 00:32:22,590
+خمسة و خمسة و خمسة و خ
+
+388
+00:32:25,960 --> 00:32:32,400
+خمسة عشر يعني خمسة و أربعين كونه ان العدد اللي طلع
+
+389
+00:32:32,400 --> 00:32:34,980
+.. طبعا ال minimum بدأ افترض كونه العدد خمسة و
+
+390
+00:32:34,980 --> 00:32:40,400
+تلاتين طلع اقل منها اقل من الخمسة و أربعين معناته
+
+391
+00:32:40,400 --> 00:32:45,700
+في واحد من العناصر هدول تمام مش frequent item
+
+392
+00:32:46,370 --> 00:32:49,270
+وبالتالي أصبحت ال data set كلياتها not frequent
+
+393
+00:32:49,270 --> 00:32:52,890
+item هذا ممكن يبين معايا في مجموعة تانية أثناء
+
+394
+00:32:52,890 --> 00:32:58,930
+التوزيع اللي ظهرت عندي وبالتالي بقيتش بقول أن ال A
+
+395
+00:32:58,930 --> 00:33:04,250
+,B طبعا و كذلك A,D و A,E is not a candidate for
+
+396
+00:33:04,250 --> 00:33:12,520
+two item sets if the sum of count ofالـ A والـ B
+
+397
+00:33:12,520 --> 00:33:18,640
+والـ A والـ D والـ A والـ D والـ A والـ A والـ B
+
+398
+00:33:18,640 --> 00:33:23,240
+والـ A والـ B والـ A والـ D والـ A والـ A والـ D
+
+399
+00:33:23,240 --> 00:33:23,420
+والـ A والـ A والـ D والـ A والـ A والـ D والـ A
+
+400
+00:33:23,420 --> 00:33:23,500
+والـ B والـ A والـ A والـ A والـ A والـ A والـ A
+
+401
+00:33:23,500 --> 00:33:23,620
+والـ A والـ A والـ A والـ A والـ A والـ A والـ A
+
+402
+00:33:23,620 --> 00:33:24,600
+والـ A والـ A والـ A والـ A والـ A والـ A والـ A
+
+403
+00:33:24,600 --> 00:33:26,320
+والـ A والـ A والـ A والـ A والـ A والـ A والـ A
+
+404
+00:33:26,320 --> 00:33:32,540
+والـ A والـ A والـأخر شغلة تقريبا عندنا الآن اللي
+
+405
+00:33:32,540 --> 00:33:35,720
+هي الـ Sampling for Frequent Patterns انا اروح
+
+406
+00:33:35,720 --> 00:33:38,260
+اعمل Sampling للـ Frequent Patterns اللي موجود
+
+407
+00:33:38,260 --> 00:33:41,380
+عندها Select a sample of original data
+
+408
+00:33:44,690 --> 00:33:48,390
+أحصل على أشكال عادية مع الـ Sample باستخدام بريوري
+
+409
+00:33:48,390 --> 00:33:53,590
+وبهيك أنا أشغل على الـ Sample من الـ Data Set و
+
+410
+00:33:53,590 --> 00:33:56,810
+أبنيهما أسكن الـ Database مرة و أمر على الـ
+
+411
+00:33:56,810 --> 00:33:58,970
+Database مرة لأكتشف أشياء عادية
+
+412
+00:34:02,410 --> 00:34:05,690
+عشان احسب ال frequency تبعت الاعلاصر الموجودة في
+
+413
+00:34:05,690 --> 00:34:10,110
+ال sample only borders of a closure frequency
+
+414
+00:34:10,110 --> 00:34:13,350
+patterns are checked طبعا انا بدور على ال bell
+
+415
+00:34:13,350 --> 00:34:17,030
+القريبة من الحد الموجود هي اللي انا بروح بقى
+
+416
+00:34:17,030 --> 00:34:21,510
+استخدمهم انا بروح بقى ادور على ال ABCD بدل ما اروح
+
+417
+00:34:21,510 --> 00:34:25,730
+ادور على ال AB و AC لحالهملماذا يا معادل الخير؟
+
+418
+00:34:25,730 --> 00:34:30,250
+لأننا متفقين إذا كنت والله انا a والb والc والd
+
+419
+00:34:30,250 --> 00:34:33,090
+are frequent معناته أي subset هيكون frequent
+
+420
+00:34:33,090 --> 00:34:39,300
+معناته a,b frequent,ac frequent,ad frequent كذلكBC
+
+421
+00:34:39,300 --> 00:34:43,540
+frequent والـ PD frequent كذلك والـ DC frequent
+
+422
+00:34:43,540 --> 00:34:46,960
+فانا اذا حصلت على هدفه هو frequent وبالتالي انا
+
+423
+00:34:46,960 --> 00:34:51,860
+بجلل عدد ال patterns اللي انا بدي اوجدها وممكن
+
+424
+00:34:51,860 --> 00:34:56,060
+ارجع لل database مرة تانية اذا كنت انا صار في عند
+
+425
+00:34:56,060 --> 00:34:59,160
+بعض ال patterns مش ملاجئلهم او مش قادر احسبلهم
+
+426
+00:34:59,160 --> 00:35:03,820
+الان بالمختصر نقدر نقول و الله انا في عند تلت او
+
+427
+00:35:03,820 --> 00:35:08,610
+في عند تلت حالاتأو هذه التقنيات اللي عشان أحسن من
+
+428
+00:35:08,610 --> 00:35:15,830
+أداء الـ Apriori أجلل عدد مرات قراءة ال database و
+
+429
+00:35:15,830 --> 00:35:18,630
+هنشوف نحنا ممكن أن انا أجسمها ل two partitions
+
+430
+00:35:18,630 --> 00:35:23,470
+أجلل من عدد ال candidates اللي موجودين عندنا و
+
+431
+00:35:23,470 --> 00:35:27,610
+أجلل ال candidates باعتماد على عصبي للمثال ال hash
+
+432
+00:35:27,610 --> 00:35:34,060
+book table أو ال hash tableأشتغل عليه الحالة
+
+433
+00:35:34,060 --> 00:35:37,160
+التالتة ان انا فعليا اشوف كيف طريقة ممكن ان اسرع
+
+434
+00:35:37,160 --> 00:35:43,320
+فيها عملية العد فانا ممكن اروح باعتمد على موضوع ال
+
+435
+00:35:43,320 --> 00:35:48,780
+sampling لل frequent patterns ومن ثم بشتغل و بشوف
+
+436
+00:35:48,780 --> 00:35:53,620
+العناصر اللي موجودة عندها هنا هنجف ان شاء الله في
+
+437
+00:35:53,620 --> 00:35:58,380
+التسجيل هذا لان الجزئية اللي ضايلة لها علاقة في ان
+
+438
+00:35:58,380 --> 00:36:03,050
+انا كيف ممكنسأبحث عن الـ Frequent Patterns بدون أن
+
+439
+00:36:03,050 --> 00:36:08,270
+أعمل Candidate Generation
+
+440
+00:36:08,270 --> 00:36:13,210
+وهنا سأتكلم عن الـ FP Growth Approach وهذا سيكون
+
+441
+00:36:13,210 --> 00:36:16,070
+موضوعنا في التسجيل القادم إن شاء الله تعالى
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/oxlQUhGi7Cg_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/oxlQUhGi7Cg_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..e12815133e359cea54e2fc391a55393a235fa128
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/oxlQUhGi7Cg_raw.json
@@ -0,0 +1 @@
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96.39, "text": "confidence condition هذا شرمالة الـ association role القوي الابريري بيستخدم او يستخدم من أجل الحصول على كل frequent item set تمام it computes the frequent item set in a data set through several iterations من خلال دورات متعددة بيصل اياش ال case iteration compute all the frequent item set", "tokens": [1671, 69, 2778, 4188, 23758, 13412, 2288, 2304, 6027, 3660, 2423, 39184, 14598, 3090, 25062, 45865, 2423, 16758, 16572, 16572, 4724, 1829, 14851, 9778, 40448, 1975, 2407, 7251, 14851, 9778, 40448, 9154, 5551, 7435, 1211, 21542, 9381, 12610, 15844, 28242, 18004, 3174, 992, 46811, 10943, 309, 715, 1819, 264, 18004, 3174, 992, 294, 257, 1412, 992, 807, 2940, 36540, 9154, 16490, 1211, 6027, 11778, 13063, 9307, 44650, 22488, 41891, 4724, 1829, 36520, 1975, 1829, 33599, 2423, 1389, 24784, 14722, 439, 264, 18004, 3174, 992], "avg_logprob": -0.3472426330342012, "compression_ratio": 1.6475770925110131, "no_speech_prob": 0.0, "words": [{"start": 66.91, "end": 67.93, "word": 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الخير احنا متفقين ان ال data set او ال attributes او ال transactional data set اللي انا بده اشتغل عليها مكونة of element elements اللي هو عددهم M من I واحد زي ما قلنا ل I M items فهي M من ال items معناته ال K تبعته تتراوح", "tokens": [6027, 7649, 35186, 10874, 15042, 27884, 33962, 13546, 1975, 5016, 8315, 44650, 5172, 4587, 9957, 16472, 2423, 1412, 992, 1975, 2407, 2423, 17212, 1975, 2407, 2423, 1145, 578, 1966, 1412, 992, 13672, 1829, 1975, 8315, 47525, 3224, 1975, 8592, 2655, 17082, 1211, 25894, 11296, 3714, 30544, 3660, 295, 4478, 4959, 13672, 1829, 31439, 6225, 3215, 3215, 16095, 376, 9154, 286, 36764, 24401, 30767, 1829, 19446, 12174, 1211, 8315, 5296, 286, 376, 4754, 6156, 3224, 1829, 376, 9154, 2423, 4754, 20449, 8315, 47395, 2423, 591, 6055, 3555, 34268, 3224, 6055, 2655, 23557, 2407, 5016], "avg_logprob": -0.3281250114136554, "compression_ratio": 1.5981735159817352, "no_speech_prob": 0.0, "words": [{"start": 98.94999999999999, "end": 99.71, "word": "الان", "probability": 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"seek": 16301, "start": 137.85, "end": 163.01, "text": "Each iteration has two steps Candidate generation بتحدد ال candidates و بعدين ال candidates counting and selection بتاخد ال candidate اللي هو المرشح ال element المرشح او ال item 6 المرشحة وبتروح بتعدلها تمام وبناء على العدد بتختارها او مابتختارهاش في المثال اللي موجود عندنا هنا جماعة الخير", "tokens": [36, 608, 24784, 575, 732, 4439, 20466, 327, 473, 5125, 39894, 24401, 3215, 2423, 11255, 4032, 39182, 9957, 2423, 11255, 13251, 293, 9450, 39894, 47283, 3215, 2423, 11532, 13672, 1829, 31439, 9673, 2288, 8592, 5016, 2423, 4478, 9673, 2288, 8592, 5016, 1975, 2407, 2423, 3174, 1386, 9673, 2288, 8592, 5016, 3660, 46599, 2655, 32887, 5016, 39894, 22488, 1211, 11296, 46811, 10943, 46599, 1863, 16606, 15844, 18863, 3215, 3215, 39894, 46456, 9640, 11296, 1975, 2407, 3714, 16758, 2655, 46456, 9640, 3224, 33599, 8978, 9673, 12984, 6027, 13672, 1829, 3714, 29245, 23328, 43242, 8315, 34105, 10874, 15042, 27884, 33962, 13546], "avg_logprob": 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عشان أعدل شغلة في ال slide هذه في طريقة عرض ال slide ممكن تكون أريح لإينا في الفهم طيب جماعة الخير أرجو المثال نعرضه بشكل أفضل إن شاء الله تعالى", "tokens": [2304, 33599, 1829, 21542, 6027, 16490, 1211, 11703, 9957, 1829, 14739, 995, 5551, 30543, 5172, 16712, 3794, 7435, 26895, 24976, 5016, 19913, 3660, 6225, 8592, 7649, 5551, 22488, 1211, 13412, 17082, 37977, 8978, 2423, 4137, 29538, 8978, 23032, 16572, 28671, 6225, 43042, 2423, 4137, 3714, 43020, 6055, 30544, 5551, 16572, 5016, 5296, 28814, 1829, 8315, 8978, 27188, 16095, 23032, 1829, 3555, 10874, 15042, 27884, 33962, 13546, 5551, 47341, 2407, 9673, 12984, 6027, 8717, 3615, 43042, 3224, 4724, 8592, 28820, 5551, 5172, 11242, 1211, 36145, 13412, 16606, 21984, 37279, 6027, 7578], "avg_logprob": -0.2378090724840269, "compression_ratio": 1.6446700507614214, "no_speech_prob": 0.0, "words": [{"start": 238.36, "end": 238.74, "word": "ماشي", "probability": 0.636962890625}, {"start": 238.74, "end": 239.08, "word": " الحال", "probability": 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algorithm كله يبحث عن ال item frequent set في الأول و بعدين بيعمل generate و قلنا ان ال app priori هان في كل step في كل iteration بيشتغل جيش بروح بساوي بيعمل generate ل", "tokens": [6027, 7649, 9122, 15042, 12174, 1211, 8315, 8608, 16758, 4587, 995, 16472, 2423, 9284, 28242, 3224, 7251, 49628, 12984, 18871, 2423, 3174, 18004, 992, 8978, 16247, 12610, 4032, 39182, 9957, 4724, 1829, 25957, 1211, 8460, 4032, 12174, 1211, 8315, 16472, 2423, 724, 4059, 72, 8032, 7649, 8978, 28242, 1823, 8978, 28242, 24784, 4724, 1829, 8592, 2655, 17082, 1211, 10874, 1829, 8592, 4724, 32887, 5016, 4724, 3794, 995, 45865, 4724, 1829, 25957, 1211, 8460, 5296], "avg_logprob": -0.5162500286102295, "compression_ratio": 1.5769230769230769, "no_speech_prob": 2.384185791015625e-07, "words": [{"start": 267.15, "end": 267.89, "word": "الان", "probability": 0.473388671875}, {"start": 267.89, "end": 268.95, "word": " كما", "probability": 0.57470703125}, {"start": 268.95, "end": 269.27, "word": " قلنا", "probability": 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"probability": 0.91357421875}], "temperature": 1.0}, {"id": 13, "seek": 31577, "start": 287.09, "end": 315.77, "text": "للـ group بالـ candidates و بعدين بيعدلوا ال elements تبعته و بعدين بيعملوا منه selection فاحنا الآن هذا مع ال algorithm اللي حاسسه الآن معناته حبدأ انا مع شغل بسميها C1 C1 هي عبارة عن ال candidates of item set with one element اللي هم I1 I2 I3 I4", "tokens": [1211, 1211, 39184, 1594, 20666, 39184, 11255, 4032, 39182, 9957, 4724, 1829, 22488, 1211, 14407, 2423, 4959, 6055, 3555, 34268, 3224, 4032, 39182, 9957, 4724, 1829, 25957, 1211, 14407, 9154, 3224, 9450, 6156, 39319, 8315, 6024, 48506, 23758, 20449, 2423, 9284, 13672, 1829, 11331, 32277, 3794, 3224, 6024, 48506, 20449, 8315, 47395, 11331, 44510, 10721, 1975, 8315, 20449, 13412, 17082, 1211, 4724, 38251, 1829, 11296, 383, 16, 383, 16, 39896, 6225, 3555, 9640, 3660, 18871, 2423, 11255, 295, 3174, 992, 365, 472, 4478, 13672, 1829, 8032, 2304, 286, 16, 286, 17, 286, 18, 286, 19], "avg_logprob": -0.377278639934957, 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الخطوة اللي بعد هيك انا بدروح احسب لهم جماعة الخير ال support لما انا بده احسب ال support لل C2 لل C1 يعني ما زلت candidate واحد الان I1 جديش هي واحدة تلاتة اربعة خمسة ستة", "tokens": [40, 18, 286, 19, 286, 20, 33962, 9566, 2407, 3660, 13672, 1829, 39182, 39896, 4117, 1975, 8315, 47525, 32887, 5016, 1975, 5016, 35457, 5296, 16095, 10874, 15042, 27884, 33962, 13546, 2423, 1406, 5296, 15042, 1975, 8315, 47525, 3224, 1975, 5016, 35457, 2423, 1406, 24976, 383, 17, 24976, 383, 16, 37495, 22653, 19446, 30767, 1211, 2655, 11532, 36764, 24401, 2423, 7649, 286, 16, 10874, 16254, 8592, 39896, 36764, 24401, 3660, 6055, 1211, 9307, 3660, 1975, 25513, 27884, 16490, 2304, 3794, 3660, 8608, 2655, 3660], "avg_logprob": -0.29575891686337336, "compression_ratio": 1.5683060109289617, "no_speech_prob": 0.0, "words": [{"start": 349.9, "end": 350.9, "word": "I3", "probability": 0.502197265625}, {"start": 350.9, "end": 351.9, "word": " I4", "probability": 0.80908203125}, {"start": 351.9, "end": 354.82, 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"probability": 0.9677734375}, {"start": 359.76, "end": 361.84, "word": " لما", "probability": 0.93994140625}, {"start": 361.84, "end": 361.96, "word": " انا", "probability": 0.875}, {"start": 361.96, "end": 362.22, "word": " بده", "probability": 0.609619140625}, {"start": 362.22, "end": 362.42, "word": " احسب", "probability": 0.8597005208333334}, {"start": 362.42, "end": 362.58, "word": " ال", "probability": 0.65478515625}, {"start": 362.58, "end": 363.08, "word": " support", "probability": 0.99560546875}, {"start": 363.08, "end": 363.38, "word": " لل", "probability": 0.46923828125}, {"start": 363.38, "end": 363.92, "word": " C2", "probability": 0.508056640625}, {"start": 363.92, "end": 364.86, "word": " لل", "probability": 0.76806640625}, {"start": 364.86, "end": 365.62, "word": " C1", "probability": 0.9658203125}, {"start": 365.62, "end": 366.04, "word": " يعني", "probability": 0.56341552734375}, {"start": 366.04, "end": 366.24, "word": " ما", "probability": 0.443115234375}, 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2407, 2744, 591, 4724, 1829, 44510, 10721, 9154, 441, 16, 337, 591, 2681, 502, 2423, 591, 20193, 6055, 3794, 995, 45865, 1025, 591, 1804, 1804, 1841, 2423, 11532, 383, 42, 30767, 16373, 3215, 36764, 24401, 11532, 8460, 2423, 591], "avg_logprob": -0.5125, "compression_ratio": 1.4971098265895955, "no_speech_prob": 0.0, "words": [{"start": 1138.39, "end": 1139.13, "word": "K", "probability": 0.157958984375}, {"start": 1139.13, "end": 1139.77, "word": " item", "probability": 0.0645751953125}, {"start": 1139.77, "end": 1140.31, "word": " set", "probability": 0.84814453125}, {"start": 1140.31, "end": 1141.61, "word": " frequent", "probability": 0.5166015625}, {"start": 1141.61, "end": 1142.21, "word": " item", "probability": 0.900390625}, {"start": 1142.21, "end": 1142.65, "word": " set", "probability": 0.9423828125}, {"start": 1142.65, "end": 1142.95, "word": " اللي", "probability": 0.5321044921875}, {"start": 1142.95, "end": 1143.05, "word": " هي", "probability": 0.3564453125}, {"start": 1143.05, "end": 1143.13, "word": " ال", "probability": 0.269287109375}, {"start": 1143.13, "end": 1143.29, "word": " list", "probability": 0.8828125}, {"start": 1143.29, "end": 1143.49, "word": " اللي", "probability": 0.850830078125}, {"start": 1143.49, "end": 1144.03, "word": " موجودة", "probability": 0.8963623046875}, {"start": 1144.03, "end": 1144.33, "word": " عندى", "probability": 0.576416015625}, {"start": 1144.33, "end": 1144.57, "word": " list", "probability": 0.4013671875}, {"start": 1144.57, "end": 1144.73, "word": " of", "probability": 0.71923828125}, {"start": 1144.73, "end": 1145.17, "word": " frequent", "probability": 0.9140625}, {"start": 1145.17, "end": 1145.61, "word": " item", "probability": 0.88525390625}, {"start": 1145.61, "end": 1145.95, "word": " set", "probability": 0.50439453125}, {"start": 1145.95, "end": 1146.15, "word": " او", "probability": 0.6990966796875}, {"start": 1146.15, "end": 1146.45, "word": " size", "probability": 0.28564453125}, {"start": 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1162.99, "word": " ال", "probability": 0.264404296875}, {"start": 1162.99, "end": 1163.25, "word": " K", "probability": 0.923828125}], "temperature": 1.0}, {"id": 45, "seek": 119182, "start": 1165.62, "end": 1191.82, "text": "طبعا انا انا زي ما اقول من هنا انا بحب اعمل generate for each transaction تيه ال database database to increment the count of candidates اللي انا هدول ال candidates هدول انا بحسب ال minimum support و ال candidates with ال minimum support اللي موجودين عندها و بنتهيأ لحق و في الآخر ايش بروح بيساوي بيعمل union ل ال case اللي موجودة يعني", "tokens": [9566, 3555, 3615, 995, 1975, 8315, 1975, 8315, 30767, 1829, 19446, 1975, 39648, 9154, 34105, 1975, 8315, 4724, 5016, 3555, 1975, 25957, 1211, 8460, 337, 1184, 14425, 6055, 1829, 3224, 2423, 8149, 8149, 281, 26200, 264, 1207, 295, 11255, 13672, 1829, 1975, 8315, 8032, 3215, 12610, 2423, 11255, 8032, 3215, 12610, 1975, 8315, 4724, 5016, 35457, 2423, 7285, 1406, 4032, 2423, 11255, 365, 2423, 7285, 1406, 13672, 1829, 3714, 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{"start": 1187.44, "end": 1187.8, "word": " بيعمل", "probability": 0.92138671875}, {"start": 1187.8, "end": 1188.28, "word": " union", "probability": 0.8837890625}, {"start": 1188.28, "end": 1189.34, "word": " ل", "probability": 0.6181640625}, {"start": 1189.34, "end": 1189.48, "word": " ال", "probability": 0.61181640625}, {"start": 1189.48, "end": 1190.02, "word": " case", "probability": 0.382080078125}, {"start": 1190.02, "end": 1190.4, "word": " اللي", "probability": 0.983154296875}, {"start": 1190.4, "end": 1191.18, "word": " موجودة", "probability": 0.9725341796875}, {"start": 1191.18, "end": 1191.82, "word": " يعني", "probability": 0.603515625}], "temperature": 1.0}, {"id": 46, "seek": 121990, "start": 1193.08, "end": 1219.9, "text": "طبعاً يا جماعة الخير لازم احنا نأكد على نقطة مهمة جدا انه ال .. طبعا ال code او حفظ ال code هذا مش .. مش مطلوب انه بقدر ما انا مطلوب ان انا فهمته من خلال الخطوات وهي ال .. ال بي سيدو code اللي موجود عندى كذلك ال .. ماما صلي علي سيدنا محمد .. مش .. 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التالتة ان انا فعليا اشوف كيف طريقة ممكن ان اسرع فيها عملية العد فانا ممكن اروح باعتمد على موضوع ال sampling لل frequent patterns ومن ثم بشتغل و بشوف العناصر اللي موجودة عندها هنا هنجف ان شاء الله في التسجيل هذا لان الجزئية اللي ضايلة لها علاقة في ان انا كيف ممكن", "tokens": [10721, 8592, 2655, 17082, 1211, 47356, 21542, 6027, 3660, 16712, 6027, 2655, 3660, 16472, 1975, 8315, 6156, 3615, 20292, 995, 1975, 8592, 38688, 9122, 33911, 23032, 16572, 28671, 3714, 43020, 16472, 1975, 3794, 2288, 3615, 8978, 11296, 6225, 42213, 10632, 18863, 3215, 6156, 7649, 995, 3714, 43020, 1975, 32887, 5016, 4724, 995, 34268, 2304, 3215, 15844, 3714, 2407, 11242, 45367, 2423, 21179, 24976, 18004, 8294, 4032, 27842, 38637, 2304, 4724, 8592, 2655, 17082, 1211, 4032, 4724, 8592, 38688, 18863, 1863, 33546, 2288, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 11296, 34105, 8032, 1863, 7435, 5172, 16472, 13412, 16606, 21984, 8978, 16712, 3794, 7435, 26895, 23758, 5296, 7649, 25724, 11622, 19986, 10632, 13672, 1829, 48812, 995, 26895, 3660, 5296, 11296, 11203, 995, 28671, 8978, 16472, 1975, 8315, 9122, 33911, 3714, 43020], "avg_logprob": -0.25190841150647814, "compression_ratio": 1.8687258687258688, "no_speech_prob": 0.0, "words": [{"start": 2131.8399999999997, "end": 2132.6, "word": "أشتغل", "probability": 0.609912109375}, {"start": 2132.6, "end": 2132.84, "word": " عليه", "probability": 0.16015625}, {"start": 2132.84, "end": 2134.06, "word": " الحالة", "probability": 0.7001953125}, {"start": 2134.06, "end": 2134.58, "word": " التالتة", "probability": 0.91748046875}, {"start": 2134.58, "end": 2134.84, "word": " ان", "probability": 0.380615234375}, {"start": 2134.84, "end": 2135.06, "word": " انا", "probability": 0.8203125}, {"start": 2135.06, "end": 2135.58, "word": " فعليا", "probability": 0.7833251953125}, {"start": 2135.58, "end": 2135.9, "word": " اشوف", "probability": 0.8258463541666666}, {"start": 2135.9, "end": 2136.06, "word": " كيف", "probability": 0.6563720703125}, {"start": 2136.06, "end": 2136.38, "word": " طريقة", "probability": 0.9290364583333334}, {"start": 2136.38, "end": 2136.68, "word": " ممكن", "probability": 0.876708984375}, {"start": 2136.68, "end": 2136.78, "word": " ان", "probability": 0.44970703125}, {"start": 2136.78, "end": 2137.16, "word": " اسرع", "probability": 0.790283203125}, {"start": 2137.16, "end": 2137.56, "word": " فيها", "probability": 0.96484375}, {"start": 2137.56, "end": 2138.24, "word": " عملية", "probability": 0.9913736979166666}, {"start": 2138.24, "end": 2138.8, "word": " العد", "probability": 0.881103515625}, {"start": 2138.8, "end": 2139.4, "word": " فانا", "probability": 0.8517252604166666}, {"start": 2139.4, "end": 2139.68, "word": " ممكن", "probability": 0.957763671875}, {"start": 2139.68, "end": 2139.98, "word": " اروح", "probability": 0.9041341145833334}, {"start": 2139.98, "end": 2140.46, "word": " باعتمد", "probability": 0.9115234375}, {"start": 2140.46, "end": 2140.84, "word": " على", "probability": 0.81005859375}, {"start": 2140.84, "end": 2143.16, "word": " موضوع", "probability": 0.951904296875}, {"start": 2143.16, "end": 2143.32, "word": " ال", "probability": 0.77294921875}, {"start": 2143.32, "end": 2143.58, "word": " sampling", "probability": 0.60107421875}, {"start": 2143.58, "end": 2143.86, "word": " لل", "probability": 0.64404296875}, {"start": 2143.86, "end": 2144.2, "word": " frequent", "probability": 0.505859375}, {"start": 2144.2, "end": 2144.78, "word": " patterns", "probability": 0.61328125}, {"start": 2144.78, "end": 2146.2, "word": " ومن", "probability": 0.76708984375}, {"start": 2146.2, "end": 2146.56, "word": " ثم", "probability": 0.9912109375}, {"start": 2146.56, "end": 2148.08, "word": " بشتغل", "probability": 0.84599609375}, {"start": 2148.08, "end": 2148.26, "word": " و", "probability": 0.84619140625}, {"start": 2148.26, "end": 2148.78, "word": " بشوف", "probability": 0.9161783854166666}, {"start": 2148.78, "end": 2149.48, "word": " العناصر", "probability": 0.8922119140625}, {"start": 2149.48, "end": 2149.72, "word": " اللي", "probability": 0.8818359375}, {"start": 2149.72, "end": 2150.1, "word": " موجودة", "probability": 0.7879638671875}, {"start": 2150.1, "end": 2150.44, "word": " عندها", "probability": 0.802490234375}, {"start": 2150.44, "end": 2151.0, "word": " هنا", "probability": 0.34130859375}, {"start": 2151.0, "end": 2151.58, "word": " هنجف", "probability": 0.7435302734375}, {"start": 2151.58, "end": 2152.7, "word": " ان", "probability": 0.47216796875}, {"start": 2152.7, "end": 2152.94, "word": " شاء", "probability": 0.939453125}, {"start": 2152.94, "end": 2152.98, "word": " الله", "probability": 0.9599609375}, {"start": 2152.98, "end": 2153.62, "word": " في", "probability": 0.88818359375}, {"start": 2153.62, "end": 2154.04, "word": " التسجيل", "probability": 0.9293212890625}, {"start": 2154.04, "end": 2154.4, "word": " هذا", "probability": 0.900390625}, {"start": 2154.4, "end": 2155.12, "word": " لان", "probability": 0.701416015625}, {"start": 2155.12, "end": 2155.54, "word": " الجزئية", "probability": 0.70947265625}, {"start": 2155.54, "end": 2155.68, "word": " اللي", "probability": 0.93798828125}, {"start": 2155.68, "end": 2156.04, "word": " ضايلة", "probability": 0.750244140625}, {"start": 2156.04, "end": 2157.32, "word": " لها", "probability": 0.5445556640625}, {"start": 2157.32, "end": 2157.82, "word": " علاقة", "probability": 0.9850260416666666}, {"start": 2157.82, "end": 2158.12, "word": " في", "probability": 0.8671875}, {"start": 2158.12, "end": 2158.38, "word": " ان", "probability": 0.80517578125}, {"start": 2158.38, "end": 2158.62, "word": " انا", "probability": 0.847900390625}, {"start": 2158.62, "end": 2158.84, "word": " كيف", "probability": 0.985595703125}, {"start": 2158.84, "end": 2159.24, "word": " ممكن", "probability": 0.976806640625}], "temperature": 1.0}, {"id": 86, "seek": 217607, "start": 2160.17, "end": 2176.07, "text": "سأبحث عن الـ Frequent Patterns بدون أن أعمل Candidate Generation وهنا سأتكلم عن الـ FP Growth Approach وهذا سيكون موضوعنا في التسجيل القادم إن شاء الله تعالى", "tokens": [3794, 10721, 49628, 12984, 18871, 2423, 39184, 6142, 28842, 34367, 3695, 47525, 11536, 14739, 5551, 25957, 1211, 20466, 327, 473, 23898, 37037, 8315, 8608, 10721, 2655, 4117, 19528, 18871, 2423, 39184, 36655, 48345, 29551, 608, 37037, 15730, 8608, 1829, 30544, 3714, 2407, 11242, 45367, 8315, 8978, 16712, 3794, 7435, 26895, 25062, 18513, 2304, 36145, 13412, 16606, 21984, 37279, 6027, 7578], "avg_logprob": -0.4623463212466631, "compression_ratio": 1.3389830508474576, "no_speech_prob": 0.0, "words": [{"start": 2160.17, "end": 2160.79, "word": "سأبحث", "probability": 0.57568359375}, {"start": 2160.79, "end": 2161.05, "word": " عن", "probability": 0.67138671875}, {"start": 2161.05, "end": 2161.17, "word": " الـ", "probability": 0.5440673828125}, {"start": 2161.17, "end": 2161.71, "word": " Frequent", "probability": 0.583740234375}, {"start": 2161.71, "end": 2162.49, "word": " Patterns", "probability": 0.75830078125}, {"start": 2162.49, "end": 2162.87, "word": " بدون", "probability": 0.827880859375}, {"start": 2162.87, "end": 2163.05, "word": " أن", "probability": 0.250732421875}, {"start": 2163.05, "end": 2163.19, "word": " أعمل", "probability": 0.711669921875}, {"start": 2163.19, "end": 2164.41, "word": " Candidate", "probability": 0.7098388671875}, {"start": 2164.41, "end": 2168.27, "word": " Generation", "probability": 0.6337890625}, {"start": 2168.27, "end": 2168.49, "word": " وهنا", "probability": 0.468994140625}, {"start": 2168.49, "end": 2168.89, "word": " سأتكلم", "probability": 0.7134521484375}, {"start": 2168.89, "end": 2169.33, "word": " عن", "probability": 0.50537109375}, {"start": 2169.33, "end": 2170.29, "word": " الـ", "probability": 0.5762939453125}, {"start": 2170.29, "end": 2170.77, "word": " FP", "probability": 0.43994140625}, {"start": 2170.77, "end": 2171.67, "word": " Growth", "probability": 0.9091796875}, {"start": 2171.67, "end": 2172.47, "word": " Approach", "probability": 0.9541015625}, {"start": 2172.47, "end": 2172.79, "word": " وهذا", "probability": 0.6629638671875}, {"start": 2172.79, "end": 2173.21, "word": " سيكون", "probability": 0.84033203125}, {"start": 2173.21, "end": 2173.97, "word": " موضوعنا", "probability": 0.9298828125}, {"start": 2173.97, "end": 2174.23, "word": " في", "probability": 0.86962890625}, {"start": 2174.23, "end": 2175.05, "word": " التسجيل", "probability": 0.9715576171875}, {"start": 2175.05, "end": 2175.37, "word": " القادم", "probability": 0.775146484375}, {"start": 2175.37, "end": 2175.51, "word": " إن", "probability": 0.34814453125}, {"start": 2175.51, "end": 2175.59, "word": " شاء", "probability": 0.96923828125}, {"start": 2175.59, "end": 2175.71, "word": " الله", "probability": 0.9287109375}, {"start": 2175.71, "end": 2176.07, "word": " تعالى", "probability": 0.7777506510416666}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 2177.9156875, "duration_after_vad": 2041.1918749999932}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/t7uwWVN30g8.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/t7uwWVN30g8.srt
new file mode 100644
index 0000000000000000000000000000000000000000..0682e8325c6468bb0f3c6fde9fb5be954f7a176b
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/t7uwWVN30g8.srt
@@ -0,0 +1,1721 @@
+1
+00:00:02,230 --> 00:00:04,390
+بسم الله الرحمن الرحيم الصلاة والسلام على رسول
+
+2
+00:00:04,390 --> 00:00:08,590
+الله أهلا وسهلا بكم إخواني الطلاب وأخواتي
+
+3
+00:00:08,590 --> 00:00:15,370
+الطالبات سنستكمل اليوم في هذا التسجيل موضوع الـ
+
+4
+00:00:15,370 --> 00:00:19,050
+classification model evaluation بعد أن تعرفت على
+
+5
+00:00:20,110 --> 00:00:25,050
+هي عبارة عن تحديد الـ Membership لجروب أو لكلاس معروفة
+
+6
+00:00:25,050 --> 00:00:30,070
+مسبقا، وتعرفت على مجموعة من الـ classifiers
+
+7
+00:00:30,070 --> 00:00:33,690
+بدءا من الـ k-nearest neighbor واعتماده، وشفنا أنه
+
+8
+00:00:33,690 --> 00:00:36,610
+يعتمد على الحساب على الـ similarity distance
+
+9
+00:00:36,610 --> 00:00:42,550
+وحكينا أنه يعتمد عليها أو يقارن أو باستخدام
+
+10
+00:00:42,550 --> 00:00:47,110
+different distances زي الـ Euclidean distance أو الـ
+
+11
+00:00:47,110 --> 00:00:52,600
+Manhattan distance، وتكلمنا على الـ Naive Bayes كـ
+
+12
+00:00:52,600 --> 00:00:57,280
+classifier، وشوفنا كيف الـ probability أو كيف تم
+
+13
+00:00:57,280 --> 00:00:59,400
+حساب الـ probability أو الـ conditional probability
+
+14
+00:00:59,400 --> 00:01:05,100
+وانتقلنا بعدها لموضوع الـ decision tree، وشوفنا
+
+15
+00:01:05,100 --> 00:01:08,920
+كيف بنينا الـ decision tree مع بعض، وآخر classifier
+
+16
+00:01:08,920 --> 00:01:12,080
+كان لـ neural network أو الـ multi-layer perceptron
+
+17
+00:01:12,080 --> 00:01:16,200
+أو الـ classifier كان neural network. الآن بعد ما
+
+18
+00:01:16,200 --> 00:01:20,480
+أنا بنيت  الموديل هذا، وأصبحت عملية الـ classification
+
+19
+00:01:20,480 --> 00:01:24,220
+مش لازم أنا أعرف جدوى عملية الـ classification تبعتي
+
+20
+00:01:24,220 --> 00:01:28,320
+صح، أو كده، فبتيجي عملية الـ evaluation هنا فعليا
+
+21
+00:01:28,320 --> 00:01:35,340
+عشان تقولي أنا والله بدي أقيم الأداء الموجود
+
+22
+00:01:35,340 --> 00:01:39,460
+عندي، يعني عفوا، مش العناصر، بدي أقيم أداء الـ
+
+23
+00:01:39,460 --> 00:01:42,260
+classifier اللي موجود عندي. يعني لما احنا بنتكلم
+
+24
+00:01:42,260 --> 00:01:46,830
+على evaluation يعني أن أنا بتكلم على تقييم فعلي
+
+25
+00:01:46,830 --> 00:01:52,610
+للـ classifier اللي موجود عندي، وهذا هو فحوى
+
+26
+00:01:52,610 --> 00:01:56,490
+محاضرتنا لليوم، أو في التسجيل هذا، إن شاء الله تعالى.
+
+27
+00:01:57,520 --> 00:02:00,740
+طبعا بحب أذكر فقط، بداية، أن أذكر بعض الشغلات
+
+28
+00:02:00,740 --> 00:02:04,660
+الأساسية. قلنا من الـ basic concept الخاص بالـ
+
+29
+00:02:04,660 --> 00:02:07,540
+classifier، في عندنا مصطلح الـ accuracy، وقلنا الـ
+
+30
+00:02:07,540 --> 00:02:11,280
+accuracy هي عبارة عن قدرة الـ classifier على التنبؤ
+
+31
+00:02:11,280 --> 00:02:16,220
+بشكل صحيح، وعادة بتمثل بنسبة عدد الـ prediction
+
+32
+00:02:16,220 --> 00:02:22,560
+الصحيحة على كل الـ predictions اللي سواها، على كل عمليات
+
+33
+00:02:22,560 --> 00:02:26,700
+التنبؤ اللي سواها الـ classifier اللي موجودة عنده.
+
+34
+00:02:27,990 --> 00:02:31,930
+وبالتالي سنقول إن الـ Accuracy بتشير لعملية القدرة
+
+35
+00:02:31,930 --> 00:02:36,090
+للـ classifier إنه يعمل correct prediction of the
+
+36
+00:02:36,090 --> 00:02:39,950
+class label for unseen data. وتكلمنا عن الـ Speed،
+
+37
+00:02:39,950 --> 00:02:44,210
+قلنا إنها عبارة عن computational cost الخاصة بالـ
+
+38
+00:02:44,210 --> 00:02:47,870
+classifier. لما تكلمنا عن computational cost،
+
+39
+00:02:50,350 --> 00:02:54,410
+أنا بهمني الوقت اللي بده يستغرقه الـ classifier
+
+40
+00:02:54,410 --> 00:02:58,350
+سواء في عملية الـ training أو حتى في عملية الـ
+
+41
+00:02:58,350 --> 00:03:05,870
+classification نفسها، أو الـ prediction نفسها عفوا، و
+
+42
+00:03:05,870 --> 00:03:08,430
+اتكلمنا كذلك على الـ robustness، وقولنا الـ
+
+43
+00:03:08,430 --> 00:03:12,170
+robustness هي عبارة عن قدرة الـ classifier
+
+44
+00:03:12,170 --> 00:03:17,690
+على أنه يعمل correct prediction لما يكون فيه عندي
+
+45
+00:03:17,690 --> 00:03:23,830
+noisy data. لما يكون فيه عندي noisy data، بعد
+
+46
+00:03:23,830 --> 00:03:26,690
+هيك تكلمنا على الـ scalability، وقلنا الـ scalability
+
+47
+00:03:26,690 --> 00:03:32,970
+تشير إلى قدرة الـ classifier على القدرة على أن أنا
+
+48
+00:03:32,970 --> 00:03:39,410
+فعليا أبني classifier بشكل مجدٍ في حالة وجود
+
+49
+00:03:39,410 --> 00:03:43,780
+البيانات الضخمة اللي موجودة عندي، و الـ Interpretability
+
+50
+00:03:43,780 --> 00:03:49,000
+أو قدرة على تفسير أو على فهم العناصر أو فهم
+
+51
+00:03:49,000 --> 00:03:55,840
+الإيحادات الصادرة أو المعلومات الصادرة عن الـ
+
+52
+00:03:55,840 --> 00:03:58,200
+classifier اللي موجود، وطبعا زي ما قلنا عملية
+
+53
+00:03:58,200 --> 00:04:01,440
+تفسيرها دائما عملية subjective حسب الأشخاص وحسب
+
+54
+00:04:01,440 --> 00:04:06,380
+الـ difficulties اللي أنا بدي أقيمها. فعليا عملية الـ
+
+55
+00:04:06,380 --> 00:04:10,940
+evaluation للـ classifiers أو الـ classification
+
+56
+00:04:10,940 --> 00:04:19,340
+models عملية نوعا ما فيها نوع من الخداع،
+
+57
+00:04:19,340 --> 00:04:25,640
+لكنها فعلا عملية ممكن تكون نوعا ما غير واضحة أو
+
+58
+00:04:25,640 --> 00:04:29,120
+فيها بعض الخبايا، لازم الواحد ينتبه لها. عشان هيك
+
+59
+00:04:29,120 --> 00:04:34,220
+بنقول نسميها tricky أو خداعة. طبعا لما نتكلم عن
+
+60
+00:04:34,220 --> 00:04:38,820
+evaluation، أول evaluation أو أول metric ممكن يخطر
+
+61
+00:04:38,820 --> 00:04:44,260
+في بالي هي عبارة عن الـ accuracy. أول
+
+62
+00:04:44,260 --> 00:04:47,540
+metric ممكن يخطر في بالي في التقييم أو في الـ
+
+63
+00:04:47,540 --> 00:04:51,820
+evaluation هي عبارة عن الـ accuracy، لكنها مش هي
+
+64
+00:04:51,820 --> 00:04:56,880
+الوحيدة. طبعا هنا لما نتكلم على الـ accuracy معناته
+
+65
+00:04:56,880 --> 00:05:01,840
+أنا بستخدم، باعتمدي على test set. أنا الـ training
+
+66
+00:05:01,840 --> 00:05:08,740
+set استخدمته في لحظة بناء
+
+67
+00:05:08,740 --> 00:05:13,480
+الموديل، والـ test set جا دورها عشان هي عبارة عن
+
+68
+00:05:13,480 --> 00:05:21,700
+unlabeled set، وأنا بدي أعمل لها prediction وبناءً
+
+69
+00:05:21,700 --> 00:05:25,640
+عليها بقيم الـ accuracy. في سؤال مهم جدا يا جماعة
+
+70
+00:05:25,640 --> 00:05:31,460
+الخطر، هل الـ test set هي عبارة عن labelled data أو
+
+71
+00:05:31,460 --> 00:05:36,140
+labelled set أو unlabelled set؟ كمان مرة السؤال
+
+72
+00:05:36,140 --> 00:05:39,980
+بأطرحه الآن، بقول هل الـ test set هي عبارة عن
+
+73
+00:05:39,980 --> 00:05:44,040
+labelled set أو unlabelled set؟  بجزم، هل لازم
+
+74
+00:05:44,040 --> 00:05:50,820
+يكون لها label ولا مش لازم يكون لها label؟ المفروض
+
+75
+00:05:51,690 --> 00:06:00,230
+الآن تعمل pause للـ recording هذا وتحاول تفكر
+
+76
+00:06:00,230 --> 00:06:03,690
+بالجواب. إحنا بنتذكر أن طرحنا خلال المحاضرات السابقة
+
+77
+00:06:03,690 --> 00:06:09,090
+الجواب الصحيح أنه لازم تكون labelled، لأن لو ما كانش
+
+78
+00:06:09,090 --> 00:06:12,190
+فيه label مش هقدر أعمل evaluation، مش هقدر أعرف
+
+79
+00:06:12,190 --> 00:06:14,770
+جدوى الـ prediction الصحيحة من الـ prediction الخاطئة.
+
+80
+00:06:14,770 --> 00:06:18,550
+وبالتالي الـ test set must be labelled.
+
+81
+00:06:21,470 --> 00:06:24,250
+طبعا عندي الـ methods اللي أنا ممكن أستخدمها مع الـ
+
+82
+00:06:24,250 --> 00:06:27,710
+classifier، مع الـ classification هنا، هي عبارة عن
+
+83
+00:06:27,710 --> 00:06:31,290
+مجموعة من الـ ... الـ method، أو في عندي two methods
+
+84
+00:06:31,290 --> 00:06:36,010
+أساسيات أنا بستخدمهم عشان أتنبأ أو أقدر أعمل تقدير
+
+85
+00:06:36,010 --> 00:06:40,110
+للـ accuracy الخاصة بالـ classifier. في عندنا الـ
+
+86
+00:06:40,110 --> 00:06:44,590
+holdout method، والـ holdout method بتعتمد على الـ
+
+87
+00:06:44,590 --> 00:06:49,760
+random sampling، وطبعا هنا فعليا أنا بقى زي ما قلنا
+
+88
+00:06:49,760 --> 00:06:52,640
+سابقا، وزي ما كان في الـ assignment السابق، أنا
+
+89
+00:06:52,640 --> 00:06:57,160
+فعليا الـ data set اللي موجودة عندها، بغض النظر عن
+
+90
+00:06:57,160 --> 00:07:02,460
+حجمها، بقسمها لـ two partitions، 70% على سبيل
+
+91
+00:07:02,460 --> 00:07:09,500
+المثال، للـ training، و 30% كانت
+
+92
+00:07:09,500 --> 00:07:13,380
+للـ testing. هذه الميثود بسميها holdout method، و
+
+93
+00:07:13,380 --> 00:07:18,700
+بقسم الـ data set تبعتي لـ training and test set، و
+
+94
+00:07:18,700 --> 00:07:21,220
+بعدين الطريقة الثانية اللي إحنا بنسميها الـ cross
+
+95
+00:07:21,220 --> 00:07:24,500
+validation، والـ cross validation هي عبارة عن مثل
+
+96
+00:07:24,500 --> 00:07:29,100
+ما كذلك، موجودة غالبا، معظم استخدامها لما بتكون الـ data
+
+97
+00:07:29,100 --> 00:07:36,600
+set تبعتي حجمها قليل. هروح بتفاصيلها بشكل كويس. طبعا
+
+98
+00:07:36,600 --> 00:07:41,260
+لما أتكلم على cross validation، طريقة ممتازة جدا،
+
+99
+00:07:41,260 --> 00:07:46,160
+بحيث أنه أنا أعرض الـ data set بالكامل في الـ
+
+100
+00:07:46,160 --> 00:07:50,980
+training على أجزاء مختلفة، وكذلك بأختبر كل الـ data
+
+101
+00:07:50,980 --> 00:07:54,900
+set، وبطلع بالمتوسط اللي موجود. لما أنا بتكلم على
+
+102
+00:07:54,900 --> 00:07:58,180
+cross validation، بتكلم إن هي عبارة عن statistical
+
+103
+00:07:58,180 --> 00:08:02,270
+method تستخدم من أجل الـ evaluation للـ
+
+104
+00:08:02,270 --> 00:08:05,170
+generalization. الـ generalization جماعة الخير،
+
+105
+00:08:05,170 --> 00:08:10,470
+المقصود فيها هنا أن أنا بأتكلم، قاعد على أو بتكلم
+
+106
+00:08:10,470 --> 00:08:16,670
+على قدرة النظام على التنبؤ الصحيح، هو إتعلم بناءً
+
+107
+00:08:16,670 --> 00:08:22,070
+على الـ training data. الآن أنا ببدأ أشوف فعليا كيف
+
+108
+00:08:22,070 --> 00:08:25,610
+أداء النظام، أو ده الـ model اللي موجود عندي هنا.
+
+109
+00:08:25,910 --> 00:08:29,510
+فكلمة الـ model بيقدر يتعامل أو يكون أداء تبعه
+
+110
+00:08:29,510 --> 00:08:33,270
+بكون كويس مع unseen data، معناته هو more general.
+
+111
+00:08:33,270 --> 00:08:36,910
+More general يعني ما انبنى فقط من أو مكان مش
+
+112
+00:08:36,910 --> 00:08:40,830
+specific للـ training data اللي استخدمناها، بل
+
+113
+00:08:40,830 --> 00:08:44,790
+بالعكس هو شغال على general data set، على أي data
+
+114
+00:08:44,790 --> 00:08:48,750
+set هيشتغل بكفاءة كويسة. طبعا الـ performance data
+
+115
+00:08:48,750 --> 00:08:50,730
+are more stable.
+
+116
+00:08:55,210 --> 00:09:01,010
+Using split، طبعا
+
+117
+00:09:01,010 --> 00:09:03,770
+اللي متكلم عن الـ cross validation، نتكلم إنه الـ
+
+118
+00:09:03,770 --> 00:09:07,690
+performance هذا، أو خلنا نقول الـ estimation تبعت الـ
+
+119
+00:09:07,690 --> 00:09:11,330
+accuracy أو الـ performance تبعت الـ model هنا
+
+120
+00:09:11,330 --> 00:09:16,410
+هتكون أكثر موثوقية أو أكثر ثباتا، ما إنه لو أنا
+
+121
+00:09:16,410 --> 00:09:20,690
+فعليا قسمت الـ data set لـ training أو testing، لأن
+
+122
+00:09:20,690 --> 00:09:25,360
+موضوع الـ randomness بيعمل فعلا مشكلة حقيقية، فالـ
+
+123
+00:09:25,360 --> 00:09:28,380
+cross validation، بدل ما أنا أقسم الـ data set
+
+124
+00:09:28,380 --> 00:09:35,340
+لمجموعتين، فعليا أنا بقسم الـ data بشكل متكرر،
+
+125
+00:09:35,340 --> 00:09:37,600
+repeatedly. شو يعني؟
+
+126
+00:09:40,410 --> 00:09:44,890
+مفهومها أنه أنا فعليا بروح بأقسم، افترض أن هذه
+
+127
+00:09:44,890 --> 00:09:49,890
+الخط، الـ data، كل واحد من الـ rows هاي بمثل الـ data
+
+128
+00:09:49,890 --> 00:09:54,350
+set كاملة. الفكرة فيها أنه أنا أقسمها لمجموعة من الـ
+
+129
+00:09:54,350 --> 00:09:58,350
+folds، والـ fold هذه واحدة منهم تستخدم للـ training،
+
+130
+00:09:58,350 --> 00:10:06,460
+والباقي يستخدم، عفوا، واحدة للـ test، والباقي يستخدم للـ
+
+131
+00:10:06,460 --> 00:10:11,400
+training. يعني تخيل لو أنا قلت هي الـ data set اللي
+
+132
+00:10:11,400 --> 00:10:14,560
+موجودة عندي. سامحوني أنا مش قادر أعمل control كتير
+
+133
+00:10:14,560 --> 00:10:17,420
+على الـ mouse أو على الـ pen اللي موجود معايا.
+
+134
+00:10:18,550 --> 00:10:22,390
+قسمتها لأربعة أجزاء، فبشكل متكرر باجي بقول والله
+
+135
+00:10:22,390 --> 00:10:26,570
+الجزء هذا الآن هو المخصص للـ training، والتلاتة هدول
+
+136
+00:10:26,570 --> 00:10:31,410
+عفوا، للـ test، والتلاتة هدول المخصصين لمين؟ لموضوع الـ
+
+137
+00:10:31,410 --> 00:10:35,290
+training. في الدورة الثانية بحدد هذا للـ test،
+
+138
+00:10:35,290 --> 00:10:40,810
+والباقي هذا كله للـ training. ولاحظوا في كل مرة أنا
+
+139
+00:10:40,810 --> 00:10:43,750
+بعتمد على القيمة اللي بتطلع من موضوع الـ testing
+
+140
+00:10:43,750 --> 00:10:49,580
+هنا، الـ accuracy. الـ accuracy، الـ Accuracy وليس
+
+141
+00:10:49,580 --> 00:10:52,280
+بالضرورة في كل مرة تديني نفس القيمة، بالعكس، تديني
+
+142
+00:10:52,280 --> 00:10:58,640
+قيم مختلفة. في النهاية أحصل على أو أحاول أخد الـ
+
+143
+00:10:58,640 --> 00:11:02,380
+average الخاصة بالـ Accuracy اللي موجودة. هيك عشان
+
+144
+00:11:02,380 --> 00:11:06,260
+هيك بنقول إن فعليا إن الـ cross validation more
+
+145
+00:11:06,260 --> 00:11:09,540
+stable. لكن فعليا لو أنا كانت عندي الـ data set  كبيرة،
+
+146
+00:11:09,540 --> 00:11:14,170
+data set كبيرة كبيرة، زي ما بتكلم 100 ألف
+
+147
+00:11:14,170 --> 00:11:17,890
+record أو 50 ألف record، ورحت والله أنا
+
+148
+00:11:17,890 --> 00:11:21,910
+أخذت منها 30%، وعارف أنه في استخدام الـ stratified
+
+149
+00:11:21,910 --> 00:11:26,970
+sampling عشان أضمن إن في عندي balance في الـ data
+
+150
+00:11:26,970 --> 00:11:32,870
+اللي موجودة عندي، ما بين الـ different classes
+
+151
+00:11:32,870 --> 00:11:36,790
+أو different labels، بتديني نتيجة برضه موثوقة، و
+
+152
+00:11:36,790 --> 00:11:40,340
+ممكن تكون أسرع من الـ cross validation. تمام، بغض
+
+153
+00:11:40,340 --> 00:11:44,240
+النظر، الطريقة اللي اتبعتها كانت الـ K-fold cross
+
+154
+00:11:44,240 --> 00:11:48,000
+-validation. طبعا الـ K نرمز لها هنا، اللي هي عدد الـ
+
+155
+00:11:48,000 --> 00:11:53,000
+folds اللي أنت بدك تقسم فيها الـ data set. يعني أنا لما
+
+156
+00:11:53,000 --> 00:11:55,800
+أقول لك مثلا، بالمثال اللي موجود عندنا على الـ slide،
+
+157
+00:11:55,800 --> 00:12:01,220
+فعليا أنا خمسة، معناته في كل part بيمثل 20% في
+
+158
+00:12:01,220 --> 00:12:03,820
+الـ المئة، 20% testing، و 80%
+
+159
+00:12:03,820 --> 00:12:07,020
+training. لاحظوا إن أنا زي مرحلة الـ training ممكن
+
+160
+00:12:07,020 --> 00:12:13,360
+أقوم بقسمها لـ عشرة، 10% testing، و 90% training. في حالتي أنا حاولت أرسمها أربعة،
+
+161
+00:12:13,360 --> 00:12:17,000
+20% testing، و 75%
+
+162
+00:12:17,000 --> 00:12:20,740
+training. فحسب الـ data أو حسب تقسيمك للـ data اللي
+
+163
+00:12:20,740 --> 00:12:25,300
+موجودة عندك. تمام. من الشغلات المهمة جدا اللي لازم
+
+164
+00:12:25,300 --> 00:12:29,730
+نستوعبها، أنا أصح، اللي هي الـ classification في الـ
+
+165
+00:12:29,730 --> 00:12:33,230
+classification model، الـ confusion matrix. طبعا عشان
+
+166
+00:12:33,230 --> 00:12:36,710
+تبسيط المفهوم، هشتغل فقط على two classes، على binary
+
+167
+00:12:36,710 --> 00:12:42,890
+classification، class A و class B، أو class 1 (C1) و
+
+168
+00:12:42,890 --> 00:12:47,710
+C2، اللي هما ممكن يكونوا positive و negative، يعني
+
+169
+00:12:47,710 --> 00:12:52,010
+لو أنا افترضت أن class 1 هذا positive وهذا negative،
+
+170
+00:12:52,010 --> 00:12:58,050
+positive و negative. الآن من اسمها confusion matrix،
+
+171
+00:12:58,050 --> 00:13:05,790
+مصفوفة
+
+172
+00:13:05,790 --> 00:13:08,890
+الـلخمة، أو مصفوفة التشتت، أو سميها زي ما بدك، أنا
+
+173
+00:13:08,890 --> 00:13:19,010
+بستخدمها لإنه فعليا بتديني بشكل واضح، وين الـ data
+
+174
+00:13:19,010 --> 00:13:26,590
+set تبعتي راحت. الفكرة أنه الآن لو أنا قلت أن
+
+175
+00:13:26,590 --> 00:13:32,910
+الـ matrix طبعا هذه الـ matrix بنتبتها دائما عشان ما
+
+176
+00:13:32,910 --> 00:13:36,010
+نعملش مشكلة عند البعض، لكن حتى لو اختلفت الـ matrix
+
+177
+00:13:36,010 --> 00:13:42,370
+كتير، أنا بعمل لها transpose، يعني ممكن أعمل
+
+178
+00:13:42,370 --> 00:13:
+
+223
+00:16:58,780 --> 00:17:02,480
+طيب بالنسبة للـ class الثاني هو عملها prediction
+
+224
+00:17:02,480 --> 00:17:08,500
+على إنها class one يعني هو قال إنها positive لكنه
+
+225
+00:17:08,500 --> 00:17:12,570
+الـ prediction هذا خطأ. ليش؟ لأنها في الحقيقة تنتمي
+
+226
+00:17:12,570 --> 00:17:16,250
+لـ class 2 اللي هو الـ negative فهي فعلياً negative
+
+227
+00:17:16,250 --> 00:17:19,710
+ولكن عملها prediction على إنها positive فهي false
+
+228
+00:17:19,710 --> 00:17:25,350
+positive تمام؟ وتبقى عندها الـ true negative هي
+
+229
+00:17:25,350 --> 00:17:30,110
+class 2، صنفتها على class 2 صحيح؟ وبالتالي هي عبارة
+
+230
+00:17:30,110 --> 00:17:33,990
+عن true negative. يعني فعلياً لو أنا بدي أفكر
+
+231
+00:17:33,990 --> 00:17:37,630
+بالجدول أو بـ confusion matrix لما أنا بدي أنشئها
+
+232
+00:17:37,630 --> 00:17:45,950
+بشكل صحيح. أي الجدول هو
+
+233
+00:17:45,950 --> 00:17:51,250
+فيه
+
+234
+00:17:51,250 --> 00:18:01,250
+مساحة بالـ powerpoint ولا ما فيش eraser
+
+235
+00:18:01,250 --> 00:18:05,810
+تمام
+
+236
+00:18:05,810 --> 00:18:08,490
+رجعها لشيء
+
+237
+00:18:17,740 --> 00:18:23,380
+الآن احنا متفقين هنا أن أنا فعلياً هنا عند الـ
+
+238
+00:18:23,380 --> 00:18:27,400
+actual والأعمدة الـ predicted
+
+239
+00:18:34,130 --> 00:18:40,910
+C2، C1، و C2 حسب الرسمة اللي موجودة. عندها حاجة
+
+240
+00:18:40,910 --> 00:18:46,930
+إعادة. الآن كم واحدة فعلياً بتنتمي لـ class one وعملها
+
+241
+00:18:46,930 --> 00:18:49,590
+prediction في الـ class one صحيح، في الـ positive
+
+242
+00:18:49,590 --> 00:18:55,550
+واحدة، اثنتين، ثلاث، أربع، تمام
+
+243
+00:18:55,550 --> 00:19:02,410
+طيب، وهذول هذيه
+
+244
+00:19:02,410 --> 00:19:06,880
+وهذه، هم أصلاً negative، class 2، لكن عمل لهم prediction
+
+245
+00:19:06,880 --> 00:19:14,840
+هان، تمام. نجي للحالة الـ negative، هي بتنتمي لـ class 1
+
+246
+00:19:14,840 --> 00:19:18,280
+لكن عمل لها prediction في class 2 اللي هم الخضر اللي
+
+247
+00:19:18,280 --> 00:19:22,340
+هان، اثنين لو
+
+248
+00:19:22,340 --> 00:19:27,140
+عديت الخضر: اثنين، أربعة، ستة، هي المجموع، وهان لازم
+
+249
+00:19:27,140 --> 00:19:33,850
+يكون هنا في عندي… عشان يكتمل عدد 2.68، فهذه هي
+
+250
+00:19:33,850 --> 00:19:37,970
+فعلياً الـ confusion matrix اللي أنا راح اشتغل عليها، تمام
+
+251
+00:19:37,970 --> 00:19:41,590
+الآن الـ accuracy، كون أن أنا حسبت الـ confusion
+
+252
+00:19:41,590 --> 00:19:46,870
+matrix، اتفقنا أن الـ accuracy هي عبارة عن الـ ratio
+
+253
+00:19:46,870 --> 00:19:56,030
+عدد، نسبة الـ test table اللي صنفتها بشكل صحيح. مين هم؟
+
+254
+00:19:56,030 --> 00:20:02,900
+الـ true positive والـ true negative، ولا لأ؟ تمام
+
+255
+00:20:02,900 --> 00:20:06,700
+معناته الـ true positive صحيحة، والـ true negative
+
+256
+00:20:06,700 --> 00:20:11,780
+صحيحة. هدول صحيحات، فبجمع هذه وهذه على كل عناصر
+
+257
+00:20:11,780 --> 00:20:14,300
+المصفوفة اللي موجودة عندي، بكون حصلت على الـ
+
+258
+00:20:14,300 --> 00:20:18,620
+accuracy على كل predict، على الـ cardinality تبعت الـ
+
+259
+00:20:18,620 --> 00:20:23,700
+test set اللي أنا باتكلم عليها. واضحة كمان مرة، الـ
+
+260
+00:20:23,700 --> 00:20:28,580
+accuracy هي عبارة عن نسبة الـ rows أو الـ tables
+
+261
+00:20:28,580 --> 00:20:32,600
+اللي في الـ test set اللي نجح الـ classifier فيه
+
+262
+00:20:32,600 --> 00:20:39,260
+تصنيفها على حجم الـ test set اللي موجودة عندي، تمام
+
+263
+00:20:39,260 --> 00:20:44,780
+بالمثال السابق، لو أنا بدي أرجع هان، الـ prediction
+
+264
+00:20:44,780 --> 00:20:54,000
+تبعي عبارة عن الـ… هان، عفواً، أربعة
+
+265
+00:20:54,000 --> 00:21:03,510
+زائد 6 على 15، لأن كل الـ data 6 بعد 15 element
+
+266
+00:21:03,510 --> 00:21:09,470
+عديناها قبل شوية، يعني بين جثتين 12 على 15، لو أنا
+
+267
+00:21:09,470 --> 00:21:14,970
+بتتكلم على 3، بتتكلم على 4، على 5، معناته أنا بتتكلم
+
+268
+00:21:14,970 --> 00:21:19,790
+جايب حدود الـ accuracy تبعي 80%
+
+269
+00:21:22,870 --> 00:21:26,790
+تمام. طبعاً الـ accuracy عكسها في عندها الـ error rate
+
+270
+00:21:26,790 --> 00:21:29,650
+طبعاً ممكن في عندي مصطلح ثاني ممكن أستخدمه مع الـ
+
+271
+00:21:29,650 --> 00:21:35,190
+accuracy اللي هو إيش؟ الـ recognition rate، وطبعاً
+
+272
+00:21:35,190 --> 00:21:38,070
+برضه من المصطلحات المستخدمة accuracy أو
+
+273
+00:21:38,070 --> 00:21:41,090
+recognition rate نفس المعنى. في عندي الـ error rate
+
+274
+00:21:41,090 --> 00:21:44,710
+الـ error rate طبعاً، أعلى نسبة اللي هي واحد- صحيح
+
+275
+00:21:44,710 --> 00:21:49,410
+يعني احنا قبل شوية كانت عندي 80%، 5 على 4 يعني 8 من
+
+276
+00:21:49,410 --> 00:21:55,830
+10، الـ error rate تساوي واحد ناقص 8 من 10 وتساوي
+
+277
+00:21:55,830 --> 00:22:01,810
+point اتنين من عشرة أو بين جثتين اللي هي عشرين في المئة
+
+278
+00:22:01,810 --> 00:22:05,150
+يعني هذا مقدار الـ error rate أو بين جثتين الـ error
+
+279
+00:22:05,150 --> 00:22:08,990
+rate زي ما احنا شايفين هنا هي عبارة عن الـ false
+
+280
+00:22:08,990 --> 00:22:11,250
+positive والـ false negative
+
+281
+00:22:14,470 --> 00:22:17,770
+له فعلياً اللي أخطأ فيه تصنيفهم، اللي أخطأ فيه
+
+282
+00:22:17,770 --> 00:22:21,290
+تصنيفهم. طبعاً، جامعة الخير، هنا في شغل مهم جداً. طيب
+
+283
+00:22:21,290 --> 00:22:23,610
+هذا يا دكتور في حالة الـ binary classification، لو
+
+284
+00:22:23,610 --> 00:22:26,490
+حد اتقرح على أي سؤال وقال يا دكتور هذا في حالة الـ
+
+285
+00:22:26,490 --> 00:22:30,910
+binary classification، طيب شوف حالة الـ multiple
+
+286
+00:22:30,910 --> 00:22:33,390
+class، يعني لو كانت المصفوفة تبعي الـ confusion
+
+287
+00:22:33,390 --> 00:22:42,830
+matrix تبعي ثلاثة في ثلاثة، إيش
+
+288
+00:22:42,830 --> 00:22:48,350
+ممكن نعمل… خلينا نعتمد نفس التوزيع السابق، الـ
+
+289
+00:22:48,350 --> 00:22:54,910
+actual في الأعمدة، الـ actual في الصفوف، والـ
+
+290
+00:22:54,910 --> 00:23:00,270
+predicted في الأعمدة. معناته هذه راح تكون true
+
+291
+00:23:00,270 --> 00:23:07,270
+positive أو هذه false
+
+292
+00:23:07,270 --> 00:23:10,740
+negative، فالس…
+
+293
+00:23:27,780 --> 00:23:31,820
+بوزيتف لكن حط لي إياهم false negative، يعني هم جالسين
+
+294
+00:23:31,820 --> 00:23:35,360
+… هو يفسر… يعني بفهم هيكل، يعني C2 و C3 not
+
+295
+00:23:35,360 --> 00:23:39,200
+positive، يعني negative، فخذ لي إياهم هان كمان في الـ
+
+296
+00:23:39,200 --> 00:23:47,040
+class الثاني، راح تكون هذه true negative، وهذه false
+
+297
+00:23:47,040 --> 00:23:55,580
+positive، false positive لـ C1، عفواً، عفواً هي C2 وهي
+
+298
+00:23:55,580 --> 00:24:06,300
+C3، وهنا راح تكون false negative، false
+
+299
+00:24:06,300 --> 00:24:09,540
+negative، false negative، false negative، false negative،
+
+300
+00:24:09,540 --> 00:24:11,220
+false negative، false negative، false negative، false
+
+301
+00:24:11,220 --> 00:24:12,280
+negative، false negative، false negative، false
+
+302
+00:24:12,280 --> 00:24:13,540
+negative، false negative، false negative، false negative،
+
+303
+00:24:13,540 --> 00:24:16,920
+false negative، false negative، false negative، false
+
+304
+00:24:16,920 --> 00:24:25,260
+negative، false negative، false negative، هذا الكلام الـ Accuracy
+
+305
+00:24:25,260 --> 00:24:31,800
+ممتازة في حالة أن العناصر أو الـ class is balanced
+
+306
+00:24:31,800 --> 00:24:35,300
+يعني بين جثتين سبعة وثمانية، جرب من بعض خمسين،
+
+307
+00:24:35,300 --> 00:24:40,020
+خمسين، ثلاثين، ثلاثين، ثلاثين، أو خمسين خمسين خمسين في
+
+308
+00:24:40,020 --> 00:24:43,500
+حالة الـ IRIS data set، الـ balance بين الـ classes
+
+309
+00:24:43,500 --> 00:24:47,680
+موجودة. لكن فعلياً لما أنا بتكلم على الـ diseases أو
+
+310
+00:24:47,680 --> 00:24:51,060
+في اللي بتكلم على الـ fraud detection، عمليات النصب
+
+311
+00:24:51,060 --> 00:24:55,620
+في، بوضع الـ classes in balance، شو يعني in
+
+312
+00:24:55,620 --> 00:24:58,480
+balance؟ أنه عدد الـ elements في الكل، وعدد الـ rows
+
+313
+00:24:58,480 --> 00:25:05,320
+مع كل class غير متساوية. طبعاً أجيب المثال أوضح، الله
+
+314
+00:25:05,320 --> 00:25:09,100
+يعافيكم كم مرة وأهليكم جميعاً، لأن كم واحد بنعمل له
+
+315
+00:25:09,100 --> 00:25:15,010
+فحص كورونا حول العالم… مئات الألوف، عشرات الألوف، بلاش
+
+316
+00:25:15,010 --> 00:25:19,370
+مئات الألوف، كم واحد بتثبت معه الحالة؟ أقل كثير
+
+317
+00:25:19,370 --> 00:25:26,350
+وبالتالي عدد الـ negative أكبر بكثير من عدد الـ
+
+318
+00:25:26,350 --> 00:25:32,210
+positive. ممتاز. طيب لو أنا سألت سؤال: مين أختار؟ واحد
+
+319
+00:25:32,210 --> 00:25:35,490
+ما عندهوش فيروس وقال للـ system لأ، أن هذا عنده فيروس
+
+320
+00:25:35,490 --> 00:25:41,760
+كورونا، ولا واحد عنده فيروس كورونا والـ system قال له
+
+321
+00:25:41,760 --> 00:25:48,480
+إنه ما عندهوش؟ شو رأيكم؟ يعني نسبة الخطأ مع الـ
+
+322
+00:25:48,480 --> 00:25:50,960
+positive ولا الخطأ مع الـ negative هي الأخطر
+
+323
+00:25:50,960 --> 00:25:55,820
+بالنسبة لنا. كلامك صح، أو كلامك صح الآن، لأنه احنا
+
+324
+00:25:55,820 --> 00:26:01,240
+فعلياً لما أخطأ الـ system وقال له إنه هذا negative
+
+325
+00:26:02,050 --> 00:26:06,030
+false negative، كانت مصيبة بالنسبة لي، لأن هذا
+
+326
+00:26:06,030 --> 00:26:10,150
+الإنسان سيتعدي
+
+327
+00:26:10,150 --> 00:26:13,490
+الناس، وبالتالي المرض سينتشر، لأنه مش معنى ونهيك عن
+
+328
+00:26:13,490 --> 00:26:17,650
+الأضرار الصحية اللي تحدث معه. لكن لو واحد negative
+
+329
+00:26:17,650 --> 00:26:21,290
+ما عندهوش المرض، والـ system قال إنه عنده المرض، إيش
+
+330
+00:26:21,290 --> 00:26:24,990
+هنعمل له؟ هناخذه، نحطه في الـ health care أو في الحجر
+
+331
+00:26:24,990 --> 00:26:30,540
+الصحي، وبعدين ندي له عناية صحية حسب حالته. في ضرر
+
+332
+00:26:30,540 --> 00:26:34,180
+في الموضوع؟ حتماً ما فيش ضرر. وبالتالي لما بكون في الـ
+
+333
+00:26:34,180 --> 00:26:39,220
+class imbalance، الـ accuracy تبعي مش صحيحة، ليش؟
+
+334
+00:26:39,220 --> 00:26:43,200
+أو بتبقى، عفواً، غير معبرة بشكل صحيح، لأن لو تخيلت
+
+335
+00:26:43,200 --> 00:26:51,820
+أن هنا أنا عدد العناصر بدي أشتغل هيك، أن عدد
+
+336
+00:26:51,820 --> 00:26:54,260
+العناصر اللي أنا بدي أفحصها 100 ألف
+
+337
+00:26:58,340 --> 00:27:06,760
+وفعلياً، أو الـ data set تبعي للهيئة كلها كان في
+
+338
+00:27:06,760 --> 00:27:14,140
+عندي مثلاً عشرة آلاف positive، و
+
+339
+00:27:14,140 --> 00:27:22,600
+تسعين ألف negative، ولما عملت prediction، اجى قال
+
+340
+00:27:22,600 --> 00:27:31,710
+لي والله من العشرة آلاف هدول أنا جبت تسعة آلاف صح، و
+
+341
+00:27:31,710 --> 00:27:46,110
+ألف ما جبتهوش. في المقابل، هذا الألف صنفته هان، أو
+
+342
+00:27:46,110 --> 00:27:49,210
+بالأحرى قال لي أنا ما أخطأت ولا حاجة هان، أو خلينا
+
+343
+00:27:49,210 --> 00:27:54,910
+نقول أخطأ، أخطأ لي بألف هان، وجاب لي هان ثمانين ألف
+
+344
+00:28:00,700 --> 00:28:08,680
+فعلياً الـ accuracy تبعي راح تكون تسعة وثمانين ألف
+
+345
+00:28:08,680 --> 00:28:15,680
+على مئة
+
+346
+00:28:15,680 --> 00:28:20,300
+ألف، صح؟ فالنسبة تبعي تسعة وثمانين في المئة، الـ
+
+347
+00:28:20,300 --> 00:28:24,560
+accuracy عالية
+
+348
+00:28:24,560 --> 00:28:29,040
+وممتازة، وما شاء الله عليها، لكنها تحمل في طياتها
+
+349
+00:28:29,040 --> 00:28:37,840
+خطورة شديدة جداً، مع من… مع الناس هذول، مع
+
+350
+00:28:37,840 --> 00:28:42,880
+الله، هان، تمام. وبالتالي الـ Accuracy بطلت عندي مجدية
+
+351
+00:28:42,880 --> 00:28:45,400
+لأن الـ 98% محدش يقول عن نسبة منخفضة، بالعكس
+
+352
+00:28:45,400 --> 00:28:49,080
+نسبة عالية، لكنه في عندي مشكلة في الـ evaluation
+
+353
+00:28:49,080 --> 00:28:52,980
+تمام. وبالتالي أنا ممكن أصبح أدور على شغل اسمها الـ
+
+354
+00:28:52,980 --> 00:28:57,220
+sensitivity، الحساسية، وطبعاً هنا بتكلم على الـ true
+
+355
+00:28:57,220 --> 00:29:02,960
+positive rate، الـ true positive rate، اللي هي
+
+356
+00:29:02,960 --> 00:29:11,720
+نسبة 9000 على العشرة آلاف. وكذلك في عندي الـ
+
+357
+00:29:11,720 --> 00:29:18,900
+specificity، التخصيص، اللي هي نسبة الـ true negative
+
+358
+00:29:18,900 --> 00:29:23,960
+rate، جد، عشان أفصل أنا… هو الـ accuracy بعد ما حصلت
+
+359
+00:29:23,960 --> 00:29:30,060
+عليها، مين كان فيه نسبته أعلى عشان أضيفه، ومش بس هيك
+
+360
+00:29:30,060 --> 00:29:33,520
+جايلي، ممكن أنا أتكلم على other metrics، وهذه أهم
+
+361
+00:29:33,520 --> 00:29:39,120
+اللي بنسميها احنا الـ precision
+
+362
+00:29:44,430 --> 00:29:47,210
+الـ precision أو الـ exactness هي عبارة عن الـ
+
+363
+00:29:47,210 --> 00:29:53,310
+ratio لمجموعة الـ tables
+
+364
+00:29:53,310 --> 00:29:58,630
+الـ classifier صنفها على أنهم positive وهم فعلياً
+
+365
+00:29:58,630 --> 00:30:03,190
+positive، نسبة
+
+366
+00:30:03,190 --> 00:30:07,070
+الـ labelled اللي جاء عليها positive وهي فعلياً
+
+367
+00:30:07,070 --> 00:30:09,810
+positive على كل الـ actual positive اللي موجودة
+
+368
+00:30:09,810 --> 00:30:12,390
+عندها، وين الـ actual positive؟
+
+369
+00:30:18,800 --> 00:30:22,720
+الـ actual هو اللي موجود في جامعة الخير في الأعمدة،
+
+370
+00:30:22,720 --> 00:30:37,440
+في العمود، في الصفوف. الآن الـ true positive هي جل…
+
+371
+00:30:37,440 --> 00:30:40,720
+الـ true positive على كل العناصر، صنفتها على
+
+372
+00:30:40,720 --> 00:30:44,220
+إنها positive، عشان أجيب نسبة الـ actual positive
+
+373
+00:30:44,220 --> 00:30:49,230
+الحقيقية اللي موجودة عندها، as positive are actually
+
+374
+00:30:49,230 --> 00:30:53,750
+positive، نسبة الـ positive الحقيقية. فهنا لما أتكلم
+
+375
+00:30:53,750 --> 00:30:57,270
+عن الـ precision أو الـ exactness، بتكلم عليها عناصر
+
+376
+00:30:57,270 --> 00:31:02,330
+العمود الأول، تمام؟ لما بأجي بتكلم على الـ recall
+
+377
+00:31:02,330 --> 00:31:07,550
+أو الـ completeness، بتكلم فعلياً على نسبة الـ
+
+378
+00:31:07,550 --> 00:31:11,130
+positive doubles، واللي فعلياً تم تصنيفها على إنها
+
+379
+00:31:11,130 --> 00:31:15,630
+positive، نسبة الـ positive doubles اللي صنفت على
+
+380
+00:31:15,630 --> 00:31:19,890
+إنها positive بشكل صحيح. وين الـ positive؟ هي الصف
+
+381
+00:31:19,890 --> 00:31:24,810
+الأول اللي
+
+382
+00:31:24,810 --> 00:31:29,090
+احنا قلنا عليها sensitivity قبل لحظات، وبالتالي الـ
+
+383
+00:31:29,090 --> 00:31:34,430
+TP بتروح الـ true
+
+384
+00:31:34,430 --> 00:31:39,550
+positive على المجموع اللي موجود عندي الـ TP والـ FN
+
+385
+00:31:39,550 --> 00:31:45,670
+تمام. ما عندي الـ F… ما عندي الـ … بما أن في عندي
+
+386
+00:31:45,670 --> 00:31:50,730
+الـ precision والـ recall، هدول متغيرات مختلفة. قال
+
+387
+00:31:50,730 --> 00:31:54,210
+في ناس فكرت جالكس نعملهم combination ما بين
+
+388
+00:31:54,210 --> 00:32:00,350
+الـ precision والـ recall في metric واحد، وسموه ليا
+
+389
+00:32:00,350 --> 00:32:08,530
+الـ F-measure، ودمجوا فيه الـ precision والـ recall
+
+390
+00:32:08,530 --> 00:32:12,710
+وكان هو يساوي 2 ضرب الـ precision ضرب الـ recall على
+
+391
+00:32:12,710 --> 00:32:15,790
+مجموع الـ recall والـ precision، أو بين قوسين هي الـ
+
+392
+00:32:15,790 --> 00:32:20,730
+F1، وهذا أنا بأستخدمه لما عادة بأفكر بالمقارنة ما
+
+393
+00:32:20,730 --> 00:32:24,740
+بين two different classifiers. الآن أنا في عندي two
+
+394
+00:32:24,740 --> 00:32:27,500
+different classifiers، وبدي أقارن بين الأداء تبعهم.
+
+395
+00:32:27,500 --> 00:32:30,740
+واحد ممكن يتفكر بالـ accuracy، الـ accuracy ممكن تكون
+
+396
+00:32:30,740 --> 00:32:34,420
+متساوية ما بين الإثنين، ما بضيش ممكن أساوي… ممكن أروح
+
+397
+00:32:34,420 --> 00:32:37,940
+على اتجاه الـ F-measure اللي أنا… ممكن تكون طبعاً أنتم
+
+398
+00:
+
+445
+00:36:53,820 --> 00:36:58,960
+إنه خلت الـ target تبعتي No وقولت
+
+446
+00:36:58,960 --> 00:37:01,600
+أنا بدي أحسب الـ recall و الـ precision لاحظوا الـ
+
+447
+00:37:01,600 --> 00:37:05,530
+accuracy ما اتغيرتش لكن أنا عيد ترتيب الأعمدة يعني
+
+448
+00:37:05,530 --> 00:37:07,930
+برينج وستين صار اهتمامي هنا highly true positive
+
+449
+00:37:07,930 --> 00:37:11,370
+لاحظوا أن الـ precision تبعتي جدّاش عالية صارت و الـ
+
+450
+00:37:11,370 --> 00:37:14,910
+recall تبعتي جدّاش عالية على كل مقالة زي ما قلنا الـ
+
+451
+00:37:14,910 --> 00:37:18,470
+perfect value تبعتنا هنا حكينا أن الـ perfect أو الـ
+
+452
+00:37:18,470 --> 00:37:23,990
+score is one كذلك مع الـ precision، الـ perfect score
+
+453
+00:37:23,990 --> 00:37:28,290
+هو 1، وبهيك أنا بكون بدي أعمل evaluation للـ classes
+
+454
+00:37:28,290 --> 00:37:31,650
+اللي موجودة عندها وبالتالي أنا بدي انتبه دائماً للـ
+
+455
+00:37:31,650 --> 00:37:34,710
+class اللي موجودة بالنسبة للـ code اللي له علاقة بالـ
+
+456
+00:37:34,710 --> 00:37:39,550
+بايثون. أنا هنا رحت أعمل import للـ data set كان
+
+457
+00:37:39,550 --> 00:37:43,970
+المعتاد على نفس المثال السابق، رحت أعمل import
+
+458
+00:37:43,970 --> 00:37:47,210
+عشان أعمل split للـ data set، والمفروض أن أنتم هاي
+
+459
+00:37:47,210 --> 00:37:51,590
+جربتوها من خلال الـ assignment اللي سلمتوه، فأنا حصلت
+
+460
+00:37:51,590 --> 00:37:55,850
+على الـ training set اللي هنا من خلال الـ split هذه
+
+461
+00:37:55,850 --> 00:37:59,790
+train test split جسمت لي أو أدتني نتيجة، أدتني four
+
+462
+00:37:59,790 --> 00:38:05,010
+different set، الـ X train و الـ label تبعتها
+
+463
+00:38:08,770 --> 00:38:17,890
+الـ Y للـ labels و X للـ attributes و الـ test text test
+
+464
+00:38:17,890 --> 00:38:21,470
+و الـ Y test، طبعاً قلت له هنا تلاتين في المئة نسبة
+
+465
+00:38:21,470 --> 00:38:25,010
+الـ test، تلاتين في المئة، وطبعاً هضل الباقي للتدريب
+
+466
+00:38:26,020 --> 00:38:29,600
+من الـ target data، واستدعيت Naive Bayes على سبيل
+
+467
+00:38:29,600 --> 00:38:36,180
+المثال، ورحت وقلت جوسان Naive Bayes، استدعيت الـ
+
+468
+00:38:36,180 --> 00:38:40,460
+constructor، قلت له روح بنيت model، وقلت له اعمل fit
+
+469
+00:38:40,460 --> 00:38:46,280
+اللي بتعمل hand training، وقلنا
+
+470
+00:38:46,280 --> 00:38:53,000
+في Naive Bayes بروح ببنيني جدول الاحتمالات، بعد ذلك
+
+471
+00:38:53,000 --> 00:38:59,860
+قمت بالتفكير في مجموعة سميته Y-predict، هذا هو
+
+472
+00:38:59,860 --> 00:39:05,200
+النتائج الـ model.predict، ودّيته X test بالكامل
+
+473
+00:39:05,200 --> 00:39:09,840
+لاحظت أنني سميتها Y-predict، أنا عندي الـ test هي الـ
+
+474
+00:39:09,840 --> 00:39:14,020
+label تبعتها موجودة هنا Y-test، فروحت وحصلت عليها
+
+475
+00:39:14,020 --> 00:39:17,280
+تمام، صارت في عندي الـ predicted وصارت عندي موجودة
+
+476
+00:39:17,280 --> 00:39:22,560
+من الـ actual label، فالآن أنا قاعد بقى أشتغل، رحت
+
+477
+00:39:22,560 --> 00:39:25,980
+عملت import، بدي أجيب الـ matrix from sklearn.metrics
+
+478
+00:39:25,980 --> 00:39:29,080
+import الـ matrix، والـ matrix هي فيها كل حاجة، فيها
+
+479
+00:39:29,080 --> 00:39:32,440
+الـ accuracy score، وطبعاً كل الـ methods في الـ matrix
+
+480
+00:39:32,440 --> 00:39:36,960
+بدها مني الـ y predicted و الـ y test، الـ y test هي
+
+481
+00:39:36,960 --> 00:39:40,840
+موجودة، أنا حصلت اللي هي فعلياً الـ actual، و الـ y
+
+482
+00:39:40,840 --> 00:39:43,600
+predicted هي الموجودة عندها، فلما أنا قلت له الـ
+
+483
+00:39:43,600 --> 00:39:46,300
+accuracy score ده، نسبة الـ confusion matrix طبعاً
+
+484
+00:39:46,300 --> 00:39:49,560
+لها، و الـ classifier أو الـ classification report
+
+485
+00:39:50,850 --> 00:39:55,090
+بتعطيني الـ f-measure و الـ precision و الـ recall لكل class
+
+486
+00:39:55,090 --> 00:40:00,790
+موجودة عندي، وهيك أنهينا أو ختمنا chapter للـ
+
+487
+00:40:00,790 --> 00:40:04,470
+classification، بتمنى تكون الشروحات واضحة، إذا في أي
+
+488
+00:40:04,470 --> 00:40:08,450
+استفسار لازم يكون من خلال الـ model أو الـ forum
+
+489
+00:40:08,450 --> 00:40:12,450
+اللي موجود عندي هنا، آخر شغلة مطلوب منها الـ
+
+490
+00:40:12,450 --> 00:40:16,190
+assignment البسيط هذا، الـ assignment هذا بدو يعمل
+
+491
+00:40:16,190 --> 00:40:18,650
+مقارنة بين three different classifiers
+
+492
+00:40:21,320 --> 00:40:26,020
+أخذنا أربعة classifiers كي نتعرف على الـ K-nearest
+
+493
+00:40:26,020 --> 00:40:28,500
+neighbour، الـ Naive Bayes، الـ decision tree و
+
+494
+00:40:28,500 --> 00:40:31,840
+الـ Multilayer Perceptron، الـ classifier اللي هو
+
+495
+00:40:31,840 --> 00:40:34,860
+تبع الـ neural network، وأنا بدي أقارن بينهم بناءً
+
+496
+00:40:34,860 --> 00:40:39,170
+على الـ accuracy، الـ Precision، الـ Recall، والـ F-
+
+497
+00:40:39,170 --> 00:40:43,310
+measure، طبعاً أنتم عندكم أو أنتم عندكم، كلّ عندكم data set
+
+498
+00:40:43,310 --> 00:40:47,950
+للـ classification، بدّكم تطبقوا الـ different classifiers
+
+499
+00:40:47,950 --> 00:40:52,230
+هدول على نفس الـ data set، على نفس الـ data set، و
+
+500
+00:40:52,230 --> 00:40:55,030
+تقارنوا ما بين الـ accuracy و الـ precision و الـ
+
+501
+00:40:55,030 --> 00:40:59,480
+recall و الـ F-measure، طبعاً بقى تزودوني بالـ python
+
+502
+00:40:59,480 --> 00:41:02,200
+code اللي أنتم اعتمدتوا عليه أو اللي أنتم اعتمدتم عليه
+
+503
+00:41:02,200 --> 00:41:04,620
+طبعاً الشغل individual يا جماعة الخير مش groups
+
+504
+00:41:04,620 --> 00:41:08,960
+ممكن تتشاوروا، تعملوا discussion مع بعض لاحقاً، لكن
+
+505
+00:41:08,960 --> 00:41:13,140
+أنتم هتسلموني الشغل، اللي هتسلموني إياه شغلتين، الأولى
+
+506
+00:41:13,140 --> 00:41:17,000
+الـ python code اللي موجود، اثنين، بالإضافة لـ report
+
+507
+00:41:17,000 --> 00:41:20,440
+عن الـ experiment اللي أنتم اشتغلتوها أو اللي أنتم
+
+508
+00:41:20,440 --> 00:41:24,160
+اشتغلتموها، الـ experiment اللي بيقول لي شو .. شو اللي
+
+509
+00:41:24,160 --> 00:41:26,920
+.. على سبيل المثال، اللي اشتغل K-nearest neighbor
+
+510
+00:41:27,690 --> 00:41:31,070
+جدّاش الـ K اللي اعتمدتها، 4 ولا 5 ولا 7 ولا 8
+
+511
+00:41:31,070 --> 00:41:35,350
+لما اشتغلنا على Naive decision tree، استخدمت الـ
+
+512
+00:41:35,350 --> 00:41:38,110
+information gain ولا استخدمت الـ gain الـ
+
+513
+00:41:38,110 --> 00:41:41,130
+multilayer perceptron، لما أنتم استخدمتوه، جدّاش عدد الـ
+
+514
+00:41:41,130 --> 00:41:44,950
+input neuron تبعتكم، يعني بدي topology، وهنا بدي توضّحوا
+
+515
+00:41:44,950 --> 00:41:47,950
+لي توصفوا الـ experiment تبعتكم والنتيجة اللي طلعت
+
+516
+00:41:47,950 --> 00:41:51,710
+طبعاً لأ أخفيكم أنها كانت المفروض تسلم الأسبوع
+
+517
+00:41:51,710 --> 00:41:59,020
+الماضي، لكن قدر الله وماشاء فعل، الآن أنا رح أحمل و
+
+518
+00:41:59,020 --> 00:42:03,640
+رح أحط الـ assignment على الـ model، وبتمنى أنكم
+
+519
+00:42:03,640 --> 00:42:07,580
+تشتغلوا وتسلموا، وربنا يكتب لكم السلامة والعافية
+
+520
+00:42:07,580 --> 00:42:12,340
+دائماً أنتم وأهليكم أجمعين، والسلام عليكم ورحمة
+
+521
+00:42:12,340 --> 00:42:14,080
+الله وبركاته
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/t7uwWVN30g8_postprocess.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/t7uwWVN30g8_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..d85caa4a762410157583633e542856aa427a061a
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/t7uwWVN30g8_postprocess.srt
@@ -0,0 +1,2084 @@
+1
+00:00:02,230 --> 00:00:04,390
+بسم الله الرحمن الرحيم الصلاة والسلام على رسول
+
+2
+00:00:04,390 --> 00:00:08,590
+الله أهلا وسهلا بكم أخواني الطلاب و أخواتي
+
+3
+00:00:08,590 --> 00:00:15,370
+الطالبات سنستكمل اليوم في هذا التسجيل موضوع ال
+
+4
+00:00:15,370 --> 00:00:19,050
+classification model evaluation بعد أن اتعرفت على
+
+5
+00:00:20,110 --> 00:00:25,050
+هي عبارة عن تحديد الـ Membership لجروب أو لكتجوري
+
+6
+00:00:25,050 --> 00:00:30,070
+معروفة مسبقا و اتعرفت على مجموعة من ال classifiers
+
+7
+00:00:30,070 --> 00:00:33,690
+بدءا من ال kennerist neighbor واعتماده و شفنا انه
+
+8
+00:00:33,690 --> 00:00:36,610
+بيعتمد على الحساب على ال similarity distance
+
+9
+00:00:36,610 --> 00:00:42,550
+وحكينا انه بيعتمد عليها او بقارن او باستخدام
+
+10
+00:00:42,550 --> 00:00:47,110
+different distances زي ال including distance او ال
+
+11
+00:00:47,110 --> 00:00:52,600
+Manhattan distanceوتكلمنا على الـ Naive bias كـ
+
+12
+00:00:52,600 --> 00:00:57,280
+classifier وشوفنا كيف ال probability او كيف تم
+
+13
+00:00:57,280 --> 00:00:59,400
+حسبة ال probability او ال conditional probability
+
+14
+00:00:59,400 --> 00:01:05,100
+وانتقلنا بعد هي كان لموضوع ال decision tree وشوفنا
+
+15
+00:01:05,100 --> 00:01:08,920
+كيف بنينا ال decision tree مع بعض واخر classifier
+
+16
+00:01:08,920 --> 00:01:12,080
+كان ل neural network او ال multilinear perceptron
+
+17
+00:01:12,080 --> 00:01:16,200
+او ال classifier كان neural network الآن بعد ما
+
+18
+00:01:16,200 --> 00:01:20,480
+أنا بنيتالموديل هذا و اصبح عملية ال classification
+
+19
+00:01:20,480 --> 00:01:24,220
+مش لازم انا اعرف جدش عملية ال classification تبعتي
+
+20
+00:01:24,220 --> 00:01:28,320
+صح او كده فبتيجي عملية ال evaluation هان فعليا
+
+21
+00:01:28,320 --> 00:01:35,340
+عشان تقولي انا والله بدي اقيم العناصر اللي موجودة
+
+22
+00:01:35,340 --> 00:01:39,460
+عندى يعنى عفو مش العناصر بدي اقيم اداء ال
+
+23
+00:01:39,460 --> 00:01:42,260
+classifier اللي موجود عندى يعنى فلما احنا بنتكلم
+
+24
+00:01:42,260 --> 00:01:46,830
+على evaluation يعني ان انا بتتكلم علىتقييم فعلي
+
+25
+00:01:46,830 --> 00:01:52,610
+للـ classifier اللي موجود عندى و هذا هم فحوة
+
+26
+00:01:52,610 --> 00:01:56,490
+محاضرتنا لليوم أو في التسجيل هذا ان شاء الله تعالى
+
+27
+00:01:57,520 --> 00:02:00,740
+طبعا بحب اذكر فقط بداية ان اذكر بعض الشغلات
+
+28
+00:02:00,740 --> 00:02:04,660
+الأساسية قلنا من ال basic concept الخاص بال
+
+29
+00:02:04,660 --> 00:02:07,540
+classifier في عند مصطلح ال accuracy و قلنا ال
+
+30
+00:02:07,540 --> 00:02:11,280
+accuracy هي عبارة على قدرة ال classifier التنبؤ
+
+31
+00:02:11,280 --> 00:02:16,220
+بشكل صحيح و عادة بتمثل النسبة عدد ال prediction
+
+32
+00:02:16,220 --> 00:02:22,560
+الصحيح على كل predictions اللي سواها على كل عمليات
+
+33
+00:02:22,560 --> 00:02:26,700
+التنبؤ اللي سواها ال classifier اللي موجودة عندها
+
+34
+00:02:27,990 --> 00:02:31,930
+وبالتالي سنقول إن الـ Accuracy بتشير لعملية القدرة
+
+35
+00:02:31,930 --> 00:02:36,090
+للـ classifier إنه يعمل correct prediction of the
+
+36
+00:02:36,090 --> 00:02:39,950
+class label for unseen data وتكلمنا عن الـ Speed
+
+37
+00:02:39,950 --> 00:02:44,210
+قلنا إنها عبارة عن computational cost الخاصة بالـ
+
+38
+00:02:44,210 --> 00:02:47,870
+classifier لما تكلمنا عن computational cost
+
+39
+00:02:50,350 --> 00:02:54,410
+أنا بهمني الوقت اللي بده يستغرقه ال classifier
+
+40
+00:02:54,410 --> 00:02:58,350
+سواء في عملية ال training أو حتى في عملية ال
+
+41
+00:02:58,350 --> 00:03:05,870
+classification نفسها أو ال prediction نفسها عفوا و
+
+42
+00:03:05,870 --> 00:03:08,430
+اتكلمنا كذلك على ال robustness و قولنا ال
+
+43
+00:03:08,430 --> 00:03:12,170
+robustness هي عبارة عن القدرة القدرة ال classifier
+
+44
+00:03:12,170 --> 00:03:17,690
+على انه يعمل correct predictionلما يكون فيه عندي
+
+45
+00:03:17,690 --> 00:03:23,830
+أنا noisy data لما يكون فيه عندي noisy data ال بعد
+
+46
+00:03:23,830 --> 00:03:26,690
+هي تكلمنا على ال scalability وقلنا ال scalability
+
+47
+00:03:26,690 --> 00:03:32,970
+تشير إلى قدرة ال classifier على القدرة على ان انا
+
+48
+00:03:32,970 --> 00:03:39,410
+فعليا ابني classifier بشكل مجدي في حالة وجود
+
+49
+00:03:39,410 --> 00:03:43,780
+البياناتالضخمة اللي موجودة عندي و Interpretability
+
+50
+00:03:43,780 --> 00:03:49,000
+أو قدرة على تفسير أو على فهم العناصر أو فهم
+
+51
+00:03:49,000 --> 00:03:55,840
+الإيهاءات الصادرة أو المعلومات الصادرة عن ال
+
+52
+00:03:55,840 --> 00:03:58,200
+classifier اللي موجود و طبعا زي ما قولنا عملية
+
+53
+00:03:58,200 --> 00:04:01,440
+تفسيرها دايما عملية subjective حسب الأشخاص و حسب
+
+54
+00:04:01,440 --> 00:04:06,380
+ال difficulties اللي أنا بدي أقيمهافعليا عملية ال
+
+55
+00:04:06,380 --> 00:04:10,940
+evaluation لل classifiers أو ال classification
+
+56
+00:04:10,940 --> 00:04:19,340
+models عملية نوعا ما فيها نوع من الخداع
+
+57
+00:04:19,340 --> 00:04:25,640
+لكنها فعلا عملية ممكن تكون نوعا ما غير واضحة أو
+
+58
+00:04:25,640 --> 00:04:29,120
+فيها بعض الخبايا لازم الواحد ينتبه لها عشان هيك
+
+59
+00:04:29,120 --> 00:04:34,220
+بنقول نسميها tricky أو خداعةطبعاً لما نتكلم عن
+
+60
+00:04:34,220 --> 00:04:38,820
+evaluation أول evaluation أو أول metric ممكن يخطر
+
+61
+00:04:38,820 --> 00:04:44,260
+في بالي هي عبارة عن ال accuracy أول
+
+62
+00:04:44,260 --> 00:04:47,540
+metric ممكن يخطر في بالي في التقييم أو في ال
+
+63
+00:04:47,540 --> 00:04:51,820
+evaluation هي عبارة عن ال accuracy لكنها مش هي
+
+64
+00:04:51,820 --> 00:04:56,880
+الوحيدة طبعاً هنا لما نتكلم على ال accuracy معناته
+
+65
+00:04:56,880 --> 00:05:01,840
+أنا استخدم باعتمادي على test setأنا الـ training
+
+66
+00:05:01,840 --> 00:05:08,740
+set استخدمته في لحظة بناء
+
+67
+00:05:08,740 --> 00:05:13,480
+الموديل و ال test set جا دورها عشان أهي عبارة عن
+
+68
+00:05:13,480 --> 00:05:21,700
+unlabeled set و أنا بدي أعملها prediction وبناء
+
+69
+00:05:21,700 --> 00:05:25,640
+عليك بقيم ال accuracy في سؤال مهم جدا يا جماعة
+
+70
+00:05:25,640 --> 00:05:31,460
+الخيار هل ال test setهي عبارة عن labelled data أو
+
+71
+00:05:31,460 --> 00:05:36,140
+labelled set أو unlabelled set كمان مرة السؤال
+
+72
+00:05:36,140 --> 00:05:39,980
+بأطرحه الآن بقول هل ال test set هي عبارة عن
+
+73
+00:05:39,980 --> 00:05:44,040
+labelled set أو unlabelled set بين جثيم هل لازم
+
+74
+00:05:44,040 --> 00:05:50,820
+يكون لها label ولا مش لازم يكون لها label المفروض
+
+75
+00:05:51,690 --> 00:06:00,230
+الان تعمل pause للـ recording هذا وتحاول تفكر
+
+76
+00:06:00,230 --> 00:06:03,690
+بالجواب احنا بتذكر ان طرحنا خلال المحاضرات السابقة
+
+77
+00:06:03,690 --> 00:06:09,090
+الجواب الصحيح انه لازم تكون labelled لأن لو ماكانش
+
+78
+00:06:09,090 --> 00:06:12,190
+فيه label مش هقدر اعمل evaluation مش هقدر اعرف
+
+79
+00:06:12,190 --> 00:06:14,770
+جديش ال prediction الصحيح من ال prediction الخطأ
+
+80
+00:06:14,770 --> 00:06:18,550
+وبالتالي ال test set must be labelled
+
+81
+00:06:21,470 --> 00:06:24,250
+طبعا عندي الـ methods اللي انا ممكن استخدمها مع ال
+
+82
+00:06:24,250 --> 00:06:27,710
+classifier مع ال classification هان هي عبارة عن
+
+83
+00:06:27,710 --> 00:06:31,290
+مجموعة من ال .. ال method أو في عندي two methods
+
+84
+00:06:31,290 --> 00:06:36,010
+أساسيات أنا بستخدمهم عشان أتنبأ أو أقدر أعمل تقدير
+
+85
+00:06:36,010 --> 00:06:40,110
+لل accuracy الخاصة بال classifier في عندها ال
+
+86
+00:06:40,110 --> 00:06:44,590
+holdout method و ال holdout method بتعتمد على ال
+
+87
+00:06:44,590 --> 00:06:49,760
+random samplingو طبعا هنا فعليا انا بقى زي ما قلنا
+
+88
+00:06:49,760 --> 00:06:52,640
+سابقا و زي ما كان في ال assignment السابق انا
+
+89
+00:06:52,640 --> 00:06:57,160
+فعليا ال data set اللي موجودة عندها بغض النظر عن
+
+90
+00:06:57,160 --> 00:07:02,460
+حجمها جسمتها ل two partitions سبعين على سبيل
+
+91
+00:07:02,460 --> 00:07:09,500
+المثال في المية لل training و تلاتين في الميةكانت
+
+92
+00:07:09,500 --> 00:07:13,380
+للـ Testing هذه الميثود بسميها holdout method و
+
+93
+00:07:13,380 --> 00:07:18,700
+بجسم ال data set تبعتي ل training and test set و
+
+94
+00:07:18,700 --> 00:07:21,220
+بعدين الطريقة التانية اللي احنا بسميها ال cross
+
+95
+00:07:21,220 --> 00:07:24,500
+validation و ال cross validation هي عبارة عن مثل
+
+96
+00:07:24,500 --> 00:07:29,100
+كذلك موجودة غالبا معظم استخدامها لما بتكون ال data
+
+97
+00:07:29,100 --> 00:07:36,600
+set تبعتي حجمها قليل هروح بتفاصيلهم بشكل كويسطبعاً
+
+98
+00:07:36,600 --> 00:07:41,260
+لما أتكلم على cross validation طريقة ممتازة جداً
+
+99
+00:07:41,260 --> 00:07:46,160
+بحيث أنه أنا أعرض ال data set بالكامل في ال
+
+100
+00:07:46,160 --> 00:07:50,980
+training على أجزاء مختلفة و كذلك باختبر كل ال data
+
+101
+00:07:50,980 --> 00:07:54,900
+set و بطلع بالمتوسط اللي موجود لما أنا بتكلم على
+
+102
+00:07:54,900 --> 00:07:58,180
+cross validation بتكلم إن هي عبارة عن statistical
+
+103
+00:07:58,180 --> 00:08:02,270
+method تستخدممن أجل الـ evaluation للـ
+
+104
+00:08:02,270 --> 00:08:05,170
+generalization الـ generalization جماعة الخير
+
+105
+00:08:05,170 --> 00:08:10,470
+المقصود فيها هان ان انا بأتكلم قاعد على او بتكلم
+
+106
+00:08:10,470 --> 00:08:16,670
+على قدرة النظام على التنبؤ الصحيح هو اتعلم بناء
+
+107
+00:08:16,670 --> 00:08:22,070
+على ال training data الان انا بدأ اشوف فعليا كيف
+
+108
+00:08:22,070 --> 00:08:25,610
+أداء النظام او ده ال model اللي موجود عندي هان
+
+109
+00:08:25,910 --> 00:08:29,510
+فكلمة الـ model بيقدر يتعامل أو يكون أداء تبعه
+
+110
+00:08:29,510 --> 00:08:33,270
+بكون كويس مع unseen data معناته هو more general
+
+111
+00:08:33,270 --> 00:08:36,910
+more general يعني ما انبناش فقط من أو مكان مش
+
+112
+00:08:36,910 --> 00:08:40,830
+specific لل training data اللي استخدمناها بل
+
+113
+00:08:40,830 --> 00:08:44,790
+بالعكس هو شغال على general data set على أي data
+
+114
+00:08:44,790 --> 00:08:48,750
+set هيشتغلوا بكفاءة كويسة طبعا ال performance data
+
+115
+00:08:48,750 --> 00:08:50,730
+are more stable
+
+116
+00:08:55,210 --> 00:09:01,010
+using split طبعاً
+
+117
+00:09:01,010 --> 00:09:03,770
+اللي متكلم عن الـ cross validation نتكلم إنه ال
+
+118
+00:09:03,770 --> 00:09:07,690
+performance هذا أو خلنا نقول ال estimation تبعت ال
+
+119
+00:09:07,690 --> 00:09:11,330
+accuracy أو ال performance تبعت ال ال model هان
+
+120
+00:09:11,330 --> 00:09:16,410
+هتكون أكثر موثوقية أو أكثر ثباتاً ما إنه لو أنا
+
+121
+00:09:16,410 --> 00:09:20,690
+فعاليا قسمت ال data set ل training أو testing لأن
+
+122
+00:09:20,690 --> 00:09:25,360
+موضوع ال randomness بيعمل فعلا مشكلةحقيقية فالـ
+
+123
+00:09:25,360 --> 00:09:28,380
+cross validation بدل ما انا جسم ال data set
+
+124
+00:09:28,380 --> 00:09:35,340
+لمجمعتين فعليا انا بجسم ال data بشكل متكرر
+
+125
+00:09:35,340 --> 00:09:37,600
+repeatedly شو يعني؟
+
+126
+00:09:40,410 --> 00:09:44,890
+مفهومها أنه انا فعلياً بروح بأجسم افترض ان هذه
+
+127
+00:09:44,890 --> 00:09:49,890
+الخط ال data كل واحد من ال rows هاي بمثل ال data
+
+128
+00:09:49,890 --> 00:09:54,350
+set كاملة الفكرة فيها انه انا اجسمها لمجموعة من ال
+
+129
+00:09:54,350 --> 00:09:58,350
+fold وال fold هذه واحدة منهم تستخدم لل training
+
+130
+00:09:58,350 --> 00:10:06,460
+والباقي يستخدم لعفوا واحدة للتست والباقي يستخدم ال
+
+131
+00:10:06,460 --> 00:10:11,400
+lettering يعني تخيل لو انا قلت هي ال data set اللي
+
+132
+00:10:11,400 --> 00:10:14,560
+موجودة عندي سامحوني انا مش جادر اعمل control كتير
+
+133
+00:10:14,560 --> 00:10:17,420
+على ال mouse او على ال pen اللي موجود معاياها
+
+134
+00:10:18,550 --> 00:10:22,390
+جسمتها لأربع أجزاء فبشكل متكرر باجي بقول والله
+
+135
+00:10:22,390 --> 00:10:26,570
+الجزء هذا الآن هو المخصص لل training والتلاتة هدوة
+
+136
+00:10:26,570 --> 00:10:31,410
+عفوا لل test والتلاتة هدوة المخصصين لمين لموضوع ال
+
+137
+00:10:31,410 --> 00:10:35,290
+training في الدورة التانية بحدد هذا لل test
+
+138
+00:10:35,290 --> 00:10:40,810
+والباقي هذا كله ل training ولاحظوا في كل مرة انا
+
+139
+00:10:40,810 --> 00:10:43,750
+باعتمد على القيمة اللي بتطلع من موضوع ال testing
+
+140
+00:10:43,750 --> 00:10:49,580
+هنا ال accuracy ال accuracyالـ Accuracy وليس
+
+141
+00:10:49,580 --> 00:10:52,280
+بالضرورة في كل مرة تديني نفس القيمة بالعكس تديني
+
+142
+00:10:52,280 --> 00:10:58,640
+قيم مختلفة في النهاية أحصل على أو أحاول أخد الـ
+
+143
+00:10:58,640 --> 00:11:02,380
+Average الخاصة بالـ Accuracy اللي موجودة هيك عشان
+
+144
+00:11:02,380 --> 00:11:06,260
+هيك بنقول انه فعليا ان ال cross validation more
+
+145
+00:11:06,260 --> 00:11:09,540
+stable لكن فعليا لو أنا كانت عند ال data ستة باعت
+
+146
+00:11:09,540 --> 00:11:14,170
+كبيرةداتا 6 بقعت كبيرة كبيرة زي ما بتكلم 100 ألف
+
+147
+00:11:14,170 --> 00:11:17,890
+record أو أو 50 ألف record و أطلع و روحت والله أنا
+
+148
+00:11:17,890 --> 00:11:21,910
+أخدت منها 30% و عارف انه في مستخدم ال stratified
+
+149
+00:11:21,910 --> 00:11:26,970
+sampling عشان اضمن ان في عندي balance في ال data
+
+150
+00:11:26,970 --> 00:11:32,870
+اللي موجودة عندى ال .. ما بين ال different classes
+
+151
+00:11:32,870 --> 00:11:36,790
+او different labels بتديني نتيجة برضه موطوقة و
+
+152
+00:11:36,790 --> 00:11:40,340
+ممكن تكون أسرع من ال cross validation تمامبغض
+
+153
+00:11:40,340 --> 00:11:44,240
+النظر الطريقة اللي اتبعتها كانت الـ K-fold cross
+
+154
+00:11:44,240 --> 00:11:48,000
+-validation طبعا الـ K نرمز لها هان اللي هي عدد ال
+
+155
+00:11:48,000 --> 00:11:53,000
+folds اللي انت بدك تجسم فيها ده ك set يعني انا لما
+
+156
+00:11:53,000 --> 00:11:55,800
+اقولك مثلا بالمثال اللي موجود عندنا على ال slide
+
+157
+00:11:55,800 --> 00:12:01,220
+فعليا انا خمسةمعناته في كل part يتمثل عشرين في
+
+158
+00:12:01,220 --> 00:12:03,820
+المية عشرين في المية testing و تمانين في المية
+
+159
+00:12:03,820 --> 00:12:07,020
+training لاحظوا ان انا زي مرحلة ال training ممكن
+
+160
+00:12:07,020 --> 00:12:13,360
+اقوم بجسمها لعشرة عشرة في المية testing وتستعين في
+
+161
+00:12:13,360 --> 00:12:17,000
+المية training في حالتي انا حاولت ارسمها اربعة
+
+162
+00:12:17,000 --> 00:12:20,740
+عشرين في المية testing وخمسة وسبعين في المية
+
+163
+00:12:20,740 --> 00:12:25,300
+training فحسب ال data او حسب تقسيمك لل data اللي
+
+164
+00:12:25,300 --> 00:12:29,730
+موجود عندك تماممن الشغلات المهمة جدا اللى لازم
+
+165
+00:12:29,730 --> 00:12:33,230
+استوعبها انا صح اللى هي ال classification في ال
+
+166
+00:12:33,230 --> 00:12:36,710
+classification model ال confusion matrix طبعا عشان
+
+167
+00:12:36,710 --> 00:12:42,890
+تبسيط المفهوم هشتغل فقط على two classes على binary
+
+168
+00:12:42,890 --> 00:12:47,710
+classification class A و class B أو class 1 C1 و
+
+169
+00:12:47,710 --> 00:12:52,010
+C2 اللى هما ممكن يكونوا positive و negative يعني
+
+170
+00:12:52,010 --> 00:12:58,050
+لو انا افترض ان class 1 هذا positiveوهذا negative
+
+171
+00:12:58,050 --> 00:13:05,790
+positive و negative الان من اسمها confusion matrix
+
+172
+00:13:05,790 --> 00:13:08,890
+مصفوفة
+
+173
+00:13:08,890 --> 00:13:19,010
+اللخمة او مصفوفة التشتوت او سميها زي ما بدك انا
+
+174
+00:13:19,010 --> 00:13:26,590
+باستخدمها لانه فعليا تديني بشكل واضحوين ال data
+
+175
+00:13:26,590 --> 00:13:32,910
+set تباعتي راحت الفكرة أنه الآن لو انا قلت ان
+
+176
+00:13:32,910 --> 00:13:36,010
+الموزع طبعا هذه التوزيعة بنتبتها دائما عشان ما
+
+177
+00:13:36,010 --> 00:13:42,370
+نعملش مشكلة عند البعض لكن حتى لو اختلفت المصفوفة
+
+178
+00:13:42,370 --> 00:13:46,930
+كتير انا بعمل لها transpose يعني ممكن اعمل
+
+179
+00:13:46,930 --> 00:13:51,450
+transpose في اماكن تانية او في اماكن تقراها
+
+180
+00:13:51,450 --> 00:13:55,790
+بالtranspose وبالتالي اعمل ال prediction هناوالـ
+
+181
+00:13:55,790 --> 00:14:00,930
+actual classes موجودة هنا لكن انا باعتمد على ان
+
+182
+00:14:00,930 --> 00:14:03,470
+الـ actual row موجودة في ال rows و ال predicted
+
+183
+00:14:03,470 --> 00:14:09,010
+موجودة في ال columns تمام معناته انا في عندى class
+
+184
+00:14:09,010 --> 00:14:13,010
+1 و class 2 positive و negative وهدول ال data set
+
+185
+00:14:13,010 --> 00:14:17,630
+اللي موجودة عندى هنامحدش قال لي مطلقا تعالى نجي
+
+186
+00:14:17,630 --> 00:14:20,950
+على الرسمة اللي بس اللي هان محدش قاللي مطلقا ان ال
+
+187
+00:14:20,950 --> 00:14:24,270
+prediction تبعتي لازم تكون صحيحة 100% يعني لو كانت
+
+188
+00:14:24,270 --> 00:14:28,950
+ال data tests تبعتي هي مقسمة بين الأخضر والأحمر
+
+189
+00:14:28,950 --> 00:14:33,650
+وال predictive model الأخضر المفروض positive
+
+190
+00:14:33,650 --> 00:14:38,410
+والأحمر negativeالله يبعد عنكم الشرك والأحباب كل
+
+191
+00:14:38,410 --> 00:14:42,090
+يوم احنا بنتكلم على كورونا فيروس موجود في العالم و
+
+192
+00:14:42,090 --> 00:14:45,390
+الكل بتجري فحوصات positive معناته هذا بيدخل في
+
+193
+00:14:45,390 --> 00:14:49,090
+المستشفى ويبدو رعاية صحية negative بيبقى في الحجر
+
+194
+00:14:49,090 --> 00:14:52,690
+الصحي لحد ما تنتهي ال 14 يوم و نتأكد ان الفيروس مش
+
+195
+00:14:52,690 --> 00:14:55,970
+موجود مش هذا اللي بيصير الله يعافيكوا و أهليكوا
+
+196
+00:14:55,970 --> 00:14:59,970
+وكل أحبابكوا يا رب العالمينالان الـ system
+
+197
+00:14:59,970 --> 00:15:03,210
+positive أو negative فالـ system هو اللي بده يعمل
+
+198
+00:15:03,210 --> 00:15:07,270
+prediction بناءً على ال data الان هو جلب .. لاحظوا
+
+199
+00:15:07,270 --> 00:15:10,390
+هو ب6 عينات هنا ال data set كلها عملها
+
+200
+00:15:10,390 --> 00:15:13,150
+classification انتوا ملاحظين انه في عندي أنا هنا
+
+201
+00:15:13,150 --> 00:15:21,330
+سبعة وفي عندي تمانية يعني هدول 15 element سبعة
+
+202
+00:15:21,330 --> 00:15:25,730
+positive وتمانية negative فلما عمل ال prediction
+
+203
+00:15:25,730 --> 00:15:29,600
+عمل أربعةأو قال لي انه في عندك sub المجموع ال
+
+204
+00:15:29,600 --> 00:15:33,400
+positive قال لي في عندي ست حالات لكن واضح ان هو
+
+205
+00:15:33,400 --> 00:15:37,520
+أخطأ في حالتين أخطأ في الحمر هدول صح تمام و ال
+
+206
+00:15:37,520 --> 00:15:42,980
+negative زيها طيب نيشي الآن في ال actual انا فعليا
+
+207
+00:15:42,980 --> 00:15:47,580
+عندي واحدة اتين تلاتة اربع خمسة ستة يعني الصف هذا
+
+208
+00:15:47,580 --> 00:15:55,380
+على امتدادهبتكون مجموعه عبارة عن مجموع العناصر أو
+
+209
+00:15:55,380 --> 00:16:01,020
+عدد العناصر الـ positive cases أو كل الـ rows اللي
+
+210
+00:16:01,020 --> 00:16:06,320
+بتنتمي ل class 1 true positive هي عبارة عن الـ
+
+211
+00:16:06,320 --> 00:16:12,920
+rows اللي هي فعليا بتنتميلـ Class 1 و الـ system
+
+212
+00:16:12,920 --> 00:16:17,400
+عملها prediction as class 1 يعني صنفها بشكل صحيح
+
+213
+00:16:17,400 --> 00:16:21,420
+فبقولها true يعني تصنيفها كان صحيح و هي فعليا
+
+214
+00:16:21,420 --> 00:16:26,460
+positive و طبعا ما تنساش او ما تنسيش ان انا بتكلم
+
+215
+00:16:26,460 --> 00:16:31,040
+على binary classification اسهل الموضوع تمام ماهو
+
+216
+00:16:31,040 --> 00:16:34,760
+ال false negative ال false negative هي فعليا
+
+217
+00:16:34,760 --> 00:16:38,400
+elements بتنتمي ل class 1 و هي positive لكن
+
+218
+00:16:38,400 --> 00:16:43,020
+صنفليها بالخطأأو أخطأ في تصنيفها و حط ليها إيش على
+
+219
+00:16:43,020 --> 00:16:46,520
+إنها negative وبالتالي أصبحت عندي هنا false
+
+220
+00:16:46,520 --> 00:16:51,020
+negative مجموح هدول العنصرين ال true positive و ال
+
+221
+00:16:51,020 --> 00:16:54,240
+false negative ال true positive و ال false
+
+222
+00:16:54,240 --> 00:16:58,780
+negative هو بتديني عدد عناصر ال class الأول تمام؟
+
+223
+00:16:58,780 --> 00:17:02,480
+طيب بالنسبة لل class التاني هو عملها prediction
+
+224
+00:17:02,480 --> 00:17:08,500
+على إنها class one يعني هو قال إنها positive لكنه
+
+225
+00:17:08,500 --> 00:17:12,570
+ال prediction هذا خطأليش؟ لأن هي في الحقيقة تنتمي
+
+226
+00:17:12,570 --> 00:17:16,250
+ل class 2 اللي هو الـ negative فهي فعليا negative
+
+227
+00:17:16,250 --> 00:17:19,710
+ولكن عملها prediction على إنها positive فهي false
+
+228
+00:17:19,710 --> 00:17:25,350
+positive تمام؟ وتبقى عندها ال true negative هي
+
+229
+00:17:25,350 --> 00:17:30,110
+class 2 صنفها على class 2 صحيح؟ وبالتالي هي عبارة
+
+230
+00:17:30,110 --> 00:17:33,990
+عن true negative يعني فعليا لو أنا بدى أفكر
+
+231
+00:17:33,990 --> 00:17:37,630
+بالجدول أو ب confusion matrix لما أنا بدى أنشئها
+
+232
+00:17:37,630 --> 00:17:45,950
+بشكل صحيحأي الجدول هو
+
+233
+00:17:45,950 --> 00:17:51,250
+فيه
+
+234
+00:17:51,250 --> 00:18:01,250
+مساحة بال powerpoint ولا مافيش eraser
+
+235
+00:18:01,250 --> 00:18:05,810
+تمام
+
+236
+00:18:05,810 --> 00:18:08,490
+رجعها لاشي
+
+237
+00:18:17,740 --> 00:18:23,380
+الان احنا متفقين هنا ان انا فعليا هنا عند الـ
+
+238
+00:18:23,380 --> 00:18:27,400
+actual والأعمدة الـ predicted
+
+239
+00:18:34,130 --> 00:18:40,910
+C2 C1 و C2 حسب الرسمة اللي موجودة عندها حاجة
+
+240
+00:18:40,910 --> 00:18:46,930
+اعدنالان كام واحدة فعليا بينتمي ل class one وعملها
+
+241
+00:18:46,930 --> 00:18:49,590
+prediction في ال class one صحيح في ال positive
+
+242
+00:18:49,590 --> 00:18:55,550
+واحدة اتنين تلاتة اربعة تمام
+
+243
+00:18:55,550 --> 00:19:02,410
+طيب و هدول هذه
+
+244
+00:19:02,410 --> 00:19:06,880
+وهذههم أصلا نيجاتيف class 2 لكن اعملهم prediction
+
+245
+00:19:06,880 --> 00:19:14,840
+هان تمام نجي للحالة النيجاتيف هي بتنتمي ل class 1
+
+246
+00:19:14,840 --> 00:19:18,280
+لكن عملها prediction في class 2 اللي هم الخضر اللي
+
+247
+00:19:18,280 --> 00:19:22,340
+هان اتنين لو
+
+248
+00:19:22,340 --> 00:19:27,140
+عديت الخضر اتنين واربعة ستة هي المجموع و هان لازم
+
+249
+00:19:27,140 --> 00:19:33,850
+يكون هنا في عندياشعشان يكتمل عدد 2.68 فهذه هي
+
+250
+00:19:33,850 --> 00:19:37,970
+فعليا ال confusion matrix اللي انا هشغل عليها تمام
+
+251
+00:19:37,970 --> 00:19:41,590
+الآن ال accuracy كون ان انا حسبت ال confusion
+
+252
+00:19:41,590 --> 00:19:46,870
+matrix اتفقنا ان ال accuracy هي عبارة عن ال ratio
+
+253
+00:19:46,870 --> 00:19:56,030
+عدد نسبة ال test table اللي صنفها بشكل صحيح مين هم
+
+254
+00:19:56,030 --> 00:20:02,900
+ال true positiveوالـ true negative و لا لأ تمام
+
+255
+00:20:02,900 --> 00:20:06,700
+معناته ال true positive صحيحة و ال true negative
+
+256
+00:20:06,700 --> 00:20:11,780
+صحيحة هدولة صحيحات فبجمع هذه و هذه على كل عناصر
+
+257
+00:20:11,780 --> 00:20:14,300
+المصفوفة اللي موجودة عندي بكون حصلت على ال
+
+258
+00:20:14,300 --> 00:20:18,620
+accuracy على كل predict على ال cardinality تبعت ال
+
+259
+00:20:18,620 --> 00:20:23,700
+test set اللي انا باتكلم عليها واضحة كمان مرة ال
+
+260
+00:20:23,700 --> 00:20:28,580
+accuracy هي عبارة عن نسبةالـ Rows أو الـ Tables
+
+261
+00:20:28,580 --> 00:20:32,600
+اللي في ال test set اللي نجح ال classifier فيه
+
+262
+00:20:32,600 --> 00:20:39,260
+تصنيفها على حجم ال test set اللي موجودة عندى تمام
+
+263
+00:20:39,260 --> 00:20:44,780
+بالمثال السابق لو انا بدى ارجع هان ال prediction
+
+264
+00:20:44,780 --> 00:20:54,000
+تبعتي عبارة عن ال هان عفوا اربع
+
+265
+00:20:54,000 --> 00:21:03,510
+زائد6 على 15 لأن كل ال data 6 بعد 15 element
+
+266
+00:21:03,510 --> 00:21:09,470
+عديناها قبل شوية يعني بين جثين 12 على 15 لو أنا
+
+267
+00:21:09,470 --> 00:21:14,970
+بتتكلم على 3 بتتكلم على 4 على 5 معناته أنا بتتكلم
+
+268
+00:21:14,970 --> 00:21:19,790
+جاعد حدود ال accuracy تبعتي 80%
+
+269
+00:21:22,870 --> 00:21:26,790
+تمام طبعا ال accuracy عكسة في عند ال error rate
+
+270
+00:21:26,790 --> 00:21:29,650
+طبعا ممكن في عند مصطلح تاني ممكن استخدمه مع ال
+
+271
+00:21:29,650 --> 00:21:35,190
+accuracy اللي هو ايش ال recognition rate وطبعا
+
+272
+00:21:35,190 --> 00:21:38,070
+برضه من المصطلحات المستخدمة accuracy او
+
+273
+00:21:38,070 --> 00:21:41,090
+recognition rate نفس المعنى في عند ال error rate
+
+274
+00:21:41,090 --> 00:21:44,710
+ال error rate طبعا اعلى نسبة اللي هي واحد مصبوط
+
+275
+00:21:44,710 --> 00:21:49,410
+يعني احنا قبل شوية كانت عندى 80% 5 على 4 يعني 8 من
+
+276
+00:21:49,410 --> 00:21:55,830
+10 ال error rate تساوي واحد ناقص8 من 10 وتساوي
+
+277
+00:21:55,830 --> 00:22:01,810
+point اتنين من عشرة او بين جثين اللي هي عشرين فيلم
+
+278
+00:22:01,810 --> 00:22:05,150
+يعني هذا مقدار ال error rate او بين جثين ال error
+
+279
+00:22:05,150 --> 00:22:08,990
+rate زي ما احنا شايفين هنا هي عبارة عن ال false
+
+280
+00:22:08,990 --> 00:22:11,250
+positive و ال false negative
+
+281
+00:22:14,470 --> 00:22:17,770
+له فعليا اللي أخطأ فيه تصنيفهم اللي أخطأ فيه
+
+282
+00:22:17,770 --> 00:22:21,290
+تصنيفهم طبعا جامعة الخيار هنا في شغل مهم جدا طب
+
+283
+00:22:21,290 --> 00:22:23,610
+هذا يا دكتور في حالتي ال binary classification لو
+
+284
+00:22:23,610 --> 00:22:26,490
+حد اتقرح على أي سؤال و قال يا دكتور هذا في حالة ال
+
+285
+00:22:26,490 --> 00:22:30,910
+binary classification طب شوف حالة ال multiple
+
+286
+00:22:30,910 --> 00:22:33,390
+class يعني لو كانت المصفوفة تبعتي ال confusion
+
+287
+00:22:33,390 --> 00:22:42,830
+matrix تبعتي تلاتة في تلاتة ايش
+
+288
+00:22:42,830 --> 00:22:48,350
+ممكن نعملخلّينا نعتمد نفس التوزيع السابقة الـ
+
+289
+00:22:48,350 --> 00:22:54,910
+actual في الأعمدة الـ actual في الصفوف و الـ
+
+290
+00:22:54,910 --> 00:23:00,270
+predicted في الأعمدة معناته هذه هتكون true
+
+291
+00:23:00,270 --> 00:23:07,270
+positive أو هذه false
+
+292
+00:23:07,270 --> 00:23:10,740
+negativeفالس
+
+293
+00:23:27,780 --> 00:23:31,820
+بوزيتف لكن حطيلي اياهم false negative يعني هم جالس
+
+294
+00:23:31,820 --> 00:23:35,360
+.. هو تفسر .. يعني بفهم هيكل يعني c2 و c3 not
+
+295
+00:23:35,360 --> 00:23:39,200
+positive يعني negative فاخدلي اياهم هان كمان في ال
+
+296
+00:23:39,200 --> 00:23:47,040
+class التاني هتكون هذه true negative و هذه false
+
+297
+00:23:47,040 --> 00:23:55,580
+positive false positive ل c1 عفوا عفوا هي c2 و هي
+
+298
+00:23:55,580 --> 00:24:06,300
+c3وهنا ستكون فالس نيجاتيف فالس
+
+299
+00:24:06,300 --> 00:24:09,540
+نيجاتيف فالس نيجاتيف فالس نيجاتيف فالس نيجاتيف
+
+300
+00:24:09,540 --> 00:24:11,220
+فالس نيجاتيف فالس نيجاتيف فالس نيجاتيف فالس
+
+301
+00:24:11,220 --> 00:24:12,280
+فالس نيجاتيف فالس نيجاتيف فالس نيجاتيف فالس
+
+302
+00:24:12,280 --> 00:24:13,540
+نيجاتيف فالس نيجاتيف فالس نيجاتيف فالس نيجاتيف
+
+303
+00:24:13,540 --> 00:24:16,920
+فالس نيجاتيف فالس نيجاتيف فالس نيجاتيف فالس
+
+304
+00:24:16,920 --> 00:24:25,260
+نيجاتيف فالس نيجاتيف فالهذا الكلام الـ Accuracy
+
+305
+00:24:25,260 --> 00:24:31,800
+ممتازة في حالة ان العناصر او ال class is balanced
+
+306
+00:24:31,800 --> 00:24:35,300
+يعني بنجوسين سبعة و تمانية جرب من بعض خمسين و
+
+307
+00:24:35,300 --> 00:24:40,020
+خمسين تلاتين تلاتين تلاتين او خمسين خمسين خمسين في
+
+308
+00:24:40,020 --> 00:24:43,500
+حالة ال IRIS data setالـ Balance بين ال classes
+
+309
+00:24:43,500 --> 00:24:47,680
+موجودة لكن فعلياً لما انا بتكلم على ال diseases أو
+
+310
+00:24:47,680 --> 00:24:51,060
+في اللي بتكلم على ال fraud detection عمليات النصب
+
+311
+00:24:51,060 --> 00:24:55,620
+في وضعات الاهتمام ال classes in balance شو يعني in
+
+312
+00:24:55,620 --> 00:24:58,480
+balance انه عدد ال elements في الكلة و عدد ال rows
+
+313
+00:24:58,480 --> 00:25:05,320
+مع كل class غير متساوية طبعا أجيب المثال أوضح الله
+
+314
+00:25:05,320 --> 00:25:09,100
+يعافيكم كم مرة وأهليكم جميعا لأن كم واحد بنعمله
+
+315
+00:25:09,100 --> 00:25:15,010
+فحص كورونا حول العالممئات الألف عشرات الألف بلاش
+
+316
+00:25:15,010 --> 00:25:19,370
+مئات الألف كام واحد بتثبت معاه الحالة أقل كتير
+
+317
+00:25:19,370 --> 00:25:26,350
+وبالتالي عدد ال negative أكبر كتير من عدد ال
+
+318
+00:25:26,350 --> 00:25:32,210
+positive ممتاز طب لو أنا سألت سؤال مين أختار؟ واحد
+
+319
+00:25:32,210 --> 00:25:35,490
+ماعهوش فيروس وقال لل system لأ ان هذا عنده فيروس
+
+320
+00:25:35,490 --> 00:25:41,760
+كورونا ولا واحد عنده فيروس كورونا وال systemقال له
+
+321
+00:25:41,760 --> 00:25:48,480
+إنه ما عندهوش شو رايكوا؟ يعني نسبة الخطأ مع ال
+
+322
+00:25:48,480 --> 00:25:50,960
+positive ولا الخطأ مع ال negative هي الأخطر
+
+323
+00:25:50,960 --> 00:25:55,820
+بالنسبة لنا كلامك صح أو كلامك صح الآن لأنه احنا
+
+324
+00:25:55,820 --> 00:26:01,240
+فعليا لما أخطأ ال system وقال له إنه هذا negative
+
+325
+00:26:02,050 --> 00:26:06,030
+false negative كانت مصيبة بالنسبة لي لأن هذا
+
+326
+00:26:06,030 --> 00:26:10,150
+الإنسان سيخلق
+
+327
+00:26:10,150 --> 00:26:13,490
+الناس وبالتالي المرض سينتشر لأنه مش معنى ونهيك عن
+
+328
+00:26:13,490 --> 00:26:17,650
+الأضرار الصحية اللي حدث معاه لكن لو واحد negative
+
+329
+00:26:17,650 --> 00:26:21,290
+ماعندوش المرض و ال system قال إنه عنده المرض إيش
+
+330
+00:26:21,290 --> 00:26:24,990
+هناخده؟ هناخده نحطه في ال health care أو في الحجر
+
+331
+00:26:24,990 --> 00:26:30,540
+الحجر الصحي و بعدين ندي عناية صحية حسب حالتهفي ضرر
+
+332
+00:26:30,540 --> 00:26:34,180
+في الموضوع حتما مافيش ضرر وبالتالي لما بكون في ال
+
+333
+00:26:34,180 --> 00:26:39,220
+class imbalance ال accuracy تبعتي مش صحيحة، ليش؟
+
+334
+00:26:39,220 --> 00:26:43,200
+او بتبقى العفوان غير معدرة بشكل صحيح لأن لو تخيلت
+
+335
+00:26:43,200 --> 00:26:51,820
+ان هنا انا عدد العناصر بدي اشتغل هيك ان عدد
+
+336
+00:26:51,820 --> 00:26:54,260
+العناصر اللي انا بدي افحصها 100 ألف
+
+337
+00:26:58,340 --> 00:27:06,760
+وفعليا او ال data set تبعتي للهيئة كلها كان في
+
+338
+00:27:06,760 --> 00:27:14,140
+عندي مثلا عشرة ألف positive و
+
+339
+00:27:14,140 --> 00:27:22,600
+تسعين ألف negative و لما عملت prediction اجى قال
+
+340
+00:27:22,600 --> 00:27:31,710
+لي والله من العشر تلاف هدولأنا جبت تسعة ألف صح و
+
+341
+00:27:31,710 --> 00:27:46,110
+ألف ما جبتهوش في المقابل هذا الألف صنفته هان أو
+
+342
+00:27:46,110 --> 00:27:49,210
+بالأحرى قال لي أنا ما أخطأتش ولا حاجة هان أو خلينا
+
+343
+00:27:49,210 --> 00:27:54,910
+نقول أخطأ اخطألي بألف هان و جابلي هان تمانين ألف
+
+344
+00:28:00,700 --> 00:28:08,680
+فعليا ال accuracy تبعتي هتكون تسعة و تمانين الف
+
+345
+00:28:08,680 --> 00:28:15,680
+على ميت
+
+346
+00:28:15,680 --> 00:28:20,300
+الف صح فالنسبة تبعتي تسعة و تمانين في المية ال
+
+347
+00:28:20,300 --> 00:28:24,560
+accuracy عالية
+
+348
+00:28:24,560 --> 00:28:29,040
+و ممتازة و ما شاء الله عليها لكنهاتحمل في طياتها
+
+349
+00:28:29,040 --> 00:28:37,840
+خطورة شديدة جدا مع من مع الناس هذول مع
+
+350
+00:28:37,840 --> 00:28:42,880
+اللهان تماموبالتالي الـ Accuracy بطلت عندي مجديا
+
+351
+00:28:42,880 --> 00:28:45,400
+لأن الـ 9.8 محدش يقول عن نسبة مخة في طلق بالعكس
+
+352
+00:28:45,400 --> 00:28:49,080
+نسبة عالية لكنه في عندى مشكلة في ال evaluation
+
+353
+00:28:49,080 --> 00:28:52,980
+تمام وبالتالي انا ممكن اصير ادور على شغل اسمها ال
+
+354
+00:28:52,980 --> 00:28:57,220
+sensitivity الحساسية وطبعا هنا بتكلم على ال true
+
+355
+00:28:57,220 --> 00:29:02,960
+positive rate ال true positive rate على اللي هي
+
+356
+00:29:02,960 --> 00:29:11,720
+نسبة 9000 على العشرة ألفوكذلك في عندي ال
+
+357
+00:29:11,720 --> 00:29:18,900
+specificity التخصيص اللي هي نسبة لل true negative
+
+358
+00:29:18,900 --> 00:29:23,960
+rate جد عشان افصل انا هو ال accuracy بعد ما حصلت
+
+359
+00:29:23,960 --> 00:29:30,060
+عليها مين كان فيه نسبته اعلى عشان اضيفه ومش بس هيك
+
+360
+00:29:30,060 --> 00:29:33,520
+جالي ممكن انا اتكلم على other metrics وهذه الأهم
+
+361
+00:29:33,520 --> 00:29:39,120
+اللي بنسميها احنا ال precision
+
+362
+00:29:44,430 --> 00:29:47,210
+الـ Precision أو الـ Exactness هي عبارة عن الـ
+
+363
+00:29:47,210 --> 00:29:53,310
+ratio لمجموعة التابلز
+
+364
+00:29:53,310 --> 00:29:58,630
+ال classifier صنفهم على أنهم positive و هم فعليا
+
+365
+00:29:58,630 --> 00:30:03,190
+positive نسبة
+
+366
+00:30:03,190 --> 00:30:07,070
+ال labelled اللي جال عليها positive و هي فعليا
+
+367
+00:30:07,070 --> 00:30:09,810
+positive على كل ال actual positive اللي موجودة
+
+368
+00:30:09,810 --> 00:30:12,390
+عندها وين ال actual positive
+
+369
+00:30:18,800 --> 00:30:22,720
+الـ actual هو اللي موجود في جامعة الخير في الأعمدة
+
+370
+00:30:22,720 --> 00:30:37,440
+في العمود في الصفوف الآن ال true positive هي جل
+
+371
+00:30:37,440 --> 00:30:40,720
+ال true positive على كل العناصر الصنافليها على
+
+372
+00:30:40,720 --> 00:30:44,220
+إنها positive عشان أجيب نسبة ال actual positive
+
+373
+00:30:44,220 --> 00:30:49,230
+الحقيقية اللي موجودة عندهاas positive are actually
+
+374
+00:30:49,230 --> 00:30:53,750
+positive نسبة الـ positive الحقيقية فهنا لما أتكلم
+
+375
+00:30:53,750 --> 00:30:57,270
+عن ال precision أو ال exactness بتكلم عليها عناصر
+
+376
+00:30:57,270 --> 00:31:02,330
+الصل عمود الأول تمام لما باجي بتكلم علي ال recall
+
+377
+00:31:02,330 --> 00:31:07,550
+أو ال completeness بتكلم فعليا على نسبة ال
+
+378
+00:31:07,550 --> 00:31:11,130
+positive double واللي فعليا تم تصنيفها على إنها
+
+379
+00:31:11,130 --> 00:31:15,630
+positive نسبة ال positive doubles اللي تصنفت على
+
+380
+00:31:15,630 --> 00:31:19,890
+إنها positive بشكل صحيحوين الـ positive هي الصف
+
+381
+00:31:19,890 --> 00:31:24,810
+الأول اللي
+
+382
+00:31:24,810 --> 00:31:29,090
+احنا قلنا عليها sensitivity قبل لحظات وبالتالي الـ
+
+383
+00:31:29,090 --> 00:31:34,430
+TB بتروح ال true
+
+384
+00:31:34,430 --> 00:31:39,550
+positive على المجموع اللي موجود عندي ال TB و ال FN
+
+385
+00:31:39,550 --> 00:31:45,670
+تمامماعندي الـ F ماعندي الـGalaxy بما أن في عندي
+
+386
+00:31:45,670 --> 00:31:50,730
+الـPrecision و الـRecall هدولة متريكات مختلفة قال
+
+387
+00:31:50,730 --> 00:31:54,210
+في ناس فكرت جالكس نعملهم combination ما بين
+
+388
+00:31:54,210 --> 00:32:00,350
+الـPrecision و الـRecall في متريك واحد و سموه ليا
+
+389
+00:32:00,350 --> 00:32:08,530
+الـF majorودمجونا فيه ال precision و ال recall
+
+390
+00:32:08,530 --> 00:32:12,710
+وكان هو يساوي 2 ضرب ال precision ضرب ال recall على
+
+391
+00:32:12,710 --> 00:32:15,790
+مجموع ال recall و ال precision أو بين قوسين هي ال
+
+392
+00:32:15,790 --> 00:32:20,730
+F1 وهذا أنا باستخدمه لما عادة بفكر بالمقارنة ما
+
+393
+00:32:20,730 --> 00:32:24,740
+بينTWO DIFFERENT CLASSIFIERS الان انا في عندى two
+
+394
+00:32:24,740 --> 00:32:27,500
+different classifiers و بدى اقارن بين الأداء تبعهم
+
+395
+00:32:27,500 --> 00:32:30,740
+واحد ممكن يتفكر بال accuracy ال accuracy ممكن تكون
+
+396
+00:32:30,740 --> 00:32:34,420
+متساوية ما بين الاتنين مابيش ممكن اساوي ممكن اروح
+
+397
+00:32:34,420 --> 00:32:37,940
+على اتجاه ال F مجار اللي انا ممكن تكون طبعا انتم
+
+398
+00:32:37,940 --> 00:32:41,770
+ملاحظين يا جماعة الخيرالـ Recall و ال Precision و
+
+399
+00:32:41,770 --> 00:32:46,370
+ال F Major
+
+400
+00:32:46,370 --> 00:32:53,370
+هدول مرتبطين بال First Attribute يعني لو أنا قلتلك
+
+401
+00:32:53,370 --> 00:32:58,270
+بدي ال F Major ل ال class التاني أو عفوا ال Recall
+
+402
+00:32:58,270 --> 00:33:02,690
+ل ال class التاني ال class التاني هيه بتصير أنا
+
+403
+00:33:02,690 --> 00:33:06,230
+بتتكلم على hand
+
+404
+00:33:08,770 --> 00:33:12,250
+مجموعة الـ Recall True Positive هي لـ Class التاني
+
+405
+00:33:12,250 --> 00:33:16,750
+هذه اللي بتمثل True Positive لل Class اللي موجودة
+
+406
+00:33:16,750 --> 00:33:22,250
+عندي على عدد عناصر اللي هي على عدد الـ N على الـ N
+
+407
+00:33:22,250 --> 00:33:26,830
+اللي موجودة عندها تمام؟ يعني هذه الشغله مرتبطه بال
+
+408
+00:33:26,830 --> 00:33:30,510
+Class لو أنا الآن كان في عندي تلاتة في تلاتة
+
+409
+00:33:34,650 --> 00:33:38,150
+المصفوفة تبعتي بنفس التوزيع لـ Prediction في
+
+410
+00:33:38,150 --> 00:33:41,190
+الأعمدة و الـ Actual .. لـ Predicted في الأعمدة و
+
+411
+00:33:41,190 --> 00:33:44,830
+الـ Actual في الصفورة و أنا الجيل قلت والله هاي ال
+
+412
+00:33:44,830 --> 00:33:50,230
+values اللي عندي الان بدي ال precision عفوا عشان
+
+413
+00:33:50,230 --> 00:33:54,950
+القانون ال recall بدي ال recall تبعتي التالت لسي
+
+414
+00:33:54,950 --> 00:33:59,830
+تلاتة و ال true positive تبعت ال class تلاتة هيها
+
+415
+00:34:02,430 --> 00:34:09,630
+هي فعليًا actually بتنتمي لـ C3 و الـ system جالب
+
+416
+00:34:09,630 --> 00:34:12,810
+predicted as C3 فعليًا هذه الـ true positive ما
+
+417
+00:34:12,810 --> 00:34:18,030
+دون ذلك الـ false negative هدولة تنتمي و بالتالي
+
+418
+00:34:18,030 --> 00:34:25,310
+ال recall لـ C3 لو انا افترض ان هذه Y وهذه Z تساوي
+
+419
+00:34:25,310 --> 00:34:30,990
+معناته ال recall لـ C3 بدها تساوي X
+
+420
+00:34:32,990 --> 00:34:40,490
+على y زائد z زائد x اللي هي بجموع كل العناصر اللي
+
+421
+00:34:40,490 --> 00:34:45,250
+موجودة عندي و طبعا y و z هم بمثله ال false
+
+422
+00:34:45,250 --> 00:34:49,670
+positive أو عفوا ال false negative ل c3 طيب
+
+423
+00:34:49,670 --> 00:34:54,710
+بالمثال خليني أخد مثال بالأرقامفي انها النتج الـ
+
+424
+00:34:54,710 --> 00:34:57,410
+classifier اللي اشتغل على ال prediction للكانسر
+
+425
+00:34:57,410 --> 00:35:01,050
+بتنبأ بالكانسر عدد الحالات اللي موجودة عندى انا
+
+426
+00:35:01,050 --> 00:35:07,330
+الف حالة كان فعليا اشتغل اللي لما وزعناهم كانت
+
+427
+00:35:07,330 --> 00:35:13,250
+عندي تسعين حالة كانوا yes و ال system عملهم
+
+428
+00:35:13,250 --> 00:35:19,320
+prediction yesو 210 حالة و هم فعليا yes و ال
+
+429
+00:35:19,320 --> 00:35:24,500
+system عملهم prediction no يعني 300 حالة ال 10,000
+
+430
+00:35:24,500 --> 00:35:31,420
+حالة اللي عندى 300 حالة سرطان و 9700 غير سرطان او
+
+431
+00:35:31,420 --> 00:35:38,240
+خلايا تضخم طبيعى غير سرطانى الان ملاحظين لو انا
+
+432
+00:35:38,240 --> 00:35:43,720
+جيت حسبت ال accuracy ال accuracy 96في المية لأنها
+
+433
+00:35:43,720 --> 00:35:48,420
+عبارة عن مجموعة تسعين زائد خمسة وتسعة تلاف وخمسمية
+
+434
+00:35:48,420 --> 00:35:54,280
+وستين على عشرة ألف ال accuracy عالية جدا لكن اه لو
+
+435
+00:35:54,280 --> 00:35:59,380
+نظرت في الموضوع لو فكرت احسب ال precision و ال
+
+436
+00:35:59,380 --> 00:36:05,260
+recall لل cancer او لل class الأول لانديهان
+
+437
+00:36:05,260 --> 00:36:11,100
+ملاحظين ال precision كدهالـ precision احنا قلنا هي
+
+438
+00:36:11,100 --> 00:36:15,980
+عبارة عن ال exactness مظبوط فعليا جداش تنبأ بشكل
+
+439
+00:36:15,980 --> 00:36:21,160
+او بشكل صحيح لل data اللي موجودة عندها وصار واضح
+
+440
+00:36:21,160 --> 00:36:29,160
+الفرق قلنا 90 على 230 قلنا في ال precision بتكلم
+
+441
+00:36:29,160 --> 00:36:35,700
+على عمود و لما اتكلم بال recall بتكلم وينعلى الصف
+
+442
+00:36:35,700 --> 00:36:43,340
+صحيح عشان هيك 90 على 230 لـ precision و 90 على 300
+
+443
+00:36:43,340 --> 00:36:48,520
+اللي هي ال recall اللي موجودة عندها لكن تخيل انه
+
+444
+00:36:48,520 --> 00:36:53,820
+انا فعليا لو قعدت ترتيب العناصر في المصفوفة بحيث
+
+445
+00:36:53,820 --> 00:36:58,960
+انه خلت ال target تبعتي No وقولت
+
+446
+00:36:58,960 --> 00:37:01,600
+انا بدي احسب ال recall و ال precision لاحظوا ال
+
+447
+00:37:01,600 --> 00:37:05,530
+accuracy ما اتغيرتشلكن انا عيد ترتيب الأعمد يعني
+
+448
+00:37:05,530 --> 00:37:07,930
+برينج وستين صار اهتمامي هان highly true positive
+
+449
+00:37:07,930 --> 00:37:11,370
+لاحظوا ان ال precision تبعتي جداش عالي صارت و ال
+
+450
+00:37:11,370 --> 00:37:14,910
+recall تبعتي جداش على كل مقالة زي ما قولنا ال
+
+451
+00:37:14,910 --> 00:37:18,470
+perfect value تبعتنا هان حكينا ان ال perfect او ال
+
+452
+00:37:18,470 --> 00:37:23,990
+score is one كذلك مع ال precisionالـ perfect score
+
+453
+00:37:23,990 --> 00:37:28,290
+هو 1 وبهكد انا بكون بدي اعمل evaluation لل classes
+
+454
+00:37:28,290 --> 00:37:31,650
+اللي موجود عندها وبالتالي انا بدي انتبه دائما لل
+
+455
+00:37:31,650 --> 00:37:34,710
+class اللي موجود بالنسبة لل code اللي له علاقة بال
+
+456
+00:37:34,710 --> 00:37:39,550
+بايثونانا هنا روحت اعمل import لل data set كان
+
+457
+00:37:39,550 --> 00:37:43,970
+المعتاد على نفس المثال السابق روحت اعمل import
+
+458
+00:37:43,970 --> 00:37:47,210
+عشان اعمل split لل data set والمفروض ان انتوا هاي
+
+459
+00:37:47,210 --> 00:37:51,590
+جربتوها من خلال ال assignment اللي سلمته فانا حصلت
+
+460
+00:37:51,590 --> 00:37:55,850
+على ال training set اللي هنا من خلال ال split هذه
+
+461
+00:37:55,850 --> 00:37:59,790
+train test split جسمتلي او ادتني نتيجة ادتني four
+
+462
+00:37:59,790 --> 00:38:05,010
+different set ال X train و ال label تبعتها
+
+463
+00:38:08,770 --> 00:38:17,890
+الـ Y لليابيل و X للattributes و ال test text test
+
+464
+00:38:17,890 --> 00:38:21,470
+و ال Y test طبعا قلت له هان تلاتين في المية نسبة
+
+465
+00:38:21,470 --> 00:38:25,010
+ال test تلاتين في المية و طبعا هضل الباجي لليترين
+
+466
+00:38:26,020 --> 00:38:29,600
+من الـ target data و استدعيت ناييف بايسين على سبيل
+
+467
+00:38:29,600 --> 00:38:36,180
+المثال و روحت و قلت جوسان ناييف بايسين استدعيت ال
+
+468
+00:38:36,180 --> 00:38:40,460
+constructor قلتله روح بنيت model و قلتله اعمل fit
+
+469
+00:38:40,460 --> 00:38:46,280
+اللي بتعمل hand training وقلنا
+
+470
+00:38:46,280 --> 00:38:53,000
+في ناييف بايسين بروح ببنيني جدول الاحتمالاتبعد ذلك
+
+471
+00:38:53,000 --> 00:38:59,860
+قمت بالتفكير في مجموع يسميته Y-predict هذا هو
+
+472
+00:38:59,860 --> 00:39:05,200
+النتائج الـ model.predict ودّيته X test بالكامل
+
+473
+00:39:05,200 --> 00:39:09,840
+لاحظت أنني سميتها Y-predict أنا عندي ال test هي ال
+
+474
+00:39:09,840 --> 00:39:14,020
+label تباعتها موجودة هنا Y-test فروحت وحصلت عليها
+
+475
+00:39:14,020 --> 00:39:17,280
+تمام صارت في عندي الـ predicted وصارت عندي موجود
+
+476
+00:39:17,280 --> 00:39:22,560
+من ال actual label فالانأنا قاعد بقى أشتغل روحت
+
+477
+00:39:22,560 --> 00:39:25,980
+عملت import بدي أجيب ال matrix from ASCII layer
+
+478
+00:39:25,980 --> 00:39:29,080
+import ال matrix و ال matrix هي فيها كل حاجة فيها
+
+479
+00:39:29,080 --> 00:39:32,440
+ال accuracy score و طبعا كل ال method في ال matrix
+
+480
+00:39:32,440 --> 00:39:36,960
+بدها مني ال y predicted و ال y test ال y test هي
+
+481
+00:39:36,960 --> 00:39:40,840
+موجودة أنا حصلت اللي هي فعليا ال actual و ال y
+
+482
+00:39:40,840 --> 00:39:43,600
+predicted هي الموجودة عندها فلما أنا قلتله ال
+
+483
+00:39:43,600 --> 00:39:46,300
+accuracy score ده نسبة ال confusion matrix طبع
+
+484
+00:39:46,300 --> 00:39:49,560
+ليها و ال classifier او ال classification report
+
+485
+00:39:50,850 --> 00:39:55,090
+بتدين الأفمجة و ال precision و ال recall لكل class
+
+486
+00:39:55,090 --> 00:40:00,790
+موجود عندي و هيك نهينا أو ختمنا chapter لل
+
+487
+00:40:00,790 --> 00:40:04,470
+classification بتمنى تكون الشروحات واضحة إذا في أي
+
+488
+00:40:04,470 --> 00:40:08,450
+استفسار لازم يكون من خلال ال model أو ال forum
+
+489
+00:40:08,450 --> 00:40:12,450
+اللي موجود عندي هنا أخر شغلة مطلوب منها ال
+
+490
+00:40:12,450 --> 00:40:16,190
+assignment البسيط هذا ال assignment هذا بدو يعمل
+
+491
+00:40:16,190 --> 00:40:18,650
+مقارنة بين three different classifiers
+
+492
+00:40:21,320 --> 00:40:26,020
+أخذنا أربعة classifiers كي نتعرف على الـ K-nearest
+
+493
+00:40:26,020 --> 00:40:28,500
+neighbour، الـ Naive bison، الـ decision tree و
+
+494
+00:40:28,500 --> 00:40:31,840
+الـ Multilayer Perceptron الـ classifier اللي هو
+
+495
+00:40:31,840 --> 00:40:34,860
+تبع الـ neural network وأنا بدي أقارن بينهم بناء
+
+496
+00:40:34,860 --> 00:40:39,170
+على الـ accuracyالـ Precision الـ Recall والـ F
+
+497
+00:40:39,170 --> 00:40:43,310
+major طبعا انت عندك او انت عندك كل عندك data set
+
+498
+00:40:43,310 --> 00:40:47,950
+لل classification بدك تطبق ال different classifier
+
+499
+00:40:47,950 --> 00:40:52,230
+هدول على نفس ال data set على نفس ال data set و
+
+500
+00:40:52,230 --> 00:40:55,030
+تقارن ما بين ال accuracy و ال precision و ال
+
+501
+00:40:55,030 --> 00:40:59,480
+recall و ال F major طبعا بقى تزودنيبالـ python
+
+502
+00:40:59,480 --> 00:41:02,200
+code اللي انت اعتمدت عليه أو اللي انت اعتمدت عليه
+
+503
+00:41:02,200 --> 00:41:04,620
+طبعا الشغل individual يا جماعة الخير مش groups
+
+504
+00:41:04,620 --> 00:41:08,960
+ممكن تتشاوروا تعملوا discussion مع بعض لاحقا لكن
+
+505
+00:41:08,960 --> 00:41:13,140
+انت هتسلموني الشغل اللي هتسلموني هي شغلتين الأولى
+
+506
+00:41:13,140 --> 00:41:17,000
+ال python code اللي موجود اتنين بالاضافة ل report
+
+507
+00:41:17,000 --> 00:41:20,440
+عن ال experiment اللي انت اشتغلتها او اللي انت
+
+508
+00:41:20,440 --> 00:41:24,160
+اشتغلتيها ال experiment اللي بيقولي شو .. شو اللي
+
+509
+00:41:24,160 --> 00:41:26,920
+.. على سبيل المثال اللي اشتغل كي nearest neighbor
+
+510
+00:41:27,690 --> 00:41:31,070
+جدّاش ال key اللي اعتمدها 4 و لا 5 و لا 7 و لا 8
+
+511
+00:41:31,070 --> 00:41:35,350
+لما اشتغلنا على نية decision tree استخدمت ال
+
+512
+00:41:35,350 --> 00:41:38,110
+information gene و لا استخدمت ال gene ال
+
+513
+00:41:38,110 --> 00:41:41,130
+multilayer receptor لما انت استخدمته جدّاش عدد ال
+
+514
+00:41:41,130 --> 00:41:44,950
+input neuron تبعتك يعني بديت تبولوجي وهانبه توضح
+
+515
+00:41:44,950 --> 00:41:47,950
+لي توصف ال experiment تبعتك و النتيجة اللي طلعت
+
+516
+00:41:47,950 --> 00:41:51,710
+طبعا لأ اخفيكوا انها كانت المفروض تسلم الأسبوع
+
+517
+00:41:51,710 --> 00:41:59,020
+الماضيلكن قدر الله و ما شاء افعل الان انا هحمل و
+
+518
+00:41:59,020 --> 00:42:03,640
+هحط ال assignment على ال model و بتمنى انكوا
+
+519
+00:42:03,640 --> 00:42:07,580
+تشتغلوا و تسلموا و ربنا يكتبلكوا السلامة و العافية
+
+520
+00:42:07,580 --> 00:42:12,340
+دائما انتم و أهليكم أجمعين و السلام عليكم و رحمة
+
+521
+00:42:12,340 --> 00:42:14,080
+الله و بركاته
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/t7uwWVN30g8_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/t7uwWVN30g8_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..69f404e7bfcb02b8f7f10f358b6f45af25d6dce5
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/t7uwWVN30g8_raw.json
@@ -0,0 +1 @@
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749.73, "end": 750.29, "word": " استوعبها", "probability": 0.8916015625}, {"start": 750.29, "end": 750.51, "word": " انا", "probability": 0.61138916015625}, {"start": 750.51, "end": 750.91, "word": " صح", "probability": 0.927001953125}, {"start": 750.91, "end": 751.15, "word": " اللى", "probability": 0.927734375}, {"start": 751.15, "end": 751.39, "word": " هي", "probability": 0.7685546875}, {"start": 751.39, "end": 751.55, "word": " ال", "probability": 0.88623046875}, {"start": 751.55, "end": 752.29, "word": " classification", "probability": 0.7080078125}, {"start": 752.29, "end": 753.15, "word": " في", "probability": 0.1461181640625}, {"start": 753.15, "end": 753.23, "word": " ال", "probability": 0.96484375}, {"start": 753.23, "end": 753.65, "word": " classification", "probability": 0.916015625}, {"start": 753.65, "end": 753.97, "word": " model", "probability": 0.931640625}, {"start": 753.97, "end": 754.15, "word": " ال", "probability": 0.71044921875}, {"start": 754.15, "end": 754.77, "word": " confusion", "probability": 0.80908203125}, {"start": 754.77, "end": 755.45, "word": " matrix", "probability": 0.93798828125}, {"start": 755.45, "end": 756.39, "word": " طبعا", "probability": 0.88671875}, {"start": 756.39, "end": 756.71, "word": " عشان", "probability": 0.9352213541666666}, {"start": 756.71, "end": 757.45, "word": " تبسيط", "probability": 0.9857421875}, {"start": 757.45, "end": 759.43, "word": " المفهوم", "probability": 0.9775390625}, {"start": 759.43, "end": 759.97, "word": " هشتغل", "probability": 0.914453125}, {"start": 759.97, "end": 760.33, "word": " فقط", "probability": 0.986328125}, {"start": 760.33, "end": 760.71, "word": " على", "probability": 0.86572265625}, {"start": 760.71, "end": 761.71, "word": " two", "probability": 0.83349609375}, {"start": 761.71, "end": 762.39, "word": " classes", "probability": 0.9248046875}, {"start": 762.39, "end": 762.61, "word": " على", "probability": 0.62939453125}, {"start": 762.61, "end": 762.89, "word": " binary", "probability": 0.94580078125}, {"start": 762.89, "end": 763.59, "word": " classification", "probability": 0.88818359375}, {"start": 763.59, "end": 764.97, "word": " class", "probability": 0.896484375}, {"start": 764.97, "end": 765.25, "word": " A", "probability": 0.7314453125}, {"start": 765.25, "end": 765.39, "word": " و", "probability": 0.97216796875}, {"start": 765.39, "end": 765.61, "word": " class", "probability": 0.8857421875}, {"start": 765.61, "end": 765.85, "word": " B", "probability": 0.9619140625}, {"start": 765.85, "end": 766.41, "word": " أو", "probability": 0.58251953125}, {"start": 766.41, "end": 766.67, "word": " class", "probability": 0.9775390625}, {"start": 766.67, "end": 766.97, "word": " 1", "probability": 0.5302734375}, {"start": 766.97, "end": 767.57, "word": " C1", "probability": 0.6171875}, {"start": 767.57, "end": 767.71, "word": " و", "probability": 0.97509765625}, {"start": 767.71, "end": 768.37, "word": " C2", "probability": 0.92578125}, {"start": 768.37, "end": 769.75, "word": " اللى", "probability": 0.7230224609375}, {"start": 769.75, "end": 769.91, "word": " هما", "probability": 0.755126953125}, {"start": 769.91, "end": 770.15, "word": " ممكن", "probability": 0.95068359375}, {"start": 770.15, "end": 770.45, "word": " يكونوا", "probability": 0.9036458333333334}, {"start": 770.45, "end": 770.77, "word": " positive", "probability": 0.90185546875}, {"start": 770.77, "end": 770.95, "word": " و", "probability": 0.97021484375}, {"start": 770.95, "end": 771.29, "word": " negative", "probability": 0.93798828125}, {"start": 771.29, "end": 772.01, "word": " يعني", "probability": 0.84912109375}, {"start": 772.01, "end": 772.15, "word": " لو", "probability": 0.630859375}, {"start": 772.15, "end": 772.29, "word": " انا", "probability": 0.83447265625}, {"start": 772.29, "end": 772.57, "word": " افترض", "probability": 0.98779296875}, {"start": 772.57, "end": 772.71, "word": " ان", "probability": 0.91943359375}, {"start": 772.71, "end": 773.03, "word": " class", "probability": 0.92578125}, {"start": 773.03, "end": 773.41, "word": " 1", "probability": 0.705078125}, {"start": 773.41, "end": 774.89, "word": " هذا", "probability": 0.30322265625}, {"start": 774.89, "end": 775.31, "word": " positive", "probability": 0.916015625}], "temperature": 1.0}, {"id": 32, "seek": 80473, "start": 777.09, "end": 804.73, "text": "وهذا negative positive و negative الان من اسمها confusion matrix مصفوفة اللخمة او مصفوفة التشتوت او سميها زي ما بدك انا باستخدمها لانه فعليا تديني بشكل واضح", "tokens": [2407, 3224, 15730, 3671, 3353, 4032, 3671, 2423, 7649, 9154, 24525, 2304, 11296, 15075, 8141, 3714, 9381, 5172, 38688, 3660, 13672, 9778, 46007, 1975, 2407, 3714, 9381, 5172, 38688, 3660, 16712, 8592, 2655, 35473, 1975, 2407, 8608, 2304, 1829, 11296, 30767, 1829, 19446, 47525, 4117, 1975, 8315, 4724, 995, 14851, 9778, 40448, 11296, 5296, 7649, 3224, 6156, 3615, 20292, 995, 6055, 3215, 9957, 1829, 4724, 8592, 28820, 4032, 46958, 5016], "avg_logprob": 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0.84931640625}, {"start": 788.89, "end": 789.33, "word": " اللخمة", "probability": 0.9248046875}, {"start": 789.33, "end": 789.55, "word": " او", "probability": 0.7081298828125}, {"start": 789.55, "end": 790.29, "word": " مصفوفة", "probability": 0.87099609375}, {"start": 790.29, "end": 791.45, "word": " التشتوت", "probability": 0.850830078125}, {"start": 791.45, "end": 791.91, "word": " او", "probability": 0.88818359375}, {"start": 791.91, "end": 793.19, "word": " سميها", "probability": 0.71832275390625}, {"start": 793.19, "end": 793.37, "word": " زي", "probability": 0.849365234375}, {"start": 793.37, "end": 793.43, "word": " ما", "probability": 0.95361328125}, {"start": 793.43, "end": 794.81, "word": " بدك", "probability": 0.921142578125}, {"start": 794.81, "end": 799.01, "word": " انا", "probability": 0.830810546875}, {"start": 799.01, "end": 799.99, "word": " باستخدمها", "probability": 0.8590494791666666}, {"start": 799.99, "end": 800.79, "word": " لانه", "probability": 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44945, 2655, 3555, 2655, 11296, 11778, 16373, 15042, 6225, 8592, 7649, 19446, 8717, 25957, 1211, 8592, 37893, 28820, 3660, 43242, 29739, 3615, 11242, 44381, 11331, 49975, 45164, 1975, 46456, 46538, 2655, 9673, 9381, 5172, 38688, 3660, 9122, 2655, 13546, 1975, 8315, 4724, 25957, 1211, 5296, 11296, 25167, 37495, 22653, 3714, 43020, 1975, 25957, 1211, 25167, 8978, 1975, 15042, 19452, 6055, 7649, 10632, 1975, 2407, 8978, 1975, 15042, 19452, 6055, 4587, 23557, 11296, 20666, 24999, 43501, 46599, 6027, 2655, 6027, 1829, 1975, 25957, 1211, 2423, 17630, 34105], "avg_logprob": -0.2721456660060432, "compression_ratio": 1.8199233716475096, "no_speech_prob": 1.4543533325195312e-05, "words": [{"start": 805.83, "end": 806.27, "word": "وين", "probability": 0.5611572265625}, {"start": 806.27, "end": 806.43, "word": " ال", "probability": 0.71337890625}, {"start": 806.43, "end": 806.59, "word": " data", "probability": 0.56396484375}, {"start": 806.59, "end": 806.97, "word": " set", "probability": 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{"start": 821.07, "end": 821.79, "word": " اختلفت", "probability": 0.91552734375}, {"start": 821.79, "end": 822.37, "word": " المصفوفة", "probability": 0.9638671875}, {"start": 822.37, "end": 823.29, "word": " كتير", "probability": 0.6652018229166666}, {"start": 823.29, "end": 823.45, "word": " انا", "probability": 0.837890625}, {"start": 823.45, "end": 823.79, "word": " بعمل", "probability": 0.8922526041666666}, {"start": 823.79, "end": 824.01, "word": " لها", "probability": 0.6761474609375}, {"start": 824.01, "end": 824.61, "word": " transpose", "probability": 0.62890625}, {"start": 824.61, "end": 826.37, "word": " يعني", "probability": 0.9208984375}, {"start": 826.37, "end": 826.65, "word": " ممكن", "probability": 0.9658203125}, {"start": 826.65, "end": 826.93, "word": " اعمل", "probability": 0.7608235677083334}, {"start": 826.93, "end": 827.49, "word": " transpose", "probability": 0.57666015625}, {"start": 827.49, "end": 827.93, "word": " في", "probability": 0.97412109375}, {"start": 827.93, "end": 829.51, "word": " اماكن", "probability": 0.9064127604166666}, {"start": 829.51, "end": 830.01, "word": " تانية", "probability": 0.9923502604166666}, {"start": 830.01, "end": 830.31, "word": " او", "probability": 0.85546875}, {"start": 830.31, "end": 830.43, "word": " في", "probability": 0.459716796875}, {"start": 830.43, "end": 831.01, "word": " اماكن", "probability": 0.5814615885416666}, {"start": 831.01, "end": 831.45, "word": " تقراها", "probability": 0.76483154296875}, {"start": 831.45, "end": 832.17, "word": " بالtranspose", "probability": 0.6735432942708334}, {"start": 832.17, "end": 833.05, "word": " وبالتالي", "probability": 0.9609375}, {"start": 833.05, "end": 833.35, "word": " اعمل", "probability": 0.8722330729166666}, {"start": 833.35, "end": 833.47, "word": " ال", "probability": 0.476806640625}, {"start": 833.47, "end": 833.87, "word": " prediction", "probability": 0.9560546875}, {"start": 833.87, "end": 834.33, "word": " هنا", "probability": 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جبتهوش في المقابل هذا الألف صنفته هان أو بالأحرى قال لي أنا ما أخطأتش ولا حاجة هان أو خلينا نقول أخطأ اخطألي بألف هان و جابلي هان تمانين ألف", "tokens": [10721, 8315, 10874, 3555, 2655, 6055, 3794, 27884, 5551, 46538, 20328, 5016, 4032, 5551, 46538, 19446, 10874, 3555, 47395, 2407, 8592, 8978, 9673, 4587, 16758, 1211, 23758, 16247, 46538, 20328, 1863, 5172, 47395, 8032, 7649, 34051, 20666, 10721, 5016, 2288, 7578, 50239, 32239, 41850, 19446, 5551, 9778, 9566, 10721, 2655, 8592, 49429, 11331, 26108, 3660, 8032, 7649, 34051, 16490, 20292, 8315, 8717, 39648, 5551, 9778, 9566, 10721, 1975, 9778, 9566, 10721, 20292, 4724, 10721, 46538, 8032, 7649, 4032, 10874, 16758, 20292, 8032, 7649, 46811, 7649, 9957, 5551, 46538], "avg_logprob": -0.21084971508283293, "compression_ratio": 1.89937106918239, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 1646.83, "end": 1647.17, "word": "أنا", "probability": 0.77099609375}, {"start": 1647.17, "end": 1647.43, "word": " جبت", "probability": 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1680.7, "end": 1707.16, "text": "فعليا ال accuracy تبعتي هتكون تسعة و تمانين الف على ميت الف صح فالنسبة تبعتي تسعة و تمانين في المية ال accuracy عالية و ممتازة و ما شاء الله عليها لكنها", "tokens": [5172, 3615, 20292, 995, 2423, 14170, 6055, 3555, 3615, 31371, 8032, 2655, 30544, 6055, 3794, 27884, 4032, 46811, 7649, 9957, 27188, 15844, 3714, 36081, 27188, 20328, 5016, 6156, 6027, 1863, 35457, 3660, 6055, 3555, 3615, 31371, 6055, 3794, 27884, 4032, 46811, 7649, 9957, 8978, 9673, 10632, 2423, 14170, 6225, 6027, 10632, 4032, 3714, 2304, 2655, 31377, 3660, 4032, 19446, 13412, 16606, 21984, 25894, 11296, 44381, 11296], "avg_logprob": -0.19846081511298222, "compression_ratio": 1.7432432432432432, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 1680.7, "end": 1681.3, "word": "فعليا", "probability": 0.78662109375}, {"start": 1681.3, "end": 1681.4, "word": " ال", "probability": 0.455810546875}, {"start": 1681.4, "end": 1681.74, "word": " accuracy", "probability": 0.7138671875}, 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{"id": 83, "seek": 214058, "start": 2115.52, "end": 2140.58, "text": "و 210 حالة و هم فعليا yes و ال system عملهم prediction no يعني 300 حالة ال 10,000 حالة اللي عندى 300 حالة سرطان و 9700 غير سرطان او خلايا تضخم طبيعى غير سرطانى الان ملاحظين لو انا جيت حسبت ال accuracy ال accuracy 96", "tokens": [2407, 42692, 11331, 6027, 3660, 4032, 8032, 2304, 6156, 3615, 20292, 995, 2086, 4032, 2423, 1185, 6225, 42213, 16095, 17630, 572, 37495, 22653, 6641, 11331, 6027, 3660, 2423, 1266, 11, 1360, 11331, 6027, 3660, 13672, 1829, 43242, 7578, 6641, 11331, 6027, 3660, 8608, 2288, 9566, 7649, 4032, 1722, 18197, 32771, 13546, 8608, 2288, 9566, 7649, 1975, 2407, 16490, 15040, 25528, 6055, 11242, 9778, 2304, 23032, 21292, 3615, 7578, 32771, 13546, 8608, 2288, 9566, 7649, 7578, 2423, 7649, 3714, 15040, 5016, 19913, 9957, 45164, 1975, 8315, 10874, 36081, 11331, 35457, 2655, 2423, 14170, 2423, 14170, 24124], "avg_logprob": -0.25358072326829034, "compression_ratio": 1.690721649484536, "no_speech_prob": 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الان", "probability": 0.635498046875}, {"start": 2136.62, "end": 2137.66, "word": " ملاحظين", "probability": 0.89248046875}, {"start": 2137.66, "end": 2138.08, "word": " لو", "probability": 0.90478515625}, {"start": 2138.08, "end": 2138.24, "word": " انا", "probability": 0.7451171875}, {"start": 2138.24, "end": 2138.38, "word": " جيت", "probability": 0.58251953125}, {"start": 2138.38, "end": 2138.86, "word": " حسبت", "probability": 0.9469401041666666}, {"start": 2138.86, "end": 2138.9, "word": " ال", "probability": 0.96728515625}, {"start": 2138.9, "end": 2139.36, "word": " accuracy", "probability": 0.93408203125}, {"start": 2139.36, "end": 2139.72, "word": " ال", "probability": 0.7197265625}, {"start": 2139.72, "end": 2140.04, "word": " accuracy", "probability": 0.939453125}, {"start": 2140.04, "end": 2140.58, "word": " 96", "probability": 0.86865234375}], "temperature": 1.0}, {"id": 84, "seek": 216867, "start": 2142.36, "end": 2168.68, "text": "في المية لأنها عبارة عن مجموعة تسعين زائد خمسة وتسعة تلاف وخمسمية وستين على عشرة ألف ال accuracy عالية جدا لكن اه لو نظرت في الموضوع لو فكرت احسب ال precision و ال recall لل cancer او لل class الأول لانديهان ملاحظين ال precision كده", "tokens": [41185, 9673, 10632, 5296, 33456, 11296, 6225, 3555, 9640, 3660, 18871, 3714, 7435, 2304, 2407, 27884, 6055, 3794, 3615, 9957, 30767, 16373, 3215, 16490, 2304, 3794, 3660, 34683, 3794, 27884, 6055, 15040, 5172, 4032, 9778, 2304, 38251, 10632, 4032, 14851, 9957, 15844, 6225, 8592, 25720, 5551, 46538, 2423, 14170, 6225, 6027, 10632, 10874, 28259, 44381, 1975, 3224, 45164, 8717, 19913, 43500, 8978, 9673, 2407, 11242, 45367, 45164, 6156, 37983, 2655, 1975, 5016, 35457, 2423, 18356, 4032, 2423, 9901, 24976, 5592, 1975, 2407, 24976, 1508, 16247, 12610, 5296, 7649, 16254, 3224, 7649, 3714, 15040, 5016, 19913, 9957, 2423, 18356, 9122, 3215, 3224], "avg_logprob": -0.2714460676207262, "compression_ratio": 1.6830357142857142, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 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"probability": 0.955078125}, {"start": 2434.86, "end": 2435.16, "word": " على", "probability": 0.65283203125}, {"start": 2435.16, "end": 2435.28, "word": " الـ", "probability": 0.744384765625}, {"start": 2435.28, "end": 2435.74, "word": " accuracy", "probability": 0.77587890625}], "temperature": 1.0}, {"id": 96, "seek": 245803, "start": 2436.61, "end": 2458.03, "text": "الـ Precision الـ Recall والـ F major طبعا انت عندك او انت عندك كل عندك data set لل classification بدك تطبق ال different classifier هدول على نفس ال data set على نفس ال data set و تقارن ما بين ال accuracy و ال precision و ال recall و ال F major طبعا بقى تزودني", "tokens": [6027, 39184, 6001, 40832, 2423, 39184, 9647, 336, 16070, 39184, 479, 2563, 23032, 3555, 3615, 995, 16472, 2655, 43242, 4117, 1975, 2407, 16472, 2655, 43242, 4117, 28242, 43242, 4117, 1412, 992, 24976, 21538, 47525, 4117, 6055, 9566, 3555, 4587, 2423, 819, 1508, 9902, 8032, 3215, 12610, 15844, 8717, 36178, 2423, 1412, 992, 15844, 8717, 36178, 2423, 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discussion مع بعض لاحقا لكن انت هتسلموني الشغل اللي هتسلموني هي شغلتين الأولى ال python code اللي موجود اتنين بالاضافة ل report عن ال experiment اللي انت اشتغلتها او اللي انت اشتغلتيها ال experiment اللي بيقولي شو .. شو اللي .. على سبيل المثال اللي اشتغل كي nearest neighbor", "tokens": [3555, 6027, 39184, 38797, 3089, 13672, 1829, 16472, 2655, 1975, 34268, 2304, 3215, 2655, 47356, 34051, 13672, 1829, 16472, 2655, 1975, 34268, 2304, 3215, 2655, 47356, 23032, 3555, 3615, 995, 25124, 17082, 1211, 2609, 35186, 10874, 15042, 27884, 33962, 13546, 37893, 3935, 3714, 43020, 6055, 2655, 8592, 995, 13063, 14407, 6055, 25957, 1211, 14407, 5017, 20449, 45030, 11242, 20193, 5016, 4587, 995, 44381, 16472, 2655, 8032, 2655, 3794, 19528, 11536, 1829, 25124, 17082, 1211, 13672, 1829, 8032, 2655, 3794, 19528, 11536, 1829, 39896, 13412, 17082, 1211, 2655, 9957, 16247, 12610, 7578, 2423, 38797, 3089, 13672, 1829, 3714, 29245, 23328, 1975, 2655, 1863, 9957, 20666, 46958, 31845, 3660, 5296, 2275, 18871, 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"probability": 0.724609375}, {"start": 2522.64, "end": 2523.28, "word": " بتمنى", "probability": 0.8341471354166666}, {"start": 2523.28, "end": 2523.64, "word": " انكوا", "probability": 0.84521484375}, {"start": 2523.64, "end": 2524.2, "word": " تشتغلوا", "probability": 0.9700520833333334}, {"start": 2524.2, "end": 2524.36, "word": " و", "probability": 0.89697265625}, {"start": 2524.36, "end": 2525.02, "word": " تسلموا", "probability": 0.94921875}, {"start": 2525.02, "end": 2525.58, "word": " و", "probability": 0.93017578125}, {"start": 2525.58, "end": 2525.82, "word": " ربنا", "probability": 0.9840494791666666}, {"start": 2525.82, "end": 2526.32, "word": " يكتبلكوا", "probability": 0.87451171875}, {"start": 2526.32, "end": 2526.94, "word": " السلامة", "probability": 0.9591471354166666}, {"start": 2526.94, "end": 2527.04, "word": " و", "probability": 0.8642578125}, {"start": 2527.04, "end": 2527.58, "word": " العافية", "probability": 0.9817708333333334}, {"start": 2527.58, "end": 2528.04, "word": " دائما", "probability": 0.93359375}, {"start": 2528.04, "end": 2528.54, "word": " انتم", "probability": 0.6202392578125}, {"start": 2528.54, "end": 2529.1, "word": " و", "probability": 0.7080078125}, {"start": 2529.1, "end": 2529.58, "word": " أهليكم", "probability": 0.89111328125}, {"start": 2529.58, "end": 2530.22, "word": " أجمعين", "probability": 0.95634765625}, {"start": 2530.22, "end": 2530.9, "word": " و", "probability": 0.442626953125}, {"start": 2530.9, "end": 2531.24, "word": " السلام", "probability": 0.977294921875}, {"start": 2531.24, "end": 2531.76, "word": " عليكم", "probability": 0.954833984375}, {"start": 2531.76, "end": 2531.96, "word": " و", "probability": 0.99755859375}, {"start": 2531.96, "end": 2532.34, "word": " رحمة", "probability": 0.9182942708333334}, {"start": 2532.34, "end": 2532.74, "word": " الله", "probability": 0.97314453125}, {"start": 2532.74, "end": 2533.34, "word": " و", "probability": 0.99267578125}, {"start": 2533.34, "end": 2534.08, "word": " بركاته", "probability": 0.8751220703125}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 2534.9224375, "duration_after_vad": 2424.261249999995}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/t7uwWVN30g8_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/t7uwWVN30g8_raw.srt
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@@ -0,0 +1,2088 @@
+1
+00:00:02,230 --> 00:00:04,390
+بسم الله الرحمن الرحيم الصلاة والسلام على رسول
+
+2
+00:00:04,390 --> 00:00:08,590
+الله أهلا وسهلا بكم أخواني الطلاب و أخواتي
+
+3
+00:00:08,590 --> 00:00:15,370
+الطالبات سنستكمل اليوم في هذا التسجيل موضوع ال
+
+4
+00:00:15,370 --> 00:00:19,050
+classification model evaluation بعد أن اتعرفت على
+
+5
+00:00:20,110 --> 00:00:25,050
+هي عبارة عن تحديد الـ Membership لجروب أو لكتجوري
+
+6
+00:00:25,050 --> 00:00:30,070
+معروفة مسبقا و اتعرفت على مجموعة من ال classifiers
+
+7
+00:00:30,070 --> 00:00:33,690
+بدءا من ال kennerist neighbor واعتماده و شفنا انه
+
+8
+00:00:33,690 --> 00:00:36,610
+بيعتمد على الحساب على ال similarity distance
+
+9
+00:00:36,610 --> 00:00:42,550
+وحكينا انه بيعتمد عليها او بقارن او باستخدام
+
+10
+00:00:42,550 --> 00:00:47,110
+different distances زي ال including distance او ال
+
+11
+00:00:47,110 --> 00:00:52,600
+Manhattan distanceوتكلمنا على الـ Naive bias كـ
+
+12
+00:00:52,600 --> 00:00:57,280
+classifier وشوفنا كيف ال probability او كيف تم
+
+13
+00:00:57,280 --> 00:00:59,400
+حسبة ال probability او ال conditional probability
+
+14
+00:00:59,400 --> 00:01:05,100
+وانتقلنا بعد هي كان لموضوع ال decision tree وشوفنا
+
+15
+00:01:05,100 --> 00:01:08,920
+كيف بنينا ال decision tree مع بعض واخر classifier
+
+16
+00:01:08,920 --> 00:01:12,080
+كان ل neural network او ال multilinear perceptron
+
+17
+00:01:12,080 --> 00:01:16,200
+او ال classifier كان neural network الآن بعد ما
+
+18
+00:01:16,200 --> 00:01:20,480
+أنا بنيتالموديل هذا و اصبح عملية ال classification
+
+19
+00:01:20,480 --> 00:01:24,220
+مش لازم انا اعرف جدش عملية ال classification تبعتي
+
+20
+00:01:24,220 --> 00:01:28,320
+صح او كده فبتيجي عملية ال evaluation هان فعليا
+
+21
+00:01:28,320 --> 00:01:35,340
+عشان تقولي انا والله بدي اقيم العناصر اللي موجودة
+
+22
+00:01:35,340 --> 00:01:39,460
+عندى يعنى عفو مش العناصر بدي اقيم اداء ال
+
+23
+00:01:39,460 --> 00:01:42,260
+classifier اللي موجود عندى يعنى فلما احنا بنتكلم
+
+24
+00:01:42,260 --> 00:01:46,830
+على evaluation يعني ان انا بتتكلم علىتقييم فعلي
+
+25
+00:01:46,830 --> 00:01:52,610
+للـ classifier اللي موجود عندى و هذا هم فحوة
+
+26
+00:01:52,610 --> 00:01:56,490
+محاضرتنا لليوم أو في التسجيل هذا ان شاء الله تعالى
+
+27
+00:01:57,520 --> 00:02:00,740
+طبعا بحب اذكر فقط بداية ان اذكر بعض الشغلات
+
+28
+00:02:00,740 --> 00:02:04,660
+الأساسية قلنا من ال basic concept الخاص بال
+
+29
+00:02:04,660 --> 00:02:07,540
+classifier في عند مصطلح ال accuracy و قلنا ال
+
+30
+00:02:07,540 --> 00:02:11,280
+accuracy هي عبارة على قدرة ال classifier التنبؤ
+
+31
+00:02:11,280 --> 00:02:16,220
+بشكل صحيح و عادة بتمثل النسبة عدد ال prediction
+
+32
+00:02:16,220 --> 00:02:22,560
+الصحيح على كل predictions اللي سواها على كل عمليات
+
+33
+00:02:22,560 --> 00:02:26,700
+التنبؤ اللي سواها ال classifier اللي موجودة عندها
+
+34
+00:02:27,990 --> 00:02:31,930
+وبالتالي سنقول إن الـ Accuracy بتشير لعملية القدرة
+
+35
+00:02:31,930 --> 00:02:36,090
+للـ classifier إنه يعمل correct prediction of the
+
+36
+00:02:36,090 --> 00:02:39,950
+class label for unseen data وتكلمنا عن الـ Speed
+
+37
+00:02:39,950 --> 00:02:44,210
+قلنا إنها عبارة عن computational cost الخاصة بالـ
+
+38
+00:02:44,210 --> 00:02:47,870
+classifier لما تكلمنا عن computational cost
+
+39
+00:02:50,350 --> 00:02:54,410
+أنا بهمني الوقت اللي بده يستغرقه ال classifier
+
+40
+00:02:54,410 --> 00:02:58,350
+سواء في عملية ال training أو حتى في عملية ال
+
+41
+00:02:58,350 --> 00:03:05,870
+classification نفسها أو ال prediction نفسها عفوا و
+
+42
+00:03:05,870 --> 00:03:08,430
+اتكلمنا كذلك على ال robustness و قولنا ال
+
+43
+00:03:08,430 --> 00:03:12,170
+robustness هي عبارة عن القدرة القدرة ال classifier
+
+44
+00:03:12,170 --> 00:03:17,690
+على انه يعمل correct predictionلما يكون فيه عندي
+
+45
+00:03:17,690 --> 00:03:23,830
+أنا noisy data لما يكون فيه عندي noisy data ال بعد
+
+46
+00:03:23,830 --> 00:03:26,690
+هي تكلمنا على ال scalability وقلنا ال scalability
+
+47
+00:03:26,690 --> 00:03:32,970
+تشير إلى قدرة ال classifier على القدرة على ان انا
+
+48
+00:03:32,970 --> 00:03:39,410
+فعليا ابني classifier بشكل مجدي في حالة وجود
+
+49
+00:03:39,410 --> 00:03:43,780
+البياناتالضخمة اللي موجودة عندي و Interpretability
+
+50
+00:03:43,780 --> 00:03:49,000
+أو قدرة على تفسير أو على فهم العناصر أو فهم
+
+51
+00:03:49,000 --> 00:03:55,840
+الإيهاءات الصادرة أو المعلومات الصادرة عن ال
+
+52
+00:03:55,840 --> 00:03:58,200
+classifier اللي موجود و طبعا زي ما قولنا عملية
+
+53
+00:03:58,200 --> 00:04:01,440
+تفسيرها دايما عملية subjective حسب الأشخاص و حسب
+
+54
+00:04:01,440 --> 00:04:06,380
+ال difficulties اللي أنا بدي أقيمهافعليا عملية ال
+
+55
+00:04:06,380 --> 00:04:10,940
+evaluation لل classifiers أو ال classification
+
+56
+00:04:10,940 --> 00:04:19,340
+models عملية نوعا ما فيها نوع من الخداع
+
+57
+00:04:19,340 --> 00:04:25,640
+لكنها فعلا عملية ممكن تكون نوعا ما غير واضحة أو
+
+58
+00:04:25,640 --> 00:04:29,120
+فيها بعض الخبايا لازم الواحد ينتبه لها عشان هيك
+
+59
+00:04:29,120 --> 00:04:34,220
+بنقول نسميها tricky أو خداعةطبعاً لما نتكلم عن
+
+60
+00:04:34,220 --> 00:04:38,820
+evaluation أول evaluation أو أول metric ممكن يخطر
+
+61
+00:04:38,820 --> 00:04:44,260
+في بالي هي عبارة عن ال accuracy أول
+
+62
+00:04:44,260 --> 00:04:47,540
+metric ممكن يخطر في بالي في التقييم أو في ال
+
+63
+00:04:47,540 --> 00:04:51,820
+evaluation هي عبارة عن ال accuracy لكنها مش هي
+
+64
+00:04:51,820 --> 00:04:56,880
+الوحيدة طبعاً هنا لما نتكلم على ال accuracy معناته
+
+65
+00:04:56,880 --> 00:05:01,840
+أنا استخدم باعتمادي على test setأنا الـ training
+
+66
+00:05:01,840 --> 00:05:08,740
+set استخدمته في لحظة بناء
+
+67
+00:05:08,740 --> 00:05:13,480
+الموديل و ال test set جا دورها عشان أهي عبارة عن
+
+68
+00:05:13,480 --> 00:05:21,700
+unlabeled set و أنا بدي أعملها prediction وبناء
+
+69
+00:05:21,700 --> 00:05:25,640
+عليك بقيم ال accuracy في سؤال مهم جدا يا جماعة
+
+70
+00:05:25,640 --> 00:05:31,460
+الخيار هل ال test setهي عبارة عن labelled data أو
+
+71
+00:05:31,460 --> 00:05:36,140
+labelled set أو unlabelled set كمان مرة السؤال
+
+72
+00:05:36,140 --> 00:05:39,980
+بأطرحه الآن بقول هل ال test set هي عبارة عن
+
+73
+00:05:39,980 --> 00:05:44,040
+labelled set أو unlabelled set بين جثيم هل لازم
+
+74
+00:05:44,040 --> 00:05:50,820
+يكون لها label ولا مش لازم يكون لها label المفروض
+
+75
+00:05:51,690 --> 00:06:00,230
+الان تعمل pause للـ recording هذا وتحاول تفكر
+
+76
+00:06:00,230 --> 00:06:03,690
+بالجواب احنا بتذكر ان طرحنا خلال المحاضرات السابقة
+
+77
+00:06:03,690 --> 00:06:09,090
+الجواب الصحيح انه لازم تكون labelled لأن لو ماكانش
+
+78
+00:06:09,090 --> 00:06:12,190
+فيه label مش هقدر اعمل evaluation مش هقدر اعرف
+
+79
+00:06:12,190 --> 00:06:14,770
+جديش ال prediction الصحيح من ال prediction الخطأ
+
+80
+00:06:14,770 --> 00:06:18,550
+وبالتالي ال test set must be labelled
+
+81
+00:06:21,470 --> 00:06:24,250
+طبعا عندي الـ methods اللي انا ممكن استخدمها مع ال
+
+82
+00:06:24,250 --> 00:06:27,710
+classifier مع ال classification هان هي عبارة عن
+
+83
+00:06:27,710 --> 00:06:31,290
+مجموعة من ال .. ال method أو في عندي two methods
+
+84
+00:06:31,290 --> 00:06:36,010
+أساسيات أنا بستخدمهم عشان أتنبأ أو أقدر أعمل تقدير
+
+85
+00:06:36,010 --> 00:06:40,110
+لل accuracy الخاصة بال classifier في عندها ال
+
+86
+00:06:40,110 --> 00:06:44,590
+holdout method و ال holdout method بتعتمد على ال
+
+87
+00:06:44,590 --> 00:06:49,760
+random samplingو طبعا هنا فعليا انا بقى زي ما قلنا
+
+88
+00:06:49,760 --> 00:06:52,640
+سابقا و زي ما كان في ال assignment السابق انا
+
+89
+00:06:52,640 --> 00:06:57,160
+فعليا ال data set اللي موجودة عندها بغض النظر عن
+
+90
+00:06:57,160 --> 00:07:02,460
+حجمها جسمتها ل two partitions سبعين على سبيل
+
+91
+00:07:02,460 --> 00:07:09,500
+المثال في المية لل training و تلاتين في الميةكانت
+
+92
+00:07:09,500 --> 00:07:13,380
+للـ Testing هذه الميثود بسميها holdout method و
+
+93
+00:07:13,380 --> 00:07:18,700
+بجسم ال data set تبعتي ل training and test set و
+
+94
+00:07:18,700 --> 00:07:21,220
+بعدين الطريقة التانية اللي احنا بسميها ال cross
+
+95
+00:07:21,220 --> 00:07:24,500
+validation و ال cross validation هي عبارة عن مثل
+
+96
+00:07:24,500 --> 00:07:29,100
+كذلك موجودة غالبا معظم استخدامها لما بتكون ال data
+
+97
+00:07:29,100 --> 00:07:36,600
+set تبعتي حجمها قليل هروح بتفاصيلهم بشكل كويسطبعاً
+
+98
+00:07:36,600 --> 00:07:41,260
+لما أتكلم على cross validation طريقة ممتازة جداً
+
+99
+00:07:41,260 --> 00:07:46,160
+بحيث أنه أنا أعرض ال data set بالكامل في ال
+
+100
+00:07:46,160 --> 00:07:50,980
+training على أجزاء مختلفة و كذلك باختبر كل ال data
+
+101
+00:07:50,980 --> 00:07:54,900
+set و بطلع بالمتوسط اللي موجود لما أنا بتكلم على
+
+102
+00:07:54,900 --> 00:07:58,180
+cross validation بتكلم إن هي عبارة عن statistical
+
+103
+00:07:58,180 --> 00:08:02,270
+method تستخدممن أجل الـ evaluation للـ
+
+104
+00:08:02,270 --> 00:08:05,170
+generalization الـ generalization جماعة الخير
+
+105
+00:08:05,170 --> 00:08:10,470
+المقصود فيها هان ان انا بأتكلم قاعد على او بتكلم
+
+106
+00:08:10,470 --> 00:08:16,670
+على قدرة النظام على التنبؤ الصحيح هو اتعلم بناء
+
+107
+00:08:16,670 --> 00:08:22,070
+على ال training data الان انا بدأ اشوف فعليا كيف
+
+108
+00:08:22,070 --> 00:08:25,610
+أداء النظام او ده ال model اللي موجود عندي هان
+
+109
+00:08:25,910 --> 00:08:29,510
+فكلمة الـ model بيقدر يتعامل أو يكون أداء تبعه
+
+110
+00:08:29,510 --> 00:08:33,270
+بكون كويس مع unseen data معناته هو more general
+
+111
+00:08:33,270 --> 00:08:36,910
+more general يعني ما انبناش فقط من أو مكان مش
+
+112
+00:08:36,910 --> 00:08:40,830
+specific لل training data اللي استخدمناها بل
+
+113
+00:08:40,830 --> 00:08:44,790
+بالعكس هو شغال على general data set على أي data
+
+114
+00:08:44,790 --> 00:08:48,750
+set هيشتغلوا بكفاءة كويسة طبعا ال performance data
+
+115
+00:08:48,750 --> 00:08:50,730
+are more stable
+
+116
+00:08:55,210 --> 00:09:01,010
+using split طبعاً
+
+117
+00:09:01,010 --> 00:09:03,770
+اللي متكلم عن الـ cross validation نتكلم إنه ال
+
+118
+00:09:03,770 --> 00:09:07,690
+performance هذا أو خلنا نقول ال estimation تبعت ال
+
+119
+00:09:07,690 --> 00:09:11,330
+accuracy أو ال performance تبعت ال ال model هان
+
+120
+00:09:11,330 --> 00:09:16,410
+هتكون أكثر موثوقية أو أكثر ثباتاً ما إنه لو أنا
+
+121
+00:09:16,410 --> 00:09:20,690
+فعاليا قسمت ال data set ل training أو testing لأن
+
+122
+00:09:20,690 --> 00:09:25,360
+موضوع ال randomness بيعمل فعلا مشكلةحقيقية فالـ
+
+123
+00:09:25,360 --> 00:09:28,380
+cross validation بدل ما انا جسم ال data set
+
+124
+00:09:28,380 --> 00:09:35,340
+لمجمعتين فعليا انا بجسم ال data بشكل متكرر
+
+125
+00:09:35,340 --> 00:09:37,600
+repeatedly شو يعني؟
+
+126
+00:09:40,410 --> 00:09:44,890
+مفهومها أنه انا فعلياً بروح بأجسم افترض ان هذه
+
+127
+00:09:44,890 --> 00:09:49,890
+الخط ال data كل واحد من ال rows هاي بمثل ال data
+
+128
+00:09:49,890 --> 00:09:54,350
+set كاملة الفكرة فيها انه انا اجسمها لمجموعة من ال
+
+129
+00:09:54,350 --> 00:09:58,350
+fold وال fold هذه واحدة منهم تستخدم لل training
+
+130
+00:09:58,350 --> 00:10:06,460
+والباقي يستخدم لعفوا واحدة للتست والباقي يستخدم ال
+
+131
+00:10:06,460 --> 00:10:11,400
+lettering يعني تخيل لو انا قلت هي ال data set اللي
+
+132
+00:10:11,400 --> 00:10:14,560
+موجودة عندي سامحوني انا مش جادر اعمل control كتير
+
+133
+00:10:14,560 --> 00:10:17,420
+على ال mouse او على ال pen اللي موجود معاياها
+
+134
+00:10:18,550 --> 00:10:22,390
+جسمتها لأربع أجزاء فبشكل متكرر باجي بقول والله
+
+135
+00:10:22,390 --> 00:10:26,570
+الجزء هذا الآن هو المخصص لل training والتلاتة هدوة
+
+136
+00:10:26,570 --> 00:10:31,410
+عفوا لل test والتلاتة هدوة المخصصين لمين لموضوع ال
+
+137
+00:10:31,410 --> 00:10:35,290
+training في الدورة التانية بحدد هذا لل test
+
+138
+00:10:35,290 --> 00:10:40,810
+والباقي هذا كله ل training ولاحظوا في كل مرة انا
+
+139
+00:10:40,810 --> 00:10:43,750
+باعتمد على القيمة اللي بتطلع من موضوع ال testing
+
+140
+00:10:43,750 --> 00:10:49,580
+هنا ال accuracy ال accuracyالـ Accuracy وليس
+
+141
+00:10:49,580 --> 00:10:52,280
+بالضرورة في كل مرة تديني نفس القيمة بالعكس تديني
+
+142
+00:10:52,280 --> 00:10:58,640
+قيم مختلفة في النهاية أحصل على أو أحاول أخد الـ
+
+143
+00:10:58,640 --> 00:11:02,380
+Average الخاصة بالـ Accuracy اللي موجودة هيك عشان
+
+144
+00:11:02,380 --> 00:11:06,260
+هيك بنقول انه فعليا ان ال cross validation more
+
+145
+00:11:06,260 --> 00:11:09,540
+stable لكن فعليا لو أنا كانت عند ال data ستة باعت
+
+146
+00:11:09,540 --> 00:11:14,170
+كبيرةداتا 6 بقعت كبيرة كبيرة زي ما بتكلم 100 ألف
+
+147
+00:11:14,170 --> 00:11:17,890
+record أو أو 50 ألف record و أطلع و روحت والله أنا
+
+148
+00:11:17,890 --> 00:11:21,910
+أخدت منها 30% و عارف انه في مستخدم ال stratified
+
+149
+00:11:21,910 --> 00:11:26,970
+sampling عشان اضمن ان في عندي balance في ال data
+
+150
+00:11:26,970 --> 00:11:32,870
+اللي موجودة عندى ال .. ما بين ال different classes
+
+151
+00:11:32,870 --> 00:11:36,790
+او different labels بتديني نتيجة برضه موطوقة و
+
+152
+00:11:36,790 --> 00:11:40,340
+ممكن تكون أسرع من ال cross validation تمامبغض
+
+153
+00:11:40,340 --> 00:11:44,240
+النظر الطريقة اللي اتبعتها كانت الـ K-fold cross
+
+154
+00:11:44,240 --> 00:11:48,000
+-validation طبعا الـ K نرمز لها هان اللي هي عدد ال
+
+155
+00:11:48,000 --> 00:11:53,000
+folds اللي انت بدك تجسم فيها ده ك set يعني انا لما
+
+156
+00:11:53,000 --> 00:11:55,800
+اقولك مثلا بالمثال اللي موجود عندنا على ال slide
+
+157
+00:11:55,800 --> 00:12:01,220
+فعليا انا خمسةمعناته في كل part يتمثل عشرين في
+
+158
+00:12:01,220 --> 00:12:03,820
+المية عشرين في المية testing و تمانين في المية
+
+159
+00:12:03,820 --> 00:12:07,020
+training لاحظوا ان انا زي مرحلة ال training ممكن
+
+160
+00:12:07,020 --> 00:12:13,360
+اقوم بجسمها لعشرة عشرة في المية testing وتستعين في
+
+161
+00:12:13,360 --> 00:12:17,000
+المية training في حالتي انا حاولت ارسمها اربعة
+
+162
+00:12:17,000 --> 00:12:20,740
+عشرين في المية testing وخمسة وسبعين في المية
+
+163
+00:12:20,740 --> 00:12:25,300
+training فحسب ال data او حسب تقسيمك لل data اللي
+
+164
+00:12:25,300 --> 00:12:29,730
+موجود عندك تماممن الشغلات المهمة جدا اللى لازم
+
+165
+00:12:29,730 --> 00:12:33,230
+استوعبها انا صح اللى هي ال classification في ال
+
+166
+00:12:33,230 --> 00:12:36,710
+classification model ال confusion matrix طبعا عشان
+
+167
+00:12:36,710 --> 00:12:42,890
+تبسيط المفهوم هشتغل فقط على two classes على binary
+
+168
+00:12:42,890 --> 00:12:47,710
+classification class A و class B أو class 1 C1 و
+
+169
+00:12:47,710 --> 00:12:52,010
+C2 اللى هما ممكن يكونوا positive و negative يعني
+
+170
+00:12:52,010 --> 00:12:58,050
+لو انا افترض ان class 1 هذا positiveوهذا negative
+
+171
+00:12:58,050 --> 00:13:05,790
+positive و negative الان من اسمها confusion matrix
+
+172
+00:13:05,790 --> 00:13:08,890
+مصفوفة
+
+173
+00:13:08,890 --> 00:13:19,010
+اللخمة او مصفوفة التشتوت او سميها زي ما بدك انا
+
+174
+00:13:19,010 --> 00:13:26,590
+باستخدمها لانه فعليا تديني بشكل واضحوين ال data
+
+175
+00:13:26,590 --> 00:13:32,910
+set تباعتي راحت الفكرة أنه الآن لو انا قلت ان
+
+176
+00:13:32,910 --> 00:13:36,010
+الموزع طبعا هذه التوزيعة بنتبتها دائما عشان ما
+
+177
+00:13:36,010 --> 00:13:42,370
+نعملش مشكلة عند البعض لكن حتى لو اختلفت المصفوفة
+
+178
+00:13:42,370 --> 00:13:46,930
+كتير انا بعمل لها transpose يعني ممكن اعمل
+
+179
+00:13:46,930 --> 00:13:51,450
+transpose في اماكن تانية او في اماكن تقراها
+
+180
+00:13:51,450 --> 00:13:55,790
+بالtranspose وبالتالي اعمل ال prediction هناوالـ
+
+181
+00:13:55,790 --> 00:14:00,930
+actual classes موجودة هنا لكن انا باعتمد على ان
+
+182
+00:14:00,930 --> 00:14:03,470
+الـ actual row موجودة في ال rows و ال predicted
+
+183
+00:14:03,470 --> 00:14:09,010
+موجودة في ال columns تمام معناته انا في عندى class
+
+184
+00:14:09,010 --> 00:14:13,010
+1 و class 2 positive و negative وهدول ال data set
+
+185
+00:14:13,010 --> 00:14:17,630
+اللي موجودة عندى هنامحدش قال لي مطلقا تعالى نجي
+
+186
+00:14:17,630 --> 00:14:20,950
+على الرسمة اللي بس اللي هان محدش قاللي مطلقا ان ال
+
+187
+00:14:20,950 --> 00:14:24,270
+prediction تبعتي لازم تكون صحيحة 100% يعني لو كانت
+
+188
+00:14:24,270 --> 00:14:28,950
+ال data tests تبعتي هي مقسمة بين الأخضر والأحمر
+
+189
+00:14:28,950 --> 00:14:33,650
+وال predictive model الأخضر المفروض positive
+
+190
+00:14:33,650 --> 00:14:38,410
+والأحمر negativeالله يبعد عنكم الشرك والأحباب كل
+
+191
+00:14:38,410 --> 00:14:42,090
+يوم احنا بنتكلم على كورونا فيروس موجود في العالم و
+
+192
+00:14:42,090 --> 00:14:45,390
+الكل بتجري فحوصات positive معناته هذا بيدخل في
+
+193
+00:14:45,390 --> 00:14:49,090
+المستشفى ويبدو رعاية صحية negative بيبقى في الحجر
+
+194
+00:14:49,090 --> 00:14:52,690
+الصحي لحد ما تنتهي ال 14 يوم و نتأكد ان الفيروس مش
+
+195
+00:14:52,690 --> 00:14:55,970
+موجود مش هذا اللي بيصير الله يعافيكوا و أهليكوا
+
+196
+00:14:55,970 --> 00:14:59,970
+وكل أحبابكوا يا رب العالمينالان الـ system
+
+197
+00:14:59,970 --> 00:15:03,210
+positive أو negative فالـ system هو اللي بده يعمل
+
+198
+00:15:03,210 --> 00:15:07,270
+prediction بناءً على ال data الان هو جلب .. لاحظوا
+
+199
+00:15:07,270 --> 00:15:10,390
+هو ب6 عينات هنا ال data set كلها عملها
+
+200
+00:15:10,390 --> 00:15:13,150
+classification انتوا ملاحظين انه في عندي أنا هنا
+
+201
+00:15:13,150 --> 00:15:21,330
+سبعة وفي عندي تمانية يعني هدول 15 element سبعة
+
+202
+00:15:21,330 --> 00:15:25,730
+positive وتمانية negative فلما عمل ال prediction
+
+203
+00:15:25,730 --> 00:15:29,600
+عمل أربعةأو قال لي انه في عندك sub المجموع ال
+
+204
+00:15:29,600 --> 00:15:33,400
+positive قال لي في عندي ست حالات لكن واضح ان هو
+
+205
+00:15:33,400 --> 00:15:37,520
+أخطأ في حالتين أخطأ في الحمر هدول صح تمام و ال
+
+206
+00:15:37,520 --> 00:15:42,980
+negative زيها طيب نيشي الآن في ال actual انا فعليا
+
+207
+00:15:42,980 --> 00:15:47,580
+عندي واحدة اتين تلاتة اربع خمسة ستة يعني الصف هذا
+
+208
+00:15:47,580 --> 00:15:55,380
+على امتدادهبتكون مجموعه عبارة عن مجموع العناصر أو
+
+209
+00:15:55,380 --> 00:16:01,020
+عدد العناصر الـ positive cases أو كل الـ rows اللي
+
+210
+00:16:01,020 --> 00:16:06,320
+بتنتمي ل class 1 true positive هي عبارة عن الـ
+
+211
+00:16:06,320 --> 00:16:12,920
+rows اللي هي فعليا بتنتميلـ Class 1 و الـ system
+
+212
+00:16:12,920 --> 00:16:17,400
+عملها prediction as class 1 يعني صنفها بشكل صحيح
+
+213
+00:16:17,400 --> 00:16:21,420
+فبقولها true يعني تصنيفها كان صحيح و هي فعليا
+
+214
+00:16:21,420 --> 00:16:26,460
+positive و طبعا ما تنساش او ما تنسيش ان انا بتكلم
+
+215
+00:16:26,460 --> 00:16:31,040
+على binary classification اسهل الموضوع تمام ماهو
+
+216
+00:16:31,040 --> 00:16:34,760
+ال false negative ال false negative هي فعليا
+
+217
+00:16:34,760 --> 00:16:38,400
+elements بتنتمي ل class 1 و هي positive لكن
+
+218
+00:16:38,400 --> 00:16:43,020
+صنفليها بالخطأأو أخطأ في تصنيفها و حط ليها إيش على
+
+219
+00:16:43,020 --> 00:16:46,520
+إنها negative وبالتالي أصبحت عندي هنا false
+
+220
+00:16:46,520 --> 00:16:51,020
+negative مجموح هدول العنصرين ال true positive و ال
+
+221
+00:16:51,020 --> 00:16:54,240
+false negative ال true positive و ال false
+
+222
+00:16:54,240 --> 00:16:58,780
+negative هو بتديني عدد عناصر ال class الأول تمام؟
+
+223
+00:16:58,780 --> 00:17:02,480
+طيب بالنسبة لل class التاني هو عملها prediction
+
+224
+00:17:02,480 --> 00:17:08,500
+على إنها class one يعني هو قال إنها positive لكنه
+
+225
+00:17:08,500 --> 00:17:12,570
+ال prediction هذا خطأليش؟ لأن هي في الحقيقة تنتمي
+
+226
+00:17:12,570 --> 00:17:16,250
+ل class 2 اللي هو الـ negative فهي فعليا negative
+
+227
+00:17:16,250 --> 00:17:19,710
+ولكن عملها prediction على إنها positive فهي false
+
+228
+00:17:19,710 --> 00:17:25,350
+positive تمام؟ وتبقى عندها ال true negative هي
+
+229
+00:17:25,350 --> 00:17:30,110
+class 2 صنفها على class 2 صحيح؟ وبالتالي هي عبارة
+
+230
+00:17:30,110 --> 00:17:33,990
+عن true negative يعني فعليا لو أنا بدى أفكر
+
+231
+00:17:33,990 --> 00:17:37,630
+بالجدول أو ب confusion matrix لما أنا بدى أنشئها
+
+232
+00:17:37,630 --> 00:17:45,950
+بشكل صحيحأي الجدول هو
+
+233
+00:17:45,950 --> 00:17:51,250
+فيه
+
+234
+00:17:51,250 --> 00:18:01,250
+مساحة بال powerpoint ولا مافيش eraser
+
+235
+00:18:01,250 --> 00:18:05,810
+تمام
+
+236
+00:18:05,810 --> 00:18:08,490
+رجعها لاشي
+
+237
+00:18:17,740 --> 00:18:23,380
+الان احنا متفقين هنا ان انا فعليا هنا عند الـ
+
+238
+00:18:23,380 --> 00:18:27,400
+actual والأعمدة الـ predicted
+
+239
+00:18:34,130 --> 00:18:40,910
+C2 C1 و C2 حسب الرسمة اللي موجودة عندها حاجة
+
+240
+00:18:40,910 --> 00:18:46,930
+اعدنالان كام واحدة فعليا بينتمي ل class one وعملها
+
+241
+00:18:46,930 --> 00:18:49,590
+prediction في ال class one صحيح في ال positive
+
+242
+00:18:49,590 --> 00:18:55,550
+واحدة اتنين تلاتة اربعة تمام
+
+243
+00:18:55,550 --> 00:19:02,410
+طيب و هدول هذه
+
+244
+00:19:02,410 --> 00:19:06,880
+وهذههم أصلا نيجاتيف class 2 لكن اعملهم prediction
+
+245
+00:19:06,880 --> 00:19:14,840
+هان تمام نجي للحالة النيجاتيف هي بتنتمي ل class 1
+
+246
+00:19:14,840 --> 00:19:18,280
+لكن عملها prediction في class 2 اللي هم الخضر اللي
+
+247
+00:19:18,280 --> 00:19:22,340
+هان اتنين لو
+
+248
+00:19:22,340 --> 00:19:27,140
+عديت الخضر اتنين واربعة ستة هي المجموع و هان لازم
+
+249
+00:19:27,140 --> 00:19:33,850
+يكون هنا في عندياشعشان يكتمل عدد 2.68 فهذه هي
+
+250
+00:19:33,850 --> 00:19:37,970
+فعليا ال confusion matrix اللي انا هشغل عليها تمام
+
+251
+00:19:37,970 --> 00:19:41,590
+الآن ال accuracy كون ان انا حسبت ال confusion
+
+252
+00:19:41,590 --> 00:19:46,870
+matrix اتفقنا ان ال accuracy هي عبارة عن ال ratio
+
+253
+00:19:46,870 --> 00:19:56,030
+عدد نسبة ال test table اللي صنفها بشكل صحيح مين هم
+
+254
+00:19:56,030 --> 00:20:02,900
+ال true positiveوالـ true negative و لا لأ تمام
+
+255
+00:20:02,900 --> 00:20:06,700
+معناته ال true positive صحيحة و ال true negative
+
+256
+00:20:06,700 --> 00:20:11,780
+صحيحة هدولة صحيحات فبجمع هذه و هذه على كل عناصر
+
+257
+00:20:11,780 --> 00:20:14,300
+المصفوفة اللي موجودة عندي بكون حصلت على ال
+
+258
+00:20:14,300 --> 00:20:18,620
+accuracy على كل predict على ال cardinality تبعت ال
+
+259
+00:20:18,620 --> 00:20:23,700
+test set اللي انا باتكلم عليها واضحة كمان مرة ال
+
+260
+00:20:23,700 --> 00:20:28,580
+accuracy هي عبارة عن نسبةالـ Rows أو الـ Tables
+
+261
+00:20:28,580 --> 00:20:32,600
+اللي في ال test set اللي نجح ال classifier فيه
+
+262
+00:20:32,600 --> 00:20:39,260
+تصنيفها على حجم ال test set اللي موجودة عندى تمام
+
+263
+00:20:39,260 --> 00:20:44,780
+بالمثال السابق لو انا بدى ارجع هان ال prediction
+
+264
+00:20:44,780 --> 00:20:54,000
+تبعتي عبارة عن ال هان عفوا اربع
+
+265
+00:20:54,000 --> 00:21:03,510
+زائد6 على 15 لأن كل ال data 6 بعد 15 element
+
+266
+00:21:03,510 --> 00:21:09,470
+عديناها قبل شوية يعني بين جثين 12 على 15 لو أنا
+
+267
+00:21:09,470 --> 00:21:14,970
+بتتكلم على 3 بتتكلم على 4 على 5 معناته أنا بتتكلم
+
+268
+00:21:14,970 --> 00:21:19,790
+جاعد حدود ال accuracy تبعتي 80%
+
+269
+00:21:22,870 --> 00:21:26,790
+تمام طبعا ال accuracy عكسة في عند ال error rate
+
+270
+00:21:26,790 --> 00:21:29,650
+طبعا ممكن في عند مصطلح تاني ممكن استخدمه مع ال
+
+271
+00:21:29,650 --> 00:21:35,190
+accuracy اللي هو ايش ال recognition rate وطبعا
+
+272
+00:21:35,190 --> 00:21:38,070
+برضه من المصطلحات المستخدمة accuracy او
+
+273
+00:21:38,070 --> 00:21:41,090
+recognition rate نفس المعنى في عند ال error rate
+
+274
+00:21:41,090 --> 00:21:44,710
+ال error rate طبعا اعلى نسبة اللي هي واحد مصبوط
+
+275
+00:21:44,710 --> 00:21:49,410
+يعني احنا قبل شوية كانت عندى 80% 5 على 4 يعني 8 من
+
+276
+00:21:49,410 --> 00:21:55,830
+10 ال error rate تساوي واحد ناقص8 من 10 وتساوي
+
+277
+00:21:55,830 --> 00:22:01,810
+point اتنين من عشرة او بين جثين اللي هي عشرين فيلم
+
+278
+00:22:01,810 --> 00:22:05,150
+يعني هذا مقدار ال error rate او بين جثين ال error
+
+279
+00:22:05,150 --> 00:22:08,990
+rate زي ما احنا شايفين هنا هي عبارة عن ال false
+
+280
+00:22:08,990 --> 00:22:11,250
+positive و ال false negative
+
+281
+00:22:14,470 --> 00:22:17,770
+له فعليا اللي أخطأ فيه تصنيفهم اللي أخطأ فيه
+
+282
+00:22:17,770 --> 00:22:21,290
+تصنيفهم طبعا جامعة الخيار هنا في شغل مهم جدا طب
+
+283
+00:22:21,290 --> 00:22:23,610
+هذا يا دكتور في حالتي ال binary classification لو
+
+284
+00:22:23,610 --> 00:22:26,490
+حد اتقرح على أي سؤال و قال يا دكتور هذا في حالة ال
+
+285
+00:22:26,490 --> 00:22:30,910
+binary classification طب شوف حالة ال multiple
+
+286
+00:22:30,910 --> 00:22:33,390
+class يعني لو كانت المصفوفة تبعتي ال confusion
+
+287
+00:22:33,390 --> 00:22:42,830
+matrix تبعتي تلاتة في تلاتة ايش
+
+288
+00:22:42,830 --> 00:22:48,350
+ممكن نعملخلّينا نعتمد نفس التوزيع السابقة الـ
+
+289
+00:22:48,350 --> 00:22:54,910
+actual في الأعمدة الـ actual في الصفوف و الـ
+
+290
+00:22:54,910 --> 00:23:00,270
+predicted في الأعمدة معناته هذه هتكون true
+
+291
+00:23:00,270 --> 00:23:07,270
+positive أو هذه false
+
+292
+00:23:07,270 --> 00:23:10,740
+negativeفالس
+
+293
+00:23:27,780 --> 00:23:31,820
+بوزيتف لكن حطيلي اياهم false negative يعني هم جالس
+
+294
+00:23:31,820 --> 00:23:35,360
+.. هو تفسر .. يعني بفهم هيكل يعني c2 و c3 not
+
+295
+00:23:35,360 --> 00:23:39,200
+positive يعني negative فاخدلي اياهم هان كمان في ال
+
+296
+00:23:39,200 --> 00:23:47,040
+class التاني هتكون هذه true negative و هذه false
+
+297
+00:23:47,040 --> 00:23:55,580
+positive false positive ل c1 عفوا عفوا هي c2 و هي
+
+298
+00:23:55,580 --> 00:24:06,300
+c3وهنا ستكون فالس نيجاتيف فالس
+
+299
+00:24:06,300 --> 00:24:09,540
+نيجاتيف فالس نيجاتيف فالس نيجاتيف فالس نيجاتيف
+
+300
+00:24:09,540 --> 00:24:11,220
+فالس نيجاتيف فالس نيجاتيف فالس نيجاتيف فالس
+
+301
+00:24:11,220 --> 00:24:11,220
+نيجاتيف فالس نيجاتيف فالس نيجاتيف فالس نيجاتيف
+
+302
+00:24:11,220 --> 00:24:12,280
+فالس نيجاتيف فالس نيجاتيف فالس نيجاتيف فالس
+
+303
+00:24:12,280 --> 00:24:13,540
+نيجاتيف فالس نيجاتيف فالس نيجاتيف فالس نيجاتيف
+
+304
+00:24:13,540 --> 00:24:16,920
+فالس نيجاتيف فالس نيجاتيف فالس نيجاتيف فالس
+
+305
+00:24:16,920 --> 00:24:25,260
+نيجاتيف فالس نيجاتيف فالهذا الكلام الـ Accuracy
+
+306
+00:24:25,260 --> 00:24:31,800
+ممتازة في حالة ان العناصر او ال class is balanced
+
+307
+00:24:31,800 --> 00:24:35,300
+يعني بنجوسين سبعة و تمانية جرب من بعض خمسين و
+
+308
+00:24:35,300 --> 00:24:40,020
+خمسين تلاتين تلاتين تلاتين او خمسين خمسين خمسين في
+
+309
+00:24:40,020 --> 00:24:43,500
+حالة ال IRIS data setالـ Balance بين ال classes
+
+310
+00:24:43,500 --> 00:24:47,680
+موجودة لكن فعلياً لما انا بتكلم على ال diseases أو
+
+311
+00:24:47,680 --> 00:24:51,060
+في اللي بتكلم على ال fraud detection عمليات النصب
+
+312
+00:24:51,060 --> 00:24:55,620
+في وضعات الاهتمام ال classes in balance شو يعني in
+
+313
+00:24:55,620 --> 00:24:58,480
+balance انه عدد ال elements في الكلة و عدد ال rows
+
+314
+00:24:58,480 --> 00:25:05,320
+مع كل class غير متساوية طبعا أجيب المثال أوضح الله
+
+315
+00:25:05,320 --> 00:25:09,100
+يعافيكم كم مرة وأهليكم جميعا لأن كم واحد بنعمله
+
+316
+00:25:09,100 --> 00:25:15,010
+فحص كورونا حول العالممئات الألف عشرات الألف بلاش
+
+317
+00:25:15,010 --> 00:25:19,370
+مئات الألف كام واحد بتثبت معاه الحالة أقل كتير
+
+318
+00:25:19,370 --> 00:25:26,350
+وبالتالي عدد ال negative أكبر كتير من عدد ال
+
+319
+00:25:26,350 --> 00:25:32,210
+positive ممتاز طب لو أنا سألت سؤال مين أختار؟ واحد
+
+320
+00:25:32,210 --> 00:25:35,490
+ماعهوش فيروس وقال لل system لأ ان هذا عنده فيروس
+
+321
+00:25:35,490 --> 00:25:41,760
+كورونا ولا واحد عنده فيروس كورونا وال systemقال له
+
+322
+00:25:41,760 --> 00:25:48,480
+إنه ما عندهوش شو رايكوا؟ يعني نسبة الخطأ مع ال
+
+323
+00:25:48,480 --> 00:25:50,960
+positive ولا الخطأ مع ال negative هي الأخطر
+
+324
+00:25:50,960 --> 00:25:55,820
+بالنسبة لنا كلامك صح أو كلامك صح الآن لأنه احنا
+
+325
+00:25:55,820 --> 00:26:01,240
+فعليا لما أخطأ ال system وقال له إنه هذا negative
+
+326
+00:26:02,050 --> 00:26:06,030
+false negative كانت مصيبة بالنسبة لي لأن هذا
+
+327
+00:26:06,030 --> 00:26:10,150
+الإنسان سيخلق
+
+328
+00:26:10,150 --> 00:26:13,490
+الناس وبالتالي المرض سينتشر لأنه مش معنى ونهيك عن
+
+329
+00:26:13,490 --> 00:26:17,650
+الأضرار الصحية اللي حدث معاه لكن لو واحد negative
+
+330
+00:26:17,650 --> 00:26:21,290
+ماعندوش المرض و ال system قال إنه عنده المرض إيش
+
+331
+00:26:21,290 --> 00:26:24,990
+هناخده؟ هناخده نحطه في ال health care أو في الحجر
+
+332
+00:26:24,990 --> 00:26:30,540
+الحجر الصحي و بعدين ندي عناية صحية حسب حالتهفي ضرر
+
+333
+00:26:30,540 --> 00:26:34,180
+في الموضوع حتما مافيش ضرر وبالتالي لما بكون في ال
+
+334
+00:26:34,180 --> 00:26:39,220
+class imbalance ال accuracy تبعتي مش صحيحة، ليش؟
+
+335
+00:26:39,220 --> 00:26:43,200
+او بتبقى العفوان غير معدرة بشكل صحيح لأن لو تخيلت
+
+336
+00:26:43,200 --> 00:26:51,820
+ان هنا انا عدد العناصر بدي اشتغل هيك ان عدد
+
+337
+00:26:51,820 --> 00:26:54,260
+العناصر اللي انا بدي افحصها 100 ألف
+
+338
+00:26:58,340 --> 00:27:06,760
+وفعليا او ال data set تبعتي للهيئة كلها كان في
+
+339
+00:27:06,760 --> 00:27:14,140
+عندي مثلا عشرة ألف positive و
+
+340
+00:27:14,140 --> 00:27:22,600
+تسعين ألف negative و لما عملت prediction اجى قال
+
+341
+00:27:22,600 --> 00:27:31,710
+لي والله من العشر تلاف هدولأنا جبت تسعة ألف صح و
+
+342
+00:27:31,710 --> 00:27:46,110
+ألف ما جبتهوش في المقابل هذا الألف صنفته هان أو
+
+343
+00:27:46,110 --> 00:27:49,210
+بالأحرى قال لي أنا ما أخطأتش ولا حاجة هان أو خلينا
+
+344
+00:27:49,210 --> 00:27:54,910
+نقول أخطأ اخطألي بألف هان و جابلي هان تمانين ألف
+
+345
+00:28:00,700 --> 00:28:08,680
+فعليا ال accuracy تبعتي هتكون تسعة و تمانين الف
+
+346
+00:28:08,680 --> 00:28:15,680
+على ميت
+
+347
+00:28:15,680 --> 00:28:20,300
+الف صح فالنسبة تبعتي تسعة و تمانين في المية ال
+
+348
+00:28:20,300 --> 00:28:24,560
+accuracy عالية
+
+349
+00:28:24,560 --> 00:28:29,040
+و ممتازة و ما شاء الله عليها لكنهاتحمل في طياتها
+
+350
+00:28:29,040 --> 00:28:37,840
+خطورة شديدة جدا مع من مع الناس هذول مع
+
+351
+00:28:37,840 --> 00:28:42,880
+اللهان تماموبالتالي الـ Accuracy بطلت عندي مجديا
+
+352
+00:28:42,880 --> 00:28:45,400
+لأن الـ 9.8 محدش يقول عن نسبة مخة في طلق بالعكس
+
+353
+00:28:45,400 --> 00:28:49,080
+نسبة عالية لكنه في عندى مشكلة في ال evaluation
+
+354
+00:28:49,080 --> 00:28:52,980
+تمام وبالتالي انا ممكن اصير ادور على شغل اسمها ال
+
+355
+00:28:52,980 --> 00:28:57,220
+sensitivity الحساسية وطبعا هنا بتكلم على ال true
+
+356
+00:28:57,220 --> 00:29:02,960
+positive rate ال true positive rate على اللي هي
+
+357
+00:29:02,960 --> 00:29:11,720
+نسبة 9000 على العشرة ألفوكذلك في عندي ال
+
+358
+00:29:11,720 --> 00:29:18,900
+specificity التخصيص اللي هي نسبة لل true negative
+
+359
+00:29:18,900 --> 00:29:23,960
+rate جد عشان افصل انا هو ال accuracy بعد ما حصلت
+
+360
+00:29:23,960 --> 00:29:30,060
+عليها مين كان فيه نسبته اعلى عشان اضيفه ومش بس هيك
+
+361
+00:29:30,060 --> 00:29:33,520
+جالي ممكن انا اتكلم على other metrics وهذه الأهم
+
+362
+00:29:33,520 --> 00:29:39,120
+اللي بنسميها احنا ال precision
+
+363
+00:29:44,430 --> 00:29:47,210
+الـ Precision أو الـ Exactness هي عبارة عن الـ
+
+364
+00:29:47,210 --> 00:29:53,310
+ratio لمجموعة التابلز
+
+365
+00:29:53,310 --> 00:29:58,630
+ال classifier صنفهم على أنهم positive و هم فعليا
+
+366
+00:29:58,630 --> 00:30:03,190
+positive نسبة
+
+367
+00:30:03,190 --> 00:30:07,070
+ال labelled اللي جال عليها positive و هي فعليا
+
+368
+00:30:07,070 --> 00:30:09,810
+positive على كل ال actual positive اللي موجودة
+
+369
+00:30:09,810 --> 00:30:12,390
+عندها وين ال actual positive
+
+370
+00:30:18,800 --> 00:30:22,720
+الـ actual هو اللي موجود في جامعة الخير في الأعمدة
+
+371
+00:30:22,720 --> 00:30:37,440
+في العمود في الصفوف الآن ال true positive هي جل
+
+372
+00:30:37,440 --> 00:30:40,720
+ال true positive على كل العناصر الصنافليها على
+
+373
+00:30:40,720 --> 00:30:44,220
+إنها positive عشان أجيب نسبة ال actual positive
+
+374
+00:30:44,220 --> 00:30:49,230
+الحقيقية اللي موجودة عندهاas positive are actually
+
+375
+00:30:49,230 --> 00:30:53,750
+positive نسبة الـ positive الحقيقية فهنا لما أتكلم
+
+376
+00:30:53,750 --> 00:30:57,270
+عن ال precision أو ال exactness بتكلم عليها عناصر
+
+377
+00:30:57,270 --> 00:31:02,330
+الصل عمود الأول تمام لما باجي بتكلم علي ال recall
+
+378
+00:31:02,330 --> 00:31:07,550
+أو ال completeness بتكلم فعليا على نسبة ال
+
+379
+00:31:07,550 --> 00:31:11,130
+positive double واللي فعليا تم تصنيفها على إنها
+
+380
+00:31:11,130 --> 00:31:15,630
+positive نسبة ال positive doubles اللي تصنفت على
+
+381
+00:31:15,630 --> 00:31:19,890
+إنها positive بشكل صحيحوين الـ positive هي الصف
+
+382
+00:31:19,890 --> 00:31:24,810
+الأول اللي
+
+383
+00:31:24,810 --> 00:31:29,090
+احنا قلنا عليها sensitivity قبل لحظات وبالتالي الـ
+
+384
+00:31:29,090 --> 00:31:34,430
+TB بتروح ال true
+
+385
+00:31:34,430 --> 00:31:39,550
+positive على المجموع اللي موجود عندي ال TB و ال FN
+
+386
+00:31:39,550 --> 00:31:45,670
+تمامماعندي الـ F ماعندي الـGalaxy بما أن في عندي
+
+387
+00:31:45,670 --> 00:31:50,730
+الـPrecision و الـRecall هدولة متريكات مختلفة قال
+
+388
+00:31:50,730 --> 00:31:54,210
+في ناس فكرت جالكس نعملهم combination ما بين
+
+389
+00:31:54,210 --> 00:32:00,350
+الـPrecision و الـRecall في متريك واحد و سموه ليا
+
+390
+00:32:00,350 --> 00:32:08,530
+الـF majorودمجونا فيه ال precision و ال recall
+
+391
+00:32:08,530 --> 00:32:12,710
+وكان هو يساوي 2 ضرب ال precision ضرب ال recall على
+
+392
+00:32:12,710 --> 00:32:15,790
+مجموع ال recall و ال precision أو بين قوسين هي ال
+
+393
+00:32:15,790 --> 00:32:20,730
+F1 وهذا أنا باستخدمه لما عادة بفكر بالمقارنة ما
+
+394
+00:32:20,730 --> 00:32:24,740
+بينTWO DIFFERENT CLASSIFIERS الان انا في عندى two
+
+395
+00:32:24,740 --> 00:32:27,500
+different classifiers و بدى اقارن بين الأداء تبعهم
+
+396
+00:32:27,500 --> 00:32:30,740
+واحد ممكن يتفكر بال accuracy ال accuracy ممكن تكون
+
+397
+00:32:30,740 --> 00:32:34,420
+متساوية ما بين الاتنين مابيش ممكن اساوي ممكن اروح
+
+398
+00:32:34,420 --> 00:32:37,940
+على اتجاه ال F مجار اللي انا ممكن تكون طبعا انتم
+
+399
+00:32:37,940 --> 00:32:41,770
+ملاحظين يا جماعة الخيرالـ Recall و ال Precision و
+
+400
+00:32:41,770 --> 00:32:46,370
+ال F Major
+
+401
+00:32:46,370 --> 00:32:53,370
+هدول مرتبطين بال First Attribute يعني لو أنا قلتلك
+
+402
+00:32:53,370 --> 00:32:58,270
+بدي ال F Major ل ال class التاني أو عفوا ال Recall
+
+403
+00:32:58,270 --> 00:33:02,690
+ل ال class التاني ال class التاني هيه بتصير أنا
+
+404
+00:33:02,690 --> 00:33:06,230
+بتتكلم على hand
+
+405
+00:33:08,770 --> 00:33:12,250
+مجموعة الـ Recall True Positive هي لـ Class التاني
+
+406
+00:33:12,250 --> 00:33:16,750
+هذه اللي بتمثل True Positive لل Class اللي موجودة
+
+407
+00:33:16,750 --> 00:33:22,250
+عندي على عدد عناصر اللي هي على عدد الـ N على الـ N
+
+408
+00:33:22,250 --> 00:33:26,830
+اللي موجودة عندها تمام؟ يعني هذه الشغله مرتبطه بال
+
+409
+00:33:26,830 --> 00:33:30,510
+Class لو أنا الآن كان في عندي تلاتة في تلاتة
+
+410
+00:33:34,650 --> 00:33:38,150
+المصفوفة تبعتي بنفس التوزيع لـ Prediction في
+
+411
+00:33:38,150 --> 00:33:41,190
+الأعمدة و الـ Actual .. لـ Predicted في الأعمدة و
+
+412
+00:33:41,190 --> 00:33:44,830
+الـ Actual في الصفورة و أنا الجيل قلت والله هاي ال
+
+413
+00:33:44,830 --> 00:33:50,230
+values اللي عندي الان بدي ال precision عفوا عشان
+
+414
+00:33:50,230 --> 00:33:54,950
+القانون ال recall بدي ال recall تبعتي التالت لسي
+
+415
+00:33:54,950 --> 00:33:59,830
+تلاتة و ال true positive تبعت ال class تلاتة هيها
+
+416
+00:34:02,430 --> 00:34:09,630
+هي فعليًا actually بتنتمي لـ C3 و الـ system جالب
+
+417
+00:34:09,630 --> 00:34:12,810
+predicted as C3 فعليًا هذه الـ true positive ما
+
+418
+00:34:12,810 --> 00:34:18,030
+دون ذلك الـ false negative هدولة تنتمي و بالتالي
+
+419
+00:34:18,030 --> 00:34:25,310
+ال recall لـ C3 لو انا افترض ان هذه Y وهذه Z تساوي
+
+420
+00:34:25,310 --> 00:34:30,990
+معناته ال recall لـ C3 بدها تساوي X
+
+421
+00:34:32,990 --> 00:34:40,490
+على y زائد z زائد x اللي هي بجموع كل العناصر اللي
+
+422
+00:34:40,490 --> 00:34:45,250
+موجودة عندي و طبعا y و z هم بمثله ال false
+
+423
+00:34:45,250 --> 00:34:49,670
+positive أو عفوا ال false negative ل c3 طيب
+
+424
+00:34:49,670 --> 00:34:54,710
+بالمثال خليني أخد مثال بالأرقامفي انها النتج الـ
+
+425
+00:34:54,710 --> 00:34:57,410
+classifier اللي اشتغل على ال prediction للكانسر
+
+426
+00:34:57,410 --> 00:35:01,050
+بتنبأ بالكانسر عدد الحالات اللي موجودة عندى انا
+
+427
+00:35:01,050 --> 00:35:07,330
+الف حالة كان فعليا اشتغل اللي لما وزعناهم كانت
+
+428
+00:35:07,330 --> 00:35:13,250
+عندي تسعين حالة كانوا yes و ال system عملهم
+
+429
+00:35:13,250 --> 00:35:19,320
+prediction yesو 210 حالة و هم فعليا yes و ال
+
+430
+00:35:19,320 --> 00:35:24,500
+system عملهم prediction no يعني 300 حالة ال 10,000
+
+431
+00:35:24,500 --> 00:35:31,420
+حالة اللي عندى 300 حالة سرطان و 9700 غير سرطان او
+
+432
+00:35:31,420 --> 00:35:38,240
+خلايا تضخم طبيعى غير سرطانى الان ملاحظين لو انا
+
+433
+00:35:38,240 --> 00:35:43,720
+جيت حسبت ال accuracy ال accuracy 96في المية لأنها
+
+434
+00:35:43,720 --> 00:35:48,420
+عبارة عن مجموعة تسعين زائد خمسة وتسعة تلاف وخمسمية
+
+435
+00:35:48,420 --> 00:35:54,280
+وستين على عشرة ألف ال accuracy عالية جدا لكن اه لو
+
+436
+00:35:54,280 --> 00:35:59,380
+نظرت في الموضوع لو فكرت احسب ال precision و ال
+
+437
+00:35:59,380 --> 00:36:05,260
+recall لل cancer او لل class الأول لانديهان
+
+438
+00:36:05,260 --> 00:36:11,100
+ملاحظين ال precision كدهالـ precision احنا قلنا هي
+
+439
+00:36:11,100 --> 00:36:15,980
+عبارة عن ال exactness مظبوط فعليا جداش تنبأ بشكل
+
+440
+00:36:15,980 --> 00:36:21,160
+او بشكل صحيح لل data اللي موجودة عندها وصار واضح
+
+441
+00:36:21,160 --> 00:36:29,160
+الفرق قلنا 90 على 230 قلنا في ال precision بتكلم
+
+442
+00:36:29,160 --> 00:36:35,700
+على عمود و لما اتكلم بال recall بتكلم وينعلى الصف
+
+443
+00:36:35,700 --> 00:36:43,340
+صحيح عشان هيك 90 على 230 لـ precision و 90 على 300
+
+444
+00:36:43,340 --> 00:36:48,520
+اللي هي ال recall اللي موجودة عندها لكن تخيل انه
+
+445
+00:36:48,520 --> 00:36:53,820
+انا فعليا لو قعدت ترتيب العناصر في المصفوفة بحيث
+
+446
+00:36:53,820 --> 00:36:58,960
+انه خلت ال target تبعتي No وقولت
+
+447
+00:36:58,960 --> 00:37:01,600
+انا بدي احسب ال recall و ال precision لاحظوا ال
+
+448
+00:37:01,600 --> 00:37:05,530
+accuracy ما اتغيرتشلكن انا عيد ترتيب الأعمد يعني
+
+449
+00:37:05,530 --> 00:37:07,930
+برينج وستين صار اهتمامي هان highly true positive
+
+450
+00:37:07,930 --> 00:37:11,370
+لاحظوا ان ال precision تبعتي جداش عالي صارت و ال
+
+451
+00:37:11,370 --> 00:37:14,910
+recall تبعتي جداش على كل مقالة زي ما قولنا ال
+
+452
+00:37:14,910 --> 00:37:18,470
+perfect value تبعتنا هان حكينا ان ال perfect او ال
+
+453
+00:37:18,470 --> 00:37:23,990
+score is one كذلك مع ال precisionالـ perfect score
+
+454
+00:37:23,990 --> 00:37:28,290
+هو 1 وبهكد انا بكون بدي اعمل evaluation لل classes
+
+455
+00:37:28,290 --> 00:37:31,650
+اللي موجود عندها وبالتالي انا بدي انتبه دائما لل
+
+456
+00:37:31,650 --> 00:37:34,710
+class اللي موجود بالنسبة لل code اللي له علاقة بال
+
+457
+00:37:34,710 --> 00:37:39,550
+بايثونانا هنا روحت اعمل import لل data set كان
+
+458
+00:37:39,550 --> 00:37:43,970
+المعتاد على نفس المثال السابق روحت اعمل import
+
+459
+00:37:43,970 --> 00:37:47,210
+عشان اعمل split لل data set والمفروض ان انتوا هاي
+
+460
+00:37:47,210 --> 00:37:51,590
+جربتوها من خلال ال assignment اللي سلمته فانا حصلت
+
+461
+00:37:51,590 --> 00:37:55,850
+على ال training set اللي هنا من خلال ال split هذه
+
+462
+00:37:55,850 --> 00:37:59,790
+train test split جسمتلي او ادتني نتيجة ادتني four
+
+463
+00:37:59,790 --> 00:38:05,010
+different set ال X train و ال label تبعتها
+
+464
+00:38:08,770 --> 00:38:17,890
+الـ Y لليابيل و X للattributes و ال test text test
+
+465
+00:38:17,890 --> 00:38:21,470
+و ال Y test طبعا قلت له هان تلاتين في المية نسبة
+
+466
+00:38:21,470 --> 00:38:25,010
+ال test تلاتين في المية و طبعا هضل الباجي لليترين
+
+467
+00:38:26,020 --> 00:38:29,600
+من الـ target data و استدعيت ناييف بايسين على سبيل
+
+468
+00:38:29,600 --> 00:38:36,180
+المثال و روحت و قلت جوسان ناييف بايسين استدعيت ال
+
+469
+00:38:36,180 --> 00:38:40,460
+constructor قلتله روح بنيت model و قلتله اعمل fit
+
+470
+00:38:40,460 --> 00:38:46,280
+اللي بتعمل hand training وقلنا
+
+471
+00:38:46,280 --> 00:38:53,000
+في ناييف بايسين بروح ببنيني جدول الاحتمالاتبعد ذلك
+
+472
+00:38:53,000 --> 00:38:59,860
+قمت بالتفكير في مجموع يسميته Y-predict هذا هو
+
+473
+00:38:59,860 --> 00:39:05,200
+النتائج الـ model.predict ودّيته X test بالكامل
+
+474
+00:39:05,200 --> 00:39:09,840
+لاحظت أنني سميتها Y-predict أنا عندي ال test هي ال
+
+475
+00:39:09,840 --> 00:39:14,020
+label تباعتها موجودة هنا Y-test فروحت وحصلت عليها
+
+476
+00:39:14,020 --> 00:39:17,280
+تمام صارت في عندي الـ predicted وصارت عندي موجود
+
+477
+00:39:17,280 --> 00:39:22,560
+من ال actual label فالانأنا قاعد بقى أشتغل روحت
+
+478
+00:39:22,560 --> 00:39:25,980
+عملت import بدي أجيب ال matrix from ASCII layer
+
+479
+00:39:25,980 --> 00:39:29,080
+import ال matrix و ال matrix هي فيها كل حاجة فيها
+
+480
+00:39:29,080 --> 00:39:32,440
+ال accuracy score و طبعا كل ال method في ال matrix
+
+481
+00:39:32,440 --> 00:39:36,960
+بدها مني ال y predicted و ال y test ال y test هي
+
+482
+00:39:36,960 --> 00:39:40,840
+موجودة أنا حصلت اللي هي فعليا ال actual و ال y
+
+483
+00:39:40,840 --> 00:39:43,600
+predicted هي الموجودة عندها فلما أنا قلتله ال
+
+484
+00:39:43,600 --> 00:39:46,300
+accuracy score ده نسبة ال confusion matrix طبع
+
+485
+00:39:46,300 --> 00:39:49,560
+ليها و ال classifier او ال classification report
+
+486
+00:39:50,850 --> 00:39:55,090
+بتدين الأفمجة و ال precision و ال recall لكل class
+
+487
+00:39:55,090 --> 00:40:00,790
+موجود عندي و هيك نهينا أو ختمنا chapter لل
+
+488
+00:40:00,790 --> 00:40:04,470
+classification بتمنى تكون الشروحات واضحة إذا في أي
+
+489
+00:40:04,470 --> 00:40:08,450
+استفسار لازم يكون من خلال ال model أو ال forum
+
+490
+00:40:08,450 --> 00:40:12,450
+اللي موجود عندي هنا أخر شغلة مطلوب منها ال
+
+491
+00:40:12,450 --> 00:40:16,190
+assignment البسيط هذا ال assignment هذا بدو يعمل
+
+492
+00:40:16,190 --> 00:40:18,650
+مقارنة بين three different classifiers
+
+493
+00:40:21,320 --> 00:40:26,020
+أخذنا أربعة classifiers كي نتعرف على الـ K-nearest
+
+494
+00:40:26,020 --> 00:40:28,500
+neighbour، الـ Naive bison، الـ decision tree و
+
+495
+00:40:28,500 --> 00:40:31,840
+الـ Multilayer Perceptron الـ classifier اللي هو
+
+496
+00:40:31,840 --> 00:40:34,860
+تبع الـ neural network وأنا بدي أقارن بينهم بناء
+
+497
+00:40:34,860 --> 00:40:39,170
+على الـ accuracyالـ Precision الـ Recall والـ F
+
+498
+00:40:39,170 --> 00:40:43,310
+major طبعا انت عندك او انت عندك كل عندك data set
+
+499
+00:40:43,310 --> 00:40:47,950
+لل classification بدك تطبق ال different classifier
+
+500
+00:40:47,950 --> 00:40:52,230
+هدول على نفس ال data set على نفس ال data set و
+
+501
+00:40:52,230 --> 00:40:55,030
+تقارن ما بين ال accuracy و ال precision و ال
+
+502
+00:40:55,030 --> 00:40:59,480
+recall و ال F major طبعا بقى تزودنيبالـ python
+
+503
+00:40:59,480 --> 00:41:02,200
+code اللي انت اعتمدت عليه أو اللي انت اعتمدت عليه
+
+504
+00:41:02,200 --> 00:41:04,620
+طبعا الشغل individual يا جماعة الخير مش groups
+
+505
+00:41:04,620 --> 00:41:08,960
+ممكن تتشاوروا تعملوا discussion مع بعض لاحقا لكن
+
+506
+00:41:08,960 --> 00:41:13,140
+انت هتسلموني الشغل اللي هتسلموني هي شغلتين الأولى
+
+507
+00:41:13,140 --> 00:41:17,000
+ال python code اللي موجود اتنين بالاضافة ل report
+
+508
+00:41:17,000 --> 00:41:20,440
+عن ال experiment اللي انت اشتغلتها او اللي انت
+
+509
+00:41:20,440 --> 00:41:24,160
+اشتغلتيها ال experiment اللي بيقولي شو .. شو اللي
+
+510
+00:41:24,160 --> 00:41:26,920
+.. على سبيل المثال اللي اشتغل كي nearest neighbor
+
+511
+00:41:27,690 --> 00:41:31,070
+جدّاش ال key اللي اعتمدها 4 و لا 5 و لا 7 و لا 8
+
+512
+00:41:31,070 --> 00:41:35,350
+لما اشتغلنا على نية decision tree استخدمت ال
+
+513
+00:41:35,350 --> 00:41:38,110
+information gene و لا استخدمت ال gene ال
+
+514
+00:41:38,110 --> 00:41:41,130
+multilayer receptor لما انت استخدمته جدّاش عدد ال
+
+515
+00:41:41,130 --> 00:41:44,950
+input neuron تبعتك يعني بديت تبولوجي وهانبه توضح
+
+516
+00:41:44,950 --> 00:41:47,950
+لي توصف ال experiment تبعتك و النتيجة اللي طلعت
+
+517
+00:41:47,950 --> 00:41:51,710
+طبعا لأ اخفيكوا انها كانت المفروض تسلم الأسبوع
+
+518
+00:41:51,710 --> 00:41:59,020
+الماضيلكن قدر الله و ما شاء افعل الان انا هحمل و
+
+519
+00:41:59,020 --> 00:42:03,640
+هحط ال assignment على ال model و بتمنى انكوا
+
+520
+00:42:03,640 --> 00:42:07,580
+تشتغلوا و تسلموا و ربنا يكتبلكوا السلامة و العافية
+
+521
+00:42:07,580 --> 00:42:12,340
+دائما انتم و أهليكم أجمعين و السلام عليكم و رحمة
+
+522
+00:42:12,340 --> 00:42:14,080
+الله و بركاته
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/u2_vU8et3ig.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/u2_vU8et3ig.srt
new file mode 100644
index 0000000000000000000000000000000000000000..61783096804da548aaa33fae492d24ea8dee44c6
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/u2_vU8et3ig.srt
@@ -0,0 +1,1279 @@
+1
+00:00:04,940 --> 00:00:07,000
+باسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:07,000 --> 00:00:11,420
+أهلا وسهلا بكم في محاضراتنا المستمرة في منصّة الـ data
+
+3
+00:00:11,420 --> 00:00:14,620
+mining، وما زلنا في باب الـ classification أو في باب
+
+4
+00:00:14,620 --> 00:00:18,120
+التصنيف. سنتكلم اليوم، أو في هذه المحاضرة إن شاء
+
+5
+00:00:18,120 --> 00:00:22,940
+الله تعالى، عن Classifierٍ متقدمٍ جدًا، مستخدم بشكل
+
+6
+00:00:22,940 --> 00:00:26,500
+كبير جدًا، وهو الـ Neural Network as Classifier أو
+
+7
+00:00:26,500 --> 00:00:30,000
+بالتحديد الـ Back-propagation Neural Network.  لـ
+
+8
+00:00:30,000 --> 00:00:33,740
+أُخفيكم، كان عندي تردد: أشرحه أم أشرح الـ Support
+
+9
+00:00:33,740 --> 00:00:37,240
+Vector Machine؟ كلاهما من المواضيع المتقدمة، و
+
+10
+00:00:37,240 --> 00:00:40,760
+التي تحتاج إلى Optimization عالية. لكن قررتُ أن
+
+11
+00:00:40,760 --> 00:00:44,320
+أشرح الـ Neural Network، كما كنا قد ذكرناه سابقًا، وخلّينا
+
+12
+00:00:44,320 --> 00:00:47,700
+نبدأ مع الـ Neural Network. الـ Neural Network أو
+
+13
+00:00:47,700 --> 00:00:51,400
+الشبكات العصبية... العصبية. بكفي أنا عصبي!
+
+14
+00:00:51,400 --> 00:00:55,360
+بالجمال، الشبكات العصبية هي عبارة عن
+
+15
+00:00:55,360 --> 00:00:59,980
+مجموعة من الـ connected input و الـ output units.
+
+16
+00:00:59,980 --> 00:01:04,850
+يعني، ببساطة، هي عبارة عن مجموعة من المدخلات
+
+17
+00:01:04,850 --> 00:01:10,390
+والمخرجات المتصلة مع بعضها البعض. وكل خط أو كل
+
+18
+00:01:10,390 --> 00:01:15,210
+Connection، أو كل خط، أو كل Link، له وزن معين
+
+19
+00:01:15,210 --> 00:01:21,010
+associated with it، مرتبط به. خلال مرحلتي التعليم
+
+20
+00:01:21,010 --> 00:01:24,370
+وهنا، يا جماعة الخير، بدأنا ننتبه جيدًا، لأن صار في عندي
+
+21
+00:01:24,370 --> 00:01:27,390
+ما يُقال لنا: نحن Machine Learning. Machine Learning هي
+
+22
+00:01:27,390 --> 00:01:32,570
+الفترة التي أقضيها في بناء الـ Model،  لأن
+
+23
+00:01:32,570 --> 00:01:35,770
+هكذا قلنا في البداية خالصًا: الـ Classification، في عندي
+
+24
+00:01:35,770 --> 00:01:39,690
+Model-based، وفي عندي Instance-based. الـ Instance
+
+25
+00:01:39,690 --> 00:01:42,550
+based كان: K-Nearest Neighbor، و الـ Model-based: Decision
+
+26
+00:01:42,550 --> 00:01:46,150
+Tree، و الـ Naive Bayesian. سؤال مهم جدًا، أريد أن أطرحه
+
+27
+00:01:46,150 --> 00:01:51,430
+عليكم. أتمنى أن تفكّروا في إجابته، لأن
+
+28
+00:01:51,430 --> 00:01:56,390
+هل الـ Naive Bayes Model-based أم Instance-based؟
+
+29
+00:01:56,390 --> 00:02:00,070
+هذا سؤال. السؤال الثاني: الـ Naive Bayes Algorithm،
+
+30
+00:02:00,070 --> 00:02:03,890
+الجدول الذي بنيته، كم مرّة بنيته؟
+
+31
+00:02:06,390 --> 00:02:11,390
+المفروض مرة واحدة. متى أحتاج إلى إعادة بنائه؟ لو تغيرت
+
+32
+00:02:11,390 --> 00:02:14,850
+الـ Training Set الموجودة عندي. وبالتالي، المفروض
+
+33
+00:02:14,850 --> 00:02:18,090
+أنّ هذا الجدول يمثّل عندي الـ Model خلال مرحلة التعليم،
+
+34
+00:02:18,090 --> 00:02:21,430
+مرحلة الـ Learning، مرحلة بناء الـ Model، الـ Network،
+
+35
+00:02:21,430 --> 00:02:25,610
+الذي هو الشبكة العصبية. تحاول تعديل الأوزان التي
+
+36
+00:02:25,610 --> 00:02:30,810
+موجودة عندها، حتى تصل إلى
+
+37
+00:02:30,810 --> 00:02:37,860
+الـ Label. يعني، بين قوسين: أدخلت الـ Input، عملت
+
+38
+00:02:37,860 --> 00:02:42,900
+Computation، حصلت على الـ Output. أقارن بين الـ
+
+39
+00:02:42,900 --> 00:02:46,680
+Output الحقيقي، والـ Predicted، وتبعًا للـ Error الذي
+
+40
+00:02:46,680 --> 00:02:49,600
+بينهما، أو الفرق الذي بينهما، أعمل Adjustment للـ
+
+41
+00:02:49,600 --> 00:02:50,880
+Weights الموجودة عندها.
+
+42
+00:02:55,350 --> 00:02:57,970
+الآن، الـ Neural Network، بشكل عام، يا جماعة الخير، هي
+
+43
+00:02:57,970 --> 00:03:01,010
+تحاكي الشبكات العصبية في الإنسان، أو الجهاز
+
+44
+00:03:01,010 --> 00:03:03,910
+العصبي في الإنسان. في الآخر، الـ Decision في الدماغ،
+
+45
+00:03:03,910 --> 00:03:09,510
+والخلايا العصبية منتشرة على كل جسمك. لو أنت ساكت، أو
+
+46
+00:03:09,510 --> 00:03:13,710
+سرحان، وقاعد بتحل في مسألة في الـ Data Mining، وجاء
+
+47
+00:03:13,710 --> 00:03:23,320
+زميلك، وطرف دبوس، وحاول يشكك في يدك، بدون ما تنتبه له،
+
+48
+00:03:23,320 --> 00:03:27,400
+أنت، بدون إرادة، ستجد أنّ يدك تحرّكت في الاتجاه
+
+49
+00:03:27,400 --> 00:03:31,980
+المضاد للّمسة، بحيث أنّها، يعني، تبعد عن مصدر الخطر.
+
+50
+00:03:31,980 --> 00:03:35,680
+الذي صار، أنت فعليًا لا تعرف ما الذي حدث، لكن مجرد
+
+51
+00:03:35,680 --> 00:03:38,840
+أنّك حركت، أبعدت يدك، ثم بدأت تفكر، لأنّ كانت
+
+52
+00:03:38,840 --> 00:03:42,240
+الحركة، أو الجهاز العصبي، أرسل إشارة إلى الدماغ، والدماغ
+
+53
+00:03:42,240 --> 00:03:45,260
+أخذ Processing سريعًا جدًا، أنّه: ابعد عن
+
+54
+00:03:45,260 --> 00:03:47,980
+الخطر هذا. وكذلك، يحدث هذا معنا في هذا الموضوع، عندما يكون
+
+55
+00:03:47,980 --> 00:03:52,510
+الشغلات: حريق، إلخ. الآن، هذا الكلام لم يحدث إلا
+
+56
+00:03:52,510 --> 00:03:56,330
+من خلال خبرة مكتسبة، موجودة عندنا. فالـ Neural
+
+57
+00:03:56,330 --> 00:03:58,870
+Network جاءت، لماذا؟ لأن الناس فكّروا فيها، في الـ
+
+58
+00:03:58,870 --> 00:04:03,050
+خمسينات، جاءت فكرة: لماذا لا نحاول محاكاة عقل الإنسان في
+
+59
+00:04:03,050 --> 00:04:07,410
+التعامل؟ نحن لا نهتم كثيرًا بالصبغة التاريخية
+
+60
+00:04:07,410 --> 00:04:13,090
+والتفاصيل كثيرًا. لكن بشكل عام، أبسط نموذج للشبكة
+
+61
+00:04:13,090 --> 00:04:15,690
+الموجودة عندي، لأنّ في النهاية، كل شيء Computation،
+
+62
+00:04:15,690 --> 00:04:20,450
+يا جماعة الخير، هي مجموعة الـ Input. مجموعة الـ Input،
+
+63
+00:04:20,450 --> 00:04:25,970
+الآن، ما هو P1 إلى PR؟ هي عبارة عن الـ Attributes،
+
+64
+00:04:25,970 --> 00:04:31,350
+تمثّل
+
+65
+00:04:31,350 --> 00:04:36,790
+الـ Input. طيب، وما هو A؟
+
+66
+00:04:36,790 --> 00:04:44,280
+الـ Output، للـ Class الموجود عندي هنا. الـ
+
+67
+00:04:44,280 --> 00:04:47,380
+Class الموجود عندي. ما الذي حدث؟ ما الذي فعلته فعليًا؟
+
+68
+00:04:47,380 --> 00:04:52,960
+كل Attribute له وزن. فأنا آخذ، أضرب قيمة الـ
+
+69
+00:04:52,960 --> 00:04:57,080
+Attribute، لاحظ، أقول: أضرب قيمة الـ Attribute في
+
+70
+00:04:57,080 --> 00:05:05,800
+الوزن، أجمعها، أضيف لها قيمة للـ Bias، و هذه الـ Function
+
+71
+00:05:05,800 --> 00:05:09,460
+تُجري Decision. أي واحد من الـ Binary Classification،
+
+72
+00:05:09,460 --> 00:05:13,210
+أو من الـ Classes، ستكون صفر أو واحد. يعني Binary
+
+73
+00:05:13,210 --> 00:05:17,090
+Classification. انتبه معي، وانتبه معي عندما
+
+74
+00:05:17,090 --> 00:05:20,830
+قلت: آخذ قيمة الـ Attribute، وأضربها. طيب، هل من الممكن أن
+
+75
+00:05:20,830 --> 00:05:24,390
+أعمل مع الـ Nominal Attribute؟ لا، هذا غير ممكن. الـ Data
+
+76
+00:05:24,390 --> 00:05:28,170
+Set الخاصة بك يجب أن تكون رقمية بالكامل. لأن لا يوجد مدى
+
+77
+00:05:28,170 --> 00:05:31,690
+أذهب إليه وأقول: والله، الـ Gender Male، أضرب في خمسة.
+
+78
+00:05:31,690 --> 00:05:34,990
+حوّلها إلى 0، 1، أو أي Attribute رقمي تراه
+
+79
+00:05:34,990 --> 00:05:39,170
+مناسبًا. الـ Income، كما رأينا قبل قليل، Fair و
+
+80
+00:05:39,170 --> 00:05:43,940
+Excellent،  أيضًا، تُحوّل إلى أرقام. وبالتالي، بدلًا
+
+81
+00:05:43,940 --> 00:05:46,800
+من أن تكون Category، تُحوّل إلى أرقام.
+
+82
+00:05:46,800 --> 00:05:51,960
+تمام، حتى لو كان هناك Coding موجودة عندي، في النهاية، ما
+
+83
+00:05:51,960 --> 00:05:58,140
+سيحدث سيكون كالتالي: الـ Function الخاصة بي، الـ Prediction
+
+84
+00:05:58,140 --> 00:06:02,520
+Function الخاصة بي، هي عبارة عن Vector من الأوزان، مضروبة
+
+85
+00:06:02,520 --> 00:06:07,450
+في الـ Input، زائد الـ Bias الموجود عندي. في مرحلة
+
+86
+00:06:07,450 --> 00:06:15,310
+الـ Learning، تصبح الشبكة تبحث عن أفضل W و B، لأنّ
+
+87
+00:06:15,310 --> 00:06:19,530
+أنت لا تنسَ أنّها معادلة خطّ مستقيم، تبحث عن أفضل W
+
+88
+00:06:19,530 --> 00:06:23,770
+و B، لكن بـ Vectors. W تمثّل الأوزان الخاصة بـ
+
+89
+00:06:23,770 --> 00:06:26,630
+الـ Connection، و B تمثّل الـ Bias الخاصة بالـ Network، التي
+
+90
+00:06:26,630 --> 00:06:30,210
+موجودة في الـ Multilayer Neural Network. شغلنا هنا
+
+91
+00:06:30,210 --> 00:06:30,870
+مختلف.
+
+92
+00:06:33,410 --> 00:06:39,370
+سابقًا، كان عندي فقط Input و Output، في الـ Simple
+
+93
+00:06:39,370 --> 00:06:42,630
+Neural Network. وقبل قليل، قلنا أنّها عبارة عن
+
+94
+00:06:42,630 --> 00:06:47,080
+مجموعة من الـ Connected Input و الـ Output Units. الآن،
+
+95
+00:06:47,080 --> 00:06:51,160
+في الـ Multilayer، أضيف عندي ما بين الـ Layer
+
+96
+00:06:51,160 --> 00:06:54,620
+الأولى، التي تمثّل الـ Input، والـ Layer
+
+97
+00:06:54,620 --> 00:06:58,680
+الأخيرة، التي هي الـ Output Layer، صار يمثّل عندي
+
+98
+00:06:58,680 --> 00:07:02,320
+ما يُسمّى الـ Hidden Layer. بالمناسبة، الكثير من
+
+99
+00:07:02,320 --> 00:07:05,740
+الناس يرفضون الـ Neural Network، لأنّهم يعتبرونها Black
+
+100
+00:07:05,740 --> 00:07:06,160
+Box.
+
+101
+00:07:09,080 --> 00:07:13,600
+ماذا يعني Black Box؟ Black Box بمعنى أنّي فعليًا
+
+102
+00:07:13,600 --> 00:07:16,140
+لا أرى ما يحدث، ولا أعرف لماذا هذه الأوزان
+
+103
+00:07:16,140 --> 00:07:19,100
+أصبحت هكذا. وفعلاً، هذه هي، للأسف، الـ Algorithm التي
+
+104
+00:07:19,100 --> 00:07:23,520
+موجودة عندنا. يعني، صعب تفسيرها.
+
+105
+00:07:23,520 --> 00:07:29,900
+طيب، الآن، الـ Input، حسب الرسم الذي عندي هنا،
+
+106
+00:07:29,900 --> 00:07:34,540
+هنا، ثلاثة Inputs، واثنان Outputs. وكما قلنا،
+
+107
+00:07:34,540 --> 00:07:37,340
+بما أنّها كلها أرقام، معناته الـ Input الخاصة بها ستكون 0، 1.
+
+108
+00:07:38,540 --> 00:07:41,280
+معناته، كل Neural Network هذه ستكون صفر، واحد في
+
+109
+00:07:41,280 --> 00:07:44,820
+المرحلة الأولى. في الـ Network السابق، يا جماعة الخير،
+
+110
+00:07:44,820 --> 00:07:48,880
+هذه الـ Function: صفر،
+
+111
+00:07:48,880 --> 00:07:52,200
+واحد. Two classes: الـ Class الأول، والـ Class الثاني.
+
+112
+00:07:52,200 --> 00:07:58,130
+هنا، صار في عندي Two Neurons في الـ Output. معناته كل
+
+113
+00:07:58,130 --> 00:08:01,350
+واحد فيهم يعطيني صفر أو واحد. معناته، صار في عندي
+
+114
+00:08:01,350 --> 00:08:06,030
+Two bits.  أجعلها Two bits: صفر، صفر؛ صفر، واحد؛
+
+115
+00:08:06,030 --> 00:08:10,010
+واحد، صفر؛ واحد، واحد. وكأنّي أتحدّث عن Four Classes.
+
+116
+00:08:10,010 --> 00:08:15,990
+يعني، بالـ Multilayer Neural Network، أصبح بإمكاني أن
+
+117
+00:08:15,990 --> 00:08:21,880
+أُعالج Dataset أكبر، أو أحصل على Multiclass
+
+118
+00:08:21,880 --> 00:08:26,240
+Classification. تعالوا نشوف الشكل العام الخاص بالـ
+
+119
+00:08:26,240 --> 00:08:30,300
+Network. هذا الشكل الذي رأيناه، نسميه
+
+120
+00:08:30,300 --> 00:08:36,100
+Network Topology. الـ Network Topology، هنا، ستحدّد
+
+121
+00:08:36,100 --> 00:08:39,720
+فيه عدد الـ Input، أو عدد الـ Units الخاصة بالـ Input، في الـ
+
+122
+00:08:39,720 --> 00:08:44,740
+Input Layer. طيب، ليس لي دخل كبير بها، لماذا؟ لأنّ
+
+123
+00:08:44,740 --> 00:08:50,880
+عادةً، عدد الـ Input Neurons يساوي
+
+124
+00:08:50,880 --> 00:08:54,720
+عدد الـ Attributes. يعني، ببساطة، كل Attribute في الـ
+
+125
+00:08:54,720 --> 00:09:01,740
+Data Set له Input Neuron واحد. يُفضّل أن تقوم بـ
+
+126
+00:09:01,740 --> 00:09:06,350
+Normalization لقيم الـ Attributes. ليس تفضيلاً،
+
+127
+00:09:06,350 --> 00:09:09,370
+بل قد يكون إلزاميًا، في مرحلة ما. لماذا؟ لأنّ
+
+128
+00:09:09,370 --> 00:09:12,530
+تتجنّب الـ Bias. ضع كل الـ Attributes الموجودة بعد
+
+129
+00:09:12,530 --> 00:09:17,050
+ما... بعد ما قمت بـ Preprocessing، وجّهزت...
+
+130
+00:09:17,050 --> 00:09:20,350
+جهزت الـ Data Set، لأنّ كل الـ Data كانت مستقلة،
+
+131
+00:09:21,310 --> 00:09:24,470
+لكنّ مُقياسها مختلف. وبما أنّ عملية
+
+132
+00:09:24,470 --> 00:09:28,810
+الحساب، كما رأينا سابقًا، تكون قيمتها، مثلًا، الـ
+
+133
+00:09:28,810 --> 00:09:31,710
+Call بالـ Minutes، خمسمائة، ألف، خمسمائة
+
+134
+00:09:31,710 --> 00:09:35,310
+دقيقة، في مقابل الـ Megabytes التي الـ Data... التي أنا
+
+135
+00:09:35,310 --> 00:09:40,490
+استخدمتها على الـ Mobile كانت بالأ... بالأيام. فواحد
+
+136
+00:09:40,490 --> 00:09:43,330
+سيكون وزنه أكبر من الآخر. فما الحل؟
+
+137
+00:09:43,330 --> 00:09:46,770
+لا، قم بـ Scaling، لتصبح من صفر إلى واحد، وسترتاح.
+
+138
+00:09:46,770 --> 00:09:51,900
+الآن، Number of Hidden Layers في الـ Topology. عدد الـ
+
+139
+00:09:51,900 --> 00:09:57,920
+Hidden Layer. وليس هذا فقط، عدد الـ Hidden Neurons في
+
+140
+00:09:57,920 --> 00:10:02,620
+الـ Hidden Layer، يعني
+
+141
+00:10:02,620 --> 00:10:05,200
+ببساطة، أنا أتحدّث عن الـ Neural Network،
+
+142
+00:10:05,200 --> 00:10:14,800
+أتحدث عن Input Layer، وأتحدث عن Hidden Layer، و
+
+143
+00:10:14,800 --> 00:10:22,100
+أتحدث عن Output Layer. ثلاث طبقات موجودة عندي. الـ
+
+144
+00:10:22,100 --> 00:10:29,260
+Input و الـ Output معروفان. ها هو Number of Classes، وهنا
+
+145
+00:10:29,260 --> 00:10:36,540
+Number of Attributes. أبو
+
+146
+00:10:36,540 --> 00:10:42,380
+هنا، هنا يا سيدي العزيز، لا أحد يُحكمك في شيء، ولا يوجد
+
+147
+00:10:42,380 --> 00:10:46,040
+قانون واضح. الآن، نحن نتحدث، لكي يكون عندي Multi
+
+148
+00:10:46,040 --> 00:10:49,580
+Layer، على الأقل يكون عندي Single Layer. وعندما
+
+149
+00:10:49,580 --> 00:10:52,500
+يكون عندي أكثر من Two Hidden Layers، تصبح Deep
+
+150
+00:10:52,500 --> 00:10:56,040
+Neural Network، تمام؟ وهذا المصطلح الذي يستخدمه
+
+151
+00:10:56,040 --> 00:10:58,660
+اليوم في الـ Machine Learning، يسمّى: Deep
+
+152
+00:10:58,660 --> 00:11:01,760
+Learning. لكنّنا الآن، بشكل بسيط، نتحدث عن
+
+153
+00:11:01,760 --> 00:11:05,630
+Input Layer، Hidden Layer واحد، و Output
+
+154
+00:11:05,630 --> 00:11:09,190
+Hidden Layer. بالنسبة لعدد الـ Neurons في الـ Hidden
+
+155
+00:11:09,190 --> 00:11:12,590
+Layer الموجودة عندي هنا، ليس لديّ
+
+156
+00:11:12,590 --> 00:11:17,210
+حسب الـ Attributes عندي. أربعة Input، أربعة Attributes،
+
+157
+00:11:17,210 --> 00:11:23,860
+وعندي Two Classes معروفة. ربما هؤلاء...  أيضًا، لا يوجد عدد
+
+158
+00:11:23,860 --> 00:11:28,140
+محدد للـ Neurons. متروك لكم للتجربة والقياس، أو
+
+159
+00:11:28,140 --> 00:11:31,300
+تجربة والخطأ، كما نسميها أحيانًا، وتحديدها،
+
+160
+00:11:31,300 --> 00:11:34,840
+لكن بعض الناس يقول لك: دعني أضع Initialisation
+
+161
+00:11:34,840 --> 00:11:44,300
+لهذا الكلام، من خلال أن أبدأ بمجموع الاثنين على اثنين.
+
+162
+00:11:44,300 --> 00:11:49,580
+يعني، الآن، أربعة واثنين، ستة.
+
+163
+00:11:53,290 --> 00:12:00,090
+على اثنين: ثلاثة. ولاحظ، وكأنّه يصير عندي رسمة الشبكة: هي أربعة
+
+164
+00:12:00,090 --> 00:12:05,990
+في الـ Input، ثلاثة في الـ Output، أو عفواً في الـ
+
+165
+00:12:05,990 --> 00:12:07,810
+Hidden، واثنان في الـ Output.
+
+166
+00:12:26,450 --> 00:12:30,210
+وهذه الشبكة الخاصة بي، تصبح بهذا الشكل. أصبحت
+
+167
+00:12:30,210 --> 00:12:33,730
+ضيقَة باتجاه الـ Output الموجودة. واحد قال: لا،
+
+168
+00:12:33,730 --> 00:12:37,850
+أريد أن آخذ ضعف الـ Input، أو أريد أن آخذ مجموعهما. لا أحد
+
+169
+00:12:37,850 --> 00:12:41,470
+سيقول لك: لا. هذا متروك لك. لماذا؟ كما قلت لك، هذه
+
+170
+00:12:41,470 --> 00:12:44,070
+الشبكة تحتاج إلى Optimization. الـ Neural Network من
+
+171
+00:12:44,070 --> 00:12:46,510
+الأشياء التي تحتاج إلى Optimization كثيرًا، وتحتاج إلى عمل
+
+172
+00:12:46,510 --> 00:12:50,820
+كثير في الـ Configuration. نرجع إلى الـ Simplest الـ
+
+173
+00:12:50,820 --> 00:12:54,540
+Neural Network الموجودة عندي. في النهاية، الـ
+
+174
+00:12:54,540 --> 00:12:58,860
+Function
+
+223
+00:16:49,840 --> 00:16:54,840
+كيف الـ neural network بتشتغل؟ بتاخد الـ input تبع الـ
+
+224
+00:16:54,840 --> 00:17:00,450
+attributes اللي موجودة عنده، وبتدخل إياهُ في الـ
+
+225
+00:17:00,450 --> 00:17:03,970
+input فترة الـ training. بتدخل اتباعاً، أو عفواً، في الـ
+
+226
+00:17:03,970 --> 00:17:07,250
+attributes بتدخل بشكل متوازي مع بعضها، لأن زي ما
+
+227
+00:17:07,250 --> 00:17:11,450
+قلنا، الـ instance بالكامل بتدخل عندي على الـ system.
+
+228
+00:17:11,450 --> 00:17:18,250
+بعد هيك، في أوزان الشبكة، عادة بتبدأ بـ random weight.
+
+229
+00:17:18,250 --> 00:17:21,970
+بتبدأ بـ random weight، و الأوزان مع كل connection
+
+230
+00:17:21,970 --> 00:17:25,490
+مع كل connection من الـ connections السابقة. هاي في
+
+231
+00:17:25,490 --> 00:17:27,950
+أول ما بتبدأ الشبكة بتحط random weight.
+
+232
+00:17:30,650 --> 00:17:37,670
+الخطوة اللي بعد هيك، لما أنا بعد ما بتروح تدخل، لاحظ
+
+233
+00:17:37,670 --> 00:17:41,190
+معايا، خلينا نقول، الـ input in your own hand. هنّفي W1
+
+234
+00:17:41,190 --> 00:17:49,520
+1, W1 2, W1 3, و W1 4. لأيش؟ لأن عندي 4 hidden neuron و
+
+235
+00:17:49,520 --> 00:17:53,500
+4 connection. الـ value تبع الـ hidden neuron، أو الـ
+
+236
+00:17:53,500 --> 00:17:56,200
+input neuron، هذا اللي تبع الـ attribute الأول.
+
+237
+00:17:56,200 --> 00:18:03,820
+خلّيني، على سبيل المثال، نقول هنا 1.7 من عشرة الآن.
+
+238
+00:18:03,820 --> 00:18:09,460
+1.7 من عشرة ضرب W1 1. جاية لمين؟ للـ hidden neuron.
+
+239
+00:18:09,460 --> 00:18:16,430
+هنا في المقابل، عندي هنا مثلاً كانت 2، وهذه الـ W 2 1.
+
+240
+00:18:16,430 --> 00:18:21,430
+و هذه الـ W 3 1، و هذه الـ W 1 1، و هذه الـ W 3 1، و
+
+241
+00:18:21,430 --> 00:18:22,910
+هذه الـ W 3 1، و هذه الـ W 3 1، و هذه الـ W 3 1، و
+
+242
+00:18:22,910 --> 00:18:23,890
+هذه الـ W 3 1، و هذه الـ W 3 1، و هذه الـ W 3 1، و
+
+243
+00:18:23,890 --> 00:18:26,510
+هذه الـ W 3 1، و هذه الـ W 3 1، و هذه الـ W 3 1، و
+
+244
+00:18:26,510 --> 00:18:28,550
+هذه الـ W 3 1، و هذه الـ W 3 1، و هذه الـ W 3 1، و
+
+245
+00:18:28,550 --> 00:18:29,110
+هذه الـ W 3 1، و هذه الـ W 3 1، و هذه الـ W 3 1، و
+
+246
+00:18:29,110 --> 00:18:30,230
+هذه الـ W 3 1، و هذه الـ W 3 1، و هذه الـ W 3 1، و
+
+247
+00:18:30,230 --> 00:18:30,370
+هذه الـ W 3 1، و هذه الـ W 3 1، و هذه الـ W 3 1، و
+
+248
+00:18:30,370 --> 00:18:30,750
+هذه الـ W 3 1، و هذه الـ W 3 1، و هذه الـ W 3 1، و
+
+249
+00:18:30,750 --> 00:18:34,510
+هذه الـ W 3 1، و هذه الـ
+
+250
+00:18:34,510 --> 00:18:43,070
+W 3 1، و هذه الـ W 3 1، و هذه الـ W 3 1.
+
+251
+00:18:46,660 --> 00:18:50,260
+وبديني decision، انه بيطلع output، و الـ output برضه
+
+252
+00:18:50,260 --> 00:18:55,540
+فيه إلها أوزان وبتتوزع على... يعني الآن السهم اللي
+
+253
+00:18:55,540 --> 00:18:58,580
+داخل على الـ neuron بيمثل الـ input، و اللي طالع منه
+
+254
+00:18:58,580 --> 00:19:02,540
+بيمثل الـ output تبعته. ايش الـ... اوكي، احنا عرفنا هنّ
+
+255
+00:19:02,540 --> 00:19:05,200
+انه الـ input. طب ايش الـ input؟ ايش الـ output؟ عفواً،
+
+256
+00:19:06,520 --> 00:19:08,840
+ما هي القيمة اللي طالعة عندي من الـ hidden neuron؟
+
+257
+00:19:08,840 --> 00:19:11,240
+هي عبارة عن تجميع على العناصر اللي موجودة عندي هنا.
+
+258
+00:19:11,240 --> 00:19:15,440
+ومن ثم بصدرليها بنفس الفكرة على الأوزان اللي جاي
+
+259
+00:19:15,440 --> 00:19:20,420
+بعدها، وهكذا بتتم عمل الشبكة. الآن هذه الشبكات
+
+260
+00:19:20,420 --> 00:19:26,520
+بتشتغل ضمن الـ feed forward neural network.
+
+261
+00:19:26,650 --> 00:19:29,030
+في الـ feed forward neural network، أنا فعلياً قاعد
+
+262
+00:19:29,030 --> 00:19:32,630
+بشتغل باتجاه واحد فقط، وهو الاتجاه أو التدفق
+
+263
+00:19:32,630 --> 00:19:36,930
+الطبيعي للشبكة، من الـ input لحد الـ output اللي
+
+264
+00:19:36,930 --> 00:19:46,190
+موجودة عندي. نقاط القوة في الشبكة، انه فعلياً بتتحكم
+
+265
+00:19:46,190 --> 00:19:49,950
+أو بتقدر تسيطر بشكل قوي على الـ noise data اللي
+
+266
+00:19:49,950 --> 00:19:55,430
+موجودة عندي. هان بتقدر تعمل classification على
+
+267
+00:19:55,430 --> 00:19:57,790
+untrained pattern، بتقدر تتحملها، detection بشكل
+
+268
+00:19:57,790 --> 00:20:02,670
+بسيط. مناسبة جداً للـ continuous value في الـ input و
+
+269
+00:20:02,670 --> 00:20:05,670
+الـ output، على خلاف اللي احنا شفناهم سابقاً، الـ
+
+270
+00:20:05,670 --> 00:20:09,750
+classifiers السابقة. بتشتغل مع أي قرية من الـ real
+
+271
+00:20:09,750 --> 00:20:15,130
+world data، حتى لو كانت بالـ handwritten. الـ
+
+272
+00:20:15,130 --> 00:20:18,150
+algorithm ممكن يطبق parallel بشكل متوازي، وبالتالي
+
+273
+00:20:18,150 --> 00:20:23,060
+هذا بيعمل على تسريع العمل. الـ weaknesses تبعتها، إنها
+
+274
+00:20:23,060 --> 00:20:26,500
+بتحتاج لفترة طويلة من التعليم، لأن زي ما شفنا أن
+
+275
+00:20:26,500 --> 00:20:33,340
+الأوزان كلها بتتغير. تخيل أنك في عندك عشرة input، في
+
+276
+00:20:33,340 --> 00:20:38,060
+عشرة hidden، في أربعة، أو بلاش في اتنين
+
+277
+00:20:41,140 --> 00:20:44,420
+output. اضرب هدول، هي عبارة عن عدد الـ connections
+
+278
+00:20:44,420 --> 00:20:47,320
+اللي موجودة، وعدد الـ connections بيساوي عدد الأوزان.
+
+279
+00:20:47,320 --> 00:20:52,760
+وبالتالي، بتكلم على 200 value كأوزان، بدها تغيير مع
+
+280
+00:20:52,760 --> 00:20:57,000
+كل عملية الـ training، و هذا مع كل instance، وبالتالي
+
+281
+00:20:57,000 --> 00:21:01,860
+موضوع الـ training هياخد منه وقت طويل. بتحتاج ده
+
+282
+00:21:01,860 --> 00:21:04,380
+كتير من الـ argument أو من الـ parameter. أنا بحتاج
+
+283
+00:21:04,380 --> 00:21:07,340
+أعملها tuning بشكل صحيح، عشان أقدر أحصل على الـ
+
+284
+00:21:07,340 --> 00:21:11,460
+result المطلوبة. منها إن الـ structure تبعتها أبسط
+
+285
+00:21:11,460 --> 00:21:15,680
+ما يمكن. ايش الـ structure؟ ايش الـ activation
+
+286
+00:21:15,680 --> 00:21:19,380
+function اللي أنا بدي اعتمدها؟ إلى آخره. الآن من
+
+287
+00:21:19,380 --> 00:21:22,520
+أهم الـ neural network اللي موجودة يا جماعة الخير،
+
+288
+00:21:22,520 --> 00:21:26,200
+شغلة بنسميها الـ back propagate neural network، back
+
+289
+00:21:26,200 --> 00:21:32,400
+propagate، الانتشار للخلف. الآن أنا هوضحها بشكل سريع.
+
+290
+00:21:32,400 --> 00:21:40,530
+هان، هحاول أرسمها على الصبورة، بس عشان تنتين، تلاتة،
+
+291
+00:21:40,530 --> 00:21:52,390
+أربعة، واحدة، تنتين، تلاتة، واحدة، تنتين، واحد، اتنين،
+
+292
+00:21:52,390 --> 00:21:54,230
+تلاتة.
+
+293
+00:22:23,390 --> 00:22:27,830
+تمام، عشان نفهم بس مبدأ الـ neural network، أو الـ
+
+294
+00:22:27,830 --> 00:22:31,210
+back propagate neural network، بشكل سريع، و مش هخش
+
+295
+00:22:31,210 --> 00:22:34,730
+في المعادلات الرياضية التفصيلية اللي هشغل عليها، لكن
+
+296
+00:22:34,730 --> 00:22:37,910
+أنا بهمني الآن نفهم الـ concept على السريع. الآن
+
+297
+00:22:37,910 --> 00:22:42,510
+تخيل أن أنا في عندي instance، أو الـ data set
+
+298
+00:22:42,510 --> 00:22:45,810
+المفروض الـ data set تبعتي، أو الـ data set تبعتي
+
+299
+00:22:45,810 --> 00:22:49,190
+مكونة من four attributes و one class attribute،
+
+300
+00:22:49,190 --> 00:22:56,110
+مظبوط، و one target. بنسميهم A1, A2, A3, A4، و الـ
+
+301
+00:22:56,110 --> 00:23:03,770
+label. طبعاً المفروض هنقل A1, A2, A3, A4، وهنا
+
+302
+00:23:03,770 --> 00:23:07,770
+المفروض في عندي الـ label. الآن الفكرة فيها أنه هياخد
+
+303
+00:23:07,770 --> 00:23:11,210
+الـ instance في الأول، أول ما بأتكلم على الـ
+
+304
+00:23:11,210 --> 00:23:16,150
+topology تبعتها، بروح بياخد مني عندي random weight.
+
+305
+00:23:19,480 --> 00:23:22,320
+بياخد أوزان من صفر لواحد، على كل الـ connections
+
+306
+00:23:22,320 --> 00:23:28,500
+اللي موجودة. تمام؟ الآن بياخد الـ value، مثلاً واحد،
+
+307
+00:23:28,500 --> 00:23:32,340
+واحد، صفر، واحد، والـ label تبعتها كانت، كانت على سبيل
+
+308
+00:23:32,340 --> 00:23:36,540
+مثال واحد، بالشكل هذا. فبياخد القيم اللي موجودة هنا،
+
+309
+00:23:36,540 --> 00:23:40,580
+وبضربها مع الأوزان اللي موجودة، لحد ما بياخد الـ
+
+310
+00:23:40,580 --> 00:23:46,100
+output. الآن في عندي الـ real class، وفي عندي الـ
+
+311
+00:23:46,100 --> 00:23:47,000
+predicted class.
+
+312
+00:23:49,540 --> 00:23:56,960
+الفرق بينهم، بياخد
+
+313
+00:23:56,960 --> 00:24:01,700
+الخطأ هذا، وبيبدأ يوزعه بالعكس. جداش الوزن كان هذا
+
+314
+00:24:01,700 --> 00:24:06,460
+random، جداش الـ connection، جداش كل connection ساهم
+
+315
+00:24:08,030 --> 00:24:13,810
+بالوزن أو بالخطأ هذا، فبتوزع عليهم الخطأ. وكل مكان
+
+316
+00:24:13,810 --> 00:24:18,010
+اللي predicted تبعتي صح، بتكون الـ error zero. معناته
+
+317
+00:24:18,010 --> 00:24:21,530
+أنا مش بحاجة أرجع. يعني، بشكل عام، الـ neural network
+
+318
+00:24:21,530 --> 00:24:23,970
+بشكل عام، أو الـ back propagation neural network
+
+319
+00:24:23,970 --> 00:24:31,830
+بشكل عام، بتشتغل على two ways. الطريقة الأولى، مرحلة الـ
+
+320
+00:24:31,830 --> 00:24:35,490
+prediction. باخد الـ input تبعتي، بدخلها على الـ data
+
+321
+00:24:35,490 --> 00:24:37,810
+على الـ neural network، بحسب لحد ما بحصل على الـ
+
+322
+00:24:37,810 --> 00:24:43,110
+output، بحسب الـ error، و بروح بوزن قيمة أو بعدل
+
+323
+00:24:43,110 --> 00:24:48,010
+الأوزان تبعاً لقيمة الخطأ اللي موجود عندهم.
+
+324
+00:24:49,890 --> 00:24:53,230
+وهذا فعلياً اللي بتصير عندنا في الـ neural network
+
+325
+00:24:53,230 --> 00:24:56,510
+في الـ back propagate الـ neural network. الـ forward
+
+326
+00:24:56,510 --> 00:25:01,970
+path، الـ path الأولى، بطبق الـ input و بحسب الـ output
+
+327
+00:25:01,970 --> 00:25:05,830
+تبع الـ activation function، و بحسب الخطأ اللي موجود
+
+328
+00:25:05,830 --> 00:25:10,990
+عندي. في الـ back propagate path، أنا فعلياً باخد
+
+329
+00:25:10,990 --> 00:25:14,990
+قيمة الخطأ، و بعدل الأوزان حسب مساهمتها في نسبة
+
+330
+00:25:14,990 --> 00:25:21,120
+الخطأ اللي موجودة عندنا هنا. آخر slide موجودة عندي
+
+331
+00:25:21,120 --> 00:25:25,880
+هان، اللي هي slide اللي لها علاقة بالبايثون. كيف
+
+332
+00:25:25,880 --> 00:25:29,380
+ممكن أنا أطبق الـ back propagation neural network
+
+333
+00:25:29,380 --> 00:25:38,420
+على الـ بايثون؟ طبعاً أنا اشتغلت كالتالي هان، عملت load
+
+334
+00:25:38,420 --> 00:25:43,360
+للـ iris للـ data set اللي موجودة عندي هان، from ASCII
+
+335
+00:25:43,360 --> 00:25:47,520
+layer.linear_model import perceptron. اشتغلت
+
+336
+00:25:47,520 --> 00:25:50,730
+على الأبسط، الـ neural network اللي موجودة عندنا هنا.
+
+337
+00:25:50,730 --> 00:25:55,970
+حددت الـ target تبعتها، و حولتها لـ numbers: setosa
+
+338
+00:25:55,970 --> 00:25:58,710
+طبعاً، أو not setosa. هيك لأن في الـ binary
+
+339
+00:25:58,710 --> 00:26:01,130
+classification، and one، أو الـ symbol. الـ neural
+
+340
+00:26:01,130 --> 00:26:03,670
+network بتشتغل على binary classification، زي ما شفنا.
+
+341
+00:26:03,670 --> 00:26:07,590
+فحولت... قلت إما هذا، فيها three classes، حولت لـ two
+
+342
+00:26:07,590 --> 00:26:13,890
+classes: صفر و واحد، setosa و not setosa. استدعيت
+
+343
+00:26:13,890 --> 00:26:17,780
+الـ neural network تبعتي، from scikit-learn.neural_
+
+344
+00:26:17,780 --> 00:26:21,020
+network import MLPClassifier.
+
+345
+00:26:21,020 --> 00:26:26,740
+الـ model هذا، بيتطلب مني اني احدد له شغلات كتيرة: عدد
+
+346
+00:26:26,740 --> 00:26:32,580
+الـ hidden layer، قلت له اتنين، و خمسة neuron في كل
+
+347
+00:26:32,580 --> 00:26:36,830
+واحدة، أو الـ solver، اللي هي الـ activation function
+
+348
+00:26:36,830 --> 00:26:39,770
+تبعتي، الـ alpha اللي بتمثل الـ learning rate، هذه
+
+349
+00:26:39,770 --> 00:26:43,290
+ما لكوش دخل فيها الآن. الـ solver و الـ hidden layer
+
+350
+00:26:43,290 --> 00:26:46,850
+size، الـ hidden layer size هي تبعتي المهمة بالنسبة
+
+351
+00:26:46,850 --> 00:26:49,750
+لي. الـ activation function هي الـ radial basis
+
+352
+00:26:49,750 --> 00:26:53,490
+function. وهنا بنتكلم على الـ network اللي موجودة
+
+353
+00:26:53,490 --> 00:26:57,430
+هنا، فقلت له أعمل train تبع الـ X و الـ Y، فرح يعدل
+
+354
+00:26:57,430 --> 00:27:00,430
+الأوزان اللي موجودة عندي هنا. فلما أنا بدي أزوده
+
+355
+00:27:00,430 --> 00:27:04,610
+الآن data، وأقول له اعملها prediction، الـ data بدها
+
+356
+00:27:04,610 --> 00:27:07,670
+تكون تماماً مع الـ data، مع الـ input اللي موجودة
+
+357
+00:27:07,670 --> 00:27:11,850
+عنديها، وهذه الـ data set هي عبارة عن مجموعة من
+
+358
+00:27:11,850 --> 00:27:15,490
+العناصر اللي موجودة عندها. إذا قدمت ليها as in، أو
+
+359
+00:27:15,490 --> 00:27:19,230
+matrix، فبياخدها، وفي الآخر هتديني prediction اللي
+
+360
+00:27:19,230 --> 00:27:22,510
+موجودة. يعني، باختصار بسيط جداً، أنا المفروض أن الـ data
+
+361
+00:27:22,510 --> 00:27:27,070
+set تبعتي، أحولها كلها لـ numeric data، في حال إذا
+
+362
+00:27:27,070 --> 00:27:31,680
+كنت أنا بدي اشتغل مع الـ Neural Network. بتمنى عليكم
+
+363
+00:27:31,680 --> 00:27:35,300
+وهذه تجربوها، وتفهموا الموضوع كويس، وزي ما قلنا
+
+364
+00:27:35,300 --> 00:27:38,040
+سابقا، على الـ forum اللي موجود على الـ model، أنا
+
+365
+00:27:38,040 --> 00:27:41,420
+مستعد إن شاء الله تعالى للإجابة على أي سؤال، وطبعاً
+
+366
+00:27:41,420 --> 00:27:44,240
+احنا اتعمدنا الإجابات على الـ forum، مش على الخاص،
+
+367
+00:27:44,240 --> 00:27:48,520
+عشان نقدر الفائدة تعمل للجميع. والسلام عليكم ورحمة
+
+368
+00:27:48,520 --> 00:27:49,540
+الله وبركاته.
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/u2_vU8et3ig_postprocess.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/u2_vU8et3ig_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..b577345a50fd730877d6d2f5628434d7aa8a785d
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/u2_vU8et3ig_postprocess.srt
@@ -0,0 +1,1472 @@
+1
+00:00:04,940 --> 00:00:07,000
+باسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:07,000 --> 00:00:11,420
+أهلا وسهلا بكم محاضراتنا المستمرة في منصق ال data
+
+3
+00:00:11,420 --> 00:00:14,620
+mining وما زلنا في باب ال classification او في باب
+
+4
+00:00:14,620 --> 00:00:18,120
+التصنيف هنتكلم اليوم او في المحاضرة هذه ان شاء
+
+5
+00:00:18,120 --> 00:00:22,940
+الله تعالى عن classifier كتير متقدمو مستخدمة بشكل
+
+6
+00:00:22,940 --> 00:00:26,500
+كبير جدا وهو الـ Neural Network as Classifier أو
+
+7
+00:00:26,500 --> 00:00:30,000
+بالتحديد الـ Back-propagate الـ Neural Network لأ
+
+8
+00:00:30,000 --> 00:00:33,740
+أخفيكم كان عندي تردد أشرحه ولا أشرح ال support
+
+9
+00:00:33,740 --> 00:00:37,240
+vector machine كلا هما من المواضيع ال advanced و
+
+10
+00:00:37,240 --> 00:00:40,760
+اللي بتحتاج إلى optimization عالية لكن قرصين على
+
+11
+00:00:40,760 --> 00:00:44,320
+ال neural network زي ما كنا قعدينهم سابقا و خلينا
+
+12
+00:00:44,320 --> 00:00:47,700
+نبدأ مع ال neural networkالـ neural network أو
+
+13
+00:00:47,700 --> 00:00:51,400
+الشبكات العصبية العصيبية مش العصبية بكفي أنا عصبي
+
+14
+00:00:51,400 --> 00:00:55,360
+بالجمال الشبكات الشبكات العصيبية هي عبارة عن
+
+15
+00:00:55,360 --> 00:00:59,980
+مجموعة من الـ connected input و ال output units
+
+16
+00:00:59,980 --> 00:01:04,850
+يعني بين جسين هي عبارة عن مجموعة منالمدخلات
+
+17
+00:01:04,850 --> 00:01:10,390
+والمخرجات المتصلة مع بعضها البعض وكل خط أو كل
+
+18
+00:01:10,390 --> 00:01:15,210
+connection أو كل خط أو كل link الوزن معين
+
+19
+00:01:15,210 --> 00:01:21,010
+associated with it مرتبط فيهاخلال مرحلتي التعليم
+
+20
+00:01:21,010 --> 00:01:24,370
+وهنا جامعة الخير بدأنا ننتبه كويس لأن صار في عندي
+
+21
+00:01:24,370 --> 00:01:27,390
+ميقولنا احنا Machine Learning Machine Learning هي
+
+22
+00:01:27,390 --> 00:01:32,570
+الفترة اللي انا بقى قضيها في بناء ال model عشان
+
+23
+00:01:32,570 --> 00:01:35,770
+هيك قلنا في البداية خالص ال classification في عندي
+
+24
+00:01:35,770 --> 00:01:39,690
+model based وفي عندي instance based ال instance
+
+25
+00:01:39,690 --> 00:01:42,550
+based كان ياريس نيبر و ال model based decision
+
+26
+00:01:42,550 --> 00:01:46,150
+tree و النايف بايسيان سؤال مهم جدا لان بدي أطرحه
+
+27
+00:01:46,150 --> 00:01:51,430
+عليكمو بتمنى انك تدور على .. او تفكر بإجابته لأن
+
+28
+00:01:51,430 --> 00:01:56,390
+هل الـ Naive bias model based ولا instance based؟
+
+29
+00:01:56,390 --> 00:02:00,070
+هذا واحد السؤال التاني الـ Naive bias algorithm
+
+30
+00:02:00,070 --> 00:02:03,890
+الجدول اللي أنا بنيته هذا كم مرة بقى بنيه؟
+
+31
+00:02:06,390 --> 00:02:11,390
+المفروض لمرة واحدة متى بحتاج إعادة بناءه لو تغيرت
+
+32
+00:02:11,390 --> 00:02:14,850
+ال training set اللي موجودة عندي وبالتالي المفروض
+
+33
+00:02:14,850 --> 00:02:18,090
+الجدول هذا بيمثل عندي model خلال مرحلة التعليم
+
+34
+00:02:18,090 --> 00:02:21,430
+مرحلة ال learning مرحلة بناء ال model ال network
+
+35
+00:02:21,430 --> 00:02:25,610
+اللي هي الشبكة العصيبية بتحاول تعدل الأوزان اللي
+
+36
+00:02:25,610 --> 00:02:30,810
+موجودة عندها لحد ما تصل مين
+
+37
+00:02:30,810 --> 00:02:37,860
+لل label يعني بين قوسينان انا دخلت ال input عملت
+
+38
+00:02:37,860 --> 00:02:42,900
+computation حصلت على ال output بقارن بقارن بين ال
+
+39
+00:02:42,900 --> 00:02:46,680
+output الحقيقي و ال predicted و تبعا لل error اللي
+
+40
+00:02:46,680 --> 00:02:49,600
+بينهم او الفرق اللي بينهم بعمل adjustment لل
+
+41
+00:02:49,600 --> 00:02:50,880
+weight اللي موجود عندها
+
+42
+00:02:55,350 --> 00:02:57,970
+الأن الـ neural network بشكل عام جماعة الخير هي
+
+43
+00:02:57,970 --> 00:03:01,010
+بتحاكي الشبكات العصيبية في الإنسان أو الجهاز
+
+44
+00:03:01,010 --> 00:03:03,910
+العصبي في الإنسان في الآخر ال decision في الدماغ
+
+45
+00:03:03,910 --> 00:03:09,510
+والخلايا العصبية منتشرة على كل جسمك لو أنت ساكت أو
+
+46
+00:03:09,510 --> 00:03:13,710
+سرحان وقاعد بتحل في المثلة في ال data mining وإجا
+
+47
+00:03:13,710 --> 00:03:23,320
+زميلك طرف دبوس وحاول يشكك في إيدكبدون ما تنتبهله
+
+48
+00:03:23,320 --> 00:03:27,400
+انت و لا إرادي هتلاقي انه ايدك تحركت بالاتجاه
+
+49
+00:03:27,400 --> 00:03:31,980
+المضاد للشكة بحيث انها يعني تبعد عن مصدر الخطر
+
+50
+00:03:31,980 --> 00:03:35,680
+اللي صار انت فعليا مش عارف ايش اللي صار لكن مجرد
+
+51
+00:03:35,680 --> 00:03:38,840
+انك حركت ابعدت ايدك و بعدين بديت تطلع لان كانت
+
+52
+00:03:38,840 --> 00:03:42,240
+الحركة أو الجهاز العصب ادى اشارة للدماغ و الدماغ
+
+53
+00:03:42,240 --> 00:03:45,260
+اخد processing عالية سريعة جدا انه لأ ابعد عن
+
+54
+00:03:45,260 --> 00:03:47,980
+الخطر هذا و كذلك بتصير معانا في الموضوع لما يكون
+
+55
+00:03:47,980 --> 00:03:52,510
+الشغلات الحريق الى اخرهالان هذا الكلام ما صار الا
+
+56
+00:03:52,510 --> 00:03:56,330
+غير من خلال حياة مكتسبة موجودة عندها فال neural
+
+57
+00:03:56,330 --> 00:03:58,870
+network جالك ليش لما الناس فكروا فيها في الداخل في
+
+58
+00:03:58,870 --> 00:04:03,050
+الخمسينات جالك ليش ما نحاول نحاكي عقل الإنسان في
+
+59
+00:04:03,050 --> 00:04:07,410
+التعامل احنا مش كتير معنى بالصبغة التاريخية
+
+60
+00:04:07,410 --> 00:04:13,090
+والتفاصيل كتيرة لكن بشكل عام أبسط نموذج للشبكة
+
+61
+00:04:13,090 --> 00:04:15,690
+اللي موجودة عندى لأن في الآخر كل شيء computation
+
+62
+00:04:15,690 --> 00:04:20,450
+يا جماعة الخير هي مجموعة ال inputمجموعة ال input
+
+63
+00:04:20,450 --> 00:04:25,970
+الان ايش P1P لحد ال PR هي عبارة عن ال attributes
+
+64
+00:04:25,970 --> 00:04:31,350
+بتمثل
+
+65
+00:04:31,350 --> 00:04:36,790
+ال input طب وال A ال
+
+66
+00:04:36,790 --> 00:04:44,280
+output لبنجوسين ل class اللي موجود عندى انا هانالـ
+
+67
+00:04:44,280 --> 00:04:47,380
+class اللى موجود عندى ايش اللى صار اللى انا فعليا
+
+68
+00:04:47,380 --> 00:04:52,960
+كل attribute كان له وزن فانا باخد بضرب قيمة ال
+
+69
+00:04:52,960 --> 00:04:57,080
+attribute لاحظ بقول بضرب قيمة ال attribute في
+
+70
+00:04:57,080 --> 00:05:05,800
+الوزن بجمعهم بضفلهم قيمة لل bias وال function هذه
+
+71
+00:05:05,800 --> 00:05:09,460
+بتاخد decision اي واحد من ال binary classification
+
+72
+00:05:09,460 --> 00:05:13,210
+او من ال classes هتكون صفر او واحديعني binary
+
+73
+00:05:13,210 --> 00:05:17,090
+classification انتبه معايا وانتبه معايا لما انا
+
+74
+00:05:17,090 --> 00:05:20,830
+قلت باخد قيمة ال attribute و بضربها طب هل ممكن انا
+
+75
+00:05:20,830 --> 00:05:24,390
+اشتغل مع ال nominal attribute؟ لأ بينفعش ال data
+
+76
+00:05:24,390 --> 00:05:28,170
+set تبعتي كلها must be numeric لازم لأن مافيش مدى
+
+77
+00:05:28,170 --> 00:05:31,690
+اللي اروح اخد والله ال gender male male ضرب خمسة
+
+78
+00:05:31,690 --> 00:05:34,990
+حوليها 01 او اي numeric attribute انت بتشوفها
+
+79
+00:05:34,990 --> 00:05:39,170
+مناسبة ال income زي ما شوفنا قبل شوية fair و
+
+80
+00:05:39,170 --> 00:05:43,940
+excellentبرضه بقى تحوّل إياهم لأرقام وبالتالي فبدل
+
+81
+00:05:43,940 --> 00:05:46,800
+ما كانت category اللي بتروح أحوّلها كلها أرقام
+
+82
+00:05:46,800 --> 00:05:51,960
+تمام حتى لو كان coding موجودة عندى في النهاية اللي
+
+83
+00:05:51,960 --> 00:05:58,140
+هيصير كالتالي ال function تبعتي ال F ال prediction
+
+84
+00:05:58,140 --> 00:06:02,520
+function تبعتي هي عبارة عن vector الأوزان مضروبة
+
+85
+00:06:02,520 --> 00:06:07,450
+في ال inputزائد الـ bias اللي موجود عندها في مرحلة
+
+86
+00:06:07,450 --> 00:06:15,310
+ال learning بتصير الشبكة تدور على أفضل W و B لأن
+
+87
+00:06:15,310 --> 00:06:19,530
+انت لا تنسى انها معادلة خط مستقيم بتدور على أفضل W
+
+88
+00:06:19,530 --> 00:06:23,770
+و B لكن بال vectors W بتمثل الأوزان تبع ال
+
+89
+00:06:23,770 --> 00:06:26,630
+connection و ال B تمثل ال bias تبع ال network اللي
+
+90
+00:06:26,630 --> 00:06:30,210
+موجودة في ال multilayer neural network شوية الشغل
+
+91
+00:06:30,210 --> 00:06:30,870
+مختلفة
+
+92
+00:06:33,410 --> 00:06:39,370
+سابقاً أنا عندي فقط input و output في الـ simple
+
+93
+00:06:39,370 --> 00:06:42,630
+neural network و احنا قبل شوية قولنا هي عبارة عن
+
+94
+00:06:42,630 --> 00:06:47,080
+مجموعة من ال connected input و ال output unitsالان
+
+95
+00:06:47,080 --> 00:06:51,160
+في الـ Multilayer أضافلي عندى فيها ما بين ال layer
+
+96
+00:06:51,160 --> 00:06:54,620
+الأولى اللى هى اللى تمثل ال input و ال layer
+
+97
+00:06:54,620 --> 00:06:58,680
+الأخيرة اللى هى ال output layer صار بيمثل عندى مين
+
+98
+00:06:58,680 --> 00:07:02,320
+في شغل بسميليها ال hidden layer بالمناسبة كتير من
+
+99
+00:07:02,320 --> 00:07:05,740
+الناس بترفض ال neural network لأنها بتعتمدها black
+
+100
+00:07:05,740 --> 00:07:06,160
+box
+
+101
+00:07:09,080 --> 00:07:13,600
+شو يعني black box؟ black box بمعنى انه انا فعلا
+
+102
+00:07:13,600 --> 00:07:16,140
+مابشوفش ايش اللي بصير ولا بعرف ليش الأوزان هذه
+
+103
+00:07:16,140 --> 00:07:19,100
+صارت هيك وفعلا هذه هي للأسف ال algorithm اللي
+
+104
+00:07:19,100 --> 00:07:23,520
+موجودة عندنا يعني صعب ال interpretation تبعتها
+
+105
+00:07:23,520 --> 00:07:29,900
+تصير عندي طيب الآن ال input حسب الرسم اللي عندي
+
+106
+00:07:29,900 --> 00:07:34,540
+هان ال three inputs و ال two outputs و زي ما قلنا
+
+107
+00:07:34,540 --> 00:07:37,340
+بما هي كلها أرقام معناته ال input تبعتها هتكون 01
+
+108
+00:07:38,540 --> 00:07:41,280
+معناته كل neural network هذه هتكون صفر واحد في
+
+109
+00:07:41,280 --> 00:07:44,820
+المرحلة الأولى في ال network السابق يا جماعة الخير
+
+110
+00:07:44,820 --> 00:07:48,880
+هذه ال function صفر
+
+111
+00:07:48,880 --> 00:07:52,200
+واحد two classes ال class الأول و ال class التاني
+
+112
+00:07:52,200 --> 00:07:58,130
+هان صار في عندي two neurons في ال outputمعناته كل
+
+113
+00:07:58,130 --> 00:08:01,350
+واحد فيهم بتديني صفر أو واحد معناته صار في عندي
+
+114
+00:08:01,350 --> 00:08:06,030
+two bits خلني أسويها two bits صفر و صفر صفر واحد
+
+115
+00:08:06,030 --> 00:08:10,010
+واحد صفر واحد واحد وكأني بتكلم على four classes
+
+116
+00:08:10,010 --> 00:08:15,990
+يعني بال multilayer neural network صار بإمكاني أنا
+
+117
+00:08:15,990 --> 00:08:21,880
+فعليا أعرضDataset أكتر أو أحصل على Multiclass
+
+118
+00:08:21,880 --> 00:08:26,240
+Classification تعالى نشوف الشكل العام تبعت الـ
+
+119
+00:08:26,240 --> 00:08:30,300
+Network تبعته ده على الشكل اللي احنا شفناه بنسميه
+
+120
+00:08:30,300 --> 00:08:36,100
+Network Topology الـ Network Topology هان بدك تحدد
+
+121
+00:08:36,100 --> 00:08:39,720
+فيه عدد ال input أو عدد ال unit لل input في ال
+
+122
+00:08:39,720 --> 00:08:44,740
+input layerطب انا ماليش دخل فيها كتير هذه ليش لأن
+
+123
+00:08:44,740 --> 00:08:50,880
+عادة عدد ال input neurons يساوي
+
+124
+00:08:50,880 --> 00:08:54,720
+عدد ال attribute يعني بينجو سين كل attribute في ال
+
+125
+00:08:54,720 --> 00:09:01,740
+data set له one input neuron يفضل انك تروح تعمل
+
+126
+00:09:01,740 --> 00:09:06,350
+normalizationللـ values تبعت ال attributes مش يفضل
+
+127
+00:09:06,350 --> 00:09:09,370
+يمكن تكون إجباريك في مرحلة من مرحلة ليش؟ عشان
+
+128
+00:09:09,370 --> 00:09:12,530
+تتجنب ال bias تحط كل ال attributes اللي موجود بعد
+
+129
+00:09:12,530 --> 00:09:17,050
+ما انت .. بعد ما انت عملت preprocessing وجهزت ..
+
+130
+00:09:17,050 --> 00:09:20,350
+وجهزت ال data set لأن كل ال data had independent
+
+131
+00:09:21,310 --> 00:09:24,470
+لكن دلت ال scaling تبعتها عالية و بما انه عملية
+
+132
+00:09:24,470 --> 00:09:28,810
+حساب زي ما شوفنا سابقا انه يكون عنده قيمة مثلا ال
+
+133
+00:09:28,810 --> 00:09:31,710
+call بال minutes خمس .. نقول ستمية و ألف و خمسمية
+
+134
+00:09:31,710 --> 00:09:35,310
+دقيقة في مقابل ال megas اللي ال data .. اللي أنا
+
+135
+00:09:35,310 --> 00:09:40,490
+استخدمتها على ال mobile كانت بال .. بالأحد فواحد
+
+136
+00:09:40,490 --> 00:09:43,330
+هيكون ال weight تبعته أكتر من التانية فإيش الحل؟
+
+137
+00:09:43,330 --> 00:09:46,770
+لأ اعمله scaling عشان تكون من صفر لواحد و بترتاح
+
+138
+00:09:46,770 --> 00:09:51,900
+الآن number of hidden layers في ال typologyعدد الـ
+
+139
+00:09:51,900 --> 00:09:57,920
+Hidden Layer ومش بس هيك عدد الـ Hidden Neuron في
+
+140
+00:09:57,920 --> 00:10:02,620
+الـ Hidden Layer يعني
+
+141
+00:10:02,620 --> 00:10:05,200
+بين جسين انا جاعد بتكلم في الـ Neural Network
+
+142
+00:10:05,200 --> 00:10:14,800
+بتكلم على Input Layer و بتكلم على Hidden Layer و
+
+143
+00:10:14,800 --> 00:10:22,100
+بتكلم على Output Layer تلت طبقات موجودة عندىال
+
+144
+00:10:22,100 --> 00:10:29,260
+input وال output معروفين ها number of classes وهنا
+
+145
+00:10:29,260 --> 00:10:36,540
+number of attributes أبو
+
+146
+00:10:36,540 --> 00:10:42,380
+هان هان يا سيد العزيز ماحدش بيحكمك في حاجة ولا في
+
+147
+00:10:42,380 --> 00:10:46,040
+قانون واضح الان احنا بتتكلم عشان تكون عندى multi
+
+148
+00:10:46,040 --> 00:10:49,580
+layer على الأقل بيكون في عندى single layerولمّا
+
+149
+00:10:49,580 --> 00:10:52,500
+بتكون في عندي اكثر من two hidden layer بتصير deep
+
+150
+00:10:52,500 --> 00:10:56,040
+neural network تمام؟ وهذا المصطلح اللي بيستخدمه
+
+151
+00:10:56,040 --> 00:10:58,660
+اليوم في ال machine learning بيسمي احنا ال deep
+
+152
+00:10:58,660 --> 00:11:01,760
+learning لكن احنا الآن خلينا بشكل بسيط بتكلم على
+
+153
+00:11:01,760 --> 00:11:05,630
+input layerhidden layer one hidden layer و output
+
+154
+00:11:05,630 --> 00:11:09,190
+hidden layer بالنسبة لعدد ال neurons في ال hidden
+
+155
+00:11:09,190 --> 00:11:12,590
+layer اللي موجودة عندي انا هانجدش انا والله عندي
+
+156
+00:11:12,590 --> 00:11:17,210
+حسب ال attribute عندي اربعة input اربعة attributes
+
+157
+00:11:17,210 --> 00:11:23,860
+وعندي two classes معروفين ربها دولبرضه مافيش عدد
+
+158
+00:11:23,860 --> 00:11:28,140
+الـ neurons مبهم ومتروك لك للتجربة و القياس او
+
+159
+00:11:28,140 --> 00:11:31,300
+تجربة و الخطأ زي ما احنا بنسميها احيانا و اتحددها
+
+160
+00:11:31,300 --> 00:11:34,840
+لكن في بعض الناس بتقولك خليني اعمل initialization
+
+161
+00:11:34,840 --> 00:11:44,300
+للكلام هذا عبر انه ابدأ بمجموع التنين على اتنين
+
+162
+00:11:44,300 --> 00:11:49,580
+يعني الان اربعة و اتنين ستة
+
+163
+00:11:53,290 --> 00:12:00,090
+على 2 ثلاثة ولاحظ وكأنه بيصير عند رسمة الشبكة هي 4
+
+164
+00:12:00,090 --> 00:12:05,990
+في ال input ثلاثة في ال output او عفوا في ال
+
+165
+00:12:05,990 --> 00:12:07,810
+hidden و 2 في ال output
+
+166
+00:12:26,450 --> 00:12:30,210
+وهذه الشبكة تبعتي بتصير بالشكل هذا قاعد بعملها
+
+167
+00:12:30,210 --> 00:12:33,730
+narrowing باتجاه ال output اللي موجودة واحد قال لأ
+
+168
+00:12:33,730 --> 00:12:37,850
+انا بدي اخد ضعف ال input او بدي اخد جدهم مافيش حد
+
+169
+00:12:37,850 --> 00:12:41,470
+هيقولك لأ القمر هذا متروك لك عشان ايه قلتلك هذه
+
+170
+00:12:41,470 --> 00:12:44,070
+الشبكة بدها optimization ال neural network من
+
+171
+00:12:44,070 --> 00:12:46,510
+الشغلات اللي بدها optimization كتير و بدها شغل
+
+172
+00:12:46,510 --> 00:12:50,820
+كتير في ال configurationنرجع للـ simplest الـ
+
+173
+00:12:50,820 --> 00:12:54,540
+neural network اللي موجودة عندها في الآخر ال
+
+174
+00:12:54,540 --> 00:12:58,860
+function انا هاللاحظ حاطين summation عشان عبارة عن
+
+175
+00:12:58,860 --> 00:13:04,300
+مضروب ال input في ال weight تبعتها و بجمعهم هذه
+
+176
+00:13:04,300 --> 00:13:09,180
+عبارة عن vector و بضفلهم ال bias لمرة واحدة و بروح
+
+177
+00:13:09,180 --> 00:13:13,470
+على ال function اللي موجودة عندهاالان الـ function
+
+178
+00:13:13,470 --> 00:13:17,470
+هذه عادة بنسميها اما ال activation function او ال
+
+179
+00:13:17,470 --> 00:13:22,050
+transformation function activation function او
+
+180
+00:13:22,050 --> 00:13:25,330
+transformation function ليش transformation او
+
+181
+00:13:25,330 --> 00:13:29,210
+transfer function لأن هي بتنقل ال input لل output
+
+182
+00:13:29,210 --> 00:13:34,190
+ليش بتسميها activation لأنها بتعمل على تنشيط ال
+
+183
+00:13:34,190 --> 00:13:38,670
+output neurons اللي موجودة عندى هنا وبتماما هخرجها
+
+184
+00:13:38,670 --> 00:13:46,610
+هطلحة لل out بكل بساطةبكل بساطة انت تخيل انا في
+
+185
+00:13:46,610 --> 00:13:50,350
+عندي function ال function تبعتي هذه لازم تحسب ..
+
+186
+00:13:50,350 --> 00:13:56,610
+تاخد .. تاخد مني input ال input لو كان اكبر او
+
+187
+00:13:56,610 --> 00:14:02,350
+تساوي واحد فال output واحد otherwise تديني صفر وفي
+
+188
+00:14:02,350 --> 00:14:08,630
+عندي بقوللي ال input تبعتي P1 و P2 هيهم الأوزان
+
+189
+00:14:08,630 --> 00:14:14,940
+تبعتهمواحد و نص و واحد معناته و ال bias تبعتي ساوي
+
+190
+00:14:14,940 --> 00:14:18,880
+سالب واحد و نص معناته حسب ال function ال output
+
+191
+00:14:18,880 --> 00:14:25,800
+تبعتي اتنين ضرب واحد و نص زي التلاتة ضرب واحد ناقص
+
+192
+00:14:25,800 --> 00:14:29,760
+واحد و نص اففف اربعة و نص اففف اربعة و نص الاربعة
+
+193
+00:14:29,760 --> 00:14:34,190
+و نص اكبر من واحد معناته دي هتعطيلياللي ال class
+
+194
+00:14:34,190 --> 00:14:38,270
+الأول بناء على ال output أو ال input المدخل عفواني
+
+195
+00:14:38,270 --> 00:14:42,210
+وبالتالي ال actual output تبعتي الفعلي بيعتمد على
+
+196
+00:14:42,210 --> 00:14:45,710
+مين؟ على ال transfer function اللي موجودة عندي هنا
+
+197
+00:14:45,710 --> 00:14:49,150
+طبعا ممكن يتغير ال threshold اللي أنا روحت فحصته
+
+198
+00:14:49,150 --> 00:14:57,450
+عنده هنا أنا هنا قلتله أكبر أو تساوي واحد yes و no
+
+199
+00:14:57,450 --> 00:15:00,150
+هي ال business logic تبعتي ال function تبعتي
+
+200
+00:15:00,150 --> 00:15:06,680
+وبالتالي اناالقيم الموجودة الان ال activation
+
+201
+00:15:06,680 --> 00:15:07,360
+function
+
+202
+00:15:10,670 --> 00:15:13,930
+هي عندي منهم مجموعة من الـ functions الأولى
+
+203
+00:15:13,930 --> 00:15:17,950
+بنسميها hard limit function أو hard limit transfer
+
+204
+00:15:17,950 --> 00:15:20,970
+function وزي ما انت شايفهان وزي ما انت شايفهان
+
+205
+00:15:20,970 --> 00:15:25,530
+hard limit بتاخد ال value و بتفحص إذا كانت بتديني
+
+206
+00:15:25,530 --> 00:15:29,070
+واحد لما تكون القيمة أكبر أو تساوي صفر أقل من صفر
+
+207
+00:15:29,070 --> 00:15:32,710
+بتديني صفر لأنه binary زي ما قلنا binary ال
+
+208
+00:15:32,710 --> 00:15:36,050
+classification و هذه بنسميها hard limit مافيش مجال
+
+209
+00:15:36,050 --> 00:15:39,880
+يا صفر يا واحد الآنفي عند الـ Linear
+
+210
+00:15:39,880 --> 00:15:42,900
+Transformation Function أو الـ Threshold Function
+
+211
+00:15:42,900 --> 00:15:47,500
+الـ Threshold Function زي ما احنا شايفين هيها إذا
+
+212
+00:15:47,500 --> 00:15:51,540
+كانت القيمة تديني أعلى من قيمة ال line هذا معناته
+
+213
+00:15:51,540 --> 00:15:56,560
+ل class A يعني كل المنطقة هي C1
+
+214
+00:15:56,560 --> 00:16:04,180
+وهذه C2 بناء على ال line اللي موجود عندي كذلك في
+
+215
+00:16:04,180 --> 00:16:05,460
+عندي ال Sigmoid Function
+
+216
+00:16:08,570 --> 00:16:14,310
+عبارة عن دالة بتعتمد على الـ exponential A
+
+217
+00:16:14,310 --> 00:16:21,450
+تساوي واحد على واحد زائد E أص ناقص N مين الـ N يا
+
+218
+00:16:21,450 --> 00:16:27,770
+جماعة الخير؟ عشان أذكركم بالـ N هي عبارة عن حاصل
+
+219
+00:16:27,770 --> 00:16:34,660
+جمع العناصر العنصرين هدول وما تنساش هذه vectorو
+
+220
+00:16:34,660 --> 00:16:37,660
+هذه vector فبنضرب في بعض هم من ثم انا حصلت على
+
+221
+00:16:37,660 --> 00:16:44,460
+العناصر اللي موجودة عندهان الان شفنا الشبكة و
+
+222
+00:16:44,460 --> 00:16:49,840
+عرفنا شغلها يعني بكل بساطة كيف انا بدي اشتغل او
+
+223
+00:16:49,840 --> 00:16:54,840
+كيف ال neural network بتشتغل بتاخد ال input تبع ال
+
+224
+00:16:54,840 --> 00:17:00,450
+attributes اللي موجودة عندهان و بتدخل إياهمو ال
+
+225
+00:17:00,450 --> 00:17:03,970
+input فترة ال training بتدخل اتباعا او عفوا في ال
+
+226
+00:17:03,970 --> 00:17:07,250
+attributes بتدخل بشكل متوازي مع بعضهم لأن زي ما
+
+227
+00:17:07,250 --> 00:17:11,450
+قلنا ال instance بالكامل بتدخل عندي على ال system
+
+228
+00:17:11,450 --> 00:17:18,250
+بعد هيك في أوزان الشبكة عادة بتبدأ ب random weight
+
+229
+00:17:18,250 --> 00:17:21,970
+بتبدأ ب random weight و الأوزان مع كل connection
+
+230
+00:17:21,970 --> 00:17:25,490
+مع كل connection من ال connections السابقة هاي في
+
+231
+00:17:25,490 --> 00:17:27,950
+اول ما بتبدأ الشبكة بتحط random weight
+
+232
+00:17:30,650 --> 00:17:37,670
+الخطوة اللي بعد هيك لما انا بعد ما بتروح تدخل لاحظ
+
+233
+00:17:37,670 --> 00:17:41,190
+معايا خلنا نقول ال input in your own hand هنفي W1
+
+234
+00:17:41,190 --> 00:17:49,520
+1 W1 2W1 3 و W1 4 لأيش؟ لأن عندي 4 hidden neuron و
+
+235
+00:17:49,520 --> 00:17:53,500
+4 connection ال value تبع ال hidden neuron أو ال
+
+236
+00:17:53,500 --> 00:17:56,200
+input neuron هذا اللي تبع ال attribute الأول
+
+237
+00:17:56,200 --> 00:18:03,820
+خلّيني على سبيل المثال نقول هنا 1.7 من عشرة الان
+
+238
+00:18:03,820 --> 00:18:09,460
+1.7 من عشرة ضرب W1 1 جاية لمين؟ لل hidden neuron
+
+239
+00:18:09,460 --> 00:18:16,430
+هنا في المقابل عندي هنا مثلا كانت 2و هذه الـ W 2 1
+
+240
+00:18:16,430 --> 00:18:21,430
+و هذه الـ W 3 1 و هذه الـ W 1 1 و هذه الـ W 3 1 و
+
+241
+00:18:21,430 --> 00:18:22,910
+هذه الـ W 3 1 و هذه الـ W 3 1 و هذه الـ W 3 1 و
+
+242
+00:18:22,910 --> 00:18:23,890
+هذه الـ W 3 1 و هذه الـ W 3 1 و هذه الـ W 3 1 و
+
+243
+00:18:23,890 --> 00:18:26,510
+هذه الـ W 3 1 و هذه الـ W 3 1 و هذه الـ W 3 1 و
+
+244
+00:18:26,510 --> 00:18:28,550
+هذه الـ W 3 1 و هذه الـ W 3 1 و هذه الـ W 3 1 و
+
+245
+00:18:28,550 --> 00:18:29,110
+هذه الـ W 3 1 و هذه الـ W 3 1 و هذه الـ W 3 1 و
+
+246
+00:18:29,110 --> 00:18:30,230
+هذه الـ W 3 1 و هذه الـ W 3 1 و هذه الـ W 3 1 و
+
+247
+00:18:30,230 --> 00:18:30,370
+هذه الـ W 3 1 و هذه الـ W 3 1 و هذه الـ W 3 1 و
+
+248
+00:18:30,370 --> 00:18:30,750
+هذه الـ W 3 1 و هذه الـ W 3 1 و هذه الـ W 3 1 و
+
+249
+00:18:30,750 --> 00:18:34,510
+هذه الـ W 3 1 و هذه الـ
+
+250
+00:18:34,510 --> 00:18:43,070
+W 3 1 و هذه الـ W 3 1 و هذه الـ W 3 1
+
+251
+00:18:46,660 --> 00:18:50,260
+وبديني decision انه بيطلع output وال output برضه
+
+252
+00:18:50,260 --> 00:18:55,540
+فيه إلها أوزان وبتتوزع على .. يعني الآن السهم اللي
+
+253
+00:18:55,540 --> 00:18:58,580
+داخل على ال neuron بيمثل ال input و اللي طالع منه
+
+254
+00:18:58,580 --> 00:19:02,540
+بيمثل ال output تبعته ايش ال .. اوكي احنا عرفنا هن
+
+255
+00:19:02,540 --> 00:19:05,200
+انه ال input طب ايش ال input ايش ال output .. عفوا
+
+256
+00:19:06,520 --> 00:19:08,840
+ما هي القيمة اللي طالع عندي من الـ hidden neuron؟
+
+257
+00:19:08,840 --> 00:19:11,240
+هي عبارة عن تجميع على العناصر اللي موجودة عندي هنا
+
+258
+00:19:11,240 --> 00:19:15,440
+ومن ثم بصدرليها بنفس الفكرة على الأوزان اللي جاي
+
+259
+00:19:15,440 --> 00:19:20,420
+بعدها وهكذا بتتم عمل الشبكة الآن هذه الشبكات
+
+260
+00:19:20,420 --> 00:19:26,520
+بتشتغل ضمن ال feed forward neural نتويرك
+
+261
+00:19:26,650 --> 00:19:29,030
+في ال feed forward neural network أنا فعليا قاعد
+
+262
+00:19:29,030 --> 00:19:32,630
+بشتغل باتجاه واحد فقط وهو الاتجاه أو التدفق
+
+263
+00:19:32,630 --> 00:19:36,930
+الطبيعي للشبكة من ال input لحد ال output اللي
+
+264
+00:19:36,930 --> 00:19:46,190
+موجودة عندى نقاط القوة في الشبكة انه فعليا بتتحكم
+
+265
+00:19:46,190 --> 00:19:49,950
+او بتقدر تسيطر بشكل قوى على ال noise data اللي
+
+266
+00:19:49,950 --> 00:19:55,430
+موجودة عندى هانبتقدر تعمل classification على
+
+267
+00:19:55,430 --> 00:19:57,790
+untrained pattern بتقدر تتحملها detection بشكل
+
+268
+00:19:57,790 --> 00:20:02,670
+بسيط مناسبة جدا لل continuous value في ال input و
+
+269
+00:20:02,670 --> 00:20:05,670
+ال output على خلاف اللي احنا شفناهم سابقا ال
+
+270
+00:20:05,670 --> 00:20:09,750
+classifiers السابقة بتشتغل مع أي قرية من ال real
+
+271
+00:20:09,750 --> 00:20:15,130
+world data حتى لو كانت بال handwritten ال
+
+272
+00:20:15,130 --> 00:20:18,150
+algorithm ممكن يطبق parallel بشكل متوازي وبتالي
+
+273
+00:20:18,150 --> 00:20:23,060
+هذا بيعمل على تسريع العمل ال weaknesses تبعتهاإنها
+
+274
+00:20:23,060 --> 00:20:26,500
+بتحتاج لفترة طويلة من التعليم لأن زي ما شوفنا أن
+
+275
+00:20:26,500 --> 00:20:33,340
+الأوزان كلها بتتغير تخيل أنك في عندك عشرة input في
+
+276
+00:20:33,340 --> 00:20:38,060
+عشرة hidden في أربعة أو بلاش في اتنين
+
+277
+00:20:41,140 --> 00:20:44,420
+output اضرب هدول هي عبارة عن عدد ال connections
+
+278
+00:20:44,420 --> 00:20:47,320
+اللي موجودة و عدد ال connections بعدد الأوزان
+
+279
+00:20:47,320 --> 00:20:52,760
+وبالتالي بتكلم على 200 value كأوزان بدها تغيير مع
+
+280
+00:20:52,760 --> 00:20:57,000
+كل عملية ال training و هذا مع كل instance وبالتالي
+
+281
+00:20:57,000 --> 00:21:01,860
+موضوع ال training هياخد منه وقت طويل بتحتاج ده
+
+282
+00:21:01,860 --> 00:21:04,380
+كتير من ال argument او من ال parameter انا بحتاج
+
+283
+00:21:04,380 --> 00:21:07,340
+اعملها tuning بشكل صحيح عشان اقدر احصل على ال
+
+284
+00:21:07,340 --> 00:21:11,460
+result المطلوبةمنها إن الـ structure تبعتها أبسط
+
+285
+00:21:11,460 --> 00:21:15,680
+ما يمكن إيش ال structure؟ إيش ال activation
+
+286
+00:21:15,680 --> 00:21:19,380
+function اللي أنا بدي اعتمدها؟ إلى آخرين الآن من
+
+287
+00:21:19,380 --> 00:21:22,520
+أهم ال neural network اللي موجودة يا جماعة الخير
+
+288
+00:21:22,520 --> 00:21:26,200
+شغلة بنسميها ال back propagate neural network back
+
+289
+00:21:26,200 --> 00:21:32,400
+propagate الانتشار للخلف الآن أنا هوضحها بشكل سريع
+
+290
+00:21:32,400 --> 00:21:40,530
+هان هحاول أرسمها على الصبورةبس عشان تنتين تلاتة
+
+291
+00:21:40,530 --> 00:21:52,390
+أربعة واحدة تنتين تلاتة واحدة تنتين واحد اتنين
+
+292
+00:21:52,390 --> 00:21:54,230
+تلاتة
+
+293
+00:22:23,390 --> 00:22:27,830
+تمام عشان نفهم بس مبدأ ال neural network او ال
+
+294
+00:22:27,830 --> 00:22:31,210
+back propagate neural network بشكل سريع و مش هخش
+
+295
+00:22:31,210 --> 00:22:34,730
+المعادلات الرياضية التفصيلية اللي هشغل عليها لكن
+
+296
+00:22:34,730 --> 00:22:37,910
+انا بهمني الان نفهم ال concept على السريع الان
+
+297
+00:22:37,910 --> 00:22:42,510
+تخيل ان انا في عندى instance او ال data set
+
+298
+00:22:42,510 --> 00:22:45,810
+المفروض ال data set تبعتي او ال data set تبعتي
+
+299
+00:22:45,810 --> 00:22:49,190
+مكونة من four attributes و one class attribute
+
+300
+00:22:49,190 --> 00:22:56,110
+مظبوط و one targetبنسميهم A1, A2, A3, A4 و ال
+
+301
+00:22:56,110 --> 00:23:03,770
+label طبعا المفروض هنقل A1, A2, A3, A4 و هنا
+
+302
+00:23:03,770 --> 00:23:07,770
+المفروض في عند ال label الآن الفكرة فيها أنه هياخد
+
+303
+00:23:07,770 --> 00:23:11,210
+ال instance في الأول أول بعد ما بأتكلم على ال
+
+304
+00:23:11,210 --> 00:23:16,150
+topology تبعتها بروح بياخد مني عندي random weight
+
+305
+00:23:19,480 --> 00:23:22,320
+بياخد أوزان من صفر لواحد على كل ال connections
+
+306
+00:23:22,320 --> 00:23:28,500
+اللي موجودة تمام؟ الآن بياخد ال value مثلا واحد
+
+307
+00:23:28,500 --> 00:23:32,340
+واحد صفر واحد وال label تبعتها وكانت كانت على سبيل
+
+308
+00:23:32,340 --> 00:23:36,540
+مثال واحد بالشكل هذا فبياخد القيام اللي موجودة هنا
+
+309
+00:23:36,540 --> 00:23:40,580
+وبضربها مع الأوزان اللي موجودة لحد ما بياخد ال
+
+310
+00:23:40,580 --> 00:23:46,100
+output الآن في عندي ال real class وفي عندي ال
+
+311
+00:23:46,100 --> 00:23:47,000
+predicted class
+
+312
+00:23:49,540 --> 00:23:56,960
+الفرق بينهم بيأخذ
+
+313
+00:23:56,960 --> 00:24:01,700
+الخطأ هذا و بيبدأ يوزع بالعكس جداش الوزن كان هذا
+
+314
+00:24:01,700 --> 00:24:06,460
+random جداش ال connection جداش كل connection ساهم
+
+315
+00:24:08,030 --> 00:24:13,810
+بالوزن أو بالخطأ هذا فبتوزع عليهم الخطأ وكل مكان
+
+316
+00:24:13,810 --> 00:24:18,010
+اللي predicted تبعتي صح بتكون ال error zero معناته
+
+317
+00:24:18,010 --> 00:24:21,530
+أنا مش بحاجة أرجع يعني بين جثين ال neural network
+
+318
+00:24:21,530 --> 00:24:23,970
+بشكل عام او ال back propagation neural network
+
+319
+00:24:23,970 --> 00:24:31,830
+بشكل عام بتشتغل على two ways الباص الأولىمرحلة ال
+
+320
+00:24:31,830 --> 00:24:35,490
+prediction باخد ال input تبعتي بدخلها على ال data
+
+321
+00:24:35,490 --> 00:24:37,810
+على ال neural network بحسب لحد ما بحصل على ال
+
+322
+00:24:37,810 --> 00:24:43,110
+output بحسب ال error و بروح بوزن قيمة أو بعدل
+
+323
+00:24:43,110 --> 00:24:48,010
+الأوزان تبعا لقيمة الخطأ اللي موجود عندهم
+
+324
+00:24:49,890 --> 00:24:53,230
+وهذا فعلياً اللي بتصير عندنا في الـ neural network
+
+325
+00:24:53,230 --> 00:24:56,510
+في ال back propagate ال neural network ال forward
+
+326
+00:24:56,510 --> 00:25:01,970
+path ال path الأولى بطبق ال input و بحسب ال output
+
+327
+00:25:01,970 --> 00:25:05,830
+تبع ال activation function و بحسب الخطأ اللي موجود
+
+328
+00:25:05,830 --> 00:25:10,990
+عندي في ال back propagate ال path أنا فعلياً باخد
+
+329
+00:25:10,990 --> 00:25:14,990
+قيمة الخطأ و بعدل الأوزان حسب مساهمتها في نسبة
+
+330
+00:25:14,990 --> 00:25:21,120
+الخطأ اللي موجودة عندنا هناأخر slide موجودة عندي
+
+331
+00:25:21,120 --> 00:25:25,880
+هان اللي هي slide اللي لها علاقة بال بايثون كيف
+
+332
+00:25:25,880 --> 00:25:29,380
+ممكن انا اطبق ال back propagation neural network
+
+333
+00:25:29,380 --> 00:25:38,420
+على ال بايثون طبعا انا اشتغلت كتالي هان عملت load
+
+334
+00:25:38,420 --> 00:25:43,360
+لل IRS لل data set اللي موجودة عندي هان from ASCII
+
+335
+00:25:43,360 --> 00:25:47,520
+layer dot linear model import perceptron اشتغلت
+
+336
+00:25:47,520 --> 00:25:50,730
+على الأبسطالـ neural network اللي موجودة عندنا هنا
+
+337
+00:25:50,730 --> 00:25:55,970
+حددت ال target تبعتها و حولتها ل numbers setosa
+
+338
+00:25:55,970 --> 00:25:58,710
+طبعا او not setosa هيك لان في ال binary
+
+339
+00:25:58,710 --> 00:26:01,130
+classification and one او ال symbol ال neural
+
+340
+00:26:01,130 --> 00:26:03,670
+network تشغل على binary classification زي ما شوفنا
+
+341
+00:26:03,670 --> 00:26:07,590
+فحولت .. قلت اما هذا فيها three classes حولت ل two
+
+342
+00:26:07,590 --> 00:26:13,890
+classes صفر و واحد setosa و not setosa استدعيت
+
+343
+00:26:13,890 --> 00:26:17,780
+ال neural network تبعتي from ASCII learn.neural
+
+344
+00:26:17,780 --> 00:26:21,020
+network and board multilayer perceptron classifier
+
+345
+00:26:21,020 --> 00:26:26,740
+الموديل هذا يتطلب مني ان احدد له شغلات كتيرة عدد
+
+346
+00:26:26,740 --> 00:26:32,580
+ال hidden layer قلت له تنتين و خمسة نيورون في كل
+
+347
+00:26:32,580 --> 00:26:36,830
+واحدةأو الـ solver اللي هي ال activation function
+
+348
+00:26:36,830 --> 00:26:39,770
+تبعتي ال alpha اللي بتمثل ال learning rate هذه
+
+349
+00:26:39,770 --> 00:26:43,290
+مالكوش دخل فيها الآن ال solver و ال hidden layer
+
+350
+00:26:43,290 --> 00:26:46,850
+size ال hidden layer size هي تبعتي المهمة بالنسبة
+
+351
+00:26:46,850 --> 00:26:49,750
+لي ال activation function هي ال radial based
+
+352
+00:26:49,750 --> 00:26:53,490
+function وهنا بنتكلم على ال network اللي موجودة
+
+353
+00:26:53,490 --> 00:26:57,430
+هنا فقلتله أعمل train تبع ال X و ال Y فرح أعدل
+
+354
+00:26:57,430 --> 00:27:00,430
+الأوزان اللي موجود عندى هنا فلما أنا بدي أزوده
+
+355
+00:27:00,430 --> 00:27:04,610
+الآنData و اقوله اعملها prediction ال data بدها
+
+356
+00:27:04,610 --> 00:27:07,670
+تكون تماما مع ال data مع ال input اللي موجودة
+
+357
+00:27:07,670 --> 00:27:11,850
+عنديها و هذه ال data set هي عبارة عن مجموعة من
+
+358
+00:27:11,850 --> 00:27:15,490
+العناصر اللي موجودة عندها اذا قدمتليها as in او
+
+359
+00:27:15,490 --> 00:27:19,230
+matrix فاخدليها و في الآخر هتدين ل prediction اللي
+
+360
+00:27:19,230 --> 00:27:22,510
+موجودة يعني باختصار بسيط جدا انا المفروض ان data
+
+361
+00:27:22,510 --> 00:27:27,070
+set تبعتي احولها كلها ل numeric data في حال اذا
+
+362
+00:27:27,070 --> 00:27:31,680
+كنت انا بدي اشتغل معالـ Neural Network بتمنى عليكم
+
+363
+00:27:31,680 --> 00:27:35,300
+وهذه تجربوها وتفهموا الموضوع كويس وزي ما قلنا
+
+364
+00:27:35,300 --> 00:27:38,040
+سابقا على ال forum اللي موجود على ال model أنا
+
+365
+00:27:38,040 --> 00:27:41,420
+مستعد ان شاء الله تعالى للإجابة على أي سؤال وطبعا
+
+366
+00:27:41,420 --> 00:27:44,240
+احنا اتعمدنا الإجابات على ال forum مش على الخاص
+
+367
+00:27:44,240 --> 00:27:48,520
+عشان نقدر الفائدة تعمل لجميع والسلام عليكم ورحمة
+
+368
+00:27:48,520 --> 00:27:49,540
+الله وبركاته
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/u2_vU8et3ig_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/u2_vU8et3ig_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..cb1cf33c31a27db0218fad96d09439baaf7f99e1
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/u2_vU8et3ig_raw.json
@@ -0,0 +1 @@
+{"segments": [{"id": 1, "seek": 2134, "start": 4.94, "end": 21.34, "text": "باسم الله والحمد لله والصلاة والسلام على رسول الله أهلا وسهلا بكم محاضراتنا المستمرة في منصق ال data mining وما زلنا في باب ال classification او في باب التصنيف هنتكلم اليوم او في المحاضرة هذه ان شاء الله تعالى عن classifier كتير متقدم", "tokens": [3555, 32277, 2304, 21984, 16070, 35571, 3215, 24976, 3224, 16070, 9381, 15040, 3660, 16070, 3794, 37440, 15844, 12602, 3794, 12610, 21984, 5551, 3224, 15040, 46952, 3224, 15040, 4724, 24793, 3714, 5016, 46958, 2288, 9307, 8315, 9673, 14851, 2304, 25720, 8978, 9154, 9381, 4587, 2423, 1412, 15512, 4032, 15042, 30767, 1211, 8315, 8978, 4724, 16758, 2423, 21538, 1975, 2407, 8978, 4724, 16758, 16712, 9381, 22653, 5172, 8032, 29399, 4117, 19528, 45595, 20498, 1975, 2407, 8978, 9673, 5016, 46958, 25720, 29538, 16472, 13412, 16606, 21984, 37279, 6027, 7578, 18871, 1508, 9902, 9122, 2655, 13546, 44650, 28543, 2304], "avg_logprob": -0.16365559694046775, "compression_ratio": 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مختلفة", "tokens": [11622, 16373, 3215, 2423, 39184, 12577, 13672, 1829, 3714, 29245, 23328, 43242, 11296, 8978, 3714, 2288, 5016, 37977, 2423, 2539, 39894, 9381, 13546, 25124, 3555, 4117, 3660, 6055, 3215, 13063, 15844, 5551, 5172, 11242, 1211, 343, 4032, 363, 5296, 33456, 16472, 2655, 20193, 6055, 1863, 3794, 7578, 16472, 11296, 20449, 18513, 37977, 16490, 9566, 3714, 14851, 4587, 32640, 39894, 3215, 13063, 15844, 5551, 5172, 11242, 1211, 343, 4032, 363, 44381, 20666, 18875, 343, 39894, 2304, 12984, 1211, 16247, 2407, 11622, 7649, 6055, 3555, 3615, 2423, 4984, 4032, 2423, 363, 46811, 12984, 1211, 2423, 12577, 6055, 3555, 3615, 2423, 3209, 13672, 1829, 3714, 29245, 23328, 3660, 8978, 2423, 2120, 388, 11167, 18161, 3209, 13412, 2407, 10632, 25124, 17082, 1211, 3714, 46456, 46538, 3660], "avg_logprob": -0.15764736378095984, "compression_ratio": 1.7251908396946565, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 364.19, "end": 364.81, "word": "زائد", "probability": 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429.08, "end": 457.34, "text": "شو يعني black box؟ black box بمعنى انه انا فعلا مابشوفش ايش اللي بصير ولا بعرف ليش الأوزان هذه صارت هيك وفعلا هذه هي للأسف ال algorithm اللي موجودة عندنا يعني صعب ال interpretation تبعتها تصير عندي طيب الآن ال input حسب الرسم اللي عندي هان ال three inputs و ال two outputs و زي ما قلنا بما هي كلها أرقام معناته ال input تبعتها هتكون 01", "tokens": [8592, 2407, 37495, 22653, 2211, 2424, 22807, 2211, 2424, 4724, 2304, 3615, 1863, 7578, 16472, 3224, 1975, 8315, 6156, 3615, 15040, 3714, 16758, 8592, 38688, 8592, 1975, 1829, 8592, 13672, 1829, 4724, 9381, 13546, 49429, 4724, 3615, 28480, 32239, 8592, 16247, 2407, 11622, 7649, 29538, 20328, 9640, 2655, 39896, 4117, 4032, 5172, 3615, 15040, 29538, 39896, 24976, 10721, 3794, 5172, 2423, 9284, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 8315, 37495, 22653, 20328, 3615, 3555, 2423, 14174, 6055, 3555, 34268, 11296, 6055, 9381, 13546, 18871, 16254, 23032, 1829, 3555, 6024, 48506, 2423, 4846, 11331, 35457, 34892, 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للتجربة و القياس او تجربة و الخطأ زي ما احنا بنسميها احيانا و اتحددها لكن في بعض الناس بتقولك خليني اعمل initialization للكلام هذا عبر انه ابدأ بمجموع التنين على اتنين يعني الان اربعة و اتنين ستة", "tokens": [3555, 43042, 3224, 19446, 41185, 8592, 6225, 3215, 3215, 2423, 39184, 22027, 3714, 3555, 16095, 4032, 2304, 2655, 32887, 4117, 5296, 4117, 24976, 2655, 7435, 25513, 3660, 4032, 25062, 25528, 3794, 1975, 2407, 6055, 7435, 25513, 3660, 4032, 33962, 9566, 10721, 30767, 1829, 19446, 1975, 5016, 8315, 44945, 38251, 1829, 11296, 1975, 5016, 1829, 7649, 995, 4032, 1975, 2655, 24401, 3215, 11296, 44381, 8978, 45030, 11242, 2423, 8315, 3794, 39894, 39648, 4117, 16490, 1211, 9957, 1829, 1975, 25957, 1211, 5883, 2144, 24976, 28820, 10943, 23758, 6225, 26890, 16472, 3224, 1975, 44510, 10721, 4724, 2304, 7435, 2304, 45367, 16712, 1863, 9957, 15844, 1975, 2655, 1863, 9957, 37495, 22653, 2423, 7649, 1975, 25513, 27884, 4032, 1975, 2655, 1863, 9957, 8608, 2655, 3660], "avg_logprob": 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في الآخر ال function انا هاللاحظ حاطين summation عشان عبارة عن مضروب ال input في ال weight تبعتها و بجمعهم هذه عبارة عن vector و بضفلهم ال bias لمرة واحدة و بروح على ال function اللي موجودة عندها", "tokens": [1863, 47341, 3615, 24976, 39184, 22811, 2423, 39184, 18161, 3209, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 11296, 8978, 6024, 95, 34740, 2423, 2445, 1975, 8315, 8032, 6027, 15040, 5016, 19913, 11331, 41193, 9957, 28811, 6225, 8592, 7649, 6225, 3555, 9640, 3660, 18871, 3714, 11242, 32887, 3555, 2423, 4846, 8978, 2423, 3364, 6055, 3555, 34268, 11296, 4032, 4724, 7435, 2304, 3615, 16095, 29538, 6225, 3555, 9640, 3660, 18871, 8062, 4032, 4724, 11242, 5172, 1211, 16095, 2423, 12577, 32767, 25720, 36764, 24401, 3660, 4032, 4724, 32887, 5016, 15844, 2423, 2445, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 11296], "avg_logprob": -0.17793367301322977, "compression_ratio": 1.7276785714285714, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 769.14, "end": 769.56, "word": 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transformation function ليش transformation او transfer function لأن هي بتنقل ال input لل output ليش بتسميها activation لأنها بتعمل على تنشيط ال output neurons اللي موجودة عندى هنا وبتماما هخرجها هطلحة لل out بكل بساطة", "tokens": [6027, 7649, 2423, 39184, 2445, 29538, 6225, 18513, 3660, 44945, 38251, 1829, 11296, 1975, 15042, 2423, 24433, 2445, 1975, 2407, 2423, 9887, 2445, 24433, 2445, 1975, 2407, 9887, 2445, 32239, 8592, 9887, 1975, 2407, 5003, 2445, 5296, 33456, 39896, 39894, 1863, 4587, 1211, 2423, 4846, 24976, 5598, 32239, 8592, 39894, 38251, 1829, 11296, 24433, 5296, 33456, 11296, 39894, 25957, 1211, 15844, 6055, 1863, 8592, 1829, 9566, 2423, 5598, 22027, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 7578, 34105, 46599, 39237, 10943, 995, 8032, 34740, 7435, 11296, 8032, 9566, 1211, 5016, 3660, 24976, 484, 4724, 28820, 4724, 3794, 41193, 3660], "avg_logprob": -0.2449999974668026, "compression_ratio": 2.0, "no_speech_prob": 0.0, "words": [{"start": 792.67, "end": 793.05, "word": 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موجود عندي كذلك في عندي ال Sigmoid Function", "tokens": [41185, 43242, 2423, 39184, 14670, 289, 6531, 8663, 11166, 882, 34051, 2423, 39184, 334, 14214, 11166, 882, 2423, 39184, 334, 14214, 11166, 882, 30767, 1829, 19446, 1975, 5016, 8315, 13412, 995, 33911, 9957, 39896, 11296, 11933, 15730, 25961, 2655, 25062, 32640, 3660, 6055, 3215, 9957, 1829, 5551, 3615, 23942, 9154, 12174, 32640, 3660, 2423, 1622, 23758, 20449, 8315, 47395, 5296, 1508, 316, 37495, 22653, 28242, 9673, 1863, 9566, 28671, 39896, 383, 16, 37037, 24192, 383, 17, 44945, 16606, 15844, 2423, 1622, 13672, 1829, 3714, 29245, 23328, 18871, 16254, 9122, 8848, 23275, 8978, 18871, 16254, 2423, 37763, 3280, 327, 11166, 882], "avg_logprob": -0.2202970261621003, "compression_ratio": 1.6528925619834711, "no_speech_prob": 0.0, "words": [{"start": 939.06, "end": 939.3, "word": "في", "probability": 0.1876220703125}, {"start": 939.3, "end": 939.46, "word": " عند", "probability": 0.9580078125}, {"start": 939.46, "end": 939.66, "word": " 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بيعمل", "probability": 0.899169921875}, {"start": 1218.59, "end": 1218.75, "word": " على", "probability": 0.89404296875}, {"start": 1218.75, "end": 1219.15, "word": " تسريع", "probability": 0.975830078125}, {"start": 1219.15, "end": 1219.45, "word": " العمل", "probability": 0.98583984375}, {"start": 1219.45, "end": 1220.17, "word": " ال", "probability": 0.96533203125}, {"start": 1220.17, "end": 1220.83, "word": " weaknesses", "probability": 0.939453125}, {"start": 1220.83, "end": 1221.83, "word": " تبعتها", "probability": 0.95654296875}], "temperature": 1.0}, {"id": 51, "seek": 123806, "start": 1222.76, "end": 1238.06, "text": "إنها بتحتاج لفترة طويلة من التعليم لأن زي ما شوفنا أن الأوزان كلها بتتغير تخيل أنك في عندك عشرة input في عشرة hidden في أربعة أو بلاش في اتنين", "tokens": [28814, 1863, 11296, 39894, 33753, 26108, 5296, 5172, 2655, 25720, 23032, 2407, 26895, 3660, 9154, 16712, 3615, 20292, 2304, 5296, 33456, 30767, 1829, 19446, 13412, 38688, 8315, 14739, 16247, 2407, 11622, 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كأوزان بدها تغيير مع كل عملية ال training و هذا مع كل instance وبالتالي موضوع ال training هياخد منه وقت طويل بتحتاج ده كتير من ال argument او من ال parameter انا بحتاج اعملها tuning بشكل صحيح عشان اقدر احصل على ال result المطلوبة", "tokens": [346, 2582, 1975, 11242, 25513, 8032, 3215, 12610, 39896, 6225, 3555, 9640, 3660, 18871, 6225, 3215, 3215, 2423, 9271, 13672, 1829, 3714, 29245, 23328, 3660, 4032, 6225, 3215, 3215, 2423, 9271, 4724, 22488, 3215, 16247, 2407, 11622, 7649, 46599, 6027, 2655, 6027, 1829, 39894, 4117, 19528, 15844, 2331, 2158, 9122, 10721, 2407, 11622, 7649, 47525, 11296, 6055, 17082, 1829, 13546, 20449, 28242, 6225, 42213, 10632, 2423, 3097, 4032, 23758, 20449, 28242, 5197, 46599, 6027, 2655, 6027, 1829, 3714, 2407, 11242, 45367, 2423, 3097, 39896, 47283, 3215, 9154, 3224, 4032, 38149, 23032, 2407, 26895, 39894, 33753, 26108, 11778, 3224, 9122, 2655, 13546, 9154, 2423, 6770, 1975, 2407, 9154, 2423, 13075, 1975, 8315, 4724, 33753, 26108, 1975, 25957, 1211, 11296, 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دخل فيها الآن ال solver و ال hidden layer size ال hidden layer size هي تبعتي المهمة بالنسبة لي ال activation function هي ال radial based function وهنا بنتكلم على ال network اللي موجودة هنا فقلتله أعمل train تبع ال X و ال Y فرح أعدل الأوزان اللي موجود عندى هنا فلما أنا بدي أزوده الآن", "tokens": [10721, 2407, 2423, 39184, 1404, 331, 13672, 1829, 39896, 2423, 24433, 2445, 6055, 3555, 3615, 31371, 2423, 8961, 13672, 1829, 39894, 2304, 12984, 1211, 2423, 2539, 3314, 29538, 3714, 6027, 4117, 2407, 8592, 11778, 9778, 1211, 8978, 11296, 6024, 48506, 2423, 1404, 331, 4032, 2423, 7633, 4583, 2744, 2423, 7633, 4583, 2744, 39896, 6055, 3555, 3615, 31371, 9673, 16095, 3660, 20666, 1863, 35457, 3660, 32239, 2423, 24433, 2445, 39896, 2423, 38783, 2361, 2445, 37037, 8315, 4724, 29399, 4117, 19528, 15844, 2423, 3209, 13672, 1829, 3714, 29245, 23328, 3660, 34105, 6156, 4587, 1211, 2655, 43761, 5551, 25957, 1211, 3847, 6055, 3555, 3615, 2423, 1783, 4032, 2423, 398, 6156, 2288, 5016, 5551, 22488, 1211, 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0.8546549479166666}, {"start": 1666.02, "end": 1666.42, "word": " تعمل", "probability": 0.8331705729166666}, {"start": 1666.42, "end": 1666.88, "word": " لجميع", "probability": 0.7984619140625}, {"start": 1666.88, "end": 1667.66, "word": " والسلام", "probability": 0.91748046875}, {"start": 1667.66, "end": 1668.08, "word": " عليكم", "probability": 0.961181640625}, {"start": 1668.08, "end": 1668.52, "word": " ورحمة", "probability": 0.942626953125}, {"start": 1668.52, "end": 1668.82, "word": " الله", "probability": 0.96875}, {"start": 1668.82, "end": 1669.54, "word": " وبركاته", "probability": 0.9662109375}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 1669.7005, "duration_after_vad": 1557.3618749999969}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/vNlYsg8cGAY.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/vNlYsg8cGAY.srt
new file mode 100644
index 0000000000000000000000000000000000000000..ac9f8ed4486f79e078ebaf881d6e4e009506456b
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/vNlYsg8cGAY.srt
@@ -0,0 +1,2302 @@
+1
+00:00:07,760 --> 00:00:09,860
+بسم الله والحمد لله والصلاة والسلام على رسول
+
+2
+00:00:09,860 --> 00:00:13,720
+الله أهلا وأهلا بالشباب الطيبين، وأتمنى لكم إن
+
+3
+00:00:13,720 --> 00:00:18,380
+شاء الله فصلا جديدا ملءه النشاط والمعرفة، وختامه
+
+4
+00:00:18,380 --> 00:00:21,400
+الدرجات العالية إن شاء الله تعالى. اليوم إن شاء
+
+5
+00:00:21,400 --> 00:00:25,720
+الله، هنبدأ نتكلم أو هنعمل مقدمة نتكلم.. نتواصل..
+
+6
+00:00:25,720 --> 00:00:30,180
+نتناقش فيها، ونعرض فيها الـ syllabus أو وصف مساق تنقيب
+
+7
+00:00:30,180 --> 00:00:34,400
+البيانات. لكن كالعادة يعني اللي بنحب الـ
+
+8
+00:00:34,400 --> 00:00:38,380
+discussion وبنحِب نتكلم معاكم بشكل كويس. لو أنا
+
+9
+00:00:38,380 --> 00:00:44,380
+سألتك أو سألت أي واحد فيكُم، شو يعني تنقيب بيانات؟
+
+10
+00:00:44,380 --> 00:00:48,660
+طيب، حد فيكم كلف نفسه يطلع على وصف المساق اللي
+
+11
+00:00:48,660 --> 00:00:53,220
+موجود على الصفحة قبل ما يسجل المساق؟ آه محمد؟ اللي
+
+12
+00:00:53,220 --> 00:00:57,020
+هي filtering the big data، filtering the big data،
+
+13
+00:00:57,020 --> 00:00:59,660
+شو يعني معاه؟ شو يعني بالعربي filter؟
+
+14
+00:01:02,490 --> 00:01:08,190
+filter معناته أنا بتكلم على تصفية، ترتيب، مصبوط لأ..
+
+15
+00:01:08,190 --> 00:01:11,930
+هي الـ data mining أو تنقيب البيانات، شغل أكبر من
+
+16
+00:01:11,930 --> 00:01:18,630
+هيك، آه الشباب، حاجة
+
+17
+00:01:18,630 --> 00:01:24,970
+صغيرة، وأفصل البيانات اللي فيها. طيب
+
+18
+00:01:24,970 --> 00:01:30,710
+الآن، أجيب pattern، أطلع شغلة غامضة، الآن يعني بديتها.. آه، رمي
+
+20
+00:01:35,260 --> 00:01:41,100
+آه، الوصول إلى معلومات مفيدة من معلومات ما لها غير
+
+21
+00:01:41,100 --> 00:01:45,880
+مرتبة، غير مرتبة، خلّيني أقول. طيب، الآن لو أنا جيت
+
+22
+00:01:45,880 --> 00:01:51,440
+سألتك، تنقيب
+
+23
+00:01:51,440 --> 00:01:58,400
+بالعربي mining شو
+
+24
+00:01:58,400 --> 00:02:03,080
+يعني كلمة تنقيب معناته بالعربي استخراج، استخراج
+
+25
+00:02:03,080 --> 00:02:07,090
+إيش؟ يعني ابن فعلا راح يقول: والله بدنا بنقب عن
+
+26
+00:02:07,090 --> 00:02:13,610
+الشواكل مثلا؟ لا.. لا.. لا، استخراج مادة من مادة
+
+27
+00:02:13,610 --> 00:02:22,230
+خام، استخراج أو بحث أثري؟
+
+28
+00:02:22,230 --> 00:02:25,330
+مادة من مادة خام. طب ممكن تقولي إيش طبيعة المادة هي
+
+29
+00:02:25,330 --> 00:02:25,870
+يا باشا؟
+
+30
+00:02:29,140 --> 00:02:31,680
+التنقيب، الآن سيبني من الـ data، الـ data عن الجهة
+
+31
+00:02:31,680 --> 00:02:39,420
+خلينا الآن نتكلم على التنقيب. أيوة، أيوة، البحث هذا
+
+32
+00:02:39,420 --> 00:02:44,260
+أو التنقيب، هذه كمسمّى أو كمصطلح مرتبط باستخراج أو
+
+33
+00:02:44,260 --> 00:02:48,940
+البحث عن أشياء
+
+34
+00:02:48,940 --> 00:02:52,080
+ثمينة،
+
+35
+00:02:52,080 --> 00:02:55,120
+نادرة،
+
+36
+00:02:55,120 --> 00:02:57,460
+الوجود.
+
+37
+00:02:58,280 --> 00:03:01,180
+يعني الآن ما فش أروح أقول: والله أنا بدي أنقب على
+
+38
+00:03:01,180 --> 00:03:06,280
+جلم رصاص! احنا بروح بنشتري جلم رصاص أو بنستلفه، لأن
+
+39
+00:03:06,280 --> 00:03:09,060
+حد بيتفرج في الـ national geographic وبيِتفرج على
+
+40
+00:03:09,060 --> 00:03:13,460
+برامج التنقيب، ليش
+
+41
+00:03:13,460 --> 00:03:22,000
+بنقبوا كانوا؟ آه يا هاشم، عن الذهب، فحم، petroleum،
+
+42
+00:03:22,000 --> 00:03:29,050
+النفط، أحجار كريمة، ولاحظ كلها.. كلها غالية
+
+43
+00:03:29,050 --> 00:03:35,830
+ونادرة الوجود، ومهمة في عالمنا اليوم. طيب، كلمة تنقيب
+
+44
+00:03:35,830 --> 00:03:44,130
+ارتبطت بمخاطر، زائد
+
+45
+00:03:44,130 --> 00:03:46,210
+تكلفة، ولا شو رايكم؟
+
+46
+00:03:49,310 --> 00:03:51,410
+الناس اللي بتعمل تنقيب على الدهب، وتنقيب على
+
+47
+00:03:51,410 --> 00:03:54,810
+البترول، هاي جِدّاش في عندهم risk عالية، لأنهم
+
+48
+00:03:54,810 --> 00:03:58,270
+بيستخدموا مكان تقيل، بيضطروا بيحفروا عميقا في الأرض،
+
+49
+00:03:58,270 --> 00:04:02,010
+أحيانا بينزلوا، أحيانا في داخل الحفرة تبعتهم، وممكن
+
+50
+00:04:02,010 --> 00:04:06,810
+تنهار عليهم، هذه
+
+51
+00:04:06,810 --> 00:04:10,510
+مخاطر على مستوى الجسد، مخاطر تانية مرتبطة بالتنقيب،
+
+52
+00:04:10,510 --> 00:04:16,710
+إنه ممكن بعد جهد كبير تطلع صفر اليدين، تمام؟
+
+53
+00:04:18,660 --> 00:04:22,720
+وتكلفة عالية، مكان وفمكانه تماما زي الصياد اللي
+
+54
+00:04:22,720 --> 00:04:28,940
+بيروح بيحاول يصيد، بس الصياد بيستنى السمك يجيه،
+
+55
+00:04:28,940 --> 00:04:33,880
+مظبوط؟ بينما المناقب هو اللي بِدور، هو اللي بِبحِث،
+
+56
+00:04:33,880 --> 00:04:38,440
+وبِدور عن العناصر اللي موجودة. فاليوم احنا هنتكلم
+
+57
+00:04:38,440 --> 00:04:44,140
+تنقيب البيانات، تمام؟
+
+58
+00:04:54,970 --> 00:04:59,450
+data، شو يعني بيانات؟
+
+59
+00:04:59,450 --> 00:05:03,010
+بيانات،
+
+60
+00:05:03,010 --> 00:05:06,970
+إيش يعني بيانات؟
+
+61
+00:05:06,970 --> 00:05:11,790
+طيب، إيش الفرق بين الـ data والـ information؟
+
+62
+00:05:15,730 --> 00:05:19,930
+data، تمت معالجتها، معناته البيانات هي البيانات الخام،
+
+63
+00:05:19,930 --> 00:05:23,070
+وببدأ أرجع للكلام اللي قلت لزميلك: استخراج مادة من
+
+64
+00:05:23,070 --> 00:05:28,330
+مادة خام. فأنت فعليا عندك بيانات طلاب الجامعات في
+
+65
+00:05:28,330 --> 00:05:35,750
+فلسطين من 2000 لـ 2020. So what؟ أنا جد موجودة أكثر
+
+66
+00:05:35,750 --> 00:05:40,270
+من database، دمجناهم مع بعض، جمعنا البيانات هذه،
+
+67
+00:05:40,270 --> 00:05:45,260
+إيش بقدر أستفيد منهم أنا؟ دورك أنت كمنقب، تبدأ تروح
+
+68
+00:05:45,260 --> 00:05:50,500
+تدور لنا على معرفة جديدة نقدر نستفيد منها في حياتنا،
+
+69
+00:05:50,500 --> 00:05:54,860
+مثل.. نسبة الذكور للإناث. آه.. لاحظ من.. أنا
+
+70
+00:05:54,860 --> 00:05:56,560
+خلّيني أَصْبر.. أنا بَضايق.. بعدين بجاوبك يعني على
+
+71
+00:05:56,560 --> 00:05:59,040
+الكلام اللي أنا بحكي فيه الآن، زميل اللي بقول مثل
+
+72
+00:05:59,040 --> 00:06:03,160
+نسبة الذكور للإناث، هذا الكلام غلط، هذا إحصاء، إحنا
+
+73
+00:06:03,160 --> 00:06:08,140
+بإحصاء بتجيبه، مش ضروري تتعلم تنقيب بيانات. وهنشوف
+
+74
+00:06:08,140 --> 00:06:11,060
+كمان شوية في التعريف تبع تنقيب البيانات، إنه أنا
+
+75
+00:06:11,060 --> 00:06:17,300
+فعليا بحاجة لاستخدام طرق غير تقليدية، وهتشوف إنه
+
+76
+00:06:17,300 --> 00:06:19,960
+تنقيب البيانات باستخدام الإحصاء، وباستخدام الـ
+
+77
+00:06:19,960 --> 00:06:22,420
+database، وباستخدام البرمجة، وباستخدام الشبكات، و
+
+78
+00:06:22,420 --> 00:06:25,760
+باستخدام معظم العلوم من أجل الوصول للهدف المطلوب،
+
+79
+00:06:25,760 --> 00:06:29,480
+لأنه هو بنقّب في معلومات
+
+80
+00:06:32,110 --> 00:06:36,270
+بنقب في الـ data عشان يطلع، أيوة. فبالتالي الآن هذه
+
+81
+00:06:36,270 --> 00:06:40,510
+بيانات مش معلومات، عشان هي، أنا بسألك إيش هي
+
+82
+00:06:40,510 --> 00:06:45,510
+البيانات؟ شوف
+
+83
+00:06:45,510 --> 00:06:51,850
+عادة.. مثلا.. الآن أنت بتستخرجي المعلومة، تمام؟
+
+84
+00:06:51,850 --> 00:07:00,630
+الآن بالعربي عادة إحنا بنقول: تنقيب عن الذهب، ما نقولش
+
+85
+00:07:00,630 --> 00:07:07,380
+بنقب في الذهب. تنقيب عن البترول، ومكان التنقيب في
+
+86
+00:07:07,380 --> 00:07:12,600
+حياتنا كبشر، مكان واحد، باطن الأرض. عشان هيك اختصر كل
+
+87
+00:07:12,600 --> 00:07:18,300
+المسميات، تمام؟ كما بقول لك: تنقيب عن، بينما هنا أنواع
+
+88
+00:07:18,300 --> 00:07:22,980
+البيانات اللي عندي مختلفة، والـ task تبعتي اللي أنا
+
+89
+00:07:22,980 --> 00:07:27,700
+باطلعها مختلفة. الـ data، مصدر البيانات، لما تكون
+
+90
+00:07:27,700 --> 00:07:31,500
+بيانات الطلاب الجامعيين على مستوى فلسطين، غير لما
+
+91
+00:07:31,500 --> 00:07:34,980
+تكون مصدر البيانات بيانات، وإما الإرشيف الصحي
+
+92
+00:07:34,980 --> 00:07:39,500
+للمواطنين الفلسطينيين، بيصير في عندي، هن بتدور على شغلة
+
+93
+00:07:39,500 --> 00:07:46,120
+مختلفة عنها، ومصدرين مختلفين، فبيصير في عندي تنقيب البيانات
+
+94
+00:07:46,120 --> 00:07:51,300
+مجلكاش تنقيب عن البيانات، فأنا بنقب في الـ.. بنقب
+
+95
+00:07:51,300 --> 00:07:56,430
+البيانات قاعد، عشان.. بهدف إني أطلع منها شغلة ممكن
+
+96
+00:07:56,430 --> 00:07:58,950
+تكون formation، بس هي فعليا أعلى من الـ information،
+
+97
+00:07:58,950 --> 00:08:03,470
+إحنا متكلمين على knowledge، معرفة، وهنشوف الفرق..
+
+98
+00:08:03,470 --> 00:08:06,370
+الفرق بين الـ data والـ information والـ knowledge
+
+99
+00:08:06,370 --> 00:08:12,270
+والحكمة أو الـ wisdom لاحقا. وبالتالي أنا الآن هدفي
+
+100
+00:08:12,270 --> 00:08:18,670
+أن أتعلم كيف أنقب البيانات في البيانات، مش عن
+
+101
+00:08:18,670 --> 00:08:23,370
+البيانات. الآن data mining، تنقيب، مقصود فيها في
+
+102
+00:08:23,370 --> 00:08:27,470
+البيانات، تنقيب البيانات نفسها من أجل استخراج معرفة
+
+103
+00:08:27,470 --> 00:08:34,870
+طيب، تتوقع العملية تكون سهلة ولا صعبة؟ حسب الـ data،
+
+104
+00:08:34,870 --> 00:08:40,810
+لكن عادة الـ data mining هي task، ليست task تقليدية،
+
+105
+00:08:40,810 --> 00:08:44,810
+ممكن تقدر تكتب برنامج، وهذا بيُعقّد إن كنت تكون
+
+106
+00:08:44,810 --> 00:08:50,120
+developer كويس. بيقتضي منك إنك تعمل import و export
+
+107
+00:08:50,120 --> 00:08:53,920
+بعض الأحيان للـ database، وكيف تعمل integration
+
+108
+00:08:53,920 --> 00:08:58,700
+وبيُلزِمك تعرف إن الـ database كويس. بيُلزِمك تتعرف على الـ
+
+109
+00:08:58,700 --> 00:09:02,660
+machine learning algorithm عشان تسخرها في عملية
+
+110
+00:09:02,660 --> 00:09:05,660
+التنقيب. يعني بنجّوزين، بدك أدوات، بدك tools، اللي
+
+111
+00:09:05,660 --> 00:09:08,600
+بِدور على الدهب، عنده حفار وعنده جرافة وعنده
+
+112
+00:09:08,600 --> 00:09:14,770
+المصفاة، وعنده الميه إلى آخره، هذه هي أدواته. وأنت
+
+113
+00:09:14,770 --> 00:09:17,390
+لازم يكون لك أدواتك اللي بقى بتستخدمها في عملية
+
+114
+00:09:17,390 --> 00:09:21,670
+التنقيب. طيب، لما نتكلم على معلومات المساق تبعنا،
+
+115
+00:09:21,670 --> 00:09:29,250
+أهم شغلة بتهمك فيها، إيميلي لأي استفسار، طبعا كلكم
+
+116
+00:09:29,250 --> 00:09:34,030
+بتعرفوا ساعات المكتبية للفصل هذا، من السبت للأربعاء
+
+117
+00:09:34,760 --> 00:09:37,640
+من الـ 11 إلى الواحدة، أنا موجود في المكتب، طبعا إلا
+
+118
+00:09:37,640 --> 00:09:40,300
+لو صار في اجتماع طارئ، أنا ما بقدرش أتحكم فيه يعني،
+
+119
+00:09:40,300 --> 00:09:43,340
+بس غالبا إن شاء الله أكون موجود، ومكتبي في الطابق
+
+120
+00:09:43,340 --> 00:09:49,100
+التالت في مبنى تكنولوجيا المعلومات. مقعد لقائنا 9 ونص
+
+121
+00:09:49,100 --> 00:09:54,960
+إلى الـ 11، كان في I 116، وجبناه للقاعة المصورة،
+
+122
+00:09:54,960 --> 00:10:02,270
+هذه وصف المساق تبعنا. المساق هذا حاولنا نعيد تصميمه
+
+123
+00:10:02,270 --> 00:10:08,730
+أو صممناه بحيث إنه يزود الطالب بمقدمة عن علم
+
+124
+00:10:08,730 --> 00:10:15,890
+البيانات، ويزوده بخبرة عملية، hand experience في
+
+125
+00:10:15,890 --> 00:10:21,630
+التعامل مع كل مراحل مشروع، أو مع شريعة قواعد data
+
+126
+00:10:21,630 --> 00:10:26,770
+mining، تنقيب البيانات. الآن hand experience، تجربة
+
+127
+00:10:26,770 --> 00:10:32,760
+عملية، with all faces، لما أتكلم with all faces،
+
+128
+00:10:32,760 --> 00:10:38,000
+معناته أنا جاي أتكلم عن إيش؟ عن مشروع بيمر في
+
+129
+00:10:38,000 --> 00:10:41,580
+مراحل، مش مرحلة واحدة. الآن في الـ database project،
+
+130
+00:10:41,580 --> 00:10:44,760
+لو أنا بدأ أُقارنها في الـ database، بتعمل analysis،
+
+131
+00:10:44,760 --> 00:10:50,560
+بتعمل design، بتعمل implementation، مظبوط؟ إيش دول
+
+132
+00:10:50,560 --> 00:10:51,200
+بعد هيك؟
+
+133
+00:10:53,820 --> 00:10:57,780
+خلاص، بدي أعمل test عشان أتأكد إن كل الأمور تمام،
+
+134
+00:10:57,780 --> 00:11:00,560
+وبعد ذلك لو أنا محتاج maintenance، بكلمك على أربع
+
+135
+00:11:00,560 --> 00:11:04,720
+مراحل. اليوم هتشوف إنه أنا في عندي 6 من 7،
+
+136
+00:11:04,720 --> 00:11:10,580
+على 8 مراحل، وكل واحدة بدها جهد ومعرفة مختلفة مني،
+
+137
+00:11:10,580 --> 00:11:16,500
+عشان أقدر أنجزها. طبعا هذا كله باعتماد على الـ real
+
+138
+00:11:16,500 --> 00:11:20,780
+data، ما بنفعش أستخدم fake data أو fabricated data، و
+
+139
+00:11:20,780 --> 00:11:23,790
+أشتغل عليها. طب دلوقت، بدي أجيب الـ real data، الـ
+
+140
+00:11:23,790 --> 00:11:26,610
+real data متاحة في مواقع كتير عالميا بتزودني بـ
+
+141
+00:11:26,610 --> 00:11:31,110
+real data، موجودة، historical data في مجالات مختلفة،
+
+142
+00:11:31,110 --> 00:11:36,450
+بدءا من التمييز بين أنواع الحشرات ومواصفاتها، لحد
+
+143
+00:11:36,450 --> 00:11:41,730
+تصنيف صور الفضاء، والشغلات هذه. فأنت وين مهتم، ممكن
+
+144
+00:11:41,730 --> 00:11:45,770
+تلاقي بيانات بتخدمك، وزودكوا إن شاء الله من خلال الـ
+
+145
+00:11:45,770 --> 00:11:49,210
+model بمجموعة من الروابط. ممكن المحاضرة الجاية أعرض
+
+146
+00:11:49,210 --> 00:11:53,430
+الروابط عليكم، نشوف بعض المواقع، بحيث إن مطلوب منك
+
+147
+00:11:53,430 --> 00:11:58,410
+فعليا تحدد data set أنت والفريق تبعك عشان تشتغل
+
+148
+00:11:58,410 --> 00:12:04,030
+عليها لحد نهاية الفصل. الآن هذا المساق هيغطي
+
+149
+00:12:04,030 --> 00:12:11,070
+مواضيع، بدءا من الـ data format، أنواع البيانات، طبعا
+
+150
+00:12:11,070 --> 00:12:15,850
+بما إنه درستوا قواعد بيانات اتنين، هسألكم شو هو
+
+151
+00:12:15,850 --> 00:12:22,190
+أنواع البيانات؟ تتذكروا المربع تبع البيانات؟
+
+152
+00:12:22,190 --> 00:12:27,810
+رسمنا رسمة زي هيك، اللي هي علاقة بالبيانات قبل ما
+
+153
+00:12:27,810 --> 00:12:33,490
+نتكلم عن الـ NoSQL Database، طبعا
+
+154
+00:12:33,490 --> 00:12:37,690
+إحنا بناخد المعلومات عشان نستخدمها، صح؟ أعين عليكم، صار
+
+155
+00:12:37,690 --> 00:12:38,490
+في عندي structured،
+
+156
+00:12:43,360 --> 00:12:50,220
+و unstructured. طيب، وإيش كمان؟ لا يا باشا، خلاص،
+
+157
+00:12:50,220 --> 00:12:52,800
+هدول هنخلصهم.. هنخلص الـ semi-structured. قلنا الـ No
+
+158
+00:12:52,800 --> 00:12:57,040
+SQL جاية عشان تتعامل مع الـ semi-structured data، و
+
+159
+00:12:57,040 --> 00:12:59,320
+لو كانت الـ structured بتتعامل معاها، unstructured
+
+160
+00:12:59,320 --> 00:13:02,960
+بتتعامل معاها غير. وفيه كمان تصنيفين: static
+
+161
+00:13:11,330 --> 00:13:16,070
+و dynamic data. الآن إن البيانات تبعتي بتتصف بواحدة
+
+162
+00:13:16,070 --> 00:13:19,590
+من الصفات هذه، بواحدة من المربعات هذه، إما هتكون
+
+163
+00:13:19,590 --> 00:13:24,510
+structured و static، أو unstructured و static. طبعا
+
+164
+00:13:24,510 --> 00:13:26,470
+لما أتكلم على structured، معناته إن أنا بتكلم على
+
+165
+00:13:26,470 --> 00:13:30,080
+بيانات جاهزة، وهذه اللي معنين فيها في المرحلة
+
+166
+00:13:30,080 --> 00:13:33,620
+الحالية في الـ Data Mining، وإلا كان صار اسم المساق
+
+167
+00:13:33,620 --> 00:13:37,900
+علوم البيانات، لأنه بيصير المفروض منك تاخد الـ
+
+168
+00:13:37,900 --> 00:13:41,160
+unstructured data، وتتعامل معاها مثل ما بتتعامل مع
+
+169
+00:13:41,160 --> 00:13:47,840
+structured. فإحنا مستهدفين المنطقة هذه، وممكن هذه في
+
+170
+00:13:47,840 --> 00:13:52,080
+الـ dynamic. وبالتالي أنا بقى أشتغل وين؟ على
+
+171
+00:13:52,080 --> 00:13:55,840
+structured data، سواء كانت dynamic أو static، مش
+
+172
+00:13:55,840 --> 00:14:00,320
+فارقة كتير معايا. عشان هيك، بالذات، أنا بُميّز من الـ
+
+173
+00:14:00,320 --> 00:14:06,540
+data format، كيف أعملها cleaning؟ شو يعني cleaning؟
+
+174
+00:14:06,540 --> 00:14:14,320
+الآن، الناس اللي بنقبوا عن الدهب، شو بيُطلّعوا؟ لا
+
+223
+00:17:38,400 --> 00:17:44,240
+قلنا وتستخدم الـ tools الحديثة ومن أهم الـ
+
+224
+00:17:44,240 --> 00:17:47,420
+tools  التي يستخدمها الشباب اليوم هي الـ tools المبنية
+
+225
+00:17:47,420 --> 00:17:50,360
+على الـ Python سواء كانت كلغة برمجة
+
+226
+00:17:50,360 --> 00:17:54,300
+programming language  تمام أو different distribution للـ Python أو حتى
+
+227
+00:17:54,300 --> 00:18:00,430
+فعلياً software packages مبنية على الـ Python بعد
+
+228
+00:18:00,430 --> 00:18:05,470
+هيك بدي أعمل evaluation  المفروض evaluation لإيش؟
+
+229
+00:18:05,470 --> 00:18:10,210
+لشغل، للنتيجة التي حصلت عليها، الآن وبعد دراسة
+
+230
+00:18:10,210 --> 00:18:15,890
+الوضع الصحي تبع المرضى اكتشفنا أن والله أن الناس
+
+231
+00:18:15,890 --> 00:18:19,490
+الذين يعانون من سوء تغذية هؤلاء ممكن برضه يكون
+
+232
+00:18:19,490 --> 00:18:24,270
+احتمالية إصابتهم بسرطان الرئة الله يبعد عنكم الشر و
+
+233
+00:18:24,270 --> 00:18:29,900
+عنكم وعن جميع المسلمين أنه عالي جداً كل الـ knowledge
+
+234
+00:18:29,900 --> 00:18:34,340
+التي لدينا نعرف أن التدخين، طيب شو دخل سوق التخزين؟ الـ
+
+235
+00:18:34,340 --> 00:18:37,080
+historical data تقول أن سوق التخزين لها دور في
+
+236
+00:18:37,080 --> 00:18:42,660
+الموضوع لأن هناك شخص كان يتغذى بشكل جيد وشرح
+
+237
+00:18:42,660 --> 00:18:46,660
+في التدخين لكنه لم يصب، لكن كل الحالات التي أصيبت
+
+238
+00:18:46,660 --> 00:18:50,340
+بالإضافة للتدخين كان لديهم سوق تخزين، معناته أصبح
+
+239
+00:18:50,340 --> 00:18:55,640
+هناك دور جديد، knowledge جديدة، من يقيمها؟
+
+240
+00:18:55,640 --> 00:19:01,310
+من يقيمها؟ الناس المختصون القائمون على الموضوع
+
+241
+00:19:01,310 --> 00:19:04,370
+هؤلاء يحتاجون أن يأخذوا، يجيبوا، يقولوا أين الـ system
+
+242
+00:19:04,370 --> 00:19:07,310
+الذي بنيته أو أين الـ project الذي بنيته، هذا صحيح
+
+243
+00:19:07,310 --> 00:19:11,430
+الحال، سيذهبون بأنفسهم ليجلبوا عينات حقيقية من الناس
+
+244
+00:19:11,430 --> 00:19:15,990
+المصابين بهذا المرض ويدرسونه، فعلياً عنده سوق
+
+245
+00:19:15,990 --> 00:19:18,870
+تغذية حسب الشروط الموجودة، يأخذون البيانات
+
+246
+00:19:18,870 --> 00:19:21,790
+ويعرضونها على الـ system، أنا لا أعرف، فالـ system عندما
+
+247
+00:19:21,790 --> 00:19:28,290
+يقول positive  سيصاب، أو negative،  هذه النسبة هي
+
+248
+00:19:28,290 --> 00:19:31,410
+بمثابة الـ evaluation، يعني تجلبون عينة من البيانات
+
+249
+00:19:31,410 --> 00:19:35,130
+الحقيقية وتُطبق على النظام، بعد ذلك يصبح النظام
+
+250
+00:19:35,130 --> 00:19:37,830
+هذا موثوقاً بالنسبة لهم، حسناً والله نحن ممكن
+
+251
+00:19:37,830 --> 00:19:43,190
+نتنبأ باحتمالية الإصابة، وممكن الآن
+
+252
+00:19:43,190 --> 00:19:47,790
+نسعى جاهدين لتحسين موضوع تغذية الناس بأهمية التغذية و
+
+253
+00:19:47,790 --> 00:19:51,920
+بحيث يتجنبوا التدخين وهكذا، آخر شغلة
+
+254
+00:19:51,920 --> 00:19:55,100
+تحتاجها، وطبعاً ممكن تكون أول شغلة أيضاً أحياناً
+
+255
+00:19:55,100 --> 00:19:58,660
+لفهم البيانات التي عندي، موضوع الـ data أو الـ
+
+256
+00:19:58,660 --> 00:20:01,140
+knowledge visualization، كيف أُظهر المعرفة؟
+
+257
+00:20:01,140 --> 00:20:04,180
+كلنا نعرف المقولة التي تقول الصورة خير من ألف
+
+258
+00:20:04,180 --> 00:20:09,920
+كلمة، الآن لو ذهبت وجلبت لك بيانات الطلاب أو جدول
+
+259
+00:20:09,920 --> 00:20:16,620
+الطلاب فيه مليون record وعلامات الطلاب موجودة، هل
+
+260
+00:20:16,620 --> 00:20:22,240
+تستطيع تحديد نسب الطلاب في كل مستوى؟ يعني مثلاً كم جيد
+
+261
+00:20:22,240 --> 00:20:26,060
+جداً، كم ممتاز، قل لي، اعمل تقريراً إحصائياً، حسناً
+
+262
+00:20:26,060 --> 00:20:29,240
+الحال، هذا التقرير لو كان فيه Graph أو
+
+263
+00:20:29,240 --> 00:20:34,700
+رسم بياني أسرع في فهمه، حتى أسرع من الجدول، لهذا السبب
+
+264
+00:20:34,700 --> 00:20:36,480
+يجب أن تكون لديك القدرة على عمل
+
+265
+00:20:36,480 --> 00:20:39,860
+visualization، الـ if then rule الذي يتحدث عنه
+
+266
+00:20:39,860 --> 00:20:43,660
+زميلنا، لو كانت نسبة الناس بحالتهم
+
+267
+00:20:43,660 --> 00:20:48,440
+الاجتماعية ودراستهم وتحصيلهم سيئ بنسبة 90%، فما
+
+268
+00:20:48,440 --> 00:20:53,540
+فوقها، هذه القاعدة تُكتب لفهمها بشكل صحيح if then
+
+269
+00:20:53,540 --> 00:20:58,210
+طيب، ممكن أروح أعمله كـ decision tree لفهم
+
+270
+00:20:58,210 --> 00:21:01,410
+كل فرع، لأننا نتحدث عن فرع واحد فقط، فممكن
+
+271
+00:21:01,410 --> 00:21:06,150
+نحتاج أن نعمل visualization من
+
+272
+00:21:06,150 --> 00:21:09,090
+أهداف المساق لدينا، بعد أن تحدثنا عن أُسس
+
+273
+00:21:09,090 --> 00:21:13,150
+المساق، أهداف المساق لدينا كانت كالآتي: providing
+
+274
+00:21:13,150 --> 00:21:18,310
+fundamental understanding، يزودنا بالفهم الأساسي
+
+275
+00:21:18,310 --> 00:21:23,750
+لمتطلبات الـ data mining حتى أستطيع استخراج المعرفة
+
+276
+00:21:23,750 --> 00:21:28,810
+المخفية في البيانات، أو المخفية في البيانات، هذه
+
+277
+00:21:28,810 --> 00:21:36,650
+النقطة الثانية: نستكشف معاً مجموعة من الـ data mining tasks
+
+278
+00:21:36,650 --> 00:21:41,230
+لاستخراج هذه المعرفة، الـ data mining tasks:
+
+279
+00:21:41,230 --> 00:21:45,230
+classification، classification  يعني تصنيف يا شباب
+
+280
+00:21:45,230 --> 00:21:49,930
+لو أردت أن أرى، في جو كالذي نحن فيه، فصل
+
+281
+00:21:49,930 --> 00:21:55,650
+الشتاء، وأريد معرفة هل الدنيا ستمطر أم لا، تلاحظ؟
+
+282
+00:22:03,800 --> 00:22:10,260
+rainy yes و no، إذا كان الـ system  يقول إن
+
+283
+00:22:10,260 --> 00:22:14,740
+الجو ماطر أو غير ماطر فهذا classification، إذا أراد
+
+284
+00:22:14,740 --> 00:22:18,260
+أن يقول لي الـ stock market أو الـ stock price سعر
+
+285
+00:22:18,260 --> 00:22:25,120
+السهم سيرتفع increase
+
+286
+00:22:25,120 --> 00:22:26,000
+or decrease
+
+287
+00:22:29,730 --> 00:22:36,050
+هذا classification  طبعاً، لكن لو كانت مسألة أخرى
+
+288
+00:22:36,050 --> 00:22:39,730
+مثل التنبؤ، أكتبها هنا، وهي الـ prediction أو الـ
+
+289
+00:22:39,730 --> 00:22:45,250
+regression، عندما أريد قيمة محددة، قيمة
+
+290
+00:22:45,250 --> 00:22:48,970
+لا تقول لي إن السهم سيرتفع أو سينخفض، قل لي كم
+
+291
+00:22:48,970 --> 00:22:53,250
+ستكون قيمة التغيير على السهم بعد يومين، وأنا أعرف
+
+292
+00:22:53,250 --> 00:22:57,330
+بنفسي هل سيرتفع أم ينخفض، ماذا تبقى؟ للقيمة
+
+293
+00:22:57,330 --> 00:23:00,790
+التي ستزودني بها، قل لي كم حجم المطر الذي سي
+
+294
+00:23:00,790 --> 00:23:06,090
+ينزل، عندما تقول لي صفر أفهم أنه لا يوجد مطر، وعندما
+
+295
+00:23:06,090 --> 00:23:12,430
+تقول لي أن نسبة المطر ستكون 5.45 ميليمتر في
+
+296
+00:23:12,430 --> 00:23:15,470
+اليوم الفلاني، معناته أفهم أن هناك مطراً، ومطراً غزيراً
+
+297
+00:23:15,470 --> 00:23:20,390
+أيضاً، وبالتالي هنا لدينا شغلة لها علاقة بـ
+
+298
+00:23:20,390 --> 00:23:24,110
+Prediction، الـ Clustering، الـ Grouping أو تجميع
+
+299
+00:23:24,110 --> 00:23:28,490
+البيانات حسب الخصائص المشتركة، طيب، أنا أبحث
+
+300
+00:23:28,490 --> 00:23:31,290
+عن الخصائص، الخصائص التي لا يمكنك تطبيقها
+
+301
+00:23:31,290 --> 00:23:34,730
+بيدك أو رؤيتها بعينيك، وسأُريك خلال مثال عملي
+
+302
+00:23:34,730 --> 00:23:38,030
+لاحقاً إن شاء الله تعالى، معاً هنا في القاعة، أو
+
+303
+00:23:38,030 --> 00:23:40,630
+سأريك أن هناك صعوبة حسب الـ
+
+304
+00:23:40,630 --> 00:23:42,870
+Requirement في الـ Clustering، أن تعمل عليها
+
+305
+00:23:42,870 --> 00:23:49,210
+Association Rules Extraction، ارتباط أو قوانين
+
+306
+00:23:49,210 --> 00:23:53,430
+الارتباط بين الأشياء في الـ supermarket؟ ما علاقة
+
+307
+00:23:53,430 --> 00:24:00,850
+علب السجائر بالقهوة بالشاي بالمشروبات الساخنة؟ هل
+
+308
+00:24:00,850 --> 00:24:04,630
+هناك علاقة بين حفاظات الأطفال والحليب والبودرة
+
+309
+00:24:04,630 --> 00:24:08,620
+والأشياء هذه أم لا؟ الناس الذين يذهبون عادةً ليشترُوا
+
+310
+00:24:08,620 --> 00:24:13,260
+مثلاً الشوكولاتة السائلة والزينة وما إلى ذلك
+
+311
+00:24:13,260 --> 00:24:16,380
+أكيد يبحثون عن طحين لعمل كيك، أو دقيق لعمل
+
+312
+00:24:16,380 --> 00:24:20,800
+كيك، هذه المعاملات الارتباطية ليست سهلة، أنا
+
+313
+00:24:20,800 --> 00:24:24,320
+أستطيع أن أعرفها وأراها، وبالتالي أنا أحتاج لـ
+
+314
+00:24:24,320 --> 00:24:29,990
+association، أخطر من هذا، حالات ظهور مرض معين إذا
+
+315
+00:24:29,990 --> 00:24:33,910
+توفرت الظروف واحد اثنان ثلاثة، معناته هذا المرض
+
+316
+00:24:33,910 --> 00:24:36,810
+ممكن أن يظهر، وهكذا تصبح قيمة الـ association rule  خاصتي
+
+317
+00:24:36,810 --> 00:24:41,150
+أكثر جدية من الأمور السابقة، الـ outlier detection
+
+318
+00:24:41,150 --> 00:24:46,450
+تحديد الحالات الشاذة في البيئة التي أعمل
+
+319
+00:24:46,450 --> 00:24:53,130
+عليها، يعني يقول لك والله فلان ماشاء الله عليه
+
+320
+00:24:53,130 --> 00:24:56,330
+الرجل مجتهد في تربية أولاده والبيت ماشاء الله
+
+321
+00:24:56,330 --> 00:25:01,330
+وأهل بيته كذلك، لكن لديه ابن، أعوذ بالله، شاذ بعيد
+
+322
+00:25:01,330 --> 00:25:04,950
+عنهم، مختلف عنهم تماماً، تقول ليس منهم يا رجل أم لا؟
+
+323
+00:25:04,950 --> 00:25:09,190
+هذا بمصطلح الباحثين الذي… نقول عنه out layer
+
+324
+00:25:09,190 --> 00:25:15,650
+مختلف، نجد نتحدث أن ثمار شجرة معينة
+
+325
+00:25:15,650 --> 00:25:20,950
+شجرة التفاح أو… بلاش، في مزرعة تفاح وأنا أُعِب
+
+326
+00:25:20,950 --> 00:25:26,210
+عليهم جميعاً، أسقيهم نفس الري ونفس الموعد ونفس
+
+327
+00:25:26,210 --> 00:25:31,410
+الكمية، يحتاجون لعلاج أو مضادات أو تغذية، أشتغل
+
+328
+00:25:31,410 --> 00:25:37,250
+عليهم جميعاً إلا أن هناك شجرة في المزرعة، ثمارها
+
+329
+00:25:37,250 --> 00:25:44,630
+غير نافعة، أحتاج لاقتلاعها ورميها؟ قد تحتاج لـ
+
+330
+00:25:44,630 --> 00:25:50,440
+اقتلاعها حتى لا تُحسب عليك في النهاية، يبقى هذا، طيب
+
+331
+00:25:50,440 --> 00:25:56,880
+الآن، هل هناك سبب معين واضح للشذوذ؟ genetic، وبالتالي
+
+332
+00:25:56,880 --> 00:26:01,360
+ممكن أن أبحث، طيب هم جميعاً مزروعون في نفس
+
+333
+00:26:01,360 --> 00:26:05,200
+الأرض، فرّج مثلاً في ارتفاع أربعة أمتار، ممكن أن تكون جولة
+
+334
+00:26:05,200 --> 00:26:09,560
+مياة، اختيارنا للأرض بالسنتيمتر، صحيح كلامك، ممكن أن تُفرق
+
+335
+00:26:09,560 --> 00:26:13,380
+الأمور، لكن في النهاية تبقى ليست ضمن السياق الذي
+
+336
+00:26:13,380 --> 00:26:17,840
+نتحدث عنه الآن، أخطر من هذا يا شباب، عادةً أنا
+
+337
+00:26:17,840 --> 00:26:22,800
+لدي server، لدي server  يقدم خدمة تسجيل للطلاب
+
+338
+00:26:22,800 --> 00:26:26,900
+للجامعة، عادي، والحركة عليه متوقعة أن
+
+339
+00:26:26,900 --> 00:26:30,660
+تأتي لي مثلاً خلال الدقيقة 100 connection ألف
+
+340
+00:26:30,660 --> 00:26:36,280
+connection، في لحظة من اللحظات جاءني مليون request
+
+341
+00:26:36,280 --> 00:26:36,940
+لـ connections
+
+342
+00:26:39,880 --> 00:26:42,280
+أها، يعني أصبح هناك attack، أصبح هناك ماذا؟
+
+343
+00:26:42,280 --> 00:26:46,400
+outlier، فيجب أن تكون، يجب أن تكون هناك القدرة على
+
+344
+00:26:46,400 --> 00:26:49,520
+تحديد هذا الـ outlier  وأسبابه، سنتحدث بالتفصيل
+
+345
+00:26:49,520 --> 00:26:53,680
+في حينها، practicing data mining project phases
+
+346
+00:26:53,680 --> 00:26:57,460
+تجربة وتطبيق فعلياً جميع المراحل، هذه
+
+347
+00:26:57,460 --> 00:27:04,640
+presenting، عرض البيانات سواء كانت في المرحلة المبكرة
+
+348
+00:27:04,640 --> 00:27:09,500
+قبل العمل، أو كانت المعرفة في نهاية الـ
+
+349
+00:27:09,500 --> 00:27:15,660
+project  الموجود لدي، ونرشد الطلبة قدر المستطاع
+
+350
+00:27:15,660 --> 00:27:21,320
+على المواضيع المتعلقة بـ data mining طبعاً
+
+351
+00:27:21,320 --> 00:27:24,660
+سيكون هناك جهد منا على هذه المواضيع معنا إن شاء
+
+352
+00:27:24,660 --> 00:27:27,000
+الله تعالى، نحاول تقوية
+
+353
+00:27:29,920 --> 00:27:34,120
+العمل الجماعي بينكم، وغالباً سأُشَكِّلُكم لمجموعات إن
+
+354
+00:27:34,120 --> 00:27:37,940
+شاء الله هذا الفصل، طيب الـ outcome، مخرجات المساق
+
+355
+00:27:37,940 --> 00:27:41,740
+أتوقع بعد نهاية المساق أن تكون قادراً على
+
+356
+00:27:41,740 --> 00:27:45,620
+تعريف الـ data mining، وصف البيانات المناسبة للـ
+
+357
+00:27:45,620 --> 00:27:50,620
+project  في الـ data mining، معرفة خمسة على الأقل من
+
+358
+00:27:50,620 --> 00:27:55,380
+الـ data mining tasks، وكل واحدة بشرحها، بتساوي collect
+
+359
+00:27:55,380 --> 00:27:58,760
+and prepare، تكون قادراً على جمع وإعداد البيانات
+
+360
+00:27:58,760 --> 00:28:04,800
+ لأي data mining project، ستتعرف
+
+361
+00:28:04,800 --> 00:28:11,240
+وتستخدم الـ machine learning algorithms  لتنفيذ
+
+362
+00:28:11,240 --> 00:28:17,270
+الـ data mining tasks المختلفة، تحليل وبناء data
+
+363
+00:28:17,270 --> 00:28:22,450
+mining project  سواء بشكل مستقل أو ضمن
+
+364
+00:28:22,450 --> 00:28:28,170
+فريق، سواء كنت عضواً في الفريق أو قائداً للفريق، تتبنى
+
+365
+00:28:28,170 --> 00:28:31,910
+أخلاقيات المهنة في المحافظة على خصوصية الناس في
+
+366
+00:28:31,910 --> 00:28:35,450
+المعلومات، لأنه عندما نتحدث عن بيانات
+
+367
+00:28:35,450 --> 00:28:39,030
+صحية أو بيانات اجتماعية أو بيانات، بمعنى
+
+368
+00:28:39,030 --> 00:28:44,350
+أن هناك privacy  يجب الالتزام به، تتصرف بأخلاق
+
+369
+00:28:44,350 --> 00:28:52,090
+حميدة وتحافظ على خصوصية الناس، يعني textbook
+
+370
+00:28:52,090 --> 00:28:56,830
+data mining concepts and techniques، النسخة الرابعة
+
+371
+00:28:56,830 --> 00:29:02,070
+2017 من Elsevier، كذلك لدينا الـ data mining الـ
+
+372
+00:29:02,070 --> 00:29:05,770
+reference book، طبعاً هذه هي الأساسية، لكن
+
+373
+00:29:05,770 --> 00:29:08,190
+ستجد في الـ references  عندي حوالي سبعة أو ثمانية
+
+374
+00:29:08,190 --> 00:29:12,010
+كتب ستكون مفيدة لك على الـ model، لأن هذه موجودة في
+
+375
+00:29:12,010 --> 00:29:16,900
+التحضير، سأنتقل بين الكتب، الـ Data Mining Practice
+
+376
+00:29:16,900 --> 00:29:20,840
+Machine Learning Tools and Techniques في 2016، قد
+
+377
+00:29:20,840 --> 00:29:24,020
+قريباً، هذه أحدث الإصدارات التي تتحدث مباشرة في
+
+378
+00:29:24,020 --> 00:29:27,460
+الـ Data Mining في 2018 و2019، تتحدث عن الـ Data
+
+379
+00:29:27,460 --> 00:29:30,860
+Science، لكن تأخذنا في الاتجاه قليلاً، مختلفة بعض الشيء عن
+
+380
+00:29:30,860 --> 00:29:35,560
+الـ structured data، الآن، ما هي المواضيع التي
+
+381
+00:29:35,560 --> 00:29:40,640
+سنغطيها؟ سنغطي مجموعة من العناوين أو المواضيع
+
+382
+00:29:40,640 --> 00:29:45,150
+بمحاولة توزيعها على الأسابيع، طبعاً كما أقول، لا يوجد شيء
+
+383
+00:29:45,150 --> 00:29:50,630
+مقدس، لكن سنحاول الالتزام بها قدر
+
+384
+00:29:50,630 --> 00:29:54,070
+المستطاع، تقريباً سنحتاج أسبوعاً لإنهاء الـ
+
+385
+00:29:54,070 --> 00:29:55,910
+introduction، يعني أسبوع، يعني محاضرة ثانية يا شباب
+
+386
+00:29:55,910 --> 00:29:58,750
+محاضرة، والمحاضرة القادمة، من المفترض أن الـ introduction
+
+387
+00:29:58,750 --> 00:30:03,570
+تنتهي، بعد ذلك سنتحدث عن الـ data
+
+388
+00:30:03,570 --> 00:30:06,470
+understanding and data preparation، وهنا تقريباً
+
+389
+00:30:06,470 --> 00:30:12,250
+سنأخذ أسبوعين، ممكن أكثر قليلاً، لكن هذا المبدأ، إذا أنا
+
+390
+00:30:12,250 --> 00:30:15,790
+أعددت البيانات وفهمتها جيداً أو فهمتها جيداً وأعددتها
+
+391
+00:30:15,790 --> 00:30:19,670
+للمهمة الخاصة بي، سنبدأ بالحديث عن knowledge
+
+392
+00:30:19,670 --> 00:30:22,030
+extraction  باستخدام الـ machine learning
+
+393
+00:30:22,030 --> 00:30:25,430
+algorithm، وكما قلنا، المهام الخاصة بنا خمسة:
+
+394
+00:30:26,620 --> 00:30:28,460
+classification، regression، clustering،
+
+395
+00:30:28,680 --> 00:30:32,800
+association rules، و outlier detection، لكل واحدة
+
+396
+00:30:32,800 --> 00:30:36,120
+فيها مقاييس مختلفة، evaluation metrics
+
+397
+00:30:36,120 --> 00:30:41,360
+ف سنشرح خوار
+
+445
+00:34:31,130 --> 00:34:36,410
+جدر يشخص لي خمسين في المئة من الحالات، تشخيص صحيح،
+
+446
+00:34:36,410 --> 00:34:39,850
+خمسين في المئة من الحالات اللي أنا مش قادر أشخصها،
+
+447
+00:34:39,850 --> 00:34:47,070
+هذا إنجاز، هذا الـ risk اللي احنا قلنا قبل شوية
+
+448
+00:34:47,070 --> 00:34:51,590
+فيها مخاطرة في التنقيب، ما هو أنت الآن جربت تبعك
+
+449
+00:34:51,590 --> 00:34:52,530
+الـ system بيكون reliable
+
+450
+00:34:55,350 --> 00:35:03,270
+شوف، أنا ممكن أرفض نظام بيديني 95% accuracy، دقة،
+
+451
+00:35:03,270 --> 00:35:05,750
+في الأمور الصحية، في الـ critical، لكن أنا قاعد
+
+452
+00:35:05,750 --> 00:35:10,230
+بقول لك إن الأعراض هي هي، والتشخيص، احنا كـ human مش
+
+453
+00:35:10,230 --> 00:35:13,770
+قادرين نشخص، عشان هيك أنا حصرتك في المجال إنه
+
+454
+00:35:13,770 --> 00:35:17,730
+complete benefit راح فعليا قدر يشخص لي تشخيص صحيح بـ
+
+455
+00:35:17,730 --> 00:35:21,370
+50% من الأعراض اللي موجودة، هاي طب تقول لي أنت شخصته
+
+456
+00:35:21,370 --> 00:35:24,630
+غلط؟ وما طب أنت مش قادر تشخصه وغالبا هتشخصه غلط
+
+457
+00:35:24,630 --> 00:35:29,750
+فما تحمل الـ system ما لا يطيق، زي ما أقول له، مع أنه
+
+458
+00:35:29,750 --> 00:35:32,530
+أنا بقول لك، إستهينش بحياة البشر، لأ لازم أشتغل و
+
+459
+00:35:32,530 --> 00:35:37,790
+أجتهد إنه تكون الأمور تمام، زي ما قلنا regression
+
+460
+00:35:37,790 --> 00:35:43,220
+أتوقع قيمة، value، real value، clustering جسم
+
+461
+00:35:43,220 --> 00:35:47,560
+لمجموعات، أروح أقول والله جسم الطلاب لثلاث مجموعات
+
+462
+00:35:47,560 --> 00:35:53,700
+هيكونوا في القاعة ثلاث مجموعات يا شباب، في الآخر اسمك
+
+463
+00:35:53,700 --> 00:35:57,940
+عبدالله، لو قلت لك جسم الطلاب لثلاث مجموعات في القاعة
+
+464
+00:35:57,940 --> 00:36:01,620
+ثلاث
+
+465
+00:36:01,620 --> 00:36:05,260
+مجموعات، اهدأ يا شباب، على السريع، عبدالله، ايوا
+
+466
+00:36:08,540 --> 00:36:11,060
+ممتاز، مع إنه مش موجود الكلام اللي أنت موجود فيه
+
+467
+00:36:11,060 --> 00:36:14,120
+بينما لو قلت له يمين أو يسار أو قلب، كان ضبطه معاك
+
+468
+00:36:14,120 --> 00:36:17,840
+100%، لاحظ إنه أنا ما تكلمتش معاك على
+
+469
+00:36:17,840 --> 00:36:23,600
+characteristics، قلت لك، كل بس كان طلبي منك جسم ليهم
+
+470
+00:36:23,600 --> 00:36:27,360
+كمجموعات، ما تحكملي في العدد، عفوا كان .. قد إيش ..
+
+471
+00:36:27,360 --> 00:36:30,200
+عفوا .. لما قلت لك ثلاث مجموعات أنا طلبت العدد هذا بس
+
+472
+00:36:30,200 --> 00:36:34,720
+ما قلت لك كم واحد في كل مجموعة، مصبوط؟ لكن أنت
+
+473
+00:36:34,720 --> 00:36:40,750
+ممكن تجي تقول لي والله هاي واحد، كمان اثنين، وهي ثلاثة،
+
+474
+00:36:40,750 --> 00:36:43,550
+طب ليش عملت هيك يا عبدالله؟ عشان أضمن توازن
+
+475
+00:36:43,550 --> 00:36:46,750
+أعداد في الأشخاص اللي موجودين، ممكن يقول آه والله
+
+476
+00:36:46,750 --> 00:36:50,430
+لا دكتور أنا بدي أصنفهم شكل مختلف، أنا بدي أروح
+
+477
+00:36:50,430 --> 00:36:57,370
+أستخدم معدلاتهم التراكمية اللي تحت الـ 75، بين 75 لـ
+
+478
+00:36:57,370 --> 00:37:00,830
+90 واللي فوق الـ 90، هاي ثلاث مجموعات، لاحظ ما حدا
+
+479
+00:37:00,830 --> 00:37:03,070
+في الدنيا بالسجل يقول لك تصنيفك غلط أو تقسيم ..
+
+480
+00:37:03,070 --> 00:37:06,730
+برنامج تقسيمك، طالما في عندك justification قوية،
+
+481
+00:37:06,730 --> 00:37:11,670
+ليش أنت قسمت هيك؟ أحيانا احنا بنعجز عن نشوف الـ
+
+482
+00:37:11,670 --> 00:37:14,910
+common properties في الـ data set، تخيل data set
+
+483
+00:37:14,910 --> 00:37:19,370
+فيها 100 attributes ومليون record، إيش الـ common
+
+484
+00:37:19,370 --> 00:37:24,030
+اللي بينهم؟ ما بعرف، فبقول للـ system أشغل نيابة عني
+
+485
+00:37:24,030 --> 00:37:29,110
+قسم لي إياهم لثلاث مجموعات، فببدأ يروح يدرس الخصائص و
+
+486
+00:37:29,110 --> 00:37:33,630
+بقسم لي إياهم، كذلك في الـ association rules سواء
+
+487
+00:37:33,630 --> 00:37:36,410
+كانت في الأمراض، في الـ marketing إلى آخره، والـ
+
+488
+00:37:36,410 --> 00:37:41,350
+outlier detection، بعد هيك،  لسبوع 13 و 14 هنبدأ في
+
+489
+00:37:41,350 --> 00:37:45,900
+الـ data visualization والـ knowledge presentation، 14
+
+490
+00:37:45,900 --> 00:37:50,560
+و 15، الـ 14 رح ن تناول موضوع من الموضوع الجديد إن
+
+491
+00:37:50,560 --> 00:37:53,880
+شاء الله تعالى، والـ 15 رح يكون في عندنا project
+
+492
+00:37:53,880 --> 00:37:57,560
+presentation and discussion، إن شاء الله تعالى
+
+493
+00:37:57,560 --> 00:38:05,560
+رح يتعلق بمسابقات تبعنا طبيعي، رح أ علمك تبرمج، رح أ علمك بما
+
+494
+00:38:05,560 --> 00:38:12,550
+يمشي لك بالمسابقة، ليش أنا جاي؟ إن شاء الله تعالى، طيب،
+
+495
+00:38:12,550 --> 00:38:18,530
+الآن أسلوبنا في التدريس رح يكون كالتالي: محاضرة،
+
+496
+00:38:18,530 --> 00:38:23,330
+مجموعة نقاش، عمل جماعي، وبعض الفيديوهات، والـ
+
+497
+00:38:23,330 --> 00:38:26,390
+presentation اللي رح أزيدك فيها، وممكن نعرض شغلة
+
+498
+00:38:26,390 --> 00:38:29,390
+ونتناقش فيها مع بعض، حسب التفكير، يعني شوية شوية
+
+499
+00:38:29,390 --> 00:38:34,250
+رح تكون الأمور رح تختلف، المادة عن database، اثنين، لأنه
+
+500
+00:38:34,250 --> 00:38:37,090
+فعليا المادة مختلفة، فيها ممكن تكون في interaction
+
+501
+00:38:37,090 --> 00:38:41,870
+بينكم وبين بعض بشكل كبير، اللي أنتم بتدوروا عليه من
+
+502
+00:38:41,870 --> 00:38:47,350
+ساعة توزيع العلامات، عشر علامات quizzes و assignments
+
+503
+00:38:47,350 --> 00:38:53,390
+عشرة على مشاركة في نشاطات المساق خلال الفصل، إيش
+
+504
+00:38:53,390 --> 00:38:56,170
+المشاركة؟ discussion، لأن ممكن تكون فيه علامات
+
+505
+00:38:56,170 --> 00:39:01,590
+وفلان، طبعا هذه العشرة بالذات، أنت فيهم صفر إلا لما
+
+506
+00:39:01,590 --> 00:39:07,210
+تشارك، يعني مثلا إيش اسم اللي بجنبك عليه؟ برضه علي؟
+
+507
+00:39:07,210 --> 00:39:12,270
+علي تربيع ولا علي اثنين؟ الآن علي قرر إنه بتبقى
+
+508
+00:39:12,270 --> 00:39:16,870
+يلعب في الجوال، قول المحاضرة مش مشكلة، فلازم تشاركني
+
+509
+00:39:16,870 --> 00:39:20,850
+في المحاضرة، عشان أسجلك، إن فلان حاضر المحاضرة،
+
+510
+00:39:20,850 --> 00:39:24,090
+هاي فلان نايم، فلان ناسِ، فلان مشغول، المحاضرة اللي
+
+511
+00:39:24,090 --> 00:39:26,990
+بتغيب فيها، العذر أنا سامحك فيها، في المناقشة وإذا
+
+512
+00:39:26,990 --> 00:39:29,150
+قررت تغيب كثير، رح أسحب لك المادة
+
+513
+00:39:33,110 --> 00:39:37,670
+مصبوط؟ عشرين في المئة، أو عشرين علامة على الـ
+
+514
+00:39:37,670 --> 00:39:43,450
+midterm، عشرين علامة على final project، وهذا غالبا
+
+515
+00:39:43,450 --> 00:39:46,310
+رح يكون فيه ثلاثات أو مجموعات، يعني حاجة simple فيه، مش
+
+516
+00:39:46,310 --> 00:39:50,550
+رح تكون لوحدك، واربعين في المئة امتحان نهائي، توزيع
+
+517
+00:39:50,550 --> 00:39:53,670
+بسيطة وسهلة، يعني ممكن تروح على الـ final عارف
+
+518
+00:39:53,670 --> 00:39:57,750
+بالضبط، وتقدر كم علامة لك عندي، وكم واحدة عشان تجيب
+
+519
+00:39:57,750 --> 00:40:03,320
+امتياز، اللي بيلزمك .. كم واحد بيعرف Python فيكم يا
+
+520
+00:40:03,320 --> 00:40:06,960
+الشباب؟ ولا واحد .. هاي في واحد .. كويس، الله يجبر
+
+521
+00:40:06,960 --> 00:40:11,660
+خاطرك، فرصة تتعلم شغلة جديدة، بس هذه رح تكون لوحدك، الـ
+
+522
+00:40:11,660 --> 00:40:15,160
+Java ما بنستخدمها كثير في الـ .. في الـ data mining
+
+523
+00:40:15,160 --> 00:40:18,660
+وإن كان الـ Python هو الـ trend، ممكن تلاقي بس رح تتغلب
+
+524
+00:40:18,660 --> 00:40:25,500
+.. رح .. لأ ما عنديش مشكلة، بتعرف الـ SQL؟  عشي
+
+525
+00:40:28,920 --> 00:40:32,220
+رح نتعرف كذلك، بيلزم نتعامل مع الـ Rapid Miner، أنتم
+
+526
+00:40:32,220 --> 00:40:35,560
+ملاحظين إن المادة ما فيش معها عمل، أي شباب، فإنت
+
+527
+00:40:35,560 --> 00:40:42,820
+معيد العملي تبع المادة، مش أنا، أنت، وبدأ المناسبة،
+
+528
+00:40:42,820 --> 00:40:47,340
+احنا أخذنا قرار في الكلية، كل مستوى ثالث من السنة،
+
+529
+00:40:47,340 --> 00:40:50,620
+عفوا، الرابع، من السنة الجاية، من الخطة الجديدة،
+
+530
+00:40:50,620 --> 00:40:55,490
+ما فيش عملي، وتالت قلصنا العملي قدر المستطاع، لأنه أنت
+
+531
+00:40:55,490 --> 00:40:58,150
+اللي المفروض تكون معيد بالسنة اللي بعديها، فخلصنا
+
+532
+00:40:58,150 --> 00:41:02,570
+يعني أبداً اشتغل، اتعب لأ، مش السنة اللي جاية هي لسه
+
+533
+00:41:02,570 --> 00:41:07,610
+عندها الخطة القديمة شغالة، متطلبات المساق، متطلبات
+
+534
+00:41:07,610 --> 00:41:10,010
+المساق، حضورك إجباري يا صاحب، ما فيش، علي علامات
+
+535
+00:41:10,010 --> 00:41:14,410
+علاماتك على نشاطك، أنت جيت وتقعد هنا عشان تتنشط
+
+536
+00:41:14,410 --> 00:41:18,010
+معنا، وناخد و نعطي مع بعض، فبن سجلك علامات، مش عشان
+
+537
+00:41:18,010 --> 00:41:25,050
+حضورك، تمام؟ 25%، الشباب، الغياب هذا قانون الجامعة، ما فيش
+
+538
+00:41:25,050 --> 00:41:29,870
+موعد مسبق للـ quiz، دربت
+
+539
+00:41:29,870 --> 00:41:33,770
+معاكم على وجوهكم الكريمة الطيبة، جامل هيك وأنا لا ..
+
+540
+00:41:33,770 --> 00:41:37,850
+ما بعرف الحال، بس ما فيش موعد .. ما فيش موعد مسبق للـ
+
+541
+00:41:37,850 --> 00:41:42,460
+quiz، وما فيش أي عذر، ما ترجعنيش في quiz، أنت غيبت عن
+
+542
+00:41:42,460 --> 00:41:45,580
+محاضرتي، إنه ما كانش معي خبر يا دكتور، وأنا بقول لك
+
+543
+00:41:45,580 --> 00:41:49,620
+ما فيش، quiz، الله يمن عليك بتمام الصحة والعافية
+
+544
+00:41:49,620 --> 00:41:54,320
+أنت ووالدك وكل أحبابك، ويمن عليك بالرزق الوفير
+
+545
+00:41:54,320 --> 00:41:58,600
+تمام؟ وتجيني كل محاضرة على البدري، على موعدها عشان
+
+546
+00:41:58,600 --> 00:42:02,740
+ما تغيبش، لأن هذه الأمور اللي ممكن تمنعك من التيجي، يعني
+
+547
+00:42:02,740 --> 00:42:08,660
+طيب، عادة بالزمن، رح أراجع باستمرار، لأن التقييم
+
+548
+00:42:08,660 --> 00:42:11,200
+رح يكون مختلف عن الأعوام الماضية، أو عن ما أنت عهدته
+
+549
+00:42:11,200 --> 00:42:14,800
+سابقا، جوالك
+
+550
+00:42:14,800 --> 00:42:17,480
+على الأقل يكون صامت، خصوصا إنه قاعتنا هي في اللي
+
+551
+00:42:17,480 --> 00:42:21,460
+احنا عاملين بنسجل الـ video وبنسجل المحاضرة و
+
+552
+00:42:21,460 --> 00:42:25,200
+بالتالي يعني يكفيني صوتي وصوتك هما اللي يكونوا
+
+553
+00:42:25,200 --> 00:42:31,700
+موجودين، صوت جوالاتنا، ما فيش داعي، لحكمة الفصل أو
+
+554
+00:42:31,700 --> 00:42:38,410
+السنة هاي، استمتع بحياتك قدر المستطاع، تمام؟ ولا تنسى
+
+555
+00:42:38,410 --> 00:42:42,670
+نصيبك من الدنيا، وأحسن كما أحسن الله إليك، كمل
+
+556
+00:42:42,670 --> 00:42:47,310
+الآية، بس احنا اتعودنا نأخذ الـ .. إيه؟ الـ .. إيه؟
+
+557
+00:42:47,310 --> 00:42:47,630
+الـ .. إيه؟ الـ .. إيه؟ الـ .. إيه؟ الـ .. إيه؟ الـ ..
+
+558
+00:42:47,630 --> 00:42:48,470
+إيه؟ الـ .. إيه؟ الـ .. إيه؟ الـ .. إيه؟ الـ .. إيه؟
+
+559
+00:42:48,470 --> 00:42:50,130
+الـ .. إيه؟ الـ .. إيه؟ الـ .. إيه؟ الـ .. إيه؟ الـ ..
+
+560
+00:42:50,130 --> 00:42:51,550
+إيه؟ الـ .. إيه؟ الـ .. إيه؟ الـ .. إيه؟ الـ .. إيه؟
+
+561
+00:42:51,550 --> 00:42:53,190
+الـ .. إيه؟ الـ .. إيه؟ الـ .. إيه؟ الـ .. إيه؟ الـ ..
+
+562
+00:42:53,190 --> 00:42:56,990
+إيه؟ الـ .. إيه؟ الـ .. إيه؟ الـ .. إيه؟ الـ ..
+
+563
+00:42:56,990 --> 00:42:59,510
+إيه؟ الـ ..
+
+564
+00:43:07,660 --> 00:43:11,920
+تمام؟ حتى كثير من أهل الدين بت .. اللي بيقولوا إن
+
+565
+00:43:11,920 --> 00:43:16,900
+حياتك أو أقدارك صنع يديك، يقال إن يوسف عليه
+
+566
+00:43:16,900 --> 00:43:21,100
+السلام، لما طال عليه السجن، قال يا ربي طال .. طال
+
+567
+00:43:21,100 --> 00:43:28,680
+السجن، آه، قال لو سألت العفو لعفوتك، وقال ربي السجن
+
+568
+00:43:28,680 --> 00:43:32,970
+وأحبه إلي مما .. ما قالش ربي اصرف عني، إيه ده، وهو
+
+569
+00:43:32,970 --> 00:43:35,770
+قدم السجن عن طلب الله الرحمن، فاخذ معينة له
+
+570
+00:43:35,770 --> 00:43:39,910
+وبالتالي أنت به، لا لفظك ولا نيتك، أنت وين بتكون
+
+571
+00:43:39,910 --> 00:43:44,770
+طبعا هاي الدرس في التنمية البشرية، كمل؟ يلا، الآن
+
+572
+00:43:44,770 --> 00:43:50,110
+بيلزّمك تصبر، لأنه مش كل شيء على كيفك، وبدك تتعدى في
+
+573
+00:43:50,110 --> 00:43:52,890
+المساق هذا، وفي الحياة كلها، يتهكّى، المساق مش ممكن
+
+574
+00:43:52,890 --> 00:43:56,170
+يجي على كيفك دائما، ولا مدرس المساق، ولا علامات
+
+575
+00:43:56,170 --> 00:43:57,450
+المساق، خلاص، راح هاشم
+
+576
+00:44:00,400 --> 00:44:05,460
+لأ، أنت شوف، أنت بتتمنى، بس أنت اجتهدت عشان تحصل
+
+577
+00:44:05,460 --> 00:44:09,700
+عليها في الآخر، يعني قد ما ممكن تجدها، دو ما ترضاش، بس
+
+578
+00:44:09,700 --> 00:44:12,640
+في الآخر هذا أصبح أمر واقعي موجود، فبدها تتعدى في
+
+579
+00:44:12,640 --> 00:44:17,040
+الآخر، لازم تصبر، كويس، وفي الآخر لازم تتمتع
+
+580
+00:44:17,040 --> 00:44:20,700
+بالجدية، لأن مش كل حياتنا لعب، عشان تحقق أهدافك،
+
+581
+00:44:20,700 --> 00:44:23,340
+شباب، من المساقات الممتعة، اللي ممكن تستفيد منه
+
+582
+00:44:23,340 --> 00:44:28,210
+بشكل كويس،  أشياء اتضاعت وأشياء اتعلمت، وأنا بحاول
+
+583
+00:44:28,210 --> 00:44:34,870
+أعلمك قدر ما أستطيع، إن شاء الله تعالى، خلص
+
+584
+00:44:34,870 --> 00:44:40,650
+السلبس، رح نهرّش شوية صغيرة كمقدمة، كمقدمة عشان ننتهي
+
+585
+00:44:40,650 --> 00:44:45,830
+زي ما انتهينا في المحاضرة السابقة، الآن في عندي هرم
+
+586
+00:44:45,830 --> 00:44:50,030
+بيسموه هرم المعلومات، أو هرم البيانات، عادةً احنا
+
+587
+00:44:50,030 --> 00:44:53,370
+بنتكلم Data Mining، وبنتكلم Data Base، مظبوط؟ وبنتكلم
+
+588
+00:44:53,370 --> 00:44:56,910
+Data Communication، كل شيء Data، ما فيش معلومات،
+
+589
+00:44:56,910 --> 00:45:03,250
+لأن الـ Data هذه بيلزمها سياق معين عشان تصير
+
+590
+00:45:03,250 --> 00:45:08,590
+معلومة، ما بنفعش وإحنا نيجي بنتكلم، بنفكر، عاملين
+
+591
+00:45:08,590 --> 00:45:12,530
+محاضرة أو جلسة حوار، عشان شو كيف بدنا نسقط صفقة
+
+592
+00:45:12,530 --> 00:45:19,170
+القرن، نقطة، واحد يقول لي والله عماد رجل طيب، ويا عز
+
+593
+00:45:19,170 --> 00:45:27,150
+ما تنعزم عنده، معلومة، data، عماد رجل كريم ومقدم
+
+594
+00:45:27,150 --> 00:45:31,730
+أكل طيب، بهمش، شو دخلها في السياق اللي احنا بنتكلم
+
+595
+00:45:31,730 --> 00:45:37,870
+فيه، حتى لو كانت معلومة قيمة، فقدت قيمتها، ليش؟ مش
+
+596
+00:45:37,870 --> 00:45:42,770
+في المكان الصح، فبالتالي إذا الـ data هاي اتوفر لها
+
+597
+00:45:42,770 --> 00:45:48,710
+context مناسب، معناته أنا بتكلم على information، صارت
+
+598
+00:45:48,710 --> 00:45:53,150
+معلومة، والمعلومة طبعا بمعناها أو بقيمتها، بالوقت أو
+
+599
+00:45:53,150 --> 00:45:59,550
+بالزمان اللي قيلت فيه، المعلومات هذه إذا نظمتها
+
+600
+00:45:59,550 --> 00:46:05,490
+rules، المعلومات هذه إذا صارت فيه rules بتحكمها و
+
+601
+00:46:05,490 --> 00:46:10,110
+بتطبقها، معناته احنا بنتكلم على knowledge أو معرفة
+
+602
+00:46:10,110 --> 00:46:11,270
+الآن
+
+603
+00:46:19,140 --> 00:46:24,660
+بَسمع إن الصائم يحق له أن يفطر في رمضان، أو المسلم
+
+604
+00:46:24,660 --> 00:46:28,140
+يحق له يفطر في رمضان، إيش بتقول يا راضي؟ الصيام فرض
+
+605
+00:46:28,140 --> 00:46:33,900
+.. فرض، في شروط، رح يلاحظ إن كان في عندي معلومة الآن
+
+606
+00:46:33,900 --> 00:46:37,460
+الشروط هذه هي اللي خلتها معرفة، لأن المعرفة بتعتمد
+
+607
+00:46:37,460 --> 00:46:40,280
+عليها تطبيق، يا جماعة الخير، المعرفة بترتب عليها
+
+608
+00:46:40,280 --> 00:46:46,300
+تطبيق، على خلاف المعلومة، الآن، طب مين اللي بيقدر أنت
+
+609
+00:46:46,300 --> 00:46:50,9
+
+667
+00:51:27,410 --> 00:51:34,770
+عليه action بينفعش أجي أتكلم مع تعوض مثلاً بعمل
+
+668
+00:51:34,770 --> 00:51:38,030
+system عشان يساعد الأطباء في الـ diagnosis وأجي
+
+669
+00:51:38,030 --> 00:51:41,930
+أقولهم هذه 01 ولو عملتلها أس تربيع وكذا ومش عارف
+
+670
+00:51:41,930 --> 00:51:46,070
+..الكلام بيعنّوش، أديله المعلومة عشان هيك هامت الـ
+
+671
+00:51:46,070 --> 00:51:50,060
+presentation، أديله المعلومة بالشكل اللي هو يفهمه
+
+672
+00:51:50,060 --> 00:51:54,460
+لأنه إذا هو أخده يا سامر..يا عارف؟ سامر ولا
+
+673
+00:51:54,460 --> 00:51:59,100
+عارف؟ سامر عارف، لو هو أخد المعلومة بالشكل اللي
+
+674
+00:51:59,100 --> 00:52:03,220
+بيفهمها تمام؟ هيبني عليها action، هتصير الشغل
+
+675
+00:52:03,220 --> 00:52:08,300
+useful بالنسبة له، طبعاً هاي تعريف الـ pattern هي
+
+676
+00:52:08,300 --> 00:52:11,540
+عبارة عن arrangement of repeated parts، هي الشغلات
+
+677
+00:52:11,540 --> 00:52:17,870
+..هو أهم شغلة فيها تكرار والترتيب، لأنه لما بيظهر
+
+678
+00:52:17,870 --> 00:52:21,950
+النسق أو الـ pattern هذا بنفهم كيفية بصير أتكلم
+
+679
+00:52:21,950 --> 00:52:25,190
+عليه better تبع لنسبة معينة محددة يا محمد زي ما
+
+680
+00:52:25,190 --> 00:52:30,450
+أنت قُلت، valid هذا لازم يكون true لما أنا بقادي
+
+681
+00:52:30,450 --> 00:52:33,770
+أطبّق عليه data جديدة، يعني أنت بتقول لي أنا والله
+
+682
+00:52:33,770 --> 00:52:36,950
+okay، أنا في عندي rule أو في عندي algorithm أو في
+
+683
+00:52:36,950 --> 00:52:42,030
+عندي data product ممكن يعمل classification لكذا
+
+684
+00:52:42,030 --> 00:52:47,360
+okay، على الـ all data صحيح، أبتعالي نجرب الـ real
+
+685
+00:52:47,360 --> 00:52:50,460
+data اللي موجودة عندنا حقيقية، جدّيش هو صحيح فيها؟
+
+686
+00:52:50,460 --> 00:52:55,040
+تمام؟ وبناء عليه أنا لازم أقبله novel زي ما قلنا
+
+687
+00:52:55,040 --> 00:52:59,200
+ما حد شافه، actionable لازم يكون عليه شغلة مفهومة
+
+688
+00:52:59,200 --> 00:53:02,760
+وزي ما قلنا سابقاً، understandable لازم يكون مفهوم
+
+689
+00:53:02,760 --> 00:53:06,560
+في البيئة اللي أنا بتكلم فيها، عشان نقدر نأخذ الـ
+
+690
+00:53:06,560 --> 00:53:10,380
+action، ليش إحنا محتاجين الـ data mining؟ الآن
+
+691
+00:53:10,380 --> 00:53:16,890
+البيانات عمّالة بتتضخم بشكل مخيف، مصادر البيانات كل
+
+692
+00:53:16,890 --> 00:53:20,790
+شيء اليوم أصبحت موجودة عندنا وبنقدر نجمعها بكل
+
+693
+00:53:20,790 --> 00:53:27,210
+بساطة، data collection و data availability، البيانات
+
+694
+00:53:27,210 --> 00:53:30,930
+متاحة، بس خد automated data collection tool موجود
+
+695
+00:53:30,930 --> 00:53:34,770
+فيه عندي أدوات في مجال أنا أجمع بيانات بشكل تلقائي
+
+696
+00:53:34,770 --> 00:53:42,070
+أه فيه، أحط sensors، أعمل برنامج يعمل scrapping للـ
+
+697
+00:53:42,070 --> 00:53:46,050
+websites أو الـ social media sites أو الـ networks
+
+698
+00:53:46,050 --> 00:53:50,450
+فأنت بتقدر تجمع البيانات بشكل.. الآن كذلك أعظم
+
+699
+00:53:50,450 --> 00:53:56,410
+المؤسسات الصحية والتعليمية والاجتماعية في البلدان عندها
+
+700
+00:53:56,410 --> 00:54:00,990
+data ضخمة جداً، بتعداد الناس اللي ساكنينها وبالتالي
+
+701
+00:54:00,990 --> 00:54:07,550
+ممكن تستفيد منها، الآن أهم تلت مصادر للناس للبيانات
+
+702
+00:54:07,550 --> 00:54:12,230
+الـ business، التجارة، طبعاً أنا بتكلم عن الاقتصاد
+
+703
+00:54:13,680 --> 00:54:22,520
+الـ Science، العلوم كلها، كانت طبية، اجتماعية، تعليمية
+
+704
+00:54:22,520 --> 00:54:27,960
+زراعية، في كل المجالات في العلوم، الـ society، في
+
+705
+00:54:27,960 --> 00:54:31,420
+الحياة الاجتماعية ما بين الناس، في الأخبار، والـ
+
+706
+00:54:31,420 --> 00:54:33,800
+digital cameras والـ YouTube والقنوات والصفحات
+
+707
+00:54:33,800 --> 00:54:38,160
+فأنت فعلياً عندك هذه أصبحت مصادر بيانات مهمة جداً
+
+708
+00:54:38,160 --> 00:54:46,580
+ممكن تبني عليها decision، فعلياً أصبحنا نغرق في
+
+709
+00:54:46,580 --> 00:54:53,380
+البيانات وبندور جوعاً للمعرفة، الآن بعض الناس أو
+
+710
+00:54:53,380 --> 00:54:55,940
+بعض المفسرين كانوا بيقولوا في القرآن أو في تفسير
+
+711
+00:54:55,940 --> 00:54:59,960
+آية القرآن، "وتلك الأيام نداولها بين الناس"، يعني
+
+712
+00:54:59,960 --> 00:55:07,260
+أحداث التاريخ تتكرر بأشخاص مختلفة، الـ behavior واحد
+
+713
+00:55:07,260 --> 00:55:11,720
+والـ action واحد، يعني ما نشوفش غريب أن نقول
+
+714
+00:55:11,720 --> 00:55:16,660
+والله انتشر فيروس في الصين مثلاً وقضى على 1500 شخص
+
+715
+00:55:16,660 --> 00:55:20,620
+طب ما هو طاعون عمواس قبل مش عارف كام سنة برضه قضى
+
+716
+00:55:20,620 --> 00:55:25,460
+على نفس العدد ويزيد تقريباً، طب شو الاختلاف؟ مُسمّى
+
+717
+00:55:25,460 --> 00:55:28,580
+الـ Virus أو مُسمّى البكتيريا أو مُسبّب المرض؟ حسب
+
+718
+00:55:28,580 --> 00:55:33,140
+العلوم بتختلف الأمور، وبالتالي الـ Historical Data
+
+719
+00:55:33,140 --> 00:55:38,960
+المتراكمة عندي بتحتوي على Knowledge تخدمني في
+
+720
+00:55:38,960 --> 00:55:43,160
+مستقبلي، لأن إذا أتعرفت على الحدث سابقاً بتعرف على
+
+721
+00:55:43,160 --> 00:55:46,980
+كيف أتجنبه أو ممكن أنا أحاول أستفيد من الخبرة
+
+722
+00:55:46,980 --> 00:55:51,560
+السابقة وأتجنبه، وبالتالي بما أن الحاجة أم الاختراع
+
+723
+00:55:52,300 --> 00:55:57,680
+فإحنا فعلياً بحاجة إلى automated analysis للـ
+
+724
+00:55:57,680 --> 00:56:02,400
+historical data أو للـ big data اللي موجودة عندنا
+
+725
+00:56:02,400 --> 00:56:08,020
+حتى نحصل على مطلوبنا من البيانات اللي موجودة عندنا
+
+726
+00:56:08,020 --> 00:56:12,400
+أنا هيك اليوم خلصت المقدمة تبعتي اللي تناولتها الـ
+
+727
+00:56:12,400 --> 00:56:16,720
+syllabus، والمقدمة البسيطة عن الـ data mining، في حد
+
+728
+00:56:16,720 --> 00:56:20,840
+عنده أي سؤال يا شباب؟ في حد عنده أي اعتراض على
+
+729
+00:56:20,840 --> 00:56:22,060
+الخطة؟
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/vNlYsg8cGAY_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/vNlYsg8cGAY_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..56bd1657ab39813c1452da32d6b5f60d0ae0fd46
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/vNlYsg8cGAY_raw.json
@@ -0,0 +1 @@
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"word": " أنه", "probability": 0.5589599609375}, {"start": 731.49, "end": 732.07, "word": " ذرسكوا", "probability": 0.760498046875}, {"start": 732.07, "end": 732.37, "word": " قواعد", "probability": 0.95068359375}, {"start": 732.37, "end": 732.77, "word": " بيانات", "probability": 0.9759521484375}, {"start": 732.77, "end": 733.15, "word": " اتنين", "probability": 0.8916015625}], "temperature": 1.0}, {"id": 28, "seek": 75849, "start": 734.19, "end": 758.49, "text": "هسألكوا شو هو أنواع البيانات تتذكروا المربع تابع البيانات؟ رسمنا رسمة زي هيك اللي هي علاقة بالبيانات قبل ما نتكلم عن الـ NoSQL Database طبعا احنا بناخد المعلومات عشان ننسى صح؟ أعين عليك صار في عندي structured", "tokens": [3224, 3794, 10721, 23275, 14407, 13412, 2407, 31439, 14739, 14407, 3615, 2423, 21292, 7649, 9307, 6055, 2655, 8848, 37983, 14407, 9673, 25513, 3615, 6055, 16758, 3615, 2423, 21292, 7649, 9307, 22807, 12602, 38251, 8315, 12602, 38251, 3660, 30767, 1829, 39896, 4117, 13672, 1829, 39896, 11203, 995, 28671, 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"probability": 0.7197265625}, {"start": 747.81, "end": 748.21, "word": " نتكلم", "probability": 0.983642578125}, {"start": 748.21, "end": 748.49, "word": " عن", "probability": 0.4658203125}, {"start": 748.49, "end": 748.71, "word": " الـ", "probability": 0.4990234375}, {"start": 748.71, "end": 749.01, "word": " NoSQL", "probability": 0.6085205078125}, {"start": 749.01, "end": 749.67, "word": " Database", "probability": 0.7607421875}, {"start": 749.67, "end": 753.49, "word": " طبعا", "probability": 0.934814453125}, {"start": 753.49, "end": 753.61, "word": " احنا", "probability": 0.7777506510416666}, {"start": 753.61, "end": 753.91, "word": " بناخد", "probability": 0.9513346354166666}, {"start": 753.91, "end": 754.33, "word": " المعلومات", "probability": 0.992431640625}, {"start": 754.33, "end": 754.55, "word": " عشان", "probability": 0.9728190104166666}, {"start": 754.55, "end": 754.93, "word": " ننسى", "probability": 0.89990234375}, {"start": 754.93, "end": 755.39, "word": " صح؟", "probability": 0.690673828125}, {"start": 755.39, "end": 756.63, "word": " أعين", "probability": 0.6562906901041666}, {"start": 756.63, "end": 757.15, "word": " عليك", "probability": 0.9638671875}, {"start": 757.15, "end": 757.69, "word": " صار", "probability": 0.791259765625}, {"start": 757.69, "end": 757.81, "word": " في", "probability": 0.93017578125}, {"start": 757.81, "end": 758.05, "word": " عندي", "probability": 0.76806640625}, {"start": 758.05, "end": 758.49, "word": " structured", "probability": 0.515625}], "temperature": 1.0}, {"id": 29, "seek": 78296, "start": 763.36, "end": 782.96, "text": "و unstructured طيب، واش كمان؟ لا يا باشا، خلاص، هدولة هنتهى .. هنتهى semi-structured قولنا الـ No SQL جاية عشان تتعامل مع الـ semi-structured data و لو كانت الـ structure بتتعامل معاها unstructured بتتعامل معاها غير و فيه كمان تصطفين static", "tokens": [2407, 18799, 46847, 23032, 1829, 3555, 12399, 4032, 33599, 9122, 2304, 7649, 22807, 20193, 35186, 4724, 33599, 995, 12399, 16490, 1211, 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767.52, "end": 768.12, "word": " كمان؟", "probability": 0.941162109375}, {"start": 768.12, "end": 769.48, "word": " لا", "probability": 0.400146484375}, {"start": 769.48, "end": 769.66, "word": " يا", "probability": 0.91552734375}, {"start": 769.66, "end": 769.94, "word": " باشا،", "probability": 0.86669921875}, {"start": 769.94, "end": 770.22, "word": " خلاص،", "probability": 0.82281494140625}, {"start": 770.22, "end": 770.4, "word": " هدولة", "probability": 0.666259765625}, {"start": 770.4, "end": 770.76, "word": " هنتهى", "probability": 0.60504150390625}, {"start": 770.76, "end": 770.76, "word": " ..", "probability": 0.1419677734375}, {"start": 770.76, "end": 771.12, "word": " هنتهى", "probability": 0.782958984375}, {"start": 771.12, "end": 771.7, "word": " semi", "probability": 0.152587890625}, {"start": 771.7, "end": 772.18, "word": "-structured", "probability": 0.7903645833333334}, {"start": 772.18, "end": 772.48, "word": " قولنا", "probability": 0.7383626302083334}, {"start": 772.48, "end": 772.7, "word": " الـ", "probability": 0.5430908203125}, {"start": 772.7, "end": 772.8, "word": " No", "probability": 0.497314453125}, {"start": 772.8, "end": 773.22, "word": " SQL", "probability": 0.662109375}, {"start": 773.22, "end": 773.74, "word": " جاية", "probability": 0.896484375}, {"start": 773.74, "end": 774.42, "word": " عشان", "probability": 0.9674479166666666}, {"start": 774.42, "end": 775.02, "word": " تتعامل", "probability": 0.9916015625}, {"start": 775.02, "end": 775.18, "word": " مع", "probability": 0.99560546875}, {"start": 775.18, "end": 775.36, "word": " الـ", "probability": 0.848876953125}, {"start": 775.36, "end": 775.46, "word": " semi", "probability": 0.60498046875}, {"start": 775.46, "end": 775.94, "word": "-structured", "probability": 0.9051106770833334}, {"start": 775.94, "end": 776.26, "word": " data", "probability": 0.6533203125}, {"start": 776.26, "end": 777.04, "word": " و", "probability": 0.8173828125}, {"start": 777.04, "end": 777.14, "word": " لو", "probability": 0.94921875}, {"start": 777.14, "end": 777.42, "word": " كانت", "probability": 0.982421875}, {"start": 777.42, "end": 777.5, "word": " الـ", "probability": 0.84912109375}, {"start": 777.5, "end": 777.76, "word": " structure", "probability": 0.39453125}, {"start": 777.76, "end": 778.18, "word": " بتتعامل", "probability": 0.94140625}, {"start": 778.18, "end": 778.72, "word": " معاها", "probability": 0.92138671875}, {"start": 778.72, "end": 779.32, "word": " unstructured", "probability": 0.87451171875}, {"start": 779.32, "end": 779.76, "word": " بتتعامل", "probability": 0.98134765625}, {"start": 779.76, "end": 780.04, "word": " معاها", "probability": 0.9466145833333334}, {"start": 780.04, "end": 780.64, "word": " غير", "probability": 0.80224609375}, {"start": 780.64, "end": 780.72, "word": " و", "probability": 0.53759765625}, {"start": 780.72, "end": 780.94, "word": " فيه", "probability": 0.58203125}, {"start": 780.94, "end": 781.32, "word": " كمان", 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عشان هيك بالذنبي أنا أميز من ال data format كيف أعملها cleaning؟ شو يعني cleaning؟ الآن حفروا الناس اللي بنقبوا عن الدهب شو طلعوا؟ لا غلطان انت بطلعوا التربة بطلع ال soil", "tokens": [37746, 6027, 2655, 6027, 1829, 41850, 4724, 4587, 7578, 5551, 8592, 2655, 17082, 1211, 4032, 9957, 22807, 15844, 3877, 1412, 8608, 2407, 16606, 25961, 2655, 8546, 34051, 13437, 37893, 6156, 9640, 28671, 9122, 2655, 13546, 20449, 995, 25528, 6225, 8592, 7649, 39896, 4117, 20666, 8848, 1863, 21292, 41850, 5551, 2304, 1829, 11622, 9154, 2423, 1412, 7877, 9122, 33911, 5551, 25957, 1211, 11296, 8924, 22807, 13412, 2407, 37495, 22653, 8924, 22807, 6024, 48506, 11331, 5172, 2288, 14407, 2423, 8315, 3794, 13672, 1829, 44945, 4587, 3555, 14407, 18871, 32748, 3224, 3555, 13412, 2407, 23032, 1211, 3615, 14407, 22807, 20193, 32771, 1211, 9566, 7649, 16472, 2655, 4724, 9566, 1211, 3615, 14407, 16712, 25513, 3660, 4724, 9566, 1211, 3615, 2423, 6704], "avg_logprob": -0.16578389211731442, "compression_ratio": 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تبعتنا كانت تالي providing fundamental understanding يزودنا بالفهم الأساسي لمتطلبات ال data mining عشان أقدر أستخرج المعرفة المخفية من", "tokens": [3615, 8592, 7649, 5551, 28543, 2288, 5551, 30544, 28242, 9819, 31439, 5296, 33456, 8717, 2655, 4117, 19528, 15844, 6156, 2288, 3615, 36764, 24401, 6156, 47432, 6156, 2304, 43020, 11933, 5016, 8315, 4724, 5016, 26108, 3660, 36145, 8315, 8717, 25957, 1211, 25801, 9154, 5551, 3224, 28259, 5172, 9673, 3794, 995, 4587, 6055, 3555, 34268, 8315, 39182, 19446, 1975, 2655, 4117, 19528, 8315, 15844, 34051, 9381, 33911, 9673, 3794, 995, 4587, 5551, 3224, 28259, 5172, 9673, 3794, 995, 4587, 6055, 3555, 34268, 8315, 25961, 2655, 6055, 6027, 1829, 6530, 8088, 3701, 7251, 11622, 23328, 8315, 20666, 5172, 16095, 16247, 3794, 32277, 1829, 32767, 2655, 9566, 46152, 9307, 2423, 1412, 15512, 6225, 8592, 7649, 5551, 28543, 2288, 5551, 14851, 34740, 7435, 9673, 3615, 28480, 3660, 9673, 9778, 5172, 10632, 9154], "avg_logprob": -0.12286376638803631, 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non-trivial مش تقليدي مش تقليدي يعني فيش شغلة جديدة", "tokens": [8592, 1829, 4587, 12399, 50113, 13546, 12399, 3714, 19913, 3555, 2407, 9566, 22807, 28242, 2423, 2115, 8032, 47302, 39894, 9381, 5172, 4724, 9307, 7435, 40294, 36764, 24401, 36145, 3224, 41850, 2423, 3601, 13672, 1829, 41850, 4724, 16254, 5551, 3215, 13063, 25894, 11296, 5296, 31377, 2304, 7251, 30544, 5296, 11296, 6055, 10721, 12984, 13546, 6024, 48506, 45030, 28480, 23275, 3714, 9381, 9566, 1211, 5016, 1880, 2107, 12, 83, 470, 22640, 37893, 6055, 4587, 20292, 16254, 37893, 6055, 4587, 20292, 16254, 37495, 22653, 8978, 8592, 13412, 17082, 37977, 10874, 16254, 41891], "avg_logprob": -0.18194444527228673, "compression_ratio": 1.5023255813953489, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 2913.37, "end": 2914.31, "word": "شيق،", "probability": 0.75347900390625}, {"start": 2914.31, "end": 2915.09, "word": " مثير،", "probability": 0.9365234375}, {"start": 2915.09, "end": 2916.11, "word": " مظبوط؟", 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1.8157894736842106, "no_speech_prob": 2.384185791015625e-07, "words": [{"start": 3323.28, "end": 3323.52, "word": "طب", "probability": 0.805419921875}, {"start": 3323.52, "end": 3323.88, "word": " شو", "probability": 0.7083740234375}, {"start": 3323.88, "end": 3325.02, "word": " الاختلاف؟", "probability": 0.8815104166666666}, {"start": 3325.02, "end": 3325.46, "word": " مُسمّى", "probability": 0.78427734375}, {"start": 3325.46, "end": 3325.6, "word": " الـ", "probability": 0.7861328125}, {"start": 3325.6, "end": 3325.84, "word": " Virus", "probability": 0.331298828125}, {"start": 3325.84, "end": 3326.02, "word": " أو", "probability": 0.9150390625}, {"start": 3326.02, "end": 3326.38, "word": " مُسمّى", "probability": 0.986328125}, {"start": 3326.38, "end": 3326.82, "word": " البكتيريا", "probability": 0.8326171875}, {"start": 3326.82, "end": 3326.96, "word": " أو", "probability": 0.96923828125}, {"start": 3326.96, "end": 3327.4, "word": " مُسبّب", "probability": 0.87705078125}, {"start": 3327.4, "end": 3328.08, "word": " المرض؟", "probability": 0.91162109375}, {"start": 3328.08, "end": 3328.58, "word": " حسب", "probability": 0.951904296875}, {"start": 3328.58, "end": 3328.94, "word": " العلوم", "probability": 0.86865234375}, {"start": 3328.94, "end": 3329.4, "word": " بتختلف", "probability": 0.8404947916666666}, {"start": 3329.4, "end": 3329.84, "word": " الأمور", "probability": 0.9845377604166666}, {"start": 3329.84, "end": 3330.98, "word": " وبالتالي", "probability": 0.909375}, {"start": 3330.98, "end": 3332.18, "word": " الـ", "probability": 0.72509765625}, {"start": 3332.18, "end": 3332.62, "word": " Historical", "probability": 0.62109375}, {"start": 3332.62, "end": 3333.14, "word": " Data", "probability": 0.6064453125}, {"start": 3333.14, "end": 3334.02, "word": " المتراكمة", "probability": 0.9166015625}, {"start": 3334.02, "end": 3334.36, "word": " عندي", "probability": 0.710693359375}, {"start": 3334.36, "end": 3335.74, "word": " بتحتوي", "probability": 0.9114583333333334}, {"start": 3335.74, "end": 3336.14, "word": " على", "probability": 0.93994140625}, {"start": 3336.14, "end": 3336.66, "word": " Knowledge", "probability": 0.62451171875}, {"start": 3336.66, "end": 3338.06, "word": " تخدمني", "probability": 0.946533203125}, {"start": 3338.06, "end": 3338.96, "word": " في", "probability": 0.9794921875}, {"start": 3338.96, "end": 3339.58, "word": " مستقبلي", "probability": 0.954296875}, {"start": 3339.58, "end": 3340.36, "word": " لأن", "probability": 0.828369140625}, {"start": 3340.36, "end": 3340.52, "word": " إذا", "probability": 0.810791015625}, {"start": 3340.52, "end": 3341.04, "word": " أتعرفت", "probability": 0.8744140625}, {"start": 3341.04, "end": 3341.18, "word": " على", "probability": 0.9541015625}, {"start": 3341.18, "end": 3341.5, "word": " الحدث", "probability": 0.98779296875}, {"start": 3341.5, "end": 3342.12, "word": " سابقًا", "probability": 0.85625}, {"start": 3342.12, "end": 3342.92, "word": " بتعرف", "probability": 0.7826334635416666}, {"start": 3342.92, "end": 3343.16, "word": " على", "probability": 0.91015625}, {"start": 3343.16, "end": 3344.2, "word": " كيف", "probability": 0.9599609375}, {"start": 3344.2, "end": 3344.74, "word": " أتجنبه", "probability": 0.9012044270833334}, {"start": 3344.74, "end": 3344.88, "word": " أو", "probability": 0.8828125}, {"start": 3344.88, "end": 3345.2, "word": " ممكن", "probability": 0.9619140625}, {"start": 3345.2, "end": 3345.38, "word": " أنا", "probability": 0.486572265625}, {"start": 3345.38, "end": 3345.96, "word": " أحاول", "probability": 0.989501953125}, {"start": 3345.96, "end": 3346.52, "word": " أستفيد", "probability": 0.9775390625}, {"start": 3346.52, "end": 3346.64, "word": " من", "probability": 0.98974609375}, {"start": 3346.64, "end": 3346.98, "word": " الخبرة", "probability": 0.9685872395833334}, {"start": 3346.98, "end": 3347.54, "word": " السابقة", "probability": 0.9920247395833334}, {"start": 3347.54, "end": 3348.6, "word": " وأتجنبه", "probability": 0.9090983072916666}, {"start": 3348.6, "end": 3349.64, "word": " وبالتالي", "probability": 0.94775390625}, {"start": 3349.64, "end": 3349.92, "word": " بما", "probability": 0.956298828125}, {"start": 3349.92, "end": 3350.08, "word": " أن", "probability": 0.54052734375}, {"start": 3350.08, "end": 3350.6, "word": " الحاجة", "probability": 0.9832356770833334}, {"start": 3350.6, "end": 3350.8, "word": " أم", "probability": 0.930419921875}, {"start": 3350.8, "end": 3351.56, "word": " الإختراع", "probability": 0.85205078125}], "temperature": 1.0}, {"id": 127, "seek": 338206, "start": 3352.3, "end": 3382.06, "text": "فاحنا فعلياً بحاجة إلى automated analysis للـ historical data أو لل big data اللي موجودة عندنا حتى نحصل على مطلوبنا من البيانات اللي موجودة عندنا أنا هيك اليوم خلصت المقدمة تبعتي اللي تناولتها ال syllabus والمقدمة البسيطة عن ال data mining في حد عنده أي سؤال يا شباب؟ في حد عنده أي اعتراض على الخطة؟", "tokens": [5172, 39319, 8315, 6156, 3615, 20292, 995, 14111, 4724, 5016, 26108, 3660, 30731, 18473, 5215, 24976, 39184, 8584, 1412, 34051, 24976, 955, 1412, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 8315, 11331, 49975, 8717, 5016, 36520, 15844, 3714, 9566, 1211, 37746, 8315, 9154, 2423, 21292, 7649, 9307, 13672, 1829, 3714, 29245, 23328, 3660, 43242, 8315, 41850, 39896, 4117, 45595, 20498, 16490, 1211, 9381, 2655, 9673, 28543, 46007, 6055, 3555, 3615, 31371, 13672, 1829, 6055, 8315, 12610, 2655, 11296, 2423, 48077, 4032, 45340, 28543, 46007, 29739, 3794, 1829, 9566, 3660, 18871, 2423, 1412, 15512, 8978, 11331, 3215, 43242, 3224, 36632, 8608, 33604, 6027, 35186, 13412, 3555, 16758, 22807, 8978, 11331, 3215, 43242, 3224, 36632, 1975, 34268, 2288, 46958, 15844, 33962, 9566, 3660, 22807], "avg_logprob": -0.15345527898005354, "compression_ratio": 1.8007380073800738, "no_speech_prob": 1.1920928955078125e-07, "words": [{"start": 3352.3, "end": 3352.78, "word": "فاحنا", "probability": 0.8917643229166666}, {"start": 3352.78, "end": 3354.16, "word": " فعلياً", "probability": 0.7880859375}, {"start": 3354.16, "end": 3355.32, "word": " بحاجة", "probability": 0.9947509765625}, {"start": 3355.32, "end": 3355.54, "word": " إلى", "probability": 0.94287109375}, {"start": 3355.54, "end": 3356.0, "word": " automated", "probability": 0.7919921875}, {"start": 3356.0, "end": 3356.72, "word": " analysis", "probability": 0.787109375}, {"start": 3356.72, "end": 3357.68, "word": " للـ", "probability": 0.52496337890625}, {"start": 3357.68, "end": 3358.08, "word": " historical", "probability": 0.297119140625}, {"start": 3358.08, "end": 3358.62, "word": " data", "probability": 0.96875}, {"start": 3358.62, "end": 3358.98, "word": " أو", "probability": 0.94970703125}, {"start": 3358.98, "end": 3359.16, "word": " لل", "probability": 0.9287109375}, {"start": 3359.16, "end": 3359.44, "word": " big", "probability": 0.402099609375}, {"start": 3359.44, "end": 3359.96, "word": " data", "probability": 0.9755859375}, {"start": 3359.96, "end": 3360.56, "word": " اللي", "probability": 0.902587890625}, {"start": 3360.56, "end": 3361.28, "word": " موجودة", "probability": 0.989990234375}, {"start": 3361.28, "end": 3362.4, "word": " عندنا", "probability": 0.85595703125}, {"start": 3362.4, "end": 3362.96, "word": " حتى", "probability": 0.906982421875}, {"start": 3362.96, "end": 3363.36, "word": " نحصل", "probability": 0.99169921875}, {"start": 3363.36, "end": 3363.66, "word": " على", "probability": 0.91455078125}, {"start": 3363.66, "end": 3365.56, "word": " مطلوبنا", "probability": 0.95859375}, {"start": 3365.56, "end": 3365.78, "word": " من", "probability": 0.99267578125}, {"start": 3365.78, "end": 3366.38, "word": " البيانات", "probability": 0.9385986328125}, {"start": 3366.38, "end": 3366.64, "word": " اللي", "probability": 0.9833984375}, {"start": 3366.64, "end": 3367.2, "word": " موجودة", "probability": 0.990478515625}, {"start": 3367.2, "end": 3368.02, "word": " عندنا", "probability": 0.97314453125}, {"start": 3368.02, "end": 3368.88, "word": " أنا", "probability": 0.62646484375}, {"start": 3368.88, "end": 3369.28, "word": " هيك", "probability": 0.8857421875}, {"start": 3369.28, "end": 3369.96, "word": " اليوم", "probability": 0.758056640625}, {"start": 3369.96, "end": 3370.34, "word": " خلصت", "probability": 0.99267578125}, {"start": 3370.34, "end": 3370.8, "word": " المقدمة", "probability": 0.9796549479166666}, {"start": 3370.8, "end": 3371.34, "word": " تبعتي", "probability": 0.8988037109375}, {"start": 3371.34, "end": 3371.64, "word": " اللي", "probability": 0.876708984375}, {"start": 3371.64, "end": 3372.3, "word": " تناولتها", "probability": 0.52607421875}, {"start": 3372.3, "end": 3372.4, "word": " ال", "probability": 0.61962890625}, {"start": 3372.4, "end": 3372.7, "word": " syllabus", "probability": 0.9833984375}, {"start": 3372.7, "end": 3373.82, "word": " والمقدمة", "probability": 0.8106689453125}, {"start": 3373.82, "end": 3374.28, "word": " البسيطة", "probability": 0.956640625}, {"start": 3374.28, "end": 3374.42, "word": " عن", "probability": 0.943359375}, {"start": 3374.42, "end": 3374.5, "word": " ال", "probability": 0.95654296875}, {"start": 3374.5, "end": 3374.62, "word": " data", "probability": 0.87255859375}, {"start": 3374.62, "end": 3375.02, "word": " mining", "probability": 0.9794921875}, {"start": 3375.02, "end": 3376.52, "word": " في", "probability": 0.494873046875}, {"start": 3376.52, "end": 3376.72, "word": " حد", "probability": 0.90673828125}, {"start": 3376.72, "end": 3376.92, "word": " عنده", "probability": 0.99365234375}, {"start": 3376.92, "end": 3377.0, "word": " أي", "probability": 0.6865234375}, {"start": 3377.0, "end": 3377.18, "word": " سؤال", "probability": 0.9952799479166666}, {"start": 3377.18, "end": 3377.32, "word": " يا", "probability": 0.5634765625}, {"start": 3377.32, "end": 3378.66, "word": " شباب؟", "probability": 0.9573974609375}, {"start": 3378.66, "end": 3378.98, "word": " في", "probability": 0.69482421875}, {"start": 3378.98, "end": 3379.24, "word": " حد", "probability": 0.989990234375}, {"start": 3379.24, "end": 3379.5, "word": " عنده", "probability": 0.990478515625}, {"start": 3379.5, "end": 3379.66, "word": " أي", "probability": 0.8291015625}, {"start": 3379.66, "end": 3380.36, "word": " اعتراض", "probability": 0.96044921875}, {"start": 3380.36, "end": 3380.84, "word": " على", "probability": 0.89892578125}, {"start": 3380.84, "end": 3382.06, "word": " الخطة؟", "probability": 0.9794921875}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 3382.0793125, "duration_after_vad": 3231.0199999999854}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/vNlYsg8cGAY_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/vNlYsg8cGAY_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..465ccb6e3e5d3b08145b770532e30ca7041f419f
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/vNlYsg8cGAY_raw.srt
@@ -0,0 +1,2924 @@
+1
+00:00:07,760 --> 00:00:09,860
+بسم الله و الحمد لله و الصلاة والسلام على رسول
+
+2
+00:00:09,860 --> 00:00:13,720
+الله أهلا و أهلا بالشباب الطيبين و أتمنى لكم إن
+
+3
+00:00:13,720 --> 00:00:18,380
+شاء الله فصل جديد ملءه النشاط و المعرفة و ختمه
+
+4
+00:00:18,380 --> 00:00:21,400
+الدرجات العالية إن شاء الله تعالى اليوم إن شاء
+
+5
+00:00:21,400 --> 00:00:25,720
+الله هنبدأ نتكلم أو هنعمل مقدمة نتكلم .. نتواصل ..
+
+6
+00:00:25,720 --> 00:00:30,180
+نتناقش فيها و نعرض فيها syllabus أو وصف مساق تنقيب
+
+7
+00:00:30,180 --> 00:00:34,400
+البياناتالـ .. لكن كالعادة يعني اللي بنحب ال
+
+8
+00:00:34,400 --> 00:00:38,380
+discussion و بنحب نتكلم معاكم بشكل كويس لو أنا
+
+9
+00:00:38,380 --> 00:00:44,380
+سألتك أو سألت أي واحد فيكوا، شو يعني تنقيب بيانات؟
+
+10
+00:00:44,380 --> 00:00:48,660
+طيب، حد فيكو كلف نفسه يطلع على وصف المساق اللي
+
+11
+00:00:48,660 --> 00:00:53,220
+موجود على الصفحة قبل ما يسجل المساق؟ أه محمد؟ اللي
+
+12
+00:00:53,220 --> 00:00:57,020
+هي filtering the big data filtering the big data
+
+13
+00:00:57,020 --> 00:00:59,660
+شو يعني معاه؟ شو يعني بالعربي filter؟
+
+14
+00:01:02,490 --> 00:01:08,190
+filter معناته أنا بتتكلم على تصفية ترتيب مصبوط لأ
+
+15
+00:01:08,190 --> 00:01:11,930
+هي ال data mining أو تنقيب البيانات شغل أكبر من
+
+16
+00:01:11,930 --> 00:01:18,630
+هيك آه الشباب حاجة
+
+17
+00:01:18,630 --> 00:01:24,970
+صغيرة و أفصل البيانات اللي فيها طيب
+
+18
+00:01:24,970 --> 00:01:30,710
+الآن أجيب pattern أطلع شغلة غامضة الآن يعني بديتها
+
+19
+00:01:30,710 --> 00:01:32,110
+.. آه رمي
+
+20
+00:01:35,260 --> 00:01:41,100
+أه الوصول إلى معلومات مفيدة من معلومات ما لها غير
+
+21
+00:01:41,100 --> 00:01:45,880
+مرتبة غير مرتبة خلّيني أقول طيب الآن لو أنا جيت
+
+22
+00:01:45,880 --> 00:01:51,440
+سألتك تنقيب
+
+23
+00:01:51,440 --> 00:01:58,400
+بالعربي mining شو
+
+24
+00:01:58,400 --> 00:02:03,080
+يعني كلمة تنقيب معناته بالعربي استخراج استخراج
+
+25
+00:02:03,080 --> 00:02:07,090
+أيش؟يعني ابن فعلا راح يقول و الله بدنا بنقب عن
+
+26
+00:02:07,090 --> 00:02:13,610
+الشواكل مثلا؟ لا .. لا .. لا استخراج مادة من مادة
+
+27
+00:02:13,610 --> 00:02:22,230
+خام استخراج أو بحث أثبت؟
+
+28
+00:02:22,230 --> 00:02:25,330
+مادة من مادة خام طب ممكن تقولي إيش طبيعة المادة هي
+
+29
+00:02:25,330 --> 00:02:25,870
+يا باشا؟
+
+30
+00:02:29,140 --> 00:02:31,680
+التنقيب الأن سيبني من ال data ال data عن الجهة
+
+31
+00:02:31,680 --> 00:02:39,420
+خلينا الآن نتكلم على التنقيب أيوة أيوة البحث هذا
+
+32
+00:02:39,420 --> 00:02:44,260
+أو التنقيب هذه كمسمة أو كمصطلح مرتبط باستخراج أو
+
+33
+00:02:44,260 --> 00:02:48,940
+البحث عن أشياء
+
+34
+00:02:48,940 --> 00:02:52,080
+ثمينة
+
+35
+00:02:52,080 --> 00:02:55,120
+نادرة
+
+36
+00:02:55,120 --> 00:02:57,460
+الوجود
+
+37
+00:02:58,280 --> 00:03:01,180
+يعني الآن مافعش أروح أقول و الله أنا بده نقب على
+
+38
+00:03:01,180 --> 00:03:06,280
+جلم أرصاص احنا بروح باشتر جلم أرصاص أو بستلفه لأن
+
+39
+00:03:06,280 --> 00:03:09,060
+حد بتتفرج في ال national geographic و بتتفرج على
+
+40
+00:03:09,060 --> 00:03:13,460
+برامج التنقيب عليش
+
+41
+00:03:13,460 --> 00:03:22,000
+بنقبه كانوا؟ اه يا هاشم عن الذهب، فحم، petrole،
+
+42
+00:03:22,000 --> 00:03:29,050
+الحفير، أحجار كريمة، ولاحظ كلها .. كلهاغالية
+
+43
+00:03:29,050 --> 00:03:35,830
+ونادرة الوجود ومهمة في عالمنا اليوم طيب كلمة تنقيب
+
+44
+00:03:35,830 --> 00:03:44,130
+ارتبطت بمخاطر زائد
+
+45
+00:03:44,130 --> 00:03:46,210
+تكلفة ولا شو رايكوا؟
+
+46
+00:03:49,310 --> 00:03:51,410
+الناس اللي بتعمل تنقيب على الدهب وتنقيب على
+
+47
+00:03:51,410 --> 00:03:54,810
+البترول هاي جداش في عندهم risk عالية لإنهم
+
+48
+00:03:54,810 --> 00:03:58,270
+بيستخدموا مكان تقيل بيضطروا بيحفروا عميقا في الأرض
+
+49
+00:03:58,270 --> 00:04:02,010
+أحيانا بينزلوا أحيانا في داخل الحفرة تبعتهم وممكن
+
+50
+00:04:02,010 --> 00:04:06,810
+تنهار عليهم هذه
+
+51
+00:04:06,810 --> 00:04:10,510
+مخاطر على مستوى الجسد مخاطر تانية مرتبطة بالتنقيب
+
+52
+00:04:10,510 --> 00:04:16,710
+إنه ممكن بعد جهد كبير تطلع صفر اليدين تمام؟
+
+53
+00:04:18,660 --> 00:04:22,720
+وتكلفة عالية، مكان وفمكانه تماما زى الصياد اللى
+
+54
+00:04:22,720 --> 00:04:28,940
+بروح بحاول يصيد بس الصياد بيستنى السمك يجيه،
+
+55
+00:04:28,940 --> 00:04:33,880
+مظبوط؟ بينما المناقب هو اللى بدور هو اللى ببحش
+
+56
+00:04:33,880 --> 00:04:38,440
+وبدور عن العناصر اللى موجودة فاليوم احنا هنتكلم
+
+57
+00:04:38,440 --> 00:04:44,140
+تنقيب البيانات تمام؟
+
+58
+00:04:54,970 --> 00:04:59,450
+data شو يعني بيانات؟
+
+59
+00:04:59,450 --> 00:05:03,010
+بيانات،
+
+60
+00:05:03,010 --> 00:05:06,970
+إيش يعني بيانات؟
+
+61
+00:05:06,970 --> 00:05:11,790
+طيب إيش الفرق بين ال data و ال information؟
+
+62
+00:05:15,730 --> 00:05:19,930
+Data تمت معالجة، معناته البيانات هي البيانات الخام
+
+63
+00:05:19,930 --> 00:05:23,070
+وبدأ أرجع للكلام اللي قلت لزميلك استخراج مادة من
+
+64
+00:05:23,070 --> 00:05:28,330
+مادة خام فانت فعليا عندك بيانات طلاب الجامعات في
+
+65
+00:05:28,330 --> 00:05:35,750
+فلسطين من 2000 ل2020 So what؟ أنا جد موجودة أكتر
+
+66
+00:05:35,750 --> 00:05:40,270
+من database، دمجناهم مع بعض جمعنا البيانات هذه،
+
+67
+00:05:40,270 --> 00:05:45,260
+إيش بقدر أستفيد منهم أنا؟دورك أنت كمنقب تبدأ تروح
+
+68
+00:05:45,260 --> 00:05:50,500
+تدورلنا على معرفة جديدة نقدر نستفيد منها في حياتنا
+
+69
+00:05:50,500 --> 00:05:54,860
+مثل .. نسبة الذكور للإناث أه .. لاحظ من .. أنا
+
+70
+00:05:54,860 --> 00:05:56,560
+خلّيني بص .. أنا بضايق .. بعدين بجاوبك يعني على
+
+71
+00:05:56,560 --> 00:05:59,040
+الكلام اللي أنا بحكي فيه الآن زميل اللي بقول مثل
+
+72
+00:05:59,040 --> 00:06:03,160
+نسبة الذكور للإناث هذا الكلام غلط، هذا أحصى ألف
+
+73
+00:06:03,160 --> 00:06:08,140
+بأحصى بتجيبها، مش ضرورة تتعلم تنقيب بياناتوهنشوف
+
+74
+00:06:08,140 --> 00:06:11,060
+كمان شوية في التعريف تبع تنقيب البيانات أنه أنا
+
+75
+00:06:11,060 --> 00:06:17,300
+فعليا بحاجة إلى استخدام طرق غير تقليدية وهتشوف أنه
+
+76
+00:06:17,300 --> 00:06:19,960
+تنقيب البيانات باستخدام الإحصاء و باستخدام ال
+
+77
+00:06:19,960 --> 00:06:22,420
+database و باستخدام البرمجة و باستخدام الشبكات و
+
+78
+00:06:22,420 --> 00:06:25,760
+باستخدام معظم العلوم من أجل الوصول للهدف المطلوب
+
+79
+00:06:25,760 --> 00:06:29,480
+لأن هو بنقمش في معلومات
+
+80
+00:06:32,110 --> 00:06:36,270
+بنقب في ال data عشان يطلع ايوة فبالتالي الان هذه
+
+81
+00:06:36,270 --> 00:06:40,510
+بيانات مش معلومات عشان هي انا بسألك ايش هي
+
+82
+00:06:40,510 --> 00:06:45,510
+البيانات شوف
+
+83
+00:06:45,510 --> 00:06:51,850
+عادة .. مثلا .. الان انت بتستخرجي المعلومة تمام؟
+
+84
+00:06:51,850 --> 00:07:00,630
+الان بالعربي عادة احنا بنقول تنقيب عن الذهب ماقولش
+
+85
+00:07:00,630 --> 00:07:07,380
+بنقب في الذهبتنقيب عن البترول ومكان التنقيب في
+
+86
+00:07:07,380 --> 00:07:12,600
+حياتنا كبشر مكان واحد باطن الأرض عشانك اختصر كل
+
+87
+00:07:12,600 --> 00:07:18,300
+المسميات تمام؟ كما بقولك تنقيب عن بينما هان أنواع
+
+88
+00:07:18,300 --> 00:07:22,980
+البيانات اللي عندي مختلفة و ال task تبعتي اللي انا
+
+89
+00:07:22,980 --> 00:07:27,700
+باطلعلهامختلفة ال data مصدر البيانات لما تكون
+
+90
+00:07:27,700 --> 00:07:31,500
+بيانات الطلاب الجامعيين على مستوى فلسطين غير لما
+
+91
+00:07:31,500 --> 00:07:34,980
+تكون مصدر البيانات بيانات وإما الإرشيف الصحي
+
+92
+00:07:34,980 --> 00:07:39,500
+للمواطنين الفلسطينيين بيصير في عندي هن بتدور عشغلة
+
+93
+00:07:39,500 --> 00:07:46,120
+مختلفة عنها ومصدرين مختلفين فبصير تنقيب البيانات
+
+94
+00:07:46,120 --> 00:07:51,300
+مجلكاش تنقيب عن البيانات فانا بنقب في ال .. بنقب
+
+95
+00:07:51,300 --> 00:07:56,430
+البيانات قاعد عشان .. بهدف أني أطلع منها شغلةممكن
+
+96
+00:07:56,430 --> 00:07:58,950
+تكون Formation بس هي فعليا أعلى من ال information
+
+97
+00:07:58,950 --> 00:08:03,470
+احنا متكلم على knowledge، معرفة وحنشوف الفرق ..
+
+98
+00:08:03,470 --> 00:08:06,370
+الفرق بين ال data و ال information و ال knowledge
+
+99
+00:08:06,370 --> 00:08:12,270
+و الحكمة أو ال wisdom لاحقا وبالتالي أنا الآن هدفي
+
+100
+00:08:12,270 --> 00:08:18,670
+ان اتعلم كيف انقب البيانات في البيانات مش عن
+
+101
+00:08:18,670 --> 00:08:23,370
+البياناتالآن data mining تنقيب مقصود فيها في
+
+102
+00:08:23,370 --> 00:08:27,470
+البيانات تنقيب البيانات نفسها من أجل استخراج معرفة
+
+103
+00:08:27,470 --> 00:08:34,870
+طيب، تتوقع العملية تكون سهلة ولا صعبة؟ حسب ال data
+
+104
+00:08:34,870 --> 00:08:40,810
+لكن عادة ال data mining هي task ليس task تقليدية
+
+105
+00:08:40,810 --> 00:08:44,810
+ممكن تقدر تكتب برنامج، و هذا يعقد إن كتبك تكون
+
+106
+00:08:44,810 --> 00:08:50,120
+developer كويسيقتضي منك إنك تعمل import و export
+
+107
+00:08:50,120 --> 00:08:53,920
+بعض الأحيان لل database وكيف تعمل integration
+
+108
+00:08:53,920 --> 00:08:58,700
+وبلزمك تعرف إن ال database كويس بلزمك تتعرف على ال
+
+109
+00:08:58,700 --> 00:09:02,660
+machine learning algorithm عشان تسخرها في عملية
+
+110
+00:09:02,660 --> 00:09:05,660
+التنقل، يعني بنجوسين بدك أدوات، بدك tools اللي
+
+111
+00:09:05,660 --> 00:09:08,600
+بدور على الدهب، عنده حفار و عنده جرافة و عنده
+
+112
+00:09:08,600 --> 00:09:14,770
+المصفاية و عنده الميه إلى آخره، هذه هي أدواتهوانت
+
+113
+00:09:14,770 --> 00:09:17,390
+لازم يكون لك أدواتك اللي بقى بتستخدمها في عملية
+
+114
+00:09:17,390 --> 00:09:21,670
+التنقيب طيب لما بنتكلم على معلومات المساق تبعنا
+
+115
+00:09:21,670 --> 00:09:29,250
+أهم شغلة بيهمك فيها إيميلي لأي استفسار طبعا كلكم
+
+116
+00:09:29,250 --> 00:09:34,030
+بتعرفوا ساعات المكتبية للفصل هذا من السبت للأربعة
+
+117
+00:09:34,760 --> 00:09:37,640
+من الـ 11 إلى الواحدة أنا موجود في المكتب طبعا إلا
+
+118
+00:09:37,640 --> 00:09:40,300
+لو صار في اجتماع طارق أنا مابقدرش أتحكم فيه يعني
+
+119
+00:09:40,300 --> 00:09:43,340
+بس غالبا ان شاء الله أكون موجود و مكتبي في الطابق
+
+120
+00:09:43,340 --> 00:09:49,100
+التالت في مبنى تكنولوجيا المعلومات مقعد لقائنا 9 و
+
+121
+00:09:49,100 --> 00:09:54,960
+نص إلى ال 11 كان في I 116 و جبناه القاعة المصورة
+
+122
+00:09:54,960 --> 00:10:02,270
+هذه وصف المسابق تبعناالمساق هذا حاولنا نعيد تصميمه
+
+123
+00:10:02,270 --> 00:10:08,730
+أو صممناه بحيث إنه يزود الطالب بمقدمة عن علم
+
+124
+00:10:08,730 --> 00:10:15,890
+البيانات ويزوده بخبرة عملية hand experience في
+
+125
+00:10:15,890 --> 00:10:21,630
+التعامل مع كل مراحل مشروع أو مع شريع قواعد data
+
+126
+00:10:21,630 --> 00:10:26,770
+mining تنقيب البيانات الآن hand experience تجربة
+
+127
+00:10:26,770 --> 00:10:32,760
+عمليةwith all faces لما أتكلم with all faces
+
+128
+00:10:32,760 --> 00:10:38,000
+معناته أنا جاعت بأتكلم عن إيش؟ عن مشروع بمر في
+
+129
+00:10:38,000 --> 00:10:41,580
+مراحل مش مرحلة واحدة الآن في ال database project
+
+130
+00:10:41,580 --> 00:10:44,760
+لو أنا بدأ قارنها في ال database بتعمل analysis
+
+131
+00:10:44,760 --> 00:10:50,560
+بتعمل design بتعمل implementation بصبت؟ ايش دول
+
+132
+00:10:50,560 --> 00:10:51,200
+بعد هيك؟
+
+133
+00:10:53,820 --> 00:10:57,780
+خلاص بدي أعمل test عشان أتأكد أن كل الأمور تمام
+
+134
+00:10:57,780 --> 00:11:00,560
+وبعد ذلك لو أنا محتاج maintenance بكلمة على أربع
+
+135
+00:11:00,560 --> 00:11:04,720
+مراحل اليوم هتشوف أنه أنا في عنيا في اندي 6 من 7
+
+136
+00:11:04,720 --> 00:11:10,580
+على 8 مراحل وكل واحدة بدها جهد ومعرفة مختلفة مني
+
+137
+00:11:10,580 --> 00:11:16,500
+عشان أقدر أنجزها طبعا هذا كله باعتماد على ال real
+
+138
+00:11:16,500 --> 00:11:20,780
+data بينفعش أستخدم fake data أو fabricated data و
+
+139
+00:11:20,780 --> 00:11:23,790
+أشتغل عليهاطب دلوقت بدأ اجيب الـ real data الـ
+
+140
+00:11:23,790 --> 00:11:26,610
+real data متاحة في مواقع كتير عالميا بتزودني بـ
+
+141
+00:11:26,610 --> 00:11:31,110
+real data موجودة historical data في مجالات مختلفة
+
+142
+00:11:31,110 --> 00:11:36,450
+بدءا من التمييز بين أنواع الحشرات ومواصفاتها لحد
+
+143
+00:11:36,450 --> 00:11:41,730
+تصنيف الصور الفضاء والشغلات هذه فانت وين مهتم ممكن
+
+144
+00:11:41,730 --> 00:11:45,770
+تلاقي بيانات بتخدمكوحزودكوا ان شاء الله من خلال ال
+
+145
+00:11:45,770 --> 00:11:49,210
+model بمجموعة من الرابط ممكن المحاضرة الجاية أعرض
+
+146
+00:11:49,210 --> 00:11:53,430
+الرابط عليكوا نشوف بعض المواقع بحيث ان مطلوب منك
+
+147
+00:11:53,430 --> 00:11:58,410
+فعليا اتحدد data set أنت و الفريق تبعك عشان تشتغل
+
+148
+00:11:58,410 --> 00:12:04,030
+عليها لحد نهاية الفصيلة الآن هذا المساق هيغطي
+
+149
+00:12:04,030 --> 00:12:11,070
+مواضيع بدءا من ال data format أنواع البيانات طبعا
+
+150
+00:12:11,070 --> 00:12:15,850
+بما أنه ذرسكوا قواعد بيانات اتنينهسألكوا شو هو
+
+151
+00:12:15,850 --> 00:12:22,190
+أنواع البيانات تتذكروا المربع تابع البيانات؟
+
+152
+00:12:22,190 --> 00:12:27,810
+رسمنا رسمة زي هيك اللي هي علاقة بالبيانات قبل ما
+
+153
+00:12:27,810 --> 00:12:33,490
+نتكلم عن الـ NoSQL Database طبعا
+
+154
+00:12:33,490 --> 00:12:37,690
+احنا بناخد المعلومات عشان ننسى صح؟ أعين عليك صار
+
+155
+00:12:37,690 --> 00:12:38,490
+في عندي structured
+
+156
+00:12:43,360 --> 00:12:50,220
+و unstructured طيب، واش كمان؟ لا يا باشا، خلاص،
+
+157
+00:12:50,220 --> 00:12:52,800
+هدولة هنتهى .. هنتهى semi-structured قولنا الـ No
+
+158
+00:12:52,800 --> 00:12:57,040
+SQL جاية عشان تتعامل مع الـ semi-structured data و
+
+159
+00:12:57,040 --> 00:12:59,320
+لو كانت الـ structure بتتعامل معاها unstructured
+
+160
+00:12:59,320 --> 00:13:02,960
+بتتعامل معاها غير و فيه كمان تصطفين static
+
+161
+00:13:11,330 --> 00:13:16,070
+و Dynamic Data الان ان البيانات تبعتي تتسم بواحدة
+
+162
+00:13:16,070 --> 00:13:19,590
+من الصفات هذه بواحدة من المربعات هذه اما هتكون
+
+163
+00:13:19,590 --> 00:13:24,510
+Structured و Static او Unstructured و Static طبعا
+
+164
+00:13:24,510 --> 00:13:26,470
+لما اتكلم على Structured معناه ان انا بتكلم على
+
+165
+00:13:26,470 --> 00:13:30,080
+جداوي الجاهزةوهذه اللي معنين فيها في المرحلة
+
+166
+00:13:30,080 --> 00:13:33,620
+الحالية في الـ Data Mining وإلا كان صار اسم المساق
+
+167
+00:13:33,620 --> 00:13:37,900
+علوم البيانات لأنه بيصير المفروض منك تاخد الـ
+
+168
+00:13:37,900 --> 00:13:41,160
+unstructured data وتتعامل معاها مثل ما بتتعامل مع
+
+169
+00:13:41,160 --> 00:13:47,840
+structured فاحنا مستهدفين المنطقة هذه وممكن هذه في
+
+170
+00:13:47,840 --> 00:13:52,080
+الـ Dynamicوبالتالي أنا بقى أشتغل وين؟ على
+
+171
+00:13:52,080 --> 00:13:55,840
+structure data سواء كانت dynamic أو static مش
+
+172
+00:13:55,840 --> 00:14:00,320
+فارقة كتير معايا عشان هيك بالذنبي أنا أميز من ال
+
+173
+00:14:00,320 --> 00:14:06,540
+data format كيف أعملها cleaning؟ شو يعني cleaning؟
+
+174
+00:14:06,540 --> 00:14:14,320
+الآن حفروا الناس اللي بنقبوا عن الدهب شو طلعوا؟ لا
+
+175
+00:14:14,320 --> 00:14:19,740
+غلطان انت بطلعوا التربة بطلع ال soilتمام؟ بياخدوا
+
+176
+00:14:19,740 --> 00:14:25,060
+الطينة هذه و بروحوا بغسلوها عشان يخلوا يشه الحجار
+
+177
+00:14:25,060 --> 00:14:30,200
+اللي بتظل بعد هيك بيبدوا ي caramelوا فيها مصبوط؟
+
+178
+00:14:30,200 --> 00:14:34,640
+يصفوها عشان يسقط كل شيء مالوش علاقة طبعا غالبا
+
+179
+00:14:34,640 --> 00:14:38,060
+بيستخدموا الميه بالدرجة الأول عشان الدهب ثقيل و
+
+180
+00:14:38,060 --> 00:14:41,720
+بترسم في الآخر انت الآن مفهوم ال cleaning هنا شوية
+
+181
+00:14:41,720 --> 00:14:46,160
+مختلف عن التعامل مع الدهب مفهوم ال cleaning هنا أن
+
+182
+00:14:46,160 --> 00:14:50,660
+ال data تبعت مش على كيفي جايةال data هذه فيها
+
+183
+00:14:50,660 --> 00:14:55,300
+بيانات بتتكلم عن ال birth date تاريخ الميلاد بينما
+
+184
+00:14:55,300 --> 00:15:01,280
+أنا محتاج للعمر بيجي بقوللي يا والله أنا في عند ال
+
+185
+00:15:01,280 --> 00:15:07,780
+GPA تبع الطالب ال GPA يعني في عندي real number و
+
+186
+00:15:07,780 --> 00:15:12,940
+huge number of values من 40 لحد 100 أنا مابديش
+
+187
+00:15:12,940 --> 00:15:15,700
+أتعامل مع ال GPA بدي أتعامل مع ال level مع ال
+
+188
+00:15:15,700 --> 00:15:20,640
+gradeممتاز جيد جدا إلى آخره في بعض ال data فيها
+
+189
+00:15:20,640 --> 00:15:24,500
+مفقودات لقيت إنه والله في record معين رقم أو معدل
+
+190
+00:15:24,500 --> 00:15:30,180
+الطالب مش موجود مين بده يعبي ليه؟ سجل المريض الصحي
+
+191
+00:15:30,180 --> 00:15:33,460
+كده فيه بيانات مفقودة بدي أعبيها في بعض ال data
+
+192
+00:15:33,460 --> 00:15:38,680
+inconsistent غير متناسقة عمره 40 سنة وتاريخ ميلاده
+
+193
+00:15:38,680 --> 00:15:39,560
+95
+
+194
+00:15:42,150 --> 00:15:45,630
+فهي بدي أتحرى فالآن وبالتالي أنا بحاجة أعمل
+
+195
+00:15:45,630 --> 00:15:50,330
+cleaning لل data وتقريبا مرحلة جمع البيانات
+
+196
+00:15:50,330 --> 00:15:58,290
+وتجهيزها أطول فترة في عمر أي مشروع مرتبط بعلوم
+
+197
+00:15:58,290 --> 00:16:02,290
+البيانات أو تنقيب البيانات بشكل واضح make a
+
+198
+00:16:02,290 --> 00:16:09,050
+prediction أنا الآن اتعرفت على البيانات جهزتها بدي
+
+199
+00:16:09,050 --> 00:16:13,500
+أتنبأ اتنبأ بإيش؟قد أشوف الـ knowledge الجديدة هذه
+
+200
+00:16:13,500 --> 00:16:17,940
+اللي أنا ممكن تخدمني أروح أشوف والله بيانات الطلاب
+
+201
+00:16:17,940 --> 00:16:21,600
+الجامعيين أو بيانات الطلاب اللي عندي في جامعات
+
+202
+00:16:21,600 --> 00:16:26,760
+الفلسطينية من الألفين لألفين وعشرين عشرين سنة في
+
+203
+00:16:26,760 --> 00:16:30,020
+كل سنة في عندي كام الف طالب يدخلوا الجامعات
+
+204
+00:16:30,020 --> 00:16:36,000
+ويتخرجوا الآن هل ممكن أنا ألاقي علاقة واضحة بين
+
+205
+00:16:36,000 --> 00:16:39,580
+على سبيل المثال الظروف الاجتماعية تبعت الطالب
+
+206
+00:16:39,580 --> 00:16:44,800
+وتحصيله العلميمن البيانات بتعرفوا .. من البيانات
+
+207
+00:16:44,800 --> 00:16:48,800
+بتعرفوا .. بس هل السؤال هذا .. هل statistics
+
+208
+00:16:48,800 --> 00:16:53,740
+إحصاء؟ كيف يعني إحصاء؟ ال statistics بتعمل تسوية
+
+209
+00:16:53,740 --> 00:16:55,280
+البيانات اللي عندك تتعمل تسوية البيانات اللي عندك
+
+210
+00:16:55,280 --> 00:16:55,300
+تتعمل تسوية البيانات اللي عندك تتعمل تسوية
+
+211
+00:16:55,300 --> 00:16:55,780
+البيانات اللي عندك تتعمل تسوية البيانات اللي عندك
+
+212
+00:16:55,780 --> 00:16:56,140
+تتعمل تسوية البيانات اللي عندك تتعمل تسوية
+
+213
+00:16:56,140 --> 00:16:57,200
+البيانات اللي عندك تتعمل تسوية البيانات اللي عندك
+
+214
+00:16:57,200 --> 00:16:57,780
+تتعمل تسوية البيانات اللي عندك تتعمل تسوية
+
+215
+00:16:57,780 --> 00:16:58,880
+البيانات اللي عندك تتعمل تسوية البيانات اللي عندك
+
+216
+00:16:58,880 --> 00:16:58,880
+ت
+
+217
+00:17:03,470 --> 00:17:08,190
+اها، اها، شوف إيش بدى يسوي هو بدى يبني role إذا
+
+218
+00:17:08,190 --> 00:17:14,330
+كان نسبة ظهور ال pattern هذا 90% فما فوق، الآن هذا
+
+219
+00:17:14,330 --> 00:17:18,050
+ال role هو بمثابة ال knowledge تبعتك لكن هذا الآن
+
+220
+00:17:18,050 --> 00:17:23,470
+مش statistic، وإن كان جزء منها هيكون statistic لما
+
+221
+00:17:23,470 --> 00:17:27,430
+تروح تدورت أنت الحالة الاجتماعية بارتباطها
+
+222
+00:17:27,430 --> 00:17:31,680
+بالتحصيل العلمي، جديشالـ frequent لما دورت على عدد
+
+223
+00:17:31,680 --> 00:17:38,400
+تكرارها استخدمت إحصاء عشان تعمل prediction زي ما
+
+224
+00:17:38,400 --> 00:17:44,240
+قلنا وتستخدم ال tools الحديثة ومن الممكن من أهم ال
+
+225
+00:17:44,240 --> 00:17:47,420
+tools الشباب المستخدم اليوم هي ال tools المبنية
+
+226
+00:17:47,420 --> 00:17:50,360
+على الـ Python سواء كانت ك programming language
+
+227
+00:17:50,360 --> 00:17:54,300
+تمام أو different distribution للـ Python أو حتى
+
+228
+00:17:54,300 --> 00:18:00,430
+فعلياً software packages مبنية على الـ Pythonبعد
+
+229
+00:18:00,430 --> 00:18:05,470
+هيك بدي أعمل evaluation المفروض evaluation لإيش؟
+
+230
+00:18:05,470 --> 00:18:10,210
+لشغل، للنتيجة اللي حصلت عليها، الآن و بعد دراسة
+
+231
+00:18:10,210 --> 00:18:15,890
+الشريف الصحي تبع المرضى اكتشفنا ان والله ان الناس
+
+232
+00:18:15,890 --> 00:18:19,490
+اللي بيكون عندها سوء تغذية هدولة ممكن برضه يكون
+
+233
+00:18:19,490 --> 00:18:24,270
+احتمالية اصابتهم بسرطان الرئى الله يبعد عنك الشر و
+
+234
+00:18:24,270 --> 00:18:29,900
+والديك و جميع المسلمين انه عالي جداكل ال knowledge
+
+235
+00:18:29,900 --> 00:18:34,340
+تبعيتنا بنعرف أنه تدخين طب شو دخل سوق التخزين؟ ال
+
+236
+00:18:34,340 --> 00:18:37,080
+historical data بتقول أن سوق التخزين لها دور في
+
+237
+00:18:37,080 --> 00:18:42,660
+الموضوع لأن هاي في عندي شخص كان بتغذى كويس و شرح
+
+238
+00:18:42,660 --> 00:18:46,660
+في التدخين لكنه لم يصب لكن كل الحالات اللي أصيبت
+
+239
+00:18:46,660 --> 00:18:50,340
+بالإضافة للتدخين كان عندهم سوق تخزين معناته أصبح
+
+240
+00:18:50,340 --> 00:18:55,640
+في عندي role جديد knowledge جديدة، مين بيقيمها؟
+
+241
+00:18:55,640 --> 00:19:01,310
+مين بيقيمها؟الناس المختصين القائمين على الموضوع
+
+242
+00:19:01,310 --> 00:19:04,370
+هذا بدهم ياخدوا يجيبوا يقولوا يا وين ال system
+
+243
+00:19:04,370 --> 00:19:07,310
+اللي بنيته أو وين ال project اللي بنيته هيه ماشي
+
+244
+00:19:07,310 --> 00:19:11,430
+الحال تعالي بروحهم بيجيبوا بعينات حقيقية من الناس
+
+245
+00:19:11,430 --> 00:19:15,990
+المصابة بالمرض هذا و بدرسوا هذا فعليا عنده سوق
+
+246
+00:19:15,990 --> 00:19:18,870
+تغذية حسب الشروق اللي موجود عندنا بياخدوا البيانات
+
+247
+00:19:18,870 --> 00:19:21,790
+و بيعرضوها لل system أنا مابعرفش فال system لما
+
+248
+00:19:21,790 --> 00:19:28,290
+بقول positive هيصابأو negative ال rate هذا هو
+
+249
+00:19:28,290 --> 00:19:31,410
+بمثابة ال evaluation يعني بتجيبوا عينة من البيانات
+
+250
+00:19:31,410 --> 00:19:35,130
+الحقيقية و بعضوها على النظام بعد هيك بصير النظام
+
+251
+00:19:35,130 --> 00:19:37,830
+هذا معتمد بالنسبة لهم ان اوكي والله احنا ممكن
+
+252
+00:19:37,830 --> 00:19:43,190
+نتنبأ ايش باحتمالية الإصابة و ممكن نسعى الآن
+
+253
+00:19:43,190 --> 00:19:47,790
+جاهدين ان نحسن موضوع أنواع الناس بأهمية التغذية و
+
+254
+00:19:47,790 --> 00:19:51,920
+بحيث انهم يتجنبوا موضوع التدخين و هكذاأخر شغلة
+
+255
+00:19:51,920 --> 00:19:55,100
+بتلزمني وطبعا ممكن تكون هي أول شغلة كمان أحيانا
+
+256
+00:19:55,100 --> 00:19:58,660
+عشان أفهم البيانات اللي عندي موضوع ال data أو ال
+
+257
+00:19:58,660 --> 00:20:01,140
+knowledge visualization كيف أظهر ال knowledge؟
+
+258
+00:20:01,140 --> 00:20:04,180
+كلنا بنعرف المقولة اللي بتقول الصورة خير من ألف
+
+259
+00:20:04,180 --> 00:20:09,920
+كلمة الآن لو أنا روحت جبتلك بيانات الطلاب أو جدول
+
+260
+00:20:09,920 --> 00:20:16,620
+الطلاب في مليون record وعلامات الطلاب موجودة هل
+
+261
+00:20:16,620 --> 00:20:22,240
+بتقدر تحصر نسب الطلاب في كل واحديعني مثلا جديش جيد
+
+262
+00:20:22,240 --> 00:20:26,060
+جدا، جديش ممتاز، قوله بقى أعمل تقرير إحصائي، ماشي
+
+263
+00:20:26,060 --> 00:20:29,240
+الحال، بقى التقرير هذا لو كانت فيه عندك Graph أو
+
+264
+00:20:29,240 --> 00:20:34,700
+رسمةأسرع في one site حتى أسرع من الجدول عشان هيك
+
+265
+00:20:34,700 --> 00:20:36,480
+أنت لازم يكون في عندك مقدرة على عمل ال
+
+266
+00:20:36,480 --> 00:20:39,860
+visualization ال if then rule اللي تتكلم فيه
+
+267
+00:20:39,860 --> 00:20:43,660
+زميلنا هان لو كانت نسبة الناس على حالتهم
+
+268
+00:20:43,660 --> 00:20:48,440
+الاجتماعية و كدراسة و كتحصيل سيئ بنسبة 90% فما
+
+269
+00:20:48,440 --> 00:20:53,540
+فوقها ده rule انكتب عشان نفهمه بشكل صحيح if then
+
+270
+00:20:53,540 --> 00:20:58,210
+طب أنا ممكن أروح أعمله as decision treeعشان أقدر
+
+271
+00:20:58,210 --> 00:21:01,410
+أكون كل branch هو لأن نتكلم على فرع واحد فقط فممكن
+
+272
+00:21:01,410 --> 00:21:06,150
+إحنا بحاجة إننا نعمل visualization من
+
+273
+00:21:06,150 --> 00:21:09,090
+أهداف المساق تبعتنا بعد ما اتكلمنا على أوصيف
+
+274
+00:21:09,090 --> 00:21:13,150
+المساق أهداف المساق تبعتنا كانت تالي providing
+
+275
+00:21:13,150 --> 00:21:18,310
+fundamental understanding يزودنا بالفهم الأساسي
+
+276
+00:21:18,310 --> 00:21:23,750
+لمتطلبات ال data mining عشان أقدر أستخرج المعرفة
+
+277
+00:21:23,750 --> 00:21:28,810
+المخفية منفي الـ data أو المخفية في الـ data هاي
+
+278
+00:21:28,810 --> 00:21:36,650
+اتنين نستكشف مع بعض مجموعة من ال data mining tasks
+
+279
+00:21:36,650 --> 00:21:41,230
+عشان أستخرج المعرفة هاي data mining tasks
+
+280
+00:21:41,230 --> 00:21:45,230
+classification classification يعني تصنيف يا شباب
+
+281
+00:21:45,230 --> 00:21:49,930
+لو أنا بدي أشوف في جو يالي زي هذا احنا في فصل
+
+282
+00:21:49,930 --> 00:21:55,650
+الشتاء و بدي أعرف الدنيا هتمطر ولا مش هتمطر تلاحظ؟
+
+283
+00:22:03,800 --> 00:22:10,260
+rainy yes و no إذا ال system بتاعي بده يقول إن
+
+284
+00:22:10,260 --> 00:22:14,740
+الجو ماطر أو غير ماطر فهذه classification إذا بده
+
+285
+00:22:14,740 --> 00:22:18,260
+يقول لي ال stock market أو ال stock price سعر
+
+286
+00:22:18,260 --> 00:22:25,120
+السهم increase
+
+287
+00:22:25,120 --> 00:22:26,000
+or decrease
+
+288
+00:22:29,730 --> 00:22:36,050
+هذه classification طبعا، لكن لو في إنا مسألة تانية
+
+289
+00:22:36,050 --> 00:22:39,730
+شكل الناس أكتبها هان اللي هي ال prediction أو ال
+
+290
+00:22:39,730 --> 00:22:45,250
+regression لما أنا بدي specific value، بدي قيمة،
+
+291
+00:22:45,250 --> 00:22:48,970
+تقولليش السهم بدي يرتفع أو بدي ينخفض، تقوللي جديش
+
+292
+00:22:48,970 --> 00:22:53,250
+قيمة التغيير على السهم هتكون بعد يومين، وأنا بعرف
+
+293
+00:22:53,250 --> 00:22:57,330
+لحالي هو هيرتفع ولا ينخفض، تبقى اللي لاقياش؟للقيمة
+
+294
+00:22:57,330 --> 00:23:00,790
+اللي هتزودني فيها قوللي قداش حجم المطر اللي بده
+
+295
+00:23:00,790 --> 00:23:06,090
+ينزل لما تقوللي صفر هفهم انه مافيش مطر و لما
+
+296
+00:23:06,090 --> 00:23:12,430
+تقوللي انه والله نسبة المطر هتكون 5.45 ميلي متر في
+
+297
+00:23:12,430 --> 00:23:15,470
+اليوم الفلاني معناته انا بفهم انه في مطر ومطر غزير
+
+298
+00:23:15,470 --> 00:23:20,390
+كمان فبالتالي هنا في عندي هانشغلة لها علاقة في الـ
+
+299
+00:23:20,390 --> 00:23:24,110
+Prediction لـ Clustering، لـ Grouping أو تجميع
+
+300
+00:23:24,110 --> 00:23:28,490
+البيانات حسب الخصائص المشتركة طب أنا بدور
+
+301
+00:23:28,490 --> 00:23:31,290
+بالخصائص، الخصائص اللي أنت مستحيل تقدر تطبقها
+
+302
+00:23:31,290 --> 00:23:34,730
+بإيدك أو تشوفها بعينك، و هورجيك خلال مثال عملي
+
+303
+00:23:34,730 --> 00:23:38,030
+لاحقا إن شاء الله تعالى مع بعض هنا في القاعة أو
+
+304
+00:23:38,030 --> 00:23:40,630
+هورجيك إنه فعلا تحس أنه في صعوبة حسب الـ
+
+305
+00:23:40,630 --> 00:23:42,870
+Requirement في الـ Clustering إنك تشتغل عليها
+
+306
+00:23:42,870 --> 00:23:49,210
+Association RulesExtraction ارتباط أو قوانين
+
+307
+00:23:49,210 --> 00:23:53,430
+الارتباط بين الأشياء في ال supermarket؟ شو علاقة
+
+308
+00:23:53,430 --> 00:24:00,850
+علب السجائر بالجهوة بالشاي بالمشروبات الساخنة؟ هل
+
+309
+00:24:00,850 --> 00:24:04,630
+في علاقة ما بين حفظات الأطفال والحليب والبودرة
+
+310
+00:24:04,630 --> 00:24:08,620
+والشغلات هذه ولا لأ؟الناس اللي عادة بتروح بتدور
+
+311
+00:24:08,620 --> 00:24:13,260
+مثلا تشتري الشوكولات السائلة والزينة ومش عارفاش
+
+312
+00:24:13,260 --> 00:24:16,380
+أكيد بتدور على لو طحين عشان تشتغل أو الدقيقة عشان
+
+313
+00:24:16,380 --> 00:24:20,800
+تعمل cake فهذه المعاملات الإرتباط مش بسهولة أنا
+
+314
+00:24:20,800 --> 00:24:24,320
+أقدر أتعرف عليها و أشوفها وبالتالي أنا بحاجة ل
+
+315
+00:24:24,320 --> 00:24:29,990
+association أخطر من هيكحالات ظهور مرض معين إذا
+
+316
+00:24:29,990 --> 00:24:33,910
+اتوفر الظرف واحد اتنين تلاتة معناته في المرض هذا
+
+317
+00:24:33,910 --> 00:24:36,810
+ممكن يظهر وهيك بيصير قيمة ال association rule تبعي
+
+318
+00:24:36,810 --> 00:24:41,150
+أكثر جدية من الأمور السابقة ال outlier detection
+
+319
+00:24:41,150 --> 00:24:46,450
+تحديد الحالات الشاذة في البيئة اللي أنا بقى أشتغل
+
+320
+00:24:46,450 --> 00:24:53,130
+عليها يعني بيجي يقولك والله فلانماشاء الله عليه
+
+321
+00:24:53,130 --> 00:24:56,330
+الراجل مجتهد على تربية أولاده و البيت ما شاء الله
+
+322
+00:24:56,330 --> 00:25:01,330
+و أهل بيته كذلك لكن عنده ولد أعوذ بالله شاذ بعيد
+
+323
+00:25:01,330 --> 00:25:04,950
+عنهم مختلف عنهم تماما تقول مش منهم يا راجل ولا لأ
+
+324
+00:25:04,950 --> 00:25:09,190
+هذا بمصطلح للبصيف اللي .. بنقول عنه out layer
+
+325
+00:25:09,190 --> 00:25:15,650
+مختلف نجد نتكلم أن والله أن ثمر تبعي في شجرة معينة
+
+326
+00:25:15,650 --> 00:25:20,950
+شجرة التفاح أو .. بلاش عند مزرعة التفاح و بقى تعب
+
+327
+00:25:20,950 --> 00:25:26,210
+عليهم كلهمبأرويهم نفس الراي و نفس الموعد و نفس
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+328
+00:25:26,210 --> 00:25:31,410
+الكمية إيش محتاجين علاج أو مضادات أو تغذية بشتغل
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+329
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+عليهم كل ياتهم إلا غير إنه في شجرة في المزرعة حبها
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+330
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+مش نافع، بدي أخلعها و أرميها؟ أنت قد تحتاج إنك
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+331
+00:25:44,630 --> 00:25:50,440
+تخلعها عشان ما تنحسبش عليكفي الآخر أبضلش هذا طب
+
+332
+00:25:50,440 --> 00:25:56,880
+الآن هل في سبب معين واضح للشدود؟ genetic وبالتالي
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+333
+00:25:56,880 --> 00:26:01,360
+أنا ممكن أصير أدور طب ما هم كلهم مزرعين في نفس
+
+334
+00:26:01,360 --> 00:26:05,200
+الأرض فرجت مثلا في الأربعة متر high ممكن على جولة
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+335
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+أهلنا وختيريتنا الأرض بالشبربصبوط كلامك ممكن تفرق
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+336
+00:26:09,560 --> 00:26:13,380
+الأمور لكن في الآخر بتضال مش من ضمن السياق اللي
+
+337
+00:26:13,380 --> 00:26:17,840
+احنا بنتكلم عليه الآن أخطر من هيك يا شباب عادة انا
+
+338
+00:26:17,840 --> 00:26:22,800
+عندي server .. عندي server بقدم خدمة تسديل الطلاب
+
+339
+00:26:22,800 --> 00:26:26,900
+للجامعة عادي و ال traffic اللي عليه انا متوقع انه
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+340
+00:26:26,900 --> 00:26:30,660
+يجيني مثلا خلال الدقيقة 100 connection ألف
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+341
+00:26:30,660 --> 00:26:36,280
+connection في لحظة من اللحظات اجاني مليون request
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+342
+00:26:36,280 --> 00:26:36,940
+ل connections
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+343
+00:26:39,880 --> 00:26:42,280
+أها يعني صار في عندي attack صار في عندي إيش
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+344
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+outlier فلازم يكون لازم يكون في عندي قدرة على
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+345
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+تحديد ال outlier هذا وإيش أسبابه هنجيها بالتفصيل
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+346
+00:26:49,520 --> 00:26:53,680
+في حينها practicing data mining project phases
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+347
+00:26:53,680 --> 00:26:57,460
+تجرب و تطبق فعليا ال faces كلها ياتا هاي
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+348
+00:26:57,460 --> 00:27:04,640
+presenting تعرض ال data سواء كانت في ال early
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+349
+00:27:04,640 --> 00:27:09,500
+stage قبل العملأو كانت الـ knowledge في نهاية الـ
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+350
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+project اللي موجود عندى نزوذ الطلبة قدر المستطاع
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+351
+00:27:15,660 --> 00:27:21,320
+بآخر المواضيع المتعلقة في ال data mining طبعا
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+352
+00:27:21,320 --> 00:27:24,660
+هيكون فيك جهد منها على المواضيع هذه معانا ان شاء
+
+353
+00:27:24,660 --> 00:27:27,000
+الله تعالى نحاول نقوى
+
+354
+00:27:29,920 --> 00:27:34,120
+العمل الجماعي ما بينكم وغالباً هشكلكوا لمجموعات ان
+
+355
+00:27:34,120 --> 00:27:37,940
+شاء الله الفصل هذا طيب ال outcome مخرجات المساق
+
+356
+00:27:37,940 --> 00:27:41,740
+أنا بتتوقع بعد نهاية المساق أنك تكون قادر على
+
+357
+00:27:41,740 --> 00:27:45,620
+تعريف ال data mining توصف البيانات المناسبة لل
+
+358
+00:27:45,620 --> 00:27:50,620
+project في ال data mining تعرف على الأقل خمسة من
+
+359
+00:27:50,620 --> 00:27:55,380
+ال data mining task وكل واحدة أشهر بتساويcollect
+
+360
+00:27:55,380 --> 00:27:58,760
+and prepare تكون قادرة على الجمع وتجهيز البيانات
+
+361
+00:27:58,760 --> 00:28:04,800
+لأي data mining project هتتعرف
+
+362
+00:28:04,800 --> 00:28:11,240
+وتستخدم ال machine learning algorithms عشان تنفذ
+
+363
+00:28:11,240 --> 00:28:17,270
+ال data mining tasks المختلفةاتحلل و تبني data
+
+364
+00:28:17,270 --> 00:28:22,450
+mining project سواء كنت بشكل مستقل، منفرد أو ضمن
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+365
+00:28:22,450 --> 00:28:28,170
+فريق، سواء كنت عضو في الفريق أو قائد الفريق تتبنى
+
+366
+00:28:28,170 --> 00:28:31,910
+أخلاقيات المهنة في محافظة على خصوصية الناس في
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+367
+00:28:31,910 --> 00:28:35,450
+المعلومات لأنه لما احنا بنروح و بنتكلم على بيانات
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+368
+00:28:35,450 --> 00:28:39,030
+صحية أو بيانات اجتماعية أو بيانات أو بيانات بمعنى
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+369
+00:28:39,030 --> 00:28:44,350
+ان في عندنا privacy لازم ينتهيشتحلّى بالأخلاق
+
+370
+00:28:44,350 --> 00:28:52,090
+الحميدة وتحافظ على خصوصية الناس يعنى textbook
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+371
+00:28:52,090 --> 00:28:56,830
+data mining concepts and techniques النسخة الرابعة
+
+372
+00:28:56,830 --> 00:29:02,070
+2017 من Elsevier كذلك في عندى ال data mining ال
+
+373
+00:29:02,070 --> 00:29:05,770
+reference book طبعا هدولة هم الأساسي اللى .. لكن
+
+374
+00:29:05,770 --> 00:29:08,190
+هتلاقي في ال references عندى حوالى سبعة أو تمانية
+
+375
+00:29:08,190 --> 00:29:12,010
+كتب هتكون مقطاط عندك على ال model لأنه هدى عدت في
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+376
+00:29:12,010 --> 00:29:16,900
+التحضيربتنقل ما بين الكتب الـ Data Mining Practice
+
+377
+00:29:16,900 --> 00:29:20,840
+Machine Learning Tools and Techniques في 2016 قد
+
+378
+00:29:20,840 --> 00:29:24,020
+قريباً هدول أحدث الـ Virgin اللي مباشرة بتكلموا في
+
+379
+00:29:24,020 --> 00:29:27,460
+الـ Data Mining في 2018 و2019 بتكلموا في الـ Data
+
+380
+00:29:27,460 --> 00:29:30,860
+Science بس بياخدونا في ال trend شوية يعني مختلف ما
+
+381
+00:29:30,860 --> 00:29:35,560
+قبل الـ Structured Data الآن إيش المواضيع اللي
+
+382
+00:29:35,560 --> 00:29:40,640
+بدنا نغطيها؟ هنغطي مجموعة من العنوين أو المواضيع
+
+383
+00:29:40,640 --> 00:29:45,150
+نجتهد توزيعها على الأسابيعطبعاً زي ما أقول مافيش
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+384
+00:29:45,150 --> 00:29:50,630
+إشي مقدس لكن هنحاول نحتفظ فيها أو نلتزم فيها قدر
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+385
+00:29:50,630 --> 00:29:54,070
+المستطاع تقريباً بدنا أسبوع عشان نخلص ال
+
+386
+00:29:54,070 --> 00:29:55,910
+introduction يعني مسبوع يعني محاضرة تانية يا شباب
+
+387
+00:29:55,910 --> 00:29:58,750
+محاضرة ومحاضرة الجاية المفروض ان ال introduction
+
+388
+00:29:58,750 --> 00:30:03,570
+تكون انتهت بعد هيك هنتكلم على ال data
+
+389
+00:30:03,570 --> 00:30:06,470
+understanding and data preparation وهنا تقريبا
+
+390
+00:30:06,470 --> 00:30:12,250
+هناخد أسبوعين ممكن أكتر شويةلكن هاي المبدأ إذا أنا
+
+391
+00:30:12,250 --> 00:30:15,790
+حضرت ال data وفهمتها كويس أو فهمتها كويس وحضرتها
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+392
+00:30:15,790 --> 00:30:19,670
+بما يلغ لل task تبعتي هنبدأ نتكلم على knowledge
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+393
+00:30:19,670 --> 00:30:22,030
+extraction باعتمادنا على ال machine learning
+
+394
+00:30:22,030 --> 00:30:25,430
+algorithm وزي ما قلنا ال task تبعتنا خمسة
+
+395
+00:30:26,620 --> 00:30:28,460
+classification, regression, clustering,
+
+396
+00:30:28,680 --> 00:30:32,800
+association rules و outlier detection لأن كل واحدة
+
+397
+00:30:32,800 --> 00:30:36,120
+فيهم لها different metrics evaluation metrics
+
+398
+00:30:36,120 --> 00:30:41,360
+فهنشرح two algorithms او واحد حسب كيف تمشي معانا
+
+399
+00:30:41,360 --> 00:30:46,200
+الأمور بحيث نثبت ال concept وهنا بيلزمك تكون ال
+
+400
+00:30:46,200 --> 00:30:50,080
+calculator تبعتك معاك لأن في مسائل حسابية بدها حل
+
+401
+00:30:50,080 --> 00:30:54,530
+فلازم تكون ال calculator معاك باستمرارتمام؟ يعني
+
+402
+00:30:54,530 --> 00:30:57,350
+ما تتعودش تجينا هيك باشا زي في الجيبة هذه الجوال
+
+403
+00:30:57,350 --> 00:31:00,430
+في الجيبة التانية بتحط بال calculator عشان ما
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+404
+00:31:00,430 --> 00:31:05,750
+تقعدش تشحت من دي زمالك زي ما اتكلمنا عفوا قبل شوية
+
+405
+00:31:05,750 --> 00:31:11,170
+classification regression ال classification قل لي
+
+406
+00:31:11,170 --> 00:31:16,910
+هو بيتبع أي فئة من الفئات اللي موجودة عندى إيش
+
+407
+00:31:16,910 --> 00:31:21,340
+تصنيفه؟ بس التصنيفات هذه already معروفةيعني باجي
+
+408
+00:31:21,340 --> 00:31:25,260
+بقول إن والله أنا الطلاب يصنفوا في الجامعة مابين
+
+409
+00:31:25,260 --> 00:31:30,880
+راسب الله يبعدكوا عنه يا رب ومقبول كذلك جيد جيد
+
+410
+00:31:30,880 --> 00:31:34,960
+جدا وممتاز في عندي خمس تصنيفات لتقييم .. لا عفوا
+
+411
+00:31:34,960 --> 00:31:40,280
+للمستوى الطالب في حد بتكلم على ستة مافيش في حد
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+412
+00:31:40,280 --> 00:31:44,000
+بتكلم على سبعة على خمسة طيب لا مافيش هم خمس
+
+413
+00:31:44,000 --> 00:31:49,200
+تصنيفات فأنا بعرف التصنيفات مسبقاباجي بتكلم مثلا
+
+414
+00:31:49,200 --> 00:32:01,440
+عن الفقاريات الفقاريات تصنف ثدييات .. تمام؟ زواحف
+
+415
+00:32:01,440 --> 00:32:09,960
+فقاريات وطيور .. تمام؟ الآن الزواحف
+
+416
+00:32:11,480 --> 00:32:14,520
+ذوات الدم بارد وذوات الدم حار هذه التصنيفات
+
+417
+00:32:14,520 --> 00:32:19,340
+already معروفة وانت مش عفوا لازم تكون خبير في
+
+418
+00:32:19,340 --> 00:32:24,360
+المجال عشان تحط تصنيف جديد دوري أنا .. دوري أنا
+
+419
+00:32:24,360 --> 00:32:30,780
+أشوف كيف ممكن أنا أعمل أو أبني model يقدر يتنبأ
+
+420
+00:32:30,780 --> 00:32:36,500
+بال class أو بالتصنيف الصح بناء على ال condition
+
+421
+00:32:36,500 --> 00:32:41,250
+معين يعني عادةإن شاء الله كلكم بتجربوها عن قريب
+
+422
+00:32:41,250 --> 00:32:45,030
+العذبية طبعا فيكوا لما بدك تروح تتزوج صار بيقولك
+
+423
+00:32:45,030 --> 00:32:51,870
+روح هتلي فحص للثلاثيمية، أصبت؟ عشان يتجنب إن المرض
+
+424
+00:32:51,870 --> 00:32:57,870
+هذا ينتشر طيب، المرض هذا أساساً فيه تلت تصنيفات أو
+
+425
+00:32:57,870 --> 00:33:01,670
+أربعة حتى
+
+426
+00:33:01,670 --> 00:33:05,470
+من المصاب كمان فيه له grades معينة، تمام؟ في
+
+427
+00:33:05,470 --> 00:33:10,690
+الآخر، في الآخر، الآن أنا ممكن أجتهدوأعمل برنامج
+
+428
+00:33:10,690 --> 00:33:14,430
+بناءً على ال data وحالات المصابين بالثلاثين أو كذا
+
+429
+00:33:14,430 --> 00:33:18,570
+إن أقول والله ممكن التغلب على المرض هذا مثلا بعد
+
+430
+00:33:18,570 --> 00:33:22,810
+أربع سنوات أو عشر سنوات من ناحية ورثية لو الناس
+
+431
+00:33:22,810 --> 00:33:28,010
+هدول اتبعوا نظام معين هذا الكلام عفوا مش هبل ولا
+
+432
+00:33:28,010 --> 00:33:33,230
+طالع من الخيال هو عبارة عن نابع عن دراسة تحليل
+
+433
+00:33:33,230 --> 00:33:38,250
+معمق لل data اللي موجودة عندىأنا كـ human مش هقدر
+
+434
+00:33:38,250 --> 00:33:41,570
+أحلل البيانات هذه بالمضمق البسيط فمحتاج لـ Machine
+
+435
+00:33:41,570 --> 00:33:46,650
+Learning Algorithm هي يتحلل و تديني decision لأن
+
+436
+00:33:46,650 --> 00:33:50,450
+جداش الناس بتعاني في العالم و احنا نفن أكتر منهم
+
+437
+00:33:50,450 --> 00:33:56,070
+في تشخيص الأمراض جداش بتسمع بلاش في مجتمعنا في غزة
+
+438
+00:33:56,070 --> 00:33:58,930
+يقولك والله فلان هو أو ابنه أو أي حد الله يعافي
+
+439
+00:33:58,930 --> 00:34:02,170
+جميع المسلمين أن هو مريض ومش قادرين يشخصوا إيش
+
+440
+00:34:02,170 --> 00:34:11,140
+ماله طب مع إن الأعراضمعروفة وغالبا تحصر القلق ممكن
+
+441
+00:34:11,140 --> 00:34:15,020
+يكون في عندي expert system أروح أدخله الأعراض
+
+442
+00:34:15,020 --> 00:34:20,200
+بالإضافة لوصف ال character هذا الإنسان عمره ووزنه
+
+443
+00:34:20,200 --> 00:34:23,720
+طبيعة غذائه يعني أبدأ أجمع معلومات عن الشخص هذا و
+
+444
+00:34:23,720 --> 00:34:26,560
+ال system يقوللي هذا غالبا مكون مصاب بكذا أو كذا
+
+445
+00:34:26,560 --> 00:34:31,130
+أو كذا ممكن بقولش أن هذا مش هيخطئبس النظام هذا إذا
+
+446
+00:34:31,130 --> 00:34:36,410
+جدر يشخصلي خمسين في المية من الحالات، تشخيص صح،
+
+447
+00:34:36,410 --> 00:34:39,850
+خمسين في المية من الحالات اللي أنا مش جادر أشخصها،
+
+448
+00:34:39,850 --> 00:34:47,070
+هذا إنجاز، هذا ال risk اللي احنا قلنا قبل شوية
+
+449
+00:34:47,070 --> 00:34:51,590
+فيها مخاطرة في التنقيب، ما هو أنت الآن جدشت تبعك
+
+450
+00:34:51,590 --> 00:34:52,530
+ال system بيكون reliable
+
+451
+00:34:55,350 --> 00:35:03,270
+شوف، أنا ممكن أرفض نظام بيديني 95% accuracy، دقة،
+
+452
+00:35:03,270 --> 00:35:05,750
+في الأمور الصحية، في الـ critical، لكن أنا قاعد
+
+453
+00:35:05,750 --> 00:35:10,230
+بقولك إن الأعراض هيها، والتشخيص، إحنا ك human مش
+
+454
+00:35:10,230 --> 00:35:13,770
+قادرين نشخص، عشان هيك أنا حصرتك في المجال إنه
+
+455
+00:35:13,770 --> 00:35:17,730
+complete benefitراح فعليا قدر يشخصني تشخيص صحيح بـ
+
+456
+00:35:17,730 --> 00:35:21,370
+50% من الأعراض اللي موجودة هاي طب تقولي أنت شخصته
+
+457
+00:35:21,370 --> 00:35:24,630
+غلط ومات طب أنت مش قادر تشخصه وغالبا هتشخصه غلط
+
+458
+00:35:24,630 --> 00:35:29,750
+فما تحملش ال system ما لا يطيقك زي ما أقوله مع أنه
+
+459
+00:35:29,750 --> 00:35:32,530
+أنا بقولك بستهينش بحياة البشر لأ لازم أشتغل و
+
+460
+00:35:32,530 --> 00:35:37,790
+أجتهد أنه تكون الأمور تمام زي ما قولنا regression
+
+461
+00:35:37,790 --> 00:35:43,220
+اتنبأ بقيمة value real valueclustering جسم
+
+462
+00:35:43,220 --> 00:35:47,560
+لمجموعات اروح اقول والله جسم الطلاب لتلت مجموعات
+
+463
+00:35:47,560 --> 00:35:53,700
+هيكوا في القاعة تلت مجموعات يا شباب في الآخر اسمك
+
+464
+00:35:53,700 --> 00:35:57,940
+عبدالله لو قلتلك جسم الطلاب لتلت مجموعات في القاعة
+
+465
+00:35:57,940 --> 00:36:01,620
+تلت
+
+466
+00:36:01,620 --> 00:36:05,260
+مجموعات اهدوا يا شباب على السريع عبدالله ايوة
+
+467
+00:36:08,540 --> 00:36:11,060
+ممتاز، مع إنه مش موجود الكلام اللي أنت موجود فيه
+
+468
+00:36:11,060 --> 00:36:14,120
+بينما لو قلتله ميمنا أو ميسر أو قلب كان ضبطه معاك
+
+469
+00:36:14,120 --> 00:36:17,840
+100% لاحظ أنه أنا ماتكلمتش معاك على
+
+470
+00:36:17,840 --> 00:36:23,600
+characteristics قلتلك كل بس كان طلبي منك جسملياهم
+
+471
+00:36:23,600 --> 00:36:27,360
+كمجموعات ماتحكمل فيك في عدد عفوا كان .. قداش ..
+
+472
+00:36:27,360 --> 00:36:30,200
+عفوا .. لما قلتلك تلت مجعات أنا طلبت العدد هذا بس
+
+473
+00:36:30,200 --> 00:36:34,720
+ماقلتلك كم واحد في جلب المجموعة، مصبوط؟ لكن أنت
+
+474
+00:36:34,720 --> 00:36:40,750
+ممكن تيش تقولي والله هاي واحد كمانتنين وهي تلاتة،
+
+475
+00:36:40,750 --> 00:36:43,550
+طب ليش اعملت هيك يا عبد الله؟ عشان أضمن توازن
+
+476
+00:36:43,550 --> 00:36:46,750
+أعداد في الأشخاص اللي موجودين، ممكن يقول آه والله
+
+477
+00:36:46,750 --> 00:36:50,430
+لا دكتور أنا بدي أصنفهم شكل مختلف، أنا بدي أروح
+
+478
+00:36:50,430 --> 00:36:57,370
+أستخدم معدلاتهم التراكمية اللي تحت الـ75بين 75 لـ
+
+479
+00:36:57,370 --> 00:37:00,830
+90 واللي فوق الـ 90، هاي تلات مجموعات لاحظ ماحدش
+
+480
+00:37:00,830 --> 00:37:03,070
+في الدنيا بالسجل يقولك تصنيف الغلط أو تقسم ..
+
+481
+00:37:03,070 --> 00:37:06,730
+برنامج تقسيمك طالما في عندك justification قوية،
+
+482
+00:37:06,730 --> 00:37:11,670
+ليش أنت قسمت هيك؟ الأحيان إحنا بنعجز عن نشوف الـ
+
+483
+00:37:11,670 --> 00:37:14,910
+common properties في ال data set تخيل data set
+
+484
+00:37:14,910 --> 00:37:19,370
+فيها 100 attributes و مليون record، إيش ال common
+
+485
+00:37:19,370 --> 00:37:24,030
+اللي بينهم؟عارفش فبقول لل system أشغل نيابة عني
+
+486
+00:37:24,030 --> 00:37:29,110
+قسملي إياهم لتلت مجموعات فببدأ يروح يدرس الخصائص و
+
+487
+00:37:29,110 --> 00:37:33,630
+بقسملك إياهم كذلك في ال association rules سواء
+
+488
+00:37:33,630 --> 00:37:36,410
+كانت في الأمراض في ال marketing إلى آخره وال
+
+489
+00:37:36,410 --> 00:37:41,350
+outlier detection بعد هيكد لسبوع تلت عشر هنبدأ في
+
+490
+00:37:41,350 --> 00:37:45,900
+ال data visualizationوال knowledge presentation 14
+
+491
+00:37:45,900 --> 00:37:50,560
+و 15 ال 14 هيكون نتناول موضوع من الموضوع الجديد ان
+
+492
+00:37:50,560 --> 00:37:53,880
+شاء الله تعالى و ال 15 هيكون في عندنا project
+
+493
+00:37:53,880 --> 00:37:57,560
+presentation and discussion ان شاء الله تعالى
+
+494
+00:37:57,560 --> 00:38:05,560
+هيتعلق مسابقين تبعين طبيعي هعلمك تجلجش هعلمك بما
+
+495
+00:38:05,560 --> 00:38:12,550
+يمشيلك المسابق ليش أنا جاي؟ ان شاء الله تعالىطيب،
+
+496
+00:38:12,550 --> 00:38:18,530
+الآن اسلوبنا في التدريس هيكون كالتالي محاضرة،
+
+497
+00:38:18,530 --> 00:38:23,330
+مجموعة نقاش، عمل جماعي وبعض الفيديوهات والـ
+
+498
+00:38:23,330 --> 00:38:26,390
+presentation اللي هزودك فيها وممكن نعرض شغلة
+
+499
+00:38:26,390 --> 00:38:29,390
+ونتناقش فيها مع بعض حسب التفكير يعني شوية شوية
+
+500
+00:38:29,390 --> 00:38:34,250
+هتكون الأمور هتختلف المادة عن database اتنين لأنه
+
+501
+00:38:34,250 --> 00:38:37,090
+فعليا المادة مختلفة فيها ممكن تكون في interaction
+
+502
+00:38:37,090 --> 00:38:41,870
+بين أو بينك بشكل كبيراللي أنتوا بتدوروا عليه من
+
+503
+00:38:41,870 --> 00:38:47,350
+ساعة توزيع العلمات عشر علامات quizات و assignment
+
+504
+00:38:47,350 --> 00:38:53,390
+عشرة على مشاركة في نشاطة المساقى خلال الفصل إيش
+
+505
+00:38:53,390 --> 00:38:56,170
+المشاركة؟ discussion لأن ممكن تكون فيه علامات
+
+506
+00:38:56,170 --> 00:39:01,590
+وفلان طبعا هذه الأعشرة بالذات أنت فيهم صفر إلا لما
+
+507
+00:39:01,590 --> 00:39:07,210
+تشارك يعني مثلا إيش اسم اللي بجنبك عليه؟برضه علي؟
+
+508
+00:39:07,210 --> 00:39:12,270
+علي تربيع ولا علي اتنين؟ الان علي قرر انك بتبقى
+
+509
+00:39:12,270 --> 00:39:16,870
+يلعب في الجوال قول المحاضرة مش مشكلة فلازم تشاركني
+
+510
+00:39:16,870 --> 00:39:20,850
+في المحاضرة عشان يسجلك ان فعلي فلان ناشيق المحاضرة
+
+511
+00:39:20,850 --> 00:39:24,090
+هاي فلان نايم فلان ناسان فلان مشغول المحاضرة اللي
+
+512
+00:39:24,090 --> 00:39:26,990
+بتغيب فيها العذر أنا سامحك فيها في المناقشة وإذا
+
+513
+00:39:26,990 --> 00:39:29,150
+قررتي تغيب كتير هسحبلك المادة
+
+514
+00:39:33,110 --> 00:39:37,670
+مصبوط؟ عشرين في المية او عشرين علامة على ال
+
+515
+00:39:37,670 --> 00:39:43,450
+midterm عشرين علامة على final project وهذا غالبا
+
+516
+00:39:43,450 --> 00:39:46,310
+هتكون فيه تلتات او مجموعات يعني حاجة simple فيه مش
+
+517
+00:39:46,310 --> 00:39:50,550
+هتكون لوحدك واربعين في المية امتحان نهائي توزيع
+
+518
+00:39:50,550 --> 00:39:53,670
+بسيطة وسهلة يعني ممكن تروح على ال final عارف
+
+519
+00:39:53,670 --> 00:39:57,750
+بالظبط وتقدش كام علامة لك عندي وكم واحدة عشان تجيب
+
+520
+00:39:57,750 --> 00:40:03,320
+امتيازاللي بيلزبك .. كم واحد بعرف Python فيكوا
+
+521
+00:40:03,320 --> 00:40:06,960
+الشباب؟ ولا واحد .. هاي في واحد .. كويس الله يجبر
+
+522
+00:40:06,960 --> 00:40:11,660
+خاطرك فرصة تتعلم شغلة جديدة بس هذه حتكون لوحدك ال
+
+523
+00:40:11,660 --> 00:40:15,160
+Java مابتخدمناش كتير في ال .. في ال data mining
+
+524
+00:40:15,160 --> 00:40:18,660
+وإن كان ال Python هي ال trend ممكن تلاقي بس حتتغلب
+
+525
+00:40:18,660 --> 00:40:25,500
+.. حت .. لأ ماعنديش مشكلة تعرف ال SQL؟ عشي
+
+526
+00:40:28,920 --> 00:40:32,220
+هنتعرف كذلك، بيلزم نتعامل مع الـ Rapid Miner أنتم
+
+527
+00:40:32,220 --> 00:40:35,560
+ملاحظين إن المادة مافيش معاها عمل أي شباب فإنت
+
+528
+00:40:35,560 --> 00:40:42,820
+معيد العملي تبع المادة، مش أنا، أنت وبدأ المناسبة،
+
+529
+00:40:42,820 --> 00:40:47,340
+احنا أخدنا قرار في الكلية كل مستوى تالت من السنة،
+
+530
+00:40:47,340 --> 00:40:50,620
+عفوا، الرابع، من السنة الجاية، من الخطة الجديدة،
+
+531
+00:40:50,620 --> 00:40:55,490
+مافيش عمليوتالت قلصنا العملي قدر المستطاع لأنه أنت
+
+532
+00:40:55,490 --> 00:40:58,150
+اللي المفروض تكون معيد بالسنة اللي بعديها فخلصنا
+
+533
+00:40:58,150 --> 00:41:02,570
+يعني ابدا اشتغل اتعب لأ مش السنة اللي جاية هي لسه
+
+534
+00:41:02,570 --> 00:41:07,610
+عندها الخط القديمة شغال متطلبات المساق متطلبات
+
+535
+00:41:07,610 --> 00:41:10,010
+المساق حضورك إجبار يا صاحب مافيش علي علامات
+
+536
+00:41:10,010 --> 00:41:14,410
+علاماتك على نشاطك أنت جيت و تقعد هنا عشان تتنشط
+
+537
+00:41:14,410 --> 00:41:18,010
+معانا و ناخد و نعطي مع بعض فبنسجلك علامات مش عشان
+
+538
+00:41:18,010 --> 00:41:25,050
+حضوركتمام؟ 25% الشباب غياب هذا قانون الجامعة مافيش
+
+539
+00:41:25,050 --> 00:41:29,870
+موعد مسبق لل quiz دربت
+
+540
+00:41:29,870 --> 00:41:33,770
+معاكم على وجوه الكريمة الطيبة جامل هيك وانا لا ..
+
+541
+00:41:33,770 --> 00:41:37,850
+ماعش الحال بس مافيش موعد .. مافيش موعد مسبق لل
+
+542
+00:41:37,850 --> 00:41:42,460
+quizومافيش أي عذر ما ترجعنيش في quiz انت غيبت عن
+
+543
+00:41:42,460 --> 00:41:45,580
+محاضرته انه ماكنش معايا خبر يا دكتور وانا بقولك
+
+544
+00:41:45,580 --> 00:41:49,620
+مافيش quiz ذات الله يمن عليك بتمام الصحة و العافية
+
+545
+00:41:49,620 --> 00:41:54,320
+انت و والدك و كل أحبابك و يمن عليك و بالرزق الوفير
+
+546
+00:41:54,320 --> 00:41:58,600
+تمام؟ و تجيني كل محاضرة على البدري على موعدها عشان
+
+547
+00:41:58,600 --> 00:42:02,740
+ما تغيبش لأن هذه الأمور اللي ممكن تمنعك لتيجي يعني
+
+548
+00:42:02,740 --> 00:42:08,660
+طيب عادة بالزمن هان اتراجع باستمرارلأن التقييم
+
+549
+00:42:08,660 --> 00:42:11,200
+هيكون مختلف عن العوام الماضية أو عن ما انت عهدته
+
+550
+00:42:11,200 --> 00:42:14,800
+سابقا جوالك
+
+551
+00:42:14,800 --> 00:42:17,480
+على الأقل يكون صامت خصوصا انه قاعتنا هي في اللي
+
+552
+00:42:17,480 --> 00:42:21,460
+احنا عاملا بنسجل ال video و بنسجل المحاضرة و
+
+553
+00:42:21,460 --> 00:42:25,200
+بالتالي يعني يكفيني صوتي و صوتك هو اللي يكونوا
+
+554
+00:42:25,200 --> 00:42:31,700
+موجودين صوت جوالاتنا مافيش داعي لحكمة الفصل أو
+
+555
+00:42:31,700 --> 00:42:38,410
+السنة هاي استمتع بحياة قدر المستطاع تمام؟و لا تنسى
+
+556
+00:42:38,410 --> 00:42:42,670
+نصيبك من الدنيا و أحسن كما أحسن الله إليك كمل
+
+557
+00:42:42,670 --> 00:42:47,310
+الآية بس إحنا اتعودنا ناخد ال .. إيه؟ ال .. إيه؟
+
+558
+00:42:47,310 --> 00:42:47,630
+ال .. إيه؟ ال .. إيه؟ ال .. إيه؟ ال .. إيه؟ ال ..
+
+559
+00:42:47,630 --> 00:42:48,470
+إيه؟ ال .. إيه؟ ال .. إيه؟ ال .. إيه؟ ال .. إيه؟
+
+560
+00:42:48,470 --> 00:42:50,130
+ال .. إيه؟ ال .. إيه؟ ال .. إيه؟ ال .. إيه؟ ال ..
+
+561
+00:42:50,130 --> 00:42:51,550
+إيه؟ ال .. إيه؟ ال .. إيه؟ ال .. إيه؟ ال .. إيه؟
+
+562
+00:42:51,550 --> 00:42:53,190
+ال .. إيه؟ ال .. إيه؟ ال .. إيه؟ ال .. إيه؟ ال ..
+
+563
+00:42:53,190 --> 00:42:56,990
+إيه؟ ال .. إيه؟ ال .. إيه؟ ال .. إيه؟ ال ..
+
+564
+00:42:56,990 --> 00:42:59,510
+إيه؟ ال ..
+
+565
+00:43:07,660 --> 00:43:11,920
+تمام؟ حتى كثير من أهل الدين بت .. اللي بيقولوا إن
+
+566
+00:43:11,920 --> 00:43:16,900
+حياتك أو أقدارك صنعوا يديك يقال إن يوسف عليه
+
+567
+00:43:16,900 --> 00:43:21,100
+السلام لما طال عليه السجن قال يا ربي طال .. طال
+
+568
+00:43:21,100 --> 00:43:28,680
+السجن اه قال لو سألت العفوة لعفينك و قال ربي السجن
+
+569
+00:43:28,680 --> 00:43:32,970
+و أحبه إليا مما .. ماقالش ربي اصرف عنك ايه دهونوهو
+
+570
+00:43:32,970 --> 00:43:35,770
+قدم السجن عن طلب الله الرحمن فاخد معينة له
+
+571
+00:43:35,770 --> 00:43:39,910
+وبالتالي انت بيه لا لفظك ولا نيتك انت وين بتكون
+
+572
+00:43:39,910 --> 00:43:44,770
+طبعا هاي الدرس في التنمية البشرية، كمل؟ يللا، الآن
+
+573
+00:43:44,770 --> 00:43:50,110
+بيظنك تصبر لإنه مش كلش على كيفك، وبدك تتعدي في
+
+574
+00:43:50,110 --> 00:43:52,890
+المساق هذا وفي الحياة كلها يتهك، المساق مش ممكن
+
+575
+00:43:52,890 --> 00:43:56,170
+يجي ع كيفك دائما، ولا مدرس المساق، ولا علامات
+
+576
+00:43:56,170 --> 00:43:57,450
+المساق، خلاش راك هاشم
+
+577
+00:44:00,400 --> 00:44:05,460
+لأ، انت شوف، انت بتتمنى، بس انت اجتهدت عشان تحصل
+
+578
+00:44:05,460 --> 00:44:09,700
+عليها في الآخر، يعني قد ممكن تجدها دو ما ترضاش، بس
+
+579
+00:44:09,700 --> 00:44:12,640
+في الآخر هذا أصبح أمر واقعي موجود، فبدها تعدي في
+
+580
+00:44:12,640 --> 00:44:17,040
+الآخر، لازم تصبر كويس، وفي الآخر لازم تتمتع
+
+581
+00:44:17,040 --> 00:44:20,700
+بالجدية، لأن مش كل حياتنا لعوم، عشان تحقق أهدافك،
+
+582
+00:44:20,700 --> 00:44:23,340
+شباب من المساقات الممتعة، اللي ممكن تستفيد منه
+
+583
+00:44:23,340 --> 00:44:28,210
+بشكل كويسانشي اتضيعوا وانشي اتستعلم وانا بحاول
+
+584
+00:44:28,210 --> 00:44:34,870
+اعلمك قدر ما بستطيع ان شاء الله تعالى خلص
+
+585
+00:44:34,870 --> 00:44:40,650
+السلبس هندردش شوية صغيرة كمقدمة كمقدمة عشان ننتهي
+
+586
+00:44:40,650 --> 00:44:45,830
+زي ما انتهينا في المحاضرة السابقة الآن في عندي هرم
+
+587
+00:44:45,830 --> 00:44:50,030
+بيسميه هرم المعلومات او هرم البياناتعادةً إحنا
+
+588
+00:44:50,030 --> 00:44:53,370
+بنتكلم Data Mining ونتكلم Data Base، مظبوط؟ ونتكلم
+
+589
+00:44:53,370 --> 00:44:56,910
+Data Communication، كل شيء Data، مافيش معلومات،
+
+590
+00:44:56,910 --> 00:45:03,250
+لأن الـ Data هذه بيلزمها سياق معين عشان تصير
+
+591
+00:45:03,250 --> 00:45:08,590
+معلومة، بنفعش وإحنا نيجي بنتكلم، بنفكر، عاملين
+
+592
+00:45:08,590 --> 00:45:12,530
+محاضرة أو جلسة حوار عشان شو كيف بدنا نسقط صفقة
+
+593
+00:45:12,530 --> 00:45:19,170
+القرن، نقط واحد يقول لي والله عماد راجل طيب،ويا عز
+
+594
+00:45:19,170 --> 00:45:27,150
+ما تنعزم عنده معلومة data عماد راجل كريم ومقدّم
+
+595
+00:45:27,150 --> 00:45:31,730
+أكل طيب بهمش، شو دخلها في السياق اللي احنا بنتكلم
+
+596
+00:45:31,730 --> 00:45:37,870
+فيه حتى لو كانت معلومة قيمة فقدت قيمتها، ليش؟ مش
+
+597
+00:45:37,870 --> 00:45:42,770
+في المكان الصح فبالتالي إذا ال data هاي اتوفر لها
+
+598
+00:45:42,770 --> 00:45:48,710
+context مناسبمعناته انا بتكلم على information صارت
+
+599
+00:45:48,710 --> 00:45:53,150
+معلومة والمعلومة طبعا بمعناها أو بقيمتها بالوقت أو
+
+600
+00:45:53,150 --> 00:45:59,550
+بالزمان اللي قيلت فيه المعلومات هذه إذا نظمتها
+
+601
+00:45:59,550 --> 00:46:05,490
+rules المعلومات هذه إذا صارت فيه rules بتحكمها و
+
+602
+00:46:05,490 --> 00:46:10,110
+بتطبقها معناته احنا بنتكلم على knowledge أو معرفة
+
+603
+00:46:10,110 --> 00:46:11,270
+الآن
+
+604
+00:46:19,140 --> 00:46:24,660
+بسمع إن الصائم يحق له أن يفطر في رمضان أو المسلم
+
+605
+00:46:24,660 --> 00:46:28,140
+يحق له يفطر في رمضان إيش بتقول يا رادي الصيام فرض
+
+606
+00:46:28,140 --> 00:46:33,900
+.. فرض في شروط هيلاحظ إن كان في عندي معلومة الآن
+
+607
+00:46:33,900 --> 00:46:37,460
+الشروط هذه هي اللي خلتها معرفة لإن المعرفة بتعتمد
+
+608
+00:46:37,460 --> 00:46:40,280
+عليها تطبيق يا جماعة الخير المعرفة بترتب عليها
+
+609
+00:46:40,280 --> 00:46:46,300
+تطبيق على خلاف المعلومة الآن طب مين اللي بيقدر أنت
+
+610
+00:46:46,300 --> 00:46:50,970
+بصحيح أقولك تفطر في رمضان ولا لأ؟إتنين طبيب مسلم
+
+611
+00:46:50,970 --> 00:46:57,050
+حاذق أو شاطر أو أنت لو كنت من أهل التقوى ونكلكوا
+
+612
+00:46:57,050 --> 00:47:00,950
+كذلك إن شاء الله تبارك وتعالى، مصبوط؟ ماينفعش حد
+
+613
+00:47:00,950 --> 00:47:04,590
+تاني يقولك يا زلمة أفطر أنت تعبان، أنت مريض، و
+
+614
+00:47:04,590 --> 00:47:07,990
+الله أدّاك رخصة أنك تفطر في رمضان، صحيح، بس أنت
+
+615
+00:47:07,990 --> 00:47:11,270
+كمان بتقيم نفسك أنا فعليا أهل الرخصة هي ولا لأ؟
+
+616
+00:47:11,990 --> 00:47:14,970
+طبعا هذه الكلام على قدر إيمانك بالله تبارك وتعالى
+
+617
+00:47:14,970 --> 00:47:18,670
+و تقواك إلهم الآن ال knowledge هذه أو المعرفة هذه
+
+618
+00:47:18,670 --> 00:47:24,090
+مع التجارب العملية صارت wisdom صارت حكمة نصينا
+
+619
+00:47:24,090 --> 00:47:28,890
+نقول فلان حكيم ليش؟ عنده معرفة واسعة و عنده تجربة
+
+620
+00:47:28,890 --> 00:47:32,210
+كبيرة في الحياة أو في المجال اللي بيشتغل فيه فهي
+
+621
+00:47:32,210 --> 00:47:42,170
+ال wisdom أعلى درجات المعرفة ومن أوتي الحكمةفقد
+
+622
+00:47:42,170 --> 00:47:49,310
+أوتي خيرا كثيرا طيب data mining ايش ال data mining
+
+623
+00:47:49,310 --> 00:47:54,030
+اولا ال data mining هي عبارة عن equivalent term ل
+
+624
+00:47:54,030 --> 00:48:01,430
+knowledge discovery from data استكشاف المعرفة من
+
+625
+00:48:01,430 --> 00:48:03,350
+البيانات KDD من ال data
+
+626
+00:48:07,360 --> 00:48:14,560
+data mining is extracting an interesting أنا هو
+
+627
+00:48:14,560 --> 00:48:26,580
+أنا بده أحط خط تحت interesting شو
+
+628
+00:48:26,580 --> 00:48:32,720
+يعني interesting ترجم ليها بالعربي مهمش ممتع
+
+629
+00:48:33,370 --> 00:48:40,130
+شيق، مثير، مظبوط؟ كل ال terms هاي بتصف باتجاه واحد
+
+630
+00:48:40,130 --> 00:48:44,990
+إنه أنا ال knowledge اللي أنا بدي أدور عليها لازم
+
+631
+00:48:44,990 --> 00:48:51,710
+يكون لها تأثير الآن بعرفلك مصطلح interesting non
+
+632
+00:48:51,710 --> 00:48:58,230
+-trivial مش تقليدي مش تقليدي يعني فيش شغلة جديدة
+
+633
+00:48:59,370 --> 00:49:03,470
+تمام؟ يعني أقول جديد هذا يعني مش الناس شايفة شبهه
+
+634
+00:49:03,470 --> 00:49:07,550
+emblest
+
+635
+00:49:07,550 --> 00:49:11,830
+هو ضمن في ال data مش أي واحد بتطلع في ال data
+
+636
+00:49:11,830 --> 00:49:15,530
+بيقدر يشوفها طبعا أنا بتكلم على interesting
+
+637
+00:49:15,530 --> 00:49:18,190
+pattern عشان تكتمل الصورة الخطوة اللي المفروض
+
+638
+00:49:18,190 --> 00:49:25,170
+يكونها ان extracting of interesting pattern الان
+
+639
+00:49:25,170 --> 00:49:28,970
+ال interesting pattern هذازي ما قلنا non-trivial
+
+640
+00:49:28,970 --> 00:49:32,470
+غير تقليدي emplaced ضمن في ال data بحتاج إلى جود
+
+641
+00:49:32,470 --> 00:49:35,690
+استخراجه ولا كل الناس صارت هتشتغل مناقبين عن الذهب
+
+642
+00:49:35,690 --> 00:49:44,170
+و تحوش الذهب ولا لا previously unknown ماحدش
+
+643
+00:49:44,170 --> 00:49:46,870
+بيعرفه مسبقا ال knowledge أو ال pattern هذا ماحدش
+
+644
+00:49:46,870 --> 00:49:50,130
+عرضه لأنه إذا حد عرضه سابقا انت قاعد بتكرر شغل
+
+645
+00:49:50,130 --> 00:49:52,690
+الآخرين potentially
+
+646
+00:49:53,870 --> 00:49:58,110
+useful لازم يكون بترتب عليه action لازم يكون فيه
+
+647
+00:49:58,110 --> 00:50:02,130
+مرافعة مابينفعش اروح اقول اللي والله اه اللي ممكن
+
+648
+00:50:02,130 --> 00:50:05,050
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+649
+00:50:05,050 --> 00:50:05,070
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+650
+00:50:05,070 --> 00:50:05,250
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+651
+00:50:05,250 --> 00:50:06,110
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+652
+00:50:06,110 --> 00:50:08,510
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+653
+00:50:08,510 --> 00:50:08,590
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+654
+00:50:08,590 --> 00:50:09,270
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+655
+00:50:09,270 --> 00:50:09,270
+اللي اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+656
+00:50:09,270 --> 00:50:17,950
+اللي اللي اللي اللي اللي اللي اللي اللي اللي
+
+657
+00:50:17,950 --> 00:50:23,280
+الليممتاز، إيش الـ action اللي بتقدر تاخده عليه؟
+
+658
+00:50:23,280 --> 00:50:28,920
+تمنع خصوف القمر أو تزرعش رز فكل الحالتين مستحيلة،
+
+659
+00:50:28,920 --> 00:50:33,620
+هذا useless ما هي كذا، معلومة بتصير زي إيش
+
+660
+00:50:33,620 --> 00:50:39,380
+المعلومات اللي لا تصمن ولا تجني من جوعك الآن ال
+
+661
+00:50:39,380 --> 00:50:44,240
+data mining ال data mining تعرف تعريف آخر ال
+
+662
+00:50:44,240 --> 00:50:53,030
+process of identifyingالعملية الغير تقليدية أو
+
+663
+00:50:53,030 --> 00:50:58,350
+الغير سهلة أو الغير بسيطة لتعريف valid شو يعني
+
+664
+00:50:58,350 --> 00:51:06,350
+valid؟ صالح، دقيق، صح، يعني بنقدر نثق فين؟ النتيجة
+
+665
+00:51:06,350 --> 00:51:13,190
+تبعته potentially useful مفيد و هيترتب عليه action
+
+666
+00:51:13,190 --> 00:51:20,110
+and ultimately understandableلازم يكون مفهوم لأنه
+
+667
+00:51:20,110 --> 00:51:23,510
+إذا أنا بدي أجيب شغلة جديدة للناس المعنية يا مؤمن
+
+668
+00:51:23,510 --> 00:51:27,410
+لازم تفهم الكلام اللي أنا بقوله عشان تقدر تاخد
+
+669
+00:51:27,410 --> 00:51:34,770
+عليه action بينفعش أجي أتكلم مع تعوض مثلا بعمل
+
+670
+00:51:34,770 --> 00:51:38,030
+system عشان يساعد الأطباء في ال diagnosis و أجي
+
+671
+00:51:38,030 --> 00:51:41,930
+أقولهم هذي 01 و لو عملتلها أس تربيع وكذا و مش عارف
+
+672
+00:51:41,930 --> 00:51:46,070
+.. الكلام بيعنهوش اديله المعلومة عشان هيك هامت ال
+
+673
+00:51:46,070 --> 00:51:50,060
+presentationاتديله المعلومة بالشكل اللي هو يفهمه
+
+674
+00:51:50,060 --> 00:51:54,460
+لأنه إذا هو أخده يا سامير .. يا عارف؟ سامير ولا
+
+675
+00:51:54,460 --> 00:51:59,100
+عارف؟ سامير عارف لو هو أخد المعلومة بالشكل اللي
+
+676
+00:51:59,100 --> 00:52:03,220
+بيفهمها تمام؟ هيبني عليها action، هتصير الشغل
+
+677
+00:52:03,220 --> 00:52:08,300
+useful بالنسبة له طبعاً هاي تعريف ال pattern هي
+
+678
+00:52:08,300 --> 00:52:11,540
+عبارة عن arrangement of repeated parts هي الشغلات
+
+679
+00:52:11,540 --> 00:52:17,870
+.. هو أهم شغلة فيها تكرار والترتيبلأنه لما بيظهر
+
+680
+00:52:17,870 --> 00:52:21,950
+النسق أو الـ pattern هذا بنفسي كيفية بصير اتكلم
+
+681
+00:52:21,950 --> 00:52:25,190
+عليه better تبع لنسبة معينة محددة يا محمد زي ما
+
+682
+00:52:25,190 --> 00:52:30,450
+انت قولت valid هذا لازم يكون true لما أنا بقادي
+
+683
+00:52:30,450 --> 00:52:33,770
+اطبق عليه data جديدة يعني انت بتقولي انا و الله
+
+684
+00:52:33,770 --> 00:52:36,950
+okay انا في عندي rule او في عندي algorithm او في
+
+685
+00:52:36,950 --> 00:52:42,030
+عندي data product ممكن يعمل classification لكذا
+
+686
+00:52:42,030 --> 00:52:47,360
+okay على ال all data صحيحأبتعالي نجرب الـ real
+
+687
+00:52:47,360 --> 00:52:50,460
+data اللي موجودة عندنا حقيقية جدّيش هو صحيح فيها
+
+688
+00:52:50,460 --> 00:52:55,040
+تمام؟ وبناء عليه أنا لازم أقبله novel زي ما قولنا
+
+689
+00:52:55,040 --> 00:52:59,200
+ما حد شافه actionable لازم يكون عليه شغلة مفهومة
+
+690
+00:52:59,200 --> 00:53:02,760
+وزي ما قولنا سابقا understandable لازم يكون مفهوم
+
+691
+00:53:02,760 --> 00:53:06,560
+في البيئة اللي أنا بتكلم فيها عشان نقدر ناخد ال
+
+692
+00:53:06,560 --> 00:53:10,380
+action ليش احنا محتاجين ال data mining؟ الآن
+
+693
+00:53:10,380 --> 00:53:16,890
+البيانات عامالها بتتضخمبشكل مخيف مصادر البيانات كل
+
+694
+00:53:16,890 --> 00:53:20,790
+شيء اليوم أصبحت موجودة عندنا وبنقدر نجمعها بكل
+
+695
+00:53:20,790 --> 00:53:27,210
+بساطة data collection و data availability البيانات
+
+696
+00:53:27,210 --> 00:53:30,930
+متاحة بس خد automated data collection tool موجود
+
+697
+00:53:30,930 --> 00:53:34,770
+فيه عندى أدوات في مجال أنا أجمع بيانات بشكل تلقائي
+
+698
+00:53:34,770 --> 00:53:42,070
+أه فيه حط sensors اعمل برنامج يعمل scrabbing لل
+
+699
+00:53:42,070 --> 00:53:46,050
+websitesأو الـ social media sites أو الـ networks
+
+700
+00:53:46,050 --> 00:53:50,450
+فانت بتقدر تجمع البيانات بشكل .. الآن كذلك أعظم
+
+701
+00:53:50,450 --> 00:53:56,410
+المؤسسات صحية وتعليمية واجتماعية في البلدان عندها
+
+702
+00:53:56,410 --> 00:54:00,990
+data ضخمة جدا بتعداد الناس اللي ساكنينها وبالتالي
+
+703
+00:54:00,990 --> 00:54:07,550
+ممكن تستفيد منها الآن أهم تلت مصادر للناس للبيانات
+
+704
+00:54:07,550 --> 00:54:12,230
+ال business، التجارة، طبعا أنا بتكلم عن الاقتصاد
+
+705
+00:54:13,680 --> 00:54:22,520
+الـ Science العلوم كلها كانت طبية اجتماعية تعليمية
+
+706
+00:54:22,520 --> 00:54:27,960
+زراعية في كل المجالات في العلوم ال society في
+
+707
+00:54:27,960 --> 00:54:31,420
+الحياة الاجتماعية ما بين الناس في الأخبار و ال
+
+708
+00:54:31,420 --> 00:54:33,800
+digital cameras و ال YouTube و القنوات و الصفحات
+
+709
+00:54:33,800 --> 00:54:38,160
+فانت فعليا عندك هذه أصبحت مصادر بيانات مهمة جدا
+
+710
+00:54:38,160 --> 00:54:46,580
+ممكن تبني عليها decision فعليا أصبحنابنغرق في
+
+711
+00:54:46,580 --> 00:54:53,380
+البيانات و بنتدور جوعا للمعرفة الآن بعض الناس أو
+
+712
+00:54:53,380 --> 00:54:55,940
+بعض المفسرين كانوا بيقولوا في القرآن أو في تفسير
+
+713
+00:54:55,940 --> 00:54:59,960
+آية القرآن و تلك الأيام نداولها بين الناس يعني
+
+714
+00:54:59,960 --> 00:55:07,260
+أحداث التاريخ تتكرر بأشخاص مختلفةالـ behavior واحد
+
+715
+00:55:07,260 --> 00:55:11,720
+والـ action واحد يعني ما نتشوف مش غريب أن نقول
+
+716
+00:55:11,720 --> 00:55:16,660
+والله انتشر فيروس في الصين مثلا وقضى على 1500 شخص
+
+717
+00:55:16,660 --> 00:55:20,620
+طب ما هو طعون عمواس قبل مش عارف كام سنة برضه قضى
+
+718
+00:55:20,620 --> 00:55:25,460
+على نفس العدد ويزيد تقريباطب شو الاختلاف؟ مُسمّى
+
+719
+00:55:25,460 --> 00:55:28,580
+الـ Virus أو مُسمّى البكتيريا أو مُسبّب المرض؟ حسب
+
+720
+00:55:28,580 --> 00:55:33,140
+العلوم بتختلف الأمور وبالتالي الـ Historical Data
+
+721
+00:55:33,140 --> 00:55:38,960
+المتراكمة عندي بتحتوي على Knowledge تخدمني في
+
+722
+00:55:38,960 --> 00:55:43,160
+مستقبلي لأن إذا أتعرفت على الحدث سابقًا بتعرف على
+
+723
+00:55:43,160 --> 00:55:46,980
+كيف أتجنبه أو ممكن أنا أحاول أستفيد من الخبرة
+
+724
+00:55:46,980 --> 00:55:51,560
+السابقة وأتجنبه وبالتالي بما أن الحاجة أم الإختراع
+
+725
+00:55:52,300 --> 00:55:57,680
+فاحنا فعلياً بحاجة إلى automated analysis للـ
+
+726
+00:55:57,680 --> 00:56:02,400
+historical data أو لل big data اللي موجودة عندنا
+
+727
+00:56:02,400 --> 00:56:08,020
+حتى نحصل على مطلوبنا من البيانات اللي موجودة عندنا
+
+728
+00:56:08,020 --> 00:56:12,400
+أنا هيك اليوم خلصت المقدمة تبعتي اللي تناولتها ال
+
+729
+00:56:12,400 --> 00:56:16,720
+syllabus والمقدمة البسيطة عن ال data mining في حد
+
+730
+00:56:16,720 --> 00:56:20,840
+عنده أي سؤال يا شباب؟ في حد عنده أي اعتراض على
+
+731
+00:56:20,840 --> 00:56:22,060
+الخطة؟
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/zzmXFQBnsgA.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/zzmXFQBnsgA.srt
new file mode 100644
index 0000000000000000000000000000000000000000..6b9f854e20d177d63e845067c89db7393ddeac13
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/zzmXFQBnsgA.srt
@@ -0,0 +1,1406 @@
+1
+00:00:00,980 --> 00:00:03,820
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:03,820 --> 00:00:10,700
+أهلا وسهلا بكم في محاضرتنا الجديدة المصورة لمساب
+
+3
+00:00:10,700 --> 00:00:14,820
+تنقيب البيانات اليوم إن شاء الله تعالى، سنتكلم عن
+
+4
+00:00:14,820 --> 00:00:20,610
+chapter regression، هنا في الـ Regression نتكلم عن
+
+5
+00:00:20,610 --> 00:00:26,830
+المهمة الثانية في التصنيف التنبؤي predictive category للـ
+
+6
+00:00:26,830 --> 00:00:30,650
+Data Mining، اتفقنا من البداية أن Data Mining
+
+7
+00:00:30,650 --> 00:00:33,730
+تنقسم إلى two tasks
+
+8
+00:00:36,820 --> 00:00:41,280
+واحدة تنبؤية predictive  والثانية وصفية descriptive، وتكلمنا تحت
+
+9
+00:00:41,280 --> 00:00:47,000
+التصنيف predictive tasks  عنده
+
+10
+00:00:47,000 --> 00:00:50,280
+التصنيف classification وهي التنبؤ بـ class label أو بـ
+
+11
+00:00:50,280 --> 00:00:58,030
+category value أو بـ nominal value، بينما المهمة task
+
+12
+00:00:58,030 --> 00:01:00,710
+الثانية هي الـ Regression والتنبؤ بالقيم المستمرة Continuous
+
+13
+00:01:00,710 --> 00:01:04,570
+Value، وفي المقابل لدينا في الـ Descriptive Task
+
+14
+00:01:04,570 --> 00:01:07,730
+كان في عندنا Clustering وعندنا Association Rules
+
+15
+00:01:07,730 --> 00:01:11,070
+وفي عندنا الـ Outlier Detection، وهذه سنتكلم عنها
+
+16
+00:01:11,070 --> 00:01:15,430
+في المحاضرات القادمة، فلنبدأ مع الـ Regression
+
+17
+00:01:16,730 --> 00:01:19,590
+الأمور التي سنتناولها في محاضرتنا اليوم:
+
+18
+00:01:19,590 --> 00:01:23,590
+مقدمة introduction و الـ Linear Regression، أو نشرحها، و
+
+19
+00:01:23,590 --> 00:01:28,610
+نكمل بعدها في...ممكن في فيديو آخر أو في تسجيل
+
+20
+00:01:28,610 --> 00:01:32,850
+آخر حسب كيف نمشي أو نُخصص  أو نستغل من الوقت
+
+21
+00:01:32,850 --> 00:01:36,210
+الموجود عندنا، طبعاً، عندما أتحدث عن الـ Regression
+
+22
+00:01:36,210 --> 00:01:41,130
+أنا أُشير إلى أن الـ Regression يُستخدم من أجل
+
+23
+00:01:41,130 --> 00:01:45,150
+التنبؤ
+
+24
+00:01:47,830 --> 00:01:54,390
+بمدى من القيم للقيم العددية range of numeric values
+
+25
+00:01:54,390 --> 00:01:59,970
+numeric values، وهنا
+
+26
+00:01:59,970 --> 00:02:04,770
+أتحدث عن القيم المستمرة continuous value بالتحديد، أتحدث عن
+
+27
+00:02:04,770 --> 00:02:09,650
+continuous value بالتحديد، طبعاً تقنية Regression
+
+28
+00:02:09,650 --> 00:02:16,440
+تُستخدم في موضوع التنبؤ prediction، كما
+
+29
+00:02:16,440 --> 00:02:20,200
+قلنا، هي واحدة من مهام التنبؤ prediction task  الموجودة
+
+30
+00:02:20,200 --> 00:02:23,280
+فيها من أجل أن أتوقع قيماً، كما قلنا، مستمرة continuous
+
+31
+00:02:23,280 --> 00:02:28,100
+value، الربح profit، قيمة المبيعات، الـ
+
+32
+00:02:28,100 --> 00:02:32,420
+ديون debit، أسعار المبيعات sales،  معدلات الاقتراض debit rates، قيمة القروض أو
+
+33
+00:02:32,420 --> 00:02:37,280
+الفوائد، قيم المنازل house values، درجات الحرارة
+
+34
+00:02:37,280 --> 00:02:42,740
+temperature، أو المسافات التي يمكن استخدامها، وكل هذه
+
+35
+00:02:42,740 --> 00:02:45,700
+التنبؤات بأي قيمة مستمرة continuous value، سواء كان في هذا المثال
+
+36
+00:02:45,700 --> 00:02:53,280
+أو  أوزان أو أعمار أو أطوال أو مدة زمنية
+
+37
+00:02:53,280 --> 00:02:57,420
+إلى آخره، نحن نتحدث هنا عن أي قيمة رقمية numeric
+
+38
+00:02:57,420 --> 00:03:01,020
+number  تظهر أمامي أو numeric value،  معناها أنا
+
+39
+00:03:01,020 --> 00:03:04,660
+أتحدث عن Regression، طبعاً الـ Regression عندما
+
+40
+00:03:04,660 --> 00:03:07,460
+أبدأ بالتحدث أو كما يُطلق عليه البعض Regression
+
+41
+00:03:07,460 --> 00:03:12,380
+analysis، أستخدمها لأجد العلاقة بين الـ
+
+42
+00:03:12,380 --> 00:03:16,080
+Independent attribute أو الـ Independent variable
+
+43
+00:03:16,080 --> 00:03:24,240
+التي هي الـ X والـ Dependent variable التي هي الـ Y
+
+44
+00:03:24,240 --> 00:03:28,320
+طبعاً، الرسم واضح جداً، يُظهر الـ Independent
+
+45
+00:03:28,320 --> 00:03:32,880
+value التي هي قيمة الـ X، وفي عندنا الـ Dependent
+
+46
+00:03:32,880 --> 00:03:36,900
+value أو الـ attribute أو الـ variable، عفواً، التي هي
+
+47
+00:03:36,900 --> 00:03:42,150
+قيمة الـ Y، وطبعاً عندما أتحدث عن الـ Regression
+
+48
+00:03:42,150 --> 00:03:48,210
+يمكن تصنيفها إلى نوعين:  Simple Regression و
+
+49
+00:03:48,210 --> 00:03:50,730
+عندما أتحدث عن اسمها Simple Regression، معناته أنا
+
+50
+00:03:50,730 --> 00:03:58,810
+أتحدث عن أبسط أنواع التنبؤ، وهذه عادةً تتضمن
+
+51
+00:03:58,810 --> 00:04:02,510
+أو Simple Regression تتضمن فقط two variables، two
+
+52
+00:04:02,510 --> 00:04:05,010
+variables، نعم، two variables، واحد يكون Dependent
+
+53
+00:04:05,010 --> 00:04:08,920
+variable، والثاني يكون Independent، طبعاً واحد يكون
+
+54
+00:04:08,920 --> 00:04:12,560
+عندي التوضيحي explanatory والثاني يكون، وهي الـ
+
+55
+00:04:12,560 --> 00:04:17,620
+Response كما سميناه، يعني الآن الـ Y هي الـ
+
+56
+00:04:17,620 --> 00:04:20,620
+Dependent والـ X هي الـ Independent، لا تنسوا من
+
+57
+00:04:20,620 --> 00:04:24,520
+الأمثلة الموجودة التي أتحدث عنها:  السكان population و
+
+58
+00:04:24,520 --> 00:04:30,100
+إنتاج الغذاء food production، زيادة السكان
+
+59
+00:04:30,100 --> 00:04:34,860
+والحاجة لإنتاج الغذاء الموجودة لديهم، طبعاً لو
+
+60
+00:04:34,860 --> 00:04:37,580
+أنا جئت وتحدثت، أردت التحدث في هذه الجزئية بشكل
+
+61
+00:04:37,580 --> 00:04:41,760
+مفصل، لو افترضت أن لدينا هنا رسم high
+
+62
+00:04:41,760 --> 00:04:47,000
+high
+
+63
+00:04:47,000 --> 00:04:51,770
+X تمثل، تقول لك من مرتبط بمن، لو سألتكم سؤال
+
+64
+00:04:51,770 --> 00:04:56,710
+الكُلّ، من مرتبط بمن، أو من معتمد على من؟ زيادة
+
+65
+00:04:56,710 --> 00:05:01,630
+السكان population معتمدة على إنتاج الغذاء، أم
+
+66
+00:05:01,630 --> 00:05:09,770
+إنتاج الغذاء معتمد على زيادة السكان؟ نعم، معناته أنا
+
+67
+00:05:09,770 --> 00:05:11,890
+أتحدث هنا، أتحدث عن population
+
+68
+00:05:14,460 --> 00:05:18,780
+هي الـ Independent Variable، لأنه حسب العدد السكاني
+
+69
+00:05:18,780 --> 00:05:23,200
+أنا أتحدث عن أنني أُريد إنتاج غذاء، وهنا أتحدث
+
+70
+00:05:23,200 --> 00:05:31,540
+عن food production، الآن لو نظرت، كان في عندي
+
+71
+00:05:31,540 --> 00:05:37,180
+معادلة خطية بهذا الشكل، ماذا يعني هذا؟ يعني كلما
+
+72
+00:05:37,180 --> 00:05:41,220
+يزيد عدد السكان
+
+73
+00:05:45,780 --> 00:05:50,120
+سيزيد عند من الحاجة
+
+74
+00:05:50,120 --> 00:05:55,400
+إلى إنتاج غذائي أكبر، وهذه هي العلاقة، هذا مفهوم الـ
+
+75
+00:05:55,400 --> 00:05:58,180
+prediction، يعني لو افترضت أن السكان سيكون
+
+76
+00:05:58,180 --> 00:06:02,660
+عددهم 200 مليار،
+
+77
+00:06:02,660 --> 00:06:09,760
+معناته يجب أن يكون لديهم كمية غير معروفة من الغذاء، تمام
+
+78
+00:06:14,860 --> 00:06:17,280
+يعني عندما أتحدث عن الـ Simple Regression، أتحدث
+
+79
+00:06:17,280 --> 00:06:20,740
+عن أن هناك فقط two variables، واحد Independent واحد
+
+80
+00:06:20,740 --> 00:06:24,120
+Dependent، بينما في الـ Multiple Regression، معناته أنا
+
+81
+00:06:24,120 --> 00:06:30,640
+لدي أكثر من Independent Variable، لاحظوا في
+
+82
+00:06:30,640 --> 00:06:34,660
+الحالة الأولى، تكلمت أن لدي 2
+
+83
+00:06:34,660 --> 00:06:38,180
+variables فقط، مجموعة البيانات data set أو المهمة task الخاصة بي
+
+84
+00:06:38,180 --> 00:06:40,760
+فقط 2 variables، ومن هنا أنا أتحدث مباشرةً واحد
+
+85
+00:06:40,760 --> 00:06:44,420
+Dependent والثاني Independent، لأنه مستحيل في الـ
+
+86
+00:06:44,420 --> 00:06:49,120
+predictive task أن يكون لدي الاثنان Independent، فيجب
+
+87
+00:06:49,120 --> 00:06:52,580
+أن يكون واحد Dependent واحد Independent، عندما جئنا
+
+88
+00:06:52,580 --> 00:06:55,500
+نتحدث عن الـ Multiple Regression، هنا قلنا الـ
+
+89
+00:06:55,500 --> 00:06:57,800
+Multiple Regression، معناته أنا أتحدث عن أكثر من one
+
+90
+00:06:57,800 --> 00:07:00,640
+more than one Independent، لدي أكثر من Independent
+
+91
+00:07:00,640 --> 00:07:04,190
+attribute، هل يوجد لدي الـ Dependent attribute؟ يجب
+
+92
+00:07:04,190 --> 00:07:08,610
+أن يكون، وإلا ستكون المهمة task وصفية descriptive وليست تنبؤية predictive
+
+93
+00:07:08,610 --> 00:07:13,930
+مثل أسعار المنازل، لو سألتكم، أسعار البيوت
+
+94
+00:07:13,930 --> 00:07:23,350
+ما الذي يحكمها؟ أمور كثيرة، مساحة البناء، الـ
+
+95
+00:07:23,350 --> 00:07:29,210
+location الموقع، السعر price، وقت البيع، موسم البيع
+
+96
+00:07:31,480 --> 00:07:36,220
+أسعار المنازل المشابهة، وأمور كثيرة قد تُحكم
+
+97
+00:07:36,220 --> 00:07:39,380
+فيها، هذه كلها تُجرى prediction، لو جئت و
+
+98
+00:07:39,380 --> 00:07:46,200
+تحدثت عن العلاقة بين مرض السكري، حفظكم الله، و
+
+99
+00:07:46,200 --> 00:07:51,820
+جميع المسلمين، إن شاء الله، وقياسات الجسم human body
+
+100
+00:07:51,820 --> 00:07:54,160
+measurement
+
+101
+00:07:58,120 --> 00:08:04,500
+المؤشرات أو القياسات المتعلقة بجسم الإنسان: طوله و
+
+102
+00:08:04,500 --> 00:08:12,000
+وزنه، عمره، اللهم صلِّ على سيدنا محمد، سلوكه behavior
+
+103
+00:08:12,000 --> 00:08:16,030
+هل من بين هذه الأمور التي ذكرناها
+
+104
+00:08:16,030 --> 00:08:18,750
+فقط يؤثر في السكري؟ أن يكون موجوداً أم لا؟ لا، بالطبع لا
+
+105
+00:08:18,750 --> 00:08:21,990
+فهذه كلها مجتمعة، والنسب الموجودة هي
+
+106
+00:08:21,990 --> 00:08:24,910
+التي لا يمكن التحكم بها، فأنا أتحدث عن
+
+107
+00:08:24,910 --> 00:08:29,250
+Multiple Regression، نحن طبعاً عندما نتحدث في الـ
+
+108
+00:08:29,250 --> 00:08:34,550
+Regression وما زلنا في المقدمة introduction، أتحدث أن الـ
+
+109
+00:08:34,550 --> 00:08:37,230
+Regression analysis  بغض النظر كان Linear
+
+110
+00:08:37,230 --> 00:08:43,670
+أو عفواً، بسيط simple أو Multiple يخضع لإحدى
+
+111
+00:08:43,670 --> 00:08:47,110
+النموذجين two models  اللذين قد يكونان موجودين
+
+112
+00:08:47,110 --> 00:08:50,430
+عندي، إما Linear Model، عندما أتحدث عن Linear Model
+
+113
+00:08:50,430 --> 00:08:54,110
+أتحدث عن علاقة خطية، أو Non-Linear Model، أتحدث عن
+
+114
+00:08:54,110 --> 00:08:57,130
+معادلة قد تكون Polynomial وقد تكون أي
+
+115
+00:08:57,130 --> 00:09:01,190
+دالة رياضية تمثل القيمة الموجودة في الرسم.
+
+116
+00:09:01,190 --> 00:09:04,070
+الأولى التي ظهرت أمامنا هنا، يوجد لدينا علاقة خطية بين
+
+117
+00:09:04,070 --> 00:09:07,720
+الـ two variables الموجودين هنا، طبعاً الرسم
+
+118
+00:09:07,720 --> 00:09:12,280
+هنا ليسهل فهم الأمر ببساطة، أتحدث عن Simple
+
+119
+00:09:12,280 --> 00:09:16,160
+Regression، أنا الآن، العلاقة، يوجد علاقة خطية بين
+
+120
+00:09:16,160 --> 00:09:24,260
+الـ X والـ Y أيضاً،
+
+121
+00:09:24,260 --> 00:09:29,460
+العلاقة الخطية واضحة، أن
+
+122
+00:09:29,460 --> 00:09:37,260
+كلما زادت الـ X، كلما زادت الـ X قيمة الـ Y تنخفض
+
+123
+00:09:37,260 --> 00:09:40,100
+Relational Model أو علاقة خطية، في النهاية يمكن
+
+124
+00:09:40,100 --> 00:09:43,060
+تمثيلها بخط مستقيم باللون الأزرق، لكن في
+
+125
+00:09:43,060 --> 00:09:45,520
+الرسم الثاني هنا، أنا أتحدث عن Linear يوجد
+
+126
+00:09:45,520 --> 00:09:53,480
+curve،  curve، ما معادلتها هذه؟ هل هي مثلاً 1 على
+
+127
+00:09:53,480 --> 00:09:58,920
+X تربيع؟ التي بين قوسين تساوي X تربيع ناقص واحد،
+
+128
+00:10:03,220 --> 00:10:05,760
+مثلاً، الله أعلم، لأن هذه قد تكون جزء من
+
+129
+00:10:05,760 --> 00:10:10,710
+curve، عامل بهذا الشكل ومعامل shift معين، وهذا أشبه
+
+130
+00:10:10,710 --> 00:10:15,430
+بالتربيع، لكن في النهاية ليست معادلة خطية، وهي يعني
+
+131
+00:10:15,430 --> 00:10:19,510
+قد تكون العلاقة بهذا الشكل، أنا في هذه الحالة
+
+132
+00:10:19,510 --> 00:10:24,650
+لن أتمكن من التحدث عن أي Model قد يمثل البيانات، لا
+
+133
+00:10:24,650 --> 00:10:28,730
+خط مستقيم ولا curve ولا exponential ولا شيء من
+
+134
+00:10:28,730 --> 00:10:31,910
+هذه الأشياء كلها، فأنا لن أتمكن من التحدث هنا، يقول أن
+
+135
+00:10:31,910 --> 00:10:35,250
+لا توجد علاقة موجودة فعلياً، طبعاً عندما أتحدث
+
+136
+00:10:35,250 --> 00:10:37,490
+عن عدم وجود علاقة، دائماً التنبؤ
+
+137
+00:10:37,490 --> 00:10:41,330
+في الاختبار test سيفشل، وستكون دقته accuracy منخفضة جداً too
+
+138
+00:10:41,330 --> 00:10:49,010
+low، تمام، معناته في نوع Regression  للنموذج model أو
+
+139
+00:10:49,010 --> 00:10:53,390
+regression models أنواعه إما Simple أو Multiple، و
+
+140
+00:10:53,390 --> 00:11:00,870
+أتحدث عن متغير واحد one variable، والمقصود به Independent
+
+141
+00:11:00,870 --> 00:11:04,030
+variable
+
+142
+00:11:05,650 --> 00:11:07,310
+عن طريق الـ Independent Variable وعن طريق الـ
+
+143
+00:11:07,310 --> 00:11:13,250
+Multiple Variable وفي كل
+
+144
+00:11:13,250 --> 00:11:17,430
+الحالتين، النموذج
+
+145
+00:11:17,430 --> 00:11:22,970
+تبعي قد يكون Linear وقد يكون Non-Linear في كل
+
+146
+00:11:22,970 --> 00:11:24,130
+الحالتين
+
+147
+00:11:26,880 --> 00:11:31,400
+بكل بساطة، لـ Linear Regression، لنفهم ما الذي
+
+148
+00:11:31,400 --> 00:11:34,300
+يحدث بالتحديد، طبعاً عندما أتحدث عن Linear
+
+149
+00:11:34,300 --> 00:11:36,360
+Regression، لنذهب باتجاه الـ
+
+150
+00:11:36,360 --> 00:11:39,740
+Simple Linear Regression في البداية، بكل بساطة عندما
+
+151
+00:11:39,740 --> 00:11:42,460
+أتحدث عن Simple Linear Regression، الـ Simple
+
+152
+00:11:42,460 --> 00:11:44,100
+Linear Regression، تذكر أن لدينا one
+
+153
+00:11:44,100 --> 00:11:47,600
+independent variable، معناته أنا أتحدث عن إيجاد
+
+154
+00:11:47,600 --> 00:11:48,680
+العلاقة بين
+
+155
+00:11:51,430 --> 00:11:54,490
+Two Continuous Attributes أو Two Continuous
+
+156
+00:11:54,490 --> 00:11:56,770
+Variables، واحد Independent Variable والثاني
+
+157
+00:11:56,770 --> 00:12:00,190
+Dependent Variable، وعندما أتحدث عن X و Y، عن
+
+158
+00:12:00,190 --> 00:12:03,370
+Dependent و Independent، أتحدث عن X و Y كما في
+
+159
+00:12:03,370 --> 00:12:06,510
+الرسم الموجود هناك في الـ Cartesian plane الموجودة، وعادةً عندما أتحدث عن Linear Model أتحدث
+
+160
+00:12:06,510 --> 00:12:14,750
+عن معادلة خط المستقيم، وهي Y تساوي M مضروبة في
+
+161
+00:12:14,750 --> 00:12:20,680
+X زائد B، حيث الـ M هي قيمة ميل slope الخط
+
+162
+00:12:20,680 --> 00:12:25,740
+المستقيم، والـ B تمثل الـ Intercept أو نقطة التقاطع
+
+163
+00:12:25,740 --> 00:12:31,820
+مع الـ Y الموجودة لدينا، طيب، الآن أي خط مستقيم،
+
+164
+00:12:39,200 --> 00:12:41,900
+أي خط مستقيم أريد رسمه، حتى لو أردت أن يمر
+
+165
+00:12:41,900 --> 00:12:51,330
+بنقطة الصفر، الميل slope  الذي يمثل هذه الزاوية، عفواً
+
+166
+00:12:51,330 --> 00:12:55,410
+هذه الزاوية، طبعاً الكل يعرف أن دائماً
+
+167
+00:12:55,410 --> 00:13:00,310
+الزاوية تُبنى مع خط مستقيم، طيب، الآن نقطة الـ
+
+168
+00:13:00,310 --> 00:13:07,610
+intercept هنا، عفواً، الصفر، التي هي نقطة التقاطع مع
+
+169
+00:13:07,610 --> 00:13:14,410
+محور الـ Y، صفر، بينما قيمتها B سواء كان هذا المثلث أو
+
+170
+00:13:14,410 --> 00:13:18,310
+أي مثلث موازٍ على الخط المستقيم، أنا الآن لو أخذت
+
+171
+00:13:18,310 --> 00:13:25,310
+محور موازٍ، لو اخترت أي نقطة على الخط المستقيم، ليس
+
+172
+00:13:25,310 --> 00:13:29,570
+الأصل، هذه النقطة، سامحوني، الرسم لدي ليس
+
+173
+00:13:29,570 --> 00:13:38,650
+جيداً،  لا أستطيع ضبطه، تمام، الآن، ليس هذا Delta X، هذا X وهذا Y
+
+174
+00:13:43,680 --> 00:13:50,560
+تمام، الآن لو أخذت نقطتين بين نقطتين، ورسمت قطعة
+
+175
+00:13:50,560 --> 00:13:53,680
+متعامدة ومتقاطعة، يعني رسمت بينهما مثلث قائم
+
+176
+00:13:53,680 --> 00:13:59,240
+الزاوية هذه، حسب فيثاغورس، الارتفاع، عفواً لو
+
+177
+00:13:59,240 --> 00:14:01,460
+افترضت أن هذه الزاوية التي قلنا تمثل
+
+178
+00:14:01,460 --> 00:14:07,360
+الميل سابقاً، الارتفاع المقابل، وهي المجاور
+
+179
+00:14:07,360 --> 00:14:10,900
+وهذا هو الوتر، حسب قانون فيثاغورس أن الوتر
+
+180
+00:14:10,900 --> 00:14:15,300
+هذا يساوي المجاور تربيع، الـ Run تربيع زائد الـ Rise
+
+181
+00:14:15,300 --> 00:14:22,540
+تربيع، تمام، الـ Slope يساوي الارتفاع
+
+182
+00:14:22,540 --> 00:14:27,120
+المقابل على المجاور
+
+223
+00:17:33,510 --> 00:17:39,330
+تبعته عبارة عن كل نقاط X ناقص متوسط نقاط X  كم
+
+224
+00:17:39,330 --> 00:17:42,070
+نقطة عندك أنت على الخط المستقيم هذا؟ أجل الخط
+
+225
+00:17:42,070 --> 00:17:44,070
+المستقيم يا جماعة الخير يجب أن يكون عنده نقطتين
+
+226
+00:17:44,070 --> 00:17:47,670
+عشان أنا أقدر أسميه، مظبوط ولا لا؟ طبعاً عادة
+
+227
+00:17:47,670 --> 00:17:50,870
+بالهدف احنا بنسميه قطعة مستقيمة محصورة بين نقطتين
+
+228
+00:17:50,870 --> 00:17:55,110
+بينما الخط المستقيم هو بتعدّى حدود النقطتين اللتين
+
+229
+00:17:55,110 --> 00:18:00,270
+موجودة عندها تمام، الآن معناته أنا بتكلم هنا أن X
+
+230
+00:18:00,270 --> 00:18:07,000
+عند مجموعة نقاط على الـ X ناقص المتوسط مضروبة في Y
+
+231
+00:18:07,000 --> 00:18:10,580
+الفروقات ما بين الـ Y و المتوسط تبعها طبعاً
+
+232
+00:18:10,580 --> 00:18:17,320
+بنجمعهم على مجموع الفروقات ما بين الـ X و المتوسط
+
+233
+00:18:17,320 --> 00:18:22,740
+والمتوسط تبعهم  لكل النقاط الموجودة عندها
+
+234
+00:18:22,740 --> 00:18:27,880
+طيب، الآن تعالوا نيجي نشوف من أين جاء التربيع يا جماعة
+
+235
+00:18:27,880 --> 00:18:32,420
+الخير؟ لأن في الآخر هذه النقاط كلها مثلثات أو فيها
+
+236
+00:18:32,420 --> 00:18:36,900
+ثغرات و كما قلت لك هذا التربيع
+
+237
+00:18:39,330 --> 00:18:42,490
+هو تربيع زائد  هاي تربيع فأعوض عن كل واحدة فيهم
+
+238
+00:18:42,490 --> 00:18:44,990
+بالتربيع الموجود فيها في الآخر احنا هذه
+
+239
+00:18:44,990 --> 00:18:48,850
+معادلتنا الموجودة و بدنا نستخدمها تعالوا نشوف
+
+240
+00:18:48,850 --> 00:18:52,550
+كيف بدنا نطبقها بشكل كويس الآن هذه النقاط التي
+
+241
+00:18:52,550 --> 00:18:56,430
+موجودة و هذه المعادلات الثلاث التي موجودة عندنا الـ
+
+242
+00:18:56,430 --> 00:19:00,650
+intercept إذا أنا حصلت على الـ M والـ Y معلومة والـ
+
+243
+00:19:00,650 --> 00:19:04,590
+X معلومة تمام بيظل عندنا الـ B معناته الـ B بدها
+
+244
+00:19:04,590 --> 00:19:10,940
+تساوي متوسط تغييرات أو متوسط قيم الـ Y ناقص الـ
+
+245
+00:19:10,940 --> 00:19:15,240
+slope في متوسط قيم الـ X الموجودة عندنا هذه
+
+246
+00:19:15,240 --> 00:19:18,440
+القيّم الموجودة وهذه هي المعادلات الثلاث التي
+
+247
+00:19:18,440 --> 00:19:22,100
+قلنا أننا نلزمها تكون حاضرة في ذهننا عند التعامل
+
+248
+00:19:22,100 --> 00:19:26,440
+مع الـ simple regression أو مع الـ regression مع الـ
+
+249
+00:19:26,440 --> 00:19:28,540
+linear regression عفواً مع الـ linear regression
+
+250
+00:19:28,540 --> 00:19:34,810
+تمام، طيب، هذه عندي X هذه الأعمدة التي بدي أشغل
+
+251
+00:19:34,810 --> 00:19:40,910
+عليها، ما هي المعادلة؟ بالبداية أن أحسب المتوسط تبع
+
+252
+00:19:40,910 --> 00:19:47,560
+الـ X والمتوسط الحسابي تبع الـ Y في كل الحالات التي
+
+253
+00:19:47,560 --> 00:19:52,480
+عندي تمام متوسط X معناته مجموعهم على عددهم واحد
+
+254
+00:19:52,480 --> 00:19:56,400
+اثنين ثلاثة أربعة خمسة ستة سبعة ثمانية تسعة عشر
+
+255
+00:19:56,400 --> 00:20:01,680
+ثلاثة إحدى عشر عشرين ثلاثين وستة وثلاثين
+
+256
+00:20:01,680 --> 00:20:09,380
+تسعة، اثنين وأربعين، ثلاثة وخمسين، أربعة وسبعين، خمسة
+
+257
+00:20:09,380 --> 00:20:20,000
+و سبعين، واحد وتسعون، بالمتوسط 9.10 حسبت المتوسط لـ X حسبنا
+
+258
+00:20:20,000 --> 00:20:28,460
+المتوسط لـ Y الخطوة التالية أنا بدي أجيب هنا مجموع
+
+259
+00:20:28,460 --> 00:20:38,780
+أو بدي أجيب حاصل ضرب كل X ناقص قيمة المتوسط 9.1
+
+260
+00:20:39,970 --> 00:20:44,930
+أضربها في قيمة الـ Y كل قيم الـ Y ناقص المتوسط
+
+261
+00:20:44,930 --> 00:20:51,590
+تبعها على كذا يعني أنا بدي أحسب X ناقص Y أو Xi
+
+262
+00:20:51,590 --> 00:20:59,350
+ناقص متوسط الـ X أحسب X أو Yi ناقص متوسط الـ Y فالجئت
+
+263
+00:20:59,350 --> 00:21:03,610
+هنا فين رحت حسبت المعادلتين، أيش اشتغلت عليهن في
+
+264
+00:21:03,610 --> 00:21:05,210
+شكل آلي ثلاثة
+
+265
+00:21:09,120 --> 00:21:14,740
+ناقص ثلاثة ناقص تسعة ناقص واحد ناقص ستة ناقص واحد ناقص
+
+266
+00:21:14,740 --> 00:21:15,940
+واحد ناقص واحد ناقص واحد ناقص واحد ناقص واحد ناقص واحد
+
+267
+00:21:15,940 --> 00:21:17,720
+ناقص واحد ناقص واحد ناقص واحد ناقص واحد ناقص واحد ناقص
+
+268
+00:21:17,720 --> 00:21:18,740
+واحد ناقص واحد ناقص واحد ناقص واحد ناقص واحد ناقص واحد
+
+269
+00:21:18,740 --> 00:21:19,220
+ناقص واحد ناقص واحد ناقص واحد ناقص واحد ناقص واحد ناقص
+
+270
+00:21:19,220 --> 00:21:25,130
+واحد ناقص واحد ناقص واحد ناقص واحد ناقص واحد ناقص واحد، 8-9
+
+271
+00:21:25,130 --> 00:21:34,830
+.1، 1.1، 57-55.4، 1.6  و أكمل الجدول بالكامل ممتاز
+
+272
+00:21:34,830 --> 00:21:39,950
+الخطوة التالية هذه العناصر بتلزمني في حالتين بدي
+
+273
+00:21:39,950 --> 00:21:43,310
+أضرب high في high و أحصل على high تربيع من أجل
+
+274
+00:21:43,310 --> 00:21:50,000
+المقام الذي هنا فإني رحت جبت العناصر البسط
+
+275
+00:21:50,000 --> 00:21:56,580
+التي هي Xi ناقص X متوسط الـ X مضروبة في Yi ناقص
+
+276
+00:21:56,580 --> 00:22:04,440
+متوسط الـ Y فبالتالي هنا ضربت سالب ستة point واحد
+
+277
+00:22:04,440 --> 00:22:07,680
+في سالب خمسة وعشرين point أربعة هي مئة وأربعة
+
+278
+00:22:07,680 --> 00:22:13,620
+وخمسين point أربعة وتسعين طيب وسالب ستة point واحد
+
+279
+00:22:13,620 --> 00:22:17,280
+ضرب سالب ستة point واحد سبعة وثلاثين point واحد
+
+280
+00:22:17,280 --> 00:22:22,460
+وعشرين وكملت للآخر كل العملية الحسابية تبعي طبعاً
+
+281
+00:22:22,460 --> 00:22:24,560
+يا جماعة الخير عشان أكون واضح معكم لو أنا جبت سؤال
+
+282
+00:22:24,560 --> 00:22:27,140
+زي هيك وقلت لك هاتلي أو هاتلي معادلة الخط
+
+283
+00:22:27,140 --> 00:22:30,840
+المستقيم مش هجيب لك فيه عشر قيم ممكن أجيب لك أربع من
+
+284
+00:22:30,840 --> 00:22:34,300
+أربع إلى خمس قيم تشتغل عليها يعني نصف القيم الموجودة و
+
+285
+00:22:34,300 --> 00:22:37,200
+عشان هيك بأكد باستمرار أن الـ calculator لازم يكون
+
+286
+00:22:37,200 --> 00:22:43,380
+عندك جاهزة في الحساب تمام الخطوة التي بعد هيك أنا
+
+287
+00:22:43,380 --> 00:22:46,320
+بتلزمني المجموع المجموع لمين؟ لكل عمود حسب
+
+288
+00:22:46,320 --> 00:22:49,180
+المعادلة التي موجودة عندي هنا فاروح أجمع العمود
+
+289
+00:22:49,180 --> 00:22:53,760
+هذا،  ثلاثمائة، التي هي قيمة البسط ثلاثمائة
+
+290
+00:22:53,760 --> 00:22:59,460
+وثمانية وخمسين point تسعة وحسبت قيمة العمود الثاني
+
+291
+00:22:59,460 --> 00:23:04,660
+ألف ومئتين وتسعة وستين point ستة تمام الآن قيمة الـ
+
+292
+00:23:04,660 --> 00:23:12,890
+M تساوي ألف ومئتين وتسعة وستين point ستة على ثلاثمائة وثمانية وخمسين point تسعة فبتطلع قيمة
+
+293
+00:23:12,890 --> 00:23:16,650
+الـ M عندي ثلاثة point خمسة ثلاثة سبعة كما نحن
+
+294
+00:23:16,650 --> 00:23:22,930
+شايفينها تمام أنا الآن حصلت على مين؟ على قيمة الـ M
+
+295
+00:23:22,930 --> 00:23:26,910
+في المعادلة هذه، من المعادلة هذه بظل عندي B، B
+
+296
+00:23:26,910 --> 00:23:30,770
+سهلة بما أن أنا حصلت على الـ M وهي معادلة الـ B
+
+297
+00:23:30,770 --> 00:23:33,970
+عفواً، أن أنا حصلت على الـ M وهي معادلة الـ B عندي
+
+298
+00:23:33,970 --> 00:23:36,650
+موجودة هنا وبالتالي أنا
+
+299
+00:23:42,300 --> 00:23:46,140
+بتساوي متوسط الـ Y التي هي الحسبة الأولى التي كانت
+
+300
+00:23:46,140 --> 00:23:51,040
+في الجدول التي لديها،  نهي متوسط الـ Y 55.4 ناقص
+
+301
+00:23:51,040 --> 00:23:57,260
+M  3.5375
+
+302
+00:23:57,260 --> 00:24:03,700
+ضرب متوسط الـ X 9.1 قيمته
+
+304
+00:24:08,260 --> 00:24:16,200
+معادلة الخط المستقيم معادلة M معادلة B معادلة M
+
+305
+00:24:16,200 --> 00:24:22,680
+معادلة B معادلة M معادلة B معادلة M معادلة B
+
+306
+00:24:22,680 --> 00:24:23,340
+معادلة M معادلة B
+
+307
+00:24:28,080 --> 00:24:40,280
+3.5375 ضرب الـ X زائد
+
+308
+00:24:40,280 --> 00:24:46,260
+الـ B لو أنا بدي أتأكد أن معادلتي صحيحة أو غير صحيحة
+
+309
+00:24:46,260 --> 00:24:49,760
+تخيل أن قيمة X تساوي واحد المفروض أنّه تساوي عشرين
+
+310
+00:24:50,690 --> 00:24:54,550
+المفروض، لكن الكلام الأدق يكون القيمة قريبة من
+
+311
+00:24:54,550 --> 00:25:05,630
+العشرين، ثلاثة point خمسة ثلاثة سبعة خمسة زائد
+
+312
+00:25:05,630 --> 00:25:11,690
+ثلاثة وعشرين point مئتين وتسعة، ملاحظين قد ايش القيمة
+
+313
+00:25:11,690 --> 00:25:18,390
+التي طلعت عندي  ثلاثة وعشرين واثنين من عشرة و
+
+314
+00:25:18,390 --> 00:25:23,850
+ثلاثة وسبعة وخمسة معناته احنا بنتكلم على ستة و
+
+315
+00:25:23,850 --> 00:25:30,350
+عشرين point سبعة هذه قيمة لما كانت الـ X تساوي واحد
+
+316
+00:25:30,350 --> 00:25:33,270
+ليش؟ لأنه بضل فيه نسبة خطأ ماحدش قال في الدنيا
+
+317
+00:25:33,270 --> 00:25:40,130
+أن هذا الـ algorithm أو هذا الـ model هيديني 100%
+
+318
+00:25:40,130 --> 00:25:44,670
+القيم المتساوية لأن هناك قيم متفرقة لو رجعت للرسم
+
+319
+00:25:44,670 --> 00:25:49,070
+على السريع عشان تشوفوها هي فعلاً هي النقاط تبعي
+
+320
+00:25:49,070 --> 00:25:52,630
+النقاط متجارة على الخط المستقيم ولو جربت أنت تأخذ
+
+321
+00:25:52,630 --> 00:25:55,490
+نقاط على الخط المستقيم هتطلع معك typical قيمة الـ
+
+322
+00:25:55,490 --> 00:26:00,030
+M وقيمة الـ B تمام بعد ما أنا حسبت القيم هذه على
+
+323
+00:26:00,030 --> 00:26:02,730
+السريع خليني أروح أشوف بالـ python إيش أنا بدي
+
+324
+00:26:02,730 --> 00:26:05,870
+أعمله، أنا رحت على الـ python استخدمت الـ numpy
+
+325
+00:26:05,870 --> 00:26:10,910
+كمكتبة عشان أتعامل مع الـ numerical python arrays
+
+326
+00:26:10,910 --> 00:26:16,060
+وبنيت الريشة الـ X وبنيت الريشة الـ Y لكن يوجد شغل
+
+327
+00:26:16,060 --> 00:26:19,180
+هنا أنه لازم أعمل Reshape عشان أعمل Transpose تبع
+
+328
+00:26:19,180 --> 00:26:25,080
+المصفوفة وهي عبارة عن مصفوفة من بعد واحد أكثر
+
+329
+00:26:25,080 --> 00:26:29,120
+وليست vector تمام فعشان هيك بعملها Reshape سالب
+
+330
+00:26:29,120 --> 00:26:31,620
+واحد هذا طبعاً لأنه أنا فعلياً يا جماعة الخير برجع
+
+331
+00:26:31,620 --> 00:26:33,800
+بأكد أنّه أنا جاهز  بدي أبني الـ data set
+
+332
+00:26:33,800 --> 00:26:35,880
+بينما الـ data set ممكن تكون معي جاهزة زي ما في
+
+333
+00:26:35,880 --> 00:26:38,340
+الـ data set التي أنت اخترتها في الواجب الأول تبع
+
+334
+00:26:38,340 --> 00:26:41,280
+الـ regression data set التي كنا بنتكلم عليها أنت
+
+335
+00:26:41,280 --> 00:26:44,700
+بدك تقطع منها عمود واحد فقط وتشتغل عليه وتشوف
+
+336
+00:26:44,700 --> 00:26:48,780
+العلاقة ما بينه وبين الـ target attribute التي هي
+
+337
+00:26:48,780 --> 00:26:50,920
+الـ continuous value بدك تعملها prediction وروح
+
+338
+00:26:50,920 --> 00:26:55,370
+أدخلت القيم الموجودة عندي أنا  الـ
+
+339
+00:26:55,370 --> 00:26:58,650
+values التي دخلتها على المصفوفة بدون ما أعمل الـ
+
+340
+00:26:58,650 --> 00:27:02,890
+reshape، رحت from الـ sklearn.linear_model
+
+341
+00:27:02,890 --> 00:27:05,710
+import LinearRegression وأنا ما زلت بأكد
+
+342
+00:27:05,710 --> 00:27:08,270
+أنّه يشغل على linear regression وبالتحديد بما أنا
+
+343
+00:27:08,270 --> 00:27:12,870
+بتكلم على one independent attribute معناته أنا
+
+344
+00:27:12,870 --> 00:27:18,330
+بتكلم على simple linear regression بنيت الموديل
+
+345
+00:27:18,330 --> 00:27:22,270
+model تساوي LinearRegression الموديل.fit عشان
+
+346
+00:27:22,270 --> 00:27:25,730
+يعمل train ويوجد العلاقة التي ما بين الـ X والـ Y
+
+347
+00:27:25,730 --> 00:27:28,430
+التي هي الـ independent attribute X والـ dependent
+
+348
+00:27:28,430 --> 00:27:33,830
+variable أو الـ dependent attribute Y فرُحت أنا
+
+349
+00:27:33,830 --> 00:27:39,390
+أعمل fit المفروض بعد عملية الـ fit هذه هو حصل على
+
+350
+00:27:39,390 --> 00:27:45,350
+الـ slope، الـ M وحصل على الـ B هنا لأن أنا بس بدي
+
+351
+00:27:45,350 --> 00:27:49,250
+أطبعهم فروحت وقلت له اطبع لي الـ model.coef_
+
+352
+00:27:49,250 --> 00:27:53,170
+الـ model.coef_ فبطبع لي
+
+353
+00:27:53,170 --> 00:27:56,730
+قيمة ورحت أضفت عليها عشان تظهر معادلة خط مستقيم
+
+354
+00:27:56,730 --> 00:27:59,430
+بس مش أكثر الـ model.coef_ والـ model.
+
+355
+00:27:59,790 --> 00:28:02,650
+intercept، الـ intercept التي هي الـ b أو التقاطع
+
+356
+00:28:02,650 --> 00:28:06,010
+مع b والـ coefficient التي هي الـ m الموجودة
+
+357
+00:28:06,010 --> 00:28:11,660
+عندي هنا الـ output طلع لي هي، لو أنا جيت طلعت في
+
+358
+00:28:11,660 --> 00:28:20,280
+قيمة ثلاثة point خمسة ثلاثة سبعة القيم التي طلعت معي
+
+359
+00:28:20,280 --> 00:28:24,100
+لما أنا اختصرتها سبعة خمسة لأنه عملت round للسبعة
+
+360
+00:28:24,100 --> 00:28:31,120
+وهنا ثلاثة وعشرين point مئتين وتسعة لأنه برضه عملت
+
+361
+00:28:31,120 --> 00:28:34,440
+round للرقم الموجود عندها، typical نفس الـ values
+
+362
+00:28:34,440 --> 00:28:38,710
+الموجودة، لو أنا بدي أعمل prediction هيبقى أنا في
+
+363
+00:28:38,710 --> 00:28:42,270
+الـ array رحت على الـ X قلت له في عندي X_test هذه
+
+364
+00:28:42,270 --> 00:28:48,710
+في عندي النقاط تبعي الـ array اثنين وتسعة وثلاثة عشر وثمانية عشر وأربعة وعشرين
+
+365
+00:28:48,710 --> 00:28:57,370
+و يعمل لي الـ Y_predict تبعها تمام الآن
+
+366
+00:28:57,370 --> 00:29:02,050
+هذول هيروح يجيب لي بناء على المعادلة هذه، هيأخذ اثنين
+
+367
+00:29:02,050 --> 00:29:09,110
+يعني ثلاثة point خمسة أربعة ضرب اثنين زائد ثلاثة
+
+368
+00:29:09,110 --> 00:29:12,690
+وعشرين، مئتين وتسعة، هذين قيمتين اثنين، تسعة لكن
+
+369
+00:29:12,690 --> 00:29:15,550
+لاحظوا الآن يا جماعة الخير أن هذه القيم المجتمعة
+
+370
+00:29:15,550 --> 00:29:20,510
+كلها بدأت تخضع لمن؟ تخضع لنفس المعادلة التي عملها
+
+371
+00:29:20,510 --> 00:29:24,270
+prediction هنا خلاص انتهى الأمر لأن أنا عمال بتكلم
+
+372
+00:29:24,270 --> 00:29:29,330
+على الـ model.predict فأنا زدت في القائمة تبعي
+
+373
+00:29:29,330 --> 00:29:35,340
+هذه وهو شرح سريع ليش أعمل predict فعشان هيك بتطلع
+
+374
+00:29:35,340 --> 00:29:38,580
+معي معادلة خط مستقيم بالتمام، طيب عشان أوجد
+
+375
+00:29:38,580 --> 00:29:42,080
+العلاقة الموجودة عندي هنا رحت استخدمت مكتبة
+
+376
+00:29:42,080 --> 00:29:43,660
+اسمها الـ
+
+377
+00:29:43,660 --> 00:29:47,360
+matplotlib mathematical plotting library
+
+378
+00:29:47,360 --> 00:29:49,980
+.pyplot
+
+379
+00:29:51,750 --> 00:29:55,190
+as plt بدي أرسم ورحت أقول في الـ plot هذه قلت له
+
+380
+00:29:55,190 --> 00:29:58,070
+في عندي scatter التي هي النقاط عند X و Y هي هم
+
+381
+00:29:58,070 --> 00:30:01,970
+موجودات، هي X و Y الموجودة فوق عندنا، والـ color
+
+382
+00:30:01,970 --> 00:30:06,690
+black، نقاط باللون الأسود وفي عندي بدي أعمل plot
+
+383
+00:30:06,690 --> 00:30:10,050
+كذلك كرسم خط مستقل الـ plot التي بتكلم على function
+
+384
+00:30:10,050 --> 00:30:14,650
+أو على equation الـ plot X_test التي هي هذه اثنين
+
+385
+00:30:14,650 --> 00:30:18,590
+وتسعة وثلاثة عشر وثمانية عشر وأربعة وعشرين، والـ color والـ
+
+386
+00:30:18,590 --> 00:30:22,780
+Y_predict هي هي الـ result تبع الـ prediction بتاعة
+
+387
+00:30:22,780 --> 00:30:25,980
+الـ model التي أنا استخدمتها والخط باللون الأخضر والـ
+
+388
+00:30:25,980 --> 00:30:30,700
+linewidth فرُحت قلت له أعمل تبين الـ text على الـ
+
+389
+00:30:30,700 --> 00:30:34,240
+X والـ Y التي هي النقاط وقلت له show تعالوا نشوف هي
+
+390
+00:30:34,240 --> 00:30:38,580
+النتيجة التي طلع لي إياها هي النقاط الموجودة هنا
+
+391
+00:30:38,580 --> 00:30:44,300
+تمام وهي الخط المستقيم الذي يمثله المعادلة التي
+
+392
+00:30:44,300 --> 00:30:47,160
+موجودة عندها، بدي أروح أنا أورّجيك الآن بس على الـ X التي
+
+393
+00:30:47,160 --> 0
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/zzmXFQBnsgA_postprocess.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/zzmXFQBnsgA_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..c9c38193b8f1f37a7badab676d757b151cb4f34f
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/zzmXFQBnsgA_postprocess.srt
@@ -0,0 +1,1676 @@
+1
+00:00:00,980 --> 00:00:03,820
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:03,820 --> 00:00:10,700
+أهلا وسهلا فيكم في محاضرتنا الجديدة المصورة لمساب
+
+3
+00:00:10,700 --> 00:00:14,820
+تنقيب البيانات اليوم إن شاء الله تعالى هنتكلم عن
+
+4
+00:00:14,820 --> 00:00:20,610
+chapter regressionهنا في الـ regression نتكلم عن
+
+5
+00:00:20,610 --> 00:00:26,830
+الـ task الثانية في الـ predictive category للـ
+
+6
+00:00:26,830 --> 00:00:30,650
+data mining اتفقنا من البداية أن ال data mining
+
+7
+00:00:30,650 --> 00:00:33,730
+تنقسم إلى two tasks
+
+8
+00:00:36,820 --> 00:00:41,280
+واحدة predictive والتانية descriptive واتكلمنا تحت
+
+9
+00:00:41,280 --> 00:00:47,000
+ال category ال predictive tasks في عنده
+
+10
+00:00:47,000 --> 00:00:50,280
+classification وهي التنبؤ بال class label أو بال
+
+11
+00:00:50,280 --> 00:00:58,030
+category value أو بال nominal value بينماالـ Task
+
+12
+00:00:58,030 --> 00:01:00,710
+التانية هي الـ Regression والتنبؤ بالـ Continuous
+
+13
+00:01:00,710 --> 00:01:04,570
+Value وفي المقابل لدينا في الـ Descriptive Task
+
+14
+00:01:04,570 --> 00:01:07,730
+كان في عندنا Clustering وعندنا Association Rules
+
+15
+00:01:07,730 --> 00:01:11,070
+وفي عندنا الـ Outlier Detection وهدول هنتكلم عليهم
+
+16
+00:01:11,070 --> 00:01:15,430
+في الشباتير الجاية خلّينا نبدأ مع الـ Regression
+
+17
+00:01:16,730 --> 00:01:19,590
+الشغلات اللي هنتناولها في محاضرتنا اليوم ال
+
+18
+00:01:19,590 --> 00:01:23,590
+introduction و ال linear regression أو نشرحها و
+
+19
+00:01:23,590 --> 00:01:28,610
+نكمل بعدها في .. ممكن في فيديو تاني او في تسجيل
+
+20
+00:01:28,610 --> 00:01:32,850
+تاني حسب كيف نمشي او ناقص تهلك أو نستخدع من الوقت
+
+21
+00:01:32,850 --> 00:01:36,210
+اللي موجود عندنا طبعا لما اتكلم على ال regression
+
+22
+00:01:36,210 --> 00:01:41,130
+انا جاعل بقى اتكلم ان ال regression يستخدم من أجل
+
+23
+00:01:41,130 --> 00:01:45,150
+التنبؤ
+
+24
+00:01:47,830 --> 00:01:54,390
+بـ range of values of numeric values range of
+
+25
+00:01:54,390 --> 00:01:59,970
+numeric values وهنا
+
+26
+00:01:59,970 --> 00:02:04,770
+بتكلم على continuous value بالتحديد بتكلم على
+
+27
+00:02:04,770 --> 00:02:09,650
+continuous value بالتحديد طبعا ال regression
+
+28
+00:02:09,650 --> 00:02:16,440
+technique تستخدم أوفي موضوع ال prediction زي ما
+
+29
+00:02:16,440 --> 00:02:20,200
+قلنا هي واحدة من ال prediction task اللي انا موجود
+
+30
+00:02:20,200 --> 00:02:23,280
+فيها من أجل ان اتنبأ بقيم زي ما قلنا continuous
+
+31
+00:02:23,280 --> 00:02:28,100
+value ال profit قيمة الأرباح قيمة المبيعات ال
+
+32
+00:02:28,100 --> 00:02:32,420
+debit ال sales عفوا ال debit rates قيمة القروض أو
+
+33
+00:02:32,420 --> 00:02:37,280
+الفائدة ال house values قيم المنازل درجات الحرارة
+
+34
+00:02:37,280 --> 00:02:42,740
+temperatureأو المسافات اللي ممكن استخدامها وكل هذه
+
+35
+00:02:42,740 --> 00:02:45,700
+التنبؤة بأي value continuous سواء كان بالمثال هذا
+
+36
+00:02:45,700 --> 00:02:53,280
+أو تتنبأ بأوزان أو أعمار أو أطوال أو مدة زمانية
+
+37
+00:02:53,280 --> 00:02:57,420
+إلى آخرهم، نحن بتتكلم جانين على أي value بديها
+
+38
+00:02:57,420 --> 00:03:01,020
+number تطلع قدامي أو numberic value، معناته أنا
+
+39
+00:03:01,020 --> 00:03:04,660
+بتتكلم على regression طبعا ال regression لما أنا
+
+40
+00:03:04,660 --> 00:03:07,460
+بقعد بتكلم أو زي ما بطلق عليه البعض regression
+
+41
+00:03:07,460 --> 00:03:12,380
+analysisباستخدمها عشان اوجد العلاقة ما بين ال
+
+42
+00:03:12,380 --> 00:03:16,080
+independent attribute او ال independent variable
+
+43
+00:03:16,080 --> 00:03:24,240
+اللي هي ال X وال dependent variable اللي هي ال Y
+
+44
+00:03:24,240 --> 00:03:28,320
+طبعا الرسمة هذه واضحة جدا بتقول هي ال independent
+
+45
+00:03:28,320 --> 00:03:32,880
+value اللي هي قيمة ال X وهي في عند ال dependent
+
+46
+00:03:32,880 --> 00:03:36,900
+value او ال attribute او ال variable عفوا اللي هي
+
+47
+00:03:36,900 --> 00:03:42,150
+قيمة ال Y وطبعالما انا بتكلم عن ال regression
+
+48
+00:03:42,150 --> 00:03:48,210
+بتقدر اصنفها لنوعين في عندي simple regression و
+
+49
+00:03:48,210 --> 00:03:50,730
+لما بتكلم عن اسمها simple regression معناته انا
+
+50
+00:03:50,730 --> 00:03:58,810
+بتكلم عن ابسط نوع من انواع التنبؤ وهذه عادة بتتضمن
+
+51
+00:03:58,810 --> 00:04:02,510
+او simple regression بتتضمن فقط two variables two
+
+52
+00:04:02,510 --> 00:04:05,010
+variables نعم two variables واحد بيكون dependent
+
+53
+00:04:05,010 --> 00:04:08,920
+variable والتاني بيكون independentطبعاً واحد بيكون
+
+54
+00:04:08,920 --> 00:04:12,560
+في عندي ال explanatory والثاني بيكون اللي هي ال
+
+55
+00:04:12,560 --> 00:04:17,620
+response زي ما احنا سمناه يعني الآن ال Y هي ال
+
+56
+00:04:17,620 --> 00:04:20,620
+dependent وال X هي ال independent ما تنساش من
+
+57
+00:04:20,620 --> 00:04:24,520
+الأمثلة الموجودة اللي أنا بتكلم عن ال population و
+
+58
+00:04:24,520 --> 00:04:30,100
+ال food production الكثقة للناسزيادة السكان
+
+59
+00:04:30,100 --> 00:04:34,860
+والحاجة إلى إنتاج الغذاء اللي موجود عندهم طبعا لو
+
+60
+00:04:34,860 --> 00:04:37,580
+أنا جاي تتكلمت أنه بدي أتكلم في المجزئية هذه بشكل
+
+61
+00:04:37,580 --> 00:04:41,760
+بصير لو انا افترضت انه انا هيكي عند الرسم high
+
+62
+00:04:41,760 --> 00:04:47,000
+high
+
+63
+00:04:47,000 --> 00:04:51,770
+X بتمثلبتقولك مين مرتبط في مين لو انا سألك سؤال
+
+64
+00:04:51,770 --> 00:04:56,710
+الكلان مين مرتبط في مين او مين معتمد على مين زيادة
+
+65
+00:04:56,710 --> 00:05:01,630
+السكان ال population معتمدة على إنتاج الغذاء ولا
+
+66
+00:05:01,630 --> 00:05:09,770
+إنتاج الغذاء معتمد على زيادة السكان نعم معناته انا
+
+67
+00:05:09,770 --> 00:05:11,890
+بتكلم ان هنا بتكلم ال population
+
+68
+00:05:14,460 --> 00:05:18,780
+هي الـ Independent Variable لأنه حسب العدد السكان
+
+69
+00:05:18,780 --> 00:05:23,200
+أنا بتكلم على اني جداش بدي أنتج غذاء وهنا بتكلم
+
+70
+00:05:23,200 --> 00:05:31,540
+على food production الآن لو أنا نظرت كان في عندي
+
+71
+00:05:31,540 --> 00:05:37,180
+معادلة خطية بالشكل هذا شو هذا بيعني؟ بيعني كل ما
+
+72
+00:05:37,180 --> 00:05:41,220
+يزيد عدد السكان
+
+73
+00:05:45,780 --> 00:05:50,120
+هيزيد عند مين الحاجة
+
+74
+00:05:50,120 --> 00:05:55,400
+إلى إنتاج غذائي أكبر وهذه هي العلاقة هيمفهوم ال
+
+75
+00:05:55,400 --> 00:05:58,180
+prediction يعني لو انا افترضت إن السكانة هيكون في
+
+76
+00:05:58,180 --> 00:06:02,660
+عندهان 200 مليار
+
+77
+00:06:02,660 --> 00:06:09,760
+معناته بدي يكون في عندهان مش عارف كام قن تمام
+
+78
+00:06:14,860 --> 00:06:17,280
+يعني لما انا بتكلم عن الـ simple regression بتكلم
+
+79
+00:06:17,280 --> 00:06:20,740
+على انه فقط two variables واحد independent واحد
+
+80
+00:06:20,740 --> 00:06:24,120
+dependent بينما بال multiple regression معناته انا
+
+81
+00:06:24,120 --> 00:06:30,640
+في عندى اكثر من independent variable لاحظوا في
+
+82
+00:06:30,640 --> 00:06:34,660
+الحالة الأولى انا اتكلمت انه انا في عندى2
+
+83
+00:06:34,660 --> 00:06:38,180
+variables فقط ال data set تبعتي أو ال task تبعتي
+
+84
+00:06:38,180 --> 00:06:40,760
+فقط 2 variables و من هنا أنا بتكلم مباشرة واحد
+
+85
+00:06:40,760 --> 00:06:44,420
+dependent والتاني independent لأنه مستحيل في ال
+
+86
+00:06:44,420 --> 00:06:49,120
+predictive task يكون عندى التنين independent فلازم
+
+87
+00:06:49,120 --> 00:06:52,580
+يكون واحد dependent واحد independent لما أجينا
+
+88
+00:06:52,580 --> 00:06:55,500
+نتكلم على ال multiple regression هنا قلنا ال
+
+89
+00:06:55,500 --> 00:06:57,800
+multiple regression معناته أنا بتكلم في عندي more
+
+90
+00:06:57,800 --> 00:07:00,640
+than one independent في عندي أكتر من independent
+
+91
+00:07:00,640 --> 00:07:04,190
+attributeهل يوجد عندي الـ dependent attribute لازم
+
+92
+00:07:04,190 --> 00:07:08,610
+يكون و الا ال task تكون descriptive مش predictive
+
+93
+00:07:08,610 --> 00:07:13,930
+مثل أسعار المنازل لأ لو أنا سألتكوا أسعار البيوت
+
+94
+00:07:13,930 --> 00:07:23,350
+ايش اللي بيحكمها شغلات كتير مساحة البناء ال
+
+95
+00:07:23,350 --> 00:07:29,210
+location الموقع ال price لما عند اخر بيع الموسم
+
+96
+00:07:31,480 --> 00:07:36,220
+أسعار المنازل المشابهة وشغلات كتيرة ممكن تتحكم
+
+97
+00:07:36,220 --> 00:07:39,380
+فيها هذه كلها تبتعمل prediction لو أنا أجيت و
+
+98
+00:07:39,380 --> 00:07:46,200
+أتكلمت على العلاقة ما بين مرض السكري عفاكم الله و
+
+99
+00:07:46,200 --> 00:07:51,820
+جميع المسلمين ان شاء الله و ال human body
+
+100
+00:07:51,820 --> 00:07:54,160
+measurement
+
+101
+00:07:58,120 --> 00:08:04,500
+المؤشرات أو القياسات المتعلقة بجسم الإنسان طوله و
+
+102
+00:08:04,500 --> 00:08:12,000
+وزنه عمره اللهم صلي على سيدنا محمد ال behavior
+
+103
+00:08:12,000 --> 00:08:16,030
+تبعههل في واحد منهم هدول على نفسه اللي انا ذكرتها
+
+104
+00:08:16,030 --> 00:08:18,750
+فقط بأثر في السكر ان يكون موجود او لأ لأ حتما لأ
+
+105
+00:08:18,750 --> 00:08:21,990
+فهدولا كلهم بيكونوا مجتمعين والنسب الموجودة هي
+
+106
+00:08:21,990 --> 00:08:24,910
+اللي ممكناش تتحكم في الموضوع فانا بكون متكلم على
+
+107
+00:08:24,910 --> 00:08:29,250
+multiple regression احنا طبعا لما نجيب نتكلم في ال
+
+108
+00:08:29,250 --> 00:08:34,550
+regression ومازلنا في ال introduction بتكلم ان ال
+
+109
+00:08:34,550 --> 00:08:37,230
+regression analysis تبعتي بغض النظر هو كان linear
+
+110
+00:08:37,230 --> 00:08:43,670
+او عفوا a symbol ولا multipleبيخضع على واحدة من
+
+111
+00:08:43,670 --> 00:08:47,110
+التنتين من الـ two models اللي ممكن يكونوا موجودات
+
+112
+00:08:47,110 --> 00:08:50,430
+عندي إما linear model لما بتكلم على linear model
+
+113
+00:08:50,430 --> 00:08:54,110
+بتكلم على علاقة خطية أو non-linear model بتكلم على
+
+114
+00:08:54,110 --> 00:08:57,130
+equation ممكن تكون polynomial وممكن تكون عندي أي
+
+115
+00:08:57,130 --> 00:09:01,190
+دالة رياضية تمثل القيمة اللي موجودة عندها الرسم
+
+116
+00:09:01,190 --> 00:09:04,070
+الأولى اللي ظهرت قدامنا هنا في عندي علاقة خطية ما
+
+117
+00:09:04,070 --> 00:09:07,720
+بينالـ two variables اللي موجودين عندها طبعا الرسم
+
+118
+00:09:07,720 --> 00:09:12,280
+هي عشان نسهل نستوعب الأمر بسهولة بتكلم على simple
+
+119
+00:09:12,280 --> 00:09:16,160
+regression أنا الآن العلاقة في عندها علاقة خطية ما
+
+120
+00:09:16,160 --> 00:09:24,260
+بين ال X و ال Y كمان
+
+121
+00:09:24,260 --> 00:09:29,460
+العلاقة الخطية واضح انه
+
+122
+00:09:29,460 --> 00:09:37,260
+كل ما بتزيد ال Xكل ما تزيد الـ X قيمة الـ Y بتنزل
+
+123
+00:09:37,260 --> 00:09:40,100
+Relational Model أو علاقة خطية في الآخر ممكن
+
+124
+00:09:40,100 --> 00:09:43,060
+أمثلها بالخط المستقيم اللي باللون الأزرق لكن في
+
+125
+00:09:43,060 --> 00:09:45,520
+الرسم التاني هنا أنا بتتكلم عن ال linear في عندك
+
+126
+00:09:45,520 --> 00:09:53,480
+curve ال curve إيش معدلته هذا؟ هل هو مثلا ال 1 على
+
+127
+00:09:53,480 --> 00:09:58,920
+X تربيه؟ اللي هي بين قسين تساوي X تربيه نقص واحد
+
+128
+00:10:03,220 --> 00:10:05,760
+مثلًا، الله أعلم، لأن هذه ممكن تكون جزء من ال
+
+129
+00:10:05,760 --> 00:10:10,710
+curveعامل بالشكل هذا ومعمله shift معين فهذا أشبه
+
+130
+00:10:10,710 --> 00:10:15,430
+بالترفيه لكن في الآخر ليس معادلة خطية وهيفي يعني
+
+131
+00:10:15,430 --> 00:10:19,510
+ممكن يكون العلاقة بالشكل هذا أنا فعليا بالحالة هذه
+
+132
+00:10:19,510 --> 00:10:24,650
+مش هقدر أتكلم على أي model ممكن يمثل البيانات لا
+
+133
+00:10:24,650 --> 00:10:28,730
+خط مستقيم ولا curve ولا exponential ولا حاجة من
+
+134
+00:10:28,730 --> 00:10:31,910
+الشغلات هذه كلها فانا مش هقدر أتكلم هنا بيقول ان
+
+135
+00:10:31,910 --> 00:10:35,250
+مافيش عندي علاقة فعليا موجودة بينناطبعاً لما اتكلم
+
+136
+00:10:35,250 --> 00:10:37,490
+من مافيش علاقة يا جماعة الخير دائما ال prediction
+
+137
+00:10:37,490 --> 00:10:41,330
+عند ال test هتفشل و هتكون ال accuracy تبعتها too
+
+138
+00:10:41,330 --> 00:10:49,010
+low تمام معناته بال regression type لل model او
+
+139
+00:10:49,010 --> 00:10:53,390
+regression models أنواعها اما simple او multiple و
+
+140
+00:10:53,390 --> 00:11:00,870
+بتكلمها one variable و المقصود فيها independent
+
+141
+00:11:00,870 --> 00:11:04,030
+variable
+
+142
+00:11:05,650 --> 00:11:07,310
+عن طريق الـ Independent Variable وعن طريق الـ
+
+143
+00:11:07,310 --> 00:11:13,250
+Multiple Variable وفي كل
+
+144
+00:11:13,250 --> 00:11:17,430
+الحالتين الموديل
+
+145
+00:11:17,430 --> 00:11:22,970
+تبعي ممكن يكون Linear وممكن يكون Non-Linear في كل
+
+146
+00:11:22,970 --> 00:11:24,130
+الحالتين
+
+147
+00:11:26,880 --> 00:11:31,400
+بكل بساطة للـ Linear Regression عشان نفهم إيش اللي
+
+148
+00:11:31,400 --> 00:11:34,300
+بصير بالتحديد طبعا لما أنا بتكلم على Linear
+
+149
+00:11:34,300 --> 00:11:36,360
+Regression يا جماعة الخير خلّيني نروح باتجاه الـ
+
+150
+00:11:36,360 --> 00:11:39,740
+Simple Linear Regression في الأول بكل بساطة لما
+
+151
+00:11:39,740 --> 00:11:42,460
+أنا بتكلم على Single Linear Regression الـ Simple
+
+152
+00:11:42,460 --> 00:11:44,100
+Linear Regression انت فاكر ان في عندي one
+
+153
+00:11:44,100 --> 00:11:47,600
+independent variable معناته أنا بتكلم على إيجاد
+
+154
+00:11:47,600 --> 00:11:48,680
+العلاقة ما بين
+
+155
+00:11:51,430 --> 00:11:54,490
+Two Continuous Attributes أو Two Continuous
+
+156
+00:11:54,490 --> 00:11:56,770
+Variables واحد Independent Variable والتاني
+
+157
+00:11:56,770 --> 00:12:00,190
+Dependent Variable ولما أنا بتكلم على X و Y على
+
+158
+00:12:00,190 --> 00:12:03,370
+Dependent و Independent بتكلم على X و Y زي ما في
+
+159
+00:12:03,370 --> 00:12:06,510
+الرسم اللي موجود عندها في الـ Cartesian plane اللي
+
+160
+00:12:06,510 --> 00:12:14,750
+موجودة وعادة لما أنا بتكلم على Linear Model بتكلم
+
+161
+00:12:14,750 --> 00:12:20,680
+على معادلة خط المستقيم اللي هي Y تساويM مضروبة في
+
+162
+00:12:20,680 --> 00:12:25,740
+X زائد B حيث الـ M هي قيمة الـ male تبع الخط
+
+163
+00:12:25,740 --> 00:12:31,820
+المستقيم والـ B تمثل الـ intercept أو نقطة التقاطع
+
+164
+00:12:31,820 --> 00:12:39,200
+مع الـ Y اللي موجودة عندنا طيب، الآن أي خط مستقيم،
+
+165
+00:12:39,200 --> 00:12:41,900
+أي خط مستقيم أنا بدي أرسمه حتى لو أنا كان بدي مر
+
+166
+00:12:41,900 --> 00:12:51,330
+بـ نقطة الصفر الو male اللي بتمثل الزاوية هذهعفواً
+
+167
+00:12:51,330 --> 00:12:55,410
+الزاوية هذه طبعا الكل اللي هابنى عرف انه دائما
+
+168
+00:12:55,410 --> 00:13:00,310
+الزاوية بتنبنى مع خط مستقيم طيب الآن نقطة ال
+
+169
+00:13:00,310 --> 00:13:07,610
+intercept هان عفواً صفر اللي هي نقطة التقاطع مع
+
+170
+00:13:07,610 --> 00:13:14,410
+محور ال Y صفربينما قيمتها B سواء كان المثلث هذا أو
+
+171
+00:13:14,410 --> 00:13:18,310
+اي مثلث موازي على الخط المستقيم انا الان لو اخدت
+
+172
+00:13:18,310 --> 00:13:25,310
+محور موازي لو اخترت اي نقطة على الخط المستقيم مش
+
+173
+00:13:25,310 --> 00:13:29,570
+الاصل هذه النقطة هيها سامحوني شوية الرسم معايا مش
+
+174
+00:13:29,570 --> 00:13:38,650
+جادر اضبطه تمام الان مش هذه delta X هذه X وهذه Y
+
+175
+00:13:43,680 --> 00:13:50,560
+تمام الان لو انا خدت نقطتي بين نقطين و رسمت تقرط
+
+176
+00:13:50,560 --> 00:13:53,680
+متقاطعة و متعامدة يعني رسمت بين جثين مثلث قائم
+
+177
+00:13:53,680 --> 00:13:59,240
+الزاوية هذا حسب فيثا غورس الارتفاع والعفوا لو انا
+
+178
+00:13:59,240 --> 00:14:01,460
+افترض ان هي الزاوية تبعتي اللي احنا قلنا بتتمثل
+
+179
+00:14:01,460 --> 00:14:07,360
+الميل سابقا ال raise الارتفاع المقابل وهي المجاور
+
+180
+00:14:07,360 --> 00:14:10,900
+وهذا هو ال water حسب قانون فيثا غورس ان ال water
+
+181
+00:14:10,900 --> 00:14:15,300
+هذا يساويالمجاور تربيع الـ Run تربيع زاد الرايس
+
+182
+00:14:15,300 --> 00:14:22,540
+تربيع تمام ال slope تساوي الارتفاع
+
+183
+00:14:22,540 --> 00:14:27,120
+المقابل على المجاور المقابل على المجاور المقابل هي
+
+184
+00:14:27,120 --> 00:14:32,300
+التغير في قيمة ال Y هي المقابل تمثل التغير في قيمة
+
+185
+00:14:32,300 --> 00:14:40,640
+ال Y والمقابل
+
+186
+00:14:40,640 --> 00:14:42,140
+التغير في قيمة
+
+187
+00:14:45,400 --> 00:14:53,620
+في قيمة الـ X وبالتالي قيمة الـ Mail هي عشان نتكلم
+
+188
+00:14:53,620 --> 00:14:58,320
+في أمثلة ممكن نفهمها بشكل صحيح خلّيني أشوف المثال
+
+189
+00:14:58,320 --> 00:15:02,040
+البسيط هذا المثال هذا عديته على الـ Excel وافترضت
+
+190
+00:15:02,040 --> 00:15:05,920
+إنه هي في عندي ال salary
+
+191
+00:15:07,280 --> 00:15:11,360
+هنا الـ salary بتمثل قيم الـ independent variable
+
+192
+00:15:11,360 --> 00:15:14,940
+عفوا اللي في عندي independent variable attribute X
+
+193
+00:15:14,940 --> 00:15:19,760
+بيمثل سنوات الخبرة وفي عندي قيمة ال salary بال K
+
+194
+00:15:19,760 --> 00:15:24,790
+أو بال ألفاللي بتمثل الـ Y وهي القيامة يعني لما
+
+195
+00:15:24,790 --> 00:15:27,350
+تكون سنوات الخبرة تلاتة معناته راتب تلاتين ألف
+
+196
+00:15:27,350 --> 00:15:31,390
+سنوات الخبرة تمانية سبعة وخمسين ألف تسعة اربع
+
+197
+00:15:31,390 --> 00:15:35,250
+وستين تلاتاش اتنين وسبعين وها كده لما حاولت ارسمهم
+
+198
+00:15:35,250 --> 00:15:37,810
+هيهم وطبعا هورجيكوا بال Excel لان ممكن انا فعليا
+
+199
+00:15:37,810 --> 00:15:42,610
+ارسم شغل زي هيك بكل بساطة تمام انا هستخدم ال data
+
+200
+00:15:42,610 --> 00:15:47,720
+set هايعشان أشوف كيف بدي أجيب الـ slope أو بدي
+
+201
+00:15:47,720 --> 00:15:50,160
+أجيب معادلة الخط المستقيم اللي بمثل الخط الأحمر
+
+202
+00:15:50,160 --> 00:15:53,840
+هذا اللي أنا قرأ اسم ال data set اللي موجودة عندي
+
+203
+00:15:53,840 --> 00:15:57,200
+تعالوا نبدأ نتذكر بس مع بعض على السريع إن
+
+204
+00:15:57,200 --> 00:16:02,320
+المعادلات اللي عندي أنا الآن معادلات ثابتة اللي هي
+
+205
+00:16:02,320 --> 00:16:08,660
+معادلة الخط المستقيم Y تساوي الـ Y اللي هي ال
+
+206
+00:16:08,660 --> 00:16:11,380
+predictive value اللي أنا بدي إياها تساوي ال M في
+
+207
+00:16:11,380 --> 00:16:17,940
+Xالـ Dependent Variable يساوي الـ male slope M في
+
+208
+00:16:17,940 --> 00:16:21,580
+قيمة الـ Independent Variable زائد B اللي هي الـ
+
+209
+00:16:21,580 --> 00:16:24,780
+Intercept اللي موجودة عندي قيمة ال slope حسب
+
+210
+00:16:24,780 --> 00:16:29,020
+المعادلة السابقة حسب الرسم اللي موجود عندي هنا في
+
+211
+00:16:29,020 --> 00:16:32,080
+الخط المستقيم عفوا ان انا في عندى slide check اللي
+
+212
+00:16:32,080 --> 00:16:38,960
+عملها hide مش قضية كتير المعادلة اللي عندي هيها
+
+213
+00:16:38,960 --> 00:16:39,180
+هنا
+
+214
+00:16:48,160 --> 00:17:00,320
+yes بالخطأ عمل hide لل slide تبع
+
+215
+00:17:00,320 --> 00:17:03,160
+لمعادلة الخط المستقيم اللي احنا بنعرفها حكينا
+
+216
+00:17:03,160 --> 00:17:08,200
+عليها سابقا حاولنا نفصل اكتر فيها هي ال slope
+
+217
+00:17:09,530 --> 00:17:13,690
+المقدار التغيير اللي على النقطة بس هذا التغيير
+
+218
+00:17:13,690 --> 00:17:17,370
+لمين؟ للنقطين هدول طب النقطين التانيات اللي في
+
+219
+00:17:17,370 --> 00:17:22,090
+المثلة أنا فعلياً ماعنديش نقطين هذا الخط المستقيم
+
+220
+00:17:22,090 --> 00:17:26,350
+مش موجود أنا عندي مجموعة نقاط تمام؟ بدي أحاول أجيب
+
+221
+00:17:26,350 --> 00:17:30,670
+أفضل خط مستقيم ما بينهم يمثلهم كلهم فأنا بتكلم
+
+222
+00:17:30,670 --> 00:17:33,510
+قاعدة الخط المستقيم تبعي هي عبارة أو ال slope
+
+223
+00:17:33,510 --> 00:17:39,330
+تبعته عبارة عن كل النقاطX ناقص متوسط نقاط X كم
+
+224
+00:17:39,330 --> 00:17:42,070
+نقطة عندك انت على الخط المستقيم هذا؟ أجل الخط
+
+225
+00:17:42,070 --> 00:17:44,070
+المستقيم لجماعة الخيربو يجب أن يكون عنده نقطين
+
+226
+00:17:44,070 --> 00:17:47,670
+عشان انا نقدر أسموه، مظبوط ولا لا؟ طبعا عادة
+
+227
+00:17:47,670 --> 00:17:50,870
+بالهدف احنا بنسميه قطعة مستقيمة محصورة من قطار
+
+228
+00:17:50,870 --> 00:17:55,110
+بينما الخط المستقيم هو بتعدى حدود النقطين اللي
+
+229
+00:17:55,110 --> 00:18:00,270
+موجودة عندها تمام، الآن معناته انا بتكلم هنا ان X
+
+230
+00:18:00,270 --> 00:18:07,000
+عند مجموعة نقاط على ال X ناقص المتوسط مضروبة فيY
+
+231
+00:18:07,000 --> 00:18:10,580
+الفروقات ما بين الـ Y في المتوسط تبعتهم طبعاً
+
+232
+00:18:10,580 --> 00:18:17,320
+بجموعهم على مجموع الفروقات ما بين الـ X XI
+
+233
+00:18:17,320 --> 00:18:22,740
+والمتوسط تبعتهم تربية لكل النقاط اللي موجودة عندها
+
+234
+00:18:22,740 --> 00:18:27,880
+طيب، الآن تعالوا نيجي نشوفمن أين جاء التربية جامعة
+
+235
+00:18:27,880 --> 00:18:32,420
+الخير؟ لأن في الاخر هذه النقاط كلها مثلثات أو فيها
+
+236
+00:18:32,420 --> 00:18:36,900
+ثغرس و كما قلت لك هذه تربية
+
+237
+00:18:39,330 --> 00:18:42,490
+هي تربيه زاد هاي تربيه فاعوض عن كل واحدة فيهم
+
+238
+00:18:42,490 --> 00:18:44,990
+بالتربيع اللي موجود فيها في الآخر احنا هادي
+
+239
+00:18:44,990 --> 00:18:48,850
+معادلتنا اللي موجودة و بدنا نستخدمها تعالى نشوف
+
+240
+00:18:48,850 --> 00:18:52,550
+كيف بدنا نطبقها بشكل كويس الآن هاي النقاط اللي
+
+241
+00:18:52,550 --> 00:18:56,430
+موجودة و هاي التلت معادلات اللي موجودة عندها ال
+
+242
+00:18:56,430 --> 00:19:00,650
+intercept اذا انا حصلت على ال M عند ال Y معلومة و
+
+243
+00:19:00,650 --> 00:19:04,590
+ال X معلومة تمام بيظل عند ال B معناته ال B بدها
+
+244
+00:19:04,590 --> 00:19:10,940
+تساويبجيب متوسط تغييرات أو متوسط قيم ال Y ناقص ال
+
+245
+00:19:10,940 --> 00:19:15,240
+slope في متوسط قيم ال X اللي موجودة عندها هذه
+
+246
+00:19:15,240 --> 00:19:18,440
+القيام الموجودة وهذه هي المعادلات الثلاثة اللي
+
+247
+00:19:18,440 --> 00:19:22,100
+قلنا أننا تلزمنا تكون حاضرة في ذهننا عند التعامل
+
+248
+00:19:22,100 --> 00:19:26,440
+مع ال symbol regression أو مع ال regression مع ال
+
+249
+00:19:26,440 --> 00:19:28,540
+linear regression عفوا مع ال linear regression
+
+250
+00:19:28,540 --> 00:19:34,810
+تمام، طيب، هي عندي Xهذه العمودين اللي بدي أشغل
+
+251
+00:19:34,810 --> 00:19:40,910
+عليهم، ماهي المعادلة؟ بالزمن أن أحسب المتوسط تبع
+
+252
+00:19:40,910 --> 00:19:47,560
+ال X والمتوسط الحسابي تبع ال Yفي كل الحالات اللي
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+253
+00:19:47,560 --> 00:19:52,480
+عندي تمام متوسط X معناته مجموحهم على عددهم واحدة
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+254
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+255
+00:19:56,400 --> 00:20:01,680
+تلاتة هي احداشر هي عشرين تلاتة وتلاتين ستة وتلاتين
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+256
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+وسبعين91 بالمتوسط 9.10 حسبت المتوسط ل X حسبنا
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+00:20:20,000 --> 00:20:28,460
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+259
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+او بدي اجيب حاصل ضرب كل X ناقص قيمة المتوسط 9-1
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+260
+00:20:39,970 --> 00:20:44,930
+أضربها في قيمة الـ y كل قيم الـ y ناقص المتوسط
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+ناقص متوسط ال x احسب x او y yi في متوسط ال y فلجيت
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+263
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+هنا فاين روحت حسبت المعادلتين ايهم اشتغلت عليهم في
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+264
+00:21:03,610 --> 00:21:05,210
+شكل آلي تلاتة
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+265
+00:21:09,120 --> 00:21:14,740
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+266
+00:21:14,740 --> 00:21:15,940
+واحد نقص واحد نقص واحد نقص واحد نقص واحد نقص واحد
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+267
+00:21:15,940 --> 00:21:17,720
+نقص واحد نقص واحد نقص واحد نقص واحد نقص واحد نقص
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+268
+00:21:17,720 --> 00:21:18,740
+واحد نقص واحد نقص واحد نقص واحد نقص واحد نقص واحد
+
+269
+00:21:18,740 --> 00:21:19,220
+نقص واحد نقص واحد نقص واحد نقص واحد نقص واحد نقص
+
+270
+00:21:19,220 --> 00:21:25,130
+واحد نقص واحد نقص واحد نقص واحد نقص واحد نقص وا8-9
+
+271
+00:21:25,130 --> 00:21:34,830
+.1 1.1 57-55.4 1.6 و بكمل الجدول بالكامل ممتاز
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+272
+00:21:34,830 --> 00:21:39,950
+الخطوة التالية هذه العناصر بتلزمني في حالتين بدي
+
+273
+00:21:39,950 --> 00:21:43,310
+اضرب high في high و احصل على high تربيع من أجل
+
+274
+00:21:43,310 --> 00:21:50,000
+المقام اللي هنا فاني روحت جبت ال busعناصر البط
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+275
+00:21:50,000 --> 00:21:56,580
+اللي هي x i ناقص x متوسط الـ x مضروبة في y i ناقص
+
+276
+00:21:56,580 --> 00:22:04,440
+متوسط الـ yبوينجوسين هانضربت سالب ستة point واحد
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+277
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+279
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+280
+00:22:17,280 --> 00:22:22,460
+وعشرين وكملتللآخر كل العملية الحسابية تبعتي طبعا
+
+281
+00:22:22,460 --> 00:22:24,560
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+282
+00:22:24,560 --> 00:22:27,140
+زي هيك و قلت لك هاتلي او هاتلي معادلة الخط
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+283
+00:22:27,140 --> 00:22:30,840
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+
+284
+00:22:30,840 --> 00:22:34,300
+اربع لخمس قيم تشتغل عليهم يعني نص القيم الموجودة و
+
+285
+00:22:34,300 --> 00:22:37,200
+عشان هيك بأكد باستمرار ان ال calculator لازم يكون
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+286
+00:22:37,200 --> 00:22:43,380
+عندك جاهزة في الحساب تمام الخطوة اللي بعد هيكأنا
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+287
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+بتلزمني المجميع المجميع لمين؟ لكل عمود حسب
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+288
+00:22:46,320 --> 00:22:49,180
+المعادلة اللى موجودة عندى هنا فروح اتجمع العمود
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+289
+00:22:49,180 --> 00:22:53,760
+هذا انهيه تلاتمية اللى هي قيمة البسط تلاتمية
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+290
+00:22:53,760 --> 00:22:59,460
+تمانية وخمسين point تسعة وحسبت قيمة العمود التانى
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+291
+00:22:59,460 --> 00:23:04,660
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+292
+00:23:04,660 --> 00:23:12,890
+M تساوي ألف و متين علىتلات تلاف وتمانية خمسة تلات
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+293
+00:23:12,890 --> 00:23:16,650
+تلاف تلاتمية تمانية وخمسين point تسعة فبتطلع قيمة
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+294
+00:23:16,650 --> 00:23:22,930
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+295
+00:23:22,930 --> 00:23:26,910
+شايفينها تمام أنا الآن حصلت على مين على قيمة ال M
+
+296
+00:23:26,910 --> 00:23:30,770
+في المعادلة هاي من المعادلة هاي بظل عندي بي بي
+
+297
+00:23:30,770 --> 00:23:33,970
+سهلة بما أن انا حصلت على ال بي هي معادلة ال بي
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+298
+00:23:33,970 --> 00:23:36,650
+عفوا ان انا حصلت على ال M وهي معادلة ال بي عندي
+
+299
+00:23:36,650 --> 00:23:38,650
+موجودة هان وبالتالي انا
+
+300
+00:23:42,300 --> 00:23:46,140
+بتساوي متوسط الـ Y التي هي الحسبة الأولى التي كانت
+
+301
+00:23:46,140 --> 00:23:51,040
+في الجدولة التي لديها نهيهم متوسط الـ Y 55.4 ناقص
+
+302
+00:23:51,040 --> 00:23:57,260
+M لـ 3.5375
+
+303
+00:23:57,260 --> 00:24:03,700
+ضرب متوسط ال X 9.1 قيمتهم
+
+304
+00:24:08,260 --> 00:24:16,200
+معادلة الخط المستقيم مُعادلة M مُعادلة P مُعادلة M
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+305
+00:24:16,200 --> 00:24:22,680
+مُعادلة P مُعادلة M مُعادلة P مُعادلة M مُعادلة P
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+306
+00:24:22,680 --> 00:24:23,340
+مُعادلة M مُعادلة P
+
+307
+00:24:28,080 --> 00:24:40,280
+3.5375 ضرب الـ M زائد
+
+308
+00:24:40,280 --> 00:24:46,260
+ال B لو انا بدى اتأكد ان معدلتي صحيحة او غير صحيحة
+
+309
+00:24:46,260 --> 00:24:49,760
+تخيل ان قيمة X تساوي 1 المفروض انها تساوي 20
+
+310
+00:24:50,690 --> 00:24:54,550
+المفروض لكن الكلام الأدق يكون القيمة قريبة من
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+311
+00:24:54,550 --> 00:25:05,630
+العشرين ثلاثة point خمسة ثلاثة سبعة خمسة زائد
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+312
+00:25:05,630 --> 00:25:11,690
+تلاتة وعشرين point متين وتسعة ملاحظين قدش القيمة
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+313
+00:25:11,690 --> 00:25:18,390
+اللي طلعت عندي أناتلاتة و عشرين و اتنين من عشرة و
+
+314
+00:25:18,390 --> 00:25:23,850
+تلاتة و سبعة و خمسة معناته احنا بنتكلم على ستة و
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+315
+00:25:23,850 --> 00:25:30,350
+عشرين point سبعة هذه قيمة لما كانت ال X تساوي واحد
+
+316
+00:25:30,350 --> 00:25:33,270
+ليش لأنه بضال فيه نسبة خاطئة ماحدش قال في الدنيا
+
+317
+00:25:33,270 --> 00:25:40,130
+ان هذا ال algorithm او هذا ال modelهيديني 100%
+
+318
+00:25:40,130 --> 00:25:44,670
+القيم المتساوية لان هناك قيم متفرقة لو رجعت للرسم
+
+319
+00:25:44,670 --> 00:25:49,070
+على السريععشان تشوفوها هيه فعلا هيه النقاط تبعتي
+
+320
+00:25:49,070 --> 00:25:52,630
+النقاط متجاهة على الخط المستقيم ولو جربت انت تاخد
+
+321
+00:25:52,630 --> 00:25:55,490
+نقاط على الخط المستقيم هتطلع معاك typical قيمة ال
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+322
+00:25:55,490 --> 00:26:00,030
+M وقيمة ال B تمام بعد ما انا حسبت القيم هذه على
+
+323
+00:26:00,030 --> 00:26:02,730
+السريع خليني اروح اشوف بال python ايش انا بده
+
+324
+00:26:02,730 --> 00:26:05,870
+اساوي انا روحت على ال python استخدمت ال numpy
+
+325
+00:26:05,870 --> 00:26:10,910
+كمكتبة عشان اتعامل مع ال numerical python arrays
+
+326
+00:26:10,910 --> 00:26:16,060
+وبنيت الريلة ال X وبنيت الريلة ال Yلكن يوجد شغل
+
+327
+00:26:16,060 --> 00:26:19,180
+هنا إنه لازم اعمل Reshape عشان اعمل Transpose تبعت
+
+328
+00:26:19,180 --> 00:26:25,080
+المصفوفة وهي عبارة عن مصفوفة من بعد واحد اكتر
+
+329
+00:26:25,080 --> 00:26:29,120
+وليست vectorتمام فعشان هيك بعملها Reshape سالب
+
+330
+00:26:29,120 --> 00:26:31,620
+واحد هذا طبعا لأنه أنا فعليا جامعة الخير برجع
+
+331
+00:26:31,620 --> 00:26:33,800
+بأكيد أنه أنا جاعت بقاشطة بدي أبني ال data set
+
+332
+00:26:33,800 --> 00:26:35,880
+بينما ال data set ممكن تكون معايا جاهزة زي ما في
+
+333
+00:26:35,880 --> 00:26:38,340
+ال data set اللي انت اختارتها في الواجب الأول تبعت
+
+334
+00:26:38,340 --> 00:26:41,280
+ال regression data set اللي كنا بنتكلم عليها أنت
+
+335
+00:26:41,280 --> 00:26:44,700
+بدك تقطع منها عمود واحد فقط وتشتغل عليه وتشوف
+
+336
+00:26:44,700 --> 00:26:48,780
+العلاقة ما بينها وبين ال target attribute اللي هي
+
+337
+00:26:48,780 --> 00:26:50,920
+ال continuous value بدك تعملها prediction وروح
+
+338
+00:26:50,920 --> 00:26:55,370
+اتدخلت القيم اللي موجودة عندي أنا غادفيه الـ
+
+339
+00:26:55,370 --> 00:26:58,650
+values اللي دخلتها على المصروفة بدون ماعمل الـ
+
+340
+00:26:58,650 --> 00:27:02,890
+Harry shape روحت from ال ASCII learn dot linear
+
+341
+00:27:02,890 --> 00:27:05,710
+model import linear regression وانا ما زلت بأكد
+
+342
+00:27:05,710 --> 00:27:08,270
+انه يشغل على linear regression وبالتحديد بما انا
+
+343
+00:27:08,270 --> 00:27:12,870
+بتكلم على one independent attribute معناته انا
+
+344
+00:27:12,870 --> 00:27:18,330
+بتكلم على simple linear regressionبنيت الموديل
+
+345
+00:27:18,330 --> 00:27:22,270
+موديل تساوي linear regression الموديل dot fit عشان
+
+346
+00:27:22,270 --> 00:27:25,730
+يعمل train ويوجد العلاقة اللي ما بين ال X وال Y
+
+347
+00:27:25,730 --> 00:27:28,430
+اللي هي ال independent attribute X وال dependent
+
+348
+00:27:28,430 --> 00:27:33,830
+variable او ال dependent attribute Y فروحت انا
+
+349
+00:27:33,830 --> 00:27:39,390
+اعمل fit المفروض بعد عملية ال fit هذه هو حصل على
+
+350
+00:27:39,390 --> 00:27:45,350
+ال slope ال M وحصل على ال Bهنا لان انا بس بدي
+
+351
+00:27:45,350 --> 00:27:49,250
+اطبعهم فروح و قلت له اطبعلي ال model. coefficient
+
+352
+00:27:49,250 --> 00:27:53,170
+ال model هيو dot coefficient underscore فبطبعلي
+
+353
+00:27:53,170 --> 00:27:56,730
+قيمة و روح اضفت عليهم عشان تظهر معادلة خط مستقيم
+
+354
+00:27:56,730 --> 00:27:59,430
+بس مش اكتر ال model. coefficient و ال model.
+
+355
+00:27:59,790 --> 00:28:02,650
+intercept ال intercept اللي هي ال mail او التقاط
+
+356
+00:28:02,650 --> 00:28:06,010
+مع بي و ال coefficient اللي هي ال mail اللي موجود
+
+357
+00:28:06,010 --> 00:28:11,660
+عندي هناالـ output طلّع ليه هى لو أنا جيت طلعت في
+
+358
+00:28:11,660 --> 00:28:20,280
+قيمة 3 point خمسة تلاتة سبعة القيم اللى طلعت معايا
+
+359
+00:28:20,280 --> 00:28:24,100
+لما انا اختصرتها سبعة خمسة لانه عملت round للسبعة
+
+360
+00:28:24,100 --> 00:28:31,120
+وهنا تلاتة وعشرين point متين وتسعة لانه برضه عملت
+
+361
+00:28:31,120 --> 00:28:34,440
+round للرقم اللى موجود عندها typical نفس ال values
+
+362
+00:28:34,440 --> 00:28:38,710
+اللى موجودة لو انا بدى اعمل predictionهيبقى انا في
+
+363
+00:28:38,710 --> 00:28:42,270
+ال array روحت على ال X قلت له في عندي X test هاي
+
+364
+00:28:42,270 --> 00:28:48,710
+في عند النقاط تبعتي ال array 2 و 9 و 13 و 18 و 24
+
+365
+00:28:48,710 --> 00:28:57,370
+و يعمل لي ال Y predict تبعتهم تمام الان
+
+366
+00:28:57,370 --> 00:29:02,050
+هادول هيروح يجيبلي بناء على المعادلة هاي هياخد 2
+
+367
+00:29:02,050 --> 00:29:09,110
+يعني تلاتة pointخمسة أربعة ضرب اتنين زائد تلاتة
+
+368
+00:29:09,110 --> 00:29:12,690
+وعشرين متين وتسعة حدين قيمتي التنين تسعة لكن
+
+369
+00:29:12,690 --> 00:29:15,550
+لاحظوا الآن يا جماعة الخير ان هذه القيم المجتمعة
+
+370
+00:29:15,550 --> 00:29:20,510
+كلها بدت تخضع لمين تخضع لنفس المعادل اللي عملها
+
+371
+00:29:20,510 --> 00:29:24,270
+prediction هنا خلاص انتهى الأمر لأن أنا عمال بتكلم
+
+372
+00:29:24,270 --> 00:29:29,330
+على ال model dot predict فانا زودت بالقائمة تبعتي
+
+373
+00:29:29,330 --> 00:29:35,340
+هذه وهو اشرح سوارح أعملها predict فعشان هيك بتطلع
+
+374
+00:29:35,340 --> 00:29:38,580
+معايا معادلة خط مستقيم بالتمام طب عشان أوجد
+
+375
+00:29:38,580 --> 00:29:42,080
+العلاقة اللي موجودة عندي هان روحت استخدية مكتبة
+
+376
+00:29:42,080 --> 00:29:43,660
+اسمها الـ
+
+377
+00:29:43,660 --> 00:29:47,360
+matplotlibrarymathematicalplottinglibrary
+
+378
+00:29:47,360 --> 00:29:49,980
+.pythonplot
+
+379
+00:29:51,750 --> 00:29:55,190
+as plt بدي ارسم و روح اقول في ال plot هذه قلت له
+
+380
+00:29:55,190 --> 00:29:58,070
+في عندي scatter اللي هي النقاط عند x و y هي هم
+
+381
+00:29:58,070 --> 00:30:01,970
+موجودات هي x و y اللي موجودات فوق عندها و ال color
+
+382
+00:30:01,970 --> 00:30:06,690
+black نقاط باللون الأسود و في عندى بدي اعمل plot
+
+383
+00:30:06,690 --> 00:30:10,050
+كذلك كرسم خط مستقل ال plot اللي بتكلم على function
+
+384
+00:30:10,050 --> 00:30:14,650
+أو على equation ال plot x test اللي هي هذه اتنين
+
+385
+00:30:14,650 --> 00:30:18,590
+وتسعة و تلتاش و تمانتاش وأربعة و في ال color و ال
+
+386
+00:30:18,590 --> 00:30:22,780
+y predictهي هي ال result تبع ال prediction بتاعة
+
+387
+00:30:22,780 --> 00:30:25,980
+ال model اللي أنا استخدمته و الخط باللون الأخضر و
+
+388
+00:30:25,980 --> 00:30:30,700
+ال line width فروحت قلتله اعمل تبين ال text على ال
+
+389
+00:30:30,700 --> 00:30:34,240
+X و ال Y اللي هي النقاط و قلتله show تعالى نشوف هى
+
+390
+00:30:34,240 --> 00:30:38,580
+النتيجة اللى قبعليها هى النقاط اللى موجودة عندهان
+
+391
+00:30:38,580 --> 00:30:44,300
+تمام و هى الخط المستقيم اللى بتمثله المعادلة اللى
+
+392
+00:30:44,300 --> 00:30:47,160
+موجودة عندها بدي اروح اناويك الان بس على ال X اللى
+
+393
+00:30:47,160 --> 00:30:51,440
+على السريعوبالـ Excel أورجيك فعليًا إنه هي الخط
+
+394
+00:30:51,440 --> 00:30:56,220
+اللي أنا اشتغلته بكل بساطة سيبني من كل من الحسبة
+
+395
+00:30:56,220 --> 00:31:00,580
+اللي انا اشتغلتها أو حاولت اشتغلها معها أطبقها هنا
+
+396
+00:31:00,580 --> 00:31:03,520
+على السريع الفكرة لو أنا هي القيم اللي موجودة عندي
+
+397
+00:31:03,520 --> 00:31:07,440
+ضللتها بالشكل هذا بالـ Excel وروحت على insert
+
+398
+00:31:07,440 --> 00:31:12,040
+وروحت
+
+399
+00:31:12,040 --> 00:31:15,820
+اخترت letter أو scatter نقاط هي النقاط
+
+400
+00:31:18,410 --> 00:31:23,050
+حاضر هكبرها شوية بحيث انه ضيين النقاط هي النقاط
+
+401
+00:31:23,050 --> 00:31:27,770
+اللي موجودة عندي هان وماخدين عندي في عندي النقاط
+
+402
+00:31:27,770 --> 00:31:31,310
+هذه بتروح على النقاط هذه لاحظوا في عندي add trend
+
+403
+00:31:31,310 --> 00:31:35,770
+line add trend line اضفتله ل trend line فراح
+
+404
+00:31:35,770 --> 00:31:38,850
+رسمليها بالشكل اللي موجود عندي هان طبعا لو قلتله
+
+405
+00:31:38,850 --> 00:31:43,510
+انا linear مباشرة هي exponential logistic
+
+406
+00:31:43,510 --> 00:31:47,910
+polynomial logarithmic عفوا logarithmic polynomial
+
+407
+00:31:48,700 --> 00:31:53,700
+الـ Power الـ Moving Averages لكن فعلياً بما أن
+
+408
+00:31:53,700 --> 00:31:58,280
+الدالة تبعتي Linear فهي أنسب خط موجود عندى مش بس
+
+409
+00:31:58,280 --> 00:32:01,200
+هيك لو انا روحت و قلت له display equation on chart
+
+410
+00:32:01,200 --> 00:32:05,900
+فرح عرضلي المعادلة او ال equation هيها هان خليني
+
+411
+00:32:05,900 --> 00:32:11,570
+بس اكبر خطها شوية صغيرة عشان نقدر نشوفه مع بعضوبعض
+
+412
+00:32:11,570 --> 00:32:14,950
+تيبيكال ليش لأنه فعليا مافيش مجال هي حسبة ال slope
+
+413
+00:32:14,950 --> 00:32:18,630
+وهي حسبة ال M وهي حسبة المعادلة الخط المستقيم اللي
+
+414
+00:32:18,630 --> 00:32:23,510
+انا ممكن اشتغل عليه وبهك احنا بنكون اتكلمنا عن ال
+
+415
+00:32:23,510 --> 00:32:27,370
+linear regression بكتفي بالتسجيل هذا ان شاء الله
+
+416
+00:32:27,370 --> 00:32:31,850
+تعالى و هكمل معاكم في ال multiple regression و ال
+
+417
+00:32:31,850 --> 00:32:36,190
+non-linear regression و ال evaluationخلال ال part
+
+418
+00:32:36,190 --> 00:32:39,110
+التاني ان شاء الله تعالى الله يعطيكم العافية
+
+419
+00:32:39,110 --> 00:32:41,650
+والسلام عليكم ورحمة الله وبركاته
+
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/zzmXFQBnsgA_raw.json b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/zzmXFQBnsgA_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..ca02ad73104b4dfd111292a534a9554a64dbee62
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/zzmXFQBnsgA_raw.json
@@ -0,0 +1 @@
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"end": 1.74, "word": " والحمد", "probability": 0.8673502604166666}, {"start": 1.74, "end": 2.04, "word": " لله", "probability": 0.972900390625}, {"start": 2.04, "end": 2.5, "word": " والصلاة", "probability": 0.8802490234375}, {"start": 2.5, "end": 2.98, "word": " والسلام", "probability": 0.9811197916666666}, {"start": 2.98, "end": 3.22, "word": " على", "probability": 0.77685546875}, {"start": 3.22, "end": 3.56, "word": " رسول", "probability": 0.9949544270833334}, {"start": 3.56, "end": 3.82, "word": " الله", "probability": 0.94873046875}, {"start": 3.82, "end": 4.92, "word": " أهلا", "probability": 0.9427083333333334}, {"start": 4.92, "end": 5.26, "word": " وسهلا", "probability": 0.7017008463541666}, {"start": 5.26, "end": 5.72, "word": " فيكم", "probability": 0.739013671875}, {"start": 5.72, "end": 6.96, "word": " في", "probability": 0.96142578125}, {"start": 6.96, "end": 7.98, "word": " محاضرتنا", "probability": 0.9740234375}, {"start": 7.98, "end": 9.14, "word": " الجديدة", 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طريق الـ Multiple Variable وفي كل الحالتين الموديل تبعي ممكن يكون Linear وممكن يكون Non-Linear في كل الحالتين", "tokens": [3615, 1863, 23032, 16572, 4587, 2423, 39184, 40310, 32511, 712, 4032, 3615, 1863, 23032, 16572, 4587, 2423, 39184, 40056, 32511, 712, 4032, 41185, 28242, 21542, 6027, 2655, 9957, 9673, 2407, 16254, 1211, 6055, 3555, 3615, 1829, 3714, 43020, 7251, 30544, 14670, 289, 4032, 2304, 43020, 7251, 30544, 8774, 12, 43, 533, 289, 8978, 28242, 21542, 6027, 2655, 9957], "avg_logprob": -0.5455508636215985, "compression_ratio": 1.6390977443609023, "no_speech_prob": 0.0, "words": [{"start": 665.65, "end": 665.91, "word": "عن", "probability": 0.267669677734375}, {"start": 665.91, "end": 665.91, "word": " طريق", "probability": 0.82861328125}, {"start": 665.91, "end": 665.91, "word": " الـ", "probability": 0.3790283203125}, {"start": 665.91, "end": 666.13, "word": " Independent", "probability": 0.26611328125}, {"start": 666.13, "end": 666.73, "word": " Variable", "probability": 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1536.65, "end": 1545.65, "text": "هيديني 100% القيم المتساوية لان هناك قيم متفرقة لو رجعت للرسم على السريع", "tokens": [3224, 1829, 3215, 9957, 1829, 2319, 4, 25062, 32640, 9673, 2655, 3794, 995, 2407, 10632, 5296, 7649, 34105, 4117, 12174, 32640, 44650, 5172, 2288, 28671, 45164, 12602, 7435, 34268, 24976, 2288, 38251, 15844, 21136, 16572, 3615], "avg_logprob": -0.35916385135135137, "compression_ratio": 1.3473684210526315, "no_speech_prob": 0.0, "words": [{"start": 1536.65, "end": 1537.83, "word": "هيديني", "probability": 0.5531005859375}, {"start": 1537.83, "end": 1539.07, "word": " 100", "probability": 0.495361328125}, {"start": 1539.07, "end": 1540.13, "word": "%", "probability": 0.9072265625}, {"start": 1540.13, "end": 1540.53, "word": " القيم", "probability": 0.75927734375}, {"start": 1540.53, "end": 1541.41, "word": " المتساوية", "probability": 0.8460286458333334}, {"start": 1541.41, "end": 1541.83, "word": " لان", "probability": 0.525634765625}, {"start": 1541.83, "end": 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1608.78, "end": 1608.86, "word": " ال", "probability": 0.75634765625}, {"start": 1608.86, "end": 1609.18, "word": " continuous", "probability": 0.85595703125}, {"start": 1609.18, "end": 1609.44, "word": " value", "probability": 0.970703125}, {"start": 1609.44, "end": 1609.62, "word": " بدك", "probability": 0.6868896484375}, {"start": 1609.62, "end": 1609.9, "word": " تعملها", "probability": 0.972412109375}, {"start": 1609.9, "end": 1610.24, "word": " prediction", "probability": 0.90234375}, {"start": 1610.24, "end": 1610.92, "word": " وروح", "probability": 0.6958821614583334}, {"start": 1610.92, "end": 1611.42, "word": " اتدخلت", "probability": 0.8670247395833334}, {"start": 1611.42, "end": 1611.76, "word": " القيم", "probability": 0.916748046875}, {"start": 1611.76, "end": 1611.96, "word": " اللي", "probability": 0.972412109375}, {"start": 1611.96, "end": 1612.5, "word": " موجودة", "probability": 0.98193359375}, {"start": 1612.5, "end": 1612.82, "word": " عندي", "probability": 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"probability": 0.87548828125}, {"start": 1623.75, "end": 1624.15, "word": " linear", "probability": 0.94287109375}, {"start": 1624.15, "end": 1624.63, "word": " regression", "probability": 0.9580078125}, {"start": 1624.63, "end": 1624.99, "word": " وانا", "probability": 0.69384765625}, {"start": 1624.99, "end": 1625.13, "word": " ما", "probability": 0.61328125}, {"start": 1625.13, "end": 1625.33, "word": " زلت", "probability": 0.94287109375}, {"start": 1625.33, "end": 1625.71, "word": " بأكد", "probability": 0.90380859375}, {"start": 1625.71, "end": 1625.85, "word": " انه", "probability": 0.668701171875}, {"start": 1625.85, "end": 1626.27, "word": " يشغل", "probability": 0.840087890625}, {"start": 1626.27, "end": 1626.45, "word": " على", "probability": 0.74560546875}, {"start": 1626.45, "end": 1626.79, "word": " linear", "probability": 0.93603515625}, {"start": 1626.79, "end": 1627.25, "word": " regression", "probability": 0.97509765625}, {"start": 1627.25, "end": 1627.99, "word": " وبالتحديد", "probability": 0.9204915364583334}, {"start": 1627.99, "end": 1628.17, "word": " بما", "probability": 0.919677734375}, {"start": 1628.17, "end": 1628.27, "word": " انا", "probability": 0.6607666015625}, {"start": 1628.27, "end": 1628.65, "word": " بتكلم", "probability": 0.9329427083333334}, {"start": 1628.65, "end": 1629.05, "word": " على", "probability": 0.873046875}, {"start": 1629.05, "end": 1630.39, "word": " one", "probability": 0.85693359375}, {"start": 1630.39, "end": 1632.07, "word": " independent", "probability": 0.9130859375}, {"start": 1632.07, "end": 1632.53, "word": " attribute", "probability": 0.9443359375}, {"start": 1632.53, "end": 1632.79, "word": " معناته", "probability": 0.7014973958333334}, {"start": 1632.79, "end": 1632.87, "word": " انا", "probability": 0.6676025390625}, {"start": 1632.87, "end": 1633.21, "word": " بتكلم", "probability": 0.9365234375}, {"start": 1633.21, "end": 1633.45, "word": " على", "probability": 0.81982421875}, {"start": 1633.45, "end": 1634.41, "word": " simple", "probability": 0.7734375}, {"start": 1634.41, "end": 1636.23, "word": " linear", "probability": 0.57080078125}, {"start": 1636.23, "end": 1636.85, "word": " regression", "probability": 0.95703125}], "temperature": 1.0}, {"id": 69, "seek": 166297, "start": 1637.51, "end": 1662.97, "text": "بنيت الموديل موديل تساوي linear regression الموديل dot fit عشان يعمل train ويوجد العلاقة اللي ما بين ال X وال Y اللي هي ال independent attribute X وال dependent variable او ال dependent attribute Y فروحت انا اعمل fit المفروض بعد عملية ال fit هذه هو حصل على ال slope ال M وحصل على ال B", "tokens": [3555, 22653, 2655, 9673, 2407, 16254, 1211, 3714, 2407, 16254, 1211, 6055, 3794, 995, 45865, 8213, 24590, 9673, 2407, 16254, 1211, 5893, 3318, 6225, 8592, 7649, 7251, 25957, 1211, 3847, 4032, 1829, 29245, 3215, 18863, 15040, 28671, 13672, 1829, 19446, 49374, 2423, 1783, 16070, 398, 13672, 1829, 39896, 2423, 6695, 19667, 1783, 16070, 12334, 7006, 1975, 2407, 2423, 12334, 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"probability": 0.91357421875}, {"start": 1651.39, "end": 1651.71, "word": " dependent", "probability": 0.86328125}, {"start": 1651.71, "end": 1652.15, "word": " attribute", "probability": 0.62744140625}, {"start": 1652.15, "end": 1652.73, "word": " Y", "probability": 0.58837890625}, {"start": 1652.73, "end": 1653.61, "word": " فروحت", "probability": 0.8771158854166666}, {"start": 1653.61, "end": 1653.83, "word": " انا", "probability": 0.77734375}, {"start": 1653.83, "end": 1654.23, "word": " اعمل", "probability": 0.8517252604166666}, {"start": 1654.23, "end": 1654.51, "word": " fit", "probability": 0.89111328125}, {"start": 1654.51, "end": 1654.99, "word": " المفروض", "probability": 0.985107421875}, {"start": 1654.99, "end": 1655.23, "word": " بعد", "probability": 0.96484375}, {"start": 1655.23, "end": 1655.67, "word": " عملية", "probability": 0.9930013020833334}, {"start": 1655.67, "end": 1655.89, "word": " ال", "probability": 0.845703125}, {"start": 1655.89, "end": 1656.23, "word": " fit", "probability": 0.76708984375}, {"start": 1656.23, "end": 1656.77, "word": " هذه", "probability": 0.6865234375}, {"start": 1656.77, "end": 1658.47, "word": " هو", "probability": 0.8515625}, {"start": 1658.47, "end": 1658.93, "word": " حصل", "probability": 0.98291015625}, {"start": 1658.93, "end": 1659.39, "word": " على", "probability": 0.9482421875}, {"start": 1659.39, "end": 1659.87, "word": " ال", "probability": 0.646484375}, {"start": 1659.87, "end": 1660.41, "word": " slope", "probability": 0.94140625}, {"start": 1660.41, "end": 1661.69, "word": " ال", "probability": 0.72216796875}, {"start": 1661.69, "end": 1661.91, "word": " M", "probability": 0.89892578125}, {"start": 1661.91, "end": 1662.49, "word": " وحصل", "probability": 0.9051106770833334}, {"start": 1662.49, "end": 1662.71, "word": " على", "probability": 0.96142578125}, {"start": 1662.71, "end": 1662.85, "word": " ال", "probability": 0.9443359375}, {"start": 1662.85, "end": 1662.97, "word": " B", "probability": 0.59326171875}], "temperature": 1.0}, {"id": 70, "seek": 168665, "start": 1664.03, "end": 1686.65, "text": "هنا لان انا بس بدي اطبعهم فروح و قلت له اطبعلي ال model. coefficient ال model هيو dot coefficient underscore فبطبعلي قيمة و روح اضفت عليهم عشان تظهر معادلة خط مستقيم بس مش اكتر ال model. coefficient و ال model. intercept ال intercept اللي هي ال mail او التقاط مع بي و ال coefficient اللي هي ال mail اللي موجود عندي هنا", "tokens": [3224, 8315, 5296, 7649, 1975, 8315, 4724, 3794, 4724, 16254, 1975, 9566, 3555, 3615, 16095, 6156, 32887, 5016, 4032, 12174, 1211, 2655, 46740, 1975, 9566, 3555, 3615, 20292, 2423, 2316, 13, 17619, 2423, 2316, 39896, 2407, 5893, 17619, 37556, 6156, 3555, 9566, 3555, 3615, 20292, 12174, 32640, 3660, 4032, 12602, 2407, 5016, 1975, 11242, 5172, 2655, 25894, 16095, 6225, 8592, 7649, 6055, 19913, 3224, 2288, 20449, 18513, 37977, 16490, 9566, 3714, 14851, 4587, 32640, 4724, 3794, 37893, 1975, 4117, 2655, 2288, 2423, 2316, 13, 17619, 4032, 2423, 2316, 13, 24700, 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"probability": 0.8426106770833334}, {"start": 1919.46, "end": 1919.56, "word": " له", "probability": 0.390869140625}, {"start": 1919.56, "end": 1919.88, "word": " display", "probability": 0.384033203125}, {"start": 1919.88, "end": 1920.52, "word": " equation", "probability": 0.88916015625}, {"start": 1920.52, "end": 1920.72, "word": " on", "probability": 0.931640625}, {"start": 1920.72, "end": 1921.2, "word": " chart", "probability": 0.87109375}, {"start": 1921.2, "end": 1922.14, "word": " فرح", "probability": 0.79345703125}, {"start": 1922.14, "end": 1922.62, "word": " عرضلي", "probability": 0.9303385416666666}, {"start": 1922.62, "end": 1923.86, "word": " المعادلة", "probability": 0.98779296875}, {"start": 1923.86, "end": 1924.12, "word": " او", "probability": 0.79833984375}, {"start": 1924.12, "end": 1924.22, "word": " ال", "probability": 0.947265625}, {"start": 1924.22, "end": 1924.62, "word": " equation", "probability": 0.93896484375}, {"start": 1924.62, "end": 1925.08, "word": " هيها", "probability": 0.902587890625}, {"start": 1925.08, "end": 1925.34, "word": " هان", "probability": 0.5806884765625}, {"start": 1925.34, "end": 1925.9, "word": " خليني", "probability": 0.8028564453125}, {"start": 1925.9, "end": 1926.08, "word": " بس", "probability": 0.947509765625}, {"start": 1926.08, "end": 1926.44, "word": " اكبر", "probability": 0.8561197916666666}, {"start": 1926.44, "end": 1926.78, "word": " خطها", "probability": 0.9871419270833334}, {"start": 1926.78, "end": 1927.06, "word": " شوية", "probability": 0.8513997395833334}, {"start": 1927.06, "end": 1927.38, "word": " صغيرة", "probability": 0.9651692708333334}, {"start": 1927.38, "end": 1927.7, "word": " عشان", "probability": 0.8450520833333334}, {"start": 1927.7, "end": 1927.96, "word": " نقدر", "probability": 0.9580078125}, {"start": 1927.96, "end": 1928.36, "word": " نشوفه", "probability": 0.9818115234375}, {"start": 1928.36, "end": 1928.52, "word": " مع", "probability": 0.9951171875}, {"start": 1928.52, "end": 1928.9, "word": " بعض", "probability": 0.99462890625}], "temperature": 1.0}, {"id": 80, "seek": 195357, "start": 1930.89, "end": 1953.57, "text": "وبعض تيبيكال ليش لأنه فعليا مافيش مجال هي حسبة ال slope وهي حسبة ال M وهي حسبة المعادلة الخط المستقيم اللي انا ممكن اشتغل عليه وبهك احنا بنكون اتكلمنا عن ال linear regression بكتفي بالتسجيل هذا ان شاء الله تعالى و هكمل معاكم في ال multiple regression و ال non-linear regression و ال evaluation", "tokens": [37746, 3615, 11242, 6055, 1829, 21292, 4117, 6027, 32239, 8592, 5296, 33456, 3224, 6156, 3615, 20292, 995, 19446, 41185, 8592, 3714, 7435, 6027, 39896, 11331, 35457, 3660, 2423, 13525, 37037, 1829, 11331, 35457, 3660, 2423, 376, 37037, 1829, 11331, 35457, 3660, 9673, 3615, 18513, 37977, 33962, 9566, 9673, 14851, 4587, 32640, 13672, 1829, 1975, 8315, 3714, 43020, 1975, 8592, 2655, 17082, 1211, 47356, 46599, 3224, 4117, 1975, 5016, 8315, 44945, 30544, 1975, 2655, 4117, 19528, 8315, 18871, 2423, 8213, 24590, 4724, 4117, 2655, 41185, 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"probability": 0.666015625}, {"start": 1934.09, "end": 1934.55, "word": " حسبة", "probability": 0.9689127604166666}, {"start": 1934.55, "end": 1934.67, "word": " ال", "probability": 0.57177734375}, {"start": 1934.67, "end": 1934.95, "word": " slope", "probability": 0.6123046875}, {"start": 1934.95, "end": 1935.21, "word": " وهي", "probability": 0.73583984375}, {"start": 1935.21, "end": 1935.63, "word": " حسبة", "probability": 0.9892578125}, {"start": 1935.63, "end": 1935.75, "word": " ال", "probability": 0.7822265625}, {"start": 1935.75, "end": 1935.89, "word": " M", "probability": 0.67333984375}, {"start": 1935.89, "end": 1936.33, "word": " وهي", "probability": 0.433349609375}, {"start": 1936.33, "end": 1936.71, "word": " حسبة", "probability": 0.99267578125}, {"start": 1936.71, "end": 1937.09, "word": " المعادلة", "probability": 0.8668212890625}, {"start": 1937.09, "end": 1937.51, "word": " الخط", "probability": 0.88916015625}, {"start": 1937.51, "end": 1938.17, "word": " المستقيم", 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"probability": 0.87841796875}, {"start": 1943.93, "end": 1945.27, "word": " regression", "probability": 0.94091796875}, {"start": 1945.27, "end": 1946.25, "word": " بكتفي", "probability": 0.860595703125}, {"start": 1946.25, "end": 1946.83, "word": " بالتسجيل", "probability": 0.9666015625}, {"start": 1946.83, "end": 1947.07, "word": " هذا", "probability": 0.79541015625}, {"start": 1947.07, "end": 1947.17, "word": " ان", "probability": 0.671875}, {"start": 1947.17, "end": 1947.35, "word": " شاء", "probability": 0.911865234375}, {"start": 1947.35, "end": 1947.37, "word": " الله", "probability": 0.92138671875}, {"start": 1947.37, "end": 1947.85, "word": " تعالى", "probability": 0.9236653645833334}, {"start": 1947.85, "end": 1948.15, "word": " و", "probability": 0.861328125}, {"start": 1948.15, "end": 1948.63, "word": " هكمل", "probability": 0.7843424479166666}, {"start": 1948.63, "end": 1949.09, "word": " معاكم", "probability": 0.9051106770833334}, {"start": 1949.09, "end": 1949.43, "word": " في", "probability": 0.884765625}, {"start": 1949.43, "end": 1949.87, "word": " ال", "probability": 0.464111328125}, {"start": 1949.87, "end": 1950.39, "word": " multiple", "probability": 0.87060546875}, {"start": 1950.39, "end": 1951.27, "word": " regression", "probability": 0.96875}, {"start": 1951.27, "end": 1951.75, "word": " و", "probability": 0.50439453125}, {"start": 1951.75, "end": 1951.85, "word": " ال", "probability": 0.8388671875}, {"start": 1951.85, "end": 1951.99, "word": " non", "probability": 0.916015625}, {"start": 1951.99, "end": 1952.25, "word": "-linear", "probability": 0.6441650390625}, {"start": 1952.25, "end": 1952.69, "word": " regression", "probability": 0.984375}, {"start": 1952.69, "end": 1952.89, "word": " و", "probability": 0.66552734375}, {"start": 1952.89, "end": 1952.97, "word": " ال", "probability": 0.76171875}, {"start": 1952.97, "end": 1953.57, "word": " evaluation", "probability": 0.982421875}], "temperature": 1.0}, {"id": 81, "seek": 196165, "start": 1954.93, "end": 1961.65, "text": "خلال ال part التاني ان شاء الله تعالى الله يعطيكم العافية والسلام عليكم ورحمة الله وبركاته", "tokens": [9778, 1211, 6027, 2423, 644, 16712, 7649, 1829, 16472, 13412, 16606, 21984, 37279, 6027, 7578, 21984, 37495, 9566, 1829, 24793, 18863, 31845, 10632, 16070, 3794, 37440, 25894, 24793, 4032, 2288, 35571, 3660, 21984, 4032, 26890, 4117, 9307, 3224], "avg_logprob": -0.1345152266514607, "compression_ratio": 1.4907407407407407, "no_speech_prob": 1.6093254089355469e-06, "words": [{"start": 1954.9299999999998, "end": 1955.61, "word": "خلال", "probability": 0.8805338541666666}, {"start": 1955.61, "end": 1955.83, "word": " ال", "probability": 0.7744140625}, {"start": 1955.83, "end": 1956.19, "word": " part", "probability": 0.61669921875}, {"start": 1956.19, "end": 1956.85, "word": " التاني", "probability": 0.9178059895833334}, {"start": 1956.85, "end": 1957.07, "word": " ان", "probability": 0.407470703125}, {"start": 1957.07, "end": 1957.39, "word": " شاء", "probability": 0.98583984375}, {"start": 1957.39, "end": 1957.85, "word": " الله", "probability": 0.9130859375}, {"start": 1957.85, "end": 1958.35, "word": " تعالى", "probability": 0.9591471354166666}, {"start": 1958.35, "end": 1958.53, "word": " الله", "probability": 0.52490234375}, {"start": 1958.53, "end": 1958.79, "word": " يعطيكم", "probability": 0.775634765625}, {"start": 1958.79, "end": 1959.11, "word": " العافية", "probability": 0.9220377604166666}, {"start": 1959.11, "end": 1959.41, "word": " والسلام", "probability": 0.9322916666666666}, {"start": 1959.41, "end": 1959.83, "word": " عليكم", "probability": 0.958251953125}, {"start": 1959.83, "end": 1960.39, "word": " ورحمة", "probability": 0.946044921875}, {"start": 1960.39, "end": 1960.71, "word": " الله", "probability": 0.97314453125}, {"start": 1960.71, "end": 1961.65, "word": " وبركاته", "probability": 0.9845703125}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 1962.8524375, "duration_after_vad": 1886.4256249999962}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/zzmXFQBnsgA_raw.srt b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/zzmXFQBnsgA_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..913347751650252682313485713a868fe8b416b2
--- /dev/null
+++ b/PL9fwy3NUQKwYNuAEg27anya7EYamnohGd/zzmXFQBnsgA_raw.srt
@@ -0,0 +1,1684 @@
+1
+00:00:00,980 --> 00:00:03,820
+بسم الله والحمد لله والصلاة والسلام على رسول الله
+
+2
+00:00:03,820 --> 00:00:10,700
+أهلا وسهلا فيكم في محاضرتنا الجديدة المصورة لمساب
+
+3
+00:00:10,700 --> 00:00:14,820
+تنقيب البيانات اليوم إن شاء الله تعالى هنتكلم عن
+
+4
+00:00:14,820 --> 00:00:20,610
+chapter regressionهنا في الـ regression نتكلم عن
+
+5
+00:00:20,610 --> 00:00:26,830
+الـ task الثانية في الـ predictive category للـ
+
+6
+00:00:26,830 --> 00:00:30,650
+data mining اتفقنا من البداية أن ال data mining
+
+7
+00:00:30,650 --> 00:00:33,730
+تنقسم إلى two tasks
+
+8
+00:00:36,820 --> 00:00:41,280
+واحدة predictive والتانية descriptive واتكلمنا تحت
+
+9
+00:00:41,280 --> 00:00:47,000
+ال category ال predictive tasks في عنده
+
+10
+00:00:47,000 --> 00:00:50,280
+classification وهي التنبؤ بال class label أو بال
+
+11
+00:00:50,280 --> 00:00:58,030
+category value أو بال nominal value بينماالـ Task
+
+12
+00:00:58,030 --> 00:01:00,710
+التانية هي الـ Regression والتنبؤ بالـ Continuous
+
+13
+00:01:00,710 --> 00:01:04,570
+Value وفي المقابل لدينا في الـ Descriptive Task
+
+14
+00:01:04,570 --> 00:01:07,730
+كان في عندنا Clustering وعندنا Association Rules
+
+15
+00:01:07,730 --> 00:01:11,070
+وفي عندنا الـ Outlier Detection وهدول هنتكلم عليهم
+
+16
+00:01:11,070 --> 00:01:15,430
+في الشباتير الجاية خلّينا نبدأ مع الـ Regression
+
+17
+00:01:16,730 --> 00:01:19,590
+الشغلات اللي هنتناولها في محاضرتنا اليوم ال
+
+18
+00:01:19,590 --> 00:01:23,590
+introduction و ال linear regression أو نشرحها و
+
+19
+00:01:23,590 --> 00:01:28,610
+نكمل بعدها في .. ممكن في فيديو تاني او في تسجيل
+
+20
+00:01:28,610 --> 00:01:32,850
+تاني حسب كيف نمشي او ناقص تهلك أو نستخدع من الوقت
+
+21
+00:01:32,850 --> 00:01:36,210
+اللي موجود عندنا طبعا لما اتكلم على ال regression
+
+22
+00:01:36,210 --> 00:01:41,130
+انا جاعل بقى اتكلم ان ال regression يستخدم من أجل
+
+23
+00:01:41,130 --> 00:01:45,150
+التنبؤ
+
+24
+00:01:47,830 --> 00:01:54,390
+بـ range of values of numeric values range of
+
+25
+00:01:54,390 --> 00:01:59,970
+numeric values وهنا
+
+26
+00:01:59,970 --> 00:02:04,770
+بتكلم على continuous value بالتحديد بتكلم على
+
+27
+00:02:04,770 --> 00:02:09,650
+continuous value بالتحديد طبعا ال regression
+
+28
+00:02:09,650 --> 00:02:16,440
+technique تستخدم أوفي موضوع ال prediction زي ما
+
+29
+00:02:16,440 --> 00:02:20,200
+قلنا هي واحدة من ال prediction task اللي انا موجود
+
+30
+00:02:20,200 --> 00:02:23,280
+فيها من أجل ان اتنبأ بقيم زي ما قلنا continuous
+
+31
+00:02:23,280 --> 00:02:28,100
+value ال profit قيمة الأرباح قيمة المبيعات ال
+
+32
+00:02:28,100 --> 00:02:32,420
+debit ال sales عفوا ال debit rates قيمة القروض أو
+
+33
+00:02:32,420 --> 00:02:37,280
+الفائدة ال house values قيم المنازل درجات الحرارة
+
+34
+00:02:37,280 --> 00:02:42,740
+temperatureأو المسافات اللي ممكن استخدامها وكل هذه
+
+35
+00:02:42,740 --> 00:02:45,700
+التنبؤة بأي value continuous سواء كان بالمثال هذا
+
+36
+00:02:45,700 --> 00:02:53,280
+أو تتنبأ بأوزان أو أعمار أو أطوال أو مدة زمانية
+
+37
+00:02:53,280 --> 00:02:57,420
+إلى آخرهم، نحن بتتكلم جانين على أي value بديها
+
+38
+00:02:57,420 --> 00:03:01,020
+number تطلع قدامي أو numberic value، معناته أنا
+
+39
+00:03:01,020 --> 00:03:04,660
+بتتكلم على regression طبعا ال regression لما أنا
+
+40
+00:03:04,660 --> 00:03:07,460
+بقعد بتكلم أو زي ما بطلق عليه البعض regression
+
+41
+00:03:07,460 --> 00:03:12,380
+analysisباستخدمها عشان اوجد العلاقة ما بين ال
+
+42
+00:03:12,380 --> 00:03:16,080
+independent attribute او ال independent variable
+
+43
+00:03:16,080 --> 00:03:24,240
+اللي هي ال X وال dependent variable اللي هي ال Y
+
+44
+00:03:24,240 --> 00:03:28,320
+طبعا الرسمة هذه واضحة جدا بتقول هي ال independent
+
+45
+00:03:28,320 --> 00:03:32,880
+value اللي هي قيمة ال X وهي في عند ال dependent
+
+46
+00:03:32,880 --> 00:03:36,900
+value او ال attribute او ال variable عفوا اللي هي
+
+47
+00:03:36,900 --> 00:03:42,150
+قيمة ال Y وطبعالما انا بتكلم عن ال regression
+
+48
+00:03:42,150 --> 00:03:48,210
+بتقدر اصنفها لنوعين في عندي simple regression و
+
+49
+00:03:48,210 --> 00:03:50,730
+لما بتكلم عن اسمها simple regression معناته انا
+
+50
+00:03:50,730 --> 00:03:58,810
+بتكلم عن ابسط نوع من انواع التنبؤ وهذه عادة بتتضمن
+
+51
+00:03:58,810 --> 00:04:02,510
+او simple regression بتتضمن فقط two variables two
+
+52
+00:04:02,510 --> 00:04:05,010
+variables نعم two variables واحد بيكون dependent
+
+53
+00:04:05,010 --> 00:04:08,920
+variable والتاني بيكون independentطبعاً واحد بيكون
+
+54
+00:04:08,920 --> 00:04:12,560
+في عندي ال explanatory والثاني بيكون اللي هي ال
+
+55
+00:04:12,560 --> 00:04:17,620
+response زي ما احنا سمناه يعني الآن ال Y هي ال
+
+56
+00:04:17,620 --> 00:04:20,620
+dependent وال X هي ال independent ما تنساش من
+
+57
+00:04:20,620 --> 00:04:24,520
+الأمثلة الموجودة اللي أنا بتكلم عن ال population و
+
+58
+00:04:24,520 --> 00:04:30,100
+ال food production الكثقة للناسزيادة السكان
+
+59
+00:04:30,100 --> 00:04:34,860
+والحاجة إلى إنتاج الغذاء اللي موجود عندهم طبعا لو
+
+60
+00:04:34,860 --> 00:04:37,580
+أنا جاي تتكلمت أنه بدي أتكلم في المجزئية هذه بشكل
+
+61
+00:04:37,580 --> 00:04:41,760
+بصير لو انا افترضت انه انا هيكي عند الرسم high
+
+62
+00:04:41,760 --> 00:04:47,000
+high
+
+63
+00:04:47,000 --> 00:04:51,770
+X بتمثلبتقولك مين مرتبط في مين لو انا سألك سؤال
+
+64
+00:04:51,770 --> 00:04:56,710
+الكلان مين مرتبط في مين او مين معتمد على مين زيادة
+
+65
+00:04:56,710 --> 00:05:01,630
+السكان ال population معتمدة على إنتاج الغذاء ولا
+
+66
+00:05:01,630 --> 00:05:09,770
+إنتاج الغذاء معتمد على زيادة السكان نعم معناته انا
+
+67
+00:05:09,770 --> 00:05:11,890
+بتكلم ان هنا بتكلم ال population
+
+68
+00:05:14,460 --> 00:05:18,780
+هي الـ Independent Variable لأنه حسب العدد السكان
+
+69
+00:05:18,780 --> 00:05:23,200
+أنا بتكلم على اني جداش بدي أنتج غذاء وهنا بتكلم
+
+70
+00:05:23,200 --> 00:05:31,540
+على food production الآن لو أنا نظرت كان في عندي
+
+71
+00:05:31,540 --> 00:05:37,180
+معادلة خطية بالشكل هذا شو هذا بيعني؟ بيعني كل ما
+
+72
+00:05:37,180 --> 00:05:41,220
+يزيد عدد السكان
+
+73
+00:05:45,780 --> 00:05:50,120
+هيزيد عند مين الحاجة
+
+74
+00:05:50,120 --> 00:05:55,400
+إلى إنتاج غذائي أكبر وهذه هي العلاقة هيمفهوم ال
+
+75
+00:05:55,400 --> 00:05:58,180
+prediction يعني لو انا افترضت إن السكانة هيكون في
+
+76
+00:05:58,180 --> 00:06:02,660
+عندهان 200 مليار
+
+77
+00:06:02,660 --> 00:06:09,760
+معناته بدي يكون في عندهان مش عارف كام قن تمام
+
+78
+00:06:14,860 --> 00:06:17,280
+يعني لما انا بتكلم عن الـ simple regression بتكلم
+
+79
+00:06:17,280 --> 00:06:20,740
+على انه فقط two variables واحد independent واحد
+
+80
+00:06:20,740 --> 00:06:24,120
+dependent بينما بال multiple regression معناته انا
+
+81
+00:06:24,120 --> 00:06:30,640
+في عندى اكثر من independent variable لاحظوا في
+
+82
+00:06:30,640 --> 00:06:34,660
+الحالة الأولى انا اتكلمت انه انا في عندى2
+
+83
+00:06:34,660 --> 00:06:38,180
+variables فقط ال data set تبعتي أو ال task تبعتي
+
+84
+00:06:38,180 --> 00:06:40,760
+فقط 2 variables و من هنا أنا بتكلم مباشرة واحد
+
+85
+00:06:40,760 --> 00:06:44,420
+dependent والتاني independent لأنه مستحيل في ال
+
+86
+00:06:44,420 --> 00:06:49,120
+predictive task يكون عندى التنين independent فلازم
+
+87
+00:06:49,120 --> 00:06:52,580
+يكون واحد dependent واحد independent لما أجينا
+
+88
+00:06:52,580 --> 00:06:55,500
+نتكلم على ال multiple regression هنا قلنا ال
+
+89
+00:06:55,500 --> 00:06:57,800
+multiple regression معناته أنا بتكلم في عندي more
+
+90
+00:06:57,800 --> 00:07:00,640
+than one independent في عندي أكتر من independent
+
+91
+00:07:00,640 --> 00:07:04,190
+attributeهل يوجد عندي الـ dependent attribute لازم
+
+92
+00:07:04,190 --> 00:07:08,610
+يكون و الا ال task تكون descriptive مش predictive
+
+93
+00:07:08,610 --> 00:07:13,930
+مثل أسعار المنازل لأ لو أنا سألتكوا أسعار البيوت
+
+94
+00:07:13,930 --> 00:07:23,350
+ايش اللي بيحكمها شغلات كتير مساحة البناء ال
+
+95
+00:07:23,350 --> 00:07:29,210
+location الموقع ال price لما عند اخر بيع الموسم
+
+96
+00:07:31,480 --> 00:07:36,220
+أسعار المنازل المشابهة وشغلات كتيرة ممكن تتحكم
+
+97
+00:07:36,220 --> 00:07:39,380
+فيها هذه كلها تبتعمل prediction لو أنا أجيت و
+
+98
+00:07:39,380 --> 00:07:46,200
+أتكلمت على العلاقة ما بين مرض السكري عفاكم الله و
+
+99
+00:07:46,200 --> 00:07:51,820
+جميع المسلمين ان شاء الله و ال human body
+
+100
+00:07:51,820 --> 00:07:54,160
+measurement
+
+101
+00:07:58,120 --> 00:08:04,500
+المؤشرات أو القياسات المتعلقة بجسم الإنسان طوله و
+
+102
+00:08:04,500 --> 00:08:12,000
+وزنه عمره اللهم صلي على سيدنا محمد ال behavior
+
+103
+00:08:12,000 --> 00:08:16,030
+تبعههل في واحد منهم هدول على نفسه اللي انا ذكرتها
+
+104
+00:08:16,030 --> 00:08:18,750
+فقط بأثر في السكر ان يكون موجود او لأ لأ حتما لأ
+
+105
+00:08:18,750 --> 00:08:21,990
+فهدولا كلهم بيكونوا مجتمعين والنسب الموجودة هي
+
+106
+00:08:21,990 --> 00:08:24,910
+اللي ممكناش تتحكم في الموضوع فانا بكون متكلم على
+
+107
+00:08:24,910 --> 00:08:29,250
+multiple regression احنا طبعا لما نجيب نتكلم في ال
+
+108
+00:08:29,250 --> 00:08:34,550
+regression ومازلنا في ال introduction بتكلم ان ال
+
+109
+00:08:34,550 --> 00:08:37,230
+regression analysis تبعتي بغض النظر هو كان linear
+
+110
+00:08:37,230 --> 00:08:43,670
+او عفوا a symbol ولا multipleبيخضع على واحدة من
+
+111
+00:08:43,670 --> 00:08:47,110
+التنتين من الـ two models اللي ممكن يكونوا موجودات
+
+112
+00:08:47,110 --> 00:08:50,430
+عندي إما linear model لما بتكلم على linear model
+
+113
+00:08:50,430 --> 00:08:54,110
+بتكلم على علاقة خطية أو non-linear model بتكلم على
+
+114
+00:08:54,110 --> 00:08:57,130
+equation ممكن تكون polynomial وممكن تكون عندي أي
+
+115
+00:08:57,130 --> 00:09:01,190
+دالة رياضية تمثل القيمة اللي موجودة عندها الرسم
+
+116
+00:09:01,190 --> 00:09:04,070
+الأولى اللي ظهرت قدامنا هنا في عندي علاقة خطية ما
+
+117
+00:09:04,070 --> 00:09:07,720
+بينالـ two variables اللي موجودين عندها طبعا الرسم
+
+118
+00:09:07,720 --> 00:09:12,280
+هي عشان نسهل نستوعب الأمر بسهولة بتكلم على simple
+
+119
+00:09:12,280 --> 00:09:16,160
+regression أنا الآن العلاقة في عندها علاقة خطية ما
+
+120
+00:09:16,160 --> 00:09:24,260
+بين ال X و ال Y كمان
+
+121
+00:09:24,260 --> 00:09:29,460
+العلاقة الخطية واضح انه
+
+122
+00:09:29,460 --> 00:09:37,260
+كل ما بتزيد ال Xكل ما تزيد الـ X قيمة الـ Y بتنزل
+
+123
+00:09:37,260 --> 00:09:40,100
+Relational Model أو علاقة خطية في الآخر ممكن
+
+124
+00:09:40,100 --> 00:09:43,060
+أمثلها بالخط المستقيم اللي باللون الأزرق لكن في
+
+125
+00:09:43,060 --> 00:09:45,520
+الرسم التاني هنا أنا بتتكلم عن ال linear في عندك
+
+126
+00:09:45,520 --> 00:09:53,480
+curve ال curve إيش معدلته هذا؟ هل هو مثلا ال 1 على
+
+127
+00:09:53,480 --> 00:09:58,920
+X تربيه؟ اللي هي بين قسين تساوي X تربيه نقص واحد
+
+128
+00:10:03,220 --> 00:10:05,760
+مثلًا، الله أعلم، لأن هذه ممكن تكون جزء من ال
+
+129
+00:10:05,760 --> 00:10:10,710
+curveعامل بالشكل هذا ومعمله shift معين فهذا أشبه
+
+130
+00:10:10,710 --> 00:10:15,430
+بالترفيه لكن في الآخر ليس معادلة خطية وهيفي يعني
+
+131
+00:10:15,430 --> 00:10:19,510
+ممكن يكون العلاقة بالشكل هذا أنا فعليا بالحالة هذه
+
+132
+00:10:19,510 --> 00:10:24,650
+مش هقدر أتكلم على أي model ممكن يمثل البيانات لا
+
+133
+00:10:24,650 --> 00:10:28,730
+خط مستقيم ولا curve ولا exponential ولا حاجة من
+
+134
+00:10:28,730 --> 00:10:31,910
+الشغلات هذه كلها فانا مش هقدر أتكلم هنا بيقول ان
+
+135
+00:10:31,910 --> 00:10:35,250
+مافيش عندي علاقة فعليا موجودة بينناطبعاً لما اتكلم
+
+136
+00:10:35,250 --> 00:10:37,490
+من مافيش علاقة يا جماعة الخير دائما ال prediction
+
+137
+00:10:37,490 --> 00:10:41,330
+عند ال test هتفشل و هتكون ال accuracy تبعتها too
+
+138
+00:10:41,330 --> 00:10:49,010
+low تمام معناته بال regression type لل model او
+
+139
+00:10:49,010 --> 00:10:53,390
+regression models أنواعها اما simple او multiple و
+
+140
+00:10:53,390 --> 00:11:00,870
+بتكلمها one variable و المقصود فيها independent
+
+141
+00:11:00,870 --> 00:11:04,030
+variable
+
+142
+00:11:05,650 --> 00:11:07,310
+عن طريق الـ Independent Variable وعن طريق الـ
+
+143
+00:11:07,310 --> 00:11:13,250
+Multiple Variable وفي كل
+
+144
+00:11:13,250 --> 00:11:17,430
+الحالتين الموديل
+
+145
+00:11:17,430 --> 00:11:22,970
+تبعي ممكن يكون Linear وممكن يكون Non-Linear في كل
+
+146
+00:11:22,970 --> 00:11:24,130
+الحالتين
+
+147
+00:11:26,880 --> 00:11:31,400
+بكل بساطة للـ Linear Regression عشان نفهم إيش اللي
+
+148
+00:11:31,400 --> 00:11:34,300
+بصير بالتحديد طبعا لما أنا بتكلم على Linear
+
+149
+00:11:34,300 --> 00:11:36,360
+Regression يا جماعة الخير خلّيني نروح باتجاه الـ
+
+150
+00:11:36,360 --> 00:11:39,740
+Simple Linear Regression في الأول بكل بساطة لما
+
+151
+00:11:39,740 --> 00:11:42,460
+أنا بتكلم على Single Linear Regression الـ Simple
+
+152
+00:11:42,460 --> 00:11:44,100
+Linear Regression انت فاكر ان في عندي one
+
+153
+00:11:44,100 --> 00:11:47,600
+independent variable معناته أنا بتكلم على إيجاد
+
+154
+00:11:47,600 --> 00:11:48,680
+العلاقة ما بين
+
+155
+00:11:51,430 --> 00:11:54,490
+Two Continuous Attributes أو Two Continuous
+
+156
+00:11:54,490 --> 00:11:56,770
+Variables واحد Independent Variable والتاني
+
+157
+00:11:56,770 --> 00:12:00,190
+Dependent Variable ولما أنا بتكلم على X و Y على
+
+158
+00:12:00,190 --> 00:12:03,370
+Dependent و Independent بتكلم على X و Y زي ما في
+
+159
+00:12:03,370 --> 00:12:06,510
+الرسم اللي موجود عندها في الـ Cartesian plane اللي
+
+160
+00:12:06,510 --> 00:12:14,750
+موجودة وعادة لما أنا بتكلم على Linear Model بتكلم
+
+161
+00:12:14,750 --> 00:12:20,680
+على معادلة خط المستقيم اللي هي Y تساويM مضروبة في
+
+162
+00:12:20,680 --> 00:12:25,740
+X زائد B حيث الـ M هي قيمة الـ male تبع الخط
+
+163
+00:12:25,740 --> 00:12:31,820
+المستقيم والـ B تمثل الـ intercept أو نقطة التقاطع
+
+164
+00:12:31,820 --> 00:12:39,200
+مع الـ Y اللي موجودة عندنا طيب، الآن أي خط مستقيم،
+
+165
+00:12:39,200 --> 00:12:41,900
+أي خط مستقيم أنا بدي أرسمه حتى لو أنا كان بدي مر
+
+166
+00:12:41,900 --> 00:12:51,330
+بـ نقطة الصفر الو male اللي بتمثل الزاوية هذهعفواً
+
+167
+00:12:51,330 --> 00:12:55,410
+الزاوية هذه طبعا الكل اللي هابنى عرف انه دائما
+
+168
+00:12:55,410 --> 00:13:00,310
+الزاوية بتنبنى مع خط مستقيم طيب الآن نقطة ال
+
+169
+00:13:00,310 --> 00:13:07,610
+intercept هان عفواً صفر اللي هي نقطة التقاطع مع
+
+170
+00:13:07,610 --> 00:13:14,410
+محور ال Y صفربينما قيمتها B سواء كان المثلث هذا أو
+
+171
+00:13:14,410 --> 00:13:18,310
+اي مثلث موازي على الخط المستقيم انا الان لو اخدت
+
+172
+00:13:18,310 --> 00:13:25,310
+محور موازي لو اخترت اي نقطة على الخط المستقيم مش
+
+173
+00:13:25,310 --> 00:13:29,570
+الاصل هذه النقطة هيها سامحوني شوية الرسم معايا مش
+
+174
+00:13:29,570 --> 00:13:38,650
+جادر اضبطه تمام الان مش هذه delta X هذه X وهذه Y
+
+175
+00:13:43,680 --> 00:13:50,560
+تمام الان لو انا خدت نقطتي بين نقطين و رسمت تقرط
+
+176
+00:13:50,560 --> 00:13:53,680
+متقاطعة و متعامدة يعني رسمت بين جثين مثلث قائم
+
+177
+00:13:53,680 --> 00:13:59,240
+الزاوية هذا حسب فيثا غورس الارتفاع والعفوا لو انا
+
+178
+00:13:59,240 --> 00:14:01,460
+افترض ان هي الزاوية تبعتي اللي احنا قلنا بتتمثل
+
+179
+00:14:01,460 --> 00:14:07,360
+الميل سابقا ال raise الارتفاع المقابل وهي المجاور
+
+180
+00:14:07,360 --> 00:14:10,900
+وهذا هو ال water حسب قانون فيثا غورس ان ال water
+
+181
+00:14:10,900 --> 00:14:15,300
+هذا يساويالمجاور تربيع الـ Run تربيع زاد الرايس
+
+182
+00:14:15,300 --> 00:14:22,540
+تربيع تمام ال slope تساوي الارتفاع
+
+183
+00:14:22,540 --> 00:14:27,120
+المقابل على المجاور المقابل على المجاور المقابل هي
+
+184
+00:14:27,120 --> 00:14:32,300
+التغير في قيمة ال Y هي المقابل تمثل التغير في قيمة
+
+185
+00:14:32,300 --> 00:14:40,640
+ال Y والمقابل
+
+186
+00:14:40,640 --> 00:14:42,140
+التغير في قيمة
+
+187
+00:14:45,400 --> 00:14:53,620
+في قيمة الـ X وبالتالي قيمة الـ Mail هي عشان نتكلم
+
+188
+00:14:53,620 --> 00:14:58,320
+في أمثلة ممكن نفهمها بشكل صحيح خلّيني أشوف المثال
+
+189
+00:14:58,320 --> 00:15:02,040
+البسيط هذا المثال هذا عديته على الـ Excel وافترضت
+
+190
+00:15:02,040 --> 00:15:05,920
+إنه هي في عندي ال salary
+
+191
+00:15:07,280 --> 00:15:11,360
+هنا الـ salary بتمثل قيم الـ independent variable
+
+192
+00:15:11,360 --> 00:15:14,940
+عفوا اللي في عندي independent variable attribute X
+
+193
+00:15:14,940 --> 00:15:19,760
+بيمثل سنوات الخبرة وفي عندي قيمة ال salary بال K
+
+194
+00:15:19,760 --> 00:15:24,790
+أو بال ألفاللي بتمثل الـ Y وهي القيامة يعني لما
+
+195
+00:15:24,790 --> 00:15:27,350
+تكون سنوات الخبرة تلاتة معناته راتب تلاتين ألف
+
+196
+00:15:27,350 --> 00:15:31,390
+سنوات الخبرة تمانية سبعة وخمسين ألف تسعة اربع
+
+197
+00:15:31,390 --> 00:15:35,250
+وستين تلاتاش اتنين وسبعين وها كده لما حاولت ارسمهم
+
+198
+00:15:35,250 --> 00:15:37,810
+هيهم وطبعا هورجيكوا بال Excel لان ممكن انا فعليا
+
+199
+00:15:37,810 --> 00:15:42,610
+ارسم شغل زي هيك بكل بساطة تمام انا هستخدم ال data
+
+200
+00:15:42,610 --> 00:15:47,720
+set هايعشان أشوف كيف بدي أجيب الـ slope أو بدي
+
+201
+00:15:47,720 --> 00:15:50,160
+أجيب معادلة الخط المستقيم اللي بمثل الخط الأحمر
+
+202
+00:15:50,160 --> 00:15:53,840
+هذا اللي أنا قرأ اسم ال data set اللي موجودة عندي
+
+203
+00:15:53,840 --> 00:15:57,200
+تعالوا نبدأ نتذكر بس مع بعض على السريع إن
+
+204
+00:15:57,200 --> 00:16:02,320
+المعادلات اللي عندي أنا الآن معادلات ثابتة اللي هي
+
+205
+00:16:02,320 --> 00:16:08,660
+معادلة الخط المستقيم Y تساوي الـ Y اللي هي ال
+
+206
+00:16:08,660 --> 00:16:11,380
+predictive value اللي أنا بدي إياها تساوي ال M في
+
+207
+00:16:11,380 --> 00:16:17,940
+Xالـ Dependent Variable يساوي الـ male slope M في
+
+208
+00:16:17,940 --> 00:16:21,580
+قيمة الـ Independent Variable زائد B اللي هي الـ
+
+209
+00:16:21,580 --> 00:16:24,780
+Intercept اللي موجودة عندي قيمة ال slope حسب
+
+210
+00:16:24,780 --> 00:16:29,020
+المعادلة السابقة حسب الرسم اللي موجود عندي هنا في
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+211
+00:16:29,020 --> 00:16:32,080
+الخط المستقيم عفوا ان انا في عندى slide check اللي
+
+212
+00:16:32,080 --> 00:16:38,960
+عملها hide مش قضية كتير المعادلة اللي عندي هيها
+
+213
+00:16:38,960 --> 00:16:39,180
+هنا
+
+214
+00:16:48,160 --> 00:17:00,320
+yes بالخطأ عمل hide لل slide تبع
+
+215
+00:17:00,320 --> 00:17:03,160
+لمعادلة الخط المستقيم اللي احنا بنعرفها حكينا
+
+216
+00:17:03,160 --> 00:17:08,200
+عليها سابقا حاولنا نفصل اكتر فيها هي ال slope
+
+217
+00:17:09,530 --> 00:17:13,690
+المقدار التغيير اللي على النقطة بس هذا التغيير
+
+218
+00:17:13,690 --> 00:17:17,370
+لمين؟ للنقطين هدول طب النقطين التانيات اللي في
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+219
+00:17:17,370 --> 00:17:22,090
+المثلة أنا فعلياً ماعنديش نقطين هذا الخط المستقيم
+
+220
+00:17:22,090 --> 00:17:26,350
+مش موجود أنا عندي مجموعة نقاط تمام؟ بدي أحاول أجيب
+
+221
+00:17:26,350 --> 00:17:30,670
+أفضل خط مستقيم ما بينهم يمثلهم كلهم فأنا بتكلم
+
+222
+00:17:30,670 --> 00:17:33,510
+قاعدة الخط المستقيم تبعي هي عبارة أو ال slope
+
+223
+00:17:33,510 --> 00:17:39,330
+تبعته عبارة عن كل النقاطX ناقص متوسط نقاط X كم
+
+224
+00:17:39,330 --> 00:17:42,070
+نقطة عندك انت على الخط المستقيم هذا؟ أجل الخط
+
+225
+00:17:42,070 --> 00:17:44,070
+المستقيم لجماعة الخيربو يجب أن يكون عنده نقطين
+
+226
+00:17:44,070 --> 00:17:47,670
+عشان انا نقدر أسموه، مظبوط ولا لا؟ طبعا عادة
+
+227
+00:17:47,670 --> 00:17:50,870
+بالهدف احنا بنسميه قطعة مستقيمة محصورة من قطار
+
+228
+00:17:50,870 --> 00:17:55,110
+بينما الخط المستقيم هو بتعدى حدود النقطين اللي
+
+229
+00:17:55,110 --> 00:18:00,270
+موجودة عندها تمام، الآن معناته انا بتكلم هنا ان X
+
+230
+00:18:00,270 --> 00:18:07,000
+عند مجموعة نقاط على ال X ناقص المتوسط مضروبة فيY
+
+231
+00:18:07,000 --> 00:18:10,580
+الفروقات ما بين الـ Y في المتوسط تبعتهم طبعاً
+
+232
+00:18:10,580 --> 00:18:17,320
+بجموعهم على مجموع الفروقات ما بين الـ X XI
+
+233
+00:18:17,320 --> 00:18:22,740
+والمتوسط تبعتهم تربية لكل النقاط اللي موجودة عندها
+
+234
+00:18:22,740 --> 00:18:27,880
+طيب، الآن تعالوا نيجي نشوفمن أين جاء التربية جامعة
+
+235
+00:18:27,880 --> 00:18:32,420
+الخير؟ لأن في الاخر هذه النقاط كلها مثلثات أو فيها
+
+236
+00:18:32,420 --> 00:18:36,900
+ثغرس و كما قلت لك هذه تربية
+
+237
+00:18:39,330 --> 00:18:42,490
+هي تربيه زاد هاي تربيه فاعوض عن كل واحدة فيهم
+
+238
+00:18:42,490 --> 00:18:44,990
+بالتربيع اللي موجود فيها في الآخر احنا هادي
+
+239
+00:18:44,990 --> 00:18:48,850
+معادلتنا اللي موجودة و بدنا نستخدمها تعالى نشوف
+
+240
+00:18:48,850 --> 00:18:52,550
+كيف بدنا نطبقها بشكل كويس الآن هاي النقاط اللي
+
+241
+00:18:52,550 --> 00:18:56,430
+موجودة و هاي التلت معادلات اللي موجودة عندها ال
+
+242
+00:18:56,430 --> 00:19:00,650
+intercept اذا انا حصلت على ال M عند ال Y معلومة و
+
+243
+00:19:00,650 --> 00:19:04,590
+ال X معلومة تمام بيظل عند ال B معناته ال B بدها
+
+244
+00:19:04,590 --> 00:19:10,940
+تساويبجيب متوسط تغييرات أو متوسط قيم ال Y ناقص ال
+
+245
+00:19:10,940 --> 00:19:15,240
+slope في متوسط قيم ال X اللي موجودة عندها هذه
+
+246
+00:19:15,240 --> 00:19:18,440
+القيام الموجودة وهذه هي المعادلات الثلاثة اللي
+
+247
+00:19:18,440 --> 00:19:22,100
+قلنا أننا تلزمنا تكون حاضرة في ذهننا عند التعامل
+
+248
+00:19:22,100 --> 00:19:26,440
+مع ال symbol regression أو مع ال regression مع ال
+
+249
+00:19:26,440 --> 00:19:28,540
+linear regression عفوا مع ال linear regression
+
+250
+00:19:28,540 --> 00:19:34,810
+تمام، طيب، هي عندي Xهذه العمودين اللي بدي أشغل
+
+251
+00:19:34,810 --> 00:19:40,910
+عليهم، ماهي المعادلة؟ بالزمن أن أحسب المتوسط تبع
+
+252
+00:19:40,910 --> 00:19:47,560
+ال X والمتوسط الحسابي تبع ال Yفي كل الحالات اللي
+
+253
+00:19:47,560 --> 00:19:52,480
+عندي تمام متوسط X معناته مجموحهم على عددهم واحدة
+
+254
+00:19:52,480 --> 00:19:56,400
+اتنين تلاتة اربعة خمسة ستة سبعة تمانية تسعة عشرة
+
+255
+00:19:56,400 --> 00:20:01,680
+تلاتة هي احداشر هي عشرين تلاتة وتلاتين ستة وتلاتين
+
+256
+00:20:01,680 --> 00:20:09,380
+تس اتنين واربعين تلاتة وخمسين اربعة وسبعين خمسة
+
+257
+00:20:09,380 --> 00:20:20,000
+وسبعين91 بالمتوسط 9.10 حسبت المتوسط ل X حسبنا
+
+258
+00:20:20,000 --> 00:20:28,460
+المتوسط ل Y الخطوة التالية انا بدي اجيب هنا مجميع
+
+259
+00:20:28,460 --> 00:20:38,780
+او بدي اجيب حاصل ضرب كل X ناقص قيمة المتوسط 9-1
+
+260
+00:20:39,970 --> 00:20:44,930
+أضربها في قيمة الـ y كل قيم الـ y ناقص المتوسط
+
+261
+00:20:44,930 --> 00:20:51,590
+تبعتها على كذا يعني انا بدي احسب x ناقص y او x i
+
+262
+00:20:51,590 --> 00:20:59,350
+ناقص متوسط ال x احسب x او y yi في متوسط ال y فلجيت
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+263
+00:20:59,350 --> 00:21:03,610
+هنا فاين روحت حسبت المعادلتين ايهم اشتغلت عليهم في
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+264
+00:21:03,610 --> 00:21:05,210
+شكل آلي تلاتة
+
+265
+00:21:09,120 --> 00:21:14,740
+نقص تلاتة ناقص تسعة نقص واحد نقص ستة نقص واحد نقص
+
+266
+00:21:14,740 --> 00:21:15,940
+واحد نقص واحد نقص واحد نقص واحد نقص واحد نقص واحد
+
+267
+00:21:15,940 --> 00:21:17,720
+نقص واحد نقص واحد نقص واحد نقص واحد نقص واحد نقص
+
+268
+00:21:17,720 --> 00:21:18,740
+واحد نقص واحد نقص واحد نقص واحد نقص واحد نقص واحد
+
+269
+00:21:18,740 --> 00:21:19,220
+نقص واحد نقص واحد نقص واحد نقص واحد نقص واحد نقص
+
+270
+00:21:19,220 --> 00:21:19,220
+واحد نقص واحد نقص واحد نقص واحد نقص واحد نقص واحد
+
+271
+00:21:19,220 --> 00:21:19,220
+نقص واحد نقص واحد نقص واحد نقص واحد نقص واحد نقص
+
+272
+00:21:19,220 --> 00:21:25,130
+واحد نقص واحد نقص واحد نقص واحد نقص واحد نقص وا8-9
+
+273
+00:21:25,130 --> 00:21:34,830
+.1 1.1 57-55.4 1.6 و بكمل الجدول بالكامل ممتاز
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+274
+00:21:34,830 --> 00:21:39,950
+الخطوة التالية هذه العناصر بتلزمني في حالتين بدي
+
+275
+00:21:39,950 --> 00:21:43,310
+اضرب high في high و احصل على high تربيع من أجل
+
+276
+00:21:43,310 --> 00:21:50,000
+المقام اللي هنا فاني روحت جبت ال busعناصر البط
+
+277
+00:21:50,000 --> 00:21:56,580
+اللي هي x i ناقص x متوسط الـ x مضروبة في y i ناقص
+
+278
+00:21:56,580 --> 00:22:04,440
+متوسط الـ yبوينجوسين هانضربت سالب ستة point واحد
+
+279
+00:22:04,440 --> 00:22:07,680
+ضرب سالب خمسة وعشرين point اربعة هي مية اربعة
+
+280
+00:22:07,680 --> 00:22:13,620
+وخمسين point اربعة وتسعين طيب وسالب ستة point واحد
+
+281
+00:22:13,620 --> 00:22:17,280
+ضرب سالب ستة point واحد سبعة وتلاتين point واحد
+
+282
+00:22:17,280 --> 00:22:22,460
+وعشرين وكملتللآخر كل العملية الحسابية تبعتي طبعا
+
+283
+00:22:22,460 --> 00:22:24,560
+جماعة الخير عشان اكون واضح معاكم لو انا جيبت سؤال
+
+284
+00:22:24,560 --> 00:22:27,140
+زي هيك و قلت لك هاتلي او هاتلي معادلة الخط
+
+285
+00:22:27,140 --> 00:22:30,840
+المستقيم مش هجيبك فيها عشر قيم ممكن اجيبك اربع من
+
+286
+00:22:30,840 --> 00:22:34,300
+اربع لخمس قيم تشتغل عليهم يعني نص القيم الموجودة و
+
+287
+00:22:34,300 --> 00:22:37,200
+عشان هيك بأكد باستمرار ان ال calculator لازم يكون
+
+288
+00:22:37,200 --> 00:22:43,380
+عندك جاهزة في الحساب تمام الخطوة اللي بعد هيكأنا
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+289
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+بتلزمني المجميع المجميع لمين؟ لكل عمود حسب
+
+290
+00:22:46,320 --> 00:22:49,180
+المعادلة اللى موجودة عندى هنا فروح اتجمع العمود
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+291
+00:22:49,180 --> 00:22:53,760
+هذا انهيه تلاتمية اللى هي قيمة البسط تلاتمية
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+292
+00:22:53,760 --> 00:22:59,460
+تمانية وخمسين point تسعة وحسبت قيمة العمود التانى
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+293
+00:22:59,460 --> 00:23:04,660
+ألف و متين تسعة وستين point ستة تمام الان قيمة ال
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+294
+00:23:04,660 --> 00:23:12,890
+M تساوي ألف و متين علىتلات تلاف وتمانية خمسة تلات
+
+295
+00:23:12,890 --> 00:23:16,650
+تلاف تلاتمية تمانية وخمسين point تسعة فبتطلع قيمة
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+296
+00:23:16,650 --> 00:23:22,930
+ال M عندي تلاتة point خمسة تلاتة سبعة زي ما أحنا
+
+297
+00:23:22,930 --> 00:23:26,910
+شايفينها تمام أنا الآن حصلت على مين على قيمة ال M
+
+298
+00:23:26,910 --> 00:23:30,770
+في المعادلة هاي من المعادلة هاي بظل عندي بي بي
+
+299
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+سهلة بما أن انا حصلت على ال بي هي معادلة ال بي
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+300
+00:23:33,970 --> 00:23:36,650
+عفوا ان انا حصلت على ال M وهي معادلة ال بي عندي
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+302
+00:23:42,300 --> 00:23:46,140
+بتساوي متوسط الـ Y التي هي الحسبة الأولى التي كانت
+
+303
+00:23:46,140 --> 00:23:51,040
+في الجدولة التي لديها نهيهم متوسط الـ Y 55.4 ناقص
+
+304
+00:23:51,040 --> 00:23:57,260
+M لـ 3.5375
+
+305
+00:23:57,260 --> 00:24:03,700
+ضرب متوسط ال X 9.1 قيمتهم
+
+306
+00:24:08,260 --> 00:24:16,200
+معادلة الخط المستقيم مُعادلة M مُعادلة P مُعادلة M
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+307
+00:24:16,200 --> 00:24:22,680
+مُعادلة P مُعادلة M مُعادلة P مُعادلة M مُعادلة P
+
+308
+00:24:22,680 --> 00:24:23,340
+مُعادلة M مُعادلة P
+
+309
+00:24:28,080 --> 00:24:40,280
+3.5375 ضرب الـ M زائد
+
+310
+00:24:40,280 --> 00:24:46,260
+ال B لو انا بدى اتأكد ان معدلتي صحيحة او غير صحيحة
+
+311
+00:24:46,260 --> 00:24:49,760
+تخيل ان قيمة X تساوي 1 المفروض انها تساوي 20
+
+312
+00:24:50,690 --> 00:24:54,550
+المفروض لكن الكلام الأدق يكون القيمة قريبة من
+
+313
+00:24:54,550 --> 00:25:05,630
+العشرين ثلاثة point خمسة ثلاثة سبعة خمسة زائد
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+314
+00:25:05,630 --> 00:25:11,690
+تلاتة وعشرين point متين وتسعة ملاحظين قدش القيمة
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+315
+00:25:11,690 --> 00:25:18,390
+اللي طلعت عندي أناتلاتة و عشرين و اتنين من عشرة و
+
+316
+00:25:18,390 --> 00:25:23,850
+تلاتة و سبعة و خمسة معناته احنا بنتكلم على ستة و
+
+317
+00:25:23,850 --> 00:25:30,350
+عشرين point سبعة هذه قيمة لما كانت ال X تساوي واحد
+
+318
+00:25:30,350 --> 00:25:33,270
+ليش لأنه بضال فيه نسبة خاطئة ماحدش قال في الدنيا
+
+319
+00:25:33,270 --> 00:25:40,130
+ان هذا ال algorithm او هذا ال modelهيديني 100%
+
+320
+00:25:40,130 --> 00:25:44,670
+القيم المتساوية لان هناك قيم متفرقة لو رجعت للرسم
+
+321
+00:25:44,670 --> 00:25:49,070
+على السريععشان تشوفوها هيه فعلا هيه النقاط تبعتي
+
+322
+00:25:49,070 --> 00:25:52,630
+النقاط متجاهة على الخط المستقيم ولو جربت انت تاخد
+
+323
+00:25:52,630 --> 00:25:55,490
+نقاط على الخط المستقيم هتطلع معاك typical قيمة ال
+
+324
+00:25:55,490 --> 00:26:00,030
+M وقيمة ال B تمام بعد ما انا حسبت القيم هذه على
+
+325
+00:26:00,030 --> 00:26:02,730
+السريع خليني اروح اشوف بال python ايش انا بده
+
+326
+00:26:02,730 --> 00:26:05,870
+اساوي انا روحت على ال python استخدمت ال numpy
+
+327
+00:26:05,870 --> 00:26:10,910
+كمكتبة عشان اتعامل مع ال numerical python arrays
+
+328
+00:26:10,910 --> 00:26:16,060
+وبنيت الريلة ال X وبنيت الريلة ال Yلكن يوجد شغل
+
+329
+00:26:16,060 --> 00:26:19,180
+هنا إنه لازم اعمل Reshape عشان اعمل Transpose تبعت
+
+330
+00:26:19,180 --> 00:26:25,080
+المصفوفة وهي عبارة عن مصفوفة من بعد واحد اكتر
+
+331
+00:26:25,080 --> 00:26:29,120
+وليست vectorتمام فعشان هيك بعملها Reshape سالب
+
+332
+00:26:29,120 --> 00:26:31,620
+واحد هذا طبعا لأنه أنا فعليا جامعة الخير برجع
+
+333
+00:26:31,620 --> 00:26:33,800
+بأكيد أنه أنا جاعت بقاشطة بدي أبني ال data set
+
+334
+00:26:33,800 --> 00:26:35,880
+بينما ال data set ممكن تكون معايا جاهزة زي ما في
+
+335
+00:26:35,880 --> 00:26:38,340
+ال data set اللي انت اختارتها في الواجب الأول تبعت
+
+336
+00:26:38,340 --> 00:26:41,280
+ال regression data set اللي كنا بنتكلم عليها أنت
+
+337
+00:26:41,280 --> 00:26:44,700
+بدك تقطع منها عمود واحد فقط وتشتغل عليه وتشوف
+
+338
+00:26:44,700 --> 00:26:48,780
+العلاقة ما بينها وبين ال target attribute اللي هي
+
+339
+00:26:48,780 --> 00:26:50,920
+ال continuous value بدك تعملها prediction وروح
+
+340
+00:26:50,920 --> 00:26:55,370
+اتدخلت القيم اللي موجودة عندي أنا غادفيه الـ
+
+341
+00:26:55,370 --> 00:26:58,650
+values اللي دخلتها على المصروفة بدون ماعمل الـ
+
+342
+00:26:58,650 --> 00:27:02,890
+Harry shape روحت from ال ASCII learn dot linear
+
+343
+00:27:02,890 --> 00:27:05,710
+model import linear regression وانا ما زلت بأكد
+
+344
+00:27:05,710 --> 00:27:08,270
+انه يشغل على linear regression وبالتحديد بما انا
+
+345
+00:27:08,270 --> 00:27:12,870
+بتكلم على one independent attribute معناته انا
+
+346
+00:27:12,870 --> 00:27:18,330
+بتكلم على simple linear regressionبنيت الموديل
+
+347
+00:27:18,330 --> 00:27:22,270
+موديل تساوي linear regression الموديل dot fit عشان
+
+348
+00:27:22,270 --> 00:27:25,730
+يعمل train ويوجد العلاقة اللي ما بين ال X وال Y
+
+349
+00:27:25,730 --> 00:27:28,430
+اللي هي ال independent attribute X وال dependent
+
+350
+00:27:28,430 --> 00:27:33,830
+variable او ال dependent attribute Y فروحت انا
+
+351
+00:27:33,830 --> 00:27:39,390
+اعمل fit المفروض بعد عملية ال fit هذه هو حصل على
+
+352
+00:27:39,390 --> 00:27:45,350
+ال slope ال M وحصل على ال Bهنا لان انا بس بدي
+
+353
+00:27:45,350 --> 00:27:49,250
+اطبعهم فروح و قلت له اطبعلي ال model. coefficient
+
+354
+00:27:49,250 --> 00:27:53,170
+ال model هيو dot coefficient underscore فبطبعلي
+
+355
+00:27:53,170 --> 00:27:56,730
+قيمة و روح اضفت عليهم عشان تظهر معادلة خط مستقيم
+
+356
+00:27:56,730 --> 00:27:59,430
+بس مش اكتر ال model. coefficient و ال model.
+
+357
+00:27:59,790 --> 00:28:02,650
+intercept ال intercept اللي هي ال mail او التقاط
+
+358
+00:28:02,650 --> 00:28:06,010
+مع بي و ال coefficient اللي هي ال mail اللي موجود
+
+359
+00:28:06,010 --> 00:28:11,660
+عندي هناالـ output طلّع ليه هى لو أنا جيت طلعت في
+
+360
+00:28:11,660 --> 00:28:20,280
+قيمة 3 point خمسة تلاتة سبعة القيم اللى طلعت معايا
+
+361
+00:28:20,280 --> 00:28:24,100
+لما انا اختصرتها سبعة خمسة لانه عملت round للسبعة
+
+362
+00:28:24,100 --> 00:28:31,120
+وهنا تلاتة وعشرين point متين وتسعة لانه برضه عملت
+
+363
+00:28:31,120 --> 00:28:34,440
+round للرقم اللى موجود عندها typical نفس ال values
+
+364
+00:28:34,440 --> 00:28:38,710
+اللى موجودة لو انا بدى اعمل predictionهيبقى انا في
+
+365
+00:28:38,710 --> 00:28:42,270
+ال array روحت على ال X قلت له في عندي X test هاي
+
+366
+00:28:42,270 --> 00:28:48,710
+في عند النقاط تبعتي ال array 2 و 9 و 13 و 18 و 24
+
+367
+00:28:48,710 --> 00:28:57,370
+و يعمل لي ال Y predict تبعتهم تمام الان
+
+368
+00:28:57,370 --> 00:29:02,050
+هادول هيروح يجيبلي بناء على المعادلة هاي هياخد 2
+
+369
+00:29:02,050 --> 00:29:09,110
+يعني تلاتة pointخمسة أربعة ضرب اتنين زائد تلاتة
+
+370
+00:29:09,110 --> 00:29:12,690
+وعشرين متين وتسعة حدين قيمتي التنين تسعة لكن
+
+371
+00:29:12,690 --> 00:29:15,550
+لاحظوا الآن يا جماعة الخير ان هذه القيم المجتمعة
+
+372
+00:29:15,550 --> 00:29:20,510
+كلها بدت تخضع لمين تخضع لنفس المعادل اللي عملها
+
+373
+00:29:20,510 --> 00:29:24,270
+prediction هنا خلاص انتهى الأمر لأن أنا عمال بتكلم
+
+374
+00:29:24,270 --> 00:29:29,330
+على ال model dot predict فانا زودت بالقائمة تبعتي
+
+375
+00:29:29,330 --> 00:29:35,340
+هذه وهو اشرح سوارح أعملها predict فعشان هيك بتطلع
+
+376
+00:29:35,340 --> 00:29:38,580
+معايا معادلة خط مستقيم بالتمام طب عشان أوجد
+
+377
+00:29:38,580 --> 00:29:42,080
+العلاقة اللي موجودة عندي هان روحت استخدية مكتبة
+
+378
+00:29:42,080 --> 00:29:43,660
+اسمها الـ
+
+379
+00:29:43,660 --> 00:29:47,360
+matplotlibrarymathematicalplottinglibrary
+
+380
+00:29:47,360 --> 00:29:49,980
+.pythonplot
+
+381
+00:29:51,750 --> 00:29:55,190
+as plt بدي ارسم و روح اقول في ال plot هذه قلت له
+
+382
+00:29:55,190 --> 00:29:58,070
+في عندي scatter اللي هي النقاط عند x و y هي هم
+
+383
+00:29:58,070 --> 00:30:01,970
+موجودات هي x و y اللي موجودات فوق عندها و ال color
+
+384
+00:30:01,970 --> 00:30:06,690
+black نقاط باللون الأسود و في عندى بدي اعمل plot
+
+385
+00:30:06,690 --> 00:30:10,050
+كذلك كرسم خط مستقل ال plot اللي بتكلم على function
+
+386
+00:30:10,050 --> 00:30:14,650
+أو على equation ال plot x test اللي هي هذه اتنين
+
+387
+00:30:14,650 --> 00:30:18,590
+وتسعة و تلتاش و تمانتاش وأربعة و في ال color و ال
+
+388
+00:30:18,590 --> 00:30:22,780
+y predictهي هي ال result تبع ال prediction بتاعة
+
+389
+00:30:22,780 --> 00:30:25,980
+ال model اللي أنا استخدمته و الخط باللون الأخضر و
+
+390
+00:30:25,980 --> 00:30:30,700
+ال line width فروحت قلتله اعمل تبين ال text على ال
+
+391
+00:30:30,700 --> 00:30:34,240
+X و ال Y اللي هي النقاط و قلتله show تعالى نشوف هى
+
+392
+00:30:34,240 --> 00:30:38,580
+النتيجة اللى قبعليها هى النقاط اللى موجودة عندهان
+
+393
+00:30:38,580 --> 00:30:44,300
+تمام و هى الخط المستقيم اللى بتمثله المعادلة اللى
+
+394
+00:30:44,300 --> 00:30:47,160
+موجودة عندها بدي اروح اناويك الان بس على ال X اللى
+
+395
+00:30:47,160 --> 00:30:51,440
+على السريعوبالـ Excel أورجيك فعليًا إنه هي الخط
+
+396
+00:30:51,440 --> 00:30:56,220
+اللي أنا اشتغلته بكل بساطة سيبني من كل من الحسبة
+
+397
+00:30:56,220 --> 00:31:00,580
+اللي انا اشتغلتها أو حاولت اشتغلها معها أطبقها هنا
+
+398
+00:31:00,580 --> 00:31:03,520
+على السريع الفكرة لو أنا هي القيم اللي موجودة عندي
+
+399
+00:31:03,520 --> 00:31:07,440
+ضللتها بالشكل هذا بالـ Excel وروحت على insert
+
+400
+00:31:07,440 --> 00:31:12,040
+وروحت
+
+401
+00:31:12,040 --> 00:31:15,820
+اخترت letter أو scatter نقاط هي النقاط
+
+402
+00:31:18,410 --> 00:31:23,050
+حاضر هكبرها شوية بحيث انه ضيين النقاط هي النقاط
+
+403
+00:31:23,050 --> 00:31:27,770
+اللي موجودة عندي هان وماخدين عندي في عندي النقاط
+
+404
+00:31:27,770 --> 00:31:31,310
+هذه بتروح على النقاط هذه لاحظوا في عندي add trend
+
+405
+00:31:31,310 --> 00:31:35,770
+line add trend line اضفتله ل trend line فراح
+
+406
+00:31:35,770 --> 00:31:38,850
+رسمليها بالشكل اللي موجود عندي هان طبعا لو قلتله
+
+407
+00:31:38,850 --> 00:31:43,510
+انا linear مباشرة هي exponential logistic
+
+408
+00:31:43,510 --> 00:31:47,910
+polynomial logarithmic عفوا logarithmic polynomial
+
+409
+00:31:48,700 --> 00:31:53,700
+الـ Power الـ Moving Averages لكن فعلياً بما أن
+
+410
+00:31:53,700 --> 00:31:58,280
+الدالة تبعتي Linear فهي أنسب خط موجود عندى مش بس
+
+411
+00:31:58,280 --> 00:32:01,200
+هيك لو انا روحت و قلت له display equation on chart
+
+412
+00:32:01,200 --> 00:32:05,900
+فرح عرضلي المعادلة او ال equation هيها هان خليني
+
+413
+00:32:05,900 --> 00:32:11,570
+بس اكبر خطها شوية صغيرة عشان نقدر نشوفه مع بعضوبعض
+
+414
+00:32:11,570 --> 00:32:14,950
+تيبيكال ليش لأنه فعليا مافيش مجال هي حسبة ال slope
+
+415
+00:32:14,950 --> 00:32:18,630
+وهي حسبة ال M وهي حسبة المعادلة الخط المستقيم اللي
+
+416
+00:32:18,630 --> 00:32:23,510
+انا ممكن اشتغل عليه وبهك احنا بنكون اتكلمنا عن ال
+
+417
+00:32:23,510 --> 00:32:27,370
+linear regression بكتفي بالتسجيل هذا ان شاء الله
+
+418
+00:32:27,370 --> 00:32:31,850
+تعالى و هكمل معاكم في ال multiple regression و ال
+
+419
+00:32:31,850 --> 00:32:36,190
+non-linear regression و ال evaluationخلال ال part
+
+420
+00:32:36,190 --> 00:32:39,110
+التاني ان شاء الله تعالى الله يعطيكم العافية
+
+421
+00:32:39,110 --> 00:32:41,650
+والسلام عليكم ورحمة الله وبركاته
+
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/0znKCBWOhCg.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/0znKCBWOhCg.srt
new file mode 100644
index 0000000000000000000000000000000000000000..e296158a7e7d9a638f880687717d46e3943bc1ce
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/0znKCBWOhCg.srt
@@ -0,0 +1,1802 @@
+1
+00:00:05,030 --> 00:00:07,870
+بسم الله الرحمن الرحيم السلام عليكم ورحمة الله و
+
+2
+00:00:07,870 --> 00:00:11,250
+بركاته اليوم هنبدأ بالـ chapter الثالث في الـ
+
+3
+00:00:11,250 --> 00:00:15,010
+machine design، واحد اللي هو failures resulting
+
+4
+00:00:15,010 --> 00:00:19,670
+from static loading، اللي هو الانهيارات أو الـ.. الـ
+
+5
+00:00:19,670 --> 00:00:24,650
+..الـ.. في الـ.. في القطع الميكانيكية نتيجة أحمال
+
+6
+00:00:24,650 --> 00:00:29,940
+ثابتة. طبعًا احنا بـ chapter الثالث والرابع كان تحضير
+
+7
+00:00:29,940 --> 00:00:34,220
+لـ chapter الخامس وchapter السادس، chapter الثالث غطينا
+
+8
+00:00:34,220 --> 00:00:39,140
+كل حسابات الـ stress analysis بكل أنواعها، الـ.. الـ
+
+9
+00:00:39,140 --> 00:00:45,530
+..الـ.. الـ.. الـ.. الـ.. الـ axial direct tensile
+
+10
+00:00:45,530 --> 00:00:49,310
+loading، سواء كان tensile accommodation عند الـ
+
+11
+00:00:49,310 --> 00:00:53,170
+bending loading عند الـ transverse shear loading
+
+12
+00:00:53,170 --> 00:00:58,150
+عند الـ torsional loading أو any combination
+
+13
+00:00:58,150 --> 00:01:04,530
+between these loading conditions. طبعًا استخدمنا الـ
+
+14
+00:01:04,530 --> 00:01:09,770
+Mohr circle عشان احسب الـ principal stresses.
+
+15
+00:01:11,570 --> 00:01:15,830
+هذا chapter الثالث، chapter الرابع غطينا الـ deflection
+
+16
+00:01:15,830 --> 00:01:20,690
+calculations. استخدمنا اللي هي الـ strain energy
+
+17
+00:01:20,690 --> 00:01:24,090
+method و Castigliano method to determine
+
+18
+00:01:24,090 --> 00:01:28,590
+deflections at various points on a mechanical
+
+19
+00:01:28,590 --> 00:01:31,930
+element. اليوم هنكمل chapter الخامس، هنحكي عن failures
+
+20
+00:01:31,930 --> 00:01:35,430
+resulting from static loading. هنحكي عن مجموعة من
+
+21
+00:01:35,430 --> 00:01:39,970
+النظريات المستخدمة في الـ static loading، منها الـ
+
+22
+00:01:39,970 --> 00:01:41,930
+maximum normal stress theory والـ maximum shear
+
+23
+00:01:41,930 --> 00:01:45,070
+stress theory والـ maximum distortion energy
+
+24
+00:01:45,070 --> 00:01:48,450
+theory والـ column theory والـ modified column
+
+25
+00:01:48,450 --> 00:01:56,230
+theory. في الأول هنعمل مراجعة على حسابات الـ stress
+
+26
+00:01:56,230 --> 00:01:59,950
+concentration due to sudden change in the cross
+
+27
+00:01:59,950 --> 00:02:02,410
+-sectional area. طبعًا sudden change في الـ cross
+
+28
+00:02:02,410 --> 00:02:06,390
+-sectional area ممكن يكون due to different aspects.
+
+29
+00:02:06,390 --> 00:02:10,570
+ممكن يكون في عندي ثقب أو يكون عندي fillet. طبعًا
+
+30
+00:02:10,570 --> 00:02:15,350
+appendix A15 وA16 بيرجوني، بيعطوني اللي هو
+
+31
+00:02:15,350 --> 00:02:18,350
+theoretical stress concentration factors for
+
+32
+00:02:18,350 --> 00:02:20,710
+different geometries and different loading
+
+33
+00:02:20,710 --> 00:02:26,350
+conditions. على سبيل المثال، figure A15-1 في الكتاب
+
+34
+00:02:26,350 --> 00:02:32,410
+بيشرح لي عند bar، intention المقطع بتاعه
+
+35
+00:02:32,410 --> 00:02:38,290
+مستطيل وفيه ثقب في النص. قطر الثقب دي small، عرض
+
+36
+00:02:38,290 --> 00:02:44,170
+القطعة W، والبعد الثالث لها T، و under axial loading
+
+37
+00:02:44,170 --> 00:02:47,270
+على المحور الأفقي يكون عندي D على W.
+
+38
+00:02:52,020 --> 00:03:01,240
+وهنا دي بيكون الكتير، والـ nominal stress σo
+
+39
+00:03:01,240 --> 00:03:12,400
+بساوي F على A، و A بيساوي اللي هي W ناقص D في
+
+40
+00:03:12,400 --> 00:03:18,720
+T. W هي القطعة، هي
+
+41
+00:03:18,720 --> 00:03:19,580
+الـ force F.
+
+42
+00:03:22,970 --> 00:03:28,510
+هذا W، هذا
+
+43
+00:03:28,510 --> 00:03:33,310
+D، و
+
+44
+00:03:33,310 --> 00:03:37,270
+البعد الثالث اللي
+
+45
+00:03:37,270 --> 00:03:40,930
+هو T.
+
+46
+00:03:40,930 --> 00:03:47,190
+فأنا بحسب، بحسب الـ net area، اللي أخدت مقطع هنا
+
+47
+00:03:47,190 --> 00:03:50,450
+هيكون
+
+48
+00:03:50,450 --> 00:03:51,410
+عندي شكل المقطع
+
+49
+00:03:54,140 --> 00:04:07,060
+بالشكل هذا. هذا
+
+50
+00:04:07,060 --> 00:04:14,360
+الـ D، هذا الـ W، هذا
+
+51
+00:04:14,360 --> 00:04:21,190
+الـ T. من حد واضح، الـ net area هي الـ area المظللة دي.
+
+52
+00:04:21,190 --> 00:04:28,210
+هتكون اللي هو العرض في الارتفاع،  الـ area دي W ناقص D
+
+53
+00:04:28,210 --> 00:04:32,210
+في T، و
+
+54
+00:04:32,210 --> 00:04:36,670
+الـ stress عند الثقب، أو عند الـ hole، σmaximum
+
+55
+00:04:36,670 --> 00:04:43,090
+هيكون بيساوي Kt في σo.
+
+56
+00:04:45,810 --> 00:04:50,550
+هذا one example. another example في الـ appendix
+
+57
+00:04:50,550 --> 00:04:53,890
+A15-9
+
+58
+00:04:53,890 --> 00:05:02,530
+في الكتاب، فيه مبين عندي mechanical element، مقطع
+
+59
+00:05:02,530 --> 00:05:06,070
+مدور، فيه تغيير في الـ cross section من D small لـ D
+
+60
+00:05:06,070 --> 00:05:06,610
+capital.
+
+61
+00:05:16,620 --> 00:05:21,180
+وفيه بتأثير على الـ bending moment، بتأثير على الـ
+
+62
+00:05:21,180 --> 00:05:25,280
+bending moment M، و
+
+63
+00:05:25,280 --> 00:05:29,960
+فيه عندي fillet هنا، الـ
+
+64
+00:05:29,960 --> 00:05:35,400
+radius بتاعها R. عشان احسب الـ stress concentration
+
+65
+00:05:35,400 --> 00:05:40,420
+عند النقطة هذه، بجي من
+
+66
+00:05:40,420 --> 00:05:44,360
+الـ two parameters، اللي هو الـ ratio بين الـ
+
+67
+00:05:44,360 --> 00:05:52,970
+fillet radius و D small. وعندي هنا different curves.
+
+68
+00:05:52,970 --> 00:05:55,850
+هذه الـ curves بيعطوني
+
+69
+00:06:01,630 --> 00:06:08,130
+different D capital على D small. يعني لو كنت أعرف D
+
+70
+00:06:08,130 --> 00:06:11,370
+capital على D small، بختار curve من الـ curves هذه، وأعرف
+
+71
+00:06:11,370 --> 00:06:14,830
+R على D. مثلًا لو كان D capital على D small بيساوي
+
+72
+00:06:14,830 --> 00:06:18,870
+ثلاثة، بحسب الـ stress concentration Kt بيطلع بيساوي
+
+73
+00:06:18,870 --> 00:06:25,570
+1.8، والـ σo في الحالة هذه بتساوي
+
+74
+00:06:25,570 --> 00:06:34,050
+طبعًا هنا عند الـ pure bending case، σo بيساوي
+
+75
+00:06:34,050 --> 00:06:43,190
+M في C على I، و C بيساوي D على 2، و I بيساوي π على
+
+76
+00:06:43,190 --> 00:06:53,770
+64 D أس 4. بتصفي σo بيساوي 32M على πD تكعيب. والـ σmaximum
+
+77
+00:06:55,710 --> 00:07:08,290
+due to stress concentration بيساوي Kt في σo.
+
+78
+00:07:08,290 --> 00:07:16,850
+due to stress concentration بيساوي Kt في σo.
+
+79
+00:07:25,770 --> 00:07:28,370
+الآن، احنا هناخد في الاعتبار الـ stress
+
+80
+00:07:28,370 --> 00:07:35,510
+concentration في حالتين: حالة أن الـ material بتاعة
+
+81
+00:07:35,510 --> 00:07:39,710
+الـ mechanical element تكون ductile، والحالة
+
+82
+00:07:39,710 --> 00:07:41,650
+الثانية أن الـ material بتاعة الـ mechanical element
+
+83
+00:07:41,650 --> 00:07:46,010
+تكون brittle. الآن لو أخدنا الحالة هذه
+
+84
+00:08:05,270 --> 00:08:10,590
+هذه الـ shaft، هذه
+
+85
+00:08:10,590 --> 00:08:15,110
+المحور للـ shaft، عندي
+
+86
+00:08:15,110 --> 00:08:25,010
+fillet هنا، R، عند القطر هنا D small، عند
+
+87
+00:08:25,010 --> 00:08:25,930
+هذه D capital.
+
+88
+00:08:36,440 --> 00:08:38,920
+طبعًا واضح أنه فيه تغيير في الـ cross section من D
+
+89
+00:08:38,920 --> 00:08:41,600
+small لـ D capital، وفيه عندي fillet radius R، معناه
+
+90
+00:08:41,600 --> 00:08:45,580
+وفيه عندي stress concentration. نفترض أن أنا under
+
+91
+00:08:45,580 --> 00:08:54,740
+bending moment M، و M due
+
+92
+00:08:54,740 --> 00:09:00,600
+to bending. هتشوف في المنطقة هي دي الـ stress
+
+93
+00:09:00,600 --> 00:09:04,440
+distribution هيكون بالشكل هي ده.
+
+94
+00:09:12,570 --> 00:09:17,350
+تحت هيكون عندي tension، و
+
+95
+00:09:17,350 --> 00:09:22,910
+هنا هيكون عندي compression.
+
+96
+00:09:22,910 --> 00:09:31,230
+هنا compression normal stress و tension normal
+
+97
+00:09:31,230 --> 00:09:36,430
+stress. يعني لو أخدنا fiber، if you take، if you
+
+98
+00:09:36,430 --> 00:09:39,170
+take a fiber.
+
+99
+00:09:42,980 --> 00:09:48,840
+الآن لو الـ moment وصلت لحد أنه صار عندي هنا، الـ due
+
+100
+00:09:48,840 --> 00:09:50,720
+to stress، كنت راح يكون عندي σmax
+
+101
+00:09:54,580 --> 00:09:59,420
+بيساوي Kt في σo. ممكن الـ σo does not reach
+
+102
+00:09:59,420 --> 00:10:03,560
+الـ yielding، لكن أنا في الآخر هحس بالـ σmaximum
+
+103
+00:10:03,560 --> 00:10:06,900
+الـ local stress عند النقطة هذه، σmaximum
+
+104
+00:10:06,900 --> 00:10:11,380
+بيساوي Kt في σo. ممكن الـ stress هيدخل في الـ..
+
+105
+00:10:11,380 --> 00:10:14,140
+في الـ plastic region، يعني هيسير عندي plastic
+
+106
+00:10:14,140 --> 00:10:20,380
+deformation، يعني هيسير yielding. المنطقة هذه، الطبقة
+
+107
+00:10:20,380 --> 00:10:26,590
+هذه، والـ yield. المادة ductile، يعني مادة ايش؟ طرية.
+
+108
+00:10:26,590 --> 00:10:31,310
+due to yielding بيصير فيها strain hardening أو cold
+
+109
+00:10:31,310 --> 00:10:33,930
+work، يعني الـ strength بتاعتها بيزيد due to
+
+110
+00:10:33,930 --> 00:10:38,630
+yielding. الآن الـ load هينتقل للـ layer اللي بعدها.
+
+111
+00:10:38,630 --> 00:10:43,230
+هينتقل للـ layer.. للطبقة اللي بعدها، وهكذا. نتيجة
+
+112
+00:10:43,230 --> 00:10:47,930
+أن المادة مرنة، بتتمد، فبيصير عندها
+
+113
+00:10:51,610 --> 00:10:56,550
+الـ.. الـ load is shared with other fibers. معناته
+
+114
+00:10:56,550 --> 00:11:01,490
+الـ.. الـ.. الـ material في الآخر بتريح.. بتريح
+
+115
+00:11:01,490 --> 00:11:06,810
+وبالتالي الـ effect بتاع الـ.. الـ.. الـ effect بتاع
+
+116
+00:11:06,810 --> 00:11:11,450
+الـ stress concentration due to the fillet أو due
+
+117
+00:11:11,450 --> 00:11:14,590
+to.. to change in cross section from D small to D
+
+118
+00:11:14,590 --> 00:11:15,350
+capital.
+
+119
+00:11:18,000 --> 00:11:23,760
+تقريباً بتتوزع على كل الـ section نتيجة أنه الـ
+
+120
+00:11:23,760 --> 00:11:28,320
+yielding، أو الـ load is shared among all the layers
+
+121
+00:11:28,320 --> 00:11:34,800
+of the body due to its ductility. في الحالة هذه،
+
+122
+00:11:34,800 --> 00:11:40,580
+stress concentration، في حالة stress concentration
+
+123
+00:11:40,580 --> 00:11:48,770
+في حالة mechanical element that is ductile and that
+
+124
+00:11:48,770 --> 00:11:54,070
+is under static loading، بالحالة هذه بنهمل الـ
+
+125
+00:11:54,070 --> 00:11:56,510
+effect بتاع الـ stress concentration. معناته إذا
+
+126
+00:11:56,510 --> 00:11:58,550
+كانت الـ material بتاعة الـ mechanical element
+
+127
+00:11:58,550 --> 00:12:03,530
+ductile، وكان الـ loading static، بهمل الـ stress
+
+128
+00:12:03,530 --> 00:12:10,170
+concentration effect. هذا في حالة ductile material.
+
+129
+00:12:15,210 --> 00:12:20,430
+لكن في حالة المادة كانت ductile، والـ loading is not
+
+130
+00:12:20,430 --> 00:12:24,010
+static، يعني الـ loading is dynamic، dynamic loading
+
+131
+00:12:24,010 --> 00:12:28,330
+يعني الـ loading مش ثابت، الـ loading بتغير، في
+
+132
+00:12:28,330 --> 00:12:32,930
+الحالة هذه فش إمكانية أهمل الـ stress
+
+133
+00:12:32,930 --> 00:12:35,230
+concentration، you have to take care of stress
+
+134
+00:12:35,230 --> 00:12:38,790
+concentration for a mechanical element that is
+
+135
+00:12:38,790 --> 00:12:43,210
+ductile and that is under dynamic loading. في حالة
+
+136
+00:12:43,210 --> 00:12:48,470
+الـ material كانت brittle، I have to consider الـ
+
+137
+00:12:48,470 --> 00:12:52,570
+stress concentration، بغض النظر لو المادة كانت
+
+138
+00:12:52,570 --> 00:13:00,290
+ductile أو brittle، لأن الـ material brittle قاسية جدًا،
+
+139
+00:13:00,290 --> 00:13:03,650
+ما بيصيرش عملية الـ sharing between different
+
+140
+00:13:03,650 --> 00:13:05,870
+layers of the material. يعني الـ material، النقطة
+
+141
+00:13:05,870 --> 00:13:08,950
+اللي صار فيها localized stress concentration أو
+
+142
+00:13:08,950 --> 00:13:13,270
+localized plastic deformation، فهي بتشيل كل الـ
+
+143
+00:13:13,270 --> 00:13:18,550
+loading، and it does not share or it does not
+
+144
+00:13:18,550 --> 00:13:20,770
+distribute.. the load is not distributed among
+
+145
+00:13:20,770 --> 00:13:25,150
+other layers. وبالتالي أنا ممكن أوصل الـ ultimate
+
+146
+00:13:25,150 --> 00:13:29,950
+tensile strength عند النقطة هذه، ويصير عندي
+
+147
+00:13:29,950 --> 00:13:33,390
+sudden failure. وبالتالي الـ stress concentration
+
+148
+00:13:33,390 --> 00:13:36,930
+effect must be included for a brittle material
+
+149
+00:13:36,930 --> 00:13:45,210
+whether the loading is static or dynamic. طيب،
+
+150
+00:13:59,340 --> 00:14:03,520
+لما كان هنا uniaxial stress element، uniaxial يعني
+
+151
+00:14:03,520 --> 00:14:09,440
+هاي stress element، وهي
+
+152
+00:14:09,440 --> 00:14:15,980
+عليه force، σ، هاي σ. لو رصدت الـ stress
+
+153
+00:14:15,980 --> 00:14:21,080
+strain curve لهذا الـ element، هيكون بالشكل هذا تقريبًا.
+
+154
+00:14:21,080 --> 00:14:26,100
+هذا strain، هذا σ، وكنا نحسب
+
+155
+00:14:30,590 --> 00:14:37,390
+هذا point to strength percent، وهذا كان σ
+
+156
+00:14:37,390 --> 00:14:44,930
+yield، وهذا σ ultimate
+
+157
+00:14:44,930 --> 00:14:49,970
+أو Sy، الـ yield strength، والـ ultimate strength، Su
+
+158
+00:14:49,970 --> 00:15:00,390
+yield، و Su ultimate. لو حكينا، هذا هو الـ actual state
+
+159
+00:15:00,390 --> 00:15:04,370
+of stress، هذه الـ σ. كنا نحصل factor of safety n
+
+160
+00:15:04,370 --> 00:15:12,490
+بيساوي الـ strength على σ. هذا في حالة uniaxial
+
+161
+00:15:12,490 --> 00:15:17,650
+stress element، لكن
+
+162
+00:15:17,650 --> 00:15:23,140
+على أرض الواقع، مش بالضرورة، أو في أغلب الأحيان
+
+163
+00:15:23,140 --> 00:15:27,340
+بيكونش الـ state of stress، يعني axle في معظم
+
+164
+00:15:27,340 --> 00:15:30,640
+الأحيان بتكون الـ state of stress is
+
+165
+00:15:30,640 --> 00:15:35,740
+multidimensional، يعني ممكن كنت لو اتطلع على الـ 3D
+
+166
+00:15:35,740 --> 00:15:40,560
+stress element، عندي هنا σx، σy، σz،
+
+167
+00:15:40,560 --> 00:15:45,940
+τxy، τxz، τyz، يعني في عندي كل أنواع الـ
+
+168
+00:15:45,940 --> 00:15:48,100
+loading conditions موجودة.
+
+169
+00:15:50,110 --> 00:15:55,230
+السؤال: how to compare.. how to compare this state
+
+170
+00:15:55,230 --> 00:15:59,150
+of stress with a single strength؟ لأن في الآخر..
+
+171
+00:15:59,150 --> 00:16:02,310
+النهاية.. في النهاية الـ material لها strength
+
+172
+00:16:02,310 --> 00:16:07,010
+واحدة. الـ material كـ material لها strength واحدة، لكن
+
+173
+00:16:07,010 --> 00:16:11,550
+الـ.. الـ.. الـ element ممكن يكون بيتعرض لـ
+
+174
+00:16:11,550 --> 00:16:18,190
+multi state of stress. معناته
+
+175
+00:16:18,190 --> 00:16:25,590
+أنا عندي one strength، one strength، عندي multiple
+
+176
+00:16:25,590 --> 00:16:30,110
+state of stress. يعني أنا عندي معضلة، كيف بدي أـ..
+
+177
+00:16:30,110 --> 00:16:34,450
+بدي أقارن one strength and multiple stresses. هذا
+
+178
+00:16:34,450 --> 00:16:41,430
+سؤال نسأله، محتاجين لإجابة عليه. how to compare one
+
+179
+00:16:41,430 --> 00:16:43,730
+strength of the material of the mechanical element
+
+180
+00:16:43,730 --> 00:16:46,050
+with a multiple state of stress?
+
+181
+00:16:50,020 --> 00:16:54,740
+الإجابة بتيجي من أنه عشان هيك احنا نحتاج لـ static
+
+182
+00:16:54,740 --> 00:16:59,480
+failure theory. الـ failure theory بتقترح علينا
+
+183
+00:16:59,480 --> 00:17:06,020
+appropriate means، طريقة للمقارنة بين multi axial
+
+184
+00:17:06,020 --> 00:17:11,040
+state of stress to single strength. معناته الـ
+
+185
+00:17:11,040 --> 00:17:16,820
+design theories أو الـ failure theories propose an
+
+186
+00:17:16,820 --> 00:17:20,080
+appropriate means، appropriate means to compare
+
+187
+00:17:20,080 --> 00:17:25,980
+multi axial state of stress to a single strength.
+
+188
+00:17:25,980 --> 00:17:33,280
+هذا اللي بيجيب على السؤال تبعنا. الآن ملخص الـ
+
+189
+00:17:33,280 --> 00:17:38
+
+223
+00:20:44,240 --> 00:20:48,680
+كلما زاد عندي الدقة كلما  is less conservative
+
+224
+00:20:48,680 --> 00:20:52,980
+أكثر مخاطرة if I need more accurate أنظر، بزيد عندي
+
+225
+00:20:52,980 --> 00:20:57,480
+results، less conservative results  بستخدم في هذه الحالة
+
+226
+00:20:57,480 --> 00:21:03,000
+هذه  الـ distortion energy theory  التي سنأتي إليها لاحقًا
+
+227
+00:21:05,150 --> 00:21:08,390
+أنا في الـ... أنا أجبت على السؤال في هذه الحالة إذا
+
+228
+00:21:08,390 --> 00:21:10,850
+أسوأ الـ... الـ yield strength in tension  والـ
+
+229
+00:21:10,850 --> 00:21:14,170
+yield strength in compression أريد أن أرى إذا أردت
+
+230
+00:21:14,170 --> 00:21:18,510
+conservative results  ، يعني المخاطرة أقل، أستخدم
+
+231
+00:21:18,510 --> 00:21:21,470
+maximum shear stress theory إذا أردت more accurate
+
+232
+00:21:21,470 --> 00:21:27,450
+results ،  المخاطرة أكثر، أستخدم الـ distortion energy theory
+
+233
+00:21:28,420 --> 00:21:31,800
+في حالة كانت الـ yield strength in tension تساوي
+
+234
+00:21:31,800 --> 00:21:35,320
+yield strength in compression أستخدم ما يسمى الـ
+
+235
+00:21:35,320 --> 00:21:39,180
+Ductile Coulomb-Moore Theory
+
+236
+00:21:39,180 --> 00:21:42,840
+Theory  التي هي المعادلة 5.26 في الكتاب
+
+237
+00:21:47,980 --> 00:21:51,200
+أنا في هذه الحلقة عالجت حالة الـ ductile
+
+238
+00:21:51,200 --> 00:21:56,200
+materials إذا كانت المادة  brittle  ، يعني F أقل
+
+239
+00:21:56,200 --> 00:22:02,220
+من نقطة  O5  أريد أن أقرر if I need conservative
+
+240
+00:22:02,220 --> 00:22:03,040
+results
+
+241
+00:22:08,380 --> 00:22:11,120
+يعني إذا أردت conservative results ، يعني العنصر
+
+242
+00:22:11,120 --> 00:22:14,000
+المخاطر في الحسابات تكون أقل، أذهب إلى الجهة اليمنى
+
+243
+00:22:14,000 --> 00:22:18,760
+إذا أردت more accurate less conservative ، يعني دقة
+
+244
+00:22:18,760 --> 00:22:22,680
+أعلى مع مخاطرة أكثر في الحسابات، أذهب إلى الجهة
+
+245
+00:22:22,680 --> 00:22:26,000
+اليسرى، انتقل، if I need conservative results أستخدم
+
+246
+00:22:26,000 --> 00:22:30,240
+الـ brittle column more theory
+
+247
+00:22:30,240 --> 00:22:36,600
+إذا أردت أنا more accurate results less
+
+248
+00:22:36,600 --> 00:22:43,980
+conservative أستخدم الـ modified more theory هذه
+
+249
+00:22:43,980 --> 00:22:48,260
+خارطة الطريق لكل فصل، هذه خارطة الطريق لكل فصل
+
+250
+00:22:49,500 --> 00:22:54,060
+الكتاب عرضها في آخر الفصل، أنا أرى أنه من الأفضل
+
+251
+00:22:54,060 --> 00:22:56,740
+عرضها في بداية الفصل وآخر الفصل، سأعرض
+
+252
+00:22:56,740 --> 00:23:00,700
+نفس الخارطة هذه، لنراجع العمل الذي قمنا به طبعًا
+
+253
+00:23:00,700 --> 00:23:04,840
+أنا هنا عرضت هذا flow chart  ، هذا كل الفصل، سنكون...
+
+254
+00:23:04,840 --> 00:23:08,020
+سنتحدث عن الـ maximum shear stress theory
+
+255
+00:23:08,020 --> 00:23:10,120
+الـ distortion energy theory ، الـ ductile column
+
+256
+00:23:10,120 --> 00:23:12,140
+wall theory ، الـ brittle column wall theory  و الـ
+
+257
+00:23:12,140 --> 00:23:15,100
+modified wall theory  هذه كلها ستُغطى في هذا
+
+258
+00:23:15,100 --> 00:23:15,360
+الفصل
+
+259
+00:23:19,860 --> 00:23:26,220
+لنبدأ في النظريات المستخدمة في static loading
+
+260
+00:23:26,220 --> 00:23:36,300
+design  أول
+
+261
+00:23:36,300 --> 00:23:40,340
+نظرية هي الـ maximum normal stress theory  نموذجها
+
+262
+00:23:40,340 --> 00:23:44,860
+برمز MNS  ،  maximum normal stress theory  ، الـ maximum
+
+263
+00:23:44,860 --> 00:23:48,440
+normal stress theory  تقول التالي، تقول أن الـ
+
+264
+00:23:48,440 --> 00:23:51,860
+yielding begins  يعني يبدأ العنصر الميكانيكي
+
+265
+00:23:51,860 --> 00:23:57,920
+يدخل  إلى  الـ plastic range  when  عندما  الـ maximum principal
+
+266
+00:23:57,920 --> 00:24:02,000
+stress in a stress element exceeds the yield
+
+267
+00:24:02,000 --> 00:24:08,860
+strength  يبدأ  يصير  yielding  عندما  الـ maximum
+
+268
+00:24:08,860 --> 00:24:14,660
+principle stress in a stress element تتجاوز الـ yield
+
+269
+00:24:14,660 --> 00:24:18,500
+strength  للمادة، في هذه الحالة أقول أن الجزء
+
+270
+00:24:18,500 --> 00:24:24,020
+is...الجزء يفشل، part fails ، يصير فشل للجزء
+
+271
+00:24:24,020 --> 00:24:27,140
+معناته according to maximum normal stress theory
+
+272
+00:24:27,140 --> 00:24:31,260
+الـ yielding يبدأ عندما الـ maximum principle stress
+
+273
+00:24:31,260 --> 00:24:35,960
+in a stress element تتجاوز الـ yield strength of the
+
+274
+00:24:35,960 --> 00:24:41,220
+material طبعًا أنا أستخدم في الفصل الثالث استخدمنا
+
+275
+00:24:41,220 --> 00:24:44,360
+الـ Mohr circle  لاستخدام more circle to find the
+
+276
+00:24:44,360 --> 00:24:47,700
+principal stresses إذا كنا نحسب سيجما واحد وسيجما
+
+277
+00:24:47,700 --> 00:24:51,920
+اثنين وسيجما ثلاثة، كنا نرتبهم بحيث يكون سيجما
+
+278
+00:24:51,920 --> 00:24:58,480
+واحد أكبر من سيجما اثنين أكبر من سيجما ثلاثة
+
+279
+00:24:58,480 --> 00:25:07,470
+معناته سيجما واحد، إذا كان سيجما واحد أكبر أو يساوي
+
+280
+00:25:07,470 --> 00:25:12,870
+الـ yield strength  في حالة الـ Ductile Material يصير فشل
+
+281
+00:25:12,870 --> 00:25:14,150
+مباشر
+
+282
+00:25:21,040 --> 00:25:24,440
+هذه هي الـ principle أو الـ maximum normal stress
+
+283
+00:25:24,440 --> 00:25:27,860
+theory تقول يصير yielding عندما الـ maximum
+
+284
+00:25:27,860 --> 00:25:32,960
+principle stress في العنصر الميكانيكي يكون أكبر
+
+285
+00:25:32,960 --> 00:25:35,780
+أو يساوي yield strength of that mechanical element
+
+286
+00:25:35,780 --> 00:25:39,580
+في هذه الحالة يصير عندي ماذا؟ failure otherwise
+
+287
+00:25:39,580 --> 00:25:45,700
+لا يوجد failure عندنا، يعني
+
+288
+00:25:45,700 --> 00:25:47,680
+لو أخذنا الـ two-D state of stress
+
+289
+00:25:51,200 --> 00:26:00,260
+سيكون عندي سيجما واحد وهي سيجما اثنين، سيجما واحد
+
+290
+00:26:00,260 --> 00:26:05,320
+التي هي الـ first principal stress  وسيجما اثنين هي
+
+291
+00:26:05,320 --> 00:26:10,020
+second principal stress إذا قسمت سيجما واحد على SY
+
+292
+00:26:10,020 --> 00:26:14,620
+وسيجما اثنين على SY
+
+293
+00:26:18,860 --> 00:26:23,020
+يعني إذا كان سيجما واحد على SY ، يعني إذا كان سيجما
+
+294
+00:26:23,020 --> 00:26:27,860
+واحد يساوي SY ، يعني سيجما واحد على SY يساوي ماذا؟ واحد
+
+295
+00:26:27,860 --> 00:26:32,520
+إذا
+
+296
+00:26:32,520 --> 00:26:40,200
+كان سيجما واحد على SY أكبر أو يساوي واحد، يصير عندي
+
+297
+00:26:40,200 --> 00:26:45,240
+ماذا؟ failure يعني إذا كنت في هذا الاتجاه من هذه
+
+298
+00:26:45,240 --> 00:26:48,140
+النقطة وأمشي يصير عندي
+
+299
+00:26:57,390 --> 00:27:06,770
+failure طبعًا هذا يمثل الـ
+
+300
+00:27:06,770 --> 00:27:14,770
+failure contour للـ
+
+301
+00:27:14,770 --> 00:27:15,790
+mechanical element
+
+302
+00:27:32,700 --> 00:27:37,300
+داخل المستطيل لا
+
+303
+00:27:37,300 --> 00:27:42,940
+يوجد failure  خارج
+
+304
+00:27:42,940 --> 00:27:48,570
+المستطيل يوجد failure ، يعني هنا...هنا خارج failure  داخل
+
+305
+00:27:48,570 --> 00:27:52,850
+safe ، أنبني هنا experimental data experimental
+
+306
+00:27:52,850 --> 00:27:57,850
+data لأرى هل النظرية تحقق الأشياء، يعني
+
+307
+00:27:57,850 --> 00:28:03,010
+متوافقة مع الواقع أم لا، لأن أنبني عندي في المربع
+
+308
+00:28:03,010 --> 00:28:05,990
+الأول، إذا كان سيجما واحد موجبة أو سيجما اثنين موجبة
+
+309
+00:28:05,990 --> 00:28:11,790
+يكون الـ...الـ experimental data  ، يعني ممكن أعتبرها
+
+310
+00:28:11,790 --> 00:28:21,270
+fits  النظرية بشكل دقيق وبشكل كاف، لكن في الربع
+
+311
+00:28:21,270 --> 00:28:25,030
+الرابع إذا كان سيجما واحد موجبة وسيجما اثنين سالبة
+
+312
+00:28:25,030 --> 00:28:28,810
+لاحظوا
+
+313
+00:28:28,810 --> 00:28:35,890
+أن في الحقيقة لو قلنا هذا هو الـ load line  في
+
+314
+00:28:35,890 --> 00:28:44,480
+الحقيقة we reach failure  وصلنا إلى الـ failure  و
+
+315
+00:28:44,480 --> 00:28:47,960
+الآن النظرية تقول لي لا، وضعك جيد، ليس failure
+
+316
+00:28:47,960 --> 00:28:52,500
+تقول لتصل إلى الـ failure  يجب أن تصل النقطة هنا، لكن
+
+317
+00:28:52,500 --> 00:28:55,840
+أنا في الحقيقة حسب الواقع، صار failure  معناته
+
+318
+00:28:55,840 --> 00:29:00,060
+النظرية في الربع الرابع تخدعني، لا تعطي شيء دقيق
+
+319
+00:29:00,060 --> 00:29:07,430
+وبالتالي it's not safe to use this theory for
+
+320
+00:29:07,430 --> 00:29:11,830
+ductile material  لسبب بسيط لأنه it does not fit أو
+
+321
+00:29:11,830 --> 00:29:14,870
+it does not predict the experimental case
+
+322
+00:29:14,870 --> 00:29:20,130
+experimental case تقول أنني أصبح في حالة failure  while
+
+323
+00:29:20,130 --> 00:29:25,070
+the maximum stress theory says that it is safe
+
+324
+00:29:25,070 --> 00:29:31,290
+failures does not reach yet it is reached yet  في
+
+325
+00:29:31,290 --> 00:29:35,850
+الحقيقة لكن حسب النظرية لا، لم نصل، لأن ذلك معناته
+
+326
+00:29:35,850 --> 00:29:45,450
+أنا آخذ نتائج أو أقول نتائج مضللة، فمعناته يعني
+
+327
+00:29:45,450 --> 00:29:50,110
+أصبحت النظرية فقط ذات قيمة تاريخية، لن نستخدمها في
+
+328
+00:29:50,110 --> 00:29:54,290
+الحسابات الخاصة بنا، النظرية
+
+329
+00:29:54,290 --> 00:30:02,530
+الثانية التي هي الـ maximum shear stress theory الـ
+
+330
+00:30:02,530 --> 00:30:07,150
+maximum
+
+331
+00:30:07,150 --> 00:30:12,630
+shear stress theory تقول التالي، يبدأ
+
+332
+00:30:12,630 --> 00:30:16,270
+المادة تدخل الـ plastic range  ، تبدأ بالتشوه عندما
+
+333
+00:30:16,270 --> 00:30:22,990
+الـ maximum shear stress in a stress element
+
+334
+00:30:24,390 --> 00:30:28,950
+يكون أكبر أو يساوي الـ maximum shear stress in a
+
+335
+00:30:28,950 --> 00:30:32,450
+tensile test specimen  الذي له نفس مادة الـ
+
+336
+00:30:32,450 --> 00:30:37,090
+mechanical element ، المعنى لأن maximum shear
+
+337
+00:30:37,090 --> 00:30:40,830
+stress  يقول التالي، يقول يصير failure أو يصير
+
+338
+00:30:40,830 --> 00:30:45,310
+yielding  أو المادة تدخل في الـ plastic range عندما الـ
+
+339
+00:30:45,310 --> 00:30:50,510
+maximum shear stress في العنصر الفعلي تتجاوز،
+
+340
+00:30:50,510 --> 00:30:54,730
+تكون أكبر أو يساوي الـ maximum shear stress in a
+
+341
+00:30:54,730 --> 00:30:57,690
+tensile test specimen ، الـ tensile test specimen
+
+342
+00:30:57,690 --> 00:31:05,810
+يكون معرضًا لحمل محوري، سيجما وسيجما، لو أنا
+
+343
+00:31:05,810 --> 00:31:07,470
+أرسم الـ Mohr circle له
+
+344
+00:31:13,220 --> 00:31:23,640
+سيكون بالشكل هذا، Mohr circle  ، هذا سيجما واحد وهذا سيجما
+
+345
+00:31:23,640 --> 00:31:30,600
+اثنين وهذا تاو ماكسيمم ، الفشل، سيجما واحد سيكون
+
+346
+00:31:30,600 --> 00:31:38,980
+أسوأ، أسوأ، معناته تاو ماكسيمم سيكون أسوأ، أسوأ
+
+347
+00:31:40,220 --> 00:31:46,980
+على اثنين in a tensile test
+
+348
+00:31:46,980 --> 00:31:56,460
+specimen  يعني
+
+349
+00:31:56,460 --> 00:32:00,460
+ممكن نصيغها بطريقة أخرى، نقول according to maximum
+
+350
+00:32:00,460 --> 00:32:05,680
+shear stress theory failure begins when yielding
+
+351
+00:32:05,680 --> 00:32:07,520
+begins or yielding begins
+
+352
+00:32:10,310 --> 00:32:19,490
+يصير عندما التاو ماكسيمم تكون أكبر أو يساوي SY على
+
+353
+00:32:19,490 --> 00:32:30,490
+اثنين، نحن
+
+354
+00:32:30,490 --> 00:32:35,350
+Mohr circle في هذا الـ tensile  بشكل عام، بشكل عام
+
+355
+00:32:37,770 --> 00:32:42,130
+تكون  هذه  Mohr circle  بالشكل هذا، هذا سيجما واحد، هذا
+
+356
+00:32:42,130 --> 00:32:46,430
+الـ
+
+357
+00:32:46,430 --> 00:32:50,370
+3D Mohr circle سيجما واحد سيجما اثنين سيجما
+
+358
+00:32:50,370 --> 00:32:54,850
+ثلاثة، أنا أرتب بحيث سيجما واحد أكبر من سيجما اثنين
+
+359
+00:32:54,850 --> 00:32:59,350
+أكبر من سيجما ثلاثة، ونحن عرفنا سابقًا، قلنا الـ
+
+360
+00:32:59,350 --> 00:33:05,650
+tau maximum  يساوي سيجما واحد ناقص سيجما ثلاثة
+
+361
+00:33:05,650 --> 00:33:11,130
+على اثنين، و according to الـ maximum shear stress
+
+362
+00:33:11,130 --> 00:33:14,670
+theory  يصير failure أو يصير yielding عندما التاو
+
+363
+00:33:14,670 --> 00:33:15,190
+maximum
+
+364
+00:33:18,660 --> 00:33:23,760
+تكون أكبر أو يساوي SY على اثنين، يعني الـ maximum
+
+365
+00:33:23,760 --> 00:33:28,880
+هي سيجما واحد ناقص سيجما ثلاثة على اثنين أكبر أو
+
+366
+00:33:28,880 --> 00:33:33,280
+يساوي SY على اثنين، يعني لو اختصرت اثنين مع اثنين
+
+367
+00:33:33,280 --> 00:33:37,420
+تكون سيجما واحد ناقص سيجما ثلاثة أكبر أو يساوي
+
+368
+00:33:37,420 --> 00:33:39,240
+SY
+
+369
+00:33:43,280 --> 00:33:48,160
+يعني exactly at failure exactly at failure تكون
+
+370
+00:33:48,160 --> 00:33:54,740
+tau maximum  يساوي SY على اثنين، إذا أنا لا أريد
+
+371
+00:33:54,740 --> 00:33:57,880
+يصير failure ، إذا لا أريد يصير failure أحط factor of
+
+372
+00:33:57,880 --> 00:34:03,840
+safety  يصير tau maximum to avoid failure  يساوي
+
+373
+00:34:03,840 --> 00:34:08,600
+SY على اثنين و factor of safety
+
+374
+00:34:16,320 --> 00:34:33,260
+الآن سنأخذ الـ maximum shear stress theory  سناخذ
+
+375
+00:34:33,260 --> 00:34:37,740
+2D state of stress
+
+376
+00:34:42,320 --> 00:34:45,440
+يعني two-D state of stress سيكون اثنين من الـ
+
+377
+00:34:45,440 --> 0:34:50,120
+principal stresses  التي هي قيم، و الـ principal
+
+378
+00:34:50,120 --> 00:34:52,800
+stress في الثالث سيكون  ساوي صفر، يعني سيكون عندي
+
+379
+00:34:52,800 --> 00:34:56,280
+سيجما واحد و سيجما اثنين و سيجما ثلاثة موجودين،  بس
+
+380
+00:34:56,280 --> 00:35:00,620
+واحد من الثلاثة هذا سيكون  ساوي صفر، معناته عند
+
+381
+00:35:00,620 --> 00:35:06,560
+plain stress state  ، سيجما A و سيجما B مثل الـ
+
+382
+00:35:06,560 --> 00:35:08,540
+two non zero principal stresses
+
+383
+00:35:11,500 --> 00:35:14,160
+سأحسب من Mohr circles سيجما واحد وسيجما اثنين و
+
+384
+00:35:14,160 --> 00:35:17,800
+سيجما ثلاثة أو أرتبهم ترتيبًا تصاعديًا بحيث يكون عندي
+
+385
+00:35:17,800 --> 00:35:23,400
+سيجما واحد أكبر من سيجما اثنين أكبر من سيجما ثلاثة
+
+386
+00:35:23,400 --> 00:35:26,680
+أو أكبر من سيجما ثلاثة أو أكبر من سيجما ثلاثة أو
+
+387
+00:35:26,680 --> 00:35:28,760
+أكبر من سيجما ثلاثة أو أكبر من سيجما ثلاثة أو أكبر
+
+388
+00:35:28,760 --> 00:35:31,220
+من سيجما ثلاثة أو أكبر من سيجما ثلاثة أو أكبر من
+
+389
+00:35:31,220 --> 00:35:35,500
+سيجما ثلاثة أو أكبر من سيجما ثلاثة أو أكبر من
+
+390
+00:35:35,500 --> 00:35:40,380
+سيجما ثلاثة أو أكبر من سيجما ثلاثة، معناته سيكون
+
+391
+00:35:40,380 --> 00:35:43,720
+عندي two normal stress component سيجما A و سيجما B
+
+392
+00:35:43,720 --> 00:35:47,980
+إما الاثنان سيكونان موجبين سيجما A و سيجما B
+
+393
+00:35:47,980 --> 00:35:55,400
+موجبين أو سيجما A موجبة و سيجما B سالبة، أو الحالة
+
+394
+00:35:55,400 --> 00:35:58,640
+الثالثة، الثانية سالبة سيجما A سالبة و سيجما B
+
+395
+00:35:58,640 --> 00:36:03,560
+سالبة، يعني عندي three cases إذا كانت سيجما A و
+
+396
+00:36:03,560 --> 00:36:09,430
+سيجما B  positive  معناته سيكون أن سيجما A أكبر
+
+397
+00:36:09,430 --> 00:36:11,570
+من صفر وسيجما B أكبر من صفر، معناته هذه كأنها
+
+398
+00:36:11,570 --> 00:36:15,030
+سيجما واحد وهذه سيجما اثنين وهذه سيجما ثلاثة، معناته سيجما واحد
+
+399
+00:36:15,030 --> 00:36:19,290
+ستكون تساوي سيجما A ، سيجما اثنين سيجما B و سيجما ثلاثة صفر
+
+400
+00:36:19,290 --> 00:36:24,010
+الحالة الثانية التي سندرسها أن واحدة موجبة وواحدة
+
+401
+00:36:24,010 --> 00:36:28,680
+سالبة، يعني ستكون حالتي بترتيب تصاعدي هذه سيجما A
+
+402
+00:36:28,680 --> 00:36:32,320
+موجبة،  أكبر أو يساوي صفر، وصفر أكبر أو يساوي
+
+403
+00:36:32,320 --> 00:36:35,980
+سيجما B معناته سيجما واحد التي هي سيجما A و سيجما
+
+404
+00:36:35,980 --> 00:36:39,540
+اثنين التي هي صفر و سي
+
+445
+00:41:24,390 --> 00:41:28,530
+الحالة الأولى الحالة الثانية case 2
+
+446
+00:41:39,690 --> 00:41:48,050
+سيجما A موجبة أكبر من أو تساوي صفر و سيجما B سالبة في
+
+447
+00:41:48,050 --> 00:41:53,350
+الحالة هذه ستكون سواء سيجما واحد هذه سيجما اثنين
+
+448
+00:41:53,350 --> 00:42:01,420
+هذه سيجما ثلاثة معناته هتكون التكون سواء سيجما واحد
+
+449
+00:42:01,420 --> 00:42:06,020
+معينة سيجما ثلاثة على اثنين بتساوي اللي هي سيجما A
+
+450
+00:42:06,020 --> 00:42:13,280
+معينة سيجما B على اثنين بيصير failure at failure أو
+
+451
+00:42:13,280 --> 00:42:18,240
+نحكي at failure سيكون
+
+452
+00:42:18,240 --> 00:42:23,840
+عندي ال tau max يساوي أسوأ  أيه على اثنين يعني سيكون
+
+453
+00:42:23,840 --> 00:42:31,240
+عندي اللي هي سيجما A ناقص سيجما B على اثنين بتساوي
+
+454
+00:42:31,240 --> 00:42:37,760
+as y على اثنين يعني سيكون عندي سيجما A ناقص سيجما
+
+455
+00:42:37,760 --> 00:42:44,820
+B يساوي as y وضبط الطرفين بـ ناقص ناقص زائد ناقص
+
+456
+00:42:44,820 --> 00:42:53,220
+بيصير عندي سيجما B يساوي سيجما A ناقص as y
+
+457
+00:43:03,410 --> 00:43:08,210
+سيجما A أنا حكيت موجبة سيجما B سالبة يعني أنا في
+
+458
+00:43:08,210 --> 00:43:11,130
+الربع الثاني في الربع الرابع هيكون هاي ال
+
+459
+00:43:11,130 --> 00:43:22,210
+loading line هذه سيجما A وهذه سيجما B exactly
+
+460
+00:43:22,210 --> 00:43:27,970
+at failure إذا كان إذا كان سيجما A at this point
+
+461
+00:43:27,970 --> 00:43:31,350
+at this point بيصير عندي failure
+
+462
+00:43:36,470 --> 00:43:44,370
+بيصير عندي ايش؟ failure في
+
+463
+00:43:44,370 --> 00:43:50,830
+الحالة هذه الخط أو
+
+464
+00:43:50,830 --> 00:43:53,130
+معادلة الخط المستقيم هذا
+
+465
+00:44:05,750 --> 00:44:09,130
+النقطة هذه الـ yield point تمثل تقاطع الخط المستقيم
+
+466
+00:44:09,130 --> 00:44:15,150
+مع الخط المستقيم هذا معادلته
+
+467
+00:44:15,150 --> 00:44:23,690
+الخط هذا عندنا لو أخذت نقطة هنا C و صفر فهي صفر و
+
+468
+00:44:23,690 --> 00:44:30,010
+ناقص sy وهي
+
+469
+00:44:30,010 --> 00:44:34,110
+عندنا الـ strength at any location في الحالة هذه
+
+470
+00:44:34,110 --> 00:44:35,030
+سيجما B
+
+471
+00:44:38,110 --> 00:44:49,150
+بـس أو سيجما A ناقص sy ال
+
+472
+00:44:49,150 --> 00:44:54,250
+case الثالثة أن both سيجما A و سيجما B are
+
+473
+00:44:54,250 --> 00:44:57,750
+negative both سيجما A و سيجما B negative يعني
+
+474
+00:44:57,750 --> 00:45:01,390
+هتكون هي سيجما A بهذا الاتجاه و سيجما B بهذا
+
+475
+00:45:01,390 --> 00:45:05,750
+الاتجاه معناته إذا كان عندي case ثلاثة
+
+476
+00:45:12,250 --> 00:45:19,210
+صفر أكبر من أو يساوي سيجما A أكبر من أو يساوي سيجما B
+
+477
+00:45:19,210 --> 00:45:25,450
+معناته هذا مثل سيجما واحد هذا سيجما اثنين وهذا ايش
+
+478
+00:45:25,450 --> 00:45:32,750
+سيجما ثلاثة معناته tau maximum تساوي سيجما واحد
+
+479
+00:45:32,750 --> 00:45:38,510
+ناقص سيجما ثلاثة على اثنين بتساوي سيجما واحد صفر
+
+480
+00:45:38,510 --> 00:45:41,010
+ناقص سيجما
+
+481
+00:45:45,310 --> 00:45:55,630
+بي على اثنين at failure سيكون
+
+482
+00:45:55,630 --> 00:46:03,270
+عندي تاو ماكس يساوي as y على اثنين اللي هو سيكون
+
+483
+00:46:03,270 --> 00:46:09,650
+عندي تاو ماكس يساوي ناقص سيجما بي على اثنين يعني at
+
+484
+00:46:09,650 --> 00:46:11,710
+failure يعني سيكون أكبر من أو يساوي
+
+485
+00:46:18,280 --> 00:46:27,380
+SY على اثنين إذا بدي أضرب الطرفين بـ .. بـ ناقص
+
+486
+00:46:27,380 --> 00:46:33,540
+يعني سيجما بي يصير أصغر من أو يساوي أصغر من أو
+
+487
+00:46:33,540 --> 00:46:40,640
+يساوي ناقص SY معناته في الحالة هذه case ثلاثة
+
+488
+00:46:45,450 --> 00:46:52,930
+يعني هذه case واحد case اثنين case ثلاثة الآن ممكن
+
+489
+00:46:52,930 --> 00:47:01,750
+يعني في different cases الآن الـ failure profile من
+
+490
+00:47:01,750 --> 00:47:07,370
+Campbell  جوا
+
+491
+00:47:07,370 --> 00:47:14,480
+الشكل هذا الـ part is safe  داخل الحدود أو برا الـ part
+
+492
+00:47:14,480 --> 00:47:18,060
+is failing according to maximum shear stress
+
+493
+00:47:18,060 --> 00:47:18,420
+theory
+
+494
+00:47:43,940 --> 00:47:53,600
+عندي هنا plot سيجما واحد على S وي سيجما اثنين على S وي
+
+495
+00:47:53,600 --> 00:48:01,300
+وهذا الـ contour lines اللي يمثل الـ failure طبقا ل
+
+496
+00:48:01,300 --> 00:48:04,500
+maximum shear stress theory وعندي هنا مبينة
+
+497
+00:48:04,500 --> 00:48:11,780
+experimental data بتلاحظوا أن الـ theory fits الـ
+
+498
+00:48:11,780 --> 00:48:17,050
+experimental data أحسن من الـ maximum number of
+
+499
+00:48:17,050 --> 00:48:18,970
+students you received سواء في الربع الأول أو في
+
+500
+00:48:18,970 --> 00:48:24,450
+الربع الرابع لاحظوا لو أخذت loading line معين في
+
+501
+00:48:24,450 --> 00:48:31,550
+الربع الأول طبق
+
+502
+00:48:31,550 --> 00:48:40,170
+للنظرية طبق للنظرية we predict failure before the
+
+503
+00:48:40,170 --> 00:48:43,800
+part is actually failed we predict failure before
+
+504
+00:48:43,800 --> 00:48:48,200
+the part is actually failed يعني نتوقع الانهيار للـ
+
+505
+00:48:48,200 --> 00:48:52,920
+mechanical element قبل ما في الحقيقة أن ايش صار له
+
+506
+00:48:52,920 --> 00:48:57,040
+انهيار أو failure هذا
+
+507
+00:48:57,040 --> 00:49:02,060
+يعني أن maximum shear stress theory is a
+
+508
+00:49:02,060 --> 00:49:07,540
+conservative theory يعني أنا بتوقع الـ failure لسه
+
+509
+00:49:07,540 --> 00:49:11,360
+لكن في الحقيقة ما صار failure معناته أنا الـ risk
+
+510
+00:49:11,360 --> 00:49:15,100
+في الحسابات بتاعتي ما فيش عندي risk في الحسابات لأن
+
+511
+00:49:15,100 --> 00:49:19,580
+أنا بحكي أنّه failed وهو في الواقع not failed
+
+512
+00:49:19,580 --> 00:49:25,320
+فمعناته it is conservative طبعا في فرق بين
+
+513
+00:49:25,320 --> 00:49:30,580
+conservative و accurate كل ما بتزيد الدقة بشكل
+
+514
+00:49:30,580 --> 00:49:37,790
+عام بيزيد عنصر المخاطرة في الحسابات يعني بتقل الـ
+
+515
+00:49:37,790 --> 00:49:42,050
+conservatism فـ the theory is conservative it
+
+516
+00:49:42,050 --> 00:49:46,570
+predicts failure before actually failure happens
+
+517
+00:49:48,860 --> 00:49:52,620
+نفس الشيء هنا أو أخذ load line هنا هاي .. هاي الـ
+
+518
+00:49:52,620 --> 00:49:57,700
+actual failure الـ theory predicts failure before
+
+519
+00:49:57,700 --> 00:50:02,000
+failure actually happens معناته الـ maximum shear
+
+520
+00:50:02,000 --> 00:50:05,600
+stress theory is a conservative theory في كل
+
+521
+00:50:05,600 --> 00:50:13,420
+الأربعة أرباع في all the quadrants طيب
+
+522
+00:50:17,430 --> 00:50:22,390
+المحاضرة الجاية هنحكي على الـ distortion energy
+
+523
+00:50:22,390 --> 00:50:27,170
+theories وبعدين هنحل أمثلة متعددة على الـ maximum
+
+524
+00:50:27,170 --> 00:50:30,410
+shear stress theory والـ distortion energy theory
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/0znKCBWOhCg_raw.json b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/0znKCBWOhCg_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..aef533cf5905b0f0626cbed3742d385740f08d41
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/0znKCBWOhCg_raw.json
@@ -0,0 +1 @@
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355.85, "text": "و small d وعندي هنا different cares هذا ال cares بيعطوني", "tokens": [2407, 1359, 274, 4032, 3615, 1863, 16254, 34105, 819, 12310, 23758, 2423, 12310, 4724, 1829, 3615, 9566, 11536, 1829], "avg_logprob": -0.4300781264901161, "compression_ratio": 0.9746835443037974, "no_speech_prob": 0.0, "words": [{"start": 347.45000000000005, "end": 348.29, "word": "و", "probability": 0.8359375}, {"start": 348.29, "end": 349.13, "word": " small", "probability": 0.475341796875}, {"start": 349.13, "end": 349.55, "word": " d", "probability": 0.76611328125}, {"start": 349.55, "end": 351.89, "word": " وعندي", "probability": 0.5843505859375}, {"start": 351.89, "end": 352.05, "word": " هنا", "probability": 0.55908203125}, {"start": 352.05, "end": 352.47, "word": " different", "probability": 0.82275390625}, {"start": 352.47, "end": 352.97, "word": " cares", "probability": 0.275634765625}, {"start": 352.97, "end": 354.49, "word": " هذا", "probability": 0.387939453125}, {"start": 354.49, "end": 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1722.41, "word": " وصلنا", "probability": 0.9659830729166666}, {"start": 1722.41, "end": 1722.57, "word": " لل", "probability": 0.405029296875}, {"start": 1722.57, "end": 1722.93, "word": " failure", "probability": 0.75146484375}], "temperature": 1.0}, {"id": 65, "seek": 174570, "start": 1724.24, "end": 1745.7, "text": "و لسه النظرية بتحكيلي لأ انت وضعك كويس مش failure بتحكي عشان تصير failure ده تصار النقطة هادئ لكن انا في الحقيقة عرض الواقع صار failure معناته النظرية في الرابع الرابع بتخدعني بتعطينيش اشي دقيق وبالتالي it's not safe to use this theory", "tokens": [2407, 5296, 3794, 3224, 28239, 19913, 2288, 10632, 39894, 5016, 4117, 1829, 20292, 5296, 10721, 16472, 2655, 4032, 11242, 3615, 4117, 9122, 45865, 3794, 37893, 7763, 39894, 5016, 4117, 1829, 6225, 8592, 7649, 6055, 9381, 13546, 7763, 11778, 3224, 6055, 9381, 9640, 28239, 47432, 3660, 8032, 18513, 19986, 44381, 1975, 8315, 8978, 21542, 38436, 28671, 6225, 43042, 2423, 14407, 4587, 3615, 20328, 9640, 7763, 20449, 8315, 47395, 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factor of safety بصير tau maximum to avoid failure بالسواء أسواء على اتنين and و and factor of safety", "tokens": [40228, 22653, 2293, 412, 7763, 2293, 412, 7763, 39894, 30544, 17842, 6674, 20666, 3794, 2407, 16606, 5551, 3794, 2407, 16606, 15844, 1975, 2655, 1863, 9957, 11933, 15730, 41850, 3714, 16758, 16254, 8592, 7251, 9381, 13546, 7763, 11933, 15730, 3714, 16758, 16254, 8592, 7251, 9381, 13546, 7763, 4724, 5016, 9566, 5952, 295, 4514, 4724, 9381, 13546, 17842, 6674, 281, 5042, 7763, 20666, 3794, 2407, 16606, 5551, 3794, 2407, 16606, 15844, 1975, 2655, 1863, 9957, 293, 4032, 293, 5952, 295, 4514], "avg_logprob": -0.1996093686670065, "compression_ratio": 1.9759036144578312, "no_speech_prob": 0.0, "words": [{"start": 2023.28, "end": 2023.64, "word": "يعني", "probability": 0.88818359375}, {"start": 2023.64, "end": 2024.32, "word": " exactly", "probability": 0.8330078125}, {"start": 2024.32, "end": 2024.62, "word": " at", "probability": 0.96337890625}, {"start": 2024.62, "end": 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"seek": 228929, "start": 2278.11, "end": 2289.29, "text": "According to maximum scarcity theory بيصير yield again دي او بيصير failure لما tau maximum تكون اكبر او يساوي as y على 2", "tokens": [47943, 3357, 281, 6674, 44181, 5261, 4724, 1829, 9381, 13546, 11257, 797, 11778, 1829, 1975, 2407, 4724, 1829, 9381, 13546, 7763, 5296, 15042, 17842, 6674, 6055, 30544, 1975, 4117, 26890, 1975, 2407, 7251, 3794, 995, 45865, 382, 288, 15844, 568], "avg_logprob": -0.43140242739421564, "compression_ratio": 1.1654135338345866, "no_speech_prob": 0.0, "words": [{"start": 2278.11, "end": 2278.71, "word": "According", "probability": 0.5955810546875}, {"start": 2278.71, "end": 2278.93, "word": " to", "probability": 0.9541015625}, {"start": 2278.93, "end": 2279.27, "word": " maximum", "probability": 0.5927734375}, {"start": 2279.27, "end": 2279.53, "word": " scarcity", "probability": 0.12188720703125}, {"start": 2279.53, "end": 2280.27, "word": " theory", "probability": 0.88916015625}, {"start": 2280.27, 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يعني sigma A ال load line هيكون بالشكل هذا هذه sigma A وهذه sigma B الآن إذا كنا هنا", "tokens": [2407, 3615, 1863, 16254, 34105, 39896, 12771, 363, 21542, 1211, 28671, 16247, 12610, 7578, 12771, 316, 5551, 4117, 26890, 9154, 12771, 363, 5551, 4117, 26890, 9154, 12771, 316, 37495, 22653, 12771, 316, 2423, 3677, 1622, 39896, 30544, 20666, 8592, 28820, 23758, 29538, 12771, 316, 37037, 24192, 12771, 363, 6024, 48506, 11933, 15730, 9122, 8315, 34105], "avg_logprob": -0.3183593787252903, "compression_ratio": 1.6408450704225352, "no_speech_prob": 0.0, "words": [{"start": 2317.44, "end": 2317.94, "word": "وعندي", "probability": 0.6591796875}, {"start": 2317.94, "end": 2318.24, "word": " هنا", "probability": 0.740234375}, {"start": 2318.24, "end": 2318.72, "word": " هي", "probability": 0.34130859375}, {"start": 2318.72, "end": 2319.26, "word": " sigma", "probability": 0.1849365234375}, {"start": 2319.26, "end": 2320.6, "word": " B", "probability": 0.3115234375}, {"start": 2320.6, "end": 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minus SY معناته في الحالة هذه case three", "tokens": [50, 56, 15844, 1975, 2655, 1863, 9957, 1975, 15730, 47525, 7578, 1975, 9566, 46152, 41950, 28480, 9957, 20666, 4386, 20666, 3175, 37495, 22653, 11331, 3794, 1829, 8315, 11778, 1829, 2423, 12771, 4724, 1829, 9381, 13546, 1975, 9381, 17082, 2288, 1975, 2407, 7251, 44510, 2407, 1975, 9381, 17082, 2288, 1975, 2407, 7251, 3794, 995, 45865, 3175, 32624, 20449, 8315, 47395, 8978, 21542, 6027, 3660, 29538, 1389, 1045], "avg_logprob": -0.33115672353488296, "compression_ratio": 1.5, "no_speech_prob": 0.0, "words": [{"start": 2778.28, "end": 2779.32, "word": "SY", "probability": 0.51513671875}, {"start": 2779.32, "end": 2780.36, "word": " على", "probability": 0.396728515625}, {"start": 2780.36, "end": 2781.8, "word": " اتنين", "probability": 0.83001708984375}, {"start": 2781.8, "end": 2782.52, "word": " اذا", "probability": 0.75634765625}, {"start": 2782.52, "end": 2782.74, "word": " بدى", "probability": 0.4691162109375}, {"start": 2782.74, 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2832.06, "end": 2838.42, "text": "ع الحدود أو برا ال part is failing according to maximum shear stress theory", "tokens": [3615, 21542, 3215, 23328, 34051, 4724, 23557, 2423, 644, 307, 18223, 4650, 281, 6674, 24082, 4244, 5261], "avg_logprob": -0.15842014220025805, "compression_ratio": 0.9888888888888889, "no_speech_prob": 0.0, "words": [{"start": 2832.06, "end": 2832.32, "word": "ع", "probability": 0.7939453125}, {"start": 2832.32, "end": 2832.9, "word": " الحدود", "probability": 0.8030598958333334}, {"start": 2832.9, "end": 2833.12, "word": " أو", "probability": 0.6572265625}, {"start": 2833.12, "end": 2833.54, "word": " برا", "probability": 0.9326171875}, {"start": 2833.54, "end": 2834.04, "word": " ال", "probability": 0.67578125}, {"start": 2834.04, "end": 2834.48, "word": " part", "probability": 0.95751953125}, {"start": 2834.48, "end": 2834.96, "word": " is", "probability": 0.9638671875}, {"start": 2834.96, "end": 2835.72, "word": " failing", "probability": 0.93701171875}, 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"end": 2943.12, "text": "we predict failure before the part is actually failed يعني نتوقع الانهيار لل mechanical element قبل ما في الحقيقة انه ايش صارله انهيار او failure هذا يعني ان maximum shear stress theory is a conservative theory يعني", "tokens": [826, 6069, 7763, 949, 264, 644, 307, 767, 7612, 37495, 22653, 8717, 2655, 30543, 3615, 2423, 7649, 3224, 1829, 9640, 24976, 12070, 4478, 12174, 36150, 19446, 8978, 21542, 38436, 28671, 16472, 3224, 1975, 1829, 8592, 20328, 9640, 43761, 16472, 3224, 1829, 9640, 1975, 2407, 7763, 23758, 37495, 22653, 16472, 6674, 24082, 4244, 5261, 307, 257, 13780, 5261, 37495, 22653], "avg_logprob": -0.18463540971279144, "compression_ratio": 1.450777202072539, "no_speech_prob": 1.1920928955078125e-07, "words": [{"start": 2922.5, "end": 2922.72, "word": "we", "probability": 0.55517578125}, {"start": 2922.72, "end": 2923.06, "word": " predict", "probability": 0.890625}, {"start": 2923.06, "end": 2923.48, "word": " failure", "probability": 0.89501953125}, 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risk في الحسابات بتاعتى مافيش عندى risk في الحسابات لأن انا بحكي انه failed و هو في الواقع not failed فمعناته it is conservative طبعا في فرق بين conservative و accurate كل ما بتزيدي الدقة بشكل عام", "tokens": [7649, 995, 39894, 30543, 3615, 2423, 7763, 5296, 3794, 3224, 44381, 8978, 21542, 38436, 28671, 19446, 9381, 9640, 8592, 7763, 20449, 8315, 47395, 1975, 8315, 2423, 3148, 8978, 21542, 3794, 16758, 9307, 39894, 995, 34268, 7578, 19446, 41185, 8592, 43242, 7578, 3148, 8978, 21542, 3794, 16758, 9307, 5296, 33456, 1975, 8315, 4724, 5016, 4117, 1829, 16472, 3224, 7612, 4032, 31439, 8978, 2423, 14407, 4587, 3615, 406, 7612, 6156, 2304, 3615, 8315, 47395, 309, 307, 13780, 23032, 3555, 3615, 995, 8978, 6156, 2288, 4587, 49374, 13780, 4032, 8559, 28242, 19446, 39894, 11622, 25708, 1829, 32748, 28671, 4724, 8592, 28820, 6225, 10943], "avg_logprob": -0.13613861681211112, "compression_ratio": 1.8133333333333332, "no_speech_prob": 0.0, "words": [{"start": 2945.14, "end": 2945.42, "word": 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diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/0znKCBWOhCg_raw.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/0znKCBWOhCg_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..c60e76236551b62468d87a8aafab6e288b43c784
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/0znKCBWOhCg_raw.srt
@@ -0,0 +1,2096 @@
+1
+00:00:05,030 --> 00:00:07,870
+بسم الله الرحمن الرحيم السلام عليكم و رحمة الله و
+
+2
+00:00:07,870 --> 00:00:11,250
+بركاته اليوم هنبدأ بال chapter التالت في ال
+
+3
+00:00:11,250 --> 00:00:15,010
+machine design واحد اللي هو failures resulting
+
+4
+00:00:15,010 --> 00:00:19,670
+from static loading اللي هو الانهيارات او ال .. ال
+
+5
+00:00:19,670 --> 00:00:24,650
+.. ال .. في ال .. في القطع الميكانيكية نتيجة أحمال
+
+6
+00:00:24,650 --> 00:00:29,940
+ثابتةطبعا احنا ب chapter التلاتة و اربعة كان تحضير
+
+7
+00:00:29,940 --> 00:00:34,220
+ل chapter خمسة و chapter ستة، chapter تلاتة غطينا
+
+8
+00:00:34,220 --> 00:00:39,140
+كل حسابات ل stress analysis بكل أنواعها، ال .. ال
+
+9
+00:00:39,140 --> 00:00:45,530
+.. ال .. ال .. ال .. ال ..ال axel direct tensile
+
+10
+00:00:45,530 --> 00:00:49,310
+loading سواء كان tensile accommodation عند ال
+
+11
+00:00:49,310 --> 00:00:53,170
+bending loading عند ال transverse shear loading
+
+12
+00:00:53,170 --> 00:00:58,150
+عند ال torsional loading او any combination
+
+13
+00:00:58,150 --> 00:01:04,530
+between these loading conditions طبعا استخدمنا ال
+
+14
+00:01:04,530 --> 00:01:09,770
+more circle عشان احسب ال principal stresses
+
+15
+00:01:11,570 --> 00:01:15,830
+هذا شبتر تلاتة شبتر اربع غطينا ال deflection
+
+16
+00:01:15,830 --> 00:01:20,690
+calculations استخدمنا اللي هي ال strain energy
+
+17
+00:01:20,690 --> 00:01:24,090
+method و Castellano method to determine
+
+18
+00:01:24,090 --> 00:01:28,590
+deflections at various points on a mechanical
+
+19
+00:01:28,590 --> 00:01:31,930
+element اليوم هنكمل شبتر خمسة هنحكي عن failures
+
+20
+00:01:31,930 --> 00:01:35,430
+resulting from static loading هنحكي عن مجموعة من
+
+21
+00:01:35,430 --> 00:01:39,970
+النظريات المستخدمة في ال static loadingمنها ال
+
+22
+00:01:39,970 --> 00:01:41,930
+maximum normal stress theory و ال maximum shear
+
+23
+00:01:41,930 --> 00:01:45,070
+stress theory و ال maximum distortion energy
+
+24
+00:01:45,070 --> 00:01:48,450
+theory و ال columnar theory و ال modified columnar
+
+25
+00:01:48,450 --> 00:01:56,230
+theoryفي الأول هنعمل مراجعة على الحسابات ال stress
+
+26
+00:01:56,230 --> 00:01:59,950
+concentration due to sudden change in the cross
+
+27
+00:01:59,950 --> 00:02:02,410
+-sectional area طبعا sudden change في ال cross
+
+28
+00:02:02,410 --> 00:02:06,390
+-sectional area ممكن يكون due to different aspects
+
+29
+00:02:06,390 --> 00:02:10,570
+ممكن يكون في عندى ثقب او يكون عندى fillet طبعا
+
+30
+00:02:10,570 --> 00:02:15,350
+appendix A15 و A16 بيرجوني بيعطوني اللي هو
+
+31
+00:02:15,350 --> 00:02:18,350
+theoretical stress concentration factorsfor
+
+32
+00:02:18,350 --> 00:02:20,710
+different geometries and different loading
+
+33
+00:02:20,710 --> 00:02:26,350
+conditions على سبيل المثال figure a 15 1 في الكتاب
+
+34
+00:02:26,350 --> 00:02:32,410
+شجلي مبين ليه عند بار intention المقطع بتاعه
+
+35
+00:02:32,410 --> 00:02:38,290
+مستطيل وفيه ثقب في النص قطل الثقب دي small عرض
+
+36
+00:02:38,290 --> 00:02:44,170
+القطع w و البعد التالت لها T و under axial loading
+
+37
+00:02:44,170 --> 00:02:47,270
+على المحور الأفقي يكون عندي D على W
+
+38
+00:02:52,020 --> 00:03:01,240
+وهنا دي بيكون الكتي و ال nominal stress sigma o
+
+39
+00:03:01,240 --> 00:03:12,400
+بسوة F على A و ال A بالساوية اللي هي W minus D في
+
+40
+00:03:12,400 --> 00:03:18,720
+T W هي القطة هي
+
+41
+00:03:18,720 --> 00:03:19,580
+ال force F
+
+42
+00:03:22,970 --> 00:03:28,510
+هذا W هذا
+
+43
+00:03:28,510 --> 00:03:33,310
+D و
+
+44
+00:03:33,310 --> 00:03:37,270
+البعد التالت اللي
+
+45
+00:03:37,270 --> 00:03:40,930
+هو T
+
+46
+00:03:40,930 --> 00:03:47,190
+فانا بحسب بحسب ال net area اللي أخدت مقطع هنا
+
+47
+00:03:47,190 --> 00:03:50,450
+هيكون
+
+48
+00:03:50,450 --> 00:03:51,410
+عندى شكل المقطع
+
+49
+00:03:54,140 --> 00:04:07,060
+بالشكل هذا هاد
+
+50
+00:04:07,060 --> 00:04:14,360
+ال D هاد ال W هاد
+
+51
+00:04:14,360 --> 00:04:21,190
+ال H Tمن حد واضح ال net area هي ال area المضلة ده
+
+52
+00:04:21,190 --> 00:04:28,210
+هتكون اللي هو العرض في الارتفاع الارض دي W ناقص D
+
+53
+00:04:28,210 --> 00:04:32,210
+في T و
+
+54
+00:04:32,210 --> 00:04:36,670
+ال stress عند الثقب و لا عند ال hole sigma maximum
+
+55
+00:04:36,670 --> 00:04:43,090
+هيكون الساوية KT في Sigma
+
+56
+00:04:45,810 --> 00:04:50,550
+هذا one example another example في ال appendix
+
+57
+00:04:50,550 --> 00:04:53,890
+A159
+
+58
+00:04:53,890 --> 00:05:02,530
+في الكتاب فى مبين عندى mechanical element مقطع
+
+59
+00:05:02,530 --> 00:05:06,070
+مدور فى تغييف ال cross section من D small ل D
+
+60
+00:05:06,070 --> 00:05:06,610
+capital
+
+61
+00:05:16,620 --> 00:05:21,180
+و فيه بتأثير على ال bending moment بتأثير على ال
+
+62
+00:05:21,180 --> 00:05:25,280
+bending moment M و
+
+63
+00:05:25,280 --> 00:05:29,960
+فيه اندي fillet هنا ال
+
+64
+00:05:29,960 --> 00:05:35,400
+radius بتاعها R عشان احسب ال stress concentration
+
+65
+00:05:35,400 --> 00:05:40,420
+عند النقطة هذه بالزي
+
+66
+00:05:40,420 --> 00:05:44,360
+من ال two parameters اللي هو ال ratio بين ال
+
+67
+00:05:44,360 --> 00:05:52,970
+fillet radiusو small d وعندي هنا different cares
+
+68
+00:05:52,970 --> 00:05:55,850
+هذا ال cares بيعطوني
+
+69
+00:06:01,630 --> 00:06:08,130
+different D capital على D small يعني لو كنت أعرف D
+
+70
+00:06:08,130 --> 00:06:11,370
+capital على D small بختار كيرن الكيرفات هذه و أعرف
+
+71
+00:06:11,370 --> 00:06:14,830
+R على D مثلا لو كان D capital على D small بيستوى
+
+72
+00:06:14,830 --> 00:06:18,870
+تلاتة بحسب ال stress concentration KT بيطلع بيستوى
+
+73
+00:06:18,870 --> 00:06:25,570
+one point eight و ال sigma O في الحالة هذهبتساوي
+
+74
+00:06:25,570 --> 00:06:34,050
+طبعا هنا عند ال pure bending case sigma o بيساوي
+
+75
+00:06:34,050 --> 00:06:43,190
+M في C على I و C بيساوي D على 2 و I بيساوي Pi على
+
+76
+00:06:43,190 --> 00:06:53,770
+64 D اص 4 بتصفي sigma o بيساوي M
+
+77
+00:06:55,710 --> 00:07:08,290
+أتنين و تلاتين ام على باي دي تكيب والسيجما maximum
+
+78
+00:07:08,290 --> 00:07:16,850
+a due to stress concentration بساوي KT في السيجما
+
+79
+00:07:25,770 --> 00:07:28,370
+الان احنا هناخد في الاعتبار ال stress
+
+80
+00:07:28,370 --> 00:07:35,510
+concentration في حالتين حالة انه ال material بتاعة
+
+81
+00:07:35,510 --> 00:07:39,710
+ال mechanical element تكون ductile و الحالة
+
+82
+00:07:39,710 --> 00:07:41,650
+التانية ان ال material بتاعة ال mechanical element
+
+83
+00:07:41,650 --> 00:07:46,010
+تكون brittle الآن لو أخدنا الحالة هذه
+
+84
+00:08:05,270 --> 00:08:10,590
+هذه الـ shaft هذه
+
+85
+00:08:10,590 --> 00:08:15,110
+المحورة للـ shaft عندى
+
+86
+00:08:15,110 --> 00:08:25,010
+fillet هنا ر عند القطر هنا دي small عند
+
+87
+00:08:25,010 --> 00:08:25,930
+هذه دي capital
+
+88
+00:08:36,440 --> 00:08:38,920
+طبعا واضح انه فيه تغيير في ال cross section من D
+
+89
+00:08:38,920 --> 00:08:41,600
+small ل D capital وفيه عندى fillet radius R معناه
+
+90
+00:08:41,600 --> 00:08:45,580
+وفيه عندى stress concentration نفترض ان انا under
+
+91
+00:08:45,580 --> 00:08:54,740
+bending M و M due
+
+92
+00:08:54,740 --> 00:09:00,600
+to bending هسير فى المنطقة هى دى ال stress
+
+93
+00:09:00,600 --> 00:09:04,440
+distribution هيكون بالشكل هى ده
+
+94
+00:09:12,570 --> 00:09:17,350
+تحت هكون عندى tension و
+
+95
+00:09:17,350 --> 00:09:22,910
+هين هكون عندى compression
+
+96
+00:09:22,910 --> 00:09:31,230
+هين compression normal stress و tension normal
+
+97
+00:09:31,230 --> 00:09:36,430
+stress يعني لو أخدنا fiber هين if you take if you
+
+98
+00:09:36,430 --> 00:09:39,170
+take a fiber
+
+99
+00:09:42,980 --> 00:09:48,840
+الان لو ال moment وصلت لحد انه صار عندي هنا ال due
+
+100
+00:09:48,840 --> 00:09:50,720
+to stress كنت راشي انا sigma max
+
+101
+00:09:54,580 --> 00:09:59,420
+بسواكتي في sigma o ممكن ال sigma o does not reach
+
+102
+00:09:59,420 --> 00:10:03,560
+ال yielding لكن انا في الآخر هحس بال sigma maximum
+
+103
+00:10:03,560 --> 00:10:06,900
+ال local stress عند النقطة هذه sigma maximum
+
+104
+00:10:06,900 --> 00:10:11,380
+سواكتي في sigma o ممكن ال stress هين ادخل في ال ..
+
+105
+00:10:11,380 --> 00:10:14,140
+في ال plastic region يعني هسير عندي plastic
+
+106
+00:10:14,140 --> 00:10:20,380
+deformation يعني هسير yielding المنطقة هذه الطبقة
+
+107
+00:10:20,380 --> 00:10:26,590
+هذه و ال yieldالمادة ductile يعني مادة ايش طرية
+
+108
+00:10:26,590 --> 00:10:31,310
+due to yielding بيصيرها strain hardening او cold
+
+109
+00:10:31,310 --> 00:10:33,930
+work يعني ال strength بتاعتها بيزيد due to
+
+110
+00:10:33,930 --> 00:10:38,630
+yielding الان ال load هينتقل لل layer اللي بعدها
+
+111
+00:10:38,630 --> 00:10:43,230
+هينتقل لل layer .. للطبقة اللي بعدها وها كذا نتيجة
+
+112
+00:10:43,230 --> 00:10:47,930
+ان المادة مرنة تموت معاه فبيصير عنده
+
+113
+00:10:51,610 --> 00:10:56,550
+ال .. ال load is shared with other fibers معناته
+
+114
+00:10:56,550 --> 00:11:01,490
+ال .. ال .. ال material في الآخر بتريح .. بتريح
+
+115
+00:11:01,490 --> 00:11:06,810
+وبالتالي ال effect بتاع ال .. ال .. ال effect بتاع
+
+116
+00:11:06,810 --> 00:11:11,450
+ال stress concentration due to the fillet او due
+
+117
+00:11:11,450 --> 00:11:14,590
+to .. to change in cross section from D small to D
+
+118
+00:11:14,590 --> 00:11:15,350
+capital
+
+119
+00:11:18,000 --> 00:11:23,760
+تقريبا بتوزع على كل ال section نتيجة انه ال
+
+120
+00:11:23,760 --> 00:11:28,320
+yielding او ال load is shared among all the layers
+
+121
+00:11:28,320 --> 00:11:34,800
+of the body due to its ductility في الحالة هذه
+
+122
+00:11:34,800 --> 00:11:40,580
+stress concentration في حالة stress concentration
+
+123
+00:11:40,580 --> 00:11:48,770
+في حالة mechanical element thatis ductile and that
+
+124
+00:11:48,770 --> 00:11:54,070
+is under static loading بالحالة هذه بنهمل ال
+
+125
+00:11:54,070 --> 00:11:56,510
+effect بتاع ال stress concentration معناته إذا
+
+126
+00:11:56,510 --> 00:11:58,550
+كانت ال material بتاعة ال mechanical element
+
+127
+00:11:58,550 --> 00:12:03,530
+ductile وكان ال loading static بهمل ال stress
+
+128
+00:12:03,530 --> 00:12:10,170
+concentration effect هذا في حالة ductile material
+
+129
+00:12:15,210 --> 00:12:20,430
+لكن في حالة المادة كانت دكتايل و ال loading is not
+
+130
+00:12:20,430 --> 00:12:24,010
+static يعني ال loading is dynamic، dynamic loading
+
+131
+00:12:24,010 --> 00:12:28,330
+يعني ال loading مش ثابت، ال loading بتغير، في
+
+132
+00:12:28,330 --> 00:12:32,930
+الحالة هذه فش إمكانية أهمل ال stress
+
+133
+00:12:32,930 --> 00:12:35,230
+concentration، you have to take care of stress
+
+134
+00:12:35,230 --> 00:12:38,790
+concentration for a mechanical element that is
+
+135
+00:12:38,790 --> 00:12:43,210
+ductile and that is under dynamic loadingفي حالة
+
+136
+00:12:43,210 --> 00:12:48,470
+ال material كانت brittle I have to consider ال
+
+137
+00:12:48,470 --> 00:12:52,570
+stress concentration بغض النظر لو المادة كانت
+
+138
+00:12:52,570 --> 00:13:00,290
+ductile او brittleلأن ال material brittle قاسة جدا
+
+139
+00:13:00,290 --> 00:13:03,650
+ما بيصيرش عملية ال sharing between different
+
+140
+00:13:03,650 --> 00:13:05,870
+layers of the material يعني ال material النقطة
+
+141
+00:13:05,870 --> 00:13:08,950
+اللي صار فيها localized stress concentration او
+
+142
+00:13:08,950 --> 00:13:13,270
+localized plastic deformation فهي بتشيل كل ال
+
+143
+00:13:13,270 --> 00:13:18,550
+loading and it does not shareor it does not
+
+144
+00:13:18,550 --> 00:13:20,770
+distribute .. the load is not distributed among
+
+145
+00:13:20,770 --> 00:13:25,150
+other layers وبالتالي انا ممكن اصل ال ultimate
+
+146
+00:13:25,150 --> 00:13:29,950
+tensile strength او عند النقطة هذه ويصير عندي
+
+147
+00:13:29,950 --> 00:13:33,390
+sudden failure وبالتالي ال stress concentration
+
+148
+00:13:33,390 --> 00:13:36,930
+effect must be included for a brittle material
+
+149
+00:13:36,930 --> 00:13:45,210
+whether the loading is static or dynamic طيب
+
+150
+00:13:59,340 --> 00:14:03,520
+لما كان هنا uniaxial stress element uniaxial يعني
+
+151
+00:14:03,520 --> 00:14:09,440
+هاي stress element وهي
+
+152
+00:14:09,440 --> 00:14:15,980
+عليه force sigma هاي sigma لو رصدت ال stress
+
+153
+00:14:15,980 --> 00:14:21,080
+strain curve لهذا ال element هيكون بشكل هذا تقريبا
+
+154
+00:14:21,080 --> 00:14:26,100
+هذا strain هذا sigma وكنا نحسب
+
+155
+00:14:30,590 --> 00:14:37,390
+هذا point to strength percent و هذا كان sigma
+
+156
+00:14:37,390 --> 00:14:44,930
+yield و هذا sigma او
+
+157
+00:14:44,930 --> 00:14:49,970
+S yield ال yield strength و ال ultimate strength S
+
+158
+00:14:49,970 --> 00:15:00,390
+yield و S ultimate لو حكينا هذا هو ال actualstate
+
+159
+00:15:00,390 --> 00:15:04,370
+of stress هذه ال sigma كنا نحصل factor of safety n
+
+160
+00:15:04,370 --> 00:15:12,490
+بصوة ال strength على sigma هذا في حالة uniaxial
+
+161
+00:15:12,490 --> 00:15:17,650
+stress element لكن
+
+162
+00:15:17,650 --> 00:15:23,140
+على أرض الواقعمش بالضرورة أو في أعظم الأحيان
+
+163
+00:15:23,140 --> 00:15:27,340
+بيكونش ال state of stress يعني أكسل في معظم
+
+164
+00:15:27,340 --> 00:15:30,640
+الأحيان بتكون ال stress of stress is
+
+165
+00:15:30,640 --> 00:15:35,740
+multidimensional يعني ممكن كنت لو اتطلع على ال 3D
+
+166
+00:15:35,740 --> 00:15:40,560
+stress element عندى هنا sigma x sigma y sigma z
+
+167
+00:15:40,560 --> 00:15:45,940
+tau xy tau xz tau yz يعني في عندى كل أنواع ال
+
+168
+00:15:45,940 --> 00:15:48,100
+loading conditions موجودة
+
+169
+00:15:50,110 --> 00:15:55,230
+السؤال how to compare .. how to compare this state
+
+170
+00:15:55,230 --> 00:15:59,150
+of stress with a single strength لأن في الأخر ..
+
+171
+00:15:59,150 --> 00:16:02,310
+النهاية .. في النهاية ال material لها strength
+
+172
+00:16:02,310 --> 00:16:07,010
+واحدة ال material كمaterial لها strength واحدة لكن
+
+173
+00:16:07,010 --> 00:16:11,550
+ال .. ال .. ال element ممكن يكون بتعرض ل
+
+174
+00:16:11,550 --> 00:16:18,190
+multistate of stress معناته
+
+175
+00:16:18,190 --> 00:16:25,590
+انا عنديone strength one strength عندي multiple
+
+176
+00:16:25,590 --> 00:16:30,110
+state of stress يعني انا عندي معضلة كيف بده ا ..
+
+177
+00:16:30,110 --> 00:16:34,450
+بده اقارن one strength and multiple stress هذا
+
+178
+00:16:34,450 --> 00:16:41,430
+سؤال نسأله محتاجين لإجابة عليه how to compare one
+
+179
+00:16:41,430 --> 00:16:43,730
+strength of the material of the mechanical element
+
+180
+00:16:43,730 --> 00:16:46,050
+with a multiple state of stress
+
+181
+00:16:50,020 --> 00:16:54,740
+الإجابة بتيجي من انه عشان هيك احنا نحتاج ل static
+
+182
+00:16:54,740 --> 00:16:59,480
+failure theory ال failure theory بتقترح علينا
+
+183
+00:16:59,480 --> 00:17:06,020
+appropriate means طريقة للمقارنة بين multi axial
+
+184
+00:17:06,020 --> 00:17:11,040
+state of stress to single strength معناته ال
+
+185
+00:17:11,040 --> 00:17:16,820
+design theories او ال failure theories proposean
+
+186
+00:17:16,820 --> 00:17:20,080
+appropriate means appropriate means to compare
+
+187
+00:17:20,080 --> 00:17:25,980
+multi axial state of stress to a single strength
+
+188
+00:17:25,980 --> 00:17:33,280
+هذا اللي بيجيب على السؤال تبعنا الان ملخص ال
+
+189
+00:17:33,280 --> 00:17:38,820
+chapter تاني اللي حتى اللي كنا تحضير هذا flow
+
+190
+00:17:38,820 --> 00:17:47,610
+diagram ل design for static loading هنمشي عليهأول
+
+191
+00:17:47,610 --> 00:17:51,910
+شي لازم أعرف أنا ال material is ductile or brittle
+
+192
+00:17:51,910 --> 00:18:00,610
+فين فين دي I question I check أبسلون F من stress
+
+193
+00:18:00,610 --> 00:18:01,650
+strain curve
+
+194
+00:18:06,950 --> 00:18:12,190
+أبسلون F هو ال strain at failure يعني أنا بضلني
+
+195
+00:18:12,190 --> 00:18:16,110
+أشد أشد element بيصير فيه deformation لحد الكسر
+
+196
+00:18:16,110 --> 00:18:21,390
+معناته أبسلون F is representative of the ductility
+
+197
+00:18:21,390 --> 00:18:23,750
+of the material إذا كانت أبسلون F كبيرة كتير
+
+198
+00:18:23,750 --> 00:18:27,510
+معناته ال material is ductile إذا أبسلون F صغيرة
+
+199
+00:18:27,510 --> 00:18:34,130
+معناته ال material is brittleالان كبيرة كتير او
+
+200
+00:18:34,130 --> 00:18:37,910
+صغيرة كتير هذا اشي نسبي معناته I have to define
+
+201
+00:18:37,910 --> 00:18:46,170
+some border line اذا كانت F أكبر او يساوي point أو
+
+202
+00:18:46,170 --> 00:18:55,910
+خمسة معناته ال material is ductile اذا
+
+203
+00:18:55,910 --> 00:18:58,830
+كانت أقل من point أو خمسة معناته ال material is
+
+204
+00:18:58,830 --> 00:18:59,270
+brittle
+
+205
+00:19:10,220 --> 00:19:13,580
+معناته إذا ال material is ductile ال flow chart
+
+206
+00:19:13,580 --> 00:19:17,280
+بروح على جهة اليمين إذا كانت brittle بروح على
+
+207
+00:19:17,280 --> 00:19:25,240
+الجهة الشمالة الآن في الجهة دي احنا حكينا we are
+
+208
+00:19:25,240 --> 00:19:29,940
+dealing with a ductile material او انا في عندى
+
+209
+00:19:29,940 --> 00:19:33,420
+cheeks تانية في فحوصات تانية بدي أشوف هل ال yield
+
+210
+00:19:33,420 --> 00:19:36,980
+strength in tension بتساوي ال yield strength in
+
+211
+00:19:36,980 --> 00:19:42,110
+compression بدي أفحص أشوفهل ال yield strength in
+
+212
+00:19:42,110 --> 00:19:46,970
+tension بيستوي ال yield strength in compression طب
+
+213
+00:19:46,970 --> 00:19:54,510
+يا اما هتسويها او مش هتسويها yes او no اذا كانت ال
+
+214
+00:19:54,510 --> 00:19:58,470
+yield strength in tension بتستوي ال yield strength
+
+215
+00:19:58,470 --> 00:20:03,310
+in compression بدى اقرر هل انا بدي conservative
+
+216
+00:20:03,310 --> 00:20:09,450
+results يعني قيم و حسابات محافظة ولا accurate
+
+217
+00:20:09,450 --> 00:20:14,790
+resultsفانا بسأل نفسي do I need conservative
+
+218
+00:20:14,790 --> 00:20:18,670
+results؟
+
+219
+00:20:18,670 --> 00:20:23,450
+يعني أنا عنصر ال conservative يعني عنصر المخاطرة
+
+220
+00:20:23,450 --> 00:20:29,250
+في حساباتي بيكون أقل if I need more conservative
+
+221
+00:20:29,250 --> 00:20:37,530
+results ممكن استخدم ما يسمى ال maximum shear
+
+222
+00:20:37,530 --> 00:20:44,240
+stress theoryif I need more accurate results which
+
+223
+00:20:44,240 --> 00:20:48,680
+is less conservative كل ما بزيد عندي الدقة كل ما
+
+224
+00:20:48,680 --> 00:20:52,980
+أنصر مخاطرة بزيد عندي if I need more accurate
+
+225
+00:20:52,980 --> 00:20:57,480
+results less conservative results بستخدم في الحالة
+
+226
+00:20:57,480 --> 00:21:03,000
+هذه ال distortion energy theory اللي هنجيها بعدين
+
+227
+00:21:05,150 --> 00:21:08,390
+أنا في ال .. أنا جوابت على السؤال الحالة هذه إذا
+
+228
+00:21:08,390 --> 00:21:10,850
+أسوء ال .. ال yield strength in tension بالسواء
+
+229
+00:21:10,850 --> 00:21:14,170
+yield strength in compression بدي أشوف إذا انا بدي
+
+230
+00:21:14,170 --> 00:21:18,510
+conservative results يعني ال risk أقل بستخدم
+
+231
+00:21:18,510 --> 00:21:21,470
+maximum share stress theory إذا بدي more accurate
+
+232
+00:21:21,470 --> 00:21:27,450
+results ال risk أكتر بستخدم storage energy theory
+
+233
+00:21:28,420 --> 00:21:31,800
+في حالة كانت الـ lead strength in tension بتسويش
+
+234
+00:21:31,800 --> 00:21:35,320
+lead strength in compression بستخدم ما يسمى الـ
+
+235
+00:21:35,320 --> 00:21:39,180
+Ductile Coulomb-Moore Theory Ductile Coulomb-Moore
+
+236
+00:21:39,180 --> 00:21:42,840
+Theory اللي هي معادلة 5.26 في الكتابة
+
+237
+00:21:47,980 --> 00:21:51,200
+أنا في الحلقة دي علجت اللي هو حالة ductile
+
+238
+00:21:51,200 --> 00:21:56,200
+materials إذا كانت ال material brittle يعني F أقل
+
+239
+00:21:56,200 --> 00:22:02,220
+من point O5 بدي أقرر if I need conservative
+
+240
+00:22:02,220 --> 00:22:03,040
+results
+
+241
+00:22:08,380 --> 00:22:11,120
+يعني إذا بدي conservative results يعني المعنصر
+
+242
+00:22:11,120 --> 00:22:14,000
+المخاطر في الحسابات تكون أقل بروح على الجهة اليمين
+
+243
+00:22:14,000 --> 00:22:18,760
+إذا بدي more accurate less conservative يعني دقة
+
+244
+00:22:18,760 --> 00:22:22,680
+أعلى مع مخاطرة أكتر في الحسابات بروح على الجهة
+
+245
+00:22:22,680 --> 00:22:26,000
+الشمال بنتقل if I need conservative results بستخدم
+
+246
+00:22:26,000 --> 00:22:30,240
+ال brittle column more theory ال brittle column
+
+247
+00:22:30,240 --> 00:22:36,600
+more theoryإذا بدي انا more accurate results less
+
+248
+00:22:36,600 --> 00:22:43,980
+conservative بستخدم ال modified more theory هذه
+
+249
+00:22:43,980 --> 00:22:48,260
+خارطة الطريق لكل شبطر هذه خارطة الطريق لكل شبطر
+
+250
+00:22:49,500 --> 00:22:54,060
+الكتاب عرضها في آخر ال chapter انا شايف احسن انه
+
+251
+00:22:54,060 --> 00:22:56,740
+عرضها في بداية ال chapter و آخر ال chapter هعرض
+
+252
+00:22:56,740 --> 00:23:00,700
+نفس الخارطة هذه عشان نرجع الشغل اللي اشتغلناه طبعا
+
+253
+00:23:00,700 --> 00:23:04,840
+انا هنا عرضت flow chart هذا كل ال chapter هكون ..
+
+254
+00:23:04,840 --> 00:23:08,020
+هنحكي على اللي هو ال maximum shear stress theory
+
+255
+00:23:08,020 --> 00:23:10,120
+ال distortion inequality theory ال ductile column
+
+256
+00:23:10,120 --> 00:23:12,140
+wall theory ال brittle column wall theory و ال
+
+257
+00:23:12,140 --> 00:23:15,100
+modified wall theory هذه كلها هتتغطى في هذا ال
+
+258
+00:23:15,100 --> 00:23:15,360
+chapter
+
+259
+00:23:19,860 --> 00:23:26,220
+نبدأ في ال theories المستخدمة في static loading
+
+260
+00:23:26,220 --> 00:23:36,300
+design اول
+
+261
+00:23:36,300 --> 00:23:40,340
+theory هي maximum normal stress theory هنموذجها
+
+262
+00:23:40,340 --> 00:23:44,860
+برمز MNS maximum normal stress theory ال maximum
+
+263
+00:23:44,860 --> 00:23:48,440
+normal stress theory بتحكي التالي بتحكي انهالـ
+
+264
+00:23:48,440 --> 00:23:51,860
+yielding begins يعني ببدأ ال mechanical element
+
+265
+00:23:51,860 --> 00:23:57,920
+يدخل ل plastic range when لما ال maximum principle
+
+266
+00:23:57,920 --> 00:24:02,000
+stress in a stress element exceeds the yield
+
+267
+00:24:02,000 --> 00:24:08,860
+strength ببدأ يصير yielding لما ال maximum
+
+268
+00:24:08,860 --> 00:24:14,660
+principle stress in a stress elementبتخطأ ال yield
+
+269
+00:24:14,660 --> 00:24:18,500
+strength ال material في الحالة هذه بحكي ان ال part
+
+270
+00:24:18,500 --> 00:24:24,020
+is .. ال part fails part fails بيصير فيلر ال part
+
+271
+00:24:24,020 --> 00:24:27,140
+معناته according to maximum normal stress theory
+
+272
+00:24:27,140 --> 00:24:31,260
+ال yielding بيبدأ لما ال maximum principle stress
+
+273
+00:24:31,260 --> 00:24:35,960
+in a stress element بتخطأ ال yield strength of the
+
+274
+00:24:35,960 --> 00:24:41,220
+materialطبعا انا بستخدم في chapter تلاتة استخدمنا
+
+275
+00:24:41,220 --> 00:24:44,360
+ال column الاستخدامنا more circle to find the
+
+276
+00:24:44,360 --> 00:24:47,700
+principal series اذا كنا نحسب sigma واحد و sigma
+
+277
+00:24:47,700 --> 00:24:51,920
+اتنين و sigma تلاتة كنا نرتبهم بحيث يكون sigma
+
+278
+00:24:51,920 --> 00:24:58,480
+واحد اكبر من sigma اتنين اكبر من sigma تلاتة
+
+279
+00:24:58,480 --> 00:25:07,470
+معناته sigma واحدإذا كان سجن واحد أكبر أو يساوي
+
+280
+00:25:07,470 --> 00:25:12,870
+الأسوار في حالة الـ Ductile Material بيصير MDH
+
+281
+00:25:12,870 --> 00:25:14,150
+فاليار
+
+282
+00:25:21,040 --> 00:25:24,440
+هذه هي ال principle أو ال maximum normal stress
+
+283
+00:25:24,440 --> 00:25:27,860
+theory بتحكي بيصير yielding لما ال maximum
+
+284
+00:25:27,860 --> 00:25:32,960
+principle stress في mechanical element بيكون أكبر
+
+285
+00:25:32,960 --> 00:25:35,780
+أو يساوي lead strength of that mechanical element
+
+286
+00:25:35,780 --> 00:25:39,580
+في الحالة هذه بيصير عندي إيه؟ failure otherwise
+
+287
+00:25:39,580 --> 00:25:45,700
+مافيش failure عندنا يعني
+
+288
+00:25:45,700 --> 00:25:47,680
+لو أخدنا ال two-D state of stress
+
+289
+00:25:51,200 --> 00:26:00,260
+سيكون عندي سيجما واحد و هي سيجما اتنين سيجما واحد
+
+290
+00:26:00,260 --> 00:26:05,320
+اللي هي ال first principle stress و سيجما اتنين هي
+
+291
+00:26:05,320 --> 00:26:10,020
+second principle stress إذا قسمت سيجما واحد على SY
+
+292
+00:26:10,020 --> 00:26:14,620
+و هي سيجما اتنين على SY
+
+293
+00:26:18,860 --> 00:26:23,020
+يعني إذا كان ال sigma 1 على SY يعني إذا كان sigma
+
+294
+00:26:23,020 --> 00:26:27,860
+1 بيساوي SY يعني sigma 1 على SY بيساوي إيش؟ واحد
+
+295
+00:26:27,860 --> 00:26:32,520
+إذا
+
+296
+00:26:32,520 --> 00:26:40,200
+كان sigma 1 على SY أكبر أو يساوي واحد بيصير عندي
+
+297
+00:26:40,200 --> 00:26:45,240
+إيش؟ failure يعني إذا كنت في هذا الاتجاه من هذا
+
+298
+00:26:45,240 --> 00:26:48,140
+النقطة وامشي بيصير عندي
+
+299
+00:26:57,390 --> 00:27:06,770
+failure طبعا هذا يمثل ال
+
+300
+00:27:06,770 --> 00:27:14,770
+failure contour لل
+
+301
+00:27:14,770 --> 00:27:15,790
+mechanical element
+
+302
+00:27:32,700 --> 00:27:37,300
+جوا المستطيل no
+
+303
+00:27:37,300 --> 00:27:42,940
+failure برا
+
+304
+00:27:42,940 --> 00:27:48,570
+المستطيلفي failure يعني هنا .. هنا برا failure جوا
+
+305
+00:27:48,570 --> 00:27:52,850
+safe انبيني هنا experimental data experimental
+
+306
+00:27:52,850 --> 00:27:57,850
+data عشان أشوف هل النظرية بتحقق الاشياء يعني
+
+307
+00:27:57,850 --> 00:28:03,010
+متوافقة مع الواقع ولا لأ لأن انبيني عندي في المربع
+
+308
+00:28:03,010 --> 00:28:05,990
+الأول إذا كان سجم واحد موجبة أو سجم اتنين موجبة
+
+309
+00:28:05,990 --> 00:28:11,790
+بيكون ال .. ال experimental data يعني ممكن اعتبرها
+
+310
+00:28:11,790 --> 00:28:21,270
+fits ال theoryبشكل دقيق وبشكل كافي لكن في الربيع
+
+311
+00:28:21,270 --> 00:28:25,030
+الرابع اذا كان sigma 1 موجبة و sigma 2 سالبة
+
+312
+00:28:25,030 --> 00:28:28,810
+لاحظوا
+
+313
+00:28:28,810 --> 00:28:35,890
+انه في الحقيقة لو حكينا هذا هو ال load line في
+
+314
+00:28:35,890 --> 00:28:44,480
+الحقيقة we reach failure احنا وصلنا لل failureو
+
+315
+00:28:44,480 --> 00:28:47,960
+لسه النظرية بتحكيلي لأ انت وضعك كويس مش failure
+
+316
+00:28:47,960 --> 00:28:52,500
+بتحكي عشان تصير failure ده تصار النقطة هادئ لكن
+
+317
+00:28:52,500 --> 00:28:55,840
+انا في الحقيقة عرض الواقع صار failure معناته
+
+318
+00:28:55,840 --> 00:29:00,060
+النظرية في الرابع الرابع بتخدعني بتعطينيش اشي دقيق
+
+319
+00:29:00,060 --> 00:29:07,430
+وبالتالي it's not safe to use this theoryfor
+
+320
+00:29:07,430 --> 00:29:11,830
+ductile material لسبب بسيط لأنه it does not fit او
+
+321
+00:29:11,830 --> 00:29:14,870
+it does not predict the experimental case
+
+322
+00:29:14,870 --> 00:29:20,130
+experimental case بتحكي ان انا بصير failure while
+
+323
+00:29:20,130 --> 00:29:25,070
+the maximum stress theory says that it is safe
+
+324
+00:29:25,070 --> 00:29:31,290
+failures does not reach yet it is reach yet في
+
+325
+00:29:31,290 --> 00:29:35,850
+الحقيقة لكن طبق النظرية لأ موصلناش لأن ذلك معناته
+
+326
+00:29:35,850 --> 00:29:45,450
+انا باخدنتائج او بحكي نتائج خادعة فمعناته يعني
+
+327
+00:29:45,450 --> 00:29:50,110
+صارت النظرية بس استيراد تاريخي مش هنستخدمه في
+
+328
+00:29:50,110 --> 00:29:54,290
+الحسابات بتاعتنا النظرية
+
+329
+00:29:54,290 --> 00:30:02,530
+التانيةاللي هي ال maximum shear stress theory ال
+
+330
+00:30:02,530 --> 00:30:07,150
+maximum
+
+331
+00:30:07,150 --> 00:30:12,630
+shear stress theory بتحكي التالي بيبدأ
+
+332
+00:30:12,630 --> 00:30:16,270
+ال material تدخل ال plastic range تبدأش تمغط معاه
+
+333
+00:30:16,270 --> 00:30:22,990
+لما ال maximum shear stress in a stress element
+
+334
+00:30:24,390 --> 00:30:28,950
+بيكون أكبر أو يساوي ال maximum shear stress in a
+
+335
+00:30:28,950 --> 00:30:32,450
+tensile test specimen اللي له نفس المادة بتاعة ال
+
+336
+00:30:32,450 --> 00:30:37,090
+mechanical element المعنى عشان maximum shear
+
+337
+00:30:37,090 --> 00:30:40,830
+stress يبتحك التالي يبتحك بيصير failure أو يصير
+
+338
+00:30:40,830 --> 00:30:45,310
+yielding أو المادة بتدخل في ال plastic rangeلما ال
+
+339
+00:30:45,310 --> 00:30:50,510
+maximum shear stress في ال actual element بتخطى،
+
+340
+00:30:50,510 --> 00:30:54,730
+بتكون أكبر أو يساوي ال maximum shear stress in a
+
+341
+00:30:54,730 --> 00:30:57,690
+tensile test specimen، ال tensile test specimen
+
+342
+00:30:57,690 --> 00:31:05,810
+بيكون متعرض ل axial loading، sigma و sigma، لو ادي
+
+343
+00:31:05,810 --> 00:31:07,470
+ارسم ال more circle له
+
+344
+00:31:13,220 --> 00:31:23,640
+سيكون بالشكل هذا مار سيركل هذا سجن واحد وهذا زرن
+
+345
+00:31:23,640 --> 00:31:30,600
+سجن اتنين وهذا تاو ماكسيمم الفشل سجن واحد سيكون
+
+346
+00:31:30,600 --> 00:31:38,980
+اسواء اسواء معناته تاو ماكسيمم سيكون اسواء اسواء
+
+347
+00:31:40,220 --> 00:31:46,980
+على اتنين in a tensile test
+
+348
+00:31:46,980 --> 00:31:56,460
+specimen يعني
+
+349
+00:31:56,460 --> 00:32:00,460
+ممكن نصيحها بطريقة تانية نحكي according to maximum
+
+350
+00:32:00,460 --> 00:32:05,680
+shear stress theory failure begins when yielding
+
+351
+00:32:05,680 --> 00:32:07,520
+begins or yielding begins
+
+352
+00:32:10,310 --> 00:32:19,490
+بصير لما ال tau maximum تكون أكبر أو يساوي S Y على
+
+353
+00:32:19,490 --> 00:32:30,490
+اتنين احنا
+
+354
+00:32:30,490 --> 00:32:35,350
+more silky في هذا ال tensile بشكل عام بشكل عام
+
+355
+00:32:37,770 --> 00:32:42,130
+بتكون دي more circle بالشكل هذا هذا ال sigma واحد
+
+356
+00:32:42,130 --> 00:32:46,430
+هذا
+
+357
+00:32:46,430 --> 00:32:50,370
+ال 3D more circle sigma واحد sigma اتنين sigma
+
+358
+00:32:50,370 --> 00:32:54,850
+تلاتة انا برتب بحيث sigma واحد اكبر من sigma اتنين
+
+359
+00:32:54,850 --> 00:32:59,350
+اكبر من sigma تلاتة و احنا عرفنا سابقا حكينا ال
+
+360
+00:32:59,350 --> 00:33:05,650
+tau maximum بالساوية sigma واحد minus sigma تلاتة
+
+361
+00:33:05,650 --> 00:33:11,130
+على اتنينو according to ال maximum share history
+
+362
+00:33:11,130 --> 00:33:14,670
+theory بيصير failure او بيصير yielding لما انتهى
+
+363
+00:33:14,670 --> 00:33:15,190
+maximum
+
+364
+00:33:18,660 --> 00:33:23,760
+بتكون اكبر او يساوي as y على اتنين يعني ال maximum
+
+365
+00:33:23,760 --> 00:33:28,880
+هي sigma واحد minus sigma تلاتة على اتنين اكبر او
+
+366
+00:33:28,880 --> 00:33:33,280
+يساوي as y على اتنين يعني لو اختصرت اتنين مع اتنين
+
+367
+00:33:33,280 --> 00:33:37,420
+بتكون sigma واحد minus sigma تلاتة اكبر او يساوي
+
+368
+00:33:37,420 --> 00:33:39,240
+as y
+
+369
+00:33:43,280 --> 00:33:48,160
+يعني exactly at failure exactly at failure بتكون
+
+370
+00:33:48,160 --> 00:33:54,740
+tau maximum بالسواء أسواء على اتنين إذا أنا مابديش
+
+371
+00:33:54,740 --> 00:33:57,880
+يصير failure إذا مابديش يصير failure بحط factor of
+
+372
+00:33:57,880 --> 00:34:03,840
+safety بصير tau maximum to avoid failure بالسواء
+
+373
+00:34:03,840 --> 00:34:08,600
+أسواء على اتنين and و and factor of safety
+
+374
+00:34:16,320 --> 00:34:33,260
+الان هناخد ال maximum share stress theory هناخد
+
+375
+00:34:33,260 --> 00:34:37,740
+2D state of stress
+
+376
+00:34:42,320 --> 00:34:45,440
+يعني two destate of stress هيكون اتنين من ال
+
+377
+00:34:45,440 --> 00:34:50,120
+principal stresses اللي هم قيم و ال principal
+
+378
+00:34:50,120 --> 00:34:52,800
+stress في التالت هيكون ساوة صفر يعني هيكون عندى
+
+379
+00:34:52,800 --> 00:34:56,280
+sigma واحد و sigma اتنين و sigma تلاتة موجودين بس
+
+380
+00:34:56,280 --> 00:35:00,620
+واحد من التلاتة ده هيكون عاشر ساوة صفر معناته عند
+
+381
+00:35:00,620 --> 00:35:06,560
+plain stress state ال sigma a و ال sigma b مثله
+
+382
+00:35:06,560 --> 00:35:08,540
+اللي هو two non zero principal stresses
+
+383
+00:35:11,500 --> 00:35:14,160
+هحسب من more circles سيجما واحد و سيجما اتنين و
+
+384
+00:35:14,160 --> 00:35:17,800
+سيجما تلاتة او ارتبهم ترتيب تصعدي بحيث يكون عنده
+
+385
+00:35:17,800 --> 00:35:23,400
+سيجما واحد اكبر من سيجما اتنين اكبر من سيجما تلاتة
+
+386
+00:35:23,400 --> 00:35:26,680
+او اكبر من سيجما تلاتة او اكبر من سيجما تلاتة او
+
+387
+00:35:26,680 --> 00:35:28,760
+اكبر من سيجما تلاتة او اكبر من سيجما تلاتة او اكبر
+
+388
+00:35:28,760 --> 00:35:31,220
+من سيجما تلاتة او اكبر من سيجما تلاتة او اكبر من
+
+389
+00:35:31,220 --> 00:35:35,500
+سيجما تلاتة او اكبر من سيجما تلاتة او اكبر من
+
+390
+00:35:35,500 --> 00:35:40,380
+سيجما تلاتة او اكبر من سيجما تلاتة اومعناته حيكون
+
+391
+00:35:40,380 --> 00:35:43,720
+عندى two normal stress component sigma a و sigma b
+
+392
+00:35:43,720 --> 00:35:47,980
+يا اما التانتين حيكون موجبات sigma a و sigma b
+
+393
+00:35:47,980 --> 00:35:55,400
+موجبات او sigma a موجبة و sigma b سالبة او الحالة
+
+394
+00:35:55,400 --> 00:35:58,640
+التالتة التانية سالبة sigma a سالبة و sigma b
+
+395
+00:35:58,640 --> 00:36:03,560
+سالبة يعني عندى three cases اذا كانت sigma a و
+
+396
+00:36:03,560 --> 00:36:09,430
+sigma b positiveمعناته هيكون ان دي sigma a أكبر
+
+397
+00:36:09,430 --> 00:36:11,570
+السواء و sigma b أكبر السواء و 0 معناته هذه كأنها
+
+398
+00:36:11,570 --> 00:36:15,030
+sigma 1 وهذه sigma 2 وهذه sigma 3 معناة sigma 1
+
+399
+00:36:15,030 --> 00:36:19,290
+هتكون تساوي sigma a sigma 2 sigma b و sigma 3 صفر
+
+400
+00:36:19,290 --> 00:36:24,010
+الحالة التانية اللي هندرسها ان واحدة موجة و واحدة
+
+401
+00:36:24,010 --> 00:36:28,680
+سالفة يعني هتكون حالتي بترتيب تصعديهذه sigma a
+
+402
+00:36:28,680 --> 00:36:32,320
+موجة بقى أكبر أوي ساوة صفر وصفر أكبر أوي ساوة
+
+403
+00:36:32,320 --> 00:36:35,980
+sigma b معناته sigma واحد اللي هي sigma a و sigma
+
+404
+00:36:35,980 --> 00:36:39,540
+اتنين اللي هي صفر و sigma تلت اللي هي sigma b
+
+405
+00:36:39,540 --> 00:36:44,180
+الحالة التالتة التنين sigma a و sigma b سوالب
+
+406
+00:36:44,180 --> 00:36:48,160
+معناته هكون صفر أكبر أوي ساوة sigma a و sigma a
+
+407
+00:36:48,160 --> 00:36:50,000
+أكبر أوي ساوة sigma b
+
+408
+00:36:57,730 --> 00:37:06,830
+ب هنوضح كل حالة على حدة graphically احنا
+
+409
+00:37:06,830 --> 00:37:15,750
+عندنا three cases case one اللي
+
+410
+00:37:15,750 --> 00:37:23,990
+هي sigma a اكبر او يساوي sigma b اكبر او يساوي
+
+411
+00:37:23,990 --> 00:37:33,360
+zero هذه case oneمعناته هكون دي sigma 1 بالساوية
+
+412
+00:37:33,360 --> 00:37:40,400
+sigma a و sigma 2 بالساوية sigma b و sigma 3
+
+413
+00:37:40,400 --> 00:37:45,000
+بالساوية 0 معناته ال tau max مش الساوية بس هو
+
+414
+00:37:45,000 --> 00:37:52,320
+sigma 1 minus sigma 3 على 2 هتساوي اللي هي sigma a
+
+415
+00:37:52,320 --> 00:37:55,220
+على 2
+
+416
+00:37:58,110 --> 00:38:00,950
+According to maximum scarcity theory بيصير yield
+
+417
+00:38:00,950 --> 00:38:06,190
+again دي او بيصير failure لما tau maximum تكون
+
+418
+00:38:06,190 --> 00:38:09,290
+اكبر او يساوي as y على 2
+
+419
+00:38:14,760 --> 00:38:20,560
+أكبر أو يساوي SY على 2 يعني Sigma A أكبر أو يساوي
+
+420
+00:38:20,560 --> 00:38:25,780
+SY at this point إذا Sigma A كانت تساوية أو أكبر
+
+421
+00:38:25,780 --> 00:38:29,240
+من ال yield strength بيصير عندي failure هذه الحالة
+
+422
+00:38:29,240 --> 00:38:34,580
+الأولى عند ال load line عند هنا هي Sigma A
+
+423
+00:38:37,440 --> 00:38:43,020
+وعندي هنا هي sigma B الحلقة الأولى sigma A أكبر من
+
+424
+00:38:43,020 --> 00:38:45,120
+sigma B أكبر من sigma A يعني sigma A ال load line
+
+425
+00:38:45,120 --> 00:38:55,640
+هيكون بالشكل هذا هذه
+
+426
+00:38:55,640 --> 00:39:07,420
+sigma A وهذه sigma B الآن إذا كنا هناهيبدأ يصير
+
+427
+00:39:07,420 --> 00:39:11,240
+yielding اذا كنا هنا كنا الحدود يعني كانت زي ما
+
+428
+00:39:11,240 --> 00:39:15,740
+حكينا sigma a بيستوى sy في الحالة هذي sigma a
+
+429
+00:39:15,740 --> 00:39:19,680
+بيستوى sy بيصير اندي failure بقى انتوا هذا failure
+
+430
+00:39:19,680 --> 00:39:23,140
+line طالما
+
+431
+00:39:23,140 --> 00:39:30,640
+اندي هنا هنا في هذا الخط عندي sigma a اكبر من
+
+432
+00:39:30,640 --> 00:39:35,020
+sigma b لان لو load line تاني كان عندى
+
+433
+00:39:38,970 --> 00:39:43,610
+جاي بالشكل هذا هذه
+
+434
+00:39:43,610 --> 00:39:55,130
+هتكون sigma a وهي
+
+435
+00:39:55,130 --> 00:40:01,770
+ال actual learning conditions sigma a وهي sigma b
+
+436
+00:40:01,770 --> 00:40:05,170
+لاحظوا ال slope هذا ال critical طبعا
+
+437
+00:40:09,290 --> 00:40:18,150
+هن ال slope ايش يساوي؟ واحد في الحالة هذه هن
+
+438
+00:40:18,150 --> 00:40:29,510
+الخط هذا sigma a بيساوي sigma b هن sigma b أكبر من
+
+439
+00:40:29,510 --> 00:40:36,650
+sigma a معناته بيصير فالية عن النقطة هذهلما بيصير
+
+440
+00:40:36,650 --> 00:40:43,370
+failure لما سجمة بيه هنا لما
+
+441
+00:40:43,370 --> 00:40:47,010
+سجمة بيه بيستوى أسوأي بيبدأ يصير عندي failure على
+
+442
+00:40:47,010 --> 00:40:56,210
+الخط هذا لما سجمة a بيستوى أسوأي هنا failure when
+
+443
+00:40:56,210 --> 00:41:03,290
+سجمة a أكبر أو يستوى أسوأي هنا عندي failure
+
+444
+00:41:06,950 --> 00:41:24,390
+when sigma B أكبر أو يساوي S Y هذه
+
+445
+00:41:24,390 --> 00:41:28,530
+الحالة الأولى الحالة التانية case 2
+
+446
+00:41:39,690 --> 00:41:48,050
+سيجما A موجبة أكبر أوي سواء صفر و سيجما B سالبة في
+
+447
+00:41:48,050 --> 00:41:53,350
+الحالة هذه ستكون سواء سيجما واحد هذه سيجما اتنين
+
+448
+00:41:53,350 --> 00:42:01,420
+هذه سيجما تلاتة معناته هتكون التكون سواء سجن واحد
+
+449
+00:42:01,420 --> 00:42:06,020
+معينة سجن تلاتة على اتنين بتساوي اللي هي سجن A
+
+450
+00:42:06,020 --> 00:42:13,280
+معينة سجن B على اتنين بيصير failure at failure او
+
+451
+00:42:13,280 --> 00:42:18,240
+نحكي at failure هكون
+
+452
+00:42:18,240 --> 00:42:23,840
+عندي ال tau max بيسوء أسوأ ايه على اتنين يعني هكون
+
+453
+00:42:23,840 --> 00:42:31,240
+عندي اللي هي سجن Aminus sigma b على اتنين بتساوي
+
+454
+00:42:31,240 --> 00:42:37,760
+as y على اتنين يعني هيكون عندى sigma a minus sigma
+
+455
+00:42:37,760 --> 00:42:44,820
+b بساوي as y وضبط الطرفين ب minus minus plus minus
+
+456
+00:42:44,820 --> 00:42:53,220
+بيصير عندى sigma b بساوي sigma a minus as y
+
+457
+00:43:03,410 --> 00:43:08,210
+سيجما ايه انا حكيت موجبة سيجما بي سالب يعني انا في
+
+458
+00:43:08,210 --> 00:43:11,130
+الرابع التاني في الرابع الرابع هيكون هاي ال
+
+459
+00:43:11,130 --> 00:43:22,210
+loading line هذه سيجما ايه وهذه سيجما بيه exactly
+
+460
+00:43:22,210 --> 00:43:27,970
+at failure اذا كان اذا كان سيجما ايه at this point
+
+461
+00:43:27,970 --> 00:43:31,350
+at this point بيصير عندي failure
+
+462
+00:43:36,470 --> 00:43:44,370
+بصير عندي ايش؟ failure في
+
+463
+00:43:44,370 --> 00:43:50,830
+الحالة هذه الخط او
+
+464
+00:43:50,830 --> 00:43:53,130
+معادة الخط المستقيم هذا
+
+465
+00:44:05,750 --> 00:44:09,130
+النقطة هذه الـ fill point تمثل تقاط الخط المستقيم
+
+466
+00:44:09,130 --> 00:44:15,150
+مع الخط المستقيم هذا معادة
+
+467
+00:44:15,150 --> 00:44:23,690
+الخط هذه عندنا لو أخدت نقطة هنا سي و صفر فهي صفر و
+
+468
+00:44:23,690 --> 00:44:30,010
+minus sy وهي
+
+469
+00:44:30,010 --> 00:44:34,110
+عندنا ال strength at any location في الحالة هذه
+
+470
+00:44:34,110 --> 00:44:35,030
+السينا دي sigma b
+
+471
+00:44:38,110 --> 00:44:49,150
+بس او sigma a minus sy ال
+
+472
+00:44:49,150 --> 00:44:54,250
+case التالتة ان both sigma a و sigma b are
+
+473
+00:44:54,250 --> 00:44:57,750
+negative both sigma a و sigma b negative يعني
+
+474
+00:44:57,750 --> 00:45:01,390
+هتكون هي sigma a بهذا الاتجاه و sigma b بهذا
+
+475
+00:45:01,390 --> 00:45:05,750
+الاتجاه معناته اذا كان عندي case تلاتة
+
+476
+00:45:12,250 --> 00:45:19,210
+سفر أكبر أو يساوي سيجما A أكبر أو يساوي سيجما B
+
+477
+00:45:19,210 --> 00:45:25,450
+معناته هذا مثل سيجما واحد هذا سيجما اتنين وهذا ايش
+
+478
+00:45:25,450 --> 00:45:32,750
+سيجما تلاتة معناته tau maximum بتساوي سيجما واحد
+
+479
+00:45:32,750 --> 00:45:38,510
+minus سيجما تلاتة على اتنين بتساوي سيجما واحد سفر
+
+480
+00:45:38,510 --> 00:45:41,010
+minus سيجما
+
+481
+00:45:45,310 --> 00:45:55,630
+بي على اتنين at failure هكون
+
+482
+00:45:55,630 --> 00:46:03,270
+عندي تاو ماكس بيساوي as y على اتنين اللي هو هكون
+
+483
+00:46:03,270 --> 00:46:09,650
+عندي تاو ماكس مبرع ماينوسيجما بي على اتنين يعني at
+
+484
+00:46:09,650 --> 00:46:11,710
+failure يعني هكون اكبر او يساوي
+
+485
+00:46:18,280 --> 00:46:27,380
+SY على اتنين اذا بدى اطلب الطرفين بال .. بال minus
+
+486
+00:46:27,380 --> 00:46:33,540
+يعني حسينا دي ال sigma بيصير اصغر او يبدو اصغر او
+
+487
+00:46:33,540 --> 00:46:40,640
+يساوي minus SY معناته في الحالة هذه case three
+
+488
+00:46:45,450 --> 00:46:52,930
+يعني هذه case one case two case three الان ممكن
+
+489
+00:46:52,930 --> 00:47:01,750
+يعني في different cases الان ال failure profile من
+
+490
+00:47:01,750 --> 00:47:07,370
+Campbell جوا
+
+491
+00:47:07,370 --> 00:47:14,480
+الشكل هذا ال part is safeع الحدود أو برا ال part
+
+492
+00:47:14,480 --> 00:47:18,060
+is failing according to maximum shear stress
+
+493
+00:47:18,060 --> 00:47:18,420
+theory
+
+494
+00:47:43,940 --> 00:47:53,600
+عندي هنا plot سجم واحد على س وي سجم اتنين على س وي
+
+495
+00:47:53,600 --> 00:48:01,300
+وهذا ال contour lines اللي يتمثل ال failure طبقا ل
+
+496
+00:48:01,300 --> 00:48:04,500
+maximum shear stress theory وعندي هنا مبينة
+
+497
+00:48:04,500 --> 00:48:11,780
+experimental data بتلاحظوا ان ال theory fits ال
+
+498
+00:48:11,780 --> 00:48:17,050
+experimentaldata أحسن من ال maximum number of
+
+499
+00:48:17,050 --> 00:48:18,970
+students you received سواء في الرُبع الأول أو في
+
+500
+00:48:18,970 --> 00:48:24,450
+الرُبع الرابع لاحظوا لو أخدت loading line معين في
+
+501
+00:48:24,450 --> 00:48:31,550
+الرُبع الأول طبق
+
+502
+00:48:31,550 --> 00:48:40,170
+للنظرية طبق للنظرية we predict failure before the
+
+503
+00:48:40,170 --> 00:48:43,800
+part is actually failedwe predict failure before
+
+504
+00:48:43,800 --> 00:48:48,200
+the part is actually failed يعني نتوقع الانهيار لل
+
+505
+00:48:48,200 --> 00:48:52,920
+mechanical element قبل ما في الحقيقة انه ايش صارله
+
+506
+00:48:52,920 --> 00:48:57,040
+انهيار او failure هذا
+
+507
+00:48:57,040 --> 00:49:02,060
+يعني ان maximum shear stress theory is a
+
+508
+00:49:02,060 --> 00:49:07,540
+conservative theory يعنيانا بتوقع ال failure لسه
+
+509
+00:49:07,540 --> 00:49:11,360
+لكن في الحقيقة ماصارش failure معناته انا ال risk
+
+510
+00:49:11,360 --> 00:49:15,100
+في الحسابات بتاعتى مافيش عندى risk في الحسابات لأن
+
+511
+00:49:15,100 --> 00:49:19,580
+انا بحكي انه failed و هو في الواقع not failed
+
+512
+00:49:19,580 --> 00:49:25,320
+فمعناته it is conservative طبعا في فرق بين
+
+513
+00:49:25,320 --> 00:49:30,580
+conservative و accurate كل ما بتزيدي الدقة بشكل
+
+514
+00:49:30,580 --> 00:49:37,790
+عامبزيد عنصر المخاطرة في الحسابات يعني بتقل ال
+
+515
+00:49:37,790 --> 00:49:42,050
+conservatism ف the theory is conservative it
+
+516
+00:49:42,050 --> 00:49:46,570
+predicts failure before actually failure happens
+
+517
+00:49:48,860 --> 00:49:52,620
+نفس الشي هين او اخد load line هين هاي .. هاي ال
+
+518
+00:49:52,620 --> 00:49:57,700
+actual failure ال theory predicts failure before
+
+519
+00:49:57,700 --> 00:50:02,000
+failure actually happens معناته ال maximum share
+
+520
+00:50:02,000 --> 00:50:05,600
+of students theory is a conservative theory في كل
+
+521
+00:50:05,600 --> 00:50:13,420
+الأربعة في all the quadrants طيب
+
+522
+00:50:17,430 --> 00:50:22,390
+المحاضرة الجاي هنحكي على ال distortion energy
+
+523
+00:50:22,390 --> 00:50:27,170
+theories و بعدين هنحل أمثلة متعددة على ال maximum
+
+524
+00:50:27,170 --> 00:50:30,410
+shear stress theory و ال distortion energy theory
+
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/5N-tCP9cvEg_postprocess.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/5N-tCP9cvEg_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..0baf6152b845f00683c043a629dc3d236220f8ae
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/5N-tCP9cvEg_postprocess.srt
@@ -0,0 +1,1792 @@
+1
+00:00:04,890 --> 00:00:07,490
+بسم الله الرحمن الرحيم السلام عليكم و رحمة الله
+
+2
+00:00:07,490 --> 00:00:12,670
+المحاضرة اللى فاتت احنا بدأنا اللى هو ال fatigue
+
+3
+00:00:12,670 --> 00:00:16,230
+design for variable loading او fatigue failure for
+
+4
+00:00:16,230 --> 00:00:21,310
+variable loading حكينا اتعرفنا على ال S-N diagram
+
+5
+00:00:21,310 --> 00:00:26,090
+عملنا
+
+6
+00:00:26,090 --> 00:00:28,990
+definitions او تعريفات لل endurance limit حكينا ال
+
+7
+00:00:28,990 --> 00:00:31,710
+endurance limit هي ال stress level below which
+
+8
+00:00:48,600 --> 00:00:53,800
+طيب في عندي حالات لأن ال software انا بحكي على
+
+9
+00:00:53,800 --> 00:01:01,680
+mechanical part بدور و مقطع مدور بدور و مقطع مدور
+
+10
+00:01:01,680 --> 00:01:09,240
+طيب في حالتين او اكتر ممكن يكون المقطع مش مدور و
+
+11
+00:01:09,240 --> 00:01:15,460
+بدور او المقطع
+
+12
+00:01:15,460 --> 00:01:23,950
+مدوروبدورش أو المقطع مش مدور وبدورش يعني عندي تلت
+
+13
+00:01:23,950 --> 00:01:38,450
+احتمالات انه يعني ال part is واحد rotating و
+
+14
+00:01:38,450 --> 00:01:45,130
+round هذا خلصنا منها حالة تانية rotating
+
+15
+00:01:49,820 --> 00:01:58,000
+and not round مش مدور الحالة
+
+16
+00:01:58,000 --> 00:02:08,600
+التالتة not rotating و
+
+17
+00:02:08,600 --> 00:02:14,180
+مدور الحالة
+
+18
+00:02:14,180 --> 00:02:24,890
+الرابعةاللي هي not rotating و
+
+19
+00:02:24,890 --> 00:02:33,050
+not round الآن
+
+20
+00:02:33,050 --> 00:02:37,790
+الحالة التانية
+
+21
+00:02:37,790 --> 00:02:44,870
+والتالتة والرابعة هدول في الحالة هذه بدي
+
+22
+00:02:44,870 --> 00:02:45,790
+أوجد equivalent
+
+23
+00:02:54,700 --> 00:03:02,060
+round and rotating specimen
+
+24
+00:03:02,060 --> 00:03:14,720
+or part الآن
+
+25
+00:03:14,720 --> 00:03:19,840
+ال equivalent round and rotating specimen is found
+
+26
+00:03:19,840 --> 00:03:24,180
+based on this principleال volume of material
+
+27
+00:03:24,180 --> 00:03:31,280
+stressed at and above 5% of maximum stress يعني لو
+
+28
+00:03:31,280 --> 00:03:39,960
+عندى إشي under بدورش و مدور هي مدور و
+
+29
+00:03:39,960 --> 00:03:49,540
+بدورش لإن ال stress distribution هيكون بالشكل هذا
+
+30
+00:04:05,610 --> 00:04:11,350
+هذا ال stress distribution باخد
+
+31
+00:04:11,350 --> 00:04:14,650
+ال mechanical part و باخد الجزء الأخير الحلقة
+
+32
+00:04:14,650 --> 00:04:15,790
+الأخرانية
+
+33
+00:04:33,120 --> 00:04:42,580
+عند هذه ال maximum stress هذا sigma maximum باخد
+
+34
+00:04:42,580 --> 00:04:52,560
+عند location بيتمثل 95% من sigma maximum بتكون ال
+
+35
+00:04:52,560 --> 00:04:53,580
+area هذه تقريبا
+
+36
+00:05:17,520 --> 00:05:26,440
+ال volume بتاع الحلقة هذه بأسوي ل same volume in
+
+37
+00:05:26,440 --> 00:05:36,480
+rotating beam specimen طبعا هذا non rotating بأسوي
+
+38
+00:05:36,480 --> 00:05:42,960
+ال volume هذا ل same volume في حالة rotating beam
+
+39
+00:05:42,960 --> 00:05:43,780
+specimen
+
+40
+00:05:46,880 --> 00:05:51,320
+الان لو العينة طولها متر و ال mechanical part
+
+41
+00:05:51,320 --> 00:05:55,180
+الحقيقه طوله متر المتر مع متر بلغه بيظل معناته
+
+42
+00:05:55,180 --> 00:06:01,260
+اللي اللي هي ال a ninety five ال a point nine five
+
+43
+00:06:01,260 --> 00:06:08,860
+sigma مش هخش في تفاصيل اشتقاق تاعها الان a point
+
+44
+00:06:08,860 --> 00:06:15,050
+ninety five for a rotatingfor a rotating ground
+
+45
+00:06:15,050 --> 00:06:21,350
+specimen مطابل علاقة هذه بصوت point o766d تربيع
+
+46
+00:06:21,350 --> 00:06:27,290
+الان لو أخدت non
+
+47
+00:06:27,290 --> 00:06:31,730
+rotating ground هتكون تسمع non rotating ground
+
+48
+00:06:31,730 --> 00:06:34,730
+هتكون ال a point nine nine point nine five sigma
+
+49
+00:06:34,730 --> 00:06:45,110
+بصوت point o146 لو سويت هذه اللي هي point o1 O 4 6
+
+50
+00:06:45,110 --> 00:06:52,030
+D2 سويتها للمعادلة السابقة اللي
+
+51
+00:06:52,030 --> 00:07:00,050
+هتكون point O 7 6 6 D equivalent دي تربيع هو ان
+
+52
+00:07:00,050 --> 00:07:06,390
+انا بحسب ال D equivalent في
+
+53
+00:07:06,390 --> 00:07:12,000
+الحالة ال D equivalent هتطلع بالساعة point 3 7سفر
+
+54
+00:07:12,000 --> 00:07:19,200
+D في
+
+55
+00:07:19,200 --> 00:07:27,060
+حالة مقطع مستطيل يعني مش مدور أو بدورش هتكون ال A
+
+56
+00:07:27,060 --> 00:07:31,680
+point nine five بالساعة point O ال A في حالة مقطع
+
+57
+00:07:31,680 --> 00:07:36,560
+مستطيل اللي
+
+58
+00:07:36,560 --> 00:07:49,160
+هي Bبتكون ال a point 95 سبب point o 5h في b هذه
+
+59
+00:07:49,160 --> 00:07:55,320
+هسويها لل a point 95 ل
+
+60
+00:07:55,320 --> 00:08:00,340
+rotating ground specifically point o 766 دي
+
+61
+00:08:00,340 --> 00:08:03,080
+equivalent ومن هنا بحسب ال d equivalent تطلع
+
+62
+00:08:03,080 --> 00:08:06,900
+المعادلة هذه point 88hb أص نص
+
+63
+00:08:10,050 --> 00:08:15,970
+تابر ستة تلاتة بيعطينا بيعطينا ال a point تسعة
+
+64
+00:08:15,970 --> 00:08:21,330
+خمسة sigma و ال D equivalent ل different cross
+
+65
+00:08:21,330 --> 00:08:25,670
+sections يعني ال cross section ده مدور و منه بحسب
+
+66
+00:08:25,670 --> 00:08:27,970
+ال D equivalent to seven point three seven D هذا
+
+67
+00:08:27,970 --> 00:08:32,450
+المقطع مستطيل B في H و منه بحسب ال D equivalent to
+
+68
+00:08:32,450 --> 00:08:37,090
+seven point eight O تمانية جزر تربيعي ل H في B
+
+69
+00:08:37,090 --> 00:08:39,110
+طبعا في مقاطع تانية
+
+70
+00:08:42,310 --> 00:08:47,370
+لو كان عندى I beam ال A point تسعة خمسة بتختلف
+
+71
+00:08:47,370 --> 00:08:52,250
+بحسب المحور ال axis ال axis واحد واحد بتكون ال A
+
+72
+00:08:52,250 --> 00:08:57,910
+point nine five اللي هي point واحد في A TF ال A
+
+73
+00:08:57,910 --> 00:09:06,690
+اللي هي هدى هدى A هدى B و TF اللي هي هدى و هدى
+
+74
+00:09:06,690 --> 00:09:13,740
+axis اتنين اتنينهذا axis 1 1 إذا ال axis 1 1 بتكون
+
+75
+00:09:13,740 --> 00:09:19,440
+ال a.95 بيساو 0.1 atf إذا ال axis 2 2 بتكون ال a
+
+76
+00:09:19,440 --> 00:09:27,860
+.95 بيساو 0.05b في a في حالة ال channel طبعا هذا
+
+77
+00:09:27,860 --> 00:09:35,160
+ال axis 1 1 وهذا ال axis 2 2 هذا b
+
+78
+00:09:40,140 --> 00:09:45,640
+وهذه a ال a point nine five ل axis واحد واحد
+
+79
+00:09:45,640 --> 00:09:49,500
+بتساوي point o خمسة a b وال a point nine five
+
+80
+00:09:49,500 --> 00:09:54,080
+بتساوي point o خمسة اتنين x في a زي ال point واحد
+
+81
+00:09:54,080 --> 00:09:56,620
+TF في b minus x، x اللي هي هذه المسافة
+
+82
+00:10:11,690 --> 00:10:15,450
+طبعا دايما بحصل equivalent round and rotating
+
+83
+00:10:15,450 --> 00:10:22,270
+specimen في حالة انه كان ال mechanical parts is
+
+84
+00:10:22,270 --> 00:10:26,590
+rotating and not round او كان not rotating and
+
+85
+00:10:26,590 --> 00:10:33,110
+round او كان not rotating and not round شوف
+
+86
+00:10:33,110 --> 00:10:33,550
+مثال
+
+87
+00:10:55,050 --> 00:10:59,290
+a steel shaft loaded in bending عندي عمود مصنوع من
+
+88
+00:10:59,290 --> 00:11:03,590
+الحديد ال loading عليه ال bending is 32 mm in
+
+89
+00:11:03,590 --> 00:11:07,130
+diameter abuting a filleted shoulder 38 mm in
+
+90
+00:11:07,130 --> 00:11:11,810
+diameter يعني أنا عندي shaft جاي زي هيك
+
+91
+00:11:39,450 --> 00:11:49,830
+هذا القطر 32 ميلي ميتا مسلم
+
+92
+00:11:49,830 --> 00:11:58,970
+للقطر اكبر 38 ميلي
+
+93
+00:11:58,970 --> 00:11:59,370
+ميتا
+
+94
+00:12:02,990 --> 00:12:06,550
+The shaft material has a mean ultimate the shaft
+
+95
+00:12:06,550 --> 00:12:09,290
+material has a mean ultimate tensile strength of
+
+96
+00:12:09,290 --> 00:12:17,650
+690 MPa يعني ال SCUT بالساوية 690 ميجاباسكال
+
+97
+00:12:17,650 --> 00:12:22,150
+estimate
+
+98
+00:12:22,150 --> 00:12:27,870
+the size factor Kb if the shaft is used in a
+
+99
+00:12:27,870 --> 00:12:28,630
+rotating mode
+
+100
+00:12:34,640 --> 00:12:44,000
+if shaft is rotating معناته
+
+101
+00:12:44,000 --> 00:12:53,620
+اذا ال shaft is rotating ال
+
+102
+00:12:53,620 --> 00:13:00,060
+KB في الحالة هذه ال
+
+103
+00:13:00,060 --> 00:13:00,480
+KB
+
+104
+00:13:05,010 --> 00:13:09,550
+لحظة القطرة اللي عندك هيكون 32 ال 32 هتكون
+
+105
+00:13:09,550 --> 00:13:13,610
+المعادلة هذه اللي هو هتكون KB هتكون ساعة واحد
+
+106
+00:13:13,610 --> 00:13:20,430
+point اتنين اربعة D اصلاقص point واحد او سبن
+
+107
+00:13:20,430 --> 00:13:26,630
+هتساوي واحد point اتنين اربعة في D اللي هي 32
+
+108
+00:13:26,630 --> 00:13:31,010
+اصلاقص minus point واحد او سبن
+
+109
+00:13:35,360 --> 00:13:43,740
+هتكون اتنين و تلاتين اص minus point one oh seven
+
+110
+00:13:43,740 --> 00:13:51,900
+هتكون في واحد point اتنين اربع هتطلع point تمانية
+
+111
+00:13:51,900 --> 00:13:58,880
+خمسة ستة هذا
+
+112
+00:13:58,880 --> 00:14:05,770
+في حالة ال shaft is rotatingطيب إذا ال shaft is
+
+113
+00:14:05,770 --> 00:14:15,210
+not rotating if shaft is
+
+114
+00:14:15,210 --> 00:14:22,610
+not rotating معناته مطلوب مني أحسب equivalent
+
+115
+00:14:22,610 --> 00:14:28,270
+round rotating specimen يعني هستخدم المعادلة
+
+116
+00:14:32,200 --> 00:14:39,300
+اللي هي DE دي equivalent هتساوي
+
+117
+00:14:39,300 --> 00:14:48,040
+point تلاتة سبعة دي هتساوي point تلاتة سبعة في
+
+118
+00:14:48,040 --> 00:14:57,300
+اتنين و تلاتين هيطلع
+
+119
+00:14:57,300 --> 00:14:57,680
+عندى
+
+120
+00:15:00,840 --> 00:15:12,100
+11.84 11.84 مليمتر once اعرفت ال equivalent
+
+121
+00:15:12,100 --> 00:15:23,570
+diameter بحسب ال KB هتساوح 1.24 دي equivalent-0
+
+122
+00:15:23,570 --> 00:15:32,770
+.107-0.107
+
+123
+00:15:32,770 --> 00:15:35,050
+-0.107
+
+124
+00:15:46,010 --> 00:15:53,450
+-0.107×1.24 كيبيا هتكون 0.952
+
+125
+00:16:11,000 --> 00:16:14,400
+نجي لل modification factor التالت اللي هو ال
+
+126
+00:16:14,400 --> 00:16:30,020
+loading factor KC ال
+
+127
+00:16:30,020 --> 00:16:35,340
+loading factor KC بياخد في عين الاعتبار التغيرات
+
+128
+00:16:35,340 --> 00:16:38,920
+في ال endurance limitالناتجة عن تغيير نوع ال
+
+129
+00:16:38,920 --> 00:16:44,380
+loading احنا حكينا ال standard fatigue specimen
+
+130
+00:16:44,380 --> 00:16:50,220
+بيصير ل completely reverse bending load لكن على
+
+131
+00:16:50,220 --> 00:16:56,570
+أرض الواقع يمكن تكون ال load axial loadممكن تورج
+
+132
+00:16:56,570 --> 00:17:01,490
+ال load ممكن bending ممكن transverse shear load
+
+133
+00:17:01,490 --> 00:17:05,910
+ممكن any combination المعادلة اللي هتشوفوها اللي
+
+134
+00:17:05,910 --> 00:17:12,370
+هي الان معدلة 626 نستخدمها في حالة single load
+
+135
+00:17:12,370 --> 00:17:18,910
+type يعني بيكون القطع الميكانيكية متعرضة لنوع محدد
+
+136
+00:17:18,910 --> 00:17:25,450
+او نوع واحد من التحميل ممكن يكون ال loadAxial أو
+
+137
+00:17:25,450 --> 00:17:28,090
+Bending أو Torsion
+
+138
+00:17:29,980 --> 00:17:32,620
+في الحالة دي بس أخد المعادلة ده إذا كان bending ما
+
+139
+00:17:32,620 --> 00:17:35,360
+هو أساسا ال standard bending معناته ال Kc هكون
+
+140
+00:17:35,360 --> 00:17:39,740
+الساعة واحد إذا كان axle Kc بيساوي 0.85 إذا كان ال
+
+141
+00:17:39,740 --> 00:17:43,320
+torsion Kc بيساوي 0.59 لكن إذا كان عندي
+
+142
+00:17:43,320 --> 00:17:46,960
+combination of loading يعني كان خلطة عندي axle مع
+
+143
+00:17:46,960 --> 00:17:51,360
+.. مع .. مع bending مع torsion بستخدم ما يسمى
+
+144
+00:17:51,360 --> 00:17:54,200
+طريقة اللي هي combination loading method اللي هي
+
+145
+00:17:54,200 --> 00:18:00,050
+مشروعة في section 614 في shigleمعناة المعادلة هذه
+
+146
+00:18:00,050 --> 00:18:08,310
+applies for single load types ال
+
+147
+00:18:08,310 --> 00:18:12,350
+modification factor الرابع اللي هو اللي بياخد في
+
+148
+00:18:12,350 --> 00:18:16,870
+الاعتبار التغير بدرجة الحرارة لأن الفحص المياري
+
+149
+00:18:16,870 --> 00:18:25,750
+بيصير عن درجة حرارة الغرفة الآن لما القطعتسخن
+
+150
+00:18:25,750 --> 00:18:31,830
+تتغير ال tensile strength بتاعتها الان في ال table
+
+151
+00:18:31,830 --> 00:18:41,190
+6.4 المرجيني ال ratio ل for steel طبعا لل tensile
+
+152
+00:18:41,190 --> 00:18:45,980
+strengththe temperature under study على ال tensile
+
+153
+00:18:45,980 --> 00:18:49,960
+strength at room temperature هنا درجة الحرارة هنا
+
+154
+00:18:49,960 --> 00:18:54,380
+ال ratio بين ال ST على SRT ال ST هي ال tensile
+
+155
+00:18:54,380 --> 00:18:58,140
+strength at ال operating temperature و ال SRT هي
+
+156
+00:18:58,140 --> 00:19:06,760
+ال tensile strength at room temperature الآن
+
+157
+00:19:06,760 --> 00:19:15,010
+عشان أحسب ال KD في عنديأكتر من حالة if ultimate
+
+158
+00:19:15,010 --> 00:19:17,710
+strength is known for the operating temperature
+
+159
+00:19:17,710 --> 00:19:24,190
+يعني ال S T معروف يعني واحد واحد
+
+160
+00:19:24,190 --> 00:19:33,490
+if ال S T at T is known
+
+161
+00:19:37,160 --> 00:19:44,480
+بعد يحكي SE' بيساوي نص ال ST و بحط كده بيساوي
+
+162
+00:19:44,480 --> 00:19:59,280
+واحد، هاي حالة حالة تانية ال ST ال SRT is non اللي
+
+163
+00:19:59,280 --> 00:20:02,040
+هي ال strength at root bridge is non
+
+164
+00:20:05,820 --> 00:20:11,220
+بروح على table 6
+
+165
+00:20:11,220 --> 00:20:18,580
+4 اللي هو هذا ال table و
+
+166
+00:20:18,580 --> 00:20:30,260
+بطلع منه S T على S room temperature و منه بحسب ال
+
+167
+00:20:30,260 --> 00:20:37,220
+S Tبعدين بحكي SE' بساوة نص ال ST و في الحالة هذه
+
+168
+00:20:37,220 --> 00:20:49,060
+برضه بحط KD بساوة واحد حالة تالتة ال
+
+169
+00:20:49,060 --> 00:20:55,100
+ال ال strength at room temperature ال
+
+170
+00:20:55,100 --> 00:20:59,700
+SRT is null
+
+171
+00:21:03,090 --> 00:21:09,350
+منها بحسب SE' بالساوية نص الـ S ال room
+
+172
+00:21:09,350 --> 00:21:18,670
+temperature بعدين من table 6 4 بحسب ال KD بالساوية
+
+173
+00:21:18,670 --> 00:21:23,690
+ST على S room temperature بعدين بعمل modification
+
+174
+00:21:23,690 --> 00:21:27,390
+SE بالساوية KD في SE'
+
+175
+00:21:37,160 --> 00:21:42,700
+البيانات اللي في جدول 6-4 معمولها
+
+176
+00:21:42,700 --> 00:21:51,480
+care fit من خلال polynomial من الدرجة الرابعة ال
+
+177
+00:21:51,480 --> 00:21:56,120
+KDis a function of temperature والتمريتشر معبر
+
+178
+00:21:56,120 --> 00:22:00,420
+عنها بوحدة الفهرون هايت ال KD is given by this
+
+179
+00:22:00,420 --> 00:22:04,640
+equation بالسواء bond 9 7 5 زي bond 4 3 2 في 10
+
+180
+00:22:04,640 --> 00:22:09,520
+أساس 3 TF minus bond 1 1 5 في 10 أساس 5 TF تربيه
+
+181
+00:22:09,520 --> 00:22:14,840
+ناقص bond 104 في 10 أس ناقص 8 في TF تكييب minus
+
+182
+00:22:14,840 --> 00:22:20,480
+bond 5 9 5 في 10 أس ناقص 12 TF أس 4 لاحظوا ان TF
+
+183
+00:22:20,480 --> 00:22:22,660
+معبر عنها بوحدة الفهرون هايت
+
+184
+00:22:28,560 --> 00:22:43,040
+نشوف مثال a
+
+185
+00:22:43,040 --> 00:22:50,040
+1035 steel عندي حديد اللي هو عشرة خمس وتلاتين
+
+186
+00:22:50,040 --> 00:22:55,280
+steel هذه ال material has a tensile strength
+
+187
+00:22:59,280 --> 00:23:05,100
+of seventy kilo pound per square inch الاسس عند ال
+
+188
+00:23:05,100 --> 00:23:10,460
+room temperature بستوى سبعين kilo pound per square
+
+189
+00:23:10,460 --> 00:23:15,020
+inch and is to be used for a part that sees
+
+190
+00:23:15,020 --> 00:23:17,260
+اربعمية خمسين degrees Fahrenheit in service في
+
+191
+00:23:17,260 --> 00:23:23,260
+الخدمة هتكون درجة الحرارة اربعمية خمسين Fahrenheit
+
+192
+00:23:23,260 --> 00:23:26,560
+estimate
+
+193
+00:23:26,560 --> 00:23:31,240
+the temperature modification factorand SE عند ..
+
+194
+00:23:31,240 --> 00:23:44,060
+بده نحسب الـ KD والـ SE عند الـ 450 if
+
+195
+00:23:44,060 --> 00:23:47,140
+room
+
+196
+00:23:47,140 --> 00:23:52,120
+temperature and unit limit by test إذا كنت عارف
+
+197
+00:23:52,120 --> 00:24:01,950
+الـ SE prime عند الـ 70 فهران هايتبتساوي تسعة
+
+198
+00:24:01,950 --> 00:24:11,730
+وتلاتين kilo pound per square inch طيب
+
+199
+00:24:11,730 --> 00:24:17,910
+اللي هسويه في الحالة هذه انا
+
+200
+00:24:17,910 --> 00:24:21,230
+معروف عندي ال SE prime عند تسعة .. عند سبعين فرن
+
+201
+00:24:21,230 --> 00:24:25,570
+هاي تسعة تلاتين و بده ال SE عند اربعمية و خمسين
+
+202
+00:24:25,570 --> 00:24:33,010
+هروح ل tableست اربعة انا درس الحلقة اربعمية و
+
+203
+00:24:33,010 --> 00:24:42,710
+خمسين يعني انا جاي في المنطقة هذه اربعمية
+
+204
+00:24:42,710 --> 00:24:49,390
+و خمسين تيجي هنا جاي
+
+205
+00:24:49,390 --> 00:24:52,690
+بين هدولتين تاني الاربعمية و خمسين جاي بالمص
+
+206
+00:24:52,690 --> 00:24:56,900
+بالظبط بين اربعمية و الخمسمية معناته بعمل ايشبعمل
+
+207
+00:24:56,900 --> 00:24:59,340
+interpolation يعني معناته ال S T على S room
+
+208
+00:24:59,340 --> 00:25:02,200
+temperature انتقال 450 هتكون القيمة المتوسطة لهذه
+
+209
+00:25:02,200 --> 00:25:10,440
+القيمتان ال S T table table
+
+210
+00:25:10,440 --> 00:25:19,440
+64 بتكون الحالة هذه S T على S room temperature
+
+211
+00:25:19,440 --> 00:25:29,700
+بتساوي اللي هي 1 pointاو واحد تمانية زائد بونت
+
+212
+00:25:29,700 --> 00:25:51,820
+تسعة تسعة خمسة على اتنين بطل
+
+213
+00:25:51,820 --> 00:25:53,080
+واحد بونت او او
+
+214
+00:25:56,190 --> 00:26:03,210
+ستة خمسة هذي
+
+215
+00:26:03,210 --> 00:26:12,270
+بتساوي كد معناته ال SE عند اربعمية و خمسين هتساوي
+
+216
+00:26:12,270 --> 00:26:18,870
+اللي هو واحد point O او ستة خمسة في ال SE عند
+
+217
+00:26:18,870 --> 00:26:21,710
+سبعين في تسعة و تلاتين
+
+218
+00:26:28,170 --> 00:26:33,510
+تبتعد تسعة وتلاتين Pound تسعة تلاتين Pound تسعة
+
+219
+00:26:33,510 --> 00:26:34,550
+تلاتين Pound تسعة تلاتين Pound تسعة تلاتين Pound
+
+220
+00:26:34,550 --> 00:26:35,350
+تسعة تلاتين Pound تسعة تلاتين Pound تسعة تلاتين
+
+221
+00:26:35,350 --> 00:26:39,670
+Pound تسعة تلاتين Pound تسعة تلاتين Pound تسعة
+
+222
+00:26:39,670 --> 00:26:39,970
+تلاتين Pound تسعة تلاتين Pound تسعة تلاتين Pound
+
+223
+00:26:39,970 --> 00:26:40,190
+تلاتين Pound تسعة تلاتين Pound تسعة تلاتين Pound
+
+224
+00:26:40,190 --> 00:26:48,650
+تسعة تلاتين Pound تسعة تلاتين Pound تسعة
+
+225
+00:26:48,650 --> 00:26:54,490
+تلاتين Pound
+
+226
+00:26:58,750 --> 00:27:01,070
+only the tensile strength at room temperature اللي
+
+227
+00:27:01,070 --> 00:27:07,790
+هي هذه is given يعني only as room temperature is
+
+228
+00:27:07,790 --> 00:27:15,370
+known يعني
+
+229
+00:27:15,370 --> 00:27:21,960
+ممكن أعمل التالي أروح على ال table six أربعةواحسب
+
+230
+00:27:21,960 --> 00:27:27,780
+ST على S رومتين ريتشار زي ما حسبنا تطلع واحد point
+
+231
+00:27:27,780 --> 00:27:35,480
+O O ستة خمسة واحسب ST بسواحد point O O ستة خمسة في
+
+232
+00:27:35,480 --> 00:27:39,620
+اللي هي سبعين
+
+233
+00:27:49,760 --> 00:27:54,900
+تطلع سبعين point أربعة خمسة
+
+234
+00:27:54,900 --> 00:28:00,760
+خمسة kilo pound per square inch و هحكي SE عند أربع
+
+235
+00:28:00,760 --> 00:28:10,120
+مية و خمسين سواء نص ال ST يعني هتكون نص في سبعين
+
+236
+00:28:10,120 --> 00:28:19,120
+point أربعة خمسة خمسة فنص هتكون
+
+237
+00:28:20,790 --> 00:28:34,290
+خمس تلاتين بونت او
+
+238
+00:28:34,290 --> 00:28:43,660
+احتياجي بتستوي كدي يعني orS E Prime سواء نص ال S U
+
+239
+00:28:43,660 --> 00:28:49,200
+T اللي هي نص في سبعين عند room temperature بتساوي
+
+240
+00:28:49,200 --> 00:28:53,520
+خمس تلاتين كيلو pound per square inch بعدين احكي S
+
+241
+00:28:53,520 --> 00:29:02,020
+E S E عند الاربعمية و خمسين بتساوي ال K D في ال S
+
+242
+00:29:02,020 --> 00:29:09,020
+E Prime عند السبعين ال
+
+243
+00:29:09,020 --> 00:29:15,470
+K Dاللي بيساوي ST على S room temperature اللي
+
+244
+00:29:15,470 --> 00:29:34,950
+بيساوي 1.0065 هتكون معناته واحدة 1.0065 في 35 تطلع
+
+245
+00:29:34,950 --> 00:29:37,370
+نفس ال issue 32
+
+246
+00:29:40,500 --> 00:29:45,500
+أو خمسة و تلاتين point اتنين اتنين سبعة خمسة kilo
+
+247
+00:29:45,500 --> 00:30:02,060
+pound per square inch بصرا نفس النتيجة ال
+
+248
+00:30:02,060 --> 00:30:04,640
+modification factor الخامس اللي هو reliability
+
+249
+00:30:04,640 --> 00:30:06,960
+factor reliability factor
+
+250
+00:30:19,090 --> 00:30:26,510
+نرجع لشكل 6.17 شكل 6.17 كان عامل plot بين ال
+
+251
+00:30:26,510 --> 00:30:33,890
+tensile strength sut و ال SE prime و كانت ال
+
+252
+00:30:33,890 --> 00:30:39,650
+relation linear في النص for
+
+253
+00:30:43,780 --> 00:30:46,600
+الخط في المصدر يمثل خمسين في المية reliability of
+
+254
+00:30:46,600 --> 00:30:52,380
+data يعني نسبة النجاح انه .. النسبة النجاح ان الخط
+
+255
+00:30:52,380 --> 00:30:56,940
+هذا يمثل ال experimental data خمسين في المية يعني
+
+256
+00:30:56,940 --> 00:30:59,580
+خمسين في المية من البيانات above خمسين في المية من
+
+257
+00:30:59,580 --> 00:31:01,400
+البيانات ash below
+
+258
+00:31:06,930 --> 00:31:10,070
+يعني اللي انا لو حكيت reliability تسعين في المية
+
+259
+00:31:10,070 --> 00:31:13,650
+معناته نسبة النجاح ان ال line to fit the data is
+
+260
+00:31:13,650 --> 00:31:16,310
+تسعين في المية نسبة النجاح تكون تسعين في المية لما
+
+261
+00:31:16,310 --> 00:31:19,950
+نحكي reliability عبارة ال reliability عادة تعرف
+
+262
+00:31:19,950 --> 00:31:27,550
+واحد minus احتمالية ال failure فلو نحكي
+
+263
+00:31:27,550 --> 00:31:31,950
+reliability تسعين في المية معناته في احتمال ان ال
+
+264
+00:31:31,950 --> 00:31:38,690
+data يكون تمثيلهاللبيانات بنسبة خطأ عشرة في المية
+
+265
+00:31:38,690 --> 00:31:44,590
+فمعناته النجاح عندى تسعين في المية فال SE prime
+
+266
+00:31:44,590 --> 00:31:56,170
+بيساوي نص SUT is based on fifty percent
+
+267
+00:31:56,170 --> 00:32:01,990
+reliability of experimental data
+
+268
+00:32:04,660 --> 00:32:09,760
+إذا بدّي more reliable fit معناته محتاج أعمل
+
+269
+00:32:09,760 --> 00:32:22,220
+modification لل SE prime ال KE موضوع في ال table 6
+
+270
+00:32:22,220 --> 00:32:29,600
+5 ال table 6 5 إذا كان reliability لل fitting لل
+
+271
+00:32:29,600 --> 00:32:32,440
+experimental data 50% معناته مش modification نفس
+
+272
+00:32:32,440 --> 00:32:37,710
+اللي احنا عملنا واحدال 90% بيبغون 8 9 7 و هكذا كل
+
+273
+00:32:37,710 --> 00:32:44,610
+ما كانت انا محتاج نسبة اعلى لتمثيل ال experimental
+
+274
+00:32:44,610 --> 00:32:50,050
+data كل ما انا محتاج انزل اللي هي ال endurance
+
+275
+00:32:50,050 --> 00:32:54,510
+limit ومعناته ال K.E بتقل بالارتفاع بقيمة
+
+276
+00:32:54,510 --> 00:32:54,990
+reliability
+
+277
+00:33:00,790 --> 00:33:05,610
+ال factor الأخير اللي هو mycelinus effects factor
+
+278
+00:33:05,610 --> 00:33:10,030
+اللي هو factor بحط كذا شغلات .. كذا شغلة مع بعض
+
+279
+00:33:10,030 --> 00:33:16,550
+يعني شغلات غير منظورة مثلا ممكن ال mechanical part
+
+280
+00:33:16,550 --> 00:33:20,850
+متعرض لبيئة .. بيئة very corrosive يعني زي بيئة
+
+281
+00:33:20,850 --> 00:33:26,930
+البحر بتعمل صدا و تأكل سريع أو محطوط مثلا معمول
+
+282
+00:33:26,930 --> 00:33:33,620
+تقسي سطحية لل mechanical partأو مطلب مادة تانية
+
+283
+00:33:33,620 --> 00:33:38,980
+مطلب كروم او مطلب ب .. ب .. ب zinc او في صارت عليه
+
+284
+00:33:38,980 --> 00:33:43,100
+عمليات .. عمليات ميكانيكية مثلا عمليات تشكيل
+
+285
+00:33:43,100 --> 00:33:49,380
+عمليات تشكيل بتخلي المادة فيها
+
+286
+00:33:49,380 --> 00:33:52,760
+stresses او صار عملية عملية الحنفة فيه stresses
+
+287
+00:33:52,760 --> 00:33:58,430
+هذه كلها different effectsلازم ناخدها بالاعتبار
+
+288
+00:33:58,430 --> 00:34:03,290
+طبعا مافيش ايش محدد تعتمد على المصمم هو يتخذ قرار
+
+289
+00:34:03,290 --> 00:34:08,590
+يقدر ال factor تاع ال miscellaneous effects ممكن
+
+290
+00:34:08,590 --> 00:34:13,010
+إذا بده شغل أدق يعمل عليها more research or
+
+291
+00:34:13,010 --> 00:34:20,590
+testing معناته
+
+292
+00:34:20,590 --> 00:34:25,640
+احنا نرجع لمعادل أصلي لنا SEالـ Modified Endurance
+
+293
+00:34:25,640 --> 00:34:30,020
+Limit بيستوى لـ KA, KB, KC, KD, KE, KF, SE Prime
+
+294
+00:34:30,020 --> 00:34:33,680
+SE Prime هي الـ Endurance Limit لـ Standard
+
+295
+00:34:33,680 --> 00:34:37,840
+Fatigue Specimen That Is Highly Polished That Is
+
+296
+00:34:37,840 --> 00:34:44,040
+Under Completely Reversed Bending وشرحنا إيش هو
+
+297
+00:34:44,040 --> 00:34:47,760
+الـ KA، إيش هو ال KB و KC و KD و KE و KF و KFA
+
+298
+00:34:47,760 --> 00:34:50,720
+قلية حساب كل factor على حدة
+
+299
+00:34:53,340 --> 00:34:56,800
+الان اذا بيصير عندي الان النقطة اللى هندرسها
+
+300
+00:34:56,800 --> 00:34:59,520
+اضافية الان اللى هي ال stress concentration and
+
+301
+00:34:59,520 --> 00:35:03,720
+notch sensitivity يعني stress concentration مثلا
+
+302
+00:35:03,720 --> 00:35:11,860
+لو انا صار عندي تغير مفاجئ في القطر تغير
+
+303
+00:35:11,860 --> 00:35:15,440
+مفاجئ بيصير عندي هنا في المنطقة هذه stress
+
+304
+00:35:15,440 --> 00:35:21,020
+concentration او
+
+305
+00:35:21,020 --> 00:35:26,680
+مثلا عندي plateو في ثقب عند ال whole عند ال whole
+
+306
+00:35:26,680 --> 00:35:31,680
+هي مباشرة بيكون ال stress is maximum بيعلى ال
+
+307
+00:35:31,680 --> 00:35:35,900
+stress من نتيجة تركيز الإجهاد احنا درسنا في
+
+308
+00:35:35,900 --> 00:35:41,560
+chapter تلاتة حكينا في appendix A15 بيعطي ال
+
+309
+00:35:41,560 --> 00:35:44,040
+geometric stress concentration factor KT في
+
+310
+00:35:44,040 --> 00:35:48,020
+appendix A15لأن احنا عندنا fatigue loading يعني ال
+
+311
+00:35:48,020 --> 00:35:51,820
+loading is variable معناته محتاج fatigue stress
+
+312
+00:35:51,820 --> 00:35:55,320
+concentration factor ال fatigue stress
+
+313
+00:35:55,320 --> 00:36:00,940
+concentration factor KF معطب
+
+314
+00:36:00,940 --> 00:36:07,760
+العلاقة واحد زاد Q في KTمينص واحد او ممكن احكي كيو
+
+315
+00:36:07,760 --> 00:36:10,980
+باسم كف مينص واحد على كتي مينص واحد في حالة اللي
+
+316
+00:36:10,980 --> 00:36:15,580
+هو ال normal stress في حالة shear stress باسم كف
+
+317
+00:36:15,580 --> 00:36:20,570
+اس مينص واحد على كتي اس مينص واحدالـ KFS اللي هو
+
+318
+00:36:20,570 --> 00:36:25,410
+shear fatigue stress concentration factor ال KTS
+
+319
+00:36:25,410 --> 00:36:28,830
+اللي هي shear geometric stress concentration
+
+320
+00:36:28,830 --> 00:36:33,470
+factor و ال Q notch sensitivity بيعبر عن مدى
+
+321
+00:36:33,470 --> 00:36:41,700
+حساسية المادة للخدوش إذا كانت ال Qصفر معناته ال
+
+322
+00:36:41,700 --> 00:36:45,720
+material مش حساسة للخدوش في الحال هذي ال K في ال
+
+323
+00:36:45,720 --> 00:36:49,100
+KF بالساوية واحد يعني إذا ال material كانت very
+
+324
+00:36:49,100 --> 00:36:54,880
+ductile مش هتكون حساسة للخدوش إذا كانت ال Q واحد
+
+325
+00:36:54,880 --> 00:36:59,500
+يعني fully sensitive هتكون ال KF بالساوية KT زي
+
+326
+00:36:59,500 --> 00:37:03,840
+المواد الناشرة أو ال very hard بتكون حساسة للخدوش
+
+327
+00:37:08,660 --> 00:37:12,240
+الان ال notch sensitivity factor بيعتمد على نوع ال
+
+328
+00:37:12,240 --> 00:37:17,010
+loading اذا كان ال loading bending and axialبحسب
+
+329
+00:37:17,010 --> 00:37:22,870
+الـ Q من figure 620 figure 620 على المحور الأفق ..
+
+330
+00:37:22,870 --> 00:37:28,170
+الأفق معطيني ال notch radius notch radius are هنا
+
+331
+00:37:28,170 --> 00:37:31,210
+بواحدة ال inch وهنا بواحدة ال millimeter يعني هنا
+
+332
+00:37:31,210 --> 00:37:34,590
+عنده نص واحد millimeter واحد و نص اتنين اتنين و نص
+
+333
+00:37:34,590 --> 00:37:37,710
+تلاتة تلاتة و نص اربعة هنا بواحدة ال inch point o
+
+334
+00:37:37,710 --> 00:37:40,530
+two point o four يعني هذا ال axis هو نفس ال axis
+
+335
+00:37:40,530 --> 00:37:43,850
+بس هذا metric unit هذا English unit على المحور
+
+336
+00:37:43,850 --> 00:37:50,640
+الرأسي معطيني ال Qوعندي different curves هذا ال
+
+337
+00:37:50,640 --> 00:37:55,800
+curveلـ steel الـ tensile strength بتاعته 200 kilo
+
+338
+00:37:55,800 --> 00:37:59,620
+pound per square inch الكيرف هذا لـ steel الـ
+
+339
+00:37:59,620 --> 00:38:02,580
+tensile strength بتاعته 150 kilo pound per square
+
+340
+00:38:02,580 --> 00:38:06,120
+inch الكيرف التالت لـ steel الـ tensile strength
+
+341
+00:38:06,120 --> 00:38:09,880
+بتاعته 100 كيرف هذا لـ steel الـ tensile strength
+
+342
+00:38:09,880 --> 00:38:15,060
+بتاعته 60 الكيرف الـ dotted للألمنيون في الحالة دي
+
+343
+00:38:15,060 --> 00:38:19,380
+KF بالساوية واحد زاد Q في KT minus واحد
+
+344
+00:38:23,770 --> 00:38:29,500
+الشكل 621 معطيني ال notch sensitivityfor torsional
+
+345
+00:38:29,500 --> 00:38:31,920
+loading نفس الاشياء على المحور الأفق عندى ال notch
+
+346
+00:38:31,920 --> 00:38:36,640
+radius بالإنش أو ال notch radius بالمليمتر هين ال
+
+347
+00:38:36,640 --> 00:38:41,540
+QS ال notch sensitivity for shear وهين معطيني ال S
+
+348
+00:38:41,540 --> 00:38:48,060
+ال tensile strength هين عندى 200 هين عندى 150 160
+
+349
+00:38:48,060 --> 00:38:53,700
+وهدى الألمانيوم و ال KFS يساوي واحد زي ال QS في
+
+350
+00:38:53,700 --> 00:38:55,420
+KTS minus واحد
+
+351
+00:39:00,510 --> 00:39:07,630
+يعني يا اما بستخدم figure 26 او figure 621 او بعمل
+
+352
+00:39:07,630 --> 00:39:13,730
+care fit equations للاشكال 26 و 6 و 1 في الحالة
+
+353
+00:39:13,730 --> 00:39:19,010
+هذه بحسب ال Q بسوء 1 على 1 على 1 زائد جزر A على
+
+354
+00:39:19,010 --> 00:39:23,170
+جزر R والكف بسوء 1 زائد KT minus 1 على 1 زائد جزر
+
+355
+00:39:23,170 --> 00:39:28,940
+A على R لان جزر Aفي حالة بنج او axle loading معطب
+
+356
+00:39:28,940 --> 00:39:32,960
+العلاقة هذه it is a function of tensile strength
+
+357
+00:39:32,960 --> 00:39:37,380
+في حالة torsional loading جزر A معطب العلاقة هذه
+
+358
+00:39:37,380 --> 00:39:40,940
+يعني انت مخير يا اما تستخدم figure ستة عشرين
+
+359
+00:39:40,940 --> 00:39:45,480
+figure ستة واحد وعشرين او بتستخدم المعادلات اللي
+
+360
+00:39:45,480 --> 00:39:49,400
+هي معادلة ستة اربع تلاتين ستة تلاتين ومعادلة هذه
+
+361
+00:39:49,400 --> 00:39:55,800
+ومعادلة هذه لحساب اللي هو ال ال KF
+
+362
+00:40:03,400 --> 00:40:10,580
+الان في حالة حديد السكب ال cast iron ال cast iron
+
+363
+00:40:10,580 --> 00:40:17,220
+already ملان بالخدوش وبالتالي لما نعملوا فحص الشد
+
+364
+00:40:17,220 --> 00:40:21,220
+لل cast iron بيكون already فيه خدوش وعملين يعني it
+
+365
+00:40:21,220 --> 00:40:24,980
+is taking care of اللي هو اللي هو ال notches
+
+366
+00:40:26,300 --> 00:40:29,840
+وبالتالي إذا هو عنده عدد كبير جدا جدا من الـ
+
+367
+00:40:29,840 --> 00:40:33,620
+notches إذا اضفت one notch او two notches مش هتفرق
+
+368
+00:40:33,620 --> 00:40:37,900
+معاه it is recommended ان نستخدم في حالة ال cast
+
+369
+00:40:37,900 --> 00:40:46,860
+iron لكي يبساط one two four cast irons نشوف
+
+370
+00:40:46,860 --> 00:40:48,320
+example ستة ستة
+
+371
+00:40:53,930 --> 00:40:58,070
+استيل شافت عمود من الحديد in bending نوع ال
+
+372
+00:40:58,070 --> 00:41:03,670
+loading bending has an ultimate strength ال SUT
+
+373
+00:41:03,670 --> 00:41:07,870
+بالساوية
+
+374
+00:41:07,870 --> 00:41:13,950
+ستمية وتسعين ميجا باسكال and
+
+375
+00:41:13,950 --> 00:41:15,910
+a shoulder with a fillet radius of three
+
+376
+00:41:15,910 --> 00:41:18,550
+millimeter connecting a thirty two millimeter with
+
+377
+00:41:18,550 --> 00:41:20,590
+a thirty eight millimeter diameter يعني دي هي
+
+378
+00:41:20,590 --> 00:41:33,970
+الجاية القطر32 مسلم قطر 38 32
+
+379
+00:41:33,970 --> 00:41:50,150
+مسلم قطر على
+
+380
+00:41:50,150 --> 00:41:50,710
+الشرط
+
+381
+00:41:54,420 --> 00:42:00,620
+هذا اتنين وتلاتين ميلي مسلم
+
+382
+00:42:00,620 --> 00:42:08,540
+تمنع تلاتين ميلي و
+
+383
+00:42:08,540 --> 00:42:17,900
+الفيلتين ال radius بتاعها تلاتة ميلي متر دوران
+
+384
+00:42:17,900 --> 00:42:25,550
+estimate KF using figure ستة عشرينأولا نحسب KF
+
+385
+00:42:25,550 --> 00:42:38,450
+باستخدام figure 26 فنروح على figure 26 figure
+
+386
+00:42:38,450 --> 00:42:42,530
+26 معطيني ال notch الفلت عندى 3 ملي 3 ملي هاي 3
+
+387
+00:42:42,530 --> 00:42:46,910
+ملي 3
+
+388
+00:42:46,910 --> 00:42:48,010
+ملي هاي 3 ملي
+
+389
+00:42:56,950 --> 00:43:05,750
+طيب ال SUT 690 ميجا عندها 1.4 جيجا يعني 1400 ميجا
+
+390
+00:43:05,750 --> 00:43:11,890
+هين 1000 ميجا هين 700 ميجا و هين يعني جاية تقريبا
+
+391
+00:43:11,890 --> 00:43:21,910
+جاية هين يعني تحت شوية من ال 700 ميجا تقريبا
+
+392
+00:43:21,910 --> 00:43:23,170
+لو أمد
+
+393
+00:43:32,840 --> 00:43:41,740
+يعني تقريبا هتطلع الكيو هذه point يعني
+
+394
+00:43:41,740 --> 00:43:47,660
+تقريبا ربع المسافة هذه مثلا point 2 ربع point 2
+
+395
+00:43:47,660 --> 00:43:53,100
+point 1 point .. point كيو هتكون سواء point 8 خمسة
+
+396
+00:43:53,100 --> 00:44:02,720
+كيو بسواء point 8 خمسة طيب ال KFبساوة واحد زاد Q
+
+397
+00:44:02,720 --> 00:44:09,760
+في KT minus واحد احنا ردى حسبنا Q بساوية point
+
+398
+00:44:09,760 --> 00:44:16,060
+تمانية خمسة طيب بدى احسب ال KT احنا عندنا bending
+
+399
+00:44:16,060 --> 00:44:19,900
+بدى
+
+400
+00:44:19,900 --> 00:44:23,100
+احسب ال KT ال KT بيقدروا يروح على appendix A خمسة
+
+401
+00:44:23,100 --> 00:44:26,960
+اش هاروح على appendix A خمسة اش
+
+402
+00:44:35,070 --> 00:44:43,890
+في كتاب شجلة A15 اللي هو هذا اللي
+
+403
+00:44:43,890 --> 00:44:51,470
+مش الحالة هذه ولا هذه هتكون
+
+404
+00:44:51,470 --> 00:44:56,310
+A15 9 خانيا أكبر عليها A15 9
+
+405
+00:45:08,030 --> 00:45:18,830
+A خمساش تسعة هاد
+
+406
+00:45:18,830 --> 00:45:23,610
+ال D small هاد
+
+407
+00:45:23,610 --> 00:45:27,410
+ال D capital و هاد ال R احنا ال D small عندنا
+
+408
+00:45:27,410 --> 00:45:34,370
+اكام؟ اتنين وتلاتين و
+
+409
+00:45:34,370 --> 00:45:44,350
+ال D capital تمانية وتلاتينو ال R تلاتة ملي عن
+
+410
+00:45:44,350 --> 00:45:50,590
+المحور الأفق هنا ر على دي ر على دي ر على دي هتكون
+
+411
+00:45:50,590 --> 00:45:54,790
+تلاتة
+
+412
+00:45:54,790 --> 00:46:02,190
+على اتنين و تلاتين يعني هتكون تلاتة
+
+413
+00:46:02,190 --> 00:46:08,880
+تقصير اتنين و تلاتينبتطلع point o تسعة point o
+
+414
+00:46:08,880 --> 00:46:18,180
+تسعة تلاتة سبعة خمسة يعني يعني تقريبا هنا تقريبا
+
+415
+00:46:18,180 --> 00:46:26,180
+يعني تقريبا point one بعدين
+
+416
+00:46:26,180 --> 00:46:30,640
+بلزمنا هدول care دي capital على دي small
+
+417
+00:46:33,620 --> 00:46:37,460
+على دي small اللي هي تمانية وتلاتين على اتنين
+
+418
+00:46:37,460 --> 00:46:50,400
+وتلاتين تمانية تلاتين تطلع
+
+419
+00:46:50,400 --> 00:46:58,700
+واحد point واحد تمانية سبعة خمسةأنا عندي هنا دي
+
+420
+00:46:58,700 --> 00:47:05,100
+capital على دي تلاتة هذه واحد و نص واحد و نص هذه
+
+421
+00:47:05,100 --> 00:47:08,420
+واحد point يعني هي جاية بين ال curve التاني
+
+422
+00:47:08,420 --> 00:47:13,760
+والتالت curve التاني والتالت يعني هنكون تقريبا في
+
+423
+00:47:13,760 --> 00:47:20,280
+المنطقة هذه يعني هتكون يعني
+
+424
+00:47:20,280 --> 00:47:27,090
+عندي هنا one point fourone point six one point six
+
+425
+00:47:27,090 --> 00:47:34,210
+خمسة يعني ممكن نحكي كت كت هتكون واحد
+
+426
+00:47:34,210 --> 00:47:40,210
+point ستة خمسة اللي هو هتكون ايه خمستاش تسعة معناه
+
+427
+00:47:40,210 --> 00:47:46,490
+كف هتكون سواحه زاد كو اللي هي point تمانية خمسة في
+
+428
+00:47:46,490 --> 00:47:50,870
+كت اللي هي واحد point ستة خمسة minus واحد
+
+429
+00:47:56,110 --> 00:48:01,210
+يعني عندي one point six خمسة في point تمانية خمسة
+
+430
+00:48:01,210 --> 00:48:07,390
+ساوية زايد واحد تطلع واحد point خمسة خمسة اتنين
+
+431
+00:48:07,390 --> 00:48:14,930
+خمسة واحد خمسة خمسة اتنين خمسة يعني هذه طريقة
+
+432
+00:48:14,930 --> 00:48:20,570
+وقالية طيب انه انا احسب ان عندي bending او axle
+
+433
+00:48:20,570 --> 00:48:24,250
+يعني طريقة تانية استخدم المعادلات
+
+434
+00:48:45,950 --> 00:48:52,170
+نتذكر ان ال KT احنا
+
+435
+00:48:52,170 --> 00:49:00,630
+طلعناها 1.65 من appendix A 15 9 لان هحصل جزر A من
+
+436
+00:49:00,630 --> 00:49:07,470
+المعادلة هذه هعوض عن S U T انتبه ال S U T هنا
+
+437
+00:49:07,470 --> 00:49:10,290
+وحدات و وحدات انجليزية هتكون مع 690 ميجا بس كده
+
+438
+00:49:10,290 --> 00:49:15,220
+هحور الوحدات انجليزية بحسب الجزر ال Aبعدين بحس
+
+439
+00:49:15,220 --> 00:49:24,800
+بيجي أحكي KF بالساوية واحد
+
+440
+00:49:24,800 --> 00:49:33,980
+زاد KT minus واحد على واحد زاد الجزر التربيعي لل A
+
+441
+00:49:33,980 --> 00:49:39,500
+او انا ممكن افضل الطريقة هذه ان احس في Q
+
+442
+00:49:43,890 --> 00:49:50,030
+بالساوية واحد على واحد زي جزر ال A على جزر ال R
+
+443
+00:49:50,030 --> 00:49:56,270
+لأن جزر ال A من المعادلة هذه وال R ما هي تلاتة ملي
+
+444
+00:49:56,270 --> 00:50:04,460
+متر بعدين بحسب ال KFسواحد زاد Q في KT minus واحد
+
+445
+00:50:04,460 --> 00:50:10,960
+حصل نفس النتيجة جربه عوضه في المعدلات و طلع ال Q و
+
+446
+00:50:10,960 --> 00:50:20,760
+طلع ال KF حتى حصل نفس النتيجة تقريبا طيب
+
+447
+00:50:34,230 --> 00:50:40,390
+طيب المحاضرة الجاي بنكمل ال application of fatigue
+
+448
+00:50:40,390 --> 00:50:42,430
+stress concentration factor
+
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/5N-tCP9cvEg_raw.json b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/5N-tCP9cvEg_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..ece7bb72e9b13ce115560617b6764b3a4e6380e0
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/5N-tCP9cvEg_raw.json
@@ -0,0 +1 @@
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is rotating and not round او كان not rotating and round او كان not rotating and not round شوف مثال", "tokens": [9566, 3555, 3615, 995, 11778, 47302, 15042, 4724, 5016, 36520, 10344, 3098, 293, 19627, 34204, 8978, 11331, 6027, 3660, 16472, 3224, 25961, 2423, 12070, 3166, 307, 19627, 293, 406, 3098, 1975, 2407, 25961, 406, 19627, 293, 3098, 1975, 2407, 25961, 406, 19627, 293, 406, 3098, 13412, 38688, 50113, 6027], "avg_logprob": -0.11976562812924385, "compression_ratio": 1.606896551724138, "no_speech_prob": 0.0, "words": [{"start": 611.69, "end": 612.61, "word": "طبعا", "probability": 0.98974609375}, {"start": 612.61, "end": 613.29, "word": " دايما", "probability": 0.8391927083333334}, {"start": 613.29, "end": 613.61, "word": " بحصل", "probability": 0.7447916666666666}, {"start": 613.61, "end": 614.13, "word": " equivalent", "probability": 0.94970703125}, {"start": 614.13, "end": 614.61, "word": " round", "probability": 0.87255859375}, {"start": 614.61, "end": 614.89, "word": " and", 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0.93212890625}, {"start": 623.07, "end": 623.69, "word": " not", "probability": 0.93701171875}, {"start": 623.69, "end": 624.15, "word": " round", "probability": 0.90185546875}, {"start": 624.15, "end": 624.73, "word": " او", "probability": 0.790771484375}, {"start": 624.73, "end": 625.41, "word": " كان", "probability": 0.9736328125}, {"start": 625.41, "end": 625.67, "word": " not", "probability": 0.9375}, {"start": 625.67, "end": 626.17, "word": " rotating", "probability": 0.97021484375}, {"start": 626.17, "end": 626.59, "word": " and", "probability": 0.96826171875}, {"start": 626.59, "end": 627.03, "word": " round", "probability": 0.92822265625}, {"start": 627.03, "end": 627.61, "word": " او", "probability": 0.94775390625}, {"start": 627.61, "end": 627.85, "word": " كان", "probability": 0.9873046875}, {"start": 627.85, "end": 628.09, "word": " not", "probability": 0.96484375}, {"start": 628.09, "end": 628.47, "word": " rotating", "probability": 0.97119140625}, {"start": 628.47, "end": 628.79, "word": " and", "probability": 0.962890625}, {"start": 628.79, "end": 629.07, "word": " not", "probability": 0.96337890625}, {"start": 629.07, "end": 629.49, "word": " round", "probability": 0.9208984375}, {"start": 629.49, "end": 633.11, "word": " شوف", "probability": 0.872314453125}, {"start": 633.11, "end": 633.55, "word": " مثال", "probability": 0.918701171875}], "temperature": 1.0}, {"id": 21, "seek": 67181, "start": 655.05, "end": 671.81, "text": "a steel shaft loaded in bending عندي عمود مصنوع من الحديد ال loading عليه ال bending is 32 mm in diameter abuting a filleted shoulder 38 mm in diameter يعني أنا عندي shaft جاي زي هيك", "tokens": [64, 8269, 18467, 13210, 294, 22487, 18871, 16254, 6225, 2304, 23328, 3714, 9381, 1863, 45367, 9154, 21542, 16254, 3215, 2423, 15114, 47356, 2423, 22487, 307, 8858, 11169, 294, 14196, 410, 10861, 257, 2836, 10993, 7948, 12843, 11169, 294, 14196, 37495, 22653, 41850, 18871, 16254, 18467, 10874, 47302, 30767, 1829, 39896, 4117], 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"probability": 0.955078125}], "temperature": 1.0}, {"id": 22, "seek": 71937, "start": 699.45, "end": 719.37, "text": "هذا القطر 32 ميلي ميتا مسلم للقطر اكبر 38 ميلي ميتا", "tokens": [3224, 15730, 25062, 9566, 2288, 8858, 3714, 1829, 20292, 3714, 36081, 995, 47524, 19528, 24976, 47432, 2288, 1975, 4117, 26890, 12843, 3714, 1829, 20292, 3714, 36081, 995], "avg_logprob": -0.2767857217362949, "compression_ratio": 1.353846153846154, "no_speech_prob": 0.0, "words": [{"start": 699.45, "end": 699.77, "word": "هذا", "probability": 0.895751953125}, {"start": 699.77, "end": 700.23, "word": " القطر", "probability": 0.9728190104166666}, {"start": 700.23, "end": 702.27, "word": " 32", "probability": 0.6552734375}, {"start": 702.27, "end": 702.53, "word": " ميلي", "probability": 0.5358072916666666}, {"start": 702.53, "end": 703.33, "word": " ميتا", "probability": 0.6477864583333334}, {"start": 703.33, "end": 709.83, "word": " مسلم", "probability": 0.6920166015625}, {"start": 709.83, "end": 710.33, "word": " للقطر", "probability": 0.8497721354166666}, {"start": 710.33, "end": 710.67, "word": " اكبر", "probability": 0.7972819010416666}, {"start": 710.67, "end": 711.21, "word": " 38", "probability": 0.81396484375}, {"start": 711.21, "end": 718.97, "word": " ميلي", "probability": 0.8450520833333334}, {"start": 718.97, "end": 719.37, "word": " ميتا", "probability": 0.9353841145833334}], "temperature": 1.0}, {"id": 23, "seek": 74863, "start": 722.99, "end": 748.63, "text": "The shaft material has a mean ultimate the shaft material has a mean ultimate tensile strength of 690 MPa يعني ال SCUT بالساوية 690 ميجاباسكال estimate the size factor Kb if the shaft is used in a rotating mode", "tokens": [2278, 18467, 2527, 575, 257, 914, 9705, 264, 18467, 2527, 575, 257, 914, 9705, 10688, 794, 3800, 295, 1386, 7771, 14146, 64, 37495, 22653, 2423, 9028, 8709, 20666, 3794, 995, 2407, 10632, 1386, 7771, 3714, 1829, 7435, 16758, 32277, 4117, 6027, 12539, 264, 2744, 5952, 591, 65, 498, 264, 18467, 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0.665283203125}, {"start": 734.51, "end": 735.43, "word": " 690", "probability": 0.83349609375}, {"start": 735.43, "end": 737.65, "word": " ميجاباسكال", "probability": 0.7877720424107143}, {"start": 737.65, "end": 742.15, "word": " estimate", "probability": 0.45263671875}, {"start": 742.15, "end": 742.55, "word": " the", "probability": 0.8935546875}, {"start": 742.55, "end": 742.85, "word": " size", "probability": 0.8037109375}, {"start": 742.85, "end": 743.29, "word": " factor", "probability": 0.89697265625}, {"start": 743.29, "end": 743.83, "word": " Kb", "probability": 0.63818359375}, {"start": 743.83, "end": 745.39, "word": " if", "probability": 0.86865234375}, {"start": 745.39, "end": 745.59, "word": " the", "probability": 0.89794921875}, {"start": 745.59, "end": 745.99, "word": " shaft", "probability": 0.94677734375}, {"start": 745.99, "end": 746.33, "word": " is", "probability": 0.95654296875}, {"start": 746.33, "end": 747.27, "word": " used", "probability": 0.80224609375}, 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"word": " هتساوح", "probability": 0.7045491536458334}, {"start": 918.44, "end": 918.84, "word": " 1", "probability": 0.63720703125}, {"start": 918.84, "end": 919.7, "word": ".24", "probability": 0.97900390625}, {"start": 919.7, "end": 920.36, "word": " دي", "probability": 0.655029296875}, {"start": 920.36, "end": 920.82, "word": " equivalent", "probability": 0.974609375}], "temperature": 1.0}, {"id": 30, "seek": 93505, "start": 922.03, "end": 935.05, "text": "-0.107-0.107-0.107", "tokens": [12, 15, 13, 3279, 22, 12, 15, 13, 3279, 22, 12, 15, 13, 3279, 22], "avg_logprob": -0.5722656100988388, "compression_ratio": 1.125, "no_speech_prob": 0.0, "words": [{"start": 922.03, "end": 923.57, "word": "-0", "probability": 0.1597900390625}, {"start": 923.57, "end": 924.85, "word": ".107", "probability": 0.93017578125}, {"start": 924.85, "end": 926.93, "word": "-0", "probability": 0.4320335388183594}, {"start": 926.93, "end": 932.77, "word": ".107", "probability": 0.9150390625}, {"start": 932.77, 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"probability": 0.90380859375}, {"start": 1228.06, "end": 1228.62, "word": " بحسب", "probability": 0.8909505208333334}, {"start": 1228.62, "end": 1230.26, "word": " ال", "probability": 0.88818359375}, {"start": 1230.26, "end": 1230.5, "word": " S", "probability": 0.91845703125}, {"start": 1230.5, "end": 1230.84, "word": " T", "probability": 0.98388671875}], "temperature": 1.0}, {"id": 43, "seek": 125970, "start": 1231.94, "end": 1259.7, "text": "بعدين بحكي SE' بساوة نص ال ST و في الحالة هذه برضه بحط KD بساوة واحد حالة تالتة ال ال ال strength at room temperature ال SRT is null", "tokens": [3555, 22488, 9957, 4724, 5016, 4117, 1829, 10269, 6, 4724, 3794, 995, 2407, 3660, 8717, 9381, 2423, 4904, 4032, 8978, 21542, 6027, 3660, 29538, 4724, 43042, 3224, 4724, 5016, 9566, 591, 35, 4724, 3794, 995, 2407, 3660, 36764, 24401, 11331, 6027, 3660, 6055, 6027, 2655, 3660, 2423, 2423, 2423, 3800, 412, 1808, 4292, 2423, 20840, 51, 307, 18184], "avg_logprob": -0.2179555104950727, "compression_ratio": 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معمولها care fit من خلال polynomial من الدرجة الرابعة ال KD", "tokens": [6027, 21292, 7649, 9307, 13672, 1829, 8978, 10874, 3215, 12610, 1386, 12, 19, 3714, 25957, 12610, 11296, 1127, 3318, 9154, 16490, 1211, 6027, 26110, 9154, 32748, 47341, 3660, 34892, 16758, 27884, 2423, 591, 35], "avg_logprob": -0.25357143878936766, "compression_ratio": 1.1271186440677967, "no_speech_prob": 0.0, "words": [{"start": 1297.16, "end": 1298.02, "word": "البيانات", "probability": 0.9586181640625}, {"start": 1298.02, "end": 1298.18, "word": " اللي", "probability": 0.71240234375}, {"start": 1298.18, "end": 1298.34, "word": " في", "probability": 0.93359375}, {"start": 1298.34, "end": 1298.78, "word": " جدول", "probability": 0.98974609375}, {"start": 1298.78, "end": 1299.2, "word": " 6", "probability": 0.7138671875}, {"start": 1299.2, "end": 1299.68, "word": "-4", "probability": 0.582763671875}, {"start": 1299.68, "end": 1302.7, "word": " معمولها", "probability": 0.7049560546875}, {"start": 1302.7, "end": 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this equation بالسواء bond 9 7 5 زي bond 4 3 2 في 10 أساس 3 TF minus bond 1 1 5 في 10 أساس 5 TF تربيه ناقص bond 104 في 10 أس ناقص 8 في TF تكييب minus bond 5 9 5 في 10 أس ناقص 12 TF أس 4 لاحظوا ان TF معبر عنها بوحدة الفهرون هايت", "tokens": [271, 257, 2445, 295, 4292, 16070, 2655, 2304, 16572, 2655, 8592, 2288, 20449, 26890, 18871, 11296, 4724, 2407, 24401, 3660, 27188, 3224, 2288, 11536, 8032, 995, 36081, 2423, 591, 35, 307, 2212, 538, 341, 5367, 20666, 3794, 2407, 16606, 6086, 1722, 1614, 1025, 30767, 1829, 6086, 1017, 805, 568, 8978, 1266, 5551, 3794, 32277, 805, 40964, 3175, 6086, 502, 502, 1025, 8978, 1266, 5551, 3794, 32277, 1025, 40964, 6055, 2288, 21292, 3224, 8717, 995, 4587, 9381, 6086, 47757, 8978, 1266, 5551, 3794, 8717, 995, 4587, 9381, 1649, 8978, 40964, 6055, 4117, 1829, 1829, 3555, 3175, 6086, 1025, 1722, 1025, 8978, 1266, 5551, 3794, 8717, 995, 4587, 9381, 2272, 40964, 5551, 3794, 1017, 20193, 5016, 19913, 14407, 16472, 40964, 20449, 26890, 18871, 11296, 4724, 2407, 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"word": " و", "probability": 0.8515625}, {"start": 2085.42, "end": 2085.82, "word": " KC", "probability": 0.729248046875}, {"start": 2085.82, "end": 2086.02, "word": " و", "probability": 0.94482421875}, {"start": 2086.02, "end": 2086.34, "word": " KD", "probability": 0.9853515625}, {"start": 2086.34, "end": 2086.58, "word": " و", "probability": 0.943359375}, {"start": 2086.58, "end": 2086.84, "word": " KE", "probability": 0.82080078125}, {"start": 2086.84, "end": 2086.98, "word": " و", "probability": 0.994140625}, {"start": 2086.98, "end": 2087.24, "word": " KF", "probability": 0.964111328125}, {"start": 2087.24, "end": 2087.38, "word": " و", "probability": 0.98779296875}, {"start": 2087.38, "end": 2087.76, "word": " KFA", "probability": 0.6527099609375}, {"start": 2087.76, "end": 2088.48, "word": " قلية", "probability": 0.502197265625}, {"start": 2088.48, "end": 2089.04, "word": " حساب", "probability": 0.97265625}, {"start": 2089.04, "end": 2089.48, "word": " كل", "probability": 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0.277099609375}], "temperature": 1.0}, {"id": 74, "seek": 214566, "start": 2123.4, "end": 2145.66, "text": "و في ثقب عند ال whole عند ال whole هي مباشرة بيكون ال stress is maximum بيعلى ال stress من نتيجة تركيز الإجهاد احنا درسنا في chapter تلاتة حكينا في appendix A15 بيعطي ال geometric stress concentration factor KT في appendix A15", "tokens": [2407, 8978, 38637, 4587, 3555, 43242, 2423, 1379, 43242, 2423, 1379, 39896, 3714, 3555, 33599, 25720, 4724, 1829, 30544, 2423, 4244, 307, 6674, 4724, 40228, 23942, 2423, 4244, 9154, 8717, 31371, 7435, 3660, 6055, 31747, 1829, 11622, 33688, 7435, 11296, 3215, 1975, 5016, 8315, 11778, 2288, 3794, 8315, 8978, 7187, 6055, 1211, 9307, 3660, 11331, 4117, 1829, 8315, 8978, 34116, 970, 316, 5211, 4724, 40228, 9566, 1829, 2423, 33246, 4244, 9856, 5952, 591, 51, 8978, 34116, 970, 316, 5211], "avg_logprob": -0.19296875651925802, "compression_ratio": 1.4928909952606635, "no_speech_prob": 1.1920928955078125e-07, "words": [{"start": 2123.4, "end": 2123.66, 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" درسنا", "probability": 0.7918701171875}, {"start": 2135.78, "end": 2135.9, "word": " في", "probability": 0.4677734375}, {"start": 2135.9, "end": 2136.28, "word": " chapter", "probability": 0.51904296875}, {"start": 2136.28, "end": 2138.12, "word": " تلاتة", "probability": 0.91259765625}, {"start": 2138.12, "end": 2138.96, "word": " حكينا", "probability": 0.9888916015625}, {"start": 2138.96, "end": 2139.2, "word": " في", "probability": 0.93603515625}, {"start": 2139.2, "end": 2140.1, "word": " appendix", "probability": 0.879638671875}, {"start": 2140.1, "end": 2140.94, "word": " A15", "probability": 0.5787353515625}, {"start": 2140.94, "end": 2141.42, "word": " بيعطي", "probability": 0.9000244140625}, {"start": 2141.42, "end": 2141.56, "word": " ال", "probability": 0.884765625}, {"start": 2141.56, "end": 2141.9, "word": " geometric", "probability": 0.9208984375}, {"start": 2141.9, "end": 2142.36, "word": " stress", "probability": 0.958984375}, {"start": 2142.36, "end": 2142.9, "word": " concentration", "probability": 0.9296875}, {"start": 2142.9, "end": 2143.4, "word": " factor", "probability": 0.9326171875}, {"start": 2143.4, "end": 2143.86, "word": " KT", "probability": 0.7958984375}, {"start": 2143.86, "end": 2144.04, "word": " في", "probability": 0.9580078125}, {"start": 2144.04, "end": 2144.44, "word": " appendix", "probability": 0.95654296875}, {"start": 2144.44, "end": 2145.66, "word": " A15", "probability": 0.97998046875}], "temperature": 1.0}, {"id": 75, "seek": 216430, "start": 2146.36, "end": 2164.3, "text": "لأن احنا عندنا fatigue loading يعني ال loading is variable معناته محتاج fatigue stress concentration factor ال fatigue stress concentration factor KF معطب العلاقة واحد زاد Q في KT", "tokens": [1211, 33456, 1975, 5016, 8315, 43242, 8315, 20574, 15114, 37495, 22653, 2423, 15114, 307, 7006, 20449, 8315, 47395, 3714, 33753, 26108, 20574, 4244, 9856, 5952, 2423, 20574, 4244, 9856, 5952, 591, 37, 20449, 9566, 3555, 18863, 15040, 28671, 36764, 24401, 30767, 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{"start": 2157.86, "end": 2160.94, "word": " معطب", "probability": 0.8709309895833334}, {"start": 2160.94, "end": 2161.48, "word": " العلاقة", "probability": 0.9446614583333334}, {"start": 2161.48, "end": 2162.2, "word": " واحد", "probability": 0.802978515625}, {"start": 2162.2, "end": 2162.66, "word": " زاد", "probability": 0.828857421875}, {"start": 2162.66, "end": 2163.24, "word": " Q", "probability": 0.39892578125}, {"start": 2163.24, "end": 2163.74, "word": " في", "probability": 0.82763671875}, {"start": 2163.74, "end": 2164.3, "word": " KT", "probability": 0.91845703125}], "temperature": 1.0}, {"id": 76, "seek": 217800, "start": 2165.08, "end": 2178.0, "text": "مينص واحد او ممكن احكي كيو باسم كف مينص واحد على كتي مينص واحد في حالة اللي هو ال normal stress في حالة shear stress باسم كف اس مينص واحد على كتي اس مينص واحد", "tokens": [2304, 9957, 9381, 36764, 24401, 1975, 2407, 3714, 43020, 1975, 5016, 4117, 1829, 9122, 1829, 2407, 4724, 32277, 2304, 9122, 5172, 3714, 9957, 9381, 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"end": 2418.58, "word": " iron", "probability": 0.90283203125}, {"start": 2418.58, "end": 2419.0, "word": " بيكون", "probability": 0.8916015625}, {"start": 2419.0, "end": 2419.3, "word": " already", "probability": 0.8525390625}, {"start": 2419.3, "end": 2419.72, "word": " فيه", "probability": 0.953125}, {"start": 2419.72, "end": 2420.1, "word": " خدوش", "probability": 0.9940185546875}, {"start": 2420.1, "end": 2420.5, "word": " وعملين", "probability": 0.8968505859375}, {"start": 2420.5, "end": 2420.98, "word": " يعني", "probability": 0.750244140625}, {"start": 2420.98, "end": 2421.22, "word": " it", "probability": 0.92822265625}, {"start": 2421.22, "end": 2421.46, "word": " is", "probability": 0.8525390625}, {"start": 2421.46, "end": 2421.78, "word": " taking", "probability": 0.8310546875}, {"start": 2421.78, "end": 2422.14, "word": " care", "probability": 0.9052734375}, {"start": 2422.14, "end": 2422.48, "word": " of", "probability": 0.98095703125}, {"start": 2422.48, "end": 2422.7, "word": " اللي", "probability": 0.96337890625}, {"start": 2422.7, "end": 2423.02, "word": " هو", "probability": 0.99462890625}, {"start": 2423.02, "end": 2423.32, "word": " اللي", "probability": 0.7099609375}, {"start": 2423.32, "end": 2423.96, "word": " هو", "probability": 0.68310546875}, {"start": 2423.96, "end": 2424.5, "word": " ال", "probability": 0.83154296875}, {"start": 2424.5, "end": 2424.98, "word": " notches", "probability": 0.929931640625}], "temperature": 1.0}, {"id": 88, "seek": 244832, "start": 2426.3, "end": 2448.32, "text": "وبالتالي إذا هو عنده عدد كبير جدا جدا من الـ notches إذا اضفت one notch او two notches مش هتفرق معاه it is recommended ان نستخدم في حالة ال cast iron لكي يبساط one two four cast irons نشوف example ستة ستة", "tokens": [37746, 6027, 2655, 6027, 1829, 11933, 15730, 31439, 43242, 3224, 6225, 3215, 3215, 9122, 3555, 13546, 10874, 28259, 10874, 28259, 9154, 2423, 39184, 406, 3781, 11933, 15730, 1975, 11242, 5172, 2655, 472, 26109, 1975, 2407, 732, 406, 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" لكي", "probability": 0.6886393229166666}, {"start": 2438.76, "end": 2439.24, "word": " يبساط", "probability": 0.56695556640625}, {"start": 2439.24, "end": 2439.76, "word": " one", "probability": 0.449462890625}, {"start": 2439.76, "end": 2440.16, "word": " two", "probability": 0.477294921875}, {"start": 2440.16, "end": 2440.52, "word": " four", "probability": 0.7265625}, {"start": 2440.52, "end": 2441.18, "word": " cast", "probability": 0.7490234375}, {"start": 2441.18, "end": 2441.64, "word": " irons", "probability": 0.7098388671875}, {"start": 2441.64, "end": 2446.86, "word": " نشوف", "probability": 0.8751627604166666}, {"start": 2446.86, "end": 2447.36, "word": " example", "probability": 0.433349609375}, {"start": 2447.36, "end": 2447.86, "word": " ستة", "probability": 0.8416341145833334}, {"start": 2447.86, "end": 2448.32, "word": " ستة", "probability": 0.9505208333333334}], "temperature": 1.0}, {"id": 89, "seek": 248211, "start": 2453.93, "end": 2482.11, "text": "استيل شافت عمود من الحديد in bending نوع ال loading bending has an ultimate strength ال SUT بالساوية ستمية وتسعين ميجا باسكال and a shoulder with a fillet radius of three millimeter connecting a thirty two millimeter with a thirty eight millimeter diameter يعني دي هي الجاية القطر", "tokens": [995, 14851, 26895, 13412, 31845, 2655, 6225, 2304, 23328, 9154, 21542, 16254, 3215, 294, 22487, 8717, 45367, 2423, 15114, 22487, 575, 364, 9705, 3800, 2423, 318, 8709, 20666, 3794, 995, 2407, 10632, 8608, 39237, 10632, 34683, 3794, 3615, 9957, 3714, 1829, 7435, 995, 4724, 32277, 4117, 6027, 293, 257, 7948, 365, 257, 2836, 302, 15845, 295, 1045, 17942, 11015, 257, 11790, 732, 17942, 365, 257, 11790, 3180, 17942, 14196, 37495, 22653, 11778, 1829, 39896, 25724, 995, 10632, 25062, 9566, 2288], "avg_logprob": -0.2876157525144977, "compression_ratio": 1.5344827586206897, "no_speech_prob": 0.0, "words": [{"start": 2453.93, "end": 2454.49, "word": "استيل", "probability": 0.53955078125}, {"start": 2454.49, "end": 2454.89, 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"end": 2474.97, "word": " with", "probability": 0.931640625}, {"start": 2474.97, "end": 2475.11, "word": " a", "probability": 0.9619140625}, {"start": 2475.11, "end": 2475.35, "word": " fillet", "probability": 0.648193359375}, {"start": 2475.35, "end": 2475.59, "word": " radius", "probability": 0.93017578125}, {"start": 2475.59, "end": 2475.71, "word": " of", "probability": 0.9599609375}, {"start": 2475.71, "end": 2475.91, "word": " three", "probability": 0.81103515625}, {"start": 2475.91, "end": 2476.37, "word": " millimeter", "probability": 0.374267578125}, {"start": 2476.37, "end": 2476.97, "word": " connecting", "probability": 0.861328125}, {"start": 2476.97, "end": 2477.21, "word": " a", "probability": 0.94140625}, {"start": 2477.21, "end": 2477.43, "word": " thirty", "probability": 0.5341796875}, {"start": 2477.43, "end": 2477.63, "word": " two", "probability": 0.70068359375}, {"start": 2477.63, "end": 2478.13, "word": " millimeter", "probability": 0.85009765625}, {"start": 2478.13, "end": 2478.55, "word": " with", "probability": 0.91357421875}, {"start": 2478.55, "end": 2478.75, "word": " a", "probability": 0.91357421875}, {"start": 2478.75, "end": 2478.97, "word": " thirty", "probability": 0.73828125}, {"start": 2478.97, "end": 2479.27, "word": " eight", "probability": 0.80078125}, {"start": 2479.27, "end": 2479.73, "word": " millimeter", "probability": 0.83984375}, {"start": 2479.73, "end": 2480.07, "word": " diameter", "probability": 0.927734375}, {"start": 2480.07, "end": 2480.25, "word": " يعني", "probability": 0.83447265625}, {"start": 2480.25, "end": 2480.41, "word": " دي", "probability": 0.919921875}, {"start": 2480.41, "end": 2480.59, "word": " هي", "probability": 0.70068359375}, {"start": 2480.59, "end": 2481.73, "word": " الجاية", "probability": 0.5895182291666666}, {"start": 2481.73, "end": 2482.11, "word": " القطر", "probability": 0.9700520833333334}], "temperature": 1.0}, {"id": 90, "seek": 251071, "start": 2483.39, "end": 2510.71, "text": "32 مسلم قطر 38 32 مسلم قطر على الشرط", "tokens": [11440, 47524, 19528, 12174, 9566, 2288, 12843, 8858, 47524, 19528, 12174, 9566, 2288, 15844, 25124, 2288, 9566], "avg_logprob": -0.203016491399871, "compression_ratio": 1.1372549019607843, "no_speech_prob": 0.0, "words": [{"start": 2483.39, "end": 2484.25, "word": "32", "probability": 0.289306640625}, {"start": 2484.25, "end": 2485.97, "word": " مسلم", "probability": 0.765380859375}, {"start": 2485.97, "end": 2486.47, "word": " قطر", "probability": 0.9270833333333334}, {"start": 2486.47, "end": 2489.37, "word": " 38", "probability": 0.783203125}, {"start": 2489.37, "end": 2493.97, "word": " 32", "probability": 0.8857421875}, {"start": 2493.97, "end": 2496.39, "word": " مسلم", "probability": 0.962158203125}, {"start": 2496.39, "end": 2497.23, "word": " قطر", "probability": 0.9168294270833334}, {"start": 2497.23, "end": 2510.15, "word": " على", "probability": 0.9287109375}, {"start": 2510.15, "end": 2510.71, "word": " الشرط", "probability": 0.8502604166666666}], "temperature": 1.0}, {"id": 91, "seek": 254267, "start": 2514.42, "end": 2542.68, "text": "هذا اتنين وتلاتين ميلي مسلم تمنع تلاتين ميلي و الفيلتين ال radius بتاعها تلاتة ميلي متر دوران estimate KF using figure ستة عشرين", "tokens": [3224, 15730, 1975, 2655, 1863, 9957, 34683, 1211, 9307, 9957, 3714, 1829, 20292, 47524, 19528, 6055, 27842, 3615, 6055, 1211, 9307, 9957, 3714, 1829, 20292, 4032, 27188, 26895, 2655, 9957, 2423, 15845, 39894, 45761, 11296, 6055, 1211, 9307, 3660, 3714, 1829, 20292, 44650, 2288, 11778, 13063, 7649, 12539, 591, 37, 1228, 2573, 8608, 2655, 3660, 6225, 46309, 9957], "avg_logprob": -0.32070974980370476, "compression_ratio": 1.4785714285714286, "no_speech_prob": 0.0, "words": [{"start": 2514.42, "end": 2514.72, "word": "هذا", "probability": 0.6063232421875}, {"start": 2514.72, "end": 2514.92, "word": " اتنين", "probability": 0.733123779296875}, {"start": 2514.92, "end": 2515.38, "word": " وتلاتين", "probability": 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0.7994791666666666}, {"start": 2951.49, "end": 2951.89, "word": " الجزر", "probability": 0.96484375}, {"start": 2951.89, "end": 2952.07, "word": " ال", "probability": 0.78662109375}, {"start": 2952.07, "end": 2952.31, "word": " A", "probability": 0.93798828125}], "temperature": 1.0}, {"id": 105, "seek": 297950, "start": 2953.66, "end": 2979.5, "text": "بعدين بحس بيجي أحكي KF بالساوية واحد زاد KT minus واحد على واحد زاد الجزر التربيعي لل A او انا ممكن افضل الطريقة هذه ان احس في Q", "tokens": [3555, 22488, 9957, 4724, 5016, 3794, 4724, 1829, 7435, 1829, 5551, 5016, 4117, 1829, 591, 37, 20666, 3794, 995, 2407, 10632, 36764, 24401, 30767, 18513, 591, 51, 3175, 36764, 24401, 15844, 36764, 24401, 30767, 18513, 25724, 11622, 2288, 16712, 2288, 21292, 3615, 1829, 24976, 316, 1975, 2407, 1975, 8315, 3714, 43020, 1975, 5172, 11242, 1211, 41950, 16572, 28671, 29538, 16472, 1975, 5016, 3794, 8978, 1249], "avg_logprob": -0.22928503200863348, "compression_ratio": 1.4342105263157894, "no_speech_prob": 0.0, "words": [{"start": 2953.66, "end": 2954.46, "word": "بعدين", "probability": 0.9407552083333334}, {"start": 2954.46, "end": 2955.22, "word": " بحس", "probability": 0.69921875}, {"start": 2955.22, "end": 2955.52, "word": " بيجي", "probability": 0.7303466796875}, {"start": 2955.52, "end": 2955.9, "word": " أحكي", "probability": 0.939697265625}, {"start": 2955.9, "end": 2957.86, "word": " KF", "probability": 0.438232421875}, {"start": 2957.86, "end": 2959.54, "word": " بالساوية", "probability": 0.68017578125}, {"start": 2959.54, "end": 2964.8, "word": " واحد", "probability": 0.77490234375}, {"start": 2964.8, "end": 2965.6, "word": " زاد", "probability": 0.7822265625}, {"start": 2965.6, "end": 2966.26, "word": " KT", "probability": 0.883544921875}, {"start": 2966.26, "end": 2967.4, "word": " minus", "probability": 0.427734375}, {"start": 2967.4, "end": 2968.06, "word": " واحد", "probability": 0.965576171875}, {"start": 2968.06, "end": 2969.36, "word": " على", "probability": 0.6220703125}, {"start": 2969.36, "end": 2969.88, "word": " واحد", "probability": 0.980224609375}, {"start": 2969.88, "end": 2970.66, "word": " زاد", "probability": 0.963623046875}, {"start": 2970.66, "end": 2972.62, "word": " الجزر", "probability": 0.9571940104166666}, {"start": 2972.62, "end": 2973.3, "word": " التربيعي", "probability": 0.83564453125}, {"start": 2973.3, "end": 2973.64, "word": " لل", "probability": 0.79541015625}, {"start": 2973.64, "end": 2973.98, "word": " A", "probability": 0.572265625}, {"start": 2973.98, "end": 2976.04, "word": " او", "probability": 0.762451171875}, {"start": 2976.04, "end": 2976.58, "word": " انا", "probability": 0.91748046875}, {"start": 2976.58, "end": 2976.78, "word": " ممكن", "probability": 0.971435546875}, {"start": 2976.78, "end": 2977.12, "word": " افضل", "probability": 0.8192138671875}, {"start": 2977.12, "end": 2977.44, "word": " الطريقة", "probability": 0.943359375}, {"start": 2977.44, "end": 2977.8, "word": " هذه", "probability": 0.76318359375}, {"start": 2977.8, "end": 2978.74, "word": " ان", "probability": 0.80126953125}, {"start": 2978.74, "end": 2979.0, "word": " احس", "probability": 0.7347819010416666}, {"start": 2979.0, "end": 2979.14, "word": " في", "probability": 0.7431640625}, {"start": 2979.14, "end": 2979.5, "word": " Q", "probability": 0.86376953125}], "temperature": 1.0}, {"id": 106, "seek": 299879, "start": 2983.89, "end": 2998.79, "text": "بالساوية واحد على واحد زي جزر ال A على جزر ال R لأن جزر ال A من المعادلة هذه وال R ما هي تلاتة ملي متر بعدين بحسب ال KF", "tokens": [3555, 6027, 3794, 995, 2407, 10632, 36764, 24401, 15844, 36764, 24401, 30767, 1829, 10874, 11622, 2288, 2423, 316, 15844, 10874, 11622, 2288, 2423, 497, 5296, 33456, 10874, 11622, 2288, 2423, 316, 9154, 9673, 3615, 18513, 37977, 29538, 16070, 497, 19446, 39896, 6055, 1211, 9307, 3660, 3714, 20292, 44650, 2288, 39182, 9957, 4724, 5016, 35457, 2423, 591, 37], "avg_logprob": -0.21363147065557284, "compression_ratio": 1.5859375, "no_speech_prob": 4.887580871582031e-06, "words": [{"start": 2983.8899999999994, "end": 2984.6899999999996, "word": "بالساوية", "probability": 0.7562662760416666}, {"start": 2984.6899999999996, "end": 2985.49, "word": " واحد", "probability": 0.771240234375}, {"start": 2985.49, "end": 2986.59, "word": " على", "probability": 0.62353515625}, {"start": 2986.59, "end": 2987.03, "word": " واحد", "probability": 0.9716796875}, {"start": 2987.03, "end": 2987.25, "word": " زي", "probability": 0.663330078125}, {"start": 2987.25, "end": 2987.65, "word": " جزر", "probability": 0.8134765625}, {"start": 2987.65, "end": 2987.81, "word": " ال", "probability": 0.9013671875}, {"start": 2987.81, "end": 2988.09, "word": " A", "probability": 0.43798828125}, {"start": 2988.09, "end": 2989.23, "word": " على", "probability": 0.6650390625}, {"start": 2989.23, "end": 2989.63, "word": " جزر", "probability": 0.99169921875}, {"start": 2989.63, "end": 2989.77, "word": " ال", "probability": 0.95751953125}, {"start": 2989.77, "end": 2990.03, "word": " R", "probability": 0.943359375}, {"start": 2990.03, "end": 2991.05, "word": " لأن", "probability": 0.645263671875}, {"start": 2991.05, "end": 2991.35, "word": " جزر", "probability": 0.9830729166666666}, {"start": 2991.35, "end": 2991.49, "word": " ال", "probability": 0.9541015625}, {"start": 2991.49, "end": 2991.77, "word": " A", "probability": 0.9814453125}, {"start": 2991.77, "end": 2993.49, "word": " من", "probability": 0.9697265625}, {"start": 2993.49, "end": 2994.01, "word": " المعادلة", "probability": 0.968017578125}, {"start": 2994.01, "end": 2994.45, "word": " هذه", "probability": 0.84765625}, {"start": 2994.45, "end": 2995.23, "word": " وال", "probability": 0.64013671875}, {"start": 2995.23, "end": 2995.45, "word": " R", "probability": 0.5390625}, {"start": 2995.45, "end": 2995.55, "word": " ما", "probability": 0.796875}, {"start": 2995.55, "end": 2995.71, "word": " هي", "probability": 0.79638671875}, {"start": 2995.71, "end": 2996.11, "word": " تلاتة", "probability": 0.889892578125}, {"start": 2996.11, "end": 2996.27, "word": " ملي", "probability": 0.711181640625}, {"start": 2996.27, "end": 2996.71, "word": " متر", "probability": 0.7169189453125}, {"start": 2996.71, "end": 2997.51, "word": " بعدين", "probability": 0.70947265625}, {"start": 2997.51, "end": 2997.91, "word": " بحسب", "probability": 0.9803059895833334}, {"start": 2997.91, "end": 2998.11, "word": " ال", "probability": 0.70849609375}, {"start": 2998.11, "end": 2998.79, "word": " KF", "probability": 0.795654296875}], "temperature": 1.0}, {"id": 107, "seek": 302076, "start": 2999.66, "end": 3020.76, "text": "سواحد زاد Q في KT minus واحد حصل نفس النتيجة جربه عوضه في المعدلات و طلع ال Q و طلع ال KF حتى حصل نفس النتيجة تقريبا طيب", "tokens": [3794, 14407, 24401, 30767, 18513, 1249, 8978, 591, 51, 3175, 36764, 24401, 11331, 36520, 8717, 36178, 28239, 31371, 7435, 3660, 10874, 25513, 3224, 6225, 2407, 11242, 3224, 8978, 9673, 22488, 1211, 9307, 4032, 23032, 1211, 3615, 2423, 1249, 4032, 23032, 1211, 3615, 2423, 591, 37, 11331, 49975, 11331, 36520, 8717, 36178, 28239, 31371, 7435, 3660, 6055, 4587, 16572, 3555, 995, 23032, 1829, 3555], "avg_logprob": -0.2418212906923145, "compression_ratio": 1.5303030303030303, "no_speech_prob": 4.76837158203125e-07, "words": [{"start": 2999.66, "end": 3000.54, "word": "سواحد", "probability": 0.5676676432291666}, {"start": 3000.54, "end": 3001.0, "word": " زاد", "probability": 0.70458984375}, {"start": 3001.0, "end": 3001.44, "word": " Q", "probability": 0.2578125}, {"start": 3001.44, "end": 3002.38, "word": " في", "probability": 0.71484375}, {"start": 3002.38, "end": 3002.9, "word": " KT", "probability": 0.766357421875}, {"start": 3002.9, "end": 3004.0, "word": " minus", "probability": 0.289794921875}, {"start": 3004.0, "end": 3004.46, "word": " واحد", "probability": 0.893798828125}, {"start": 3004.46, "end": 3005.34, "word": " حصل", "probability": 0.90966796875}, {"start": 3005.34, "end": 3005.66, "word": " نفس", "probability": 0.805419921875}, {"start": 3005.66, "end": 3006.3, "word": " النتيجة", "probability": 0.9530029296875}, {"start": 3006.3, "end": 3007.48, "word": " جربه", "probability": 0.8544921875}, {"start": 3007.48, "end": 3008.34, "word": " عوضه", "probability": 0.76953125}, {"start": 3008.34, "end": 3008.42, "word": " في", "probability": 0.892578125}, {"start": 3008.42, "end": 3009.04, "word": " المعدلات", "probability": 0.88720703125}, {"start": 3009.04, "end": 3009.94, "word": " و", "probability": 0.97607421875}, {"start": 3009.94, "end": 3010.26, "word": " طلع", "probability": 0.8416341145833334}, {"start": 3010.26, "end": 3010.44, "word": " ال", "probability": 0.7470703125}, {"start": 3010.44, "end": 3010.76, "word": " Q", "probability": 0.52587890625}, {"start": 3010.76, "end": 3010.96, "word": " و", "probability": 0.955078125}, {"start": 3010.96, "end": 3011.14, "word": " طلع", "probability": 0.8728841145833334}, {"start": 3011.14, "end": 3011.24, "word": " ال", "probability": 0.88916015625}, {"start": 3011.24, "end": 3011.56, "word": " KF", "probability": 0.9267578125}, {"start": 3011.56, "end": 3011.78, "word": " حتى", "probability": 0.745849609375}, {"start": 3011.78, "end": 3011.92, "word": " حصل", "probability": 0.60198974609375}, {"start": 3011.92, "end": 3012.22, "word": " نفس", "probability": 0.94140625}, {"start": 3012.22, "end": 3012.66, "word": " النتيجة", "probability": 0.963134765625}, {"start": 3012.66, "end": 3013.36, "word": " تقريبا", "probability": 0.99189453125}, {"start": 3013.36, "end": 3020.76, "word": " طيب", "probability": 0.9283854166666666}], "temperature": 1.0}, {"id": 108, "seek": 304243, "start": 3034.23, "end": 3042.43, "text": "طيب المحاضرة الجاي بنكمل ال application of fatigue stress concentration factor", "tokens": [9566, 1829, 3555, 9673, 5016, 46958, 25720, 25724, 47302, 44945, 24793, 1211, 2423, 3861, 295, 20574, 4244, 9856, 5952], "avg_logprob": -0.12275391221046447, "compression_ratio": 1.074468085106383, "no_speech_prob": 4.291534423828125e-06, "words": [{"start": 3034.2299999999996, "end": 3035.1099999999997, "word": "طيب", "probability": 0.98583984375}, {"start": 3035.1099999999997, "end": 3035.99, "word": " المحاضرة", "probability": 0.951904296875}, {"start": 3035.99, "end": 3036.43, "word": " الجاي", "probability": 0.775146484375}, {"start": 3036.43, "end": 3038.93, "word": " بنكمل", "probability": 0.9093424479166666}, {"start": 3038.93, "end": 3039.19, "word": " ال", "probability": 0.5693359375}, {"start": 3039.19, "end": 3039.75, "word": " application", "probability": 0.96533203125}, {"start": 3039.75, "end": 3040.07, "word": " of", "probability": 0.97900390625}, {"start": 3040.07, "end": 3040.39, "word": " fatigue", "probability": 0.9453125}, {"start": 3040.39, "end": 3040.79, "word": " stress", "probability": 0.7373046875}, {"start": 3040.79, "end": 3041.73, "word": " concentration", "probability": 0.92333984375}, {"start": 3041.73, "end": 3042.43, "word": " factor", "probability": 0.89013671875}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 3043.2305, "duration_after_vad": 2602.9943749999875}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/5N-tCP9cvEg_raw.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/5N-tCP9cvEg_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..3bc07dc047d430171548c898684c3168da67e85d
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/5N-tCP9cvEg_raw.srt
@@ -0,0 +1,1804 @@
+1
+00:00:04,890 --> 00:00:07,490
+بسم الله الرحمن الرحيم السلام عليكم و رحمة الله
+
+2
+00:00:07,490 --> 00:00:12,670
+المحاضرة اللى فاتت احنا بدأنا اللى هو ال fatigue
+
+3
+00:00:12,670 --> 00:00:16,230
+design for variable loading او fatigue failure for
+
+4
+00:00:16,230 --> 00:00:21,310
+variable loading حكينا اتعرفنا على ال S-N diagram
+
+5
+00:00:21,310 --> 00:00:26,090
+عملنا
+
+6
+00:00:26,090 --> 00:00:28,990
+definitions او تعريفات لل endurance limit حكينا ال
+
+7
+00:00:28,990 --> 00:00:31,710
+endurance limit هي ال stress level below which
+
+8
+00:00:48,600 --> 00:00:53,800
+طيب في عندي حالات لأن ال software انا بحكي على
+
+9
+00:00:53,800 --> 00:01:01,680
+mechanical part بدور و مقطع مدور بدور و مقطع مدور
+
+10
+00:01:01,680 --> 00:01:09,240
+طيب في حالتين او اكتر ممكن يكون المقطع مش مدور و
+
+11
+00:01:09,240 --> 00:01:15,460
+بدور او المقطع
+
+12
+00:01:15,460 --> 00:01:23,950
+مدوروبدورش أو المقطع مش مدور وبدورش يعني عندي تلت
+
+13
+00:01:23,950 --> 00:01:38,450
+احتمالات انه يعني ال part is واحد rotating و
+
+14
+00:01:38,450 --> 00:01:45,130
+round هذا خلصنا منها حالة تانية rotating
+
+15
+00:01:49,820 --> 00:01:58,000
+and not round مش مدور الحالة
+
+16
+00:01:58,000 --> 00:02:08,600
+التالتة not rotating و
+
+17
+00:02:08,600 --> 00:02:14,180
+مدور الحالة
+
+18
+00:02:14,180 --> 00:02:24,890
+الرابعةاللي هي not rotating و
+
+19
+00:02:24,890 --> 00:02:33,050
+not round الآن
+
+20
+00:02:33,050 --> 00:02:37,790
+الحالة التانية
+
+21
+00:02:37,790 --> 00:02:44,870
+والتالتة والرابعة هدول في الحالة هذه بدي
+
+22
+00:02:44,870 --> 00:02:45,790
+أوجد equivalent
+
+23
+00:02:54,700 --> 00:03:02,060
+round and rotating specimen
+
+24
+00:03:02,060 --> 00:03:14,720
+or part الآن
+
+25
+00:03:14,720 --> 00:03:19,840
+ال equivalent round and rotating specimen is found
+
+26
+00:03:19,840 --> 00:03:24,180
+based on this principleال volume of material
+
+27
+00:03:24,180 --> 00:03:31,280
+stressed at and above 5% of maximum stress يعني لو
+
+28
+00:03:31,280 --> 00:03:39,960
+عندى إشي under بدورش و مدور هي مدور و
+
+29
+00:03:39,960 --> 00:03:49,540
+بدورش لإن ال stress distribution هيكون بالشكل هذا
+
+30
+00:04:05,610 --> 00:04:11,350
+هذا ال stress distribution باخد
+
+31
+00:04:11,350 --> 00:04:14,650
+ال mechanical part و باخد الجزء الأخير الحلقة
+
+32
+00:04:14,650 --> 00:04:15,790
+الأخرانية
+
+33
+00:04:33,120 --> 00:04:42,580
+عند هذه ال maximum stress هذا sigma maximum باخد
+
+34
+00:04:42,580 --> 00:04:52,560
+عند location بيتمثل 95% من sigma maximum بتكون ال
+
+35
+00:04:52,560 --> 00:04:53,580
+area هذه تقريبا
+
+36
+00:05:17,520 --> 00:05:26,440
+ال volume بتاع الحلقة هذه بأسوي ل same volume in
+
+37
+00:05:26,440 --> 00:05:36,480
+rotating beam specimen طبعا هذا non rotating بأسوي
+
+38
+00:05:36,480 --> 00:05:42,960
+ال volume هذا ل same volume في حالة rotating beam
+
+39
+00:05:42,960 --> 00:05:43,780
+specimen
+
+40
+00:05:46,880 --> 00:05:51,320
+الان لو العينة طولها متر و ال mechanical part
+
+41
+00:05:51,320 --> 00:05:55,180
+الحقيقه طوله متر المتر مع متر بلغه بيظل معناته
+
+42
+00:05:55,180 --> 00:06:01,260
+اللي اللي هي ال a ninety five ال a point nine five
+
+43
+00:06:01,260 --> 00:06:08,860
+sigma مش هخش في تفاصيل اشتقاق تاعها الان a point
+
+44
+00:06:08,860 --> 00:06:15,050
+ninety five for a rotatingfor a rotating ground
+
+45
+00:06:15,050 --> 00:06:21,350
+specimen مطابل علاقة هذه بصوت point o766d تربيع
+
+46
+00:06:21,350 --> 00:06:27,290
+الان لو أخدت non
+
+47
+00:06:27,290 --> 00:06:31,730
+rotating ground هتكون تسمع non rotating ground
+
+48
+00:06:31,730 --> 00:06:34,730
+هتكون ال a point nine nine point nine five sigma
+
+49
+00:06:34,730 --> 00:06:45,110
+بصوت point o146 لو سويت هذه اللي هي point o1 O 4 6
+
+50
+00:06:45,110 --> 00:06:52,030
+D2 سويتها للمعادلة السابقة اللي
+
+51
+00:06:52,030 --> 00:07:00,050
+هتكون point O 7 6 6 D equivalent دي تربيع هو ان
+
+52
+00:07:00,050 --> 00:07:06,390
+انا بحسب ال D equivalent في
+
+53
+00:07:06,390 --> 00:07:12,000
+الحالة ال D equivalent هتطلع بالساعة point 3 7سفر
+
+54
+00:07:12,000 --> 00:07:19,200
+D في
+
+55
+00:07:19,200 --> 00:07:27,060
+حالة مقطع مستطيل يعني مش مدور أو بدورش هتكون ال A
+
+56
+00:07:27,060 --> 00:07:31,680
+point nine five بالساعة point O ال A في حالة مقطع
+
+57
+00:07:31,680 --> 00:07:36,560
+مستطيل اللي
+
+58
+00:07:36,560 --> 00:07:49,160
+هي Bبتكون ال a point 95 سبب point o 5h في b هذه
+
+59
+00:07:49,160 --> 00:07:55,320
+هسويها لل a point 95 ل
+
+60
+00:07:55,320 --> 00:08:00,340
+rotating ground specifically point o 766 دي
+
+61
+00:08:00,340 --> 00:08:03,080
+equivalent ومن هنا بحسب ال d equivalent تطلع
+
+62
+00:08:03,080 --> 00:08:06,900
+المعادلة هذه point 88hb أص نص
+
+63
+00:08:10,050 --> 00:08:15,970
+تابر ستة تلاتة بيعطينا بيعطينا ال a point تسعة
+
+64
+00:08:15,970 --> 00:08:21,330
+خمسة sigma و ال D equivalent ل different cross
+
+65
+00:08:21,330 --> 00:08:25,670
+sections يعني ال cross section ده مدور و منه بحسب
+
+66
+00:08:25,670 --> 00:08:27,970
+ال D equivalent to seven point three seven D هذا
+
+67
+00:08:27,970 --> 00:08:32,450
+المقطع مستطيل B في H و منه بحسب ال D equivalent to
+
+68
+00:08:32,450 --> 00:08:37,090
+seven point eight O تمانية جزر تربيعي ل H في B
+
+69
+00:08:37,090 --> 00:08:39,110
+طبعا في مقاطع تانية
+
+70
+00:08:42,310 --> 00:08:47,370
+لو كان عندى I beam ال A point تسعة خمسة بتختلف
+
+71
+00:08:47,370 --> 00:08:52,250
+بحسب المحور ال axis ال axis واحد واحد بتكون ال A
+
+72
+00:08:52,250 --> 00:08:57,910
+point nine five اللي هي point واحد في A TF ال A
+
+73
+00:08:57,910 --> 00:09:06,690
+اللي هي هدى هدى A هدى B و TF اللي هي هدى و هدى
+
+74
+00:09:06,690 --> 00:09:13,740
+axis اتنين اتنينهذا axis 1 1 إذا ال axis 1 1 بتكون
+
+75
+00:09:13,740 --> 00:09:19,440
+ال a.95 بيساو 0.1 atf إذا ال axis 2 2 بتكون ال a
+
+76
+00:09:19,440 --> 00:09:27,860
+.95 بيساو 0.05b في a في حالة ال channel طبعا هذا
+
+77
+00:09:27,860 --> 00:09:35,160
+ال axis 1 1 وهذا ال axis 2 2 هذا b
+
+78
+00:09:40,140 --> 00:09:45,640
+وهذه a ال a point nine five ل axis واحد واحد
+
+79
+00:09:45,640 --> 00:09:49,500
+بتساوي point o خمسة a b وال a point nine five
+
+80
+00:09:49,500 --> 00:09:54,080
+بتساوي point o خمسة اتنين x في a زي ال point واحد
+
+81
+00:09:54,080 --> 00:09:56,620
+TF في b minus x، x اللي هي هذه المسافة
+
+82
+00:10:11,690 --> 00:10:15,450
+طبعا دايما بحصل equivalent round and rotating
+
+83
+00:10:15,450 --> 00:10:22,270
+specimen في حالة انه كان ال mechanical parts is
+
+84
+00:10:22,270 --> 00:10:26,590
+rotating and not round او كان not rotating and
+
+85
+00:10:26,590 --> 00:10:33,110
+round او كان not rotating and not round شوف
+
+86
+00:10:33,110 --> 00:10:33,550
+مثال
+
+87
+00:10:55,050 --> 00:10:59,290
+a steel shaft loaded in bending عندي عمود مصنوع من
+
+88
+00:10:59,290 --> 00:11:03,590
+الحديد ال loading عليه ال bending is 32 mm in
+
+89
+00:11:03,590 --> 00:11:07,130
+diameter abuting a filleted shoulder 38 mm in
+
+90
+00:11:07,130 --> 00:11:11,810
+diameter يعني أنا عندي shaft جاي زي هيك
+
+91
+00:11:39,450 --> 00:11:49,830
+هذا القطر 32 ميلي ميتا مسلم
+
+92
+00:11:49,830 --> 00:11:58,970
+للقطر اكبر 38 ميلي
+
+93
+00:11:58,970 --> 00:11:59,370
+ميتا
+
+94
+00:12:02,990 --> 00:12:06,550
+The shaft material has a mean ultimate the shaft
+
+95
+00:12:06,550 --> 00:12:09,290
+material has a mean ultimate tensile strength of
+
+96
+00:12:09,290 --> 00:12:17,650
+690 MPa يعني ال SCUT بالساوية 690 ميجاباسكال
+
+97
+00:12:17,650 --> 00:12:22,150
+estimate
+
+98
+00:12:22,150 --> 00:12:27,870
+the size factor Kb if the shaft is used in a
+
+99
+00:12:27,870 --> 00:12:28,630
+rotating mode
+
+100
+00:12:34,640 --> 00:12:44,000
+if shaft is rotating معناته
+
+101
+00:12:44,000 --> 00:12:53,620
+اذا ال shaft is rotating ال
+
+102
+00:12:53,620 --> 00:13:00,060
+KB في الحالة هذه ال
+
+103
+00:13:00,060 --> 00:13:00,480
+KB
+
+104
+00:13:05,010 --> 00:13:09,550
+لحظة القطرة اللي عندك هيكون 32 ال 32 هتكون
+
+105
+00:13:09,550 --> 00:13:13,610
+المعادلة هذه اللي هو هتكون KB هتكون ساعة واحد
+
+106
+00:13:13,610 --> 00:13:20,430
+point اتنين اربعة D اصلاقص point واحد او سبن
+
+107
+00:13:20,430 --> 00:13:26,630
+هتساوي واحد point اتنين اربعة في D اللي هي 32
+
+108
+00:13:26,630 --> 00:13:31,010
+اصلاقص minus point واحد او سبن
+
+109
+00:13:35,360 --> 00:13:43,740
+هتكون اتنين و تلاتين اص minus point one oh seven
+
+110
+00:13:43,740 --> 00:13:51,900
+هتكون في واحد point اتنين اربع هتطلع point تمانية
+
+111
+00:13:51,900 --> 00:13:58,880
+خمسة ستة هذا
+
+112
+00:13:58,880 --> 00:14:05,770
+في حالة ال shaft is rotatingطيب إذا ال shaft is
+
+113
+00:14:05,770 --> 00:14:15,210
+not rotating if shaft is
+
+114
+00:14:15,210 --> 00:14:22,610
+not rotating معناته مطلوب مني أحسب equivalent
+
+115
+00:14:22,610 --> 00:14:28,270
+round rotating specimen يعني هستخدم المعادلة
+
+116
+00:14:32,200 --> 00:14:39,300
+اللي هي DE دي equivalent هتساوي
+
+117
+00:14:39,300 --> 00:14:48,040
+point تلاتة سبعة دي هتساوي point تلاتة سبعة في
+
+118
+00:14:48,040 --> 00:14:57,300
+اتنين و تلاتين هيطلع
+
+119
+00:14:57,300 --> 00:14:57,680
+عندى
+
+120
+00:15:00,840 --> 00:15:12,100
+11.84 11.84 مليمتر once اعرفت ال equivalent
+
+121
+00:15:12,100 --> 00:15:23,570
+diameter بحسب ال KB هتساوح 1.24 دي equivalent-0
+
+122
+00:15:23,570 --> 00:15:32,770
+.107-0.107
+
+123
+00:15:32,770 --> 00:15:35,050
+-0.107
+
+124
+00:15:46,010 --> 00:15:53,450
+-0.107×1.24 كيبيا هتكون 0.952
+
+125
+00:16:11,000 --> 00:16:14,400
+نجي لل modification factor التالت اللي هو ال
+
+126
+00:16:14,400 --> 00:16:30,020
+loading factor KC ال
+
+127
+00:16:30,020 --> 00:16:35,340
+loading factor KC بياخد في عين الاعتبار التغيرات
+
+128
+00:16:35,340 --> 00:16:38,920
+في ال endurance limitالناتجة عن تغيير نوع ال
+
+129
+00:16:38,920 --> 00:16:44,380
+loading احنا حكينا ال standard fatigue specimen
+
+130
+00:16:44,380 --> 00:16:50,220
+بيصير ل completely reverse bending load لكن على
+
+131
+00:16:50,220 --> 00:16:56,570
+أرض الواقع يمكن تكون ال load axial loadممكن تورج
+
+132
+00:16:56,570 --> 00:17:01,490
+ال load ممكن bending ممكن transverse shear load
+
+133
+00:17:01,490 --> 00:17:05,910
+ممكن any combination المعادلة اللي هتشوفوها اللي
+
+134
+00:17:05,910 --> 00:17:12,370
+هي الان معدلة 626 نستخدمها في حالة single load
+
+135
+00:17:12,370 --> 00:17:18,910
+type يعني بيكون القطع الميكانيكية متعرضة لنوع محدد
+
+136
+00:17:18,910 --> 00:17:25,450
+او نوع واحد من التحميل ممكن يكون ال loadAxial أو
+
+137
+00:17:25,450 --> 00:17:28,090
+Bending أو Torsion
+
+138
+00:17:29,980 --> 00:17:32,620
+في الحالة دي بس أخد المعادلة ده إذا كان bending ما
+
+139
+00:17:32,620 --> 00:17:35,360
+هو أساسا ال standard bending معناته ال Kc هكون
+
+140
+00:17:35,360 --> 00:17:39,740
+الساعة واحد إذا كان axle Kc بيساوي 0.85 إذا كان ال
+
+141
+00:17:39,740 --> 00:17:43,320
+torsion Kc بيساوي 0.59 لكن إذا كان عندي
+
+142
+00:17:43,320 --> 00:17:46,960
+combination of loading يعني كان خلطة عندي axle مع
+
+143
+00:17:46,960 --> 00:17:51,360
+.. مع .. مع bending مع torsion بستخدم ما يسمى
+
+144
+00:17:51,360 --> 00:17:54,200
+طريقة اللي هي combination loading method اللي هي
+
+145
+00:17:54,200 --> 00:18:00,050
+مشروعة في section 614 في shigleمعناة المعادلة هذه
+
+146
+00:18:00,050 --> 00:18:08,310
+applies for single load types ال
+
+147
+00:18:08,310 --> 00:18:12,350
+modification factor الرابع اللي هو اللي بياخد في
+
+148
+00:18:12,350 --> 00:18:16,870
+الاعتبار التغير بدرجة الحرارة لأن الفحص المياري
+
+149
+00:18:16,870 --> 00:18:25,750
+بيصير عن درجة حرارة الغرفة الآن لما القطعتسخن
+
+150
+00:18:25,750 --> 00:18:31,830
+تتغير ال tensile strength بتاعتها الان في ال table
+
+151
+00:18:31,830 --> 00:18:41,190
+6.4 المرجيني ال ratio ل for steel طبعا لل tensile
+
+152
+00:18:41,190 --> 00:18:45,980
+strengththe temperature under study على ال tensile
+
+153
+00:18:45,980 --> 00:18:49,960
+strength at room temperature هنا درجة الحرارة هنا
+
+154
+00:18:49,960 --> 00:18:54,380
+ال ratio بين ال ST على SRT ال ST هي ال tensile
+
+155
+00:18:54,380 --> 00:18:58,140
+strength at ال operating temperature و ال SRT هي
+
+156
+00:18:58,140 --> 00:19:06,760
+ال tensile strength at room temperature الآن
+
+157
+00:19:06,760 --> 00:19:15,010
+عشان أحسب ال KD في عنديأكتر من حالة if ultimate
+
+158
+00:19:15,010 --> 00:19:17,710
+strength is known for the operating temperature
+
+159
+00:19:17,710 --> 00:19:24,190
+يعني ال S T معروف يعني واحد واحد
+
+160
+00:19:24,190 --> 00:19:33,490
+if ال S T at T is known
+
+161
+00:19:37,160 --> 00:19:44,480
+بعد يحكي SE' بيساوي نص ال ST و بحط كده بيساوي
+
+162
+00:19:44,480 --> 00:19:59,280
+واحد، هاي حالة حالة تانية ال ST ال SRT is non اللي
+
+163
+00:19:59,280 --> 00:20:02,040
+هي ال strength at root bridge is non
+
+164
+00:20:05,820 --> 00:20:11,220
+بروح على table 6
+
+165
+00:20:11,220 --> 00:20:18,580
+4 اللي هو هذا ال table و
+
+166
+00:20:18,580 --> 00:20:30,260
+بطلع منه S T على S room temperature و منه بحسب ال
+
+167
+00:20:30,260 --> 00:20:37,220
+S Tبعدين بحكي SE' بساوة نص ال ST و في الحالة هذه
+
+168
+00:20:37,220 --> 00:20:49,060
+برضه بحط KD بساوة واحد حالة تالتة ال
+
+169
+00:20:49,060 --> 00:20:55,100
+ال ال strength at room temperature ال
+
+170
+00:20:55,100 --> 00:20:59,700
+SRT is null
+
+171
+00:21:03,090 --> 00:21:09,350
+منها بحسب SE' بالساوية نص الـ S ال room
+
+172
+00:21:09,350 --> 00:21:18,670
+temperature بعدين من table 6 4 بحسب ال KD بالساوية
+
+173
+00:21:18,670 --> 00:21:23,690
+ST على S room temperature بعدين بعمل modification
+
+174
+00:21:23,690 --> 00:21:27,390
+SE بالساوية KD في SE'
+
+175
+00:21:37,160 --> 00:21:42,700
+البيانات اللي في جدول 6-4 معمولها
+
+176
+00:21:42,700 --> 00:21:51,480
+care fit من خلال polynomial من الدرجة الرابعة ال
+
+177
+00:21:51,480 --> 00:21:56,120
+KDis a function of temperature والتمريتشر معبر
+
+178
+00:21:56,120 --> 00:22:00,420
+عنها بوحدة الفهرون هايت ال KD is given by this
+
+179
+00:22:00,420 --> 00:22:04,640
+equation بالسواء bond 9 7 5 زي bond 4 3 2 في 10
+
+180
+00:22:04,640 --> 00:22:09,520
+أساس 3 TF minus bond 1 1 5 في 10 أساس 5 TF تربيه
+
+181
+00:22:09,520 --> 00:22:14,840
+ناقص bond 104 في 10 أس ناقص 8 في TF تكييب minus
+
+182
+00:22:14,840 --> 00:22:20,480
+bond 5 9 5 في 10 أس ناقص 12 TF أس 4 لاحظوا ان TF
+
+183
+00:22:20,480 --> 00:22:22,660
+معبر عنها بوحدة الفهرون هايت
+
+184
+00:22:28,560 --> 00:22:43,040
+نشوف مثال a
+
+185
+00:22:43,040 --> 00:22:50,040
+1035 steel عندي حديد اللي هو عشرة خمس وتلاتين
+
+186
+00:22:50,040 --> 00:22:55,280
+steel هذه ال material has a tensile strength
+
+187
+00:22:59,280 --> 00:23:05,100
+of seventy kilo pound per square inch الاسس عند ال
+
+188
+00:23:05,100 --> 00:23:10,460
+room temperature بستوى سبعين kilo pound per square
+
+189
+00:23:10,460 --> 00:23:15,020
+inch and is to be used for a part that sees
+
+190
+00:23:15,020 --> 00:23:17,260
+اربعمية خمسين degrees Fahrenheit in service في
+
+191
+00:23:17,260 --> 00:23:23,260
+الخدمة هتكون درجة الحرارة اربعمية خمسين Fahrenheit
+
+192
+00:23:23,260 --> 00:23:26,560
+estimate
+
+193
+00:23:26,560 --> 00:23:31,240
+the temperature modification factorand SE عند ..
+
+194
+00:23:31,240 --> 00:23:44,060
+بده نحسب الـ KD والـ SE عند الـ 450 if
+
+195
+00:23:44,060 --> 00:23:47,140
+room
+
+196
+00:23:47,140 --> 00:23:52,120
+temperature and unit limit by test إذا كنت عارف
+
+197
+00:23:52,120 --> 00:24:01,950
+الـ SE prime عند الـ 70 فهران هايتبتساوي تسعة
+
+198
+00:24:01,950 --> 00:24:11,730
+وتلاتين kilo pound per square inch طيب
+
+199
+00:24:11,730 --> 00:24:17,910
+اللي هسويه في الحالة هذه انا
+
+200
+00:24:17,910 --> 00:24:21,230
+معروف عندي ال SE prime عند تسعة .. عند سبعين فرن
+
+201
+00:24:21,230 --> 00:24:25,570
+هاي تسعة تلاتين و بده ال SE عند اربعمية و خمسين
+
+202
+00:24:25,570 --> 00:24:33,010
+هروح ل tableست اربعة انا درس الحلقة اربعمية و
+
+203
+00:24:33,010 --> 00:24:42,710
+خمسين يعني انا جاي في المنطقة هذه اربعمية
+
+204
+00:24:42,710 --> 00:24:49,390
+و خمسين تيجي هنا جاي
+
+205
+00:24:49,390 --> 00:24:52,690
+بين هدولتين تاني الاربعمية و خمسين جاي بالمص
+
+206
+00:24:52,690 --> 00:24:56,900
+بالظبط بين اربعمية و الخمسمية معناته بعمل ايشبعمل
+
+207
+00:24:56,900 --> 00:24:59,340
+interpolation يعني معناته ال S T على S room
+
+208
+00:24:59,340 --> 00:25:02,200
+temperature انتقال 450 هتكون القيمة المتوسطة لهذه
+
+209
+00:25:02,200 --> 00:25:10,440
+القيمتان ال S T table table
+
+210
+00:25:10,440 --> 00:25:19,440
+64 بتكون الحالة هذه S T على S room temperature
+
+211
+00:25:19,440 --> 00:25:29,700
+بتساوي اللي هي 1 pointاو واحد تمانية زائد بونت
+
+212
+00:25:29,700 --> 00:25:51,820
+تسعة تسعة خمسة على اتنين بطل
+
+213
+00:25:51,820 --> 00:25:53,080
+واحد بونت او او
+
+214
+00:25:56,190 --> 00:26:03,210
+ستة خمسة هذي
+
+215
+00:26:03,210 --> 00:26:12,270
+بتساوي كد معناته ال SE عند اربعمية و خمسين هتساوي
+
+216
+00:26:12,270 --> 00:26:18,870
+اللي هو واحد point O او ستة خمسة في ال SE عند
+
+217
+00:26:18,870 --> 00:26:21,710
+سبعين في تسعة و تلاتين
+
+218
+00:26:28,170 --> 00:26:33,510
+تبتعد تسعة وتلاتين Pound تسعة تلاتين Pound تسعة
+
+219
+00:26:33,510 --> 00:26:34,550
+تلاتين Pound تسعة تلاتين Pound تسعة تلاتين Pound
+
+220
+00:26:34,550 --> 00:26:35,350
+تسعة تلاتين Pound تسعة تلاتين Pound تسعة تلاتين
+
+221
+00:26:35,350 --> 00:26:39,670
+Pound تسعة تلاتين Pound تسعة تلاتين Pound تسعة
+
+222
+00:26:39,670 --> 00:26:39,970
+تلاتين Pound تسعة تلاتين Pound تسعة تلاتين Pound
+
+223
+00:26:39,970 --> 00:26:39,970
+تسعة تلاتين Pound تسعة تلاتين Pound تسعة تلاتين
+
+224
+00:26:39,970 --> 00:26:39,970
+Pound تسعة تلاتين Pound تسعة تلاتين Pound تسعة
+
+225
+00:26:39,970 --> 00:26:40,190
+تلاتين Pound تسعة تلاتين Pound تسعة تلاتين Pound
+
+226
+00:26:40,190 --> 00:26:48,650
+تسعة تلاتين Pound تسعة تلاتين Pound تسعة
+
+227
+00:26:48,650 --> 00:26:54,490
+تلاتين Pound
+
+228
+00:26:54,490 --> 00:26:54,490
+تسعة ت
+
+229
+00:26:58,750 --> 00:27:01,070
+only the tensile strength at room temperature اللي
+
+230
+00:27:01,070 --> 00:27:07,790
+هي هذه is given يعني only as room temperature is
+
+231
+00:27:07,790 --> 00:27:15,370
+known يعني
+
+232
+00:27:15,370 --> 00:27:21,960
+ممكن أعمل التالي أروح على ال table six أربعةواحسب
+
+233
+00:27:21,960 --> 00:27:27,780
+ST على S رومتين ريتشار زي ما حسبنا تطلع واحد point
+
+234
+00:27:27,780 --> 00:27:35,480
+O O ستة خمسة واحسب ST بسواحد point O O ستة خمسة في
+
+235
+00:27:35,480 --> 00:27:39,620
+اللي هي سبعين
+
+236
+00:27:49,760 --> 00:27:54,900
+تطلع سبعين point أربعة خمسة
+
+237
+00:27:54,900 --> 00:28:00,760
+خمسة kilo pound per square inch و هحكي SE عند أربع
+
+238
+00:28:00,760 --> 00:28:10,120
+مية و خمسين سواء نص ال ST يعني هتكون نص في سبعين
+
+239
+00:28:10,120 --> 00:28:19,120
+point أربعة خمسة خمسة فنص هتكون
+
+240
+00:28:20,790 --> 00:28:34,290
+خمس تلاتين بونت او
+
+241
+00:28:34,290 --> 00:28:43,660
+احتياجي بتستوي كدي يعني orS E Prime سواء نص ال S U
+
+242
+00:28:43,660 --> 00:28:49,200
+T اللي هي نص في سبعين عند room temperature بتساوي
+
+243
+00:28:49,200 --> 00:28:53,520
+خمس تلاتين كيلو pound per square inch بعدين احكي S
+
+244
+00:28:53,520 --> 00:29:02,020
+E S E عند الاربعمية و خمسين بتساوي ال K D في ال S
+
+245
+00:29:02,020 --> 00:29:09,020
+E Prime عند السبعين ال
+
+246
+00:29:09,020 --> 00:29:15,470
+K Dاللي بيساوي ST على S room temperature اللي
+
+247
+00:29:15,470 --> 00:29:34,950
+بيساوي 1.0065 هتكون معناته واحدة 1.0065 في 35 تطلع
+
+248
+00:29:34,950 --> 00:29:37,370
+نفس ال issue 32
+
+249
+00:29:40,500 --> 00:29:45,500
+أو خمسة و تلاتين point اتنين اتنين سبعة خمسة kilo
+
+250
+00:29:45,500 --> 00:30:02,060
+pound per square inch بصرا نفس النتيجة ال
+
+251
+00:30:02,060 --> 00:30:04,640
+modification factor الخامس اللي هو reliability
+
+252
+00:30:04,640 --> 00:30:06,960
+factor reliability factor
+
+253
+00:30:19,090 --> 00:30:26,510
+نرجع لشكل 6.17 شكل 6.17 كان عامل plot بين ال
+
+254
+00:30:26,510 --> 00:30:33,890
+tensile strength sut و ال SE prime و كانت ال
+
+255
+00:30:33,890 --> 00:30:39,650
+relation linear في النص for
+
+256
+00:30:43,780 --> 00:30:46,600
+الخط في المصدر يمثل خمسين في المية reliability of
+
+257
+00:30:46,600 --> 00:30:52,380
+data يعني نسبة النجاح انه .. النسبة النجاح ان الخط
+
+258
+00:30:52,380 --> 00:30:56,940
+هذا يمثل ال experimental data خمسين في المية يعني
+
+259
+00:30:56,940 --> 00:30:59,580
+خمسين في المية من البيانات above خمسين في المية من
+
+260
+00:30:59,580 --> 00:31:01,400
+البيانات ash below
+
+261
+00:31:06,930 --> 00:31:10,070
+يعني اللي انا لو حكيت reliability تسعين في المية
+
+262
+00:31:10,070 --> 00:31:13,650
+معناته نسبة النجاح ان ال line to fit the data is
+
+263
+00:31:13,650 --> 00:31:16,310
+تسعين في المية نسبة النجاح تكون تسعين في المية لما
+
+264
+00:31:16,310 --> 00:31:19,950
+نحكي reliability عبارة ال reliability عادة تعرف
+
+265
+00:31:19,950 --> 00:31:27,550
+واحد minus احتمالية ال failure فلو نحكي
+
+266
+00:31:27,550 --> 00:31:31,950
+reliability تسعين في المية معناته في احتمال ان ال
+
+267
+00:31:31,950 --> 00:31:38,690
+data يكون تمثيلهاللبيانات بنسبة خطأ عشرة في المية
+
+268
+00:31:38,690 --> 00:31:44,590
+فمعناته النجاح عندى تسعين في المية فال SE prime
+
+269
+00:31:44,590 --> 00:31:56,170
+بيساوي نص SUT is based on fifty percent
+
+270
+00:31:56,170 --> 00:32:01,990
+reliability of experimental data
+
+271
+00:32:04,660 --> 00:32:09,760
+إذا بدّي more reliable fit معناته محتاج أعمل
+
+272
+00:32:09,760 --> 00:32:22,220
+modification لل SE prime ال KE موضوع في ال table 6
+
+273
+00:32:22,220 --> 00:32:29,600
+5 ال table 6 5 إذا كان reliability لل fitting لل
+
+274
+00:32:29,600 --> 00:32:32,440
+experimental data 50% معناته مش modification نفس
+
+275
+00:32:32,440 --> 00:32:37,710
+اللي احنا عملنا واحدال 90% بيبغون 8 9 7 و هكذا كل
+
+276
+00:32:37,710 --> 00:32:44,610
+ما كانت انا محتاج نسبة اعلى لتمثيل ال experimental
+
+277
+00:32:44,610 --> 00:32:50,050
+data كل ما انا محتاج انزل اللي هي ال endurance
+
+278
+00:32:50,050 --> 00:32:54,510
+limit ومعناته ال K.E بتقل بالارتفاع بقيمة
+
+279
+00:32:54,510 --> 00:32:54,990
+reliability
+
+280
+00:33:00,790 --> 00:33:05,610
+ال factor الأخير اللي هو mycelinus effects factor
+
+281
+00:33:05,610 --> 00:33:10,030
+اللي هو factor بحط كذا شغلات .. كذا شغلة مع بعض
+
+282
+00:33:10,030 --> 00:33:16,550
+يعني شغلات غير منظورة مثلا ممكن ال mechanical part
+
+283
+00:33:16,550 --> 00:33:20,850
+متعرض لبيئة .. بيئة very corrosive يعني زي بيئة
+
+284
+00:33:20,850 --> 00:33:26,930
+البحر بتعمل صدا و تأكل سريع أو محطوط مثلا معمول
+
+285
+00:33:26,930 --> 00:33:33,620
+تقسي سطحية لل mechanical partأو مطلب مادة تانية
+
+286
+00:33:33,620 --> 00:33:38,980
+مطلب كروم او مطلب ب .. ب .. ب zinc او في صارت عليه
+
+287
+00:33:38,980 --> 00:33:43,100
+عمليات .. عمليات ميكانيكية مثلا عمليات تشكيل
+
+288
+00:33:43,100 --> 00:33:49,380
+عمليات تشكيل بتخلي المادة فيها
+
+289
+00:33:49,380 --> 00:33:52,760
+stresses او صار عملية عملية الحنفة فيه stresses
+
+290
+00:33:52,760 --> 00:33:58,430
+هذه كلها different effectsلازم ناخدها بالاعتبار
+
+291
+00:33:58,430 --> 00:34:03,290
+طبعا مافيش ايش محدد تعتمد على المصمم هو يتخذ قرار
+
+292
+00:34:03,290 --> 00:34:08,590
+يقدر ال factor تاع ال miscellaneous effects ممكن
+
+293
+00:34:08,590 --> 00:34:13,010
+إذا بده شغل أدق يعمل عليها more research or
+
+294
+00:34:13,010 --> 00:34:20,590
+testing معناته
+
+295
+00:34:20,590 --> 00:34:25,640
+احنا نرجع لمعادل أصلي لنا SEالـ Modified Endurance
+
+296
+00:34:25,640 --> 00:34:30,020
+Limit بيستوى لـ KA, KB, KC, KD, KE, KF, SE Prime
+
+297
+00:34:30,020 --> 00:34:33,680
+SE Prime هي الـ Endurance Limit لـ Standard
+
+298
+00:34:33,680 --> 00:34:37,840
+Fatigue Specimen That Is Highly Polished That Is
+
+299
+00:34:37,840 --> 00:34:44,040
+Under Completely Reversed Bending وشرحنا إيش هو
+
+300
+00:34:44,040 --> 00:34:47,760
+الـ KA، إيش هو ال KB و KC و KD و KE و KF و KFA
+
+301
+00:34:47,760 --> 00:34:50,720
+قلية حساب كل factor على حدة
+
+302
+00:34:53,340 --> 00:34:56,800
+الان اذا بيصير عندي الان النقطة اللى هندرسها
+
+303
+00:34:56,800 --> 00:34:59,520
+اضافية الان اللى هي ال stress concentration and
+
+304
+00:34:59,520 --> 00:35:03,720
+notch sensitivity يعني stress concentration مثلا
+
+305
+00:35:03,720 --> 00:35:11,860
+لو انا صار عندي تغير مفاجئ في القطر تغير
+
+306
+00:35:11,860 --> 00:35:15,440
+مفاجئ بيصير عندي هنا في المنطقة هذه stress
+
+307
+00:35:15,440 --> 00:35:21,020
+concentration او
+
+308
+00:35:21,020 --> 00:35:26,680
+مثلا عندي plateو في ثقب عند ال whole عند ال whole
+
+309
+00:35:26,680 --> 00:35:31,680
+هي مباشرة بيكون ال stress is maximum بيعلى ال
+
+310
+00:35:31,680 --> 00:35:35,900
+stress من نتيجة تركيز الإجهاد احنا درسنا في
+
+311
+00:35:35,900 --> 00:35:41,560
+chapter تلاتة حكينا في appendix A15 بيعطي ال
+
+312
+00:35:41,560 --> 00:35:44,040
+geometric stress concentration factor KT في
+
+313
+00:35:44,040 --> 00:35:48,020
+appendix A15لأن احنا عندنا fatigue loading يعني ال
+
+314
+00:35:48,020 --> 00:35:51,820
+loading is variable معناته محتاج fatigue stress
+
+315
+00:35:51,820 --> 00:35:55,320
+concentration factor ال fatigue stress
+
+316
+00:35:55,320 --> 00:36:00,940
+concentration factor KF معطب
+
+317
+00:36:00,940 --> 00:36:07,760
+العلاقة واحد زاد Q في KTمينص واحد او ممكن احكي كيو
+
+318
+00:36:07,760 --> 00:36:10,980
+باسم كف مينص واحد على كتي مينص واحد في حالة اللي
+
+319
+00:36:10,980 --> 00:36:15,580
+هو ال normal stress في حالة shear stress باسم كف
+
+320
+00:36:15,580 --> 00:36:20,570
+اس مينص واحد على كتي اس مينص واحدالـ KFS اللي هو
+
+321
+00:36:20,570 --> 00:36:25,410
+shear fatigue stress concentration factor ال KTS
+
+322
+00:36:25,410 --> 00:36:28,830
+اللي هي shear geometric stress concentration
+
+323
+00:36:28,830 --> 00:36:33,470
+factor و ال Q notch sensitivity بيعبر عن مدى
+
+324
+00:36:33,470 --> 00:36:41,700
+حساسية المادة للخدوش إذا كانت ال Qصفر معناته ال
+
+325
+00:36:41,700 --> 00:36:45,720
+material مش حساسة للخدوش في الحال هذي ال K في ال
+
+326
+00:36:45,720 --> 00:36:49,100
+KF بالساوية واحد يعني إذا ال material كانت very
+
+327
+00:36:49,100 --> 00:36:54,880
+ductile مش هتكون حساسة للخدوش إذا كانت ال Q واحد
+
+328
+00:36:54,880 --> 00:36:59,500
+يعني fully sensitive هتكون ال KF بالساوية KT زي
+
+329
+00:36:59,500 --> 00:37:03,840
+المواد الناشرة أو ال very hard بتكون حساسة للخدوش
+
+330
+00:37:08,660 --> 00:37:12,240
+الان ال notch sensitivity factor بيعتمد على نوع ال
+
+331
+00:37:12,240 --> 00:37:17,010
+loading اذا كان ال loading bending and axialبحسب
+
+332
+00:37:17,010 --> 00:37:22,870
+الـ Q من figure 620 figure 620 على المحور الأفق ..
+
+333
+00:37:22,870 --> 00:37:28,170
+الأفق معطيني ال notch radius notch radius are هنا
+
+334
+00:37:28,170 --> 00:37:31,210
+بواحدة ال inch وهنا بواحدة ال millimeter يعني هنا
+
+335
+00:37:31,210 --> 00:37:34,590
+عنده نص واحد millimeter واحد و نص اتنين اتنين و نص
+
+336
+00:37:34,590 --> 00:37:37,710
+تلاتة تلاتة و نص اربعة هنا بواحدة ال inch point o
+
+337
+00:37:37,710 --> 00:37:40,530
+two point o four يعني هذا ال axis هو نفس ال axis
+
+338
+00:37:40,530 --> 00:37:43,850
+بس هذا metric unit هذا English unit على المحور
+
+339
+00:37:43,850 --> 00:37:50,640
+الرأسي معطيني ال Qوعندي different curves هذا ال
+
+340
+00:37:50,640 --> 00:37:55,800
+curveلـ steel الـ tensile strength بتاعته 200 kilo
+
+341
+00:37:55,800 --> 00:37:59,620
+pound per square inch الكيرف هذا لـ steel الـ
+
+342
+00:37:59,620 --> 00:38:02,580
+tensile strength بتاعته 150 kilo pound per square
+
+343
+00:38:02,580 --> 00:38:06,120
+inch الكيرف التالت لـ steel الـ tensile strength
+
+344
+00:38:06,120 --> 00:38:09,880
+بتاعته 100 كيرف هذا لـ steel الـ tensile strength
+
+345
+00:38:09,880 --> 00:38:15,060
+بتاعته 60 الكيرف الـ dotted للألمنيون في الحالة دي
+
+346
+00:38:15,060 --> 00:38:19,380
+KF بالساوية واحد زاد Q في KT minus واحد
+
+347
+00:38:23,770 --> 00:38:29,500
+الشكل 621 معطيني ال notch sensitivityfor torsional
+
+348
+00:38:29,500 --> 00:38:31,920
+loading نفس الاشياء على المحور الأفق عندى ال notch
+
+349
+00:38:31,920 --> 00:38:36,640
+radius بالإنش أو ال notch radius بالمليمتر هين ال
+
+350
+00:38:36,640 --> 00:38:41,540
+QS ال notch sensitivity for shear وهين معطيني ال S
+
+351
+00:38:41,540 --> 00:38:48,060
+ال tensile strength هين عندى 200 هين عندى 150 160
+
+352
+00:38:48,060 --> 00:38:53,700
+وهدى الألمانيوم و ال KFS يساوي واحد زي ال QS في
+
+353
+00:38:53,700 --> 00:38:55,420
+KTS minus واحد
+
+354
+00:39:00,510 --> 00:39:07,630
+يعني يا اما بستخدم figure 26 او figure 621 او بعمل
+
+355
+00:39:07,630 --> 00:39:13,730
+care fit equations للاشكال 26 و 6 و 1 في الحالة
+
+356
+00:39:13,730 --> 00:39:19,010
+هذه بحسب ال Q بسوء 1 على 1 على 1 زائد جزر A على
+
+357
+00:39:19,010 --> 00:39:23,170
+جزر R والكف بسوء 1 زائد KT minus 1 على 1 زائد جزر
+
+358
+00:39:23,170 --> 00:39:28,940
+A على R لان جزر Aفي حالة بنج او axle loading معطب
+
+359
+00:39:28,940 --> 00:39:32,960
+العلاقة هذه it is a function of tensile strength
+
+360
+00:39:32,960 --> 00:39:37,380
+في حالة torsional loading جزر A معطب العلاقة هذه
+
+361
+00:39:37,380 --> 00:39:40,940
+يعني انت مخير يا اما تستخدم figure ستة عشرين
+
+362
+00:39:40,940 --> 00:39:45,480
+figure ستة واحد وعشرين او بتستخدم المعادلات اللي
+
+363
+00:39:45,480 --> 00:39:49,400
+هي معادلة ستة اربع تلاتين ستة تلاتين ومعادلة هذه
+
+364
+00:39:49,400 --> 00:39:55,800
+ومعادلة هذه لحساب اللي هو ال ال KF
+
+365
+00:40:03,400 --> 00:40:10,580
+الان في حالة حديد السكب ال cast iron ال cast iron
+
+366
+00:40:10,580 --> 00:40:17,220
+already ملان بالخدوش وبالتالي لما نعملوا فحص الشد
+
+367
+00:40:17,220 --> 00:40:21,220
+لل cast iron بيكون already فيه خدوش وعملين يعني it
+
+368
+00:40:21,220 --> 00:40:24,980
+is taking care of اللي هو اللي هو ال notches
+
+369
+00:40:26,300 --> 00:40:29,840
+وبالتالي إذا هو عنده عدد كبير جدا جدا من الـ
+
+370
+00:40:29,840 --> 00:40:33,620
+notches إذا اضفت one notch او two notches مش هتفرق
+
+371
+00:40:33,620 --> 00:40:37,900
+معاه it is recommended ان نستخدم في حالة ال cast
+
+372
+00:40:37,900 --> 00:40:46,860
+iron لكي يبساط one two four cast irons نشوف
+
+373
+00:40:46,860 --> 00:40:48,320
+example ستة ستة
+
+374
+00:40:53,930 --> 00:40:58,070
+استيل شافت عمود من الحديد in bending نوع ال
+
+375
+00:40:58,070 --> 00:41:03,670
+loading bending has an ultimate strength ال SUT
+
+376
+00:41:03,670 --> 00:41:07,870
+بالساوية
+
+377
+00:41:07,870 --> 00:41:13,950
+ستمية وتسعين ميجا باسكال and
+
+378
+00:41:13,950 --> 00:41:15,910
+a shoulder with a fillet radius of three
+
+379
+00:41:15,910 --> 00:41:18,550
+millimeter connecting a thirty two millimeter with
+
+380
+00:41:18,550 --> 00:41:20,590
+a thirty eight millimeter diameter يعني دي هي
+
+381
+00:41:20,590 --> 00:41:33,970
+الجاية القطر32 مسلم قطر 38 32
+
+382
+00:41:33,970 --> 00:41:50,150
+مسلم قطر على
+
+383
+00:41:50,150 --> 00:41:50,710
+الشرط
+
+384
+00:41:54,420 --> 00:42:00,620
+هذا اتنين وتلاتين ميلي مسلم
+
+385
+00:42:00,620 --> 00:42:08,540
+تمنع تلاتين ميلي و
+
+386
+00:42:08,540 --> 00:42:17,900
+الفيلتين ال radius بتاعها تلاتة ميلي متر دوران
+
+387
+00:42:17,900 --> 00:42:25,550
+estimate KF using figure ستة عشرينأولا نحسب KF
+
+388
+00:42:25,550 --> 00:42:38,450
+باستخدام figure 26 فنروح على figure 26 figure
+
+389
+00:42:38,450 --> 00:42:42,530
+26 معطيني ال notch الفلت عندى 3 ملي 3 ملي هاي 3
+
+390
+00:42:42,530 --> 00:42:46,910
+ملي 3
+
+391
+00:42:46,910 --> 00:42:48,010
+ملي هاي 3 ملي
+
+392
+00:42:56,950 --> 00:43:05,750
+طيب ال SUT 690 ميجا عندها 1.4 جيجا يعني 1400 ميجا
+
+393
+00:43:05,750 --> 00:43:11,890
+هين 1000 ميجا هين 700 ميجا و هين يعني جاية تقريبا
+
+394
+00:43:11,890 --> 00:43:21,910
+جاية هين يعني تحت شوية من ال 700 ميجا تقريبا
+
+395
+00:43:21,910 --> 00:43:23,170
+لو أمد
+
+396
+00:43:32,840 --> 00:43:41,740
+يعني تقريبا هتطلع الكيو هذه point يعني
+
+397
+00:43:41,740 --> 00:43:47,660
+تقريبا ربع المسافة هذه مثلا point 2 ربع point 2
+
+398
+00:43:47,660 --> 00:43:53,100
+point 1 point .. point كيو هتكون سواء point 8 خمسة
+
+399
+00:43:53,100 --> 00:44:02,720
+كيو بسواء point 8 خمسة طيب ال KFبساوة واحد زاد Q
+
+400
+00:44:02,720 --> 00:44:09,760
+في KT minus واحد احنا ردى حسبنا Q بساوية point
+
+401
+00:44:09,760 --> 00:44:16,060
+تمانية خمسة طيب بدى احسب ال KT احنا عندنا bending
+
+402
+00:44:16,060 --> 00:44:19,900
+بدى
+
+403
+00:44:19,900 --> 00:44:23,100
+احسب ال KT ال KT بيقدروا يروح على appendix A خمسة
+
+404
+00:44:23,100 --> 00:44:26,960
+اش هاروح على appendix A خمسة اش
+
+405
+00:44:35,070 --> 00:44:43,890
+في كتاب شجلة A15 اللي هو هذا اللي
+
+406
+00:44:43,890 --> 00:44:51,470
+مش الحالة هذه ولا هذه هتكون
+
+407
+00:44:51,470 --> 00:44:56,310
+A15 9 خانيا أكبر عليها A15 9
+
+408
+00:45:08,030 --> 00:45:18,830
+A خمساش تسعة هاد
+
+409
+00:45:18,830 --> 00:45:23,610
+ال D small هاد
+
+410
+00:45:23,610 --> 00:45:27,410
+ال D capital و هاد ال R احنا ال D small عندنا
+
+411
+00:45:27,410 --> 00:45:34,370
+اكام؟ اتنين وتلاتين و
+
+412
+00:45:34,370 --> 00:45:44,350
+ال D capital تمانية وتلاتينو ال R تلاتة ملي عن
+
+413
+00:45:44,350 --> 00:45:50,590
+المحور الأفق هنا ر على دي ر على دي ر على دي هتكون
+
+414
+00:45:50,590 --> 00:45:54,790
+تلاتة
+
+415
+00:45:54,790 --> 00:46:02,190
+على اتنين و تلاتين يعني هتكون تلاتة
+
+416
+00:46:02,190 --> 00:46:08,880
+تقصير اتنين و تلاتينبتطلع point o تسعة point o
+
+417
+00:46:08,880 --> 00:46:18,180
+تسعة تلاتة سبعة خمسة يعني يعني تقريبا هنا تقريبا
+
+418
+00:46:18,180 --> 00:46:26,180
+يعني تقريبا point one بعدين
+
+419
+00:46:26,180 --> 00:46:30,640
+بلزمنا هدول care دي capital على دي small
+
+420
+00:46:33,620 --> 00:46:37,460
+على دي small اللي هي تمانية وتلاتين على اتنين
+
+421
+00:46:37,460 --> 00:46:50,400
+وتلاتين تمانية تلاتين تطلع
+
+422
+00:46:50,400 --> 00:46:58,700
+واحد point واحد تمانية سبعة خمسةأنا عندي هنا دي
+
+423
+00:46:58,700 --> 00:47:05,100
+capital على دي تلاتة هذه واحد و نص واحد و نص هذه
+
+424
+00:47:05,100 --> 00:47:08,420
+واحد point يعني هي جاية بين ال curve التاني
+
+425
+00:47:08,420 --> 00:47:13,760
+والتالت curve التاني والتالت يعني هنكون تقريبا في
+
+426
+00:47:13,760 --> 00:47:20,280
+المنطقة هذه يعني هتكون يعني
+
+427
+00:47:20,280 --> 00:47:27,090
+عندي هنا one point fourone point six one point six
+
+428
+00:47:27,090 --> 00:47:34,210
+خمسة يعني ممكن نحكي كت كت هتكون واحد
+
+429
+00:47:34,210 --> 00:47:40,210
+point ستة خمسة اللي هو هتكون ايه خمستاش تسعة معناه
+
+430
+00:47:40,210 --> 00:47:46,490
+كف هتكون سواحه زاد كو اللي هي point تمانية خمسة في
+
+431
+00:47:46,490 --> 00:47:50,870
+كت اللي هي واحد point ستة خمسة minus واحد
+
+432
+00:47:56,110 --> 00:48:01,210
+يعني عندي one point six خمسة في point تمانية خمسة
+
+433
+00:48:01,210 --> 00:48:07,390
+ساوية زايد واحد تطلع واحد point خمسة خمسة اتنين
+
+434
+00:48:07,390 --> 00:48:14,930
+خمسة واحد خمسة خمسة اتنين خمسة يعني هذه طريقة
+
+435
+00:48:14,930 --> 00:48:20,570
+وقالية طيب انه انا احسب ان عندي bending او axle
+
+436
+00:48:20,570 --> 00:48:24,250
+يعني طريقة تانية استخدم المعادلات
+
+437
+00:48:45,950 --> 00:48:52,170
+نتذكر ان ال KT احنا
+
+438
+00:48:52,170 --> 00:49:00,630
+طلعناها 1.65 من appendix A 15 9 لان هحصل جزر A من
+
+439
+00:49:00,630 --> 00:49:07,470
+المعادلة هذه هعوض عن S U T انتبه ال S U T هنا
+
+440
+00:49:07,470 --> 00:49:10,290
+وحدات و وحدات انجليزية هتكون مع 690 ميجا بس كده
+
+441
+00:49:10,290 --> 00:49:15,220
+هحور الوحدات انجليزية بحسب الجزر ال Aبعدين بحس
+
+442
+00:49:15,220 --> 00:49:24,800
+بيجي أحكي KF بالساوية واحد
+
+443
+00:49:24,800 --> 00:49:33,980
+زاد KT minus واحد على واحد زاد الجزر التربيعي لل A
+
+444
+00:49:33,980 --> 00:49:39,500
+او انا ممكن افضل الطريقة هذه ان احس في Q
+
+445
+00:49:43,890 --> 00:49:50,030
+بالساوية واحد على واحد زي جزر ال A على جزر ال R
+
+446
+00:49:50,030 --> 00:49:56,270
+لأن جزر ال A من المعادلة هذه وال R ما هي تلاتة ملي
+
+447
+00:49:56,270 --> 00:50:04,460
+متر بعدين بحسب ال KFسواحد زاد Q في KT minus واحد
+
+448
+00:50:04,460 --> 00:50:10,960
+حصل نفس النتيجة جربه عوضه في المعدلات و طلع ال Q و
+
+449
+00:50:10,960 --> 00:50:20,760
+طلع ال KF حتى حصل نفس النتيجة تقريبا طيب
+
+450
+00:50:34,230 --> 00:50:40,390
+طيب المحاضرة الجاي بنكمل ال application of fatigue
+
+451
+00:50:40,390 --> 00:50:42,430
+stress concentration factor
+
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/A-1SThU8Qv4_postprocess.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/A-1SThU8Qv4_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..593ed38b014972c6b77228094cf3da2ab40b77a3
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/A-1SThU8Qv4_postprocess.srt
@@ -0,0 +1,1396 @@
+1
+00:00:05,090 --> 00:00:09,710
+السلام عليكم اليوم هنكمل chapter أربعة او
+
+2
+00:00:09,710 --> 00:00:14,490
+deflection and stiffness of beams في المحاضرة اللي
+
+3
+00:00:14,490 --> 00:00:17,930
+الفاتة تعرفنا ال elasticity اللي هي خاصية للمادة
+
+4
+00:00:17,930 --> 00:00:23,030
+بتمكنها من استعادة شكلها بمجرد رفع الأحمال ال
+
+5
+00:00:23,030 --> 00:00:26,030
+spraying جايبها عن mechanical element اللي لو
+
+6
+00:00:26,030 --> 00:00:27,870
+عملتله deflection بيعطيني force
+
+7
+00:00:30,960 --> 00:00:34,700
+ال spring rate اللي هو كان عرفناه K بيساوي DF على
+
+8
+00:00:34,700 --> 00:00:40,540
+DY في حالة linear spring ال K بيساوي F على Y عرفنا
+
+9
+00:00:40,540 --> 00:00:44,280
+ال spring او we derive ال spring constant ل X
+
+10
+00:00:44,280 --> 00:00:49,000
+reloaded member كان ال K بيساوي A في E على L في
+
+11
+00:00:49,000 --> 00:00:53,400
+حالة torsion reloaded member كان عنده ال stiffness
+
+12
+00:00:53,400 --> 00:00:57,360
+constant او ال stiffness rate K بيساوي G في G على
+
+13
+00:00:57,360 --> 00:00:58,140
+L
+
+14
+00:01:01,070 --> 00:01:04,410
+بعدين درسنا deflection due to bending in straight
+
+15
+00:01:04,410 --> 00:01:10,550
+beams وصلنا لعلاقة أنه ال bending moment M على EI
+
+16
+00:01:10,550 --> 00:01:15,930
+بساوة D²Y بDX² باستخدام العلاقة هذه ممكن يوجد
+
+17
+00:01:15,930 --> 00:01:22,370
+slope أو و a deflection at any point along the
+
+18
+00:01:22,370 --> 00:01:30,150
+beam as a function of X حلينا two examplesجيب ده
+
+19
+00:01:30,150 --> 00:01:34,690
+الـ deflection و ال slopes at any location for a
+
+20
+00:01:34,690 --> 00:01:40,450
+beam عليه distributed load باستخدام معادلة اللي هي
+
+21
+00:01:40,450 --> 00:01:46,410
+M على EI بيستوى D²Y بقى DX² بعد حكينا فيه أكتر من
+
+22
+00:01:46,410 --> 00:01:50,550
+طريقة لحسابات الـ deflection منها superposition ال
+
+23
+00:01:50,550 --> 00:01:55,710
+numerical integration و Castellano methodبدأنا في
+
+24
+00:01:55,710 --> 00:01:59,190
+ال superposition ال superposition بتحكي ببساطة ان
+
+25
+00:01:59,190 --> 00:02:03,870
+ال total effect due to the combined loading
+
+26
+00:02:03,870 --> 00:02:09,670
+condition بيساوي مجموع ال individual effect due to
+
+27
+00:02:09,670 --> 00:02:14,070
+individual loading conditions طبعا عشان نحل ال
+
+28
+00:02:14,070 --> 00:02:18,550
+superposition هنستخدم table A9 في الكتاب حلينا
+
+29
+00:02:18,550 --> 00:02:22,430
+exam الأربعة اتنين باستخدام ال superposition
+
+30
+00:02:26,090 --> 00:02:29,990
+هنحل المسألة التانية باستخدام ال support position
+
+31
+00:02:29,990 --> 00:02:36,930
+هنحل المسألة التالية determine the deflection
+
+32
+00:02:36,930 --> 00:02:40,230
+equations using support position for the given
+
+33
+00:02:40,230 --> 00:02:47,480
+beam في عند beam simply supported عند a و bوطاير
+
+34
+00:02:47,480 --> 00:02:52,680
+من B ل C فيه بأثر على الـ distributed load بين A
+
+35
+00:02:52,680 --> 00:02:59,300
+وB وفيه concentrated load عند طرف الطاير C معناته
+
+36
+00:02:59,300 --> 00:03:06,060
+هنا عندي support عندي
+
+37
+00:03:06,060 --> 00:03:06,880
+hand support
+
+38
+00:03:13,250 --> 00:03:16,210
+بنحسب ال reactions و ال deflections due to this
+
+39
+00:03:16,210 --> 00:03:23,110
+loading condition باستخدام ال superposition أنا
+
+40
+00:03:23,110 --> 00:03:28,750
+المثل هذه عشان أحلها لازم أجزئها بحيث ممكن أستخدم
+
+41
+00:03:28,750 --> 00:03:33,650
+الجداول في appendix A9 يعني المثل كله ممكن أحكي
+
+42
+00:03:33,650 --> 00:03:38,030
+التالي أنا عندي هاي ال total condition
+
+43
+00:03:49,330 --> 00:03:57,050
+عندي هنا distributed
+
+44
+00:03:57,050 --> 00:04:07,870
+load W وعندي هنا total load F هذا اللي كنا نحكيه
+
+45
+00:04:07,870 --> 00:04:11,690
+انها عبارة هذا ال total effect عبارة عن مجموع two
+
+46
+00:04:11,690 --> 00:04:13,590
+effects ال effect الأولاني
+
+47
+00:04:24,080 --> 00:04:34,440
+عبارة عن distributed load زائد
+
+48
+00:04:34,440 --> 00:04:37,980
+concentrated
+
+49
+00:04:37,980 --> 00:04:38,620
+load
+
+50
+00:04:55,340 --> 00:05:00,800
+F معناته هذا ال total effect عندي distributed load
+
+51
+00:05:00,800 --> 00:05:05,420
+وعندي concentrated load هذا عبارة عن مجموع ال two
+
+52
+00:05:05,420 --> 00:05:10,920
+effects ال effect due to concentrated load W و ال
+
+53
+00:05:10,920 --> 00:05:15,160
+effect due to concentrated load F طبعا هكون عندي
+
+54
+00:05:15,160 --> 00:05:18,940
+due
+
+55
+00:05:18,940 --> 00:05:28,890
+to this في عندي هين عندي هين هكونR1' وهنا عنده R2'
+
+56
+00:05:30,230 --> 00:05:35,990
+وهنا رح يكون عنده R1W'
+
+57
+00:05:36,610 --> 00:05:40,510
+وهنا R2W'
+
+58
+00:05:41,210 --> 00:05:47,890
+وفي عندي برضه هنا Y' due to this deflection وYW'
+
+59
+00:05:48,410 --> 00:05:50,090
+due to this deflection
+
+60
+00:05:55,670 --> 00:06:04,310
+معناته هاخد two conditions الحالة
+
+61
+00:06:04,310 --> 00:06:09,150
+الأولى .. الحالة الأولى عبارة عن distributed load
+
+62
+00:06:37,290 --> 00:06:52,830
+و الحالة التانية عبارة عن concentrated load F
+
+63
+00:06:52,830 --> 00:07:05,750
+هنا عندي R1 prime و R2 prime هنا عندي R1double
+
+64
+00:07:05,750 --> 00:07:13,930
+prime وهنا عندي R2 double prime بدي
+
+65
+00:07:13,930 --> 00:07:17,770
+أشوف loading condition موجودة في ال table تشبه هذه
+
+66
+00:07:17,770 --> 00:07:20,050
+الحالة و loading condition موجودة في ال table
+
+67
+00:07:20,050 --> 00:07:25,090
+مكافئة للحالة هذه لما
+
+68
+00:07:25,090 --> 00:07:29,030
+بالنسبة للحالة الأولى هذه هتكون الحالة المكافئة
+
+69
+00:07:29,030 --> 00:07:31,470
+اللي هي A
+
+70
+00:07:33,510 --> 00:07:38,570
+تسعة سبعة اية السبعة الاية هذه بس بختلف ان انا
+
+71
+00:07:38,570 --> 00:07:44,210
+عندي F فيه زيادة هنا يعني هكون في عندي ايش فيه
+
+72
+00:07:44,210 --> 00:07:50,310
+زيادة طول هذا هو ال deflected beam ال
+
+73
+00:07:50,310 --> 00:07:56,250
+R واحد ال prime هتكون
+
+74
+00:07:56,250 --> 00:08:06,060
+بالساوي زي ما انتوا شايفينبيستوى R2' بيستوى
+
+75
+00:08:06,060 --> 00:08:15,820
+WL .. خنت أتأكد أن التسمية تانية هنا WL على
+
+76
+00:08:15,820 --> 00:08:25,540
+اتنين هذه .. هذه بالمناسبة هذه .. هذه L وهذه إيش؟
+
+77
+00:08:25,540 --> 00:08:25,860
+A
+
+78
+00:08:32,630 --> 00:08:39,350
+ال و إيه؟
+
+79
+00:08:39,350 --> 00:08:49,950
+ال و إيه؟ و نفس الأش عندهين ال
+
+80
+00:08:49,950 --> 00:08:56,490
+و إيه؟ و هنا ال
+
+81
+00:08:56,490 --> 00:08:58,070
+و إيه؟
+
+82
+00:09:02,500 --> 00:09:05,360
+والـ deflection من النقطة هدا نقطة هاد is given by
+
+83
+00:09:05,360 --> 00:09:14,880
+this equation الـ Y' لهذه الحالة Y' هتساوي
+
+84
+00:09:14,880 --> 00:09:23,300
+اللي هو WX على
+
+85
+00:09:23,300 --> 00:09:30,800
+24EI في 2LX تربيع
+
+86
+00:09:36,110 --> 00:09:40,710
+ناقص X تكييب ناقص
+
+87
+00:09:40,710 --> 00:09:55,670
+L تكييب طبعا هذه العلاقة X من سفر ل L الان
+
+88
+00:09:55,670 --> 00:09:57,110
+due to loading
+
+89
+00:10:08,660 --> 00:10:20,000
+عندي a,b,c عندي هي a,b,c الأعناء ال beam هيكون ال
+
+90
+00:10:20,000 --> 00:10:26,620
+deflection بتاعه عندي
+
+91
+00:10:26,620 --> 00:10:27,260
+هي a
+
+92
+00:10:37,230 --> 00:10:57,850
+A B C ال deflection هتحصير بالشكل هذا يعني
+
+93
+00:10:57,850 --> 00:11:01,830
+هذه المعادلة تطيل ال deflection من A ل B من النقطة
+
+94
+00:11:01,830 --> 00:11:04,690
+هذه لنقطة هذه لأن من B ل C
+
+95
+00:11:09,310 --> 00:11:13,930
+يعني هيضل ال slope من B ل C هيضل ال slope constant
+
+96
+00:11:13,930 --> 00:11:22,550
+يعني لو جت slope اللي أنا عندي y prime dy by dx ل
+
+97
+00:11:22,550 --> 00:11:32,070
+y prime هتكون W على 24EI هذا بشكل عام فيه
+
+98
+00:11:36,920 --> 00:11:46,560
+هكون ستة ال X تربيع ناقص
+
+99
+00:11:46,560 --> 00:11:56,960
+أربعة X تكييب ناقص التكييب هذا at any location بين
+
+100
+00:11:56,960 --> 00:12:03,220
+X .. بين X for X هنا بين سفر و L
+
+101
+00:12:07,210 --> 00:12:15,450
+at x equal L يعني dy by dx prime at x بالساوية L
+
+102
+00:12:15,450 --> 00:12:22,910
+هتكون تساوية W
+
+103
+00:12:22,910 --> 00:12:32,770
+على أربع وعشرين EI في ستة
+
+104
+00:12:32,770 --> 00:12:35,250
+التكييب
+
+105
+00:12:37,040 --> 00:12:47,400
+ناقص أربعة التكييب ناقص التكييب حيساوى
+
+106
+00:12:47,400 --> 00:12:53,860
+ستة ناقص أربعة اتنين ناقص واحد واحد حيكون W
+
+107
+00:12:53,860 --> 00:13:07,780
+التكييب على أربعة وعشرينE في I هذا ال slope اللي
+
+108
+00:13:07,780 --> 00:13:15,580
+هي هذه الذرة theta هذا ال slope الان هذه المسافة
+
+109
+00:13:15,580 --> 00:13:20,040
+او
+
+110
+00:13:20,040 --> 00:13:23,720
+عند اي location عند اي location X
+
+111
+00:13:27,210 --> 00:13:31,350
+هذه المسافة هتكون إيه؟ X معناته هذه المسافة هتكون
+
+112
+00:13:31,350 --> 00:13:40,590
+إيه؟ X minus L at
+
+113
+00:13:40,590 --> 00:13:50,210
+X at any location X at any location at any
+
+114
+00:13:50,210 --> 00:13:52,870
+location
+
+115
+00:13:57,520 --> 00:14:06,920
+x بكل slope اللي هو tan θ اللي
+
+116
+00:14:06,920 --> 00:14:20,180
+هو عبارة عن dy by dx اللي هو هذا tan θ هكون w ال
+
+117
+00:14:20,180 --> 00:14:34,070
+تكيب على 24EI بتساوي ال slope هيكون اللي هو ال Y
+
+118
+00:14:34,070 --> 00:14:40,690
+على
+
+119
+00:14:40,690 --> 00:14:52,030
+X ناقص L X ناقص L معناته
+
+120
+00:14:52,030 --> 00:14:53,130
+Y prime
+
+121
+00:14:59,250 --> 00:15:12,550
+بالساوية W التكييب في X ناقص
+
+122
+00:15:12,550 --> 00:15:18,950
+L على 24EI
+
+123
+00:15:18,950 --> 00:15:24,870
+طبعا هذه عند N في المنطقة هذه بس بين B وC معناته
+
+124
+00:15:25,560 --> 00:15:27,700
+ممكن احكي الـ deflection due to the distributed
+
+125
+00:15:27,700 --> 00:15:36,680
+load هيكون Y' Y'
+
+126
+00:15:37,180 --> 00:15:41,120
+بيساوي
+
+127
+00:15:41,120 --> 00:15:50,840
+جزئين الجزء الأول هيكون
+
+128
+00:15:50,840 --> 00:15:54,360
+هذا اللي هو WX
+
+129
+00:16:01,160 --> 00:16:06,180
+انتبه هنا للإشارات لل
+
+130
+00:16:06,180 --> 00:16:12,240
+.. للإشارات إذا عوضت مثلا X بالساوية L على 2 X L
+
+131
+00:16:12,240 --> 00:16:17,220
+على 2 هتكون ال Y Maximum minus 5WL أربع على تلاتين
+
+132
+00:16:17,220 --> 00:16:26,840
+على اتنين في E على I الآن ال Y Prime هتكون WX على
+
+133
+00:16:26,840 --> 00:16:30,560
+أربع و عشرين EI
+
+134
+00:16:32,400 --> 00:16:48,740
+في اتنين L X تربيع minus X تكييب minus L تكييب X
+
+135
+00:16:48,740 --> 00:16:56,840
+بين سفر و L الفترة التانية هتكون
+
+136
+00:17:01,660 --> 00:17:06,820
+بتكون تساوي W L
+
+137
+00:17:06,820 --> 00:17:20,620
+تكيب على 24 EI في
+
+138
+00:17:20,620 --> 00:17:25,520
+X minus
+
+139
+00:17:25,520 --> 00:17:39,970
+L طبعا هنا Xأكبر من L و أصغر من L زائد A معناته
+
+140
+00:17:39,970 --> 00:17:45,530
+we find deflection due to this loading condition
+
+141
+00:17:45,530 --> 00:17:50,670
+اللي هناخد الحالة التانية الحالة هذه
+
+142
+00:17:58,180 --> 00:18:05,200
+load أو ال beam تحت أثير قوة مركزة عند الطرف الحر
+
+143
+00:18:05,200 --> 00:18:12,440
+نرجع
+
+144
+00:18:12,440 --> 00:18:20,600
+للمسألة تاعتنا أقرب
+
+145
+00:18:20,600 --> 00:18:27,060
+حالة للحالة تاعتنا اللي هي appendix A
+
+146
+00:18:29,830 --> 00:18:36,890
+تسعة عشرة معطيني
+
+147
+00:18:36,890 --> 00:18:44,890
+هنا R واحد double prime بتساوي
+
+148
+00:18:44,890 --> 00:18:55,230
+FA على L وR اتنين double
+
+149
+00:18:55,230 --> 00:18:58,490
+prime بتساوي
+
+150
+00:19:02,130 --> 00:19:09,290
+بس انتبهوا للإشارات R واحد احنا هتكون بالسالب انا
+
+151
+00:19:09,290 --> 00:19:17,950
+جاله تحت هتكون بالسالب و R اتنين double prime F
+
+152
+00:19:17,950 --> 00:19:29,130
+على L في L زائد A بالنسبال
+
+153
+00:19:29,130 --> 00:19:36,560
+ال deflectionالـ deflection عبارة عن مقطعين فيه
+
+154
+00:19:36,560 --> 00:19:41,300
+deflection معادلة من a ل b و فيه معادلة من b ل c
+
+155
+00:19:41,300 --> 00:19:50,620
+يعني هيكون عندي y double prime من
+
+156
+00:19:50,620 --> 00:19:58,580
+a ل b هيكون fax على
+
+157
+00:19:58,580 --> 00:19:59,440
+6eil
+
+158
+00:20:04,770 --> 00:20:10,870
+في L تربية نقص X تربية يعني
+
+159
+00:20:10,870 --> 00:20:16,610
+هنا X بين سفر و
+
+160
+00:20:16,610 --> 00:20:24,910
+L و المقطع التاني FX-L
+
+161
+00:20:24,910 --> 00:20:31,130
+على 6EI
+
+162
+00:20:36,700 --> 00:20:50,060
+في x ناقص L الكل تربية minus
+
+163
+00:20:50,060 --> 00:21:03,810
+a في تلاتة x minus Lو X أكبر أو يساوي L أخر يساوي
+
+164
+00:21:03,810 --> 00:21:09,950
+A زائد L معناته
+
+165
+00:21:09,950 --> 00:21:12,830
+إحنا وجدنا ال individual effect for each loading
+
+166
+00:21:12,830 --> 00:21:18,810
+condition وجدنا R1 prime وR2 prime وY prime ووجدنا
+
+167
+00:21:18,810 --> 00:21:22,270
+ال individual effect due to this loading condition
+
+168
+00:21:22,270 --> 00:21:27,110
+عندي R1 prime وR2 prime وY W prime معناته ال total
+
+169
+00:21:27,110 --> 00:21:34,500
+effect ال R1R1' R1W'
+
+170
+00:21:35,080 --> 00:21:49,200
+R1' WL 2-FA L R2
+
+171
+00:21:49,200 --> 00:21:54,440
+R2' R2W'
+
+172
+00:21:55,400 --> 00:22:12,040
+WLعلى اتنين زائد F على L في L زائد A ال
+
+173
+00:22:12,040 --> 00:22:17,020
+total deflection ال Y بيساوي
+
+174
+00:22:17,020 --> 00:22:24,180
+Y prime زائد Y W prime يعني ال Y هتكون الساوى
+
+175
+00:22:26,000 --> 00:22:33,100
+المقطع الأولاني الـ WX الـ
+
+176
+00:22:33,100 --> 00:22:38,900
+WX الـ
+
+177
+00:22:38,900 --> 00:22:54,740
+WX على 24 EI في 2 L X تربيع minus X تكييب minus L
+
+178
+00:22:54,740 --> 00:23:11,820
+تكييبزاد F A X على 6 E I L في L تربيع و minus X
+
+179
+00:23:11,820 --> 00:23:18,920
+تربيع طبعا هنا X من صفر لأقل المقطع التاني اللي هو
+
+180
+00:23:18,920 --> 00:23:22,880
+W L
+
+181
+00:23:22,880 --> 00:23:34,590
+تكيبعلى 24EI في X minus L زائد
+
+182
+00:23:34,590 --> 00:23:51,410
+F في X minus L على 6EI في X minus L الكل تربيع
+
+183
+00:23:51,410 --> 00:24:01,900
+minus Aفي تلاتة X minus L هنا X أكبر أو يساوي L
+
+184
+00:24:01,900 --> 00:24:09,700
+أزال يساوي A زائد L هيك وجدنا ال total effect
+
+185
+00:24:09,700 --> 00:24:13,300
+وجدنا ال reactions R واحد وR اتنين و ال total
+
+186
+00:24:13,300 --> 00:24:19,360
+deflection at any location Y و to double check ال
+
+187
+00:24:19,360 --> 00:24:27,900
+calculation بتاعتكعوض X بالساوية سفر هتعطيني ايش؟
+
+188
+00:24:27,900 --> 00:24:33,040
+Deflection بالساوية سفر عوض X بالساوية L هي سفر
+
+189
+00:24:33,040 --> 00:24:36,520
+وهي سفر معناته الاشي صحيح
+
+190
+00:25:21,630 --> 00:25:28,630
+إذا عندى زنبرك و سحبت وضلت من ال mask بيكون فى
+
+191
+00:25:28,630 --> 00:25:32,990
+طاقة مقتزنة بسميها strain energy هذه الطاقة
+
+192
+00:25:32,990 --> 00:25:37,650
+المقتزنة نتيجة إن فى عليه deflection لو سيبت طرف
+
+193
+00:25:38,540 --> 00:25:41,900
+الزنبارك هيرجع معناته في potential energy طالما
+
+194
+00:25:41,900 --> 00:25:46,200
+أنا مسكها هي ممسوكة طالما فلاتتها هيرجع الزنبارك
+
+195
+00:25:46,200 --> 00:25:50,920
+لحاله معناته هيكون في عندي شغل أو طاقة مختزنة
+
+196
+00:25:50,920 --> 00:25:54,860
+بسميها strain energy due to deflection إذا عند
+
+197
+00:25:54,860 --> 00:26:04,860
+زنبارك هاي X هاي F وlinear spring عكينا الشغل
+
+198
+00:26:04,860 --> 00:26:11,240
+عبارة عن أياشالشغل عبارة عن force في distance
+
+199
+00:26:11,240 --> 00:26:19,400
+معناه الشغل من هنا ل هنا هيكون المساعة تحت الممحنة
+
+200
+00:26:19,400 --> 00:26:30,580
+هيكون الشغل U هيكون مساعة مثلث نص نص
+
+201
+00:26:30,580 --> 00:26:35,320
+هذه F نص في X في F
+
+202
+00:26:39,040 --> 00:26:44,620
+و ال X احنا عارفينها عبارة عن عندي برضه ال F
+
+203
+00:26:44,620 --> 00:26:50,420
+بالساوية K في X معناته ال X بالساوية F على K يعني
+
+204
+00:26:50,420 --> 00:26:58,460
+هتكون في F على K هتكون نص F Square على K اللي هي
+
+205
+00:26:58,460 --> 00:27:03,880
+زي ما يبين عندى ال U سواء F Square على 2K
+
+206
+00:27:12,760 --> 00:27:19,180
+معناته ال strain energy هتكون ال
+
+207
+00:27:19,180 --> 00:27:31,400
+U بسوة F2 على 2K في
+
+208
+00:27:31,400 --> 00:27:33,860
+حالة axially loaded member axially loaded member
+
+209
+00:27:33,860 --> 00:27:43,160
+يعني هاي axially loaded member تحت اثير Fاحنا
+
+210
+00:27:43,160 --> 00:27:48,400
+حكينا ال K تعني تعني ايش كان سواء ال K؟ A E على L
+
+211
+00:27:48,400 --> 00:27:51,440
+يعني
+
+212
+00:27:51,440 --> 00:27:59,340
+ال U هتكون سواء F Square على 2 في ال K اللي هي A E
+
+213
+00:27:59,340 --> 00:28:07,930
+على Lيعني هتكون .. هتطلع ال L هصير F squared L على
+
+214
+00:28:07,930 --> 00:28:15,350
+اتنين A E هذا في حالة كان ال cross section ثابت و
+
+215
+00:28:15,350 --> 00:28:21,290
+في حال كانت ال force ثابتة الآن لو كانت ال cross
+
+216
+00:28:21,290 --> 00:28:26,930
+section متغير أو و ال force متغيرة بيصير ان ال L
+
+217
+00:28:26,930 --> 00:28:33,390
+بيصير بدلها ايش DX يعني هصير انديوبيساوي F squared
+
+218
+00:28:33,390 --> 00:28:40,190
+DX على اتنين A A و ال U هيكوناش ال integration
+
+219
+00:28:40,190 --> 00:28:48,890
+يعني ال U هيكون تكامل F squared DX على اتنين A A
+
+220
+00:28:48,890 --> 00:28:58,690
+هذا في حالة X reloaded member في
+
+221
+00:28:58,690 --> 00:28:59,810
+حالة original
+
+222
+00:29:02,740 --> 00:29:07,340
+Torsional Torsional loaded member فاكرين أن ال K
+
+223
+00:29:07,340 --> 00:29:15,500
+كان سوى GG على L ال K سوى GG على L ال U نرجع
+
+224
+00:29:15,500 --> 00:29:23,000
+للمعادل الأصلية ال U بسوء F square على 2K
+
+225
+00:29:26,010 --> 00:29:32,390
+و ال K في الحالة هت يعني بتساوي يعني ال F is
+
+226
+00:29:32,390 --> 00:29:42,430
+analog لل torque و ال K عبارة عن GG على L يعني ال
+
+227
+00:29:42,430 --> 00:29:47,570
+U في حالة torque in loaded member هتكون عوض عن F
+
+228
+00:29:47,570 --> 00:29:55,320
+في Tعلى اتنين في K اللي هو G G على L يعني هتكون
+
+229
+00:29:55,320 --> 00:30:04,480
+سوا T square L على اتنين G في G هدف الحال كان ال
+
+230
+00:30:04,480 --> 00:30:09,560
+torque constant و المقطع constant مع الطول لو كان
+
+231
+00:30:09,560 --> 00:30:17,950
+واحد من ال torque او المقطع متغير مع الطولأو
+
+232
+00:30:17,950 --> 00:30:23,730
+كلاهما بيصير عند ال U تكامل بيصير ال U ساوى تكامل
+
+233
+00:30:23,730 --> 00:30:33,130
+T squared على اتنين GJDX في
+
+234
+00:30:33,130 --> 00:30:38,290
+حالة direct shear loading هذا direct شيري هذا
+
+235
+00:30:38,290 --> 00:30:43,440
+torsional shear في حالة direct shear loadingبيكون
+
+236
+00:30:43,440 --> 00:30:46,540
+الـ strain energy due to direct shear is given by
+
+237
+00:30:46,540 --> 00:30:51,460
+this equation الـ
+
+238
+00:30:51,460 --> 00:30:55,140
+A مساحة المقطع الـ G ال modulus of rigidity في حال
+
+239
+00:30:55,140 --> 00:30:59,000
+كانت ال force متغيرة قيمتها أو ال cross section
+
+240
+00:30:59,000 --> 00:31:02,720
+بتغير من مكان لمكان بيصير تتحول لمعادلة
+
+241
+00:31:02,720 --> 00:31:10,000
+integration في حال
+
+242
+00:31:10,000 --> 00:31:17,250
+bending هذاbending condition ال .. ال .. ال strain
+
+243
+00:31:17,250 --> 00:31:20,770
+energy due to bending is given by this equation M
+
+244
+00:31:20,770 --> 00:31:24,130
+squared L على 2EI هذا في حالة كانت ال bending
+
+245
+00:31:24,130 --> 00:31:29,530
+moment ثابتة مع الطول و المقطع ثابت مع الطول في
+
+246
+00:31:29,530 --> 00:31:36,540
+حالة كان المقطع متغير مع الطولأو و البنجم هو متغير
+
+247
+00:31:36,540 --> 00:31:39,500
+مع المقطع والطول بيصير عندي list of energy is
+
+248
+00:31:39,500 --> 00:31:42,800
+given by this equation تكامل M squared على 2 EI DX
+
+249
+00:31:53,660 --> 00:31:58,260
+في حالة transverse shear loading يعني بيكون عندى
+
+250
+00:31:58,260 --> 00:32:01,760
+bending يعني عندى ال load هنا بس بيكون shear هنا
+
+251
+00:32:01,760 --> 00:32:05,180
+يعني ال shear متجه عند ال load هذا بيسمى
+
+252
+00:32:05,180 --> 00:32:08,640
+transverse shear condition في الحالة ده ال U
+
+253
+00:32:08,640 --> 00:32:15,740
+بيستوى C في V square L على 2A في Gال V اللي هو ال
+
+254
+00:32:15,740 --> 00:32:20,220
+shear load أو ال transverse shear ال L الطول ال M
+
+255
+00:32:20,220 --> 00:32:24,900
+المقطع و ال G ال modulus of rigidity و ال C
+
+256
+00:32:24,900 --> 00:32:29,820
+modifier constant بيعتمد على شكل المقطع الشكل
+
+257
+00:32:29,820 --> 00:32:34,340
+المقطع ممكن مدور مستطيل مثلث ال C تعتمد على شكل
+
+258
+00:32:34,340 --> 00:32:35,380
+المقطع
+
+259
+00:32:43,240 --> 00:32:48,160
+جدول اربعة واحد ماعطيني ال modifier factor C في
+
+260
+00:32:48,160 --> 00:32:54,690
+حالة transverse shear loading conditionمقطع شكله
+
+261
+00:32:54,690 --> 00:32:58,330
+مستطيل ال C بيكون سواء واحد point اتنين في حالة
+
+262
+00:32:58,330 --> 00:33:02,590
+مقطع شكله مدور بتكون ال C two point one one في
+
+263
+00:33:02,590 --> 00:33:06,650
+حالة المقطع عبارة عن انبوب مدورة و رفيعة بتكون ال
+
+264
+00:33:06,650 --> 00:33:10,950
+C بيساوي اتنين في حالة box section بتكون ساوي ال
+
+265
+00:33:10,950 --> 00:33:20,670
+ال ال ال ال C بيساوي واحد نشوف مثال هذا
+
+266
+00:33:20,670 --> 00:33:25,400
+المثال الليهنحل السؤال هذا وننهي المحاضرة ان شاء
+
+267
+00:33:25,400 --> 00:33:28,800
+الله
+
+268
+00:33:28,800 --> 00:33:45,280
+ال
+
+269
+00:33:45,280 --> 00:33:51,000
+cantilever beamwith around cross section with
+
+270
+00:33:51,000 --> 00:33:53,920
+around cross section the cantilever beam مقطعه
+
+271
+00:33:53,920 --> 00:34:01,520
+مدور مقطعته مدور has a concentrated load F at the
+
+272
+00:34:01,520 --> 00:34:07,540
+end فيه load مركز عند الطرف قيمة ال load F
+
+273
+00:34:09,720 --> 00:34:15,800
+Find the strain energy in the beam أولا
+
+274
+00:34:15,800 --> 00:34:18,360
+عشان أحل مثل زيك لازم I have to define ال
+
+275
+00:34:18,360 --> 00:34:25,940
+coordinate system تبعي عندي هاي ال Y هذا
+
+276
+00:34:25,940 --> 00:34:32,300
+ال Y هذا
+
+277
+00:34:32,300 --> 00:34:43,120
+ال Xباخد على مسافة باخد هي section على بعد X
+
+278
+00:34:43,120 --> 00:34:58,660
+و باخد free body diagram عند
+
+279
+00:34:58,660 --> 00:34:59,760
+هذه ال force F
+
+280
+00:35:05,100 --> 00:35:13,440
+و هذه المسافة X أكيد
+
+281
+00:35:13,440 --> 00:35:21,400
+هيعكسها force F احيانا او خلينا نسميها V هتعمل
+
+282
+00:35:21,400 --> 00:35:28,640
+counter clockwise moment هتعكسها clockwise moment
+
+283
+00:35:28,640 --> 00:35:31,840
+وهي
+
+284
+00:35:31,840 --> 00:35:44,400
+عند ال Xو هاي ال Y اللي
+
+285
+00:35:44,400 --> 00:35:51,300
+أخد submission of forces بتجاه
+
+286
+00:35:51,300 --> 00:36:00,490
+ال Y بالساوة Zeroهيكون عندي minus F زائد V يعني ال
+
+287
+00:36:00,490 --> 00:36:12,570
+V لترانزل شير ايه شو ساوي؟ F لاخدت
+
+288
+00:36:12,570 --> 00:36:18,450
+ال .. ال .. ال moment هين summation of moment
+
+289
+00:36:18,450 --> 00:36:29,840
+حوالين نقطة X بالساوية سفرهيكون minus F في X زائد
+
+290
+00:36:29,840 --> 00:36:40,780
+M يعني ال M هستوى عندي إيه؟ F في X طيب
+
+291
+00:36:40,780 --> 00:36:46,640
+اللحظة و أنا عندي at any cross section at any
+
+292
+00:36:46,640 --> 00:36:51,140
+cross
+
+293
+00:36:51,140 --> 00:36:51,600
+section
+
+294
+00:36:55,670 --> 00:37:00,210
+we have bending
+
+295
+00:37:00,210 --> 00:37:04,790
+moment
+
+296
+00:37:04,790 --> 00:37:09,210
+and
+
+297
+00:37:09,210 --> 00:37:13,610
+transverse
+
+298
+00:37:13,610 --> 00:37:18,410
+shear معناته
+
+299
+00:37:18,410 --> 00:37:23,310
+total strain energy ال U هتكون U U ت transverse
+
+300
+00:37:23,310 --> 00:37:33,650
+shearthe due due to pending moment نرجع
+
+301
+00:37:33,650 --> 00:37:49,430
+لمعادلات due
+
+302
+00:37:49,430 --> 00:37:51,130
+to pending moment you
+
+303
+00:37:54,880 --> 00:38:04,860
+due to bending moment المعادلة هذه بيساوي تكامل M2
+
+304
+00:38:04,860 --> 00:38:11,400
+على 2EIDX
+
+305
+00:38:11,400 --> 00:38:19,300
+حيث ساوى طبعا التكامل حق من 0 لL هيكون تكامل من 0
+
+306
+00:38:19,300 --> 00:38:26,470
+لLالـ M هيبقى عبارة عن F X حاسس أن عندي F تربية X
+
+307
+00:38:26,470 --> 00:38:35,050
+تربية على 2EI DX لاحظوا أن المقطع ثابت و ال force
+
+308
+00:38:35,050 --> 00:38:37,370
+ثابتة هيطلع عبارة عن ال integration هيكون الساوية
+
+309
+00:38:37,370 --> 00:38:48,450
+F square على 2EI تكامل X
+
+310
+00:38:48,450 --> 00:38:56,200
+تربيةDX من سفر لأقل يعني إذا بعملها تكامل هتكون F2
+
+311
+00:38:56,200 --> 00:39:06,600
+على 2EI ل X تكييب على 3 من سفر لأقل يعني هتكون
+
+312
+00:39:06,600 --> 00:39:17,960
+تساوي F تربيع التكييب على 6EI
+
+313
+00:39:22,040 --> 00:39:27,940
+الان المقطع المدور ال I للمقطع المدور ال I للمقطع
+
+314
+00:39:27,940 --> 00:39:33,680
+المدور عبارة عن باي على أربع و ستين D أس أربعة
+
+315
+00:39:33,680 --> 00:39:38,240
+يعني
+
+316
+00:39:38,240 --> 00:39:47,900
+هتصير ال U to bending moment هتكون تساوي F
+
+317
+00:39:47,900 --> 00:39:57,450
+تربيعالتا كيب على ستة ا في I اللي هي باي على أربع
+
+318
+00:39:57,450 --> 00:40:06,730
+ستين ديقص أربعة هتساوي
+
+319
+00:40:06,730 --> 00:40:11,150
+اتنين
+
+320
+00:40:11,150 --> 00:40:18,230
+و تلاتين F تربيع ال تا كيب
+
+321
+00:40:21,780 --> 00:40:32,780
+على تلاتة E by D أُص أربعة هذا ال strain energy
+
+322
+00:40:32,780 --> 00:40:37,460
+due to bending طيب في عندي ال strain energy due to
+
+323
+00:40:37,460 --> 00:40:47,640
+transverse shear U due to transverse shear اللي
+
+324
+00:40:47,640 --> 00:40:50,500
+هي مواطنة على الأقل U هتكون تستاوية تكامل
+
+325
+00:41:20,450 --> 00:41:26,540
+معناه تحسين عن دي؟تكامل واحد point واحد واحد ال V
+
+326
+00:41:26,540 --> 00:41:34,240
+بيستوى F بصير ان دي F تربيع على اتنين ال A عبارة
+
+327
+00:41:34,240 --> 00:41:46,660
+عن باي على اربعة دي تربيع في G DX حسين
+
+328
+00:41:46,660 --> 00:41:47,540
+ان دي واحد
+
+329
+00:41:51,430 --> 00:42:04,710
+one point واحد في اتنين F square على by D تربيع في
+
+330
+00:42:04,710 --> 00:42:10,970
+G في L معناه
+
+331
+00:42:10,970 --> 00:42:13,710
+ال total strain energy هتكون U transverse shear
+
+332
+00:42:13,710 --> 00:42:19,270
+stress زي U bending moment هتكون تساوي اللي هي
+
+333
+00:42:19,270 --> 00:42:27,910
+حجمه اتنيناتنين point اتنين اتنين F تربيع L على
+
+334
+00:42:27,910 --> 00:42:37,490
+باي D تربيع G زاد U depending moment اتنين و
+
+335
+00:42:37,490 --> 00:42:51,630
+تلاتين F square التكيب على تلاتة
+
+336
+00:42:58,820 --> 00:43:11,600
+E by D أربعة يعني لو بدنا نبسط أكتر شوية أخدنا F
+
+337
+00:43:11,600 --> 00:43:21,380
+square L على by D تربيع F square L على by D تربيع
+
+338
+00:43:21,380 --> 00:43:25,680
+بالسيراندي اتنين
+
+339
+00:43:27,420 --> 00:43:38,980
+بونت اتنين اتنين على جي زائد اتنين و تلاتين
+
+340
+00:43:38,980 --> 00:43:42,140
+التربية
+
+341
+00:43:42,140 --> 00:43:45,340
+على
+
+342
+00:43:45,340 --> 00:43:48,980
+تلاتة
+
+343
+00:43:48,980 --> 00:43:51,880
+ا دي تربية
+
+344
+00:43:57,630 --> 00:44:03,050
+هيك يكون وجدنا total strain energy due to both
+
+345
+00:44:03,050 --> 00:44:08,050
+اللي هو transverse shear loading و bending loading
+
+346
+00:44:08,050 --> 00:44:14,770
+المحاضرة الجاي بنكمل
+
+347
+00:44:14,770 --> 00:44:17,990
+في ال strain energy بس هندرس اشي اسمه Castellano
+
+348
+00:44:17,990 --> 00:44:22,630
+theorem عشان نوجد deflection عند أي موقع في .. في
+
+349
+00:44:22,630 --> 00:44:25,370
+.. في beam تحت أثير أحمل
+
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/A-1SThU8Qv4_raw.json b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/A-1SThU8Qv4_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..5ddf8c2c19a163c55fbfba84603870813cd95bbd
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/A-1SThU8Qv4_raw.json
@@ -0,0 +1 @@
+{"segments": [{"id": 1, "seek": 2787, "start": 5.09, "end": 27.87, "text": "السلام عليكم اليوم هنكمل chapter أربعة او deflection and stiffness of beams في المحاضرة اللي الفاتة تعرفنا ال elasticity اللي هي خاصية للمادة بتمكنها من استعادة شكلها بمجرد رفع الأحمال ال spraying جايبها عن mechanical element اللي لو عملتله deflection بيعطيني force", "tokens": [6027, 3794, 37440, 25894, 24793, 45595, 20498, 8032, 1863, 24793, 1211, 7187, 5551, 25513, 27884, 1975, 2407, 1060, 5450, 293, 37759, 295, 31040, 8978, 9673, 5016, 46958, 25720, 13672, 1829, 27188, 9307, 3660, 37279, 28480, 8315, 2423, 46260, 13672, 1829, 39896, 16490, 33546, 10632, 5296, 19528, 18513, 3660, 39894, 43020, 11296, 9154, 44713, 3615, 18513, 3660, 13412, 28820, 11296, 4724, 2304, 7435, 2288, 3215, 12602, 5172, 3615, 16247, 35571, 6027, 2423, 36658, 10874, 47302, 3555, 11296, 18871, 12070, 4478, 13672, 1829, 45164, 6225, 42213, 2655, 43761, 1060, 5450, 4724, 40228, 9566, 9957, 1829, 3464], "avg_logprob": -0.1365131582084455, 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" ل", "probability": 0.94140625}, {"start": 43.96, "end": 44.28, "word": " X", "probability": 0.27587890625}, {"start": 44.28, "end": 44.76, "word": " reloaded", "probability": 0.955078125}, {"start": 44.76, "end": 45.06, "word": " member", "probability": 0.9443359375}, {"start": 45.06, "end": 45.34, "word": " كان", "probability": 0.978515625}, {"start": 45.34, "end": 45.52, "word": " ال", "probability": 0.689453125}, {"start": 45.52, "end": 45.7, "word": " K", "probability": 0.96533203125}, {"start": 45.7, "end": 46.16, "word": " بيساوي", "probability": 0.980859375}, {"start": 46.16, "end": 46.44, "word": " A", "probability": 0.91015625}, {"start": 46.44, "end": 46.62, "word": " في", "probability": 0.90673828125}, {"start": 46.62, "end": 46.82, "word": " E", "probability": 0.8603515625}, {"start": 46.82, "end": 47.02, "word": " على", "probability": 0.8984375}, {"start": 47.02, "end": 47.4, "word": " L", "probability": 0.990234375}, {"start": 47.4, "end": 49.0, "word": " في", 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"probability": 0.6171875}, {"start": 101.55, "end": 102.11, "word": " D²Y", "probability": 0.5395914713541666}, {"start": 102.11, "end": 102.29, "word": " بقى", "probability": 0.86767578125}, {"start": 102.29, "end": 103.17, "word": " DX²", "probability": 0.670654296875}, {"start": 103.17, "end": 105.35, "word": " بعد", "probability": 0.5947265625}, {"start": 105.35, "end": 105.71, "word": " حكينا", "probability": 0.8687744140625}, {"start": 105.71, "end": 105.95, "word": " فيه", "probability": 0.904541015625}, {"start": 105.95, "end": 106.25, "word": " أكتر", "probability": 0.890625}, {"start": 106.25, "end": 106.41, "word": " من", "probability": 0.99365234375}, {"start": 106.41, "end": 106.81, "word": " طريقة", "probability": 0.9949544270833334}, {"start": 106.81, "end": 108.15, "word": " لحسابات", "probability": 0.9310546875}, {"start": 108.15, "end": 108.55, "word": " الـ", "probability": 0.631591796875}, {"start": 108.55, "end": 109.11, "word": " deflection", "probability": 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الكتاب حلينا exam الأربعة اتنين باستخدام ال superposition", "tokens": [44510, 10721, 8315, 8978, 2423, 1687, 38078, 2423, 1687, 38078, 39894, 5016, 4117, 1829, 4724, 3555, 3794, 41193, 3660, 16472, 2423, 3217, 1802, 3462, 281, 264, 9354, 15114, 4188, 4724, 1829, 3794, 995, 45865, 3714, 7435, 2304, 45367, 2423, 2609, 1802, 3462, 281, 2609, 15114, 4487, 23032, 3555, 3615, 995, 6225, 8592, 7649, 8717, 5016, 1211, 2423, 1687, 38078, 8032, 1863, 14851, 9778, 40448, 3199, 316, 24, 8978, 33251, 2655, 16758, 11331, 20292, 8315, 1139, 16247, 25513, 27884, 1975, 2655, 1863, 9957, 4724, 995, 14851, 9778, 3215, 10943, 2423, 1687, 38078], "avg_logprob": -0.1672894023358822, "compression_ratio": 1.7788018433179724, "no_speech_prob": 0.0, "words": [{"start": 115.05, "end": 115.57, "word": "بدأنا", "probability": 0.7972005208333334}, {"start": 115.57, "end": 115.71, "word": " في", "probability": 0.7568359375}, {"start": 115.71, "end": 115.89, "word": " ال", "probability": 0.441650390625}, {"start": 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"end": 123.45, "word": " combined", "probability": 0.8525390625}, {"start": 123.45, "end": 123.87, "word": " loading", "probability": 0.91796875}, {"start": 123.87, "end": 124.73, "word": " condition", "probability": 0.73974609375}, {"start": 124.73, "end": 125.97, "word": " بيساوي", "probability": 0.63779296875}, {"start": 125.97, "end": 126.55, "word": " مجموع", "probability": 0.9381103515625}, {"start": 126.55, "end": 126.73, "word": " ال", "probability": 0.95654296875}, {"start": 126.73, "end": 127.31, "word": " individual", "probability": 0.85546875}, {"start": 127.31, "end": 129.05, "word": " effect", "probability": 0.8896484375}, {"start": 129.05, "end": 129.45, "word": " due", "probability": 0.89990234375}, {"start": 129.45, "end": 129.67, "word": " to", "probability": 0.96044921875}, {"start": 129.67, "end": 130.67, "word": " individual", "probability": 0.92578125}, {"start": 130.67, "end": 131.41, "word": " loading", "probability": 0.87841796875}, {"start": 131.41, "end": 132.25, "word": " conditions", "probability": 0.72802734375}, {"start": 132.25, "end": 133.25, "word": " طبعا", "probability": 0.978515625}, {"start": 133.25, "end": 133.53, "word": " عشان", "probability": 0.9646809895833334}, {"start": 133.53, "end": 133.93, "word": " نحل", "probability": 0.9900716145833334}, {"start": 133.93, "end": 134.07, "word": " ال", "probability": 0.92529296875}, {"start": 134.07, "end": 134.53, "word": " superposition", "probability": 0.97265625}, {"start": 134.53, "end": 135.23, "word": " هنستخدم", "probability": 0.9140625}, {"start": 135.23, "end": 135.67, "word": " table", "probability": 0.66455078125}, {"start": 135.67, "end": 136.41, "word": " A9", "probability": 0.784912109375}, {"start": 136.41, "end": 136.67, "word": " في", "probability": 0.88720703125}, {"start": 136.67, "end": 137.19, "word": " الكتاب", "probability": 0.9853515625}, {"start": 137.19, "end": 138.55, "word": " حلينا", "probability": 0.8601888020833334}, {"start": 138.55, "end": 138.89, "word": " exam", "probability": 0.78955078125}, {"start": 138.89, "end": 139.67, "word": " الأربعة", "probability": 0.6221516927083334}, {"start": 139.67, "end": 140.69, "word": " اتنين", "probability": 0.9398193359375}, {"start": 140.69, "end": 141.43, "word": " باستخدام", "probability": 0.992431640625}, {"start": 141.43, "end": 141.71, "word": " ال", "probability": 0.94580078125}, {"start": 141.71, "end": 142.43, "word": " superposition", "probability": 0.965087890625}], "temperature": 1.0}, {"id": 6, "seek": 16563, "start": 146.09, "end": 165.63, "text": "هنحل المسألة التانية باستخدام ال support position هنحل المسألة التالية determine the deflection equations using support position for the given beam في عند beam simply supported عند a و b", "tokens": [3224, 1863, 5016, 1211, 9673, 3794, 10721, 37977, 16712, 7649, 10632, 4724, 995, 14851, 9778, 3215, 10943, 2423, 1406, 2535, 8032, 1863, 5016, 1211, 9673, 3794, 10721, 37977, 16712, 6027, 10632, 6997, 264, 1060, 5450, 11787, 1228, 1406, 2535, 337, 264, 2212, 14269, 8978, 43242, 14269, 2935, 8104, 43242, 257, 4032, 272], "avg_logprob": -0.15138561320754718, "compression_ratio": 1.5548387096774194, "no_speech_prob": 0.0, "words": [{"start": 146.09, "end": 146.59, "word": "هنحل", "probability": 0.8887939453125}, {"start": 146.59, "end": 147.05, "word": " المسألة", "probability": 0.901123046875}, {"start": 147.05, "end": 147.43, "word": " التانية", "probability": 0.908203125}, {"start": 147.43, "end": 148.17, "word": " باستخدام", "probability": 0.9803059895833334}, {"start": 148.17, "end": 148.67, "word": " ال", "probability": 0.626953125}, {"start": 148.67, "end": 148.93, "word": " support", "probability": 0.56298828125}, {"start": 148.93, "end": 149.99, "word": " position", "probability": 0.9755859375}, {"start": 149.99, "end": 151.89, "word": " هنحل", "probability": 0.9088134765625}, {"start": 151.89, "end": 152.99, "word": " المسألة", "probability": 0.975830078125}, {"start": 152.99, "end": 153.81, "word": " 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992.4, "end": 1016.84, "text": "في اتنين L X تربيع minus X تكييب minus L تكييب X بين سفر و L الفترة التانية هتكون", "tokens": [41185, 1975, 2655, 1863, 9957, 441, 1783, 6055, 2288, 21292, 3615, 3175, 1783, 6055, 4117, 1829, 1829, 3555, 3175, 441, 6055, 4117, 1829, 1829, 3555, 1783, 49374, 8608, 5172, 2288, 4032, 441, 27188, 2655, 25720, 16712, 7649, 10632, 8032, 2655, 30544], "avg_logprob": -0.18787201919725963, "compression_ratio": 1.3195876288659794, "no_speech_prob": 0.0, "words": [{"start": 992.4, "end": 992.68, "word": "في", "probability": 0.244384765625}, {"start": 992.68, "end": 993.22, "word": " اتنين", "probability": 0.838623046875}, {"start": 993.22, "end": 994.76, "word": " L", "probability": 0.286865234375}, {"start": 994.76, "end": 996.1, "word": " X", "probability": 0.69091796875}, {"start": 996.1, "end": 996.68, "word": " تربيع", "probability": 0.7362060546875}, {"start": 996.68, "end": 999.02, "word": " minus", "probability": 0.55859375}, {"start": 999.02, "end": 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"probability": 0.96875}], "temperature": 1.0}, {"id": 35, "seek": 104842, "start": 1021.66, "end": 1048.42, "text": "بتكون تساوي W L تكيب على 24 EI في X minus L طبعا هنا X", "tokens": [3555, 2655, 30544, 6055, 3794, 995, 45865, 343, 441, 6055, 4117, 1829, 3555, 15844, 4022, 462, 40, 8978, 1783, 3175, 441, 23032, 3555, 3615, 995, 34105, 1783], "avg_logprob": -0.3292410799435207, "compression_ratio": 0.975609756097561, "no_speech_prob": 0.0, "words": [{"start": 1021.66, "end": 1022.1, "word": "بتكون", "probability": 0.7183837890625}, {"start": 1022.1, "end": 1022.48, "word": " تساوي", "probability": 0.7296142578125}, {"start": 1022.48, "end": 1023.12, "word": " W", "probability": 0.40625}, {"start": 1023.12, "end": 1026.82, "word": " L", "probability": 0.380859375}, {"start": 1026.82, "end": 1027.48, "word": " تكيب", "probability": 0.8052978515625}, {"start": 1027.48, "end": 1029.38, "word": " على", "probability": 0.60546875}, {"start": 1029.38, "end": 1030.0, "word": " 24", 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{"start": 1092.44, "end": 1092.96, "word": " للمسألة", "probability": 0.858642578125}, {"start": 1092.96, "end": 1094.22, "word": " تاعتنا", "probability": 0.781768798828125}, {"start": 1094.22, "end": 1100.6, "word": " أقرب", "probability": 0.9142252604166666}, {"start": 1100.6, "end": 1101.08, "word": " حالة", "probability": 0.9921875}, {"start": 1101.08, "end": 1101.6, "word": " للحالة", "probability": 0.8721923828125}, {"start": 1101.6, "end": 1102.02, "word": " تاعتنا", "probability": 0.958251953125}, {"start": 1102.02, "end": 1102.22, "word": " اللي", "probability": 0.70458984375}, {"start": 1102.22, "end": 1103.1, "word": " هي", "probability": 0.91748046875}, {"start": 1103.1, "end": 1104.36, "word": " appendix", "probability": 0.80078125}, {"start": 1104.36, "end": 1107.06, "word": " A", "probability": 0.439208984375}], "temperature": 1.0}, {"id": 38, "seek": 113849, "start": 1109.83, "end": 1138.49, "text": "تسعة عشرة معطيني هنا R واحد double prime بتساوي FA على L وR اتنين double prime بتساوي", "tokens": [2655, 3794, 27884, 6225, 8592, 25720, 3714, 3615, 9566, 9957, 1829, 34105, 497, 36764, 24401, 3834, 5835, 39894, 3794, 995, 45865, 19894, 15844, 441, 4032, 49, 1975, 2655, 1863, 9957, 3834, 5835, 39894, 3794, 995, 45865], "avg_logprob": -0.29011825290886134, "compression_ratio": 1.2211538461538463, "no_speech_prob": 7.748603820800781e-07, "words": [{"start": 1109.83, "end": 1110.43, "word": "تسعة", "probability": 0.7242431640625}, {"start": 1110.43, "end": 1112.03, "word": " عشرة", "probability": 0.8863932291666666}, {"start": 1112.03, "end": 1116.89, "word": " معطيني", "probability": 0.63447265625}, {"start": 1116.89, "end": 1117.07, "word": " هنا", "probability": 0.57080078125}, {"start": 1117.07, "end": 1117.37, "word": " R", "probability": 0.48779296875}, {"start": 1117.37, "end": 1117.85, "word": " واحد", "probability": 0.846923828125}, {"start": 1117.85, "end": 1118.09, "word": " double", "probability": 0.74755859375}, {"start": 1118.09, "end": 1118.61, "word": " prime", "probability": 0.86767578125}, {"start": 1118.61, "end": 1124.89, "word": " بتساوي", "probability": 0.8031005859375}, {"start": 1124.89, "end": 1126.23, "word": " FA", "probability": 0.371337890625}, {"start": 1126.23, "end": 1128.27, "word": " على", "probability": 0.80859375}, {"start": 1128.27, "end": 1128.65, "word": " L", "probability": 0.892578125}, {"start": 1128.65, "end": 1131.01, "word": " وR", "probability": 0.733642578125}, {"start": 1131.01, "end": 1131.57, "word": " اتنين", "probability": 0.9447021484375}, {"start": 1131.57, "end": 1135.23, "word": " double", "probability": 0.892578125}, {"start": 1135.23, "end": 1135.77, "word": " prime", "probability": 0.89892578125}, {"start": 1135.77, "end": 1138.49, "word": " بتساوي", "probability": 0.964599609375}], "temperature": 1.0}, {"id": 39, "seek": 116977, "start": 1142.13, "end": 1169.77, "text": "بس انتبهوا للإشارات R واحد احنا هتكون بالسالب انا جاله تحت هتكون بالسالب و R اتنين double prime F على L في L زائد A بالنسبال ال deflection", "tokens": [3555, 3794, 16472, 2655, 3555, 3224, 14407, 24976, 28814, 8592, 9640, 9307, 497, 36764, 24401, 1975, 5016, 8315, 8032, 2655, 30544, 20666, 3794, 6027, 3555, 1975, 8315, 10874, 6027, 3224, 6055, 33753, 8032, 2655, 30544, 20666, 3794, 6027, 3555, 4032, 497, 1975, 2655, 1863, 9957, 3834, 5835, 479, 15844, 441, 8978, 441, 30767, 16373, 3215, 316, 20666, 1863, 35457, 6027, 2423, 1060, 5450], "avg_logprob": -0.1947021537926048, "compression_ratio": 1.4230769230769231, "no_speech_prob": 0.0, "words": [{"start": 1142.13, "end": 1142.53, "word": "بس", "probability": 0.954345703125}, {"start": 1142.53, "end": 1142.95, "word": " انتبهوا", "probability": 0.97666015625}, {"start": 1142.95, "end": 1144.21, "word": " للإشارات", "probability": 0.924609375}, {"start": 1144.21, "end": 1145.19, "word": " R", "probability": 0.47119140625}, {"start": 1145.19, "end": 1145.63, "word": " واحد", "probability": 0.59185791015625}, {"start": 1145.63, "end": 1146.09, "word": " احنا", "probability": 0.8932291666666666}, {"start": 1146.09, "end": 1146.77, "word": " هتكون", "probability": 0.9122721354166666}, {"start": 1146.77, "end": 1147.67, "word": " بالسالب", "probability": 0.9056396484375}, {"start": 1147.67, "end": 1149.29, "word": " انا", "probability": 0.60723876953125}, {"start": 1149.29, "end": 1149.57, "word": " جاله", "probability": 0.7726236979166666}, {"start": 1149.57, "end": 1149.97, "word": " تحت", "probability": 0.9892578125}, {"start": 1149.97, "end": 1152.43, "word": " هتكون", "probability": 0.880859375}, {"start": 1152.43, "end": 1153.21, "word": " بالسالب", "probability": 0.9862060546875}, {"start": 1153.21, "end": 1154.75, "word": " و", "probability": 0.78076171875}, {"start": 1154.75, "end": 1154.95, "word": " R", "probability": 0.60693359375}, {"start": 1154.95, "end": 1155.37, "word": " اتنين", "probability": 0.92529296875}, {"start": 1155.37, "end": 1155.65, "word": " double", "probability": 0.4462890625}, {"start": 1155.65, "end": 1156.47, "word": " prime", "probability": 0.8408203125}, {"start": 1156.47, "end": 1157.95, "word": " F", "probability": 0.8203125}, {"start": 1157.95, "end": 1160.59, "word": " على", "probability": 0.81494140625}, {"start": 1160.59, "end": 1160.99, "word": " L", "probability": 0.951171875}, {"start": 1160.99, "end": 1162.67, "word": " في", "probability": 0.69140625}, {"start": 1162.67, "end": 1162.97, "word": " L", "probability": 0.9287109375}, {"start": 1162.97, "end": 1163.83, "word": " زائد", "probability": 0.8883463541666666}, {"start": 1163.83, "end": 1164.59, "word": " A", "probability": 0.91943359375}, {"start": 1164.59, "end": 1169.13, "word": " بالنسبال", "probability": 0.9140625}, {"start": 1169.13, "end": 1169.23, "word": " ال", "probability": 0.3056640625}, {"start": 1169.23, "end": 1169.77, "word": " deflection", "probability": 0.729248046875}], "temperature": 1.0}, {"id": 40, "seek": 119944, "start": 1172.14, "end": 1199.44, "text": "الـ deflection عبارة عن مقطعين فيه deflection معادلة من a ل b و فيه معادلة من b ل c يعني هيكون عندي y double prime من a ل b هيكون fax على 6eil", "tokens": [6027, 39184, 1060, 5450, 6225, 3555, 9640, 3660, 18871, 3714, 47432, 3615, 9957, 8978, 3224, 1060, 5450, 20449, 18513, 37977, 9154, 257, 5296, 272, 4032, 8978, 3224, 20449, 18513, 37977, 9154, 272, 5296, 269, 37495, 22653, 8032, 1829, 30544, 18871, 16254, 288, 3834, 5835, 9154, 257, 5296, 272, 39896, 30544, 283, 2797, 15844, 1386, 30684], "avg_logprob": -0.2607421949505806, "compression_ratio": 1.5, "no_speech_prob": 0.0, "words": [{"start": 1172.14, "end": 1172.44, "word": "الـ", "probability": 0.7919921875}, {"start": 1172.44, "end": 1172.8, "word": " deflection", "probability": 0.6904296875}, {"start": 1172.8, "end": 1173.3, "word": " عبارة", "probability": 0.941162109375}, {"start": 1173.3, "end": 1174.6, "word": " عن", "probability": 0.9970703125}, {"start": 1174.6, "end": 1176.12, "word": " مقطعين", "probability": 0.9754638671875}, {"start": 1176.12, "end": 1176.56, "word": " فيه", "probability": 0.5535888671875}, {"start": 1176.56, "end": 1177.08, "word": " deflection", "probability": 0.72900390625}, {"start": 1177.08, "end": 1177.76, "word": " معادلة", "probability": 0.9685872395833334}, {"start": 1177.76, "end": 1178.0, "word": " من", "probability": 0.97412109375}, {"start": 1178.0, "end": 1178.18, "word": " a", "probability": 0.55859375}, {"start": 1178.18, "end": 1178.3, "word": " ل", "probability": 0.7451171875}, {"start": 1178.3, "end": 1178.58, "word": " b", "probability": 0.66064453125}, {"start": 1178.58, "end": 1179.34, "word": " و", "probability": 0.7333984375}, {"start": 1179.34, "end": 1179.5, "word": " فيه", "probability": 0.44989013671875}, {"start": 1179.5, "end": 1179.94, "word": " معادلة", "probability": 0.9869791666666666}, {"start": 1179.94, "end": 1180.16, "word": " من", "probability": 0.9560546875}, {"start": 1180.16, "end": 1180.6, "word": " b", "probability": 0.95361328125}, {"start": 1180.6, "end": 1181.0, 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"word": " تربية", "probability": 0.6998697916666666}, {"start": 1205.73, "end": 1206.09, "word": " نقص", "probability": 0.6693522135416666}, {"start": 1206.09, "end": 1206.23, "word": " X", "probability": 0.935546875}, {"start": 1206.23, "end": 1206.57, "word": " تربية", "probability": 0.95556640625}, {"start": 1206.57, "end": 1210.87, "word": " يعني", "probability": 0.4962158203125}, {"start": 1210.87, "end": 1211.75, "word": " هنا", "probability": 0.53515625}, {"start": 1211.75, "end": 1212.09, "word": " X", "probability": 0.94482421875}, {"start": 1212.09, "end": 1212.31, "word": " بين", "probability": 0.85009765625}, {"start": 1212.31, "end": 1212.71, "word": " سفر", "probability": 0.670654296875}, {"start": 1212.71, "end": 1216.61, "word": " و", "probability": 0.576171875}, {"start": 1216.61, "end": 1217.01, "word": " L", "probability": 0.72021484375}, {"start": 1217.01, "end": 1218.09, "word": " و", "probability": 0.54541015625}, {"start": 1218.09, "end": 1218.55, "word": " 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1259.75, "end": 1288.39, "text": "و X أكبر أو يساوي L أخر يساوي A زائد L معناته إحنا وجدنا ال individual effect for each loading condition وجدنا R1 prime وR2 prime وY prime ووجدنا ال individual effect due to this loading condition عندي R1 prime وR2 prime وY W prime معناته ال total effect ال R1", "tokens": [2407, 1783, 5551, 4117, 26890, 34051, 7251, 3794, 995, 45865, 441, 5551, 34740, 7251, 3794, 995, 45865, 316, 30767, 16373, 3215, 441, 20449, 8315, 47395, 11933, 5016, 8315, 49610, 3215, 8315, 2423, 2609, 1802, 337, 1184, 15114, 4188, 49610, 3215, 8315, 497, 16, 5835, 4032, 49, 17, 5835, 4032, 56, 5835, 4032, 29245, 3215, 8315, 2423, 2609, 1802, 3462, 281, 341, 15114, 4188, 18871, 16254, 497, 16, 5835, 4032, 49, 17, 5835, 4032, 56, 343, 5835, 20449, 8315, 47395, 2423, 3217, 1802, 2423, 497, 16], "avg_logprob": -0.24000727246667064, "compression_ratio": 1.8043478260869565, "no_speech_prob": 0.0, "words": [{"start": 1259.75, "end": 1259.97, "word": "و", "probability": 0.43994140625}, 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1458.44, "end": 1458.7, "word": " double", "probability": 0.88427734375}, {"start": 1458.7, "end": 1459.14, "word": " check", "probability": 0.93115234375}, {"start": 1459.14, "end": 1459.36, "word": " ال", "probability": 0.84619140625}, {"start": 1459.36, "end": 1459.88, "word": " calculation", "probability": 0.94384765625}, {"start": 1459.88, "end": 1460.52, "word": " بتاعتك", "probability": 0.870361328125}], "temperature": 1.0}, {"id": 50, "seek": 147652, "start": 1461.64, "end": 1476.52, "text": "عوض X بالساوية سفر هتعطيني ايش؟ Deflection بالساوية سفر عوض X بالساوية L هي سفر وهي سفر معناته الاشي صحيح", "tokens": [3615, 2407, 11242, 1783, 20666, 3794, 995, 2407, 10632, 8608, 5172, 2288, 8032, 2655, 3615, 9566, 1829, 22653, 1975, 1829, 8592, 22807, 9548, 5450, 20666, 3794, 995, 2407, 10632, 8608, 5172, 2288, 6225, 2407, 11242, 1783, 20666, 3794, 995, 2407, 10632, 441, 39896, 8608, 5172, 2288, 37037, 1829, 8608, 5172, 2288, 20449, 8315, 47395, 2423, 33599, 1829, 20328, 5016, 1829, 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عليه deflection لو سيبت طرف", "tokens": [28814, 15730, 43242, 7578, 30767, 1863, 26890, 4117, 4032, 8608, 5016, 3555, 2655, 4032, 11242, 1211, 2655, 9154, 2423, 6094, 4724, 1829, 30544, 6156, 7578, 23032, 995, 28671, 3714, 38149, 11622, 1863, 3660, 4724, 38251, 1829, 11296, 14249, 2281, 29538, 41950, 995, 28671, 9673, 38149, 11622, 1863, 3660, 8717, 31371, 7435, 3660, 36145, 6156, 7578, 47356, 1060, 5450, 45164, 8608, 1829, 3555, 2655, 23032, 28480], "avg_logprob": -0.23757101911487002, "compression_ratio": 1.4303797468354431, "no_speech_prob": 0.0, "words": [{"start": 1521.63, "end": 1522.01, "word": "إذا", "probability": 0.894287109375}, {"start": 1522.01, "end": 1522.55, "word": " عندى", "probability": 0.71142578125}, {"start": 1522.55, "end": 1523.23, "word": " زنبرك", "probability": 0.716796875}, {"start": 1523.23, "end": 1525.13, "word": " و", "probability": 0.8232421875}, {"start": 1525.13, "end": 1525.63, "word": " سحبت", "probability": 0.96533203125}, {"start": 1525.63, "end": 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" سوى", "probability": 0.738525390625}, {"start": 1751.5, "end": 1751.78, "word": " GG", "probability": 0.9541015625}, {"start": 1751.78, "end": 1752.2, "word": " على", "probability": 0.8544921875}, {"start": 1752.2, "end": 1753.24, "word": " L", "probability": 0.9833984375}, {"start": 1753.24, "end": 1754.16, "word": " ال", "probability": 0.853515625}, {"start": 1754.16, "end": 1754.46, "word": " U", "probability": 0.96728515625}, {"start": 1754.46, "end": 1755.5, "word": " نرجع", "probability": 0.83740234375}, {"start": 1755.5, "end": 1755.86, "word": " للمعادل", "probability": 0.764208984375}, {"start": 1755.86, "end": 1756.3, "word": " الأصلية", "probability": 0.79248046875}, {"start": 1756.3, "end": 1756.48, "word": " ال", "probability": 0.84033203125}, {"start": 1756.48, "end": 1756.78, "word": " U", "probability": 0.97509765625}, {"start": 1756.78, "end": 1758.56, "word": " بسوء", "probability": 0.68359375}, {"start": 1758.56, "end": 1758.82, "word": " F", "probability": 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analog", "probability": 0.81689453125}, {"start": 1772.93, "end": 1774.15, "word": " لل", "probability": 0.403076171875}, {"start": 1774.15, "end": 1774.69, "word": " torque", "probability": 0.79931640625}, {"start": 1774.69, "end": 1776.29, "word": " و", "probability": 0.8017578125}, {"start": 1776.29, "end": 1776.51, "word": " ال", "probability": 0.654296875}, {"start": 1776.51, "end": 1776.81, "word": " K", "probability": 0.9677734375}, {"start": 1776.81, "end": 1777.65, "word": " عبارة", "probability": 0.9129638671875}, {"start": 1777.65, "end": 1777.89, "word": " عن", "probability": 0.98388671875}, {"start": 1777.89, "end": 1779.05, "word": " GG", "probability": 0.4814453125}, {"start": 1779.05, "end": 1780.59, "word": " على", "probability": 0.4931640625}, {"start": 1780.59, "end": 1781.25, "word": " L", "probability": 0.98095703125}, {"start": 1781.25, "end": 1782.29, "word": " يعني", "probability": 0.950927734375}, {"start": 1782.29, "end": 1782.43, "word": " ال", "probability": 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{"start": 1787.77, "end": 1787.97, "word": " T", "probability": 0.921875}], "temperature": 1.0}, {"id": 61, "seek": 181688, "start": 1789.68, "end": 1816.88, "text": "على اتنين في K اللي هو G G على L يعني هتكون سوا T square L على اتنين G في G هدف الحال كان ال torque constant و المقطع constant مع الطول لو كان واحد من ال torque او المقطع متغير مع الطول", "tokens": [3615, 23942, 1975, 2655, 1863, 9957, 8978, 591, 13672, 1829, 31439, 460, 460, 15844, 441, 37495, 22653, 8032, 2655, 30544, 8608, 14407, 314, 3732, 441, 15844, 1975, 2655, 1863, 9957, 460, 8978, 460, 8032, 3215, 5172, 21542, 6027, 25961, 2423, 16437, 5754, 4032, 9673, 47432, 3615, 5754, 20449, 41950, 12610, 45164, 25961, 36764, 24401, 9154, 2423, 16437, 1975, 2407, 9673, 47432, 3615, 44650, 17082, 13546, 20449, 41950, 12610], "avg_logprob": -0.24479166148365408, "compression_ratio": 1.7023809523809523, "no_speech_prob": 1.1920928955078125e-07, "words": [{"start": 1789.68, "end": 1790.0, "word": "على", "probability": 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1795.62, "end": 1795.88, "word": " T", "probability": 0.57861328125}, {"start": 1795.88, "end": 1796.52, "word": " square", "probability": 0.212646484375}, {"start": 1796.52, "end": 1797.72, "word": " L", "probability": 0.90771484375}, {"start": 1797.72, "end": 1798.52, "word": " على", "probability": 0.78564453125}, {"start": 1798.52, "end": 1799.1, "word": " اتنين", "probability": 0.9605712890625}, {"start": 1799.1, "end": 1799.72, "word": " G", "probability": 0.9052734375}, {"start": 1799.72, "end": 1801.5, "word": " في", "probability": 0.85205078125}, {"start": 1801.5, "end": 1801.76, "word": " G", "probability": 0.572265625}, {"start": 1801.76, "end": 1803.48, "word": " هدف", "probability": 0.8426106770833334}, {"start": 1803.48, "end": 1803.82, "word": " الحال", "probability": 0.93896484375}, {"start": 1803.82, "end": 1804.12, "word": " كان", "probability": 0.9765625}, {"start": 1804.12, "end": 1804.48, "word": " ال", "probability": 0.9013671875}, {"start": 1804.48, "end": 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"probability": 0.95654296875}], "temperature": 1.0}, {"id": 63, "seek": 187106, "start": 1842.98, "end": 1871.06, "text": "بيكون الـ strain energy due to direct shear is given by this equation الـ A مساحة المقطع الـ G ال modulus of rigidity في حال كانت ال force متغيرة قيمتها أو ال cross section بتغير من مكان لمكان بيصير تتحول لمعادلة integration في حال bending هذا", "tokens": [3555, 1829, 30544, 2423, 39184, 14249, 2281, 3462, 281, 2047, 24082, 307, 2212, 538, 341, 5367, 2423, 39184, 316, 47524, 39319, 3660, 9673, 47432, 3615, 2423, 39184, 460, 2423, 42287, 295, 8329, 17711, 8978, 11331, 6027, 25961, 2655, 2423, 3464, 44650, 17082, 48923, 12174, 32640, 2655, 11296, 34051, 2423, 3278, 3541, 39894, 17082, 13546, 9154, 3714, 41361, 32767, 41361, 4724, 1829, 9381, 13546, 6055, 2655, 5016, 12610, 32767, 3615, 18513, 37977, 10980, 8978, 11331, 6027, 22487, 23758], "avg_logprob": -0.26582532547987425, "compression_ratio": 1.4632034632034632, "no_speech_prob": 0.0, "words": [{"start": 1842.98, 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moment ثابتة مع الطول و المقطع ثابت مع الطول في حالة كان المقطع متغير مع الطول", "tokens": [65, 2029, 4188, 2423, 4386, 2423, 4386, 2423, 14249, 2281, 3462, 281, 22487, 307, 2212, 538, 341, 5367, 376, 8889, 441, 15844, 568, 36, 40, 23758, 8978, 11331, 6027, 3660, 25961, 2655, 2423, 22487, 1623, 38637, 16758, 2655, 3660, 20449, 41950, 12610, 4032, 9673, 47432, 3615, 38637, 16758, 2655, 20449, 41950, 12610, 8978, 11331, 6027, 3660, 25961, 9673, 47432, 3615, 44650, 17082, 13546, 20449, 41950, 12610], "avg_logprob": -0.17012592838771307, "compression_ratio": 1.6388888888888888, "no_speech_prob": 0.0, "words": [{"start": 1873.09, "end": 1873.51, "word": "bending", "probability": 0.544677734375}, {"start": 1873.51, "end": 1874.09, "word": " condition", "probability": 0.92333984375}, {"start": 1874.09, "end": 1875.93, "word": " ال", "probability": 0.49169921875}, {"start": 1875.93, "end": 1875.93, "word": " ..", "probability": 0.277587890625}, {"start": 1875.93, "end": 1876.43, "word": " ال", 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193318, "start": 1913.66, "end": 1933.18, "text": "في حالة transverse shear loading يعني بيكون عندى bending يعني عندى ال load هنا بس بيكون shear هنا يعني ال shear متجه عند ال load هذا بيسمى transverse shear condition في الحالة ده ال U بيستوى C في V square L على 2A في G", "tokens": [41185, 11331, 6027, 3660, 1145, 4308, 24082, 15114, 37495, 22653, 4724, 1829, 30544, 43242, 7578, 22487, 37495, 22653, 43242, 7578, 2423, 3677, 34105, 4724, 3794, 4724, 1829, 30544, 24082, 34105, 37495, 22653, 2423, 24082, 44650, 7435, 3224, 43242, 2423, 3677, 23758, 4724, 1829, 38251, 7578, 1145, 4308, 24082, 4188, 8978, 21542, 6027, 3660, 11778, 3224, 2423, 624, 4724, 1829, 14851, 2407, 7578, 383, 8978, 691, 3732, 441, 15844, 568, 32, 8978, 460], "avg_logprob": -0.29815923351131074, "compression_ratio": 1.7401129943502824, "no_speech_prob": 0.0, "words": [{"start": 1913.66, "end": 1913.9, "word": "في", "probability": 0.60693359375}, {"start": 1913.9, "end": 1914.4, "word": " حالة", "probability": 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2036.62, "word": " مدور", "probability": 0.9710286458333334}, {"start": 2036.62, "end": 2039.24, "word": " has", "probability": 0.72705078125}, {"start": 2039.24, "end": 2039.54, "word": " a", "probability": 0.98779296875}, {"start": 2039.54, "end": 2040.22, "word": " concentrated", "probability": 0.96484375}, {"start": 2040.22, "end": 2040.7, "word": " load", "probability": 0.9697265625}, {"start": 2040.7, "end": 2041.06, "word": " F", "probability": 0.71728515625}, {"start": 2041.06, "end": 2041.36, "word": " at", "probability": 0.89892578125}, {"start": 2041.36, "end": 2041.52, "word": " the", "probability": 0.91064453125}, {"start": 2041.52, "end": 2041.78, "word": " end", "probability": 0.91943359375}, {"start": 2041.78, "end": 2042.82, "word": " فيه", "probability": 0.632080078125}, {"start": 2042.82, "end": 2043.62, "word": " load", "probability": 0.8642578125}, {"start": 2043.62, "end": 2044.52, "word": " مركز", "probability": 0.94873046875}, {"start": 2044.52, "end": 2044.8, "word": " عند", "probability": 0.98388671875}, {"start": 2044.8, "end": 2045.3, "word": " الطرف", "probability": 0.988037109375}, {"start": 2045.3, "end": 2046.26, "word": " قيمة", "probability": 0.9842122395833334}, {"start": 2046.26, "end": 2046.36, "word": " ال", "probability": 0.89111328125}, {"start": 2046.36, "end": 2046.64, "word": " load", "probability": 0.859375}, {"start": 2046.64, "end": 2047.54, "word": " F", "probability": 0.9140625}], "temperature": 1.0}, {"id": 72, "seek": 207278, "start": 2049.72, "end": 2072.78, "text": "Find the strain energy in the beam أولا عشان أحل مثل زيك لازم I have to define ال coordinate system تبعي عندي هاي ال Y هذا ال Y هذا ال X", "tokens": [37, 471, 264, 14249, 2281, 294, 264, 14269, 5551, 12610, 995, 6225, 8592, 7649, 5551, 5016, 1211, 50113, 1211, 30767, 1829, 4117, 5296, 31377, 2304, 286, 362, 281, 6964, 2423, 15670, 1185, 6055, 3555, 3615, 1829, 18871, 16254, 8032, 47302, 2423, 398, 23758, 2423, 398, 23758, 2423, 1783], "avg_logprob": 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0.65673828125}, {"start": 2056.74, "end": 2057.02, "word": " زيك", "probability": 0.8146158854166666}, {"start": 2057.02, "end": 2057.32, "word": " لازم", "probability": 0.9339192708333334}, {"start": 2057.32, "end": 2057.48, "word": " I", "probability": 0.471435546875}, {"start": 2057.48, "end": 2057.72, "word": " have", "probability": 0.95703125}, {"start": 2057.72, "end": 2057.84, "word": " to", "probability": 0.94482421875}, {"start": 2057.84, "end": 2058.24, "word": " define", "probability": 0.98095703125}, {"start": 2058.24, "end": 2058.36, "word": " ال", "probability": 0.84130859375}, {"start": 2058.36, "end": 2058.68, "word": " coordinate", "probability": 0.4267578125}, {"start": 2058.68, "end": 2059.16, "word": " system", "probability": 0.970703125}, {"start": 2059.16, "end": 2059.58, "word": " تبعي", "probability": 0.793701171875}, {"start": 2059.58, "end": 2060.62, "word": " عندي", "probability": 0.583984375}, {"start": 2060.62, "end": 2060.88, "word": " هاي", "probability": 0.6475830078125}, {"start": 2060.88, "end": 2061.12, "word": " ال", "probability": 0.97021484375}, {"start": 2061.12, "end": 2061.62, "word": " Y", "probability": 0.77001953125}, {"start": 2061.62, "end": 2065.94, "word": " هذا", "probability": 0.6669921875}, {"start": 2065.94, "end": 2066.1, "word": " ال", "probability": 0.94677734375}, {"start": 2066.1, "end": 2067.46, "word": " Y", "probability": 0.943359375}, {"start": 2067.46, "end": 2072.3, "word": " هذا", "probability": 0.94384765625}, {"start": 2072.3, "end": 2072.46, "word": " ال", "probability": 0.890625}, {"start": 2072.46, "end": 2072.78, "word": " X", "probability": 0.97802734375}], "temperature": 1.0}, {"id": 73, "seek": 209976, "start": 2075.12, "end": 2099.76, "text": "باخد على مسافة باخد هي section على بعد X و باخد free body diagram عند هذه ال force F", "tokens": [3555, 47283, 3215, 15844, 47524, 31845, 3660, 4724, 47283, 3215, 39896, 3541, 15844, 39182, 1783, 4032, 4724, 47283, 3215, 1737, 1772, 10686, 43242, 29538, 2423, 3464, 479], "avg_logprob": -0.2809709736279079, "compression_ratio": 1.174757281553398, "no_speech_prob": 0.0, "words": [{"start": 2075.12, "end": 2075.54, "word": "باخد", "probability": 0.8531901041666666}, {"start": 2075.54, "end": 2075.68, "word": " على", "probability": 0.6708984375}, {"start": 2075.68, "end": 2076.16, "word": " مسافة", "probability": 0.98388671875}, {"start": 2076.16, "end": 2076.72, "word": " باخد", "probability": 0.8836263020833334}, {"start": 2076.72, "end": 2077.76, "word": " هي", "probability": 0.3291015625}, {"start": 2077.76, "end": 2078.3, "word": " section", "probability": 0.458251953125}, {"start": 2078.3, "end": 2079.64, "word": " على", "probability": 0.78125}, {"start": 2079.64, "end": 2080.06, "word": " بعد", "probability": 0.76513671875}, {"start": 2080.06, "end": 2083.12, "word": " X", "probability": 0.6494140625}, {"start": 2083.12, "end": 2085.28, "word": " و", "probability": 0.481201171875}, {"start": 2085.28, "end": 2085.64, "word": " باخد", "probability": 0.9757486979166666}, {"start": 2085.64, "end": 2085.94, "word": " free", "probability": 0.60009765625}, {"start": 2085.94, "end": 2086.22, "word": " body", "probability": 0.8603515625}, {"start": 2086.22, "end": 2086.7, "word": " diagram", "probability": 0.88134765625}, {"start": 2086.7, "end": 2098.66, "word": " عند", "probability": 0.54052734375}, {"start": 2098.66, "end": 2098.9, "word": " هذه", "probability": 0.372314453125}, {"start": 2098.9, "end": 2099.04, "word": " ال", "probability": 0.78515625}, {"start": 2099.04, "end": 2099.34, "word": " force", "probability": 0.9716796875}, {"start": 2099.34, "end": 2099.76, "word": " F", "probability": 0.896484375}], "temperature": 1.0}, {"id": 74, "seek": 213244, "start": 2105.1, "end": 2132.44, "text": "و هذه المسافة X أكيد هيعكسها force F احيانا او خلينا نسميها V هتعمل counter clockwise moment هتعكسها clockwise moment وهي عند ال X", "tokens": [2407, 29538, 9673, 3794, 31845, 3660, 1783, 5551, 4117, 25708, 39896, 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"probability": 0.8759765625}, {"start": 2115.16, "end": 2115.84, "word": " احيانا", "probability": 0.69306640625}, {"start": 2115.84, "end": 2117.14, "word": " او", "probability": 0.886962890625}, {"start": 2117.14, "end": 2117.38, "word": " خلينا", "probability": 0.83447265625}, {"start": 2117.38, "end": 2117.86, "word": " نسميها", "probability": 0.9857177734375}, {"start": 2117.86, "end": 2118.5, "word": " V", "probability": 0.787109375}, {"start": 2118.5, "end": 2121.4, "word": " هتعمل", "probability": 0.928466796875}, {"start": 2121.4, "end": 2122.46, "word": " counter", "probability": 0.89013671875}, {"start": 2122.46, "end": 2122.94, "word": " clockwise", "probability": 0.587890625}, {"start": 2122.94, "end": 2123.42, "word": " moment", "probability": 0.6728515625}, {"start": 2123.42, "end": 2125.26, "word": " هتعكسها", "probability": 0.9222005208333334}, {"start": 2125.26, "end": 2126.82, "word": " clockwise", "probability": 0.88623046875}, {"start": 2126.82, "end": 2128.64, "word": " moment", "probability": 0.962890625}, {"start": 2128.64, "end": 2131.84, "word": " وهي", "probability": 0.63671875}, {"start": 2131.84, "end": 2131.98, "word": " عند", "probability": 0.9013671875}, {"start": 2131.98, "end": 2132.16, "word": " ال", "probability": 0.51806640625}, {"start": 2132.16, "end": 2132.44, "word": " X", "probability": 0.95849609375}], "temperature": 1.0}, {"id": 75, "seek": 215304, "start": 2134.08, "end": 2153.04, "text": "و هاي ال Y اللي أخد submission of forces بتجاه ال Y بالساوة Zero", "tokens": [2407, 8032, 47302, 2423, 398, 13672, 1829, 5551, 9778, 3215, 23689, 295, 5874, 4724, 2655, 7435, 40294, 2423, 398, 20666, 3794, 995, 2407, 3660, 17182], "avg_logprob": -0.4131610576923077, "compression_ratio": 1.1097560975609757, "no_speech_prob": 0.0, "words": [{"start": 2134.08, "end": 2134.32, "word": "و", "probability": 0.89208984375}, {"start": 2134.32, "end": 2134.48, "word": " هاي", "probability": 0.4986572265625}, {"start": 2134.48, "end": 2134.62, "word": " ال", "probability": 0.9609375}, {"start": 2134.62, "end": 2134.82, "word": " Y", "probability": 0.5166015625}, {"start": 2134.82, "end": 2144.4, "word": " اللي", "probability": 0.51483154296875}, {"start": 2144.4, "end": 2144.56, "word": " أخد", "probability": 0.90087890625}, {"start": 2144.56, "end": 2144.94, "word": " submission", "probability": 0.443603515625}, {"start": 2144.94, "end": 2145.22, "word": " of", "probability": 0.943359375}, {"start": 2145.22, "end": 2145.74, "word": " forces", "probability": 0.91845703125}, {"start": 2145.74, "end": 2151.3, "word": " بتجاه", "probability": 0.73431396484375}, {"start": 2151.3, "end": 2151.46, "word": " ال", "probability": 0.93798828125}, {"start": 2151.46, "end": 2151.72, "word": " Y", "probability": 0.91455078125}, {"start": 2151.72, "end": 2152.76, "word": " بالساوة", "probability": 0.598876953125}, {"start": 2152.76, "end": 2153.04, "word": " Zero", "probability": 0.3837890625}], "temperature": 1.0}, {"id": 76, "seek": 218079, "start": 2155.73, "end": 2180.79, "text": "هيكون عندي minus F زائد V يعني ال V لترانزل شير ايه شو ساوي؟ F لاخدت ال .. ال .. ال moment هين summation of moment حوالين نقطة X بالساوية سفر", "tokens": [3224, 1829, 30544, 18871, 16254, 3175, 479, 30767, 16373, 3215, 691, 37495, 22653, 2423, 691, 5296, 2655, 2288, 7649, 11622, 1211, 13412, 13546, 1975, 1829, 3224, 13412, 2407, 8608, 995, 45865, 22807, 479, 5296, 47283, 3215, 2655, 2423, 4386, 2423, 4386, 2423, 1623, 8032, 9957, 28811, 295, 1623, 11331, 2407, 6027, 9957, 8717, 47432, 3660, 1783, 20666, 3794, 995, 2407, 10632, 8608, 5172, 2288], "avg_logprob": -0.41586538461538464, "compression_ratio": 1.3694267515923566, "no_speech_prob": 0.0, "words": [{"start": 2155.73, "end": 2156.15, "word": "هيكون", "probability": 0.5869140625}, {"start": 2156.15, "end": 2156.49, "word": " عندي", "probability": 0.580322265625}, {"start": 2156.49, "end": 2157.13, "word": " minus", "probability": 0.255859375}, {"start": 2157.13, "end": 2157.65, "word": " F", "probability": 0.6494140625}, {"start": 2157.65, "end": 2159.01, "word": " زائد", "probability": 0.71337890625}, {"start": 2159.01, "end": 2159.37, "word": " V", "probability": 0.9462890625}, {"start": 2159.37, "end": 2160.33, "word": " يعني", "probability": 0.80810546875}, {"start": 2160.33, "end": 2160.49, "word": " ال", "probability": 0.576171875}, {"start": 2160.49, "end": 2160.73, "word": " V", "probability": 0.8974609375}, {"start": 2160.73, "end": 2162.75, "word": " لترانزل", "probability": 0.5979207356770834}, {"start": 2162.75, "end": 2163.09, "word": " شير", "probability": 0.56884765625}, {"start": 2163.09, "end": 2163.25, "word": " ايه", "probability": 0.5279134114583334}, {"start": 2163.25, "end": 2163.35, "word": " شو", "probability": 0.5732421875}, {"start": 2163.35, "end": 2164.71, "word": " ساوي؟", "probability": 0.68109130859375}, {"start": 2164.71, "end": 2165.35, "word": " F", "probability": 0.8046875}, {"start": 2165.35, "end": 2172.57, "word": " 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"word": " U", "probability": 0.578125}, {"start": 2242.17, "end": 2242.53, "word": " U", "probability": 0.337646484375}, {"start": 2242.53, "end": 2242.63, "word": " ت", "probability": 0.4345703125}, {"start": 2242.63, "end": 2243.31, "word": " transverse", "probability": 0.59185791015625}, {"start": 2243.31, "end": 2244.19, "word": " shear", "probability": 0.94970703125}], "temperature": 1.0}, {"id": 79, "seek": 227113, "start": 2244.93, "end": 2271.13, "text": "the due due to pending moment نرجع لمعادلات due to pending moment you", "tokens": [3322, 3462, 3462, 281, 32110, 1623, 8717, 47341, 3615, 32767, 3615, 18513, 1211, 9307, 3462, 281, 32110, 1623, 291], "avg_logprob": -0.19707031100988387, "compression_ratio": 1.265625, "no_speech_prob": 0.0, "words": [{"start": 2244.93, "end": 2245.37, "word": "the", "probability": 0.6806640625}, {"start": 2245.37, "end": 2245.85, "word": " due", "probability": 0.939453125}, {"start": 2245.85, "end": 2246.29, "word": " due", "probability": 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حيث ساوى طبعا التكامل حق من 0 لL هيكون تكامل من 0 لL", "tokens": [769, 68, 281, 22487, 1623, 9673, 3615, 18513, 37977, 29538, 4724, 1829, 3794, 995, 45865, 6055, 4117, 10943, 1211, 376, 17, 15844, 568, 36, 2777, 55, 11331, 1829, 12984, 8608, 995, 2407, 7578, 23032, 3555, 3615, 995, 16712, 4117, 10943, 1211, 11331, 4587, 9154, 1958, 5296, 43, 39896, 30544, 6055, 4117, 10943, 1211, 9154, 1958, 5296, 43], "avg_logprob": -0.31896553060104105, "compression_ratio": 1.288888888888889, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 2274.88, "end": 2275.34, "word": "due", "probability": 0.58001708984375}, {"start": 2275.34, "end": 2275.46, "word": " to", "probability": 0.9716796875}, {"start": 2275.46, "end": 2275.72, "word": " bending", "probability": 0.90966796875}, {"start": 2275.72, "end": 2276.18, "word": " moment", "probability": 0.95849609375}, {"start": 2276.18, "end": 2279.08, "word": " المعادلة", "probability": 0.846435546875}, {"start": 2279.08, "end": 2279.34, "word": " هذه", "probability": 0.45947265625}, {"start": 2279.34, "end": 2279.76, "word": " بيساوي", "probability": 0.679248046875}, {"start": 2279.76, "end": 2280.44, "word": " تكامل", "probability": 0.975830078125}, {"start": 2280.44, "end": 2284.86, "word": " M2", "probability": 0.45556640625}, {"start": 2284.86, "end": 2286.68, "word": " على", "probability": 0.1025390625}, {"start": 2286.68, "end": 2291.4, "word": " 2EIDX", "probability": 0.7596435546875}, {"start": 2291.4, "end": 2292.5, "word": " حيث", "probability": 0.7127685546875}, {"start": 2292.5, "end": 2293.38, "word": " ساوى", "probability": 0.7723388671875}, {"start": 2293.38, "end": 2293.98, "word": " طبعا", "probability": 0.85955810546875}, {"start": 2293.98, "end": 2294.5, "word": " التكامل", "probability": 0.9620361328125}, {"start": 2294.5, "end": 2294.66, "word": " حق", "probability": 0.324951171875}, {"start": 2294.66, "end": 2294.78, "word": " من", "probability": 0.8876953125}, {"start": 2294.78, "end": 2295.12, "word": " 0", "probability": 0.53515625}, {"start": 2295.12, "end": 2296.6, "word": " لL", "probability": 0.80078125}, {"start": 2296.6, "end": 2298.28, "word": " هيكون", "probability": 0.68017578125}, {"start": 2298.28, "end": 2298.84, "word": " تكامل", "probability": 0.9298095703125}, {"start": 2298.84, "end": 2298.98, "word": " من", "probability": 0.974609375}, {"start": 2298.98, "end": 2299.3, "word": " 0", "probability": 0.96337890625}, {"start": 2299.3, "end": 2299.82, "word": " لL", "probability": 0.91552734375}], "temperature": 1.0}, {"id": 81, "seek": 232896, "start": 2301.23, "end": 2328.97, "text": "الـ M هيبقى عبارة عن F X حاسس أن عندي F تربية X تربية على 2EI DX لاحظوا أن المقطع ثابت و ال force ثابتة هيطلع عبارة عن ال integration هيكون الساوية F square على 2EI تكامل X تربية", "tokens": [6027, 39184, 376, 39896, 3555, 4587, 7578, 6225, 3555, 9640, 3660, 18871, 479, 1783, 11331, 32277, 3794, 14739, 18871, 16254, 479, 6055, 25513, 10632, 1783, 6055, 25513, 10632, 15844, 568, 36, 40, 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2312.63, "end": 2313.11, "word": " المقطع", "probability": 0.9869791666666666}, {"start": 2313.11, "end": 2313.71, "word": " ثابت", "probability": 0.9959309895833334}, {"start": 2313.71, "end": 2314.49, "word": " و", "probability": 0.67724609375}, {"start": 2314.49, "end": 2314.65, "word": " ال", "probability": 0.79736328125}, {"start": 2314.65, "end": 2315.05, "word": " force", "probability": 0.87255859375}, {"start": 2315.05, "end": 2315.57, "word": " ثابتة", "probability": 0.77642822265625}, {"start": 2315.57, "end": 2315.89, "word": " هيطلع", "probability": 0.8193359375}, {"start": 2315.89, "end": 2316.11, "word": " عبارة", "probability": 0.77740478515625}, {"start": 2316.11, "end": 2316.13, "word": " عن", "probability": 0.95458984375}, {"start": 2316.13, "end": 2316.23, "word": " ال", "probability": 0.7060546875}, {"start": 2316.23, "end": 2316.53, "word": " integration", "probability": 0.93017578125}, {"start": 2316.53, "end": 2316.85, "word": " هيكون", "probability": 0.8359375}, {"start": 2316.85, "end": 2317.37, "word": " الساوية", "probability": 0.77392578125}, {"start": 2317.37, "end": 2318.55, "word": " F", "probability": 0.92724609375}, {"start": 2318.55, "end": 2319.15, "word": " square", "probability": 0.20947265625}, {"start": 2319.15, "end": 2320.55, "word": " على", "probability": 0.61767578125}, {"start": 2320.55, "end": 2322.21, "word": " 2EI", "probability": 0.9886067708333334}, {"start": 2322.21, "end": 2324.31, "word": " تكامل", "probability": 0.9658203125}, {"start": 2324.31, "end": 2328.45, "word": " X", "probability": 0.9658203125}, {"start": 2328.45, "end": 2328.97, "word": " تربية", "probability": 0.9695638020833334}], "temperature": 1.0}, {"id": 82, "seek": 235796, "start": 2330.18, "end": 2357.96, "text": "DX من سفر لأقل يعني إذا بعملها تكامل هتكون F2 على 2EI ل X تكييب على 3 من سفر لأقل يعني هتكون تساوي F تربيع التكييب على 6EI", "tokens": [35, 55, 9154, 8608, 5172, 2288, 5296, 10721, 4587, 1211, 37495, 22653, 11933, 15730, 4724, 25957, 1211, 11296, 6055, 4117, 10943, 1211, 8032, 2655, 30544, 479, 17, 15844, 568, 36, 40, 5296, 1783, 6055, 4117, 1829, 1829, 3555, 15844, 805, 9154, 8608, 5172, 2288, 5296, 10721, 4587, 1211, 37495, 22653, 8032, 2655, 30544, 6055, 3794, 995, 45865, 479, 6055, 2288, 21292, 3615, 16712, 4117, 1829, 1829, 3555, 15844, 1386, 36, 40], "avg_logprob": -0.2096354156318638, "compression_ratio": 1.6585365853658536, "no_speech_prob": 8.344650268554688e-07, "words": [{"start": 2330.18, "end": 2330.92, "word": "DX", "probability": 0.5048828125}, {"start": 2330.92, "end": 2331.84, "word": " من", "probability": 0.5498046875}, {"start": 2331.84, "end": 2332.26, "word": " سفر", "probability": 0.654296875}, {"start": 2332.26, "end": 2332.84, "word": " لأقل", "probability": 0.947021484375}, {"start": 2332.84, "end": 2333.8, "word": " يعني", "probability": 0.801513671875}, {"start": 2333.8, "end": 2333.94, "word": " إذا", "probability": 0.722900390625}, {"start": 2333.94, "end": 2334.48, "word": " بعملها", "probability": 0.7894287109375}, {"start": 2334.48, "end": 2334.9, "word": " تكامل", "probability": 0.9781494140625}, {"start": 2334.9, "end": 2335.3, "word": " هتكون", "probability": 0.8605143229166666}, {"start": 2335.3, "end": 2336.2, "word": " F2", "probability": 0.47515869140625}, {"start": 2336.2, "end": 2338.14, "word": " على", "probability": 0.25244140625}, {"start": 2338.14, "end": 2339.68, "word": " 2EI", "probability": 0.91943359375}, {"start": 2339.68, "end": 2341.56, "word": " ل", "probability": 0.76953125}, {"start": 2341.56, "end": 2341.82, "word": " X", "probability": 0.7236328125}, {"start": 2341.82, "end": 2342.42, "word": " تكييب", "probability": 0.9103515625}, {"start": 2342.42, "end": 2343.68, "word": " على", "probability": 0.76708984375}, {"start": 2343.68, "end": 2344.04, "word": " 3", "probability": 0.70361328125}, {"start": 2344.04, "end": 2344.94, "word": " من", "probability": 0.951171875}, {"start": 2344.94, "end": 2345.28, "word": " سفر", "probability": 0.9654947916666666}, {"start": 2345.28, "end": 2345.7, "word": " لأقل", "probability": 0.975830078125}, {"start": 2345.7, "end": 2346.06, "word": " يعني", "probability": 0.887451171875}, {"start": 2346.06, "end": 2346.6, "word": " هتكون", "probability": 0.9449869791666666}, {"start": 2346.6, "end": 2347.96, "word": " تساوي", "probability": 0.9322509765625}, {"start": 2347.96, "end": 2350.38, "word": " F", "probability": 0.90673828125}, {"start": 2350.38, "end": 2352.0, "word": " تربيع", "probability": 0.75482177734375}, {"start": 2352.0, "end": 2353.88, "word": " التكييب", "probability": 0.876953125}, {"start": 2353.88, "end": 2355.04, "word": " على", "probability": 0.8955078125}, {"start": 2355.04, "end": 2357.96, "word": " 6EI", "probability": 0.764892578125}], "temperature": 1.0}, {"id": 83, "seek": 238904, "start": 2362.04, "end": 2389.04, "text": "الان المقطع المدور ال I للمقطع المدور ال I للمقطع المدور عبارة عن باي على أربع و ستين D أس أربعة يعني هتصير ال U to bending moment 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"E", "probability": 0.6728515625}, {"start": 2579.86, "end": 2580.9, "word": " by", "probability": 0.1378173828125}, {"start": 2580.9, "end": 2583.42, "word": " D", "probability": 0.796875}, {"start": 2583.42, "end": 2584.74, "word": " أربعة", "probability": 0.6185506184895834}, {"start": 2584.74, "end": 2587.7, "word": " يعني", "probability": 0.8935546875}, {"start": 2587.7, "end": 2587.82, "word": " لو", "probability": 0.9404296875}, {"start": 2587.82, "end": 2587.98, "word": " بدنا", "probability": 0.799072265625}, {"start": 2587.98, "end": 2588.32, "word": " نبسط", "probability": 0.98583984375}, {"start": 2588.32, "end": 2588.7, "word": " أكتر", "probability": 0.958251953125}, {"start": 2588.7, "end": 2589.16, "word": " شوية", "probability": 0.9375}, {"start": 2589.16, "end": 2591.18, "word": " أخدنا", "probability": 0.9564208984375}, {"start": 2591.18, "end": 2591.6, "word": " F", "probability": 0.880859375}, {"start": 2591.6, "end": 2592.1, "word": " square", "probability": 0.23681640625}, {"start": 2592.1, "end": 2592.5, "word": " L", "probability": 0.91748046875}, {"start": 2592.5, "end": 2592.76, "word": " على", "probability": 0.82080078125}, {"start": 2592.76, "end": 2593.14, "word": " by", "probability": 0.40380859375}, {"start": 2593.14, "end": 2593.36, "word": " D", "probability": 0.64697265625}, {"start": 2593.36, "end": 2593.84, "word": " تربيع", "probability": 0.83282470703125}, {"start": 2593.84, "end": 2594.38, "word": " F", "probability": 0.8408203125}, {"start": 2594.38, "end": 2596.22, "word": " square", "probability": 0.6884765625}, {"start": 2596.22, "end": 2597.72, "word": " L", "probability": 0.96826171875}, {"start": 2597.72, "end": 2598.82, "word": " على", "probability": 0.927734375}, {"start": 2598.82, "end": 2599.2, "word": " by", "probability": 0.94384765625}, {"start": 2599.2, "end": 2600.66, "word": " D", "probability": 0.95947265625}, {"start": 2600.66, "end": 2601.38, "word": " تربيع", "probability": 0.951416015625}, {"start": 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\ No newline at end of file
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BTYGbzBT3fw.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BTYGbzBT3fw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..2b6a9be67ca2f1a04f6995c82a56727b212a4a9e
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BTYGbzBT3fw.srt
@@ -0,0 +1,1986 @@
+1
+00:00:04,890 --> 00:00:07,550
+بسم الله الرحمن الرحيم السلام عليكم ورحمة الله و
+
+2
+00:00:07,550 --> 00:00:11,870
+بركاته، عودة
+
+3
+00:00:11,870 --> 00:00:16,330
+انتقلت إلى مادة تصميم الآلات واحد، احنا بدأنا ب
+
+4
+00:00:16,330 --> 00:00:19,090
+chapter أربعة. chapter أربعة كان يحكي على ال
+
+5
+00:00:19,090 --> 00:00:21,570
+deflection and stiffness analysis of mechanical
+
+6
+00:00:21,570 --> 00:00:26,930
+members. هنرجع للمحاضرة السابقة، المحاضرة السابقة we
+
+7
+00:00:26,930 --> 00:00:30,550
+defined the strain energy due to forces acting on a
+
+8
+00:00:30,550 --> 00:00:35,030
+mechanical part as U = F square على اتنين K. ال
+
+9
+00:00:35,030 --> 00:00:40,470
+F اللي هي ال applied force, ال K هي ال stiffness of
+
+10
+00:00:40,470 --> 00:00:44,790
+the mechanical part. طبعا ال strain energy كانت
+
+11
+00:00:44,790 --> 00:00:49,630
+تعتمد على نوعية ال loading. في حالة axial loading,
+
+12
+00:00:49,630 --> 00:00:53,990
+سواء كان tension أو compression, ال formula لل
+
+13
+00:00:53,990 --> 00:00:59,870
+strain energy كانت تكامل لل F² dx على 2 AE. ال F هي
+
+14
+00:00:59,870 --> 00:01:03,530
+axial force, ال A هي ال cross section area لل member,
+
+15
+00:01:03,530 --> 00:01:06,690
+ال E هي ال modulus of elasticity, و Dx هي
+
+16
+00:01:06,690 --> 00:01:11,090
+displacement بالنسبة
+
+17
+00:01:11,090 --> 00:01:14,030
+لل strain energy. ل torsional loading condition,
+
+18
+00:01:14,030 --> 00:01:18,860
+كانت is given by this equation: U = تكامل T
+
+19
+00:01:18,860 --> 00:01:23,940
+squared على اتنين G J DX. ال T اللي هي ال applied
+
+20
+00:01:23,940 --> 00:01:27,960
+torque, ال G اللي هي ال modulus of rigidity أو ال
+
+21
+00:01:27,960 --> 00:01:34,400
+shear modulus, وال J هي ال polar moment of inertia. في
+
+22
+00:01:34,400 --> 00:01:39,750
+حالة direct shear loading, ال Strain Energy is
+
+23
+00:01:39,750 --> 00:01:45,650
+given by تكامل F² على اتنين A G DX. برضه ال
+
+24
+00:01:45,650 --> 00:01:48,990
+F هي ال shear force, ال A هي ال cross sectional
+
+25
+00:01:48,990 --> 00:01:51,750
+area, ال G هي ال modulus of rigidity أو ال shear
+
+26
+00:01:51,750 --> 00:01:59,390
+modulus. في حالة bending loading, ال energy is given
+
+27
+00:01:59,390 --> 00:02:05,610
+by the formula: U = تكامل M² على 2 EI DX. ال
+
+28
+00:02:05,610 --> 00:02:08,710
+M هي bending moment at the cross section, ال E هي ال
+
+29
+00:02:08,710 --> 00:02:14,370
+modulus of elasticity, ال I هي ال cross sectional
+
+30
+00:02:14,370 --> 00:02:20,160
+moment of inertia. في حالة Transverse Shear Loading
+
+31
+00:02:20,160 --> 00:02:23,020
+وإن فيه عندنا bending, بيكون عندنا Transverse Shear
+
+32
+00:02:23,020 --> 00:02:25,360
+Loading.  ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+33
+00:02:25,360 --> 00:02:25,720
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+34
+00:02:25,720 --> 00:02:26,940
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+35
+00:02:26,940 --> 00:02:27,160
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+36
+00:02:27,160 --> 00:02:27,860
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+37
+00:02:27,860 --> 00:02:29,560
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+38
+00:02:29,560 --> 00:02:35,520
+ال ال ال
+
+39
+00:02:35,520 --> 00:02:35,540
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+40
+00:02:35,540 --> 00:02:35,580
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+41
+00:02:35,580 --> 00:02:37,800
+ال ال ال ال ال ال ال ال ال
+
+42
+00:02:45,730 --> 00:02:49,890
+مستطيل، مدور، or any other cross section.  تابل أربع
+
+43
+00:02:49,890 --> 00:02:54,770
+واحد بيعطينا قيم ال C for different cross sections.
+
+44
+00:02:54,770 --> 00:03:00,130
+في حالة مقطع مستطيل، ال C كانت 1.2. في حالة مقطع
+
+45
+00:03:00,130 --> 00:03:09,970
+مدور، ال C = 1.11.  حلّ example أربعة وتمانية أو جدّ
+
+46
+00:03:09,970 --> 00:03:14,790
+deflection عند ال force F باستخدام ال strain energy
+
+47
+00:03:14,790 --> 00:03:20,630
+method. هذا آخر شيء وصلنا له اليوم. هنكمل اللي
+
+48
+00:03:20,630 --> 00:03:26,150
+هو Castigliano theorem. Castigliano theorem بتحكي
+
+49
+00:03:26,150 --> 00:03:30,270
+التالي: forces act on anelastic systems subject أو
+
+50
+00:03:30,270 --> 00:03:34,830
+أول شيء، ال Castigliano theorem, ال application بتاعتها
+
+51
+00:03:34,830 --> 00:03:40,430
+applies only for forces acting on mechanical
+
+52
+00:03:40,430 --> 00:03:44,510
+elements subjected to small displacements. يعني إذا
+
+53
+00:03:44,510 --> 00:03:48,030
+كانت ال displacement كبيرة، Castigliano theorem is
+
+54
+00:03:48,030 --> 00:03:51,990
+not valid. يعني we apply Castigliano theorem in case
+
+55
+00:03:51,990 --> 00:03:56,570
+of forces acting on mechanical elements with small
+
+56
+00:03:56,570 --> 00:04:01,770
+displacement. الآن،
+
+57
+00:04:01,770 --> 00:04:05,350
+according to Castigliano, displacement
+
+58
+00:04:07,200 --> 00:04:11,620
+corresponding to any force along its direction. لو
+
+59
+00:04:11,620 --> 00:04:19,180
+عندي mechanical element، طبعا
+
+60
+00:04:19,180 --> 00:04:28,200
+نتيجة ال loading، حأحسب عندي إيش؟ deflection. هذا
+
+61
+00:04:28,200 --> 00:04:33,360
+ال force F. هذا كان cantilever beam. according to
+
+62
+00:04:33,360 --> 00:04:37,930
+Castigliano, ال displacement Δ is given by ال
+
+63
+00:04:37,930 --> 00:04:41,930
+partial differential لل total strain energy
+
+64
+00:04:41,930 --> 00:04:49,090
+بالنسبة لل force F. يعني displacement Δ بيساوي
+
+65
+00:04:49,090 --> 00:04:54,670
+ال partial derivative لل total strain energy with
+
+66
+00:04:54,670 --> 00:04:59,730
+respect to the force F. هذا في حالة force. في حالة
+
+67
+00:04:59,730 --> 00:05:05,170
+rotation, rotational displacement θ = ∂U / ∂M. خليني
+
+68
+00:05:05,170 --> 00:05:23,110
+أحلّ مثال، نشوف كيف ممكن نستخدم ال Castigliano
+
+69
+00:05:23,110 --> 00:05:27,250
+theorem. نفس ال example السابق.
+
+70
+00:05:27,250 --> 00:05:31,590
+نفس المثال السابق.
+
+71
+00:05:34,380 --> 00:05:38,360
+The cantilever shown. في عندي cantilever مثبت من
+
+72
+00:05:38,360 --> 00:05:44,740
+الطرف هذا. is a carbon steel bar. عبارة عن بار مصنوع
+
+73
+00:05:44,740 --> 00:05:53,120
+من الحديد الكربوني، ten inches long. طوله
+
+74
+00:05:53,120 --> 00:05:57,820
+عشرة إنش.
+
+75
+00:05:57,820 --> 00:05:59,680
+ten inches long.
+
+76
+00:06:02,460 --> 00:06:08,620
+والقطر بتاع المقطع مدور بيساوي
+
+77
+00:06:08,620 --> 00:06:27,100
+واحد إنش، ومدور.  بفرصة F بيساوي
+
+78
+00:06:27,100 --> 00:06:27,940
+مئتي باوند.
+
+79
+00:06:34,160 --> 00:06:39,480
+Find the maximum deflection using
+
+80
+00:06:39,480 --> 00:06:43,440
+Castigliano's theorem, including that due to shear.
+
+81
+00:06:43,440 --> 00:06:57,700
+أوجد ال maximum deflection. بده y<sub>max</sub>. ال
+
+82
+00:06:57,700 --> 00:07:02,100
+y هتكون = ∂U /
+
+83
+00:07:04,120 --> 00:07:12,920
+∂F.
+
+84
+00:07:12,920 --> 00:07:18,800
+ال
+
+85
+00:07:18,800 --> 00:07:26,540
+U هتكون مكونة من two components. U هتكون strain
+
+86
+00:07:26,540 --> 00:07:34,860
+energy due to bending + U due to transverse shear.
+
+87
+00:07:34,860 --> 00:07:42,220
+U<sub>b</sub> + U<sub>s</sub>. لو
+
+88
+00:07:42,220 --> 00:07:50,740
+أخذت section هنا على بعد X، طلّعت
+
+89
+00:07:50,740 --> 00:07:59,040
+free body diagram. هاي ال force F، هذه المسافة
+
+90
+00:07:59,040 --> 00:08:00,980
+X.
+
+91
+00:08:02,860 --> 00:08:08,660
+في عندي force F، في
+
+92
+00:08:08,660 --> 00:08:16,320
+عندي moment M، أو
+
+93
+00:08:16,320 --> 00:08:17,860
+V.
+
+94
+00:08:22,820 --> 00:08:28,020
+طبعا هيكون عند ال...ال...ال...ال...ال V قيمتها
+
+95
+00:08:28,020 --> 00:08:44,800
+هتكون تساوي F، و ال M هتكون = F X. الآن،
+
+96
+00:08:44,800 --> 00:08:49,040
+ال U due to bending، نرجع للمعادلات... للمعادلات
+
+97
+00:08:49,040 --> 00:08:51,600
+السابقة. ال U due to bending، U<sub>b</sub>
+
+98
+00:08:55,140 --> 00:09:08,520
+= تكامل M² على 2EI DX =
+
+99
+00:09:08,520 --> 00:09:20,000
+تكامل من 0 ل L. ال M عندي اللي هي F
+
+100
+00:09:20,000 --> 00:09:31,890
+X الكل تربيع على 2EI DX من صفر ل L =
+
+101
+00:09:31,890 --> 00:09:40,910
+طبعا عندي ال F is constant، فحأحسب عندي F² على
+
+102
+00:09:40,910 --> 00:09:54,050
+2EI تكامل X² DX من صفر ل L =
+
+103
+00:09:54,050 --> 00:10:05,770
+X³/3، يعني هذه هتصير F² L³/6EI. ال
+
+104
+00:10:05,770 --> 00:10:17,690
+U<sub>b</sub>.  U due to shear.
+
+105
+00:10:17,690 --> 00:10:19,530
+U<sub>s</sub> due to shear.
+
+106
+00:10:25,570 --> 00:10:32,790
+Transverse shear = تكامل C
+
+107
+00:10:32,790 --> 00:10:47,690
+V² على 2 AG من 0 ل L = تكامل ال C
+
+108
+00:10:47,690 --> 00:10:53,870
+constant. ال C في الحالة هذه لمقطع مدور، من الجدول
+
+109
+00:10:55,880 --> 00:11:05,000
+للمقطع المدور C = 1.11. هتكون
+
+110
+00:11:05,000 --> 00:11:18,240
+C F² على 2 AG DX. طبعا
+
+111
+00:11:18,240 --> 00:11:23,940
+أنا عندي ال C، و ال F، و ال A، و ال G ثوابت، من 0 ل L،
+
+112
+00:11:25,710 --> 00:11:34,390
+معناته التكامل هيكون C F²
+
+113
+00:11:34,390 --> 00:11:38,590
+L / 2AG.
+
+114
+00:11:38,590 --> 00:11:46,910
+يعني
+
+115
+00:11:46,910 --> 00:11:54,710
+أنا أقول إن ال Deflection Y = ∂U / ∂F
+
+116
+00:11:54,710 --> 00:12:06,190
+= ∂U<sub>b</sub> / ∂F + ∂U<sub>s</sub> / ∂F. احنا هنا ممكن نعرف إن
+
+117
+00:12:06,190 --> 00:12:18,490
+هو ∂U<sub>b</sub> / ∂F
+
+118
+00:12:18,490 --> 00:12:19,770
+∂U<sub>b</sub> / ∂F
+
+119
+00:12:23,530 --> 00:12:32,970
+= 2 F L³/6 AI =
+
+120
+00:12:32,970 --> 00:12:45,310
+F L³/3 AI. و ∂U<sub>s</sub> /
+
+121
+00:12:45,310 --> 00:12:51,370
+∂F = 2C
+
+122
+00:12:53,310 --> 00:13:07,250
+FL / 2AG. يعني أنا هستخدم C FL / AG.
+
+123
+00:13:07,250 --> 00:13:13,530
+يعني
+
+124
+00:13:13,530 --> 00:13:21,250
+أنا ممكن أحكي Y هيكون مؤلف من مكونين: Y due to bending
+
+125
+00:13:22,520 --> 00:13:32,480
++ Y due to shear. ال Y due to bending
+
+126
+00:13:32,480 --> 00:13:45,580
+= ∂U<sub>b</sub> / ∂F = F L³/3 EI.
+
+127
+00:13:45,580 --> 00:13:49,120
+3 EI.
+
+128
+00:13:59,950 --> 00:14:05,430
+خليني أحسب بعض الشغلات هنا. أنا
+
+129
+00:14:05,430 --> 00:14:10,470
+بدي أحسب مساحة المقطع المدور. ال A = π / 4
+
+130
+00:14:10,470 --> 00:14:17,890
+d². يعني π / 4 × 1² =
+
+131
+00:14:17,890 --> 00:14:26,010
+π / 4. هذه ال area. و ال I = π / 64
+
+132
+00:14:26,010 --> 00:14:31,500
+d⁴ = π / 64
+
+133
+00:14:31,500 --> 00:14:44,840
+× 1⁴ = π / 64. ال
+
+134
+00:14:44,840 --> 00:14:51,160
+E من الجداول، ال E لل carbon steel = 30
+
+135
+00:14:51,160 --> 00:15:01,620
+ميجا باوند per square inch. و ال G = 11.5
+
+136
+00:15:01,620 --> 00:15:10,620
+جيجا باوند per square inch أو
+
+137
+00:15:10,620 --> 00:15:20,940
+ميجا باوند per square
+
+138
+00:15:20,940 --> 00:15:25,120
+inch. يعني
+
+139
+00:15:25,120 --> 00:15:27,240
+ال Y due to bending هتكون
+
+140
+00:15:29,740 --> 00:15:39,460
+ال F عندي كم؟ معطيني مئة. و ال L عشرة.  10³
+
+141
+00:15:39,460 --> 00:15:57,040
+على 3 × ال E × 30 × 10⁶ × ال I اللي هي π / 64. و بنحسب ال Y due to
+
+142
+00:15:57,040 --> 00:16:05,330
+bending. ال
+
+143
+00:16:05,330 --> 00:16:09,970
+Y due to shear اللي
+
+144
+00:16:09,970 --> 00:16:16,590
+هي هتكون ∂U<sub>s</sub> / ∂F. نعملها بالساعة، و ال C
+
+145
+00:16:26,850 --> 00:16:36,870
+= FL / AG. ال C = 1.11، ال F = 100،
+
+146
+00:16:36,870 --> 00:16:46,990
+و ال L = 10، و ال A = π / 4. π / 4، و ال G
+
+147
+00:16:46,990 --> 00:16:53,590
+خلينا نتأكد. ال G للحديد = 11.5 ميجا
+
+149
+00:16:59,160 --> 00:17:00,360
+هنفتح الجداول
+
+150
+00:17:33,200 --> 00:17:40,760
+اللي هو A5، عندنا هيكون ال
+
+151
+00:17:40,760 --> 00:17:48,500
+carbon steel، ال G = 11.5 ميجا باوند per square
+
+152
+00:17:48,500 --> 00:17:55,440
+inch، و ال E = 30. صحيح، طيب.
+
+153
+00:17:55,440 --> 00:17:57,640
+ال G = 11.5
+
+154
+00:18:01,300 --> 00:18:11,160
+في 10⁶. و بنحسبها. لو
+
+155
+00:18:11,160 --> 00:18:21,480
+حسبنا ال Y due to bending، هيكون عندي
+
+156
+00:18:21,480 --> 00:18:25,160
+0.226
+
+157
+00:18:25,160 --> 00:18:36,440
+in. ال Y due to shear
+
+158
+00:18:36,440 --> 00:18:51,200
+لحالها بيطلع
+
+159
+00:18:51,200 --> 00:18:57,780
+عندي 0.001 in. 0.001
+
+160
+00:18:57,780 --> 00:19:02,850
+in. ال Y due to shear لحالها
+
+161
+00:19:34,040 --> 00:19:42,600
+بيطلع 0.001 in. 0.001
+
+162
+00:19:42,600 --> 00:19:49,580
+in. معناه ال total deflection Y هيكون مجموعهم
+
+163
+00:19:49,580 --> 00:19:59,700
+0.226 + 0.001 =
+
+164
+00:19:59,700 --> 00:20:09,400
+هيكون 0.227 in.
+
+165
+00:20:42,930 --> 00:20:48,330
+طيب، هذا المطلوب الثاني. What error is introduced if
+
+166
+00:20:48,330 --> 00:20:51,030
+shear is neglected؟ إذا أهملت الشير، يعني اعتبرت
+
+167
+00:20:51,030 --> 00:21:02,290
+ال shear مهمل. يعني لو حكيت if shear is
+
+168
+00:21:02,290 --> 00:21:06,650
+neglected، هيكون
+
+169
+00:21:06,650 --> 00:21:14,510
+ال Y هي ال Y بتاعة ال bending بس، تقريبا = 0.226 in. لو بنحسب
+
+170
+00:21:14,510 --> 00:21:24,110
+percentage error due to ignorance of shear هيكون
+
+171
+00:21:32,110 --> 00:21:39,130
+= 0.227 - 0.226 / 0.227 × 100 =
+
+172
+00:21:39,130 --> 00:21:54,080
+يعني
+
+173
+00:21:54,080 --> 00:21:54,580
+هيكون
+
+175
+00:22:30,440 --> 00:22:37,340
+بيطلع نسبة الخطأ 0.44%. 0.44%
+
+176
+00:22:37,340 --> 00:22:43,160
+معناته ال...إذا في معظم الأحيان، إذا كان موجود
+
+177
+00:22:43,160 --> 00:22:47,540
+عندي bending و transverse shear، ال deflection due
+
+178
+00:22:47,540 --> 00:22:53,700
+to transverse shear صغير جدا بالمقارنة مع ال...ال
+
+179
+00:22:53,700 --> 00:22:58,040
+deflection due to bending. و الدليل لما حسبنا هنا،
+
+180
+00:22:58,040 --> 00:23:03,810
+طلعت نسبة الخطأ في... في الإجابة حوالي 0.4%. إذا
+
+181
+00:23:03,810 --> 00:23:09,110
+أهملت ال...إيش؟ ال shear effect. و بتاع بشكل عام،
+
+182
+00:23:09,110 --> 00:23:12,990
+احنا ممكن نهمل ال shear effect لأنه is not
+
+183
+00:23:12,990 --> 00:23:20,170
+significant. ليس ذو قيمة. نكمل.
+
+184
+00:23:20,170 --> 00:23:20,810
+طيب.
+
+185
+00:23:45,440 --> 00:23:50,380
+احنا حكينا من الشروط بتاعة Castigliano، عشان أحسب ال
+
+186
+00:23:50,380 --> 00:23:55,360
+deflection at any location لازم تكون القوة مؤثرة
+
+187
+00:23:55,360 --> 00:23:57,840
+عند ال location تحت الدراسة. يعني لو أنا عندي
+
+188
+00:23:57,840 --> 00:24:05,890
+cantilever، و في عندي force F، بدي أحسب عند هذه النقطة، في
+
+189
+00:24:05,890 --> 00:24:11,430
+force F بتأثر. طيب، إذا بدي أحسب عند هذه النقطة، ما فيش
+
+190
+00:24:11,430 --> 00:24:20,730
+force F
+
+223
+00:27:58,840 --> 00:28:03,060
+delta I ال location بيصيح واحدة على AE في FDF by
+
+224
+00:28:03,060 --> 00:28:09,840
+DFI DX و theta I due to bending واحدة على GJ في
+
+225
+00:28:09,840 --> 00:28:14,360
+TDT
+
+226
+00:28:14,360 --> 00:28:21,480
+by DMI و delta I due to bending هتكون واحدة دي I
+
+227
+00:28:21,480 --> 00:28:23,700
+في MDM by DFI في DX
+
+228
+00:28:28,190 --> 00:28:46,910
+تشوف مثال تاني تشوف
+
+229
+00:28:46,910 --> 00:28:51,650
+مثال تاني using
+
+230
+00:28:51,650 --> 00:28:56,010
+Castellanos method باستخدام طريقة Castellanos
+
+231
+00:28:57,700 --> 00:29:03,340
+determine deflections of points A and B نقطة A
+
+232
+00:29:03,340 --> 00:29:11,360
+ونقطة B نقطة A ونقطة
+
+233
+00:29:11,360 --> 00:29:21,480
+B due to the force F نقطة F نقطة F نقطة F نقطة F
+
+234
+00:29:21,480 --> 00:29:24,940
+نقطة F نقطة F نقطة F نقطة
+
+235
+00:29:27,670 --> 00:29:33,110
+المقاطع الثانية للمقاطع A B وهذا مقاطع A B وهذا
+
+236
+00:29:33,110 --> 00:29:39,730
+مقاطع B C R
+
+237
+00:29:39,730 --> 00:29:46,710
+I واحد واتنين
+
+238
+00:29:46,710 --> 00:29:50,630
+I واحد respectively
+
+239
+00:29:52,220 --> 00:29:56,240
+بيده deflection عند a و deflection عند b لان خيانه
+
+240
+00:29:56,240 --> 00:30:03,040
+find deflection at a find deflection
+
+241
+00:30:03,040 --> 00:30:07,180
+at
+
+242
+00:30:07,180 --> 00:30:12,160
+a اول
+
+243
+00:30:12,160 --> 00:30:18,460
+شي اللحظة أن المقطع مش منتظم المقطع عند في الجزء
+
+244
+00:30:18,460 --> 00:30:23,320
+الأول يعني من a ل b مختلف عن المقطع في الجزء من B ل C
+
+245
+00:30:23,320 --> 00:30:30,160
+I واحد هنا عند ال I للمقطع BC ضعف ال I للمقطع AB
+
+246
+00:30:30,160 --> 00:30:34,340
+احنا
+
+247
+00:30:34,340 --> 00:30:39,980
+في المثال السابق أثبتنا أن قيمة ال deflection due
+
+248
+00:30:39,980 --> 00:30:46,160
+to transverse shear is very small compared to that
+
+249
+00:30:46,160 --> 00:30:51,430
+due to bending. Our assumption: we neglect deflection
+
+250
+00:30:51,430 --> 00:30:59,010
+due to transverse shear. معناته neglect اهمل
+
+251
+00:30:59,010 --> 00:31:06,470
+deflection due
+
+252
+00:31:06,470 --> 00:31:13,670
+to transverse shear
+
+253
+00:31:13,670 --> 00:31:16,310
+هاي أول assumption
+
+254
+00:31:19,160 --> 00:31:26,460
+عندي هاي ال X Axis و
+
+255
+00:31:26,460 --> 00:31:32,280
+هاي ال Y Axis الان
+
+256
+00:31:32,280 --> 00:31:39,960
+at any given section على بعد X هاخد free body
+
+257
+00:31:39,960 --> 00:31:46,300
+diagram هاي
+
+258
+00:31:46,300 --> 00:31:47,200
+ال force F
+
+259
+00:31:50,470 --> 00:32:01,710
+عند المسافة X هنا هيكون في عنده F هيكون في عنده
+
+260
+00:32:01,710 --> 00:32:06,270
+moment M لاحظوا
+
+261
+00:32:06,270 --> 00:32:09,190
+لما أنا مش هاهتم في إشارتها negative ولا positive
+
+262
+00:32:09,190 --> 00:32:13,090
+لأنه في الآخر هضرب two terms negative مع negative
+
+263
+00:32:13,090 --> 00:32:18,610
+إيش هيعطيني positive وبالتالي مش هيأثر كتير أو مش
+
+264
+00:32:18,610 --> 00:32:29,510
+هيأثر. الإشارة على الحل عند ال moment هتكون بستوي
+
+265
+00:32:29,510 --> 00:32:34,790
+F X I
+
+266
+00:32:34,790 --> 00:32:42,370
+have only bending. معناته ال delta عند A هتكون
+
+267
+00:32:42,370 --> 00:32:42,870
+بستوي
+
+268
+00:32:49,010 --> 00:32:52,370
+طالما أنا عندي ال two sections مختلفين عن بعض
+
+269
+00:32:52,370 --> 00:32:57,710
+بيبقى جزء ال مثل الجزءين جزء a,b زاد الجزء b,c
+
+270
+00:32:57,710 --> 00:33:11,050
+وأنا عندي I have only bending هتكون delta a هتكون
+
+271
+00:33:11,050 --> 00:33:16,410
+تساوي تكامل
+
+272
+00:33:18,840 --> 00:33:24,220
+واحد على EI ل
+
+273
+00:33:24,220 --> 00:33:37,080
+M DM by DF DX طبعا
+
+274
+00:33:37,080 --> 00:33:42,900
+عندي two terms أو عندي two sections واحد على EI
+
+275
+00:33:42,900 --> 00:33:46,480
+واحد من صفر ل L على اتنين
+
+276
+00:33:49,740 --> 00:33:59,780
+زائد واحد على E احنا حكينا I2 اتنين
+
+277
+00:33:59,780 --> 00:34:03,740
+I واحد زائد
+
+278
+00:34:03,740 --> 00:34:09,540
+واحد على E I اتنين اللي هي عبارة عن اتنين I واحد
+
+279
+00:34:09,540 --> 00:34:12,640
+في
+
+280
+00:34:12,640 --> 00:34:13,640
+M
+
+281
+00:34:19,240 --> 00:34:30,700
+DM by DF DX ال X تغير من L على 2 ل L أنا رودي عند
+
+282
+00:34:30,700 --> 00:34:44,020
+ال F بالساوية FX ال M معناته
+
+283
+00:34:44,020 --> 00:34:54,330
+DM و بعدين F هتكون تساوياش X يعني
+
+284
+00:34:54,330 --> 00:35:05,190
+Delta A هتكون تساوي تكامل من 0 ل L على 2 1 على E I
+
+285
+00:35:05,190 --> 00:35:22,610
+1 ال M عندي عبارة عن F X و DMYDF F X DX زائد التكامل
+
+286
+00:35:22,610 --> 00:35:40,770
+من L على 2 ل L 1 على 2 E I 1 M F X F X DX هيساوي
+
+287
+00:35:40,770 --> 00:35:51,950
+هيطلع عندي طبعا بره اللي هو F على E I واحد تكامل
+
+288
+00:35:51,950 --> 00:36:01,770
+من صفر ل L على اتنين ل X تربيع DX زائد واحد على
+
+289
+00:36:01,770 --> 00:36:03,650
+اتنين E I واحد
+
+290
+00:36:06,900 --> 00:36:16,780
+في F طبعا تكامل من L على 2 ل L ل X تربيع DX حيث
+
+291
+00:36:16,780 --> 00:36:22,180
+ساوي طبعا أول تكامل هيكون قيمته هصيرها DX تكعيب
+
+292
+00:36:22,180 --> 00:36:32,560
+على 3 من 0 ل L على 2 يعني هيكون عندي F L
+
+293
+00:36:32,560 --> 00:36:41,110
+تكعيب على أربعة و عشرين E
+
+294
+00:36:41,110 --> 00:36:45,990
+I واحد زائد
+
+295
+00:36:45,990 --> 00:36:49,130
+F
+
+296
+00:36:49,130 --> 00:36:59,390
+على اتنين E I واحد طبعا هنا ستة هيكون في
+
+297
+00:36:59,390 --> 00:37:03,210
+هيكون تكعيب
+
+298
+00:37:06,810 --> 00:37:16,390
+ناقص تكعيب على تمانية يعني
+
+299
+00:37:16,390 --> 00:37:25,670
+Delta A هتكون تساوي F تكعيب على أربعة وعشرين E I
+
+300
+00:37:25,670 --> 00:37:32,150
+واحد زائد طبعا هنا تكعيب ناقص تكعيب على
+
+301
+00:37:32,150 --> 00:37:32,650
+تمانية
+
+302
+00:37:39,520 --> 00:37:45,440
+هتكون سبعة على تمانية × تمانية = ستة و أربعين
+
+303
+00:37:45,440 --> 00:37:57,600
+على ستة و أربعين في
+
+304
+00:37:57,600 --> 00:37:58,020
+سبعة
+
+305
+00:38:06,440 --> 00:38:14,760
+يعني deflection هيكون يساوي هجمعهم عشرة أو
+
+306
+00:38:14,760 --> 00:38:19,820
+تسعة هتكون
+
+307
+00:38:19,820 --> 00:38:28,620
+سبعة زائد اتنين = سبعة زائد اتنين = تسعة تسعة if ال
+
+308
+00:38:28,620 --> 00:38:38,700
+تكعيب على الستة و الأربعين EI واحد يعني أنا هيكون
+
+309
+00:38:38,700 --> 00:38:49,540
+عند A تلاتة F تكعيب على ستة عشر EI واحد هذه ال
+
+310
+00:38:49,540 --> 00:38:54,300
+deflection عند A طبعا
+
+311
+00:38:54,300 --> 00:39:01,680
+بتوقع منكم تتراجعوا الحسابات هذه ورايا. تأكدوا من
+
+312
+00:39:01,680 --> 00:39:10,080
+دقتها. إذا في أي خطأ صححه. طيب
+
+313
+00:39:10,080 --> 00:39:13,220
+هذا
+
+314
+00:39:13,220 --> 00:39:15,560
+المطلوب الأول. المطلوب الثاني: بدي أحسب ال deflection
+
+315
+00:39:15,560 --> 00:39:16,380
+عند B
+
+316
+00:39:30,580 --> 00:39:34,860
+الآن عند B ما فيش
+
+317
+00:39:34,860 --> 00:39:40,440
+force. عشان أحسب deflection عند B لازم أحط force
+
+318
+00:39:40,440 --> 00:39:48,460
+تخيلية. بدي أحط force تخيلية وأسميها
+
+319
+00:39:48,460 --> 00:39:53,420
+H EQ معناته
+
+320
+00:39:53,420 --> 00:39:58,640
+ال deflection عند B دلتا B هيكون يساوي
+
+321
+00:40:01,310 --> 00:40:05,750
+اللي هو دلتا
+
+322
+00:40:05,750 --> 00:40:16,630
+عند B يساوي دي يو باي دي كيو We
+
+323
+00:40:16,630 --> 00:40:21,250
+have only bending و
+
+324
+00:40:21,250 --> 00:40:26,190
+أهملنا ال transverse shear. رقم واحد رقم اتنين
+
+325
+00:40:28,800 --> 00:40:35,500
+لازم أنقسم ال beam ل two parts لسببين. أول سبب
+
+326
+00:40:35,500 --> 00:40:39,380
+الأول: أنه أنا عندي ال section في ال a,b مساحة
+
+327
+00:40:39,380 --> 00:40:42,760
+المقطع مختلفة عن مساحة المقطع في ال section b,c
+
+328
+00:40:42,760 --> 00:40:49,940
+سبب ثاني: صار في عندي كمان قوة مركزة تخيلية ليها Q
+
+329
+00:40:49,940 --> 00:40:51,120
+عند نقطة B
+
+330
+00:41:01,080 --> 00:41:06,700
+معناته هاخد ال free body diagram في الفترة من a ل
+
+331
+00:41:06,700 --> 00:41:16,860
+b يعني هاخد أول شي section هي section على بعد X لو
+
+332
+00:41:16,860 --> 00:41:25,220
+أخد section على بعد X هي عندي force F وهذه المسافة
+
+333
+00:41:25,220 --> 00:41:29,540
+إيش X هيكون
+
+334
+00:41:29,540 --> 00:41:53,190
+عندي هنا F وعندي M.  خصمها MAB. MAB بتساوي FX
+
+335
+00:41:53,190 --> 00:41:58,090
+هاي الحالة. لقول الحالة الثانية هاخد section هنا
+
+336
+00:42:01,650 --> 00:42:09,630
+هذه هي ال X عندي اللي
+
+337
+00:42:09,630 --> 00:42:17,910
+هي ال section الثاني هذه
+
+338
+00:42:17,910 --> 00:42:28,130
+A هذه B وعندي هنا F وعندي هنا Q وعندي هذه المسافة
+
+339
+00:42:28,130 --> 00:42:28,970
+إيش كلها X
+
+340
+00:42:33,140 --> 00:42:40,420
+هذه المسافة L على 2 هين
+
+341
+00:42:40,420 --> 00:42:46,820
+هيكون طبعا force V بتعكسهم وفي
+
+342
+00:42:46,820 --> 00:43:01,400
+bending moment M V C و M V C هتساوي F
+
+343
+00:43:01,400 --> 00:43:01,880
+X
+
+344
+00:43:09,900 --> 00:43:17,460
+زائد Q في
+
+345
+00:43:17,460 --> 00:43:26,900
+X ناقص L على اتنين هنا
+
+346
+00:43:26,900 --> 00:43:32,060
+لازم نحسب DMAB
+
+347
+00:43:32,060 --> 00:43:34,420
+BY DQ
+
+348
+00:43:37,610 --> 00:43:45,950
+صفر لأن هذه F وهذه X هنا سأحسب DMBC
+
+349
+00:43:45,950 --> 00:43:56,570
+BY DQ هتكون صفر زائد X ناقص L على اتنين
+
+350
+00:44:10,710 --> 00:44:19,470
+I have only bending. معناته delta B هتكون تساوي أنا
+
+351
+00:44:19,470 --> 00:44:30,110
+هقسم لجزئين من A ل B و من B ل C تكامل من 0 ل L على
+
+352
+00:44:30,110 --> 00:44:37,630
+2 ل 1 على E ال section AB ال I بتاعه I واحد
+
+353
+00:44:41,260 --> 00:44:46,320
+في MAB DMAB
+
+354
+00:44:46,320 --> 00:45:01,000
+by DQ DX زائد التكامل من L على 2 ل L في 1 على E ال
+
+355
+00:45:01,000 --> 00:45:05,000
+I بتاع ال section 2 عبارة عن 2EI 1
+
+356
+00:45:10,240 --> 00:45:23,420
+MBC DMBC BY DQ DX
+
+357
+00:45:23,420 --> 00:45:27,980
+احنا already we find DMAB BY DQ يساوي
+
+358
+00:45:27,980 --> 00:45:35,140
+صفر. معناته الترم الأول هذا الترم كله
+
+359
+00:45:35,140 --> 00:45:45,930
+هذا يساوي صفر. معناته أنت هتحسب delta B يساوي
+
+360
+00:45:45,930 --> 00:45:57,310
+واحد على تكامل من L على 2 ل L هطلع واحد على اتنين EI
+
+361
+00:45:57,310 --> 00:46:03,110
+واحد مضروب في MBC. MBC عبارة عن FX
+
+362
+00:46:10,030 --> 00:46:23,210
+زائد Q في X ناقص L على 2. هذا ال MBC في DMBC by DQ
+
+363
+00:46:23,210 --> 00:46:31,810
+اللي هي X ناقص L على 2 في DX
+
+364
+00:46:36,220 --> 00:46:42,000
+الآن set up  Q باسمها و صفر. خلي Q هذه و حط Q
+
+365
+00:46:42,000 --> 00:46:46,620
+باسمها و صفر. احنا
+
+366
+00:46:46,620 --> 00:46:57,280
+اتعاملنا عليها بس هتصفي هذه تكامل واحد
+
+367
+00:46:57,280 --> 00:47:10,490
+على اتنين E I واحد تكامل من L على اتنين ل L ل
+
+368
+00:47:10,490 --> 00:47:15,750
+FX في
+
+369
+00:47:15,750 --> 00:47:29,310
+X ناقص L على 2 DX يعني هتصير هطلع ال F بره. F
+
+370
+00:47:29,310 --> 00:47:42,710
+على 2EI 1 تكامل من L على 2 ل L هدخل X جوه X تربيع
+
+371
+00:47:42,710 --> 00:48:01,070
+ناقص XL على 2 DX يعني هتكون F على 2 E I 1 في تكامل
+
+372
+00:48:01,070 --> 00:48:11,230
+X تربيع عبارة عن إيش؟ في X تكعيب على تلاتة ناقص X
+
+373
+00:48:11,230 --> 00:48:20,130
+تربيع L على أربعة. والتكامل حدوده من L على اتنين ل
+
+374
+00:48:20,130 --> 00:48:27,650
+L يعني هيكون يساوي F
+
+375
+00:48:29,210 --> 00:48:37,970
+على اتنين E I واحد في تلت
+
+376
+00:48:37,970 --> 00:48:41,830
+ال
+
+377
+00:48:41,830 --> 00:48:45,730
+تكعيب ناقص
+
+378
+00:48:45,730 --> 00:48:53,130
+ال تكعيب على تمانية ناقص
+
+379
+00:48:53,130 --> 00:49:04,110
+ال على أربعة في L تربيع ناقص L تربيع على أربعة
+
+380
+00:49:04,110 --> 00:49:07,430
+يعني
+
+381
+00:49:07,430 --> 00:49:15,510
+هاخد L تكعيب بره. F L تكعيب على
+
+382
+00:49:15,510 --> 00:49:24,750
+اتنين E I واحد في هذا هتكون عندي تمانية أو واحد
+
+383
+00:49:24,750 --> 00:49:28,770
+ناقص ثمانية = سبعة على تمانية يعني هتكون عندي سبعة على
+
+384
+00:49:28,770 --> 00:49:29,750
+أربعة وعشرين
+
+385
+00:49:34,340 --> 00:49:45,160
+ناقص واحد ناقص ربع = تلت. أربعة - تلت = أربعة في ربع = تلت
+
+386
+00:49:45,160 --> 00:49:53,200
+ع ستة عشر يعني
+
+387
+00:49:53,200 --> 00:49:57,280
+هتصفي أربعة وعشرين
+
+388
+00:50:00,010 --> 00:50:13,250
+يعني هيكون عندي FL تكعيب على اتنين EI واحد في عندي
+
+389
+00:50:13,250 --> 00:50:17,690
+هيكون أربعة و ثمانين. أربعة و ثمانين على أربعة و
+
+390
+00:50:17,690 --> 00:50:26,130
+عشرين = اتنين في سبعة = أربعة عشر. ناقص أربعة و ثمانين
+
+391
+00:50:26,130 --> 00:50:32,800
+على ستة عشر = تلاتة. تلاتة = تسعة. أربعة عشر ناقص تسعة
+
+392
+00:50:32,800 --> 00:50:45,040
+اللي هي خمسة يعني هتصفي خمسة F L تكعيب على ستة
+
+393
+00:50:45,040 --> 00:50:51,080
+وتسعين E I واحد
+
+394
+00:50:52,500 --> 00:50:58,780
+معناته deflection at B اللي هو F L تكعيب على 96EI
+
+395
+00:50:58,780 --> 00:51:03,020
+أكيد ال deflection at B ارجع للحل قارنه بال
+
+396
+00:51:03,020 --> 00:51:17,800
+deflection at A. أكيد عند B هيكون أقل من عند A. طيب
+
+397
+00:51:17,800 --> 00:51:20,300
+نكمل
+
+398
+00:51:51,710 --> 00:51:59,810
+هنحل مسألة ثانية أكثر تعقيدا فيها تفاصيل أكثر
+
+399
+00:51:59,810 --> 00:52:03,310
+for
+
+400
+00:52:03,310 --> 00:52:08,430
+the wire form of diameter D as shown. في عندي سلك
+
+401
+00:52:08,430 --> 00:52:14,810
+مشكل بالشكل هذا ومثبت عند الطرف G السلك اللي هو
+
+402
+00:52:14,810 --> 00:52:19,330
+BCDG
+
+403
+00:52:19,330 --> 00:52:26,060
+مثبت عند الطرف G. قطره D small. قطر السلك D small
+
+404
+00:52:26,060 --> 00:52:30,220
+determine
+
+405
+00:52:30,220 --> 00:52:34,880
+the deflection of point B in the direction of the
+
+406
+00:52:34,880 --> 00:52:39,580
+applied force F. أوجد ال deflection عن نقطة B في
+
+407
+00:52:39,580 --> 00:52:43,120
+اتجاه ال force F. يعني في اتجاه هذا ال deflection
+
+408
+00:52:43,120 --> 00:52:46,420
+اللي بدي إياه. لو بدي ال deflection في هذا الاتجاه لازم
+
+409
+00:52:46,420 --> 00:52:49,540
+أحط force تخيليا Q. طيب
+
+410
+00:52:52,670 --> 00:52:58,070
+معطيني ملاحظة أو إشارة بيحكي neglect the effect of
+
+411
+00:52:58,070 --> 00:53:02,470
+
+445
+00:57:28,280 --> 00:57:36,340
+MBC by DX اللي هي X هتصير  دي في X  DX هيساوي هطلع
+
+446
+00:57:36,340 --> 00:57:38,660
+F على EI
+
+447
+00:57:42,410 --> 00:57:47,390
+هيبقى من صفر لـ A تكامل X تربيع على X تكعيب على
+
+448
+00:57:47,390 --> 00:57:56,250
+ثلاثة هتصير هذه الـ H تكاملها A تكعيب الـ Delta بـ C
+
+449
+00:57:56,250 --> 00:58:01,550
+الآن
+
+450
+00:58:01,550 --> 00:58:07,350
+CD هي CD CD
+
+451
+00:58:07,350 --> 00:58:14,140
+and the force هي هنا عند B هتعمل torsion هيو  تعمل
+
+452
+00:58:14,140 --> 00:58:26,420
+torsion عليه اللي هي الـ force بمسافة a اللي
+
+453
+00:58:26,420 --> 00:58:35,160
+هو هذا BC اللي هو هذا CD هذا هو اللي هتعمل
+
+454
+00:58:35,160 --> 00:58:36,900
+torsion
+
+455
+00:58:38,300 --> 00:58:43,240
+و في كمان bending moment اللي هتكون هذه المسافة X
+
+456
+00:58:43,240 --> 00:58:46,260
+يعني
+
+457
+00:58:46,260 --> 00:58:56,320
+هتكون عندي torsion section BC عندي
+
+458
+00:58:56,320 --> 00:59:03,480
+الـ bending moment MCD هتكون هذه المسافة X في الـ
+
+459
+00:59:03,480 --> 00:59:13,410
+force F  و في torsion CD اللي هيحبها راح تكون F A
+
+460
+00:59:13,410 --> 00:59:31,650
+F A هيكون عندها DMCD by DF بالساوية X و D TCD by
+
+461
+00:59:31,650 --> 00:59:34,550
+DF بالساوية A
+
+462
+00:59:39,170 --> 00:59:48,070
+معناته هيكون الـ Delta CD الـ Delta CD هيكون جزءين
+
+463
+00:59:48,070 --> 00:59:56,470
+جزء due to bending تكامل من واحد
+
+464
+00:59:56,470 --> 01:00:00,850
+على EI لـ
+
+465
+01:00:00,850 --> 01:00:12,610
+MCD DMCD by DF DXو الـ X تغير من صفر لـ B طوله B
+
+466
+01:00:12,610 --> 01:00:19,710
+من صفر لـ B زائد
+
+467
+01:00:19,710 --> 01:00:25,110
+تكامل لأن في عندي الـ torsion المعادلة نرجع لمعادلة
+
+468
+01:00:25,110 --> 01:00:29,470
+الـ torsion الـ torsion اللي هي هذه المعادلة
+
+469
+01:00:35,820 --> 01:00:45,740
+الـ .. الـ .. الـ .. الـ energy المعادلة الأصلية الـ
+
+470
+01:00:45,740 --> 01:00:49,460
+torsion هتكون
+
+471
+01:00:49,460 --> 01:00:57,600
+لما اشتق هذه بيصير واحد على G J
+
+472
+01:00:59,710 --> 01:01:21,870
+في TCD في DTCD by DF DX والـ X تغير من صفر لـ V نبدأ
+
+473
+01:01:21,870 --> 01:01:22,470
+نعوضها
+
+474
+01:01:32,110 --> 01:01:40,530
+يعني أنا هيكون عندي هنا الـ delta CD بتساوي تكامل من
+
+475
+01:01:40,530 --> 01:01:57,870
+0 لـ B من 0 لـ B لـ 1 على EI MCD اللي هي F X و DMCD
+
+476
+01:01:57,870 --> 01:02:07,230
+بقى DF اللي هي X DX زائد التكامل من 0 لـ V لـ 1 على G
+
+477
+01:02:07,230 --> 01:02:22,370
+J TCD اللي هي F في A في A DX يعني
+
+478
+01:02:22,370 --> 01:02:29,610
+هيكون يساوي F على EI تكامل
+
+479
+01:02:32,680 --> 01:02:40,300
+X تربيع DX من 0 لـ B زائد
+
+480
+01:02:40,300 --> 01:02:57,680
+1 على GJ تكامل في F طبعا F A تربيع تكامل DX من 0 لـ
+
+481
+01:02:57,680 --> 01:02:57,880
+B
+
+482
+01:03:04,500 --> 01:03:15,160
+يعني هيكون F B تكعيب على ثلاثة EI زائد
+
+483
+01:03:15,160 --> 01:03:29,940
+F A تربيع B على G J هذه الـ deflection في
+
+484
+01:03:29,940 --> 01:03:42,460
+الـ .. due to strain energy in section CD  ناخد
+
+485
+01:03:42,460 --> 01:03:48,980
+section DG هاخد أنا free body diagram الـ section DG الـ
+
+486
+01:03:48,980 --> 01:03:53,700
+force دي F هيعاكسها force هنا F زي دي  حكينا أنا اللي
+
+487
+01:03:53,700 --> 01:03:57,260
+عليه bending في مستويين فيه bending في هذا الاتجاه
+
+488
+01:03:58,340 --> 01:04:03,100
+و في bending في هذا الاتجاه يعني هيكون عندي في bending
+
+489
+01:04:03,100 --> 01:04:08,360
+بيحاول بهذا الاتجاه ايه و في bending بهذا الاتجاه
+
+490
+01:04:08,360 --> 01:04:12,420
+يعني
+
+491
+01:04:12,420 --> 01:04:16,200
+خلينا نسميها MDG 1 و MDG 2
+
+492
+01:04:29,510 --> 01:04:39,550
+MDG واحد هتكون
+
+493
+01:04:39,550 --> 01:04:51,630
+F في A هتعمل bending بهذا الاتجاه F في A دي
+
+494
+01:04:51,630 --> 01:05:04,220
+MDG واحد by DF هتكون الساوية A و الـ DG اتنين
+
+495
+01:05:04,220 --> 01:05:14,800
+هتكون بتحاول تلفها زي هيك هتكون F B F B يعني
+
+496
+01:05:14,800 --> 01:05:18,800
+هتكون الـ DM DG
+
+497
+01:05:18,800 --> 01:05:28,830
+اتنين by DF هتكون الساوية B معناته الـ Delta الـ
+
+498
+01:05:28,830 --> 01:05:36,690
+delta و في عندي axial force axial force معناته الـ
+
+499
+01:05:36,690 --> 01:05:42,850
+delta DG هتكون
+
+500
+01:05:42,850 --> 01:05:51,890
+due to this bending تكامل لأن نرجع للشكل على طوله
+
+501
+01:05:51,890 --> 01:05:56,130
+C هيكون
+
+502
+01:06:00,480 --> 01:06:08,280
+هيكون تكامل عند الـ bending الأولاني واحد على EI تكامل
+
+503
+01:06:08,280 --> 01:06:27,620
+صفر لـ C لـ MDG واحد في الـ DMDG 1 by DF DX زائد
+
+504
+01:06:27,620 --> 01:06:34,960
+التكامل من 0 لـ C 1 على EI  الآخر بين الـ component
+
+505
+01:06:34,960 --> 01:06:52,450
+اللي هي M DG 2 في DMDG 2 by DF في DX زائد في ان احنا
+
+506
+01:06:52,450 --> 01:06:56,650
+حكينا الـ Axial component Axial component اللي هي
+
+507
+01:06:56,650 --> 01:07:09,770
+هي معادلتها لها دي المعادلة تكامل من 0 لـ C 1 على A A
+
+508
+01:07:12,410 --> 01:07:19,110
+في F في .. في الـ .. في F في
+
+509
+01:07:19,110 --> 01:07:29,850
+DF by DF DX اه نبدأ نحل الـ integral هيكون يساوي
+
+510
+01:07:29,850 --> 01:07:33,550
+واحد
+
+511
+01:07:33,550 --> 01:07:38,130
+على EI تكامل من صفر لـ C
+
+512
+01:07:47,510 --> 01:07:54,710
+الـ MDG 1 حكينا F A و
+
+513
+01:07:54,710 --> 01:08:04,570
+DMG 1 بديها في اللي هي A DX زي التكامل من 0 لـ C
+
+514
+01:08:04,570 --> 01:08:15,390
+طبعا 1 على AI بتطلع برا MDG 2 اللي هي FB و
+
+515
+01:08:15,390 --> 01:08:22,760
+DMG 2 by df ب ب ب ب ب ب ب ب ب ب ب ب ب ب ب ب ب
+
+516
+01:08:22,760 --> 01:08:22,820
+ب ب ب ب ب ب ب ب ب ب ب ب ب ب ب ب
+
+517
+01:08:22,820 --> 01:08:26,180
+ب ب ب ب ب ب ب ب ب ب ب ب ب ب ب
+
+518
+01:08:26,180 --> 01:08:31,140
+ب ب ب ب ب ب ب ب ب ب ب ب ب ب ب
+
+519
+01:08:31,140 --> 01:08:31,160
+ب ب ب ب ب ب ب ب ب ب ب ب ب ب ب
+
+520
+01:08:31,160 --> 01:08:36,840
+ب ب ب ب ب ب ب ب ب ب
+
+521
+01:08:36,840 --> 01:08:44,900
+ب
+
+522
+01:08:44,900 --> 01:08:54,620
+بأول تكامل هذا عبارة عن F A تربيع في C F A تربيع
+
+523
+01:08:54,620 --> 01:09:01,260
+في C على EI زائد
+
+524
+01:09:01,260 --> 01:09:14,200
+F B تربيع C على EI زائد
+
+525
+01:09:18,900 --> 01:09:26,100
+FC على A في A لأن
+
+526
+01:09:26,100 --> 01:09:30,240
+خلينا نجمع إحنا أكدنا الـ deflection at B عبارة عن
+
+527
+01:09:30,240 --> 01:09:33,640
+deflection for section BC زي الـ deflection for
+
+528
+01:09:33,640 --> 01:09:38,980
+section CD زي الـ deflection for section DG معناته
+
+529
+01:09:38,980 --> 01:09:41,200
+الـ delta الكلية delta B
+
+530
+01:09:45,670 --> 01:09:50,970
+دلتا B الكلية هتكون
+
+531
+01:09:50,970 --> 01:09:57,490
+أول واحدة دلتا BC طلعت معنا F على
+
+532
+01:09:57,490 --> 01:10:06,430
+ثلاثة EI في A تكعيب هاي أول واحدة زائد الـ
+
+533
+01:10:06,430 --> 01:10:10,210
+deflection due to CD دي هي F B تكعيب
+
+534
+01:10:15,040 --> 01:10:25,940
+على ثلاثة EI اللي هي هذا الـ term زائد F A تربيع B
+
+535
+01:10:25,940 --> 01:10:33,240
+على G في J الـ
+
+536
+01:10:33,240 --> 01:10:42,300
+term الثالث اللي هو delta DG اللي هو هذا زائد F A
+
+537
+01:10:42,300 --> 01:11:01,200
+تربيع C على EI زائد FB تربيع C على EI زائد FC على A
+
+538
+01:11:01,200 --> 01:11:09,820
+في A هيك
+
+539
+01:11:09,820 --> 01:11:18,380
+حسبنا deflection عن نقطة B طبعا ممكن تكمل أكثر الآن
+
+540
+01:11:18,380 --> 01:11:22,860
+فيها اللي هو أن الـ I و الـ J و الـ A الـ A ايش
+
+541
+01:11:22,860 --> 01:11:32,420
+بالساوية باي على أربعة دي تربيع و الـ I باي على
+
+542
+01:11:32,420 --> 01:11:42,060
+أربعة و ستين دي قُطر أربعة و الـ J بالساوية باي على
+
+543
+01:11:42,060 --> 01:11:42,940
+اثنين و ثلاثين
+
+544
+01:11:45,620 --> 01:11:51,240
+D  أربعة D
+
+545
+01:11:51,240 --> 01:11:56,960
+أربعة و
+
+546
+01:11:56,960 --> 01:12:04,480
+في علاقة بين الـ E و الـ G من خلال Poisson's ratio في
+
+547
+01:12:04,480 --> 01:12:06,540
+علاقة بين الـ E و الـ G من خلال Poisson's ratio ممكن
+
+548
+01:12:06,540 --> 01:12:11,960
+تبسطها و تخليها بدلالة الـ E كلها أو بدلالة الـ G
+
+549
+01:12:15,400 --> 01:12:19,660
+يعني ممكن تعمل more simplification بس الـ .. الـ ..
+
+550
+01:12:19,660 --> 01:12:23,900
+الـ .. الـ main body للمثال حالناها و بعدين بيصير
+
+551
+01:12:23,900 --> 01:12:32,040
+الشغل شبر و تبسيط و بس يعني .. يعني ممكن يعملوا
+
+552
+01:12:32,040 --> 01:12:38,100
+طلاب أول سنة و ثانية سنة ممكن يشتغلوا الشغل زي هيك
+
+553
+01:12:49,860 --> 01:12:54,360
+طيب المرة الجاية بنكمل الـ deflection of curved
+
+554
+01:12:54,360 --> 01:13:02,080
+members بعدين هنشوف كيف نحل مسائل غير قابلة للحل
+
+555
+01:13:02,080 --> 01:13:05,420
+باستخدام طرق الاستاتيكا التقليدية
+
+556
+01:13:11,010 --> 01:13:13,950
+اللي هو statically indeterminate problems بعدين
+
+557
+01:13:13,950 --> 01:13:17,830
+الـ buckling of compression columns  تأثير نكون
+
+558
+01:13:17,830 --> 01:13:22,090
+خلصنا chapter أربعة طبعا chapter ثلاثة و أربعة
+
+559
+01:13:22,090 --> 01:13:27,310
+كانت تحضير و تهيئة للـ .. للـ  أساسيات في
+
+560
+01:13:27,310 --> 01:13:31,030
+المادة اللي هي design for static or static
+
+561
+01:13:31,030 --> 01:13:34,690
+design و عندنا fatigue design or design for
+
+562
+01:13:34,690 --> 01:13:38,160
+dynamic loading و فينا design for static loading
+
+563
+01:13:38,160 --> 01:13:42,580
+chapter ثلاثة وأربعة تجهيز و تحضير لهذول الـ two
+
+564
+01:13:42,580 --> 01:13:47,780
+chapters اللي هو المثال اللي هو قلب المادة
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BTYGbzBT3fw_raw.json b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BTYGbzBT3fw_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..9f04aab290b3cce57f37154e13bf282a15be24de
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BTYGbzBT3fw_raw.json
@@ -0,0 +1 @@
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"text": "طيب هذا المطلوب التاني what error is introduced if shear is neglected إذا أهملت الشير يعني اعتبرت الشير مهمل يعني لو حكيت if shear is neglected هكون ال y هي ال y بتاعة ال bending", "tokens": [9566, 1829, 3555, 23758, 9673, 9566, 1211, 37746, 16712, 7649, 1829, 437, 6713, 307, 7268, 498, 24082, 307, 32701, 11933, 15730, 5551, 16095, 1211, 2655, 25124, 13546, 37495, 22653, 1975, 34268, 26890, 2655, 25124, 13546, 3714, 16095, 1211, 37495, 22653, 45164, 11331, 4117, 36081, 498, 24082, 307, 32701, 8032, 30544, 2423, 288, 39896, 2423, 288, 39894, 995, 27884, 2423, 22487], "avg_logprob": -0.16892930523293917, "compression_ratio": 1.5802469135802468, "no_speech_prob": 0.0, "words": [{"start": 1242.93, "end": 1243.37, "word": "طيب", "probability": 0.9671223958333334}, {"start": 1243.37, "end": 1243.69, "word": " هذا", "probability": 0.58349609375}, {"start": 1243.69, "end": 1244.29, "word": " المطلوب", "probability": 0.9539794921875}, {"start": 1244.29, "end": 1245.71, "word": " 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"start": 1620.56, "end": 1647.8, "text": "Differential M with respect to F هتكون M هتكون اتنين M في DM by DF DX اتنين مع اتنين بتصفه سوى واحد على EI في M DM by DF DX", "tokens": [35, 12612, 2549, 376, 365, 3104, 281, 479, 8032, 2655, 30544, 376, 8032, 2655, 30544, 1975, 2655, 1863, 9957, 376, 8978, 15322, 538, 48336, 48817, 1975, 2655, 1863, 9957, 20449, 1975, 2655, 1863, 9957, 39894, 9381, 5172, 3224, 8608, 2407, 7578, 36764, 24401, 15844, 462, 40, 8978, 376, 15322, 538, 48336, 48817], "avg_logprob": -0.198260616581395, "compression_ratio": 1.330708661417323, "no_speech_prob": 0.0, "words": [{"start": 1620.56, "end": 1621.22, "word": "Differential", "probability": 0.5204264322916666}, {"start": 1621.22, "end": 1621.72, "word": " M", "probability": 0.7490234375}, {"start": 1621.72, "end": 1621.94, "word": " with", "probability": 0.8818359375}, {"start": 1621.94, "end": 1622.34, "word": " respect", "probability": 0.9599609375}, {"start": 1622.34, "end": 1622.6, "word": " to", 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GJ في TDT by DMI و delta I due to bending هتكون واحدة دي I في MDM by DFI في DX", "tokens": [3555, 3215, 9778, 1211, 2423, 39184, 15756, 10874, 14407, 4724, 1829, 9381, 13546, 16472, 2423, 39184, 8289, 286, 2423, 4914, 286, 4724, 1829, 9381, 1829, 5016, 36764, 24401, 3660, 15844, 32207, 8978, 479, 35, 37, 538, 48336, 40, 48817, 4032, 9725, 286, 3462, 281, 22487, 36764, 24401, 3660, 15844, 460, 41, 8978, 314, 35, 51, 538, 15322, 40, 4032, 8289, 286, 3462, 281, 22487, 8032, 2655, 30544, 36764, 24401, 3660, 11778, 1829, 286, 8978, 22521, 44, 538, 48336, 40, 8978, 48817], "avg_logprob": -0.3542301760214131, "compression_ratio": 1.5277777777777777, "no_speech_prob": 0.0, "words": [{"start": 1677.1, "end": 1677.6, "word": "بدخل", "probability": 0.8033447265625}, {"start": 1677.6, "end": 1677.68, "word": " الـ", "probability": 0.429443359375}, {"start": 1677.68, "end": 1677.98, "word": " differential", "probability": 0.673828125}, {"start": 1677.98, "end": 1678.32, "word": " جوا", 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"word": " هتكون", "probability": 0.8919270833333334}, {"start": 1700.82, "end": 1701.14, "word": " واحدة", "probability": 0.9798177083333334}, {"start": 1701.14, "end": 1701.28, "word": " دي", "probability": 0.53515625}, {"start": 1701.28, "end": 1701.48, "word": " I", "probability": 0.93212890625}, {"start": 1701.48, "end": 1701.68, "word": " في", "probability": 0.9287109375}, {"start": 1701.68, "end": 1702.26, "word": " MDM", "probability": 0.8017578125}, {"start": 1702.26, "end": 1702.44, "word": " by", "probability": 0.9677734375}, {"start": 1702.44, "end": 1702.92, "word": " DFI", "probability": 0.794677734375}, {"start": 1702.92, "end": 1703.1, "word": " في", "probability": 0.81005859375}, {"start": 1703.1, "end": 1703.7, "word": " DX", "probability": 0.9873046875}], "temperature": 1.0}, {"id": 60, "seek": 173601, "start": 1708.19, "end": 1736.01, "text": "تشوف مثال تاني تشوف مثال تاني using Castellanos method باستخدام طريقة Castellanos", "tokens": [2655, 8592, 38688, 50113, 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due to transverse shear is very small compared to that due to bending", "tokens": [2304, 46456, 46538, 18871, 9673, 47432, 3615, 8978, 25724, 11622, 38207, 9154, 363, 5296, 34, 286, 36764, 24401, 34105, 43242, 2423, 286, 5296, 19528, 47432, 3615, 14359, 48812, 3615, 5172, 2423, 286, 5296, 19528, 47432, 3615, 13838, 1975, 5016, 8315, 8978, 9673, 12984, 6027, 21136, 16758, 4587, 1975, 12984, 3555, 2655, 8315, 16472, 12174, 32640, 3660, 2423, 1060, 5450, 3462, 281, 1145, 4308, 24082, 307, 588, 1359, 5347, 281, 300, 3462, 281, 22487], "avg_logprob": -0.19172297659757975, "compression_ratio": 1.4742268041237114, "no_speech_prob": 0.0, "words": [{"start": 1820.34, "end": 1821.04, "word": "مختلف", "probability": 0.9104817708333334}, {"start": 1821.04, "end": 1821.28, "word": " عن", "probability": 0.7783203125}, {"start": 1821.28, "end": 1821.84, "word": " المقطع", "probability": 0.9755859375}, {"start": 1821.84, "end": 1821.96, "word": " في", "probability": 0.49267578125}, {"start": 1821.96, 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X minus L على اتنين", "tokens": [15, 5296, 33456, 29538, 479, 37037, 24192, 1783, 34105, 8608, 10721, 5016, 35457, 15322, 7869, 26930, 413, 48, 8032, 2655, 30544, 8608, 5172, 2288, 30767, 16373, 3215, 1783, 3175, 441, 15844, 1975, 2655, 1863, 9957], "avg_logprob": -0.4257812599341075, "compression_ratio": 1.018181818181818, "no_speech_prob": 2.384185791015625e-07, "words": [{"start": 2617.61, "end": 2618.11, "word": "0", "probability": 0.2264404296875}, {"start": 2618.11, "end": 2618.69, "word": " لأن", "probability": 0.694580078125}, {"start": 2618.69, "end": 2618.85, "word": " هذه", "probability": 0.469970703125}, {"start": 2618.85, "end": 2619.05, "word": " F", "probability": 0.5205078125}, {"start": 2619.05, "end": 2619.27, "word": " وهذه", "probability": 0.87109375}, {"start": 2619.27, "end": 2619.61, "word": " X", "probability": 0.94384765625}, {"start": 2619.61, "end": 2621.73, "word": " هنا", "probability": 0.1756591796875}, {"start": 2621.73, "end": 2622.31, "word": " سأحسب", 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"start": 2650.71, "end": 2677.63, "text": "I have only bending معناته delta B هتكون تساوي انا هقسم لجزئين من A ل B و من B ل C تكامل من 0 ل L على 2 ل 1 على E ال section AB ال I تعته I واحد", "tokens": [40, 362, 787, 22487, 20449, 8315, 47395, 8289, 363, 8032, 2655, 30544, 6055, 3794, 995, 45865, 1975, 8315, 8032, 4587, 38251, 5296, 7435, 11622, 19986, 9957, 9154, 316, 5296, 363, 4032, 9154, 363, 5296, 383, 6055, 4117, 10943, 1211, 9154, 1958, 5296, 441, 15844, 568, 5296, 502, 15844, 462, 2423, 3541, 13838, 2423, 286, 6055, 34268, 3224, 286, 36764, 24401], "avg_logprob": -0.24859117679908627, "compression_ratio": 1.2857142857142858, "no_speech_prob": 0.0, "words": [{"start": 2650.71, "end": 2650.99, "word": "I", "probability": 0.89013671875}, {"start": 2650.99, "end": 2651.25, "word": " have", "probability": 0.8857421875}, {"start": 2651.25, "end": 2651.59, "word": " only", "probability": 0.939453125}, {"start": 2651.59, "end": 2652.07, "word": " bending", "probability": 0.81494140625}, 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2705.0, "text": "في MAB DMAB by DQ DX زائد التكامل من L على 2 لL في 1 على E ال I بتاع ال section 2 عبارة عن 2EI 1", "tokens": [41185, 376, 13868, 15322, 13868, 538, 413, 48, 48817, 30767, 16373, 3215, 16712, 4117, 10943, 1211, 9154, 441, 15844, 568, 5296, 43, 8978, 502, 15844, 462, 2423, 286, 39894, 45761, 2423, 3541, 568, 6225, 3555, 9640, 3660, 18871, 568, 36, 40, 502], "avg_logprob": -0.3095930357312047, "compression_ratio": 1.1065573770491803, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 2681.26, "end": 2682.26, "word": "في", "probability": 0.20751953125}, {"start": 2682.26, "end": 2683.26, "word": " MAB", "probability": 0.683349609375}, {"start": 2683.26, "end": 2686.32, "word": " DMAB", "probability": 0.85888671875}, {"start": 2686.32, "end": 2688.24, "word": " by", "probability": 0.419921875}, {"start": 2688.24, "end": 2688.92, "word": " DQ", "probability": 0.734375}, {"start": 2688.92, "end": 2690.64, "word": " DX", "probability": 0.78564453125}, {"start": 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تلاتة", "probability": 0.794677734375}, {"start": 3468.13, "end": 3471.11, "word": " هتصير", "probability": 0.52435302734375}, {"start": 3471.11, "end": 3471.29, "word": " هذه", "probability": 0.34619140625}, {"start": 3471.29, "end": 3471.51, "word": " ال", "probability": 0.8447265625}, {"start": 3471.51, "end": 3471.51, "word": " H", "probability": 0.52392578125}, {"start": 3471.51, "end": 3472.35, "word": " تكملها", "probability": 0.9361572265625}, {"start": 3472.35, "end": 3473.53, "word": " A", "probability": 0.8505859375}, {"start": 3473.53, "end": 3474.05, "word": " تكييب", "probability": 0.990625}, {"start": 3474.05, "end": 3475.15, "word": " ال", "probability": 0.260498046875}, {"start": 3475.15, "end": 3475.49, "word": " Delta", "probability": 0.4443359375}, {"start": 3475.49, "end": 3476.25, "word": " بC", "probability": 0.5484619140625}, {"start": 3476.25, "end": 3481.55, "word": " الان", "probability": 0.638671875}, {"start": 3481.55, "end": 3483.01, "word": " CD", "probability": 0.79736328125}, {"start": 3483.01, "end": 3483.25, "word": " هي", "probability": 0.63720703125}, {"start": 3483.25, "end": 3484.19, "word": " CD", "probability": 0.72412109375}, {"start": 3484.19, "end": 3487.35, "word": " CD", "probability": 0.48876953125}, {"start": 3487.35, "end": 3487.53, "word": " and", "probability": 0.60693359375}, {"start": 3487.53, "end": 3487.99, "word": " force", "probability": 0.1680908203125}, {"start": 3487.99, "end": 3488.19, "word": " هي", "probability": 0.728515625}, {"start": 3488.19, "end": 3488.41, "word": " هنا", "probability": 0.61572265625}, {"start": 3488.41, "end": 3488.61, "word": " عند", "probability": 0.10577392578125}, {"start": 3488.61, "end": 3488.83, "word": " B", "probability": 0.6591796875}, {"start": 3488.83, "end": 3490.93, "word": " هتعمل", "probability": 0.9609375}, {"start": 3490.93, "end": 3491.57, "word": " torsion", "probability": 0.7433268229166666}], "temperature": 1.0}, {"id": 120, "seek": 351690, "start": 3492.7, "end": 3516.9, "text": "هيو تعملي torsion عليه اللي هي ال force بمسافة a اللي هو هذا بي سي اللي هو هذا سي دي هذا هو اللي هتعملي torsion", "tokens": [3224, 1829, 2407, 6055, 25957, 20292, 3930, 82, 313, 47356, 13672, 1829, 39896, 2423, 3464, 4724, 2304, 3794, 31845, 3660, 257, 13672, 1829, 31439, 23758, 4724, 1829, 8608, 1829, 13672, 1829, 31439, 23758, 8608, 1829, 11778, 1829, 23758, 31439, 13672, 1829, 8032, 2655, 25957, 20292, 3930, 82, 313], "avg_logprob": -0.421556112717609, "compression_ratio": 1.6952380952380952, "no_speech_prob": 0.0, "words": [{"start": 3492.7, "end": 3493.24, "word": "هيو", "probability": 0.5066731770833334}, {"start": 3493.24, "end": 3494.14, "word": " تعملي", "probability": 0.74853515625}, {"start": 3494.14, "end": 3494.66, "word": " torsion", "probability": 0.611572265625}, {"start": 3494.66, "end": 3495.02, "word": " عليه", "probability": 0.46435546875}, {"start": 3495.02, "end": 3496.24, "word": " اللي", "probability": 0.750244140625}, {"start": 3496.24, "end": 3496.36, "word": " هي", "probability": 0.85888671875}, {"start": 3496.36, "end": 3496.48, "word": " ال", "probability": 0.398193359375}, {"start": 3496.48, "end": 3496.6, "word": " force", "probability": 0.84228515625}, {"start": 3496.6, "end": 3498.08, "word": " بمسافة", "probability": 0.83076171875}, {"start": 3498.08, "end": 3499.16, "word": " a", "probability": 0.362548828125}, {"start": 3499.16, "end": 3506.42, "word": " اللي", "probability": 0.952880859375}, {"start": 3506.42, "end": 3506.54, "word": " هو", "probability": 0.8369140625}, {"start": 3506.54, "end": 3506.76, "word": " هذا", "probability": 0.7705078125}, {"start": 3506.76, "end": 3507.08, "word": " بي", "probability": 0.734619140625}, {"start": 3507.08, "end": 3507.36, "word": " سي", "probability": 0.766357421875}, {"start": 3507.36, "end": 3508.74, "word": " اللي", "probability": 0.6258544921875}, {"start": 3508.74, "end": 3508.86, "word": " هو", "probability": 0.37890625}, {"start": 3508.86, "end": 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37495, 22653, 8032, 2655, 30544, 18871, 16254, 3930, 82, 313, 3541, 14359, 18871, 16254, 2423, 22487, 1623, 8797, 35, 8032, 2655, 30544, 29538, 9673, 3794, 31845, 3660, 1783, 8978, 2423, 3464, 479, 1783], "avg_logprob": -0.28410455813774693, "compression_ratio": 1.6614173228346456, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 3518.3, "end": 3518.52, "word": "و", "probability": 0.740234375}, {"start": 3518.52, "end": 3518.66, "word": " في", "probability": 0.31591796875}, {"start": 3518.66, "end": 3519.12, "word": " كمان", "probability": 0.9464518229166666}, {"start": 3519.12, "end": 3519.52, "word": " bending", "probability": 0.47216796875}, {"start": 3519.52, "end": 3520.0, "word": " moment", "probability": 0.97900390625}, {"start": 3520.0, "end": 3521.76, "word": " اللي", "probability": 0.3778076171875}, {"start": 3521.76, "end": 3522.08, "word": " هتكون", "probability": 0.9365234375}, {"start": 3522.08, "end": 3522.3, "word": " هذه", "probability": 0.79052734375}, {"start": 3522.3, "end": 3522.74, "word": " المسافة", "probability": 0.984130859375}, {"start": 3522.74, "end": 3523.24, "word": " X", "probability": 0.54150390625}, {"start": 3523.24, "end": 3526.26, "word": " يعني", "probability": 0.905029296875}, {"start": 3526.26, "end": 3526.56, "word": " هتكون", "probability": 0.8439127604166666}, {"start": 3526.56, "end": 3526.88, "word": " عندي", "probability": 0.67626953125}, {"start": 3526.88, "end": 3527.86, "word": " torsion", "probability": 0.8409830729166666}, {"start": 3527.86, "end": 3530.34, "word": " section", "probability": 0.247314453125}, {"start": 3530.34, "end": 3530.86, "word": " BC", "probability": 0.677734375}, {"start": 3530.86, "end": 3536.32, "word": " عندي", "probability": 0.74072265625}, {"start": 3536.32, "end": 3537.4, "word": " ال", "probability": 0.468994140625}, {"start": 3537.4, "end": 3537.94, "word": " bending", "probability": 0.77392578125}, {"start": 3537.94, "end": 3538.22, "word": " moment", "probability": 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بالساوية X و D TCD by DF بالساوية A", "tokens": [2407, 8978, 8717, 2655, 13063, 7435, 9957, 6743, 13672, 1829, 39896, 5016, 3555, 11296, 12602, 39319, 6055, 30544, 479, 316, 479, 316, 8032, 1829, 30544, 43242, 3224, 7649, 15322, 16508, 538, 48336, 20666, 3794, 995, 2407, 10632, 1783, 4032, 413, 314, 16508, 538, 48336, 20666, 3794, 995, 2407, 10632, 316], "avg_logprob": -0.38756126282261866, "compression_ratio": 1.382608695652174, "no_speech_prob": 0.0, "words": [{"start": 3547.73, "end": 3547.95, "word": "و", "probability": 0.6279296875}, {"start": 3547.95, "end": 3548.03, "word": " في", "probability": 0.60205078125}, {"start": 3548.03, "end": 3548.73, "word": " نتورجين", "probability": 0.59873046875}, {"start": 3548.73, "end": 3549.71, "word": " CD", "probability": 0.324462890625}, {"start": 3549.71, "end": 3551.51, "word": " اللي", "probability": 0.57452392578125}, {"start": 3551.51, "end": 3551.83, "word": " هيحبها", "probability": 0.6558837890625}, {"start": 3551.83, "end": 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عندنا", "probability": 0.877197265625}, {"start": 4412.53, "end": 4412.91, "word": " fatigue", "probability": 0.966796875}, {"start": 4412.91, "end": 4413.53, "word": " design", "probability": 0.9833984375}, {"start": 4413.53, "end": 4413.93, "word": " او", "probability": 0.876220703125}, {"start": 4413.93, "end": 4414.33, "word": " design", "probability": 0.96533203125}, {"start": 4414.33, "end": 4414.69, "word": " for", "probability": 0.98046875}, {"start": 4414.69, "end": 4415.25, "word": " dynamic", "probability": 0.7939453125}, {"start": 4415.25, "end": 4415.83, "word": " loading", "probability": 0.93896484375}], "temperature": 1.0}, {"id": 152, "seek": 442778, "start": 4416.42, "end": 4427.78, "text": "و فينا design for static loading chapter تلاتة وأربعة تجهيز و تحضير لهدول ال two chapters اللي هو مثله اللي هو قلب المادة", "tokens": [2407, 8978, 8315, 1715, 337, 13437, 15114, 7187, 6055, 1211, 9307, 3660, 36725, 25513, 27884, 6055, 7435, 3224, 1829, 11622, 4032, 6055, 5016, 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\ No newline at end of file
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BohkPcY7GQQ_postprocess.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BohkPcY7GQQ_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..55b6e09ce2d6facd83f9b558871bb2b9b5afcedc
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BohkPcY7GQQ_postprocess.srt
@@ -0,0 +1,1932 @@
+1
+00:00:05,150 --> 00:00:11,390
+السلام عليكم المرة اللي فاتت حكينا عن كيفية حساب
+
+2
+00:00:11,390 --> 00:00:14,430
+ال fatigue stress concentration factor حكينا كف
+
+3
+00:00:14,430 --> 00:00:23,770
+بساوي كف بساوي واحد زاد كيو في كت ماينوس واحد الكت
+
+4
+00:00:23,770 --> 00:00:26,470
+ال geometric stress concentration factor الكيو ال
+
+5
+00:00:26,470 --> 00:00:29,870
+notch sensitivity factor الكيو حكيها بنحسب من شكل
+
+6
+00:00:29,870 --> 00:00:34,080
+ستة عشرين وشكل ستة واحد عشرينو ال kit هي من
+
+7
+00:00:34,080 --> 00:00:39,020
+appendix A9 بتحسب طبيعة ال loading و حسب طبيعة ال
+
+8
+00:00:39,020 --> 00:00:43,020
+geometry لل mechanical part الآن السؤال اليوم how
+
+9
+00:00:43,020 --> 00:00:47,980
+to apply fatigue stress concentration factor الان
+
+10
+00:00:47,980 --> 00:00:51,920
+use KF as a multiplier to increase nominal stress
+
+11
+00:00:51,920 --> 00:00:58,410
+يعني انا حسب nominal stress sigma مثلا ميةوالـ KF
+
+12
+00:00:58,410 --> 00:01:03,470
+حسبته طالع عندي مثلا واحد point تمانية هحكس ..
+
+13
+00:01:03,470 --> 00:01:09,970
+هضرب KF في Sigma O هيكون واحد point تمانية في مية
+
+14
+00:01:09,970 --> 00:01:16,390
+هيكون عندي مية و تمانين بعض
+
+15
+00:01:16,390 --> 00:01:22,530
+المصممين بتقالله endurance strength بيقسملي SE او
+
+16
+00:01:22,530 --> 00:01:26,790
+or بيحكيلي SE على
+
+17
+00:01:28,610 --> 00:01:34,110
+كيف ياما ياما بترفع ال stress level أو بتنزل ال
+
+18
+00:01:34,110 --> 00:01:38,130
+endurance limit يعني ممكن تستخدمه as a multiplier
+
+19
+00:01:38,130 --> 00:01:43,090
+or as a reduction في الحالة دي for infinite life
+
+20
+00:01:43,090 --> 00:01:47,790
+for infinite life ال NF بالساوية SE في كيف على
+
+21
+00:01:47,790 --> 00:01:51,700
+سيجماال KF في sigma عبارة عن multiplier انا برفع
+
+22
+00:01:51,700 --> 00:01:55,680
+ال stress او بحكي واحدة ل KF في SE Reducer ان الكف
+
+23
+00:01:55,680 --> 00:02:02,600
+استخدمت عشان اقلل ال endurance limit هذا في حالة
+
+24
+00:02:02,600 --> 00:02:07,480
+infinite life for finite lifeحالة finite life
+
+25
+00:02:07,480 --> 00:02:11,680
+increasing stress is more conservative أنه أرفع ال
+
+26
+00:02:11,680 --> 00:02:17,160
+stress بيعطيني نتائج محافظة أكتر يعني يعني أنصر
+
+27
+00:02:17,160 --> 00:02:21,160
+المخاطرة في الحسابة بتاعتي بيكون أقل decreasing SF
+
+28
+00:02:21,160 --> 00:02:27,420
+applies more to high cycle than low cycle fatigue
+
+29
+00:02:27,420 --> 00:02:29,660
+نشوف example
+
+30
+00:02:37,220 --> 00:02:40,960
+for the step shaft of example ستة ستة احنا كانت في
+
+31
+00:02:40,960 --> 00:02:45,580
+ال exam ستة ستة عندي step shaft
+
+32
+00:02:45,580 --> 00:03:03,440
+هذه
+
+33
+00:03:03,440 --> 00:03:23,500
+كانتع فكرة هي كراسة مغلط ها
+
+34
+00:03:23,500 --> 00:03:29,380
+step shaft ال exhaust ستكانها دي اتنين و تلاتين
+
+35
+00:03:29,380 --> 00:03:41,730
+ميلي وهذا ديR تلاتة الفيلت وهذه تمانية وتلاتين it
+
+36
+00:03:41,730 --> 00:03:46,290
+is
+
+37
+00:03:46,290 --> 00:03:48,750
+it is determined that the fully corrected
+
+38
+00:03:48,750 --> 00:03:54,330
+endurance limit ال SE fully corrected يعني انا ا
+
+39
+00:03:54,330 --> 00:03:58,590
+take care of ال modification factors K A K B K C K
+
+40
+00:03:58,590 --> 00:04:09,220
+D E K A K F بالساعتين و تمانينميجا بسكال consider
+
+41
+00:04:09,220 --> 00:04:13,680
+the shaft undergoing a fully reversed nominal
+
+42
+00:04:13,680 --> 00:04:21,460
+stress sigma reversible nominal هسميها او بس هو
+
+43
+00:04:21,460 --> 00:04:29,780
+متين وستين ميجا بسكال estimate the number of
+
+44
+00:04:29,780 --> 00:04:31,580
+cycles due failure
+
+45
+00:04:35,330 --> 00:04:39,790
+الان هذا النمو ال stress without stress without
+
+46
+00:04:39,790 --> 00:04:45,050
+stress concentration اذا فاكرين من example السابق
+
+47
+00:04:45,050 --> 00:04:50,850
+انا حسبت ال KF بالساوية
+
+48
+00:04:50,850 --> 00:04:57,810
+احنا حسبنا ال ال KF
+
+49
+00:05:02,160 --> 00:05:08,280
+أظن ان واحد bond ستة خمسة هنا مطلوب انكم تتأكدوا
+
+50
+00:05:08,280 --> 00:05:12,900
+تأكدوا ارجعوا للفيديو تأكدوا من القيمة هذه افرض
+
+51
+00:05:12,900 --> 00:05:20,140
+هنا KF يساوي bond ستة خمسة معناته ال sigma هتكون
+
+52
+00:05:20,140 --> 00:05:25,300
+KF في
+
+53
+00:05:25,300 --> 00:05:45,880
+sigma reversible nominal يعني هيكون1.65×260 تطلع
+
+54
+00:05:45,880 --> 00:05:51,180
+429 ميجا
+
+55
+00:05:51,180 --> 00:05:57,380
+باسكال ال SUT كان معطنيها في ال exam ال سابق ال
+
+56
+00:05:57,380 --> 00:05:57,920
+SUT
+
+57
+00:06:04,160 --> 00:06:12,080
+كان معطينا ال STD 690 ميجا بسكال 690 ميجا بسكال
+
+58
+00:06:12,080 --> 00:06:19,340
+لاحظوا
+
+59
+00:06:19,340 --> 00:06:26,160
+ال sigma reversible أكبر
+
+60
+00:06:26,160 --> 00:06:31,520
+من ال endurance limit وأصغر من ال tensile strength
+
+61
+00:06:33,340 --> 00:06:37,740
+ما زالها أكبر من ال SE
+
+62
+00:06:37,740 --> 00:06:47,000
+معناته we have infinite life sigma reversible أكبر
+
+63
+00:06:47,000 --> 00:06:56,920
+من ال SE و أصغر من ال SUT معناته we have finite
+
+64
+00:06:56,920 --> 00:07:00,440
+life
+
+65
+00:07:05,100 --> 00:07:10,480
+ما زال finite life هنستخدم المعادلات اللي هو في
+
+66
+00:07:10,480 --> 00:07:17,580
+المحاضرة السابقة اللي هي finite
+
+67
+00:07:17,580 --> 00:07:18,140
+life
+
+68
+00:07:40,650 --> 00:07:45,090
+أه اللي هي المعادلة الهادئة المعادلة 613 SF نحسب
+
+69
+00:07:45,090 --> 00:07:51,510
+SF بالثوابة
+
+70
+00:07:51,510 --> 00:07:58,970
+A فى N أقصى B و
+
+71
+00:07:58,970 --> 00:08:11,420
+A بسوء F S U T الكل تربية على S Aو ال B بيستوى
+
+72
+00:08:11,420 --> 00:08:25,480
+ناقص تلت log اللي هو F S U T على S A الان واضح ان
+
+73
+00:08:25,480 --> 00:08:32,940
+انا محتاج ال F ال F من هنا بحسبها من
+
+74
+00:08:32,940 --> 00:08:39,700
+figure ستة تمانتاش figure ستة تمانتاش
+
+75
+00:08:44,300 --> 00:08:54,160
+ال ستمية وتسعين ميجا باسكال حوالي ميت كيلو باسكال
+
+76
+00:08:54,160 --> 00:08:59,380
+ستمية وتسعين كيلو هدف بال English unit بتساوي ميت
+
+77
+00:08:59,380 --> 00:09:07,540
+كيلو pound per square inch عند مية عشان احسب ال F
+
+78
+00:09:07,540 --> 00:09:10,940
+من figure ستة تمانتاش هاي المية
+
+79
+00:09:27,940 --> 00:09:41,920
+ال F يعني
+
+80
+00:09:41,920 --> 00:09:49,600
+ممكن أحكي بون تمانية أربعة خمسة تطلع ال F بصابون
+
+81
+00:09:49,600 --> 00:09:51,700
+تمانية أربعة
+
+82
+00:09:53,610 --> 00:10:00,930
+خمسة من figure ستة تمانتاش و أنا بتبقى نحسب ال a
+
+83
+00:10:00,930 --> 00:10:08,930
+هنا حسه bond تمانية أربعة خمسة في ستمية وتسعين
+
+84
+00:10:08,930 --> 00:10:20,510
+الكل تربيع على SE SE اللي هي متين و تمانينوانا
+
+85
+00:10:20,510 --> 00:10:30,450
+بحسب ال A ال B هتكون سوى ناقص تلت log اللي هو ال F
+
+86
+00:10:30,450 --> 00:10:36,690
+اللي هي upon تمانية أربعة خمسة في ستمية وتسعين على
+
+87
+00:10:36,690 --> 00:10:38,530
+الاسم يومتين و تمانين
+
+88
+00:11:00,600 --> 00:11:09,580
+تطلع ألف و متين و أربعة و اتاش وال
+
+89
+00:11:09,580 --> 00:11:23,160
+B point
+
+90
+00:11:23,160 --> 00:11:24,740
+تمانية أربعة و خمسة
+
+91
+00:11:44,610 --> 00:11:50,570
+تقسم تلاتة تطلع minus minus
+
+92
+00:11:50,570 --> 00:11:54,670
+point
+
+93
+00:11:54,670 --> 00:12:00,030
+واحد زيرو ستة اتنين
+
+94
+00:12:15,440 --> 00:12:27,180
+الان الان الان هتساوي sigma reversible على a سواحد
+
+95
+00:12:27,180 --> 00:12:31,520
+على بي يعني هيتساوي sigma reversible يعني حسبناها
+
+96
+00:12:31,520 --> 00:12:34,360
+بعد after applying اللي هو ال stress fatigue
+
+97
+00:12:34,360 --> 00:12:39,080
+stress concentration factor أربعمية و تسعة و عشرين
+
+98
+00:12:39,080 --> 00:12:48,990
+على ال a اللي هي الف و متين و أربعتاشرأس واحد على
+
+99
+00:12:48,990 --> 00:12:58,690
+سالب point واحد ستة اتنين اربعمائة
+
+100
+00:12:58,690 --> 00:13:07,430
+وتسعة وعشرين تقسيم ألف ومتين واربعتاش ساوي أس
+
+101
+00:13:11,030 --> 00:13:19,870
+واحد على سالب point one zero six اتنين
+
+102
+00:13:19,870 --> 00:13:27,690
+تطلع سبعتاشر الف تسعمية
+
+103
+00:13:27,690 --> 00:13:33,190
+و اتنين و اربعين cycle يعني ال shaft هذا هيلف
+
+104
+00:13:33,190 --> 00:13:37,450
+سبعتاشر الف تسعمية و اتنين و اربعين لفة و بعدين
+
+105
+00:13:37,450 --> 00:13:38,050
+هيصير ال failure
+
+106
+00:13:59,550 --> 00:14:05,230
+طيب هيك احنا حسبنا النبر of cycles to failure نشوف
+
+107
+00:14:05,230 --> 00:14:26,890
+مثال تاني مثال 68 طيب
+
+108
+00:14:29,720 --> 00:14:33,060
+a ten fifteen hot rolled steel ال material بتاعت
+
+109
+00:14:33,060 --> 00:14:40,240
+ال bar ال material بتاعته عشرة خمستاش
+
+110
+00:14:40,240 --> 00:14:50,160
+hot rolled steel حديد نفس الكربون في point واحد
+
+111
+00:14:50,160 --> 00:14:55,180
+خمسة ومسحوب على الساخن has been machined to a
+
+112
+00:14:55,180 --> 00:15:05,360
+meter of one inch القطر بتاع ال shaftوحد انش it
+
+113
+00:15:05,360 --> 00:15:09,520
+is to be placed in a reversed axial loading for
+
+114
+00:15:09,520 --> 00:15:13,200
+seventy thousand cycles الان number of cycles
+
+115
+00:15:13,200 --> 00:15:16,260
+سبعين
+
+116
+00:15:16,260 --> 00:15:20,880
+الف to
+
+117
+00:15:20,880 --> 00:15:25,160
+failure in an operating environment of خمس بيه و
+
+118
+00:15:25,160 --> 00:15:30,600
+خمسين Fahrenheit درجة الحرارةخمسمية و خمسين
+
+119
+00:15:30,600 --> 00:15:37,540
+degrees Fahrenheit using
+
+120
+00:15:37,540 --> 00:15:42,160
+ASTM minimum properties and a reliability of
+
+121
+00:15:42,160 --> 00:15:46,960
+ninety-nine percent ال R&D تسعة وتسعين في المية
+
+122
+00:15:46,960 --> 00:15:50,640
+estimate
+
+123
+00:15:50,640 --> 00:15:56,660
+the endurance limit and fatigue strength at يعني
+
+124
+00:15:56,660 --> 00:15:57,800
+بدنا نحسب ال SE
+
+125
+00:16:01,100 --> 00:16:04,980
+و ال SF SFN
+
+126
+00:16:04,980 --> 00:16:09,000
+أول
+
+127
+00:16:09,000 --> 00:16:13,360
+شي مثال زي هيك بدي أطلع الخواص الميكانيكية للمعدن
+
+128
+00:16:13,360 --> 00:16:19,580
+هذا هروح على الجدول هروح على جدول A20 في شجلة هروح
+
+129
+00:16:19,580 --> 00:16:20,680
+على جدول A20
+
+130
+00:16:32,740 --> 00:16:38,580
+هذا ايه عشرين ايه عشرين دي hot rolled steel الف و
+
+131
+00:16:38,580 --> 00:16:46,580
+خمس عشر اللي هو هذا هذا الف و خمس عشر hot rolled
+
+132
+00:16:46,580 --> 00:16:52,320
+معطينة هذه ال tensile strength هذه ال yield
+
+133
+00:16:52,320 --> 00:17:03,050
+strength ال .. ال tensile strengthالو خمسين كيلو
+
+134
+00:17:03,050 --> 00:17:10,970
+pound per square inch ال SUT خمسين
+
+135
+00:17:10,970 --> 00:17:21,410
+كيلو pound per square inch خليني أكبرها شوية
+
+136
+00:17:21,410 --> 00:17:27,190
+هاي
+
+137
+00:17:27,190 --> 00:17:27,390
+ها
+
+138
+00:17:30,280 --> 00:17:38,700
+وهذا ال yield strength والأسواق له مستوى
+
+139
+00:17:38,700 --> 00:17:43,900
+سبعة وعشر و نص كيلو pound per square inch
+
+140
+00:18:05,760 --> 00:18:12,100
+طيب هذا ال table A20
+
+141
+00:18:12,100 --> 00:18:18,140
+أول
+
+142
+00:18:18,140 --> 00:18:24,880
+شي هحسب ال S A prime اللي هي ال S A prime هتكون نص
+
+143
+00:18:24,880 --> 00:18:27,320
+ال S U T
+
+144
+00:18:30,610 --> 00:18:37,970
+في خمسين سواء خمسة وعشرين kilo pound per square
+
+145
+00:18:37,970 --> 00:18:44,930
+inch ال SE هتكون
+
+146
+00:18:44,930 --> 00:18:57,270
+KA KB KC KD KE KF في ال SE primeالـ SE Prime
+
+147
+00:18:57,270 --> 00:18:59,870
+already حصلت لـ 25% الـ KA اللي هو الـ service
+
+148
+00:18:59,870 --> 00:19:00,930
+finish factor
+
+149
+00:19:30,450 --> 00:19:38,730
+الـ K A بالسواء
+
+150
+00:19:38,730 --> 00:19:45,550
+A في S U T AUS B انا
+
+151
+00:19:45,550 --> 00:19:49,610
+عندي hot rolled هاي hot rolled و الوحدات اللي هي
+
+152
+00:19:49,610 --> 00:19:54,630
+انجلزية معناته هتكون عنديا ال A
+
+153
+00:20:01,390 --> 00:20:12,490
+بتساوى أربع تاش point أربع وال
+
+154
+00:20:12,490 --> 00:20:23,810
+بي minus point سبعة واحد تمانية minus على
+
+155
+00:20:23,810 --> 00:20:33,470
+table ستة اتنين هدولتابل ستة اتنين معناته يعني ال
+
+156
+00:20:33,470 --> 00:20:38,650
+K A هيكون ال A اللي هي أربع تاش point أربعة في ال
+
+157
+00:20:38,650 --> 00:20:44,950
+SUT خمسين أس minus point سبعة واحد تمانية
+
+158
+00:21:17,190 --> 00:21:26,490
+فى بيطلع بون تمانية ستة تمانية بون تمانية ستة
+
+159
+00:21:26,490 --> 00:21:35,130
+تمانية ال KB ال
+
+160
+00:21:35,130 --> 00:21:41,130
+size factor ال KB هكون
+
+161
+00:21:41,130 --> 00:21:41,670
+ساوى
+
+162
+00:21:45,670 --> 00:21:54,150
+بون تمانية سبعة تسعة في دي
+
+163
+00:21:54,150 --> 00:22:01,290
+اص minus point one zero seven هيساوي بون تمانية
+
+164
+00:22:01,290 --> 00:22:06,790
+سبعة تسعة في دي اللي هي واحد اص minus point one
+
+165
+00:22:06,790 --> 00:22:07,570
+zero seven
+
+166
+00:22:15,180 --> 00:22:31,540
+واحد أس واحد
+
+167
+00:22:31,540 --> 00:22:40,820
+يعني هاتكون point تمانية سبعة تسعة هاد
+
+168
+00:22:40,820 --> 00:22:41,320
+الكابي
+
+169
+00:22:53,760 --> 00:23:02,980
+الان هو حكالي it is under ال KC هتكون
+
+170
+00:23:02,980 --> 00:23:05,860
+تساوى point تمانية خمسة لأن هو under point تمانية
+
+171
+00:23:05,860 --> 00:23:14,500
+خمسة completely reversed
+
+172
+00:23:14,500 --> 00:23:18,000
+axial loading
+
+173
+00:23:22,090 --> 00:23:26,170
+لأن بالنسبة ل KD اللي هي ال factor بتاع الحرارة
+
+174
+00:23:26,170 --> 00:23:31,550
+الحرارة عندي خمسمية و خمسين فهرام height يعني هكون
+
+175
+00:23:31,550 --> 00:23:39,330
+هنا معناته
+
+176
+00:23:39,330 --> 00:23:47,230
+ال KD او ال ال KD هيكون
+
+177
+00:23:47,230 --> 00:23:50,650
+الساوى ال average value اللي بقون تسعة تسعة خمسة
+
+178
+00:23:53,290 --> 00:24:16,330
+زائد point تسعة ستة تلاتة على اتنين بيطلع
+
+179
+00:24:16,330 --> 00:24:21,210
+point تسعة سبعة تسعة
+
+180
+00:24:23,720 --> 00:24:27,800
+ال reliability عندى تسعة وتسعين في المية هروح احسب
+
+181
+00:24:27,800 --> 00:24:34,120
+ال K E تسعة
+
+182
+00:24:34,120 --> 00:24:38,900
+وتسعين في المية تسعة
+
+183
+00:24:38,900 --> 00:24:43,220
+وتسعين في المية هتكون
+
+184
+00:24:43,220 --> 00:24:44,540
+ال K E
+
+185
+00:24:51,010 --> 00:24:57,490
+بساوة point تمانية واحد اربعة معناته
+
+186
+00:24:57,490 --> 00:25:03,510
+هنا انا هحسب ال SE K A انا already حسبتها اللي هي
+
+187
+00:25:03,510 --> 00:25:13,850
+point تمانية ستة تمانية في KB point تمانية سبعة
+
+188
+00:25:13,850 --> 00:25:25,050
+تسعة في KC point تمانية خمسةفي كد بون تسعة سبعة
+
+189
+00:25:25,050 --> 00:25:33,130
+تسعة في كي بون تمانية واحد اربع في خمسة وعشرين
+
+190
+00:26:07,180 --> 00:26:21,000
+تطلع اتناش بون تسعة اتنين اتناش المعنى
+
+191
+00:26:21,000 --> 00:26:29,700
+اول مطلوب حسبته لان
+
+192
+00:26:29,700 --> 00:26:35,100
+عشان اعيش الف cycle ال sf ال sf
+
+193
+00:26:43,210 --> 00:26:48,810
+الـ S F بالساوية
+
+194
+00:26:48,810 --> 00:27:03,230
+A نقص B الـ A بالساوية F S U T الكول تربيع على S A
+
+195
+00:27:03,230 --> 00:27:10,330
+الـ F هنحسبها الـ S U T عندي خمسين
+
+196
+00:27:31,120 --> 00:27:41,120
+بحد سبعين هنا عندي bond تسعة ال F هتكون تساوي bond
+
+197
+00:27:41,120 --> 00:27:49,740
+تسعة اللي هو figure ستة تمانتاش هتكون عند ال A ال
+
+198
+00:27:49,740 --> 00:27:56,740
+F اللي هي bond تسعة في ال SUT اللي هي خمسين كل
+
+199
+00:27:56,740 --> 00:28:08,560
+تربية على ال SE اللي هي اتناشبون تسعة اتنين هتكون
+
+200
+00:28:08,560 --> 00:28:17,280
+اللي بون تسعة في خمسين يساوي تربيع تقسيم اتناش بون
+
+201
+00:28:17,280 --> 00:28:26,420
+تسعة اتنين تطلع مية و ستة و خمسين بون سبعة مية
+
+202
+00:28:26,420 --> 00:28:28,020
+و ستة و خمسين
+
+203
+00:28:34,160 --> 00:28:45,160
+square inch ال B يكون سوى minus تلت log F sut على
+
+204
+00:28:45,160 --> 00:28:53,100
+S A يكون سوى minus تلت log F
+
+205
+00:28:53,100 --> 00:28:59,220
+الهي bond تسعة فSut خمسين على اتناش bond تسعة
+
+206
+00:28:59,220 --> 00:28:59,640
+اتنين
+
+207
+00:29:41,070 --> 00:29:49,610
+log بونت تسعة في خمسين تقسيم اتناش بونت تسعة اتنين
+
+208
+00:29:49,610 --> 00:29:59,850
+يساوي تقسيم تلاتة سالب بونت
+
+209
+00:29:59,850 --> 00:30:07,390
+واحد تمانية سفر ستة خمسة هذه ال P معناته
+
+210
+00:30:07,390 --> 00:30:08,130
+الأسقف
+
+211
+00:30:10,890 --> 00:30:15,030
+هتكون ال a احنا عسبناها مية و ستة و خمسين point
+
+212
+00:30:15,030 --> 00:30:21,410
+سبعة ال n سبعين الف اص
+
+213
+00:30:21,410 --> 00:30:27,750
+بي اص بي اللي هي minus point واحد تمانية سفر ستة
+
+214
+00:30:27,750 --> 00:30:37,470
+خمسة سبعين
+
+215
+00:30:37,470 --> 00:30:37,870
+الف
+
+216
+00:30:40,780 --> 00:30:48,980
+اس سالب zero point واحد تمانية سفر ستة خمسة يساوي
+
+217
+00:30:48,980 --> 00:30:57,360
+في مية وستة خمسين point سبعة هتكون عشرين point
+
+218
+00:30:57,360 --> 00:31:04,280
+تمانية تمانية تلت عشرين point تسعة kilo
+
+219
+00:31:04,280 --> 00:31:11,380
+pound per square inchيعني at stress amplitude of
+
+220
+00:31:11,380 --> 00:31:16,080
+20.9 kilo pound per square inch ال .. ال .. ال
+
+221
+00:31:16,080 --> 00:31:20,320
+part هيعيش لسبعين الف دورة سبعين الف cycle
+
+222
+00:31:52,410 --> 00:32:17,370
+نشوف مثال تالت نشوف
+
+223
+00:32:17,370 --> 00:32:24,090
+مثال تالتthe figure shows a rotating shaft عندى ال
+
+224
+00:32:24,090 --> 00:32:30,370
+figure مبين دى shaft عموض دوار simply supported in
+
+225
+00:32:30,370 --> 00:32:36,630
+ball bearings at a and d بيلي عند a و بيلي عند d
+
+226
+00:32:36,630 --> 00:32:41,730
+يعني هذه a وهذه
+
+227
+00:32:41,730 --> 00:32:47,310
+d at
+
+228
+00:32:47,310 --> 00:32:53,630
+a and dand loaded by a non-rotating force F قمة 6
+
+229
+00:32:53,630 --> 00:32:59,090
+.8 كيلونيوتن force F قمة
+
+230
+00:32:59,090 --> 00:33:08,450
+6.8 كيلونيوتن using
+
+231
+00:33:08,450 --> 00:33:14,030
+ASTM minimum
+
+232
+00:33:14,030 --> 00:33:18,780
+strengthestimate the life of the part احسب ال life
+
+233
+00:33:18,780 --> 00:33:34,300
+بتاعة ال part يعني انك تحسب ال an طب
+
+234
+00:33:34,300 --> 00:33:39,960
+هين المفروض يعطيني ال ال material بتاعة ال ال
+
+235
+00:33:39,960 --> 00:33:43,300
+shaft خنروح شوف ايش ال material بتاعة ال shaft
+
+236
+00:33:43,300 --> 00:33:47,410
+المفروض معطنيهافي ال example في الكتاب
+
+237
+00:34:21,890 --> 00:34:26,750
+اه هو مفترض ال material مفترض ان ال SUT عنده ستمية
+
+238
+00:34:26,750 --> 00:34:29,510
+وتسعين ميجا باسكال والاسواي خمسمية و تمانية ميجا
+
+239
+00:34:29,510 --> 00:34:34,610
+باسكال ال SUT هذا اللي هو المفروض يكون معطوه ال
+
+240
+00:34:34,610 --> 00:34:42,050
+SUT ستمية وتسعين ميجا باسكال وخمسمية و تمانية
+
+241
+00:34:42,050 --> 00:34:47,790
+ستمية وتسعين ميجا باسكال والاسواي
+
+242
+00:34:52,190 --> 00:34:57,710
+خمسمية و اتمانين ماجي بس كان في حال اتمثال زي هيك
+
+243
+00:34:57,710 --> 00:35:04,590
+اول شي لازم نعمل ما يسمى ال ..
+
+244
+00:35:04,590 --> 00:35:10,510
+نحسب ال reactions عند a و d بعدين نرسم ال shear
+
+245
+00:35:10,510 --> 00:35:16,630
+diagram و ال moment diagram بعدين specify ال
+
+246
+00:35:16,630 --> 00:35:22,050
+critical locationswhile taking care of stress
+
+247
+00:35:22,050 --> 00:35:25,690
+concentrations وهنا احنا هنبدأ في التسلسل اول شي
+
+248
+00:35:25,690 --> 00:35:29,150
+calculate reactions عشان to calculate reactions I
+
+249
+00:35:29,150 --> 00:35:33,650
+have to make a free body diagram بدي اعمل free
+
+250
+00:35:33,650 --> 00:35:39,650
+body diagram او عندي .. عندي هذه A وهذه
+
+251
+00:35:39,650 --> 00:35:48,150
+D عندي هذه 6.8 كيلو نيوتن ده أحس بال reactionsعندي
+
+252
+00:35:48,150 --> 00:35:51,150
+a و d ده احسب r واحد و r اتنين هاخد summation of
+
+253
+00:35:51,150 --> 00:35:59,510
+moment summation of moment عندي بالساوة سفر هعتبر
+
+254
+00:35:59,510 --> 00:36:08,610
+بعكس عقار الساعة موجب هكون ساوة هكون عندي هنا ستة
+
+255
+00:36:08,610 --> 00:36:11,590
+point تمانية في مية زائد مية و خمس و عشرين يعني
+
+256
+00:36:11,590 --> 00:36:13,330
+ميتين و خمس و عشرين ستة point تمانية
+
+257
+00:36:17,570 --> 00:36:22,550
+في متين و خمسة و عشرين ناقص عند ال R واحد في
+
+258
+00:36:22,550 --> 00:36:29,490
+المسافة هذه عند مية
+
+259
+00:36:29,490 --> 00:36:32,750
+زي مية و خمسة و عشرين متين و خمسة و عشرين زي خمسة
+
+260
+00:36:32,750 --> 00:36:41,470
+و سبعين تلت مية زي متين و خمسينكمان والله 125 225
+
+261
+00:36:41,470 --> 00:36:57,410
+300 زاد 250 550 ناقص 550 في R1 ومنها
+
+262
+00:36:57,410 --> 00:37:01,950
+بحسب ال R1 هتكون
+
+263
+00:37:03,790 --> 00:37:12,990
+6.8 في 225 تقسم تطلع
+
+264
+00:37:12,990 --> 00:37:21,150
+2.781 كيلو
+
+265
+00:37:21,150 --> 00:37:22,490
+نيوتن
+
+266
+00:37:25,300 --> 00:37:32,560
+هحكي summation لل FY بالساوية 0 هيكون الساوية R1
+
+267
+00:37:32,560 --> 00:37:42,260
+زائد R2 minus 6.8 ومنها بحسب ال R2 هتكون 6.8 minus
+
+268
+00:37:42,260 --> 00:37:44,200
+2.781
+
+269
+00:37:59,490 --> 00:38:08,490
+بتطلع اربع point او تسعتاش خلي
+
+270
+00:38:08,490 --> 00:38:12,030
+هذا بالنيوتن يعني هتكون الفين و سبعمية واحد تمانية
+
+271
+00:38:12,030 --> 00:38:19,650
+نيوتن هذا هتكون اربع تلاف و تسعتاش نيوتن حسبت R
+
+272
+00:38:19,650 --> 00:38:24,050
+واحد و R اتنين هعمل ال .. ال shear و ال moon
+
+273
+00:38:24,050 --> 00:38:25,570
+diagram ال shear diagram
+
+274
+00:38:46,520 --> 00:38:54,320
+الشير دياجرام انا
+
+275
+00:38:54,320 --> 00:39:06,800
+عند ال R1 اللي هي 2781 هكون شكل
+
+276
+00:39:06,800 --> 00:39:07,500
+الشير دياجرام
+
+277
+00:39:20,590 --> 00:39:28,770
+هذا الشير عندهين
+
+278
+00:39:28,770 --> 00:39:37,350
+ألفين و سبعة مية و واحد و تمانين وهين ناقص أربع
+
+279
+00:39:37,350 --> 00:39:45,690
+تلاف و تسعة عشر ال moment diagram هكون
+
+280
+00:39:45,690 --> 00:39:46,710
+جاي بالشكل هذا
+
+281
+00:39:55,490 --> 00:40:00,610
+عندي هذه هتكون
+
+282
+00:40:00,610 --> 00:40:03,370
+ال area هذه ال area اللي هي هتكون الفين هذه
+
+283
+00:40:03,370 --> 00:40:09,510
+المسافة بيتين و خمسين زيادة خمسين تلت مية و خمسة و
+
+284
+00:40:09,510 --> 00:40:11,030
+عشرين يعني هذه هتكون
+
+285
+00:40:18,710 --> 00:40:22,890
+ألف فى هنا سبعمية واحد تمانين فى تلت مية خمسة و
+
+286
+00:40:22,890 --> 00:40:30,390
+عشرين تقسيم الف تطلع
+
+287
+00:40:30,390 --> 00:40:34,850
+تسعمية و تلاتة point تسعمية و تلاتة point أو
+
+288
+00:40:34,850 --> 00:40:40,730
+تسعمية و أربعة نحكي تسعمية و أربعة نيوتن
+
+289
+00:40:40,730 --> 00:40:43,850
+متر هذا ال moment diagram
+
+290
+00:40:47,940 --> 00:40:52,900
+الـ moment diagram الآن
+
+291
+00:40:52,900 --> 00:41:04,300
+السؤال لحظة القطر هنا عندى القطر هنا 32 والقطر
+
+292
+00:41:04,300 --> 00:41:15,020
+هنا 38 والقطر هنا 35 الآن
+
+293
+00:41:15,020 --> 00:41:23,740
+في عندى نقطة Bو نقطة C لأن القطر صح ال moment هنا
+
+294
+00:41:23,740 --> 00:41:28,040
+maximum لكن عند النقطة هذه مافيش stress
+
+295
+00:41:28,040 --> 00:41:33,400
+concentration الآن معناته ال critical point هتكون
+
+296
+00:41:33,400 --> 00:41:40,440
+يا إما B يا إما C لأن في شغل تاني عند B القطر أصغر
+
+297
+00:41:40,440 --> 00:41:45,850
+من القطر C معناته من ناحية القطرهتكون B is more
+
+298
+00:41:45,850 --> 00:41:53,270
+critical than C بعدين عندك هنا B أقرب على ال load
+
+299
+00:41:53,270 --> 00:41:56,930
+معناته ال moment هنا هتكون أعلى عن B يعني أنت عند
+
+300
+00:41:56,930 --> 00:42:01,770
+B القطر أصغر و ال moment أعلى معناته ال critical
+
+301
+00:42:01,770 --> 00:42:10,630
+point هي نقطة B معناته أنا لازم أنزل هنا و
+
+302
+00:42:10,630 --> 00:42:19,610
+أحسب ال momentand B بمعنى بي بي
+
+303
+00:42:19,610 --> 00:42:27,930
+is the critical location at
+
+304
+00:42:27,930 --> 00:42:32,230
+B
+
+305
+00:42:32,230 --> 00:42:43,330
+و ال moment عن بي هتكون هعمل تشابه مثلثات هذه
+
+306
+00:42:43,330 --> 00:42:53,130
+م بيهذه المسافة كم؟ هذه متين و خمسين متين
+
+307
+00:42:53,130 --> 00:42:58,690
+و خمسين و هذه كلها تلت مية و خمسة و عشرين هذه كلها
+
+308
+00:42:58,690 --> 00:43:01,990
+تلت
+
+309
+00:43:01,990 --> 00:43:08,950
+مية و خمسة و عشرين معناته MB MB
+
+310
+00:43:13,480 --> 00:43:16,660
+على ال .. ال .. ال .. ال moment اللي هنا اللي هي
+
+311
+00:43:16,660 --> 00:43:23,460
+تسعة مية وأربعة من تشابه مثلثات بتساوي متين و
+
+312
+00:43:23,460 --> 00:43:30,240
+خمسين ع تلات مية و خمسة و عشرين منها بحسب ال Mb
+
+313
+00:43:46,950 --> 00:43:52,870
+وبتطلع ستمية و خمسة وتسعين نيوتن
+
+314
+00:43:52,870 --> 00:43:56,070
+متر ال Mb
+
+315
+00:44:06,200 --> 00:44:11,960
+ال .. طبعا انا هنا ه .. ه .. ه .. هحمل اللي هو ال
+
+316
+00:44:11,960 --> 00:44:15,480
+transfers shear stress لأن anyway .. anyway مش
+
+317
+00:44:15,480 --> 00:44:18,240
+هحمله anyway على المحيط ال transfers shear stress
+
+318
+00:44:18,240 --> 00:44:22,560
+بيكون ساوي سفر بيكون maximum في النص ال bend .. ال
+
+319
+00:44:22,560 --> 00:44:24,360
+stress .. ال normal stress due to bending بيكون
+
+320
+00:44:24,360 --> 00:44:28,500
+maximum على المحيط و سفر في النص معناته I will
+
+321
+00:44:28,500 --> 00:44:31,980
+consider only bending في الحال .. الحالة دي ال
+
+322
+00:44:31,980 --> 00:44:39,690
+sigmaعن بي ال normal stress sigma o هتكون السواء م
+
+323
+00:44:39,690 --> 00:44:49,790
+بي في C على I هتكون السواء م بي ال C عبارة عن دي
+
+324
+00:44:49,790 --> 00:44:59,450
+على اتنين وال I باي على اربعة و ستين دي اص اربعة
+
+325
+00:44:59,450 --> 00:45:08,820
+يعني هتكون السواء اتنين و تلاتينم بي على باي دي قص
+
+326
+00:45:08,820 --> 00:45:16,600
+تلاتة يعنى هتساوى اتنين و تلاتين ال م بي اللى هى
+
+327
+00:45:16,600 --> 00:45:25,440
+ستمية و خمسة و تسعين على باي ال دي اللى هتساوى
+
+328
+00:45:25,440 --> 00:45:28,840
+اتنين و تلاتين م بي اللى هتساوى اتنين و تلاتين في
+
+329
+00:45:28,840 --> 00:45:37,650
+بونتأو تلاتة اتنين الكل تكييب عشان احاوله لميجا
+
+330
+00:45:37,650 --> 00:45:47,490
+باسكال حضره في عشرة أسالب ستة هتكون نحسب اتنين و
+
+331
+00:45:47,490 --> 00:45:55,490
+تلاتين في ستمية و خمسة وتسعين تقسيم ال by
+
+332
+00:46:02,920 --> 00:46:07,900
+ع فكرة الالحس بتاعة ابني لسه انا مش متعود عليها
+
+333
+00:46:07,900 --> 00:46:13,420
+خليني تقسيم تلاتة point واحد اربعة تقسيم point O
+
+334
+00:46:13,420 --> 00:46:24,360
+تلاتة اتنين اص تلاتة يساوي اقل تقسيم مليون تقسيم
+
+335
+00:46:24,360 --> 00:46:29,040
+الف يساوي تطلع متين وستاش
+
+336
+00:46:32,950 --> 00:46:39,130
+ميجا باسكال ميجا باسكال ميجا باسكال ميجا باسكال
+
+337
+00:46:39,130 --> 00:46:40,790
+ميجا باسكال ميجا باسكال ميجا باسكال ميجا باسكال
+
+338
+00:46:40,790 --> 00:46:40,950
+ميجا باسكال ميجا باسكال ميجا باسكال ميجا باسكال
+
+339
+00:46:40,950 --> 00:46:50,790
+ميجا باسكال ميجا
+
+340
+00:46:50,790 --> 00:47:02,210
+باسكال ميجا باسكال ميجا باسكال
+
+341
+00:47:04,000 --> 00:47:10,040
+الـ KT هضطر
+
+342
+00:47:10,040 --> 00:47:21,300
+أستخدم ال appendix A A 15 9 هروح ل A 15 9 عشان
+
+343
+00:47:21,300 --> 00:47:26,040
+أحسب ال KT هنشوف ال appendix A 15 9
+
+344
+00:47:43,250 --> 00:47:56,570
+اللي هي دي الحالة طيب
+
+345
+00:47:56,570 --> 00:48:01,610
+عند
+
+346
+00:48:01,610 --> 00:48:08,910
+ال R على D بلزمني أحسب ال R على D بلزمني
+
+347
+00:48:08,910 --> 00:48:16,130
+أحسب ال R على Dالـ R تلاتة على اتنين و تلاتين او
+
+348
+00:48:16,130 --> 00:48:26,730
+احسب ال D capital على D تمانية و تلاتين على
+
+349
+00:48:26,730 --> 00:48:31,930
+اتنين و تلاتين تلاتة
+
+350
+00:48:31,930 --> 00:48:40,670
+تقسيم اتنين و تلاتين تطلع تقريبا point one وهذه
+
+351
+00:48:40,670 --> 00:48:41,490
+تمانية و تلاتين
+
+352
+00:48:46,680 --> 00:48:54,020
+بتطلع واحد point واحد تمانية سبعة خمسة انا عند هنا
+
+353
+00:48:54,020 --> 00:49:01,160
+point واحد بجاء
+
+354
+00:49:01,160 --> 00:49:08,800
+بين التانية التانية و التالت تقرع واحد point ستة
+
+355
+00:49:08,800 --> 00:49:11,800
+واحد point ستة خمسة ال KT
+
+356
+00:49:16,060 --> 00:49:43,280
+1.65 حسبت
+
+357
+00:49:43,280 --> 00:49:58,210
+الكتاب يطلع 1.6خمسة بدي احسب ال .. KF So واحد زاد
+
+358
+00:49:58,210 --> 00:50:05,670
+كيو في KT minus واحد ال KT قرري حسبتها ال كيو هروح
+
+359
+00:50:05,670 --> 00:50:13,410
+على شكل ستة عشرين هنروح في figure ستة عشرين هنشوف
+
+360
+00:50:13,410 --> 00:50:14,510
+figure ستة عشرين
+
+361
+00:50:20,810 --> 00:50:34,930
+عند ال SUT عند ال R تلاتة ملي التلت
+
+362
+00:50:34,930 --> 00:50:46,370
+يعني تقريبا bond two bond two على تلاتة زائد
+
+363
+00:50:46,370 --> 00:50:47,510
+bond تمانية
+
+364
+00:50:51,320 --> 00:50:57,640
+بتطلع تقريبا بون تمانية ستة كيو
+
+365
+00:50:57,640 --> 00:51:00,660
+بس
+
+366
+00:51:00,660 --> 00:51:06,700
+هو بون تمانية ستة خمسة ومنها بحسب الكي أف هتكون
+
+367
+00:51:06,700 --> 00:51:12,520
+واحد زائد بون تمانية ستة خمسة في واحد بون ستة خمسة
+
+368
+00:51:12,520 --> 00:51:13,420
+ناقص واحد
+
+369
+00:51:25,900 --> 00:51:32,000
+واحد point خمسة ستة اتنين واحد point خمسة ستة
+
+370
+00:51:32,000 --> 00:51:38,000
+اتنين معناته ال maximum stress عند ال critical
+
+371
+00:51:38,000 --> 00:51:45,400
+point ال sigma هتكون KF في ال sigma O
+
+372
+00:51:50,420 --> 00:51:56,720
+اللي هي واحد point خمسة ستة اتنين في sigma o اللي
+
+373
+00:51:56,720 --> 00:52:09,200
+هي متين وستاش تطلع
+
+374
+00:52:09,200 --> 00:52:15,620
+تلتمية و سبعة و تلتين ميجا
+
+375
+00:52:15,620 --> 00:52:17,660
+بسكال
+
+376
+00:52:45,730 --> 00:52:52,410
+طيب لأن هحسب ال S A' بسوا
+
+377
+00:52:52,410 --> 00:53:01,970
+نص ال S U T هتسوا نص ال S U T اللي هي ستمية وتسعين
+
+378
+00:53:01,970 --> 00:53:06,670
+ميجا يعني هكون تلاتة
+
+379
+00:53:09,780 --> 00:53:22,480
+تلاتمية و خمسة و اربعين ميجا باسكال طب
+
+380
+00:53:22,480 --> 00:53:29,280
+محتاج اعملها correction لل .. correction لل SE
+
+381
+00:53:29,280 --> 00:53:30,100
+prime
+
+382
+00:53:37,910 --> 00:53:52,510
+بدي أحسب ال K A ال K A so A S U T بص B طبعا هذا it
+
+383
+00:53:52,510 --> 00:53:57,210
+is machined أكيد الشفت هذا مش معمله hot rolling
+
+384
+00:53:57,210 --> 00:53:58,390
+أكيد machined
+
+385
+00:54:06,470 --> 00:54:14,230
+الـ K A مازالوا ماشيين هتكون ال
+
+386
+00:54:14,230 --> 00:54:21,530
+.. ال .. ال K بتاعته ال A أربعة point أربعة point
+
+387
+00:54:21,530 --> 00:54:28,730
+خمسة واحد أربعة ال A هتكون أربعة point خمسة واحد
+
+388
+00:54:28,730 --> 00:54:33,870
+في ال SC2 ستمية وتسعين أص B دي minus point
+
+389
+00:54:36,820 --> 00:54:43,300
+اتنين ستة خمسة ال K.A عندى
+
+390
+00:54:43,300 --> 00:54:51,840
+ستمية وتسعين اقصى minus point اتنين ستة خمسة في
+
+391
+00:54:51,840 --> 00:54:57,900
+اربع point خمسة واحد هيطلع point سبعة تسعة تمانية
+
+392
+00:54:57,900 --> 00:55:01,940
+point سبعة تسعة
+
+393
+00:55:01,940 --> 00:55:05,320
+تمانية هذا ال K.A هذا اللى هى ال surface finish
+
+394
+00:55:05,320 --> 00:55:18,080
+factorال كيبي الكيبي الكيبي هتكون اللي هو ال size
+
+395
+00:55:18,080 --> 00:55:23,640
+factor كيبي بتساوي
+
+396
+00:55:23,640 --> 00:55:28,380
+واحد point اتنين four في
+
+397
+00:55:28,380 --> 00:55:32,620
+دي قصة minus point واحد زير و سبعة يعني واحد point
+
+398
+00:55:32,620 --> 00:55:40,510
+اتنين اربعة القطر عندىاتنين و تلاتين اص minus
+
+399
+00:55:40,510 --> 00:55:46,430
+point واحد سفر سبعة اتنين
+
+400
+00:55:46,430 --> 00:55:55,150
+و تلاتين اص minus zero point واحد سفر سبعة يساوي
+
+401
+00:55:55,150 --> 00:56:01,670
+في واحد point اتنين اربعة تطلع point خمس تمانية
+
+402
+00:56:01,670 --> 00:56:04,790
+خمسة
+
+403
+00:56:04,790 --> 00:56:05,530
+ستة
+
+404
+00:56:22,120 --> 00:56:30,960
+.856 ال loading factor bending معناه كسي بتساوي
+
+405
+00:56:30,960 --> 00:56:38,230
+واحد فش ال temperature effectو مافيش هنا معلومات
+
+406
+00:56:38,230 --> 00:56:43,070
+عن ريابلتي معناته بيساوي ال KD ال KD بيساوي واحد
+
+407
+00:56:43,070 --> 00:56:52,270
+وال KE بيساوي واحد معناته ال SE هتساوي
+
+408
+00:56:52,270 --> 00:57:01,770
+KA اللي هي point 7 تسعة تمانية ال KB اللي هي واحد
+
+409
+00:57:01,770 --> 00:57:10,070
+point تمانية خمسة ستةفي SE Prime اللي هي تلت مية و
+
+410
+00:57:10,070 --> 00:57:16,990
+خمسة و أربعين ميجا يعني
+
+411
+00:57:16,990 --> 00:57:23,530
+عندي بونت سبعة تسعة تمانية في بونت تمانية خمسة ستة
+
+412
+00:57:23,530 --> 00:57:28,970
+في تلت مية و خمسة و أربعين بتطلع متين و خمسة و
+
+413
+00:57:28,970 --> 00:57:33,010
+تلتين ميجا باسكال
+
+414
+00:57:59,930 --> 00:58:07,330
+لنحسب ال life ال life لل .. طبعاً لل SE اللي هي
+
+415
+00:58:07,330 --> 00:58:15,850
+ميتين و خمس تلاتين ميجا باسكال و ال sigma ..
+
+416
+00:58:15,850 --> 00:58:20,190
+لاحظوا ال sigma .. ال sigma .. لاحظوا ال sigma
+
+417
+00:58:20,190 --> 00:58:27,270
+بتاعتي تلت مية و سبعة و تلتين أكبر من ال SE و أصغر
+
+418
+00:58:27,270 --> 00:58:36,940
+من ال SY ال sigmaالـ Sigma أكبر من ال SE و أصغر من
+
+419
+00:58:36,940 --> 00:58:41,500
+ال SY معناته ما زال أكبر من ال .. من ال .. من ال
+
+420
+00:58:41,500 --> 00:58:47,340
+SE معناته finite life و أصغر ال SY معناته مش هصير
+
+421
+00:58:47,340 --> 00:58:50,700
+يعني على الأغلب مش هصير yielding يعني معناته هتكون
+
+422
+00:58:50,700 --> 00:58:56,240
+هذه finite life problem finite life
+
+423
+00:58:56,240 --> 00:58:57,000
+problem
+
+424
+00:59:02,520 --> 00:59:08,020
+الان ما زال finite life problem بدي أحسب ال number
+
+425
+00:59:08,020 --> 00:59:12,000
+of cycles من المعادلة السابقة مرت علينا خلينا نرجع
+
+426
+00:59:12,000 --> 00:59:19,940
+أرجع لورا أيوة
+
+427
+00:59:19,940 --> 00:59:22,060
+اللي هي n بالساوية
+
+428
+00:59:29,990 --> 00:59:35,710
+بالساوية sigma reversible على
+
+429
+00:59:35,710 --> 00:59:43,530
+a أس واحد على بيه
+
+430
+00:59:43,530 --> 00:59:46,970
+طيب نرجع لمسألتنا
+
+431
+00:59:56,940 --> 01:00:03,240
+الان ال A ال A ال
+
+432
+01:00:03,240 --> 01:00:14,720
+A بالسواء F S U T هنكتبها هنا أحسن ال A بالسواء
+
+433
+01:00:14,720 --> 01:00:21,120
+F S U T الكل تربية على ال S E
+
+434
+01:00:28,140 --> 01:00:32,820
+معناته مطلوب ان نحسب ال F مطلوب نحسب ال F ال F
+
+435
+01:00:32,820 --> 01:00:50,220
+هتكون من شكل عند
+
+436
+01:00:50,220 --> 01:00:54,260
+ان ال SUT 690 ميجاباسكال يعني في ال kilo Pascal
+
+437
+01:00:54,260 --> 01:01:05,630
+هقسم علىست مية وتسعين تقسيم ستة point تمانية بتطلع
+
+438
+01:01:05,630 --> 01:01:10,090
+يعني حوالي مية واحد كيلو بسكال يعني حوالي مية كيلو
+
+439
+01:01:10,090 --> 01:01:19,890
+بسكال يعني ان احكي هنا هنا هنا يعني
+
+440
+01:01:19,890 --> 01:01:27,280
+تقريبابونت تمانية اربعة خمسة ال F بالساوية بونت
+
+441
+01:01:27,280 --> 01:01:33,880
+تمانية اربعة خمسة من شكل ستة تمانتاش شكل ستة
+
+442
+01:01:33,880 --> 01:01:39,960
+تمانتاش معناته ال A هتكون تساوية بونت تمانية اربعة
+
+443
+01:01:39,960 --> 01:01:45,480
+خمسة في ال SUT اللي هي ستمائية وتسعين على ال SE
+
+444
+01:01:45,480 --> 01:01:49,840
+اللي هي متين وخمس وتلاتين هتكون تساوية
+
+445
+01:01:53,310 --> 01:01:58,950
+بونت تمانية اربعة خمسة في ستمية وتسعين تقسيم اتنين
+
+446
+01:01:58,950 --> 01:02:08,170
+وخمسة تلاتين تطلع اتنين بونت اربعة تمانية
+
+447
+01:02:08,170 --> 01:02:12,450
+واحد وال B
+
+448
+01:02:15,260 --> 01:02:25,340
+الـ B بالساوية minus تلت log ال F S U T على ال S A
+
+449
+01:02:25,340 --> 01:02:33,820
+يعني هتكون ساوية minus تلت log log ال F عندي اللي
+
+450
+01:02:33,820 --> 01:02:42,000
+هي bond تمانيةاربع خمسة في ستمية وتسعين على متين
+
+451
+01:02:42,000 --> 01:02:49,520
+وخمسة وتلاتين هتكون تساوي log اللي هي bond تمانية
+
+452
+01:02:49,520 --> 01:02:54,700
+اربعة خمسة في ستمية وتسعين تقسيم اتين وخمسة
+
+453
+01:02:54,700 --> 01:03:04,950
+وتلاتين يساوي تقسيم تلاتة هتكون minusبونت واحد
+
+454
+01:03:04,950 --> 01:03:24,770
+تلاتة واحد خمسة طيب
+
+455
+01:03:24,770 --> 01:03:31,170
+معناته
+
+456
+01:03:31,170 --> 01:03:31,630
+الأن
+
+457
+01:03:35,590 --> 01:03:43,330
+الان بساوية sigma reversible على a أسواحد على b
+
+458
+01:03:43,330 --> 01:03:48,390
+سيكون sigma reversible اللي احنا حسبناها اللي هي
+
+459
+01:03:48,390 --> 01:03:51,790
+تلت مية و سبعة و تلتين تلت مية و سبعة و تلتين
+
+460
+01:03:54,250 --> 01:04:00,570
+اندي اتنين point اربعة تمانية واحد اص واحد على
+
+461
+01:04:00,570 --> 01:04:11,090
+minus point واحد تلاتة واحد خمسة نحسبها تلاتمية
+
+462
+01:04:11,090 --> 01:04:15,670
+و سبعة و تلاتين تقسيم
+
+463
+01:04:15,670 --> 01:04:22,050
+اتنين point اربعة تمانية واحد يساوي اص
+
+464
+01:04:27,020 --> 01:04:35,940
+واحد تقسيم minus zero point واحد تلاتة واحد خمسة
+
+465
+01:04:35,940 --> 01:04:41,540
+ايه الساعة؟ مافيه
+
+466
+01:04:41,540 --> 01:04:45,660
+ايش غلط على فكرة عند هنا اه ال a هنا غلط هذا هو
+
+467
+01:04:45,660 --> 01:04:50,040
+التربيع طبعا عرفت ان انا غلط طلع عندى الرقم اشي
+
+468
+01:04:50,040 --> 01:04:53,240
+عشر او اصلاق السبعتاش الرقم مش منطقي بيعني انه فيه
+
+469
+01:04:53,240 --> 01:04:58,340
+غلطلازم يكون عندك حس في الأرقام مانوية هاد ال a
+
+470
+01:04:58,340 --> 01:05:02,360
+غلط عندي هيكون ال a خلنا نحسبها point تمانية أربعة
+
+471
+01:05:02,360 --> 01:05:10,820
+خمسة في ستمية وتسعين يساوي تربيع يساوي تقسيم اتنين
+
+472
+01:05:10,820 --> 01:05:17,780
+وخمسة و تلاتين بتطلع ألف و أربعمية و سبعة و أربعين
+
+473
+01:05:17,780 --> 01:05:21,020
+هاد
+
+474
+01:05:21,020 --> 01:05:23,380
+ال a عشان هيك الأشياء هيختلف
+
+475
+01:05:26,270 --> 01:05:33,770
+ألف أربعمية أُص سبعة وأربعين نحسب تلاتة السبعة
+
+476
+01:05:33,770 --> 01:05:42,590
+تقسيم واحد أربعة أربعة سبعة يساوي أُص واحد تقسيم
+
+477
+01:05:42,590 --> 01:05:50,690
+سالب zero point واحد تلاتة وواحد خمسة يساوى تطلع
+
+478
+01:05:50,690 --> 01:05:57,890
+حوالي أربعة وستين ألفتسعمية و اتنين و تلاتين cycle
+
+479
+01:05:57,890 --> 01:06:03,570
+معناته ال part هذا هيصمد هيعيش حوالي خمسة و ستين
+
+480
+01:06:03,570 --> 01:06:08,550
+الف cycle ل ال loading الموجود اللي هو عنده في
+
+481
+01:06:08,550 --> 01:06:17,750
+النص 6.8 كيلونيوتر نكتفي اليوم بكرا بن .. بنخش على
+
+482
+01:06:17,750 --> 01:06:23,510
+موضوع جديد في ال fatigue designبتفصيل أكتر يعني
+
+483
+01:06:23,510 --> 01:06:27,910
+هكون شغل أكتر من الشغل اللي سوناه لحتى اللحظة
+
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BohkPcY7GQQ_raw.json b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BohkPcY7GQQ_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..1331a095c201f3f5f7d79bb7c659cd74c1f833ff
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BohkPcY7GQQ_raw.json
@@ -0,0 +1 @@
+{"segments": [{"id": 1, "seek": 3199, "start": 5.15, "end": 31.99, "text": "السلام عليكم المرة اللي فاتت حكينا عن كيفية حساب ال fatigue stress concentration factor حكينا كف بساوي كف بساوي واحد زاد كيو في كت ماينوس واحد الكت ال geometric stress concentration factor الكيو ال notch sensitivity factor الكيو حكيها بنحسب من شكل ستة عشرين وشكل ستة واحد عشرين", "tokens": [6027, 3794, 37440, 25894, 24793, 9673, 25720, 13672, 1829, 6156, 9307, 2655, 11331, 4117, 1829, 8315, 18871, 9122, 33911, 10632, 11331, 3794, 16758, 2423, 20574, 4244, 9856, 5952, 11331, 4117, 1829, 8315, 9122, 5172, 4724, 3794, 995, 45865, 9122, 5172, 4724, 3794, 995, 45865, 36764, 24401, 30767, 18513, 9122, 1829, 2407, 8978, 9122, 2655, 19446, 9957, 41779, 36764, 24401, 33251, 2655, 2423, 33246, 4244, 9856, 5952, 33251, 1829, 2407, 2423, 26109, 19392, 5952, 33251, 1829, 2407, 11331, 4117, 1829, 11296, 44945, 5016, 35457, 9154, 13412, 28820, 8608, 2655, 3660, 6225, 46309, 9957, 4032, 8592, 28820, 8608, 2655, 3660, 36764, 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241.53, "word": " تمانين", "probability": 0.9332682291666666}], "temperature": 1.0}, {"id": 10, "seek": 27158, "start": 243.84, "end": 271.58, "text": "ميجا بسكال consider the shaft undergoing a fully reversed nominal stress sigma reversible nominal هسميها او بس هو متين وستين ميجا بسكال estimate the number of cycles due failure", "tokens": [2304, 1829, 7435, 995, 4724, 3794, 4117, 6027, 1949, 264, 18467, 40033, 257, 4498, 30563, 41641, 4244, 12771, 44788, 41641, 8032, 38251, 1829, 11296, 1975, 2407, 4724, 3794, 31439, 44650, 9957, 4032, 14851, 9957, 3714, 1829, 7435, 995, 4724, 3794, 4117, 6027, 12539, 264, 1230, 295, 17796, 3462, 7763], "avg_logprob": -0.28859375476837157, "compression_ratio": 1.411764705882353, "no_speech_prob": 0.0, "words": [{"start": 243.84, "end": 245.12, "word": "ميجا", "probability": 0.702423095703125}, {"start": 245.12, "end": 246.4, "word": " بسكال", "probability": 0.8426513671875}, {"start": 246.4, "end": 249.22, "word": " consider", "probability": 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"word": " due", "probability": 0.6103515625}, {"start": 270.76, "end": 271.58, "word": " failure", "probability": 0.8427734375}], "temperature": 1.0}, {"id": 11, "seek": 29781, "start": 275.33, "end": 297.81, "text": "الان هذا النمو ال stress without stress without stress concentration اذا فاكرين من example السابق انا حسبت ال KF بالساوية احنا حسبنا ال ال KF", "tokens": [6027, 7649, 23758, 28239, 2304, 2407, 2423, 4244, 1553, 4244, 1553, 4244, 9856, 1975, 15730, 6156, 995, 37983, 9957, 9154, 1365, 21136, 16758, 4587, 1975, 8315, 11331, 35457, 2655, 2423, 591, 37, 20666, 3794, 995, 2407, 10632, 1975, 5016, 8315, 11331, 35457, 8315, 2423, 2423, 591, 37], "avg_logprob": -0.20003254556407532, "compression_ratio": 1.463768115942029, "no_speech_prob": 0.0, "words": [{"start": 275.33, "end": 275.65, "word": "الان", "probability": 0.5635986328125}, {"start": 275.65, "end": 275.91, "word": " هذا", "probability": 0.73095703125}, {"start": 275.91, "end": 276.23, "word": " النمو", "probability": 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تأكدوا من القيمة هذه افرض هنا KF يساوي bond ستة خمسة معناته ال sigma هتكون KF في sigma reversible nominal يعني هيكون", "tokens": [10721, 19913, 1863, 16472, 36764, 24401, 6086, 8608, 2655, 3660, 16490, 2304, 3794, 3660, 34105, 3714, 9566, 1211, 37746, 16472, 24793, 6055, 2655, 10721, 4117, 3215, 14407, 6055, 10721, 4117, 3215, 14407, 1975, 47341, 3615, 14407, 24976, 41185, 16254, 2407, 6055, 10721, 4117, 3215, 14407, 9154, 25062, 32640, 3660, 29538, 1975, 5172, 43042, 34105, 591, 37, 7251, 3794, 995, 45865, 6086, 8608, 2655, 3660, 16490, 2304, 3794, 3660, 20449, 8315, 47395, 2423, 12771, 8032, 2655, 30544, 591, 37, 8978, 12771, 44788, 41641, 37495, 22653, 8032, 1829, 30544], "avg_logprob": -0.2444957381283695, "compression_ratio": 1.6358695652173914, "no_speech_prob": 0.0, "words": [{"start": 302.16, "end": 302.6, "word": "أظن", "probability": 0.72509765625}, {"start": 302.6, "end": 302.74, "word": " ان", "probability": 0.284423828125}, {"start": 302.74, "end": 303.1, "word": " واحد", 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{"start": 316.7, "end": 320.14, "word": " هتكون", "probability": 0.8187662760416666}, {"start": 320.14, "end": 321.26, "word": " KF", "probability": 0.913818359375}, {"start": 321.26, "end": 325.3, "word": " في", "probability": 0.76123046875}, {"start": 325.3, "end": 325.96, "word": " sigma", "probability": 0.8505859375}, {"start": 325.96, "end": 326.64, "word": " reversible", "probability": 0.97314453125}, {"start": 326.64, "end": 327.9, "word": " nominal", "probability": 0.96728515625}, {"start": 327.9, "end": 328.6, "word": " يعني", "probability": 0.901611328125}, {"start": 328.6, "end": 329.04, "word": " هيكون", "probability": 0.8072916666666666}], "temperature": 1.0}, {"id": 13, "seek": 35792, "start": 330.26, "end": 357.92, "text": "1.65×260 تطلع 429 ميجا باسكال ال SUT كان معطنيها في ال exam ال سابق ال SUT", "tokens": [16, 13, 16824, 37550, 17, 4550, 6055, 9566, 1211, 3615, 1017, 11871, 3714, 1829, 7435, 995, 4724, 32277, 4117, 6027, 2423, 318, 8709, 25961, 20449, 9566, 22653, 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"probability": 0.9326171875}, {"start": 955.2, "end": 955.86, "word": " strength", "probability": 0.92578125}, {"start": 955.86, "end": 956.46, "word": " at", "probability": 0.77978515625}, {"start": 956.46, "end": 956.66, "word": " يعني", "probability": 0.72314453125}, {"start": 956.66, "end": 956.94, "word": " بدنا", "probability": 0.68603515625}, {"start": 956.94, "end": 957.22, "word": " نحسب", "probability": 0.9913736979166666}, {"start": 957.22, "end": 957.38, "word": " ال", "probability": 0.84130859375}, {"start": 957.38, "end": 957.8, "word": " SE", "probability": 0.5458984375}], "temperature": 1.0}, {"id": 32, "seek": 98068, "start": 961.1, "end": 980.68, "text": "و ال SF SFN أول شي مثال زي هيك بدي أطلع الخواص الميكانيكية للمعدن هذا هروح على الجدول هروح على جدول A20 في شجلة هروح على جدول A20", "tokens": [2407, 2423, 31095, 31095, 45, 5551, 12610, 44049, 50113, 6027, 30767, 1829, 39896, 4117, 4724, 16254, 5551, 9566, 1211, 3615, 33962, 14407, 9381, 9673, 1829, 41361, 1829, 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975.18, "end": 975.46, "word": " جدول", "probability": 0.94482421875}, {"start": 975.46, "end": 976.26, "word": " A20", "probability": 0.892822265625}, {"start": 976.26, "end": 977.02, "word": " في", "probability": 0.939453125}, {"start": 977.02, "end": 977.46, "word": " شجلة", "probability": 0.9290364583333334}, {"start": 977.46, "end": 979.58, "word": " هروح", "probability": 0.9544270833333334}, {"start": 979.58, "end": 979.7, "word": " على", "probability": 0.92724609375}, {"start": 979.7, "end": 979.96, "word": " جدول", "probability": 0.9817708333333334}, {"start": 979.96, "end": 980.68, "word": " A20", "probability": 0.991943359375}], "temperature": 1.0}, {"id": 33, "seek": 101944, "start": 992.74, "end": 1019.44, "text": "هذا ايه عشرين ايه عشرين دي hot rolled steel الف و خمس عشر اللي هو هذا هذا الف و خمس عشر hot rolled معطينة هذه ال tensile strength هذه ال yield strength ال .. ال tensile strength", "tokens": [3224, 15730, 1975, 1829, 3224, 6225, 46309, 9957, 1975, 1829, 3224, 6225, 46309, 9957, 11778, 1829, 2368, 14306, 8269, 27188, 4032, 16490, 2304, 3794, 6225, 46309, 13672, 1829, 31439, 23758, 23758, 27188, 4032, 16490, 2304, 3794, 6225, 46309, 2368, 14306, 20449, 9566, 9957, 3660, 29538, 2423, 10688, 794, 3800, 29538, 2423, 11257, 3800, 2423, 4386, 2423, 10688, 794, 3800], "avg_logprob": -0.3007812480131785, "compression_ratio": 1.838235294117647, "no_speech_prob": 0.0, "words": [{"start": 992.74, "end": 993.08, "word": "هذا", "probability": 0.76416015625}, {"start": 993.08, "end": 993.26, "word": " ايه", "probability": 0.6365559895833334}, {"start": 993.26, "end": 993.76, "word": " عشرين", "probability": 0.8697916666666666}, {"start": 993.76, "end": 996.5, "word": " ايه", "probability": 0.7296549479166666}, {"start": 996.5, "end": 996.78, "word": " عشرين", "probability": 0.8972981770833334}, {"start": 996.78, "end": 996.98, "word": " دي", "probability": 0.78759765625}, {"start": 996.98, "end": 997.28, "word": " hot", "probability": 0.8564453125}, {"start": 997.28, "end": 997.7, "word": " rolled", "probability": 0.861328125}, {"start": 997.7, "end": 998.14, "word": " steel", "probability": 0.2081298828125}, {"start": 998.14, "end": 998.46, "word": " الف", "probability": 0.66845703125}, {"start": 998.46, "end": 998.58, "word": " و", "probability": 0.9921875}, {"start": 998.58, "end": 998.82, "word": " خمس", "probability": 0.8772786458333334}, {"start": 998.82, "end": 999.14, "word": " عشر", "probability": 0.3109130859375}, {"start": 999.14, "end": 1000.34, "word": " اللي", "probability": 0.938720703125}, {"start": 1000.34, "end": 1000.46, "word": " هو", "probability": 0.978515625}, {"start": 1000.46, "end": 1000.84, "word": " هذا", "probability": 0.82861328125}, {"start": 1000.84, "end": 1002.84, "word": " هذا", "probability": 0.455078125}, {"start": 1002.84, "end": 1003.42, "word": " الف", "probability": 0.94287109375}, {"start": 1003.42, "end": 1003.66, "word": " و", "probability": 0.9990234375}, {"start": 1003.66, "end": 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1014.14, "word": " strength", "probability": 0.9541015625}, {"start": 1014.14, "end": 1015.96, "word": " ال", "probability": 0.923828125}, {"start": 1015.96, "end": 1016.52, "word": " ..", "probability": 0.38720703125}, {"start": 1016.52, "end": 1018.16, "word": " ال", "probability": 0.87060546875}, {"start": 1018.16, "end": 1018.8, "word": " tensile", "probability": 0.963134765625}, {"start": 1018.8, "end": 1019.44, "word": " strength", "probability": 0.94921875}], "temperature": 1.0}, {"id": 34, "seek": 104739, "start": 1021.27, "end": 1047.39, "text": "الو خمسين كيلو pound per square inch ال SUT خمسين كيلو pound per square inch خليني أكبرها شوية هاي ها", "tokens": [6027, 2407, 16490, 2304, 3794, 9957, 9122, 26895, 2407, 12013, 680, 3732, 7227, 2423, 318, 8709, 16490, 2304, 3794, 9957, 9122, 26895, 2407, 12013, 680, 3732, 7227, 16490, 1211, 9957, 1829, 5551, 4117, 26890, 11296, 13412, 2407, 10632, 8032, 47302, 8032, 995], "avg_logprob": -0.19821947743726331, "compression_ratio": 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1032.27, "word": " pound", "probability": 0.97900390625}, {"start": 1032.27, "end": 1033.25, "word": " per", "probability": 0.953125}, {"start": 1033.25, "end": 1033.63, "word": " square", "probability": 0.890625}, {"start": 1033.63, "end": 1034.15, "word": " inch", "probability": 0.97216796875}, {"start": 1034.15, "end": 1036.81, "word": " خليني", "probability": 0.74322509765625}, {"start": 1036.81, "end": 1037.39, "word": " أكبرها", "probability": 0.9290771484375}, {"start": 1037.39, "end": 1041.41, "word": " شوية", "probability": 0.9420572916666666}, {"start": 1041.41, "end": 1047.19, "word": " هاي", "probability": 0.55615234375}, {"start": 1047.19, "end": 1047.39, "word": " ها", "probability": 0.82373046875}], "temperature": 1.0}, {"id": 35, "seek": 106390, "start": 1050.28, "end": 1063.9, "text": "وهذا ال yield strength والأسواق له مستوى سبعة وعشر و نص كيلو pound per square inch", "tokens": [2407, 3224, 15730, 2423, 11257, 3800, 16070, 10721, 3794, 14407, 4587, 46740, 3714, 14851, 2407, 7578, 8608, 3555, 27884, 4032, 3615, 46309, 4032, 8717, 9381, 9122, 26895, 2407, 12013, 680, 3732, 7227], "avg_logprob": -0.3385416666666667, "compression_ratio": 1.063063063063063, "no_speech_prob": 0.0, "words": [{"start": 1050.28, "end": 1050.7, "word": "وهذا", "probability": 0.7374674479166666}, {"start": 1050.7, "end": 1050.86, "word": " ال", "probability": 0.26220703125}, {"start": 1050.86, "end": 1050.98, "word": " yield", "probability": 0.61181640625}, {"start": 1050.98, "end": 1051.56, "word": " strength", "probability": 0.9599609375}, {"start": 1051.56, "end": 1053.58, "word": " والأسواق", "probability": 0.717626953125}, {"start": 1053.58, "end": 1053.96, "word": " له", "probability": 0.52294921875}, {"start": 1053.96, "end": 1058.7, "word": " مستوى", "probability": 0.63311767578125}, {"start": 1058.7, "end": 1059.24, "word": " سبعة", "probability": 0.8600260416666666}, {"start": 1059.24, "end": 1059.44, "word": " وعشر", "probability": 0.72412109375}, {"start": 1059.44, "end": 1059.6, "word": " و", "probability": 0.84765625}, {"start": 1059.6, "end": 1059.94, "word": " نص", "probability": 0.769287109375}, {"start": 1059.94, "end": 1062.4, "word": " كيلو", "probability": 0.7562662760416666}, {"start": 1062.4, "end": 1062.76, "word": " pound", "probability": 0.89306640625}, {"start": 1062.76, "end": 1063.16, "word": " per", "probability": 0.96484375}, {"start": 1063.16, "end": 1063.52, "word": " square", "probability": 0.91064453125}, {"start": 1063.52, "end": 1063.9, "word": " inch", "probability": 0.9833984375}], "temperature": 1.0}, {"id": 36, "seek": 110732, "start": 1085.76, "end": 1107.32, "text": "طيب هذا ال table A20 أول شي هحسب ال S A prime اللي هي ال S A prime هتكون نص ال S U T", "tokens": [9566, 1829, 3555, 23758, 2423, 3199, 316, 2009, 5551, 12610, 44049, 8032, 5016, 35457, 2423, 318, 316, 5835, 13672, 1829, 39896, 2423, 318, 316, 5835, 8032, 2655, 30544, 8717, 9381, 2423, 318, 624, 314], "avg_logprob": -0.2631696513720921, "compression_ratio": 1.263157894736842, "no_speech_prob": 0.0, "words": [{"start": 1085.76, "end": 1086.48, "word": "طيب", "probability": 0.97265625}, {"start": 1086.48, "end": 1087.2, "word": " هذا", "probability": 0.611328125}, {"start": 1087.2, "end": 1087.66, "word": " ال", "probability": 0.84619140625}, {"start": 1087.66, "end": 1088.08, "word": " table", "probability": 0.56982421875}, {"start": 1088.08, "end": 1092.1, "word": " A20", "probability": 0.607421875}, {"start": 1092.1, "end": 1098.14, "word": " أول", "probability": 0.887939453125}, {"start": 1098.14, "end": 1098.22, "word": " شي", "probability": 0.34912109375}, {"start": 1098.22, "end": 1098.5, "word": " هحسب", "probability": 0.7234700520833334}, {"start": 1098.5, "end": 1098.66, "word": " ال", "probability": 0.8134765625}, {"start": 1098.66, "end": 1098.86, "word": " S", "probability": 0.72509765625}, {"start": 1098.86, "end": 1099.02, "word": " A", "probability": 0.88427734375}, {"start": 1099.02, "end": 1099.38, "word": " prime", "probability": 0.31396484375}, {"start": 1099.38, "end": 1102.3, "word": " اللي", "probability": 0.8251953125}, {"start": 1102.3, "end": 1102.58, "word": " هي", "probability": 0.83056640625}, {"start": 1102.58, "end": 1102.78, "word": " ال", "probability": 0.7666015625}, {"start": 1102.78, "end": 1103.42, "word": " S", "probability": 0.8349609375}, {"start": 1103.42, "end": 1103.6, "word": " A", "probability": 0.87255859375}, {"start": 1103.6, "end": 1103.96, "word": " prime", "probability": 0.8828125}, {"start": 1103.96, "end": 1104.38, "word": " هتكون", "probability": 0.935546875}, {"start": 1104.38, "end": 1104.88, "word": " نص", "probability": 0.99072265625}, {"start": 1104.88, "end": 1106.58, "word": " ال", "probability": 0.919921875}, {"start": 1106.58, "end": 1106.84, "word": " S", "probability": 0.9013671875}, {"start": 1106.84, "end": 1107.06, "word": " U", "probability": 0.8017578125}, {"start": 1107.06, "end": 1107.32, "word": " T", "probability": 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تساوى point تمانية خمسة لأن هو under point تمانية خمسة completely reversed axial loading", "tokens": [6027, 7649, 31439, 11331, 4117, 6027, 1829, 309, 307, 833, 2423, 591, 34, 8032, 2655, 30544, 6055, 3794, 995, 2407, 7578, 935, 46811, 7649, 10632, 16490, 2304, 3794, 3660, 5296, 33456, 31439, 833, 935, 46811, 7649, 10632, 16490, 2304, 3794, 3660, 2584, 30563, 46851, 15114], "avg_logprob": -0.2885529787644096, "compression_ratio": 1.3384615384615384, "no_speech_prob": 0.0, "words": [{"start": 1373.76, "end": 1374.32, "word": "الان", "probability": 0.74951171875}, {"start": 1374.32, "end": 1375.32, "word": " هو", "probability": 0.47998046875}, {"start": 1375.32, "end": 1375.84, "word": " حكالي", "probability": 0.848388671875}, {"start": 1375.84, "end": 1376.28, "word": " it", "probability": 0.80029296875}, {"start": 1376.28, "end": 1376.56, "word": " is", "probability": 0.912109375}, {"start": 1376.56, "end": 1377.06, "word": " under", "probability": 0.89453125}, {"start": 1377.06, 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"no_speech_prob": 5.960464477539063e-08, "words": [{"start": 3954.59, "end": 3955.35, "word": "تسعمية", "probability": 0.750732421875}, {"start": 3955.35, "end": 3955.57, "word": " و", "probability": 0.8583984375}, {"start": 3955.57, "end": 3956.03, "word": " اتنين", "probability": 0.885498046875}, {"start": 3956.03, "end": 3956.23, "word": " و", "probability": 0.78466796875}, {"start": 3956.23, "end": 3956.97, "word": " تلاتين", "probability": 0.94384765625}, {"start": 3956.97, "end": 3957.89, "word": " cycle", "probability": 0.476806640625}, {"start": 3957.89, "end": 3958.33, "word": " معناته", "probability": 0.8562825520833334}, {"start": 3958.33, "end": 3958.49, "word": " ال", "probability": 0.92431640625}, {"start": 3958.49, "end": 3958.83, "word": " part", "probability": 0.9619140625}, {"start": 3958.83, "end": 3959.19, "word": " هذا", "probability": 0.75634765625}, {"start": 3959.19, "end": 3960.59, "word": " هيصمد", "probability": 0.880126953125}, {"start": 3960.59, "end": 3961.31, "word": " هيعيش", "probability": 0.923095703125}, {"start": 3961.31, "end": 3962.39, "word": " حوالي", "probability": 0.9610595703125}, {"start": 3962.39, "end": 3962.85, "word": " خمسة", "probability": 0.980224609375}, {"start": 3962.85, "end": 3962.95, "word": " و", "probability": 0.69677734375}, {"start": 3962.95, "end": 3963.57, "word": " ستين", "probability": 0.9339192708333334}, {"start": 3963.57, "end": 3964.11, "word": " الف", "probability": 0.73095703125}, {"start": 3964.11, "end": 3965.43, "word": " cycle", "probability": 0.8994140625}, {"start": 3965.43, "end": 3966.45, "word": " ل", "probability": 0.78759765625}, {"start": 3966.45, "end": 3966.75, "word": " ال", "probability": 0.74755859375}, {"start": 3966.75, "end": 3967.13, "word": " loading", "probability": 0.95458984375}, {"start": 3967.13, "end": 3967.75, "word": " الموجود", "probability": 0.9363606770833334}, {"start": 3967.75, "end": 3967.91, "word": " اللي", "probability": 0.91796875}, {"start": 3967.91, "end": 3968.09, "word": " هو", "probability": 0.97021484375}, {"start": 3968.09, "end": 3968.43, "word": " عنده", "probability": 0.61083984375}, {"start": 3968.43, "end": 3968.55, "word": " في", "probability": 0.93701171875}, {"start": 3968.55, "end": 3968.87, "word": " النص", "probability": 0.7174072265625}, {"start": 3968.87, "end": 3969.35, "word": " 6", "probability": 0.265625}, {"start": 3969.35, "end": 3970.89, "word": ".8", "probability": 0.9609375}, {"start": 3970.89, "end": 3972.41, "word": " كيلونيوتر", "probability": 0.8250325520833334}, {"start": 3972.41, "end": 3973.67, "word": " نكتفي", "probability": 0.888916015625}, {"start": 3973.67, "end": 3974.47, "word": " اليوم", "probability": 0.980712890625}, {"start": 3974.47, "end": 3976.01, "word": " بكرا", "probability": 0.8356119791666666}, {"start": 3976.01, "end": 3976.31, "word": " بن", "probability": 0.90234375}, {"start": 3976.31, "end": 3976.49, "word": " ..", "probability": 0.4853515625}, {"start": 3976.49, "end": 3977.57, "word": " بنخش", "probability": 0.9661458333333334}, {"start": 3977.57, "end": 3977.75, "word": " على", "probability": 0.86083984375}, {"start": 3977.75, "end": 3978.27, "word": " موضوع", "probability": 0.9962158203125}, {"start": 3978.27, "end": 3979.11, "word": " جديد", "probability": 0.9900716145833334}, {"start": 3979.11, "end": 3979.31, "word": " في", "probability": 0.966796875}, {"start": 3979.31, "end": 3979.53, "word": " ال", "probability": 0.89111328125}, {"start": 3979.53, "end": 3980.07, "word": " fatigue", "probability": 0.9833984375}, {"start": 3980.07, "end": 3980.79, "word": " design", "probability": 0.96875}], "temperature": 1.0}, {"id": 129, "seek": 398791, "start": 3981.97, "end": 3987.91, "text": "بتفصيل أكتر يعني هكون شغل أكتر من الشغل اللي سوناه لحتى اللحظة", "tokens": [3555, 2655, 5172, 9381, 26895, 5551, 4117, 2655, 2288, 37495, 22653, 8032, 30544, 13412, 17082, 1211, 5551, 4117, 2655, 2288, 9154, 25124, 17082, 1211, 13672, 1829, 8608, 2407, 8315, 3224, 5296, 33753, 7578, 13672, 5016, 19913, 3660], "avg_logprob": -0.17485608513417997, "compression_ratio": 1.3294117647058823, "no_speech_prob": 0.00021338462829589844, "words": [{"start": 3981.97, "end": 3982.73, "word": "بتفصيل", "probability": 0.96259765625}, {"start": 3982.73, "end": 3983.39, "word": " أكتر", "probability": 0.89697265625}, {"start": 3983.39, "end": 3983.51, "word": " يعني", "probability": 0.724853515625}, {"start": 3983.51, "end": 3983.87, "word": " هكون", "probability": 0.82861328125}, {"start": 3983.87, "end": 3984.55, "word": " شغل", "probability": 0.8938802083333334}, {"start": 3984.55, "end": 3984.93, "word": " أكتر", "probability": 0.96240234375}, {"start": 3984.93, "end": 3985.13, "word": " من", "probability": 0.99267578125}, {"start": 3985.13, "end": 3986.45, "word": " الشغل", "probability": 0.9246419270833334}, {"start": 3986.45, "end": 3986.55, "word": " اللي", "probability": 0.87158203125}, {"start": 3986.55, "end": 3986.89, "word": " سوناه", "probability": 0.69964599609375}, {"start": 3986.89, "end": 3987.27, "word": " لحتى", "probability": 0.8372395833333334}, {"start": 3987.27, "end": 3987.91, "word": " اللحظة", "probability": 0.9937744140625}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 3988.97925, "duration_after_vad": 3194.8999999999833}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BohkPcY7GQQ_raw.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BohkPcY7GQQ_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..847804d4124491cafd2028e184643aa1ca400ada
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/BohkPcY7GQQ_raw.srt
@@ -0,0 +1,1944 @@
+1
+00:00:05,150 --> 00:00:11,390
+السلام عليكم المرة اللي فاتت حكينا عن كيفية حساب
+
+2
+00:00:11,390 --> 00:00:14,430
+ال fatigue stress concentration factor حكينا كف
+
+3
+00:00:14,430 --> 00:00:23,770
+بساوي كف بساوي واحد زاد كيو في كت ماينوس واحد الكت
+
+4
+00:00:23,770 --> 00:00:26,470
+ال geometric stress concentration factor الكيو ال
+
+5
+00:00:26,470 --> 00:00:29,870
+notch sensitivity factor الكيو حكيها بنحسب من شكل
+
+6
+00:00:29,870 --> 00:00:34,080
+ستة عشرين وشكل ستة واحد عشرينو ال kit هي من
+
+7
+00:00:34,080 --> 00:00:39,020
+appendix A9 بتحسب طبيعة ال loading و حسب طبيعة ال
+
+8
+00:00:39,020 --> 00:00:43,020
+geometry لل mechanical part الآن السؤال اليوم how
+
+9
+00:00:43,020 --> 00:00:47,980
+to apply fatigue stress concentration factor الان
+
+10
+00:00:47,980 --> 00:00:51,920
+use KF as a multiplier to increase nominal stress
+
+11
+00:00:51,920 --> 00:00:58,410
+يعني انا حسب nominal stress sigma مثلا ميةوالـ KF
+
+12
+00:00:58,410 --> 00:01:03,470
+حسبته طالع عندي مثلا واحد point تمانية هحكس ..
+
+13
+00:01:03,470 --> 00:01:09,970
+هضرب KF في Sigma O هيكون واحد point تمانية في مية
+
+14
+00:01:09,970 --> 00:01:16,390
+هيكون عندي مية و تمانين بعض
+
+15
+00:01:16,390 --> 00:01:22,530
+المصممين بتقالله endurance strength بيقسملي SE او
+
+16
+00:01:22,530 --> 00:01:26,790
+or بيحكيلي SE على
+
+17
+00:01:28,610 --> 00:01:34,110
+كيف ياما ياما بترفع ال stress level أو بتنزل ال
+
+18
+00:01:34,110 --> 00:01:38,130
+endurance limit يعني ممكن تستخدمه as a multiplier
+
+19
+00:01:38,130 --> 00:01:43,090
+or as a reduction في الحالة دي for infinite life
+
+20
+00:01:43,090 --> 00:01:47,790
+for infinite life ال NF بالساوية SE في كيف على
+
+21
+00:01:47,790 --> 00:01:51,700
+سيجماال KF في sigma عبارة عن multiplier انا برفع
+
+22
+00:01:51,700 --> 00:01:55,680
+ال stress او بحكي واحدة ل KF في SE Reducer ان الكف
+
+23
+00:01:55,680 --> 00:02:02,600
+استخدمت عشان اقلل ال endurance limit هذا في حالة
+
+24
+00:02:02,600 --> 00:02:07,480
+infinite life for finite lifeحالة finite life
+
+25
+00:02:07,480 --> 00:02:11,680
+increasing stress is more conservative أنه أرفع ال
+
+26
+00:02:11,680 --> 00:02:17,160
+stress بيعطيني نتائج محافظة أكتر يعني يعني أنصر
+
+27
+00:02:17,160 --> 00:02:21,160
+المخاطرة في الحسابة بتاعتي بيكون أقل decreasing SF
+
+28
+00:02:21,160 --> 00:02:27,420
+applies more to high cycle than low cycle fatigue
+
+29
+00:02:27,420 --> 00:02:29,660
+نشوف example
+
+30
+00:02:37,220 --> 00:02:40,960
+for the step shaft of example ستة ستة احنا كانت في
+
+31
+00:02:40,960 --> 00:02:45,580
+ال exam ستة ستة عندي step shaft
+
+32
+00:02:45,580 --> 00:03:03,440
+هذه
+
+33
+00:03:03,440 --> 00:03:23,500
+كانتع فكرة هي كراسة مغلط ها
+
+34
+00:03:23,500 --> 00:03:29,380
+step shaft ال exhaust ستكانها دي اتنين و تلاتين
+
+35
+00:03:29,380 --> 00:03:41,730
+ميلي وهذا ديR تلاتة الفيلت وهذه تمانية وتلاتين it
+
+36
+00:03:41,730 --> 00:03:46,290
+is
+
+37
+00:03:46,290 --> 00:03:48,750
+it is determined that the fully corrected
+
+38
+00:03:48,750 --> 00:03:54,330
+endurance limit ال SE fully corrected يعني انا ا
+
+39
+00:03:54,330 --> 00:03:58,590
+take care of ال modification factors K A K B K C K
+
+40
+00:03:58,590 --> 00:04:09,220
+D E K A K F بالساعتين و تمانينميجا بسكال consider
+
+41
+00:04:09,220 --> 00:04:13,680
+the shaft undergoing a fully reversed nominal
+
+42
+00:04:13,680 --> 00:04:21,460
+stress sigma reversible nominal هسميها او بس هو
+
+43
+00:04:21,460 --> 00:04:29,780
+متين وستين ميجا بسكال estimate the number of
+
+44
+00:04:29,780 --> 00:04:31,580
+cycles due failure
+
+45
+00:04:35,330 --> 00:04:39,790
+الان هذا النمو ال stress without stress without
+
+46
+00:04:39,790 --> 00:04:45,050
+stress concentration اذا فاكرين من example السابق
+
+47
+00:04:45,050 --> 00:04:50,850
+انا حسبت ال KF بالساوية
+
+48
+00:04:50,850 --> 00:04:57,810
+احنا حسبنا ال ال KF
+
+49
+00:05:02,160 --> 00:05:08,280
+أظن ان واحد bond ستة خمسة هنا مطلوب انكم تتأكدوا
+
+50
+00:05:08,280 --> 00:05:12,900
+تأكدوا ارجعوا للفيديو تأكدوا من القيمة هذه افرض
+
+51
+00:05:12,900 --> 00:05:20,140
+هنا KF يساوي bond ستة خمسة معناته ال sigma هتكون
+
+52
+00:05:20,140 --> 00:05:25,300
+KF في
+
+53
+00:05:25,300 --> 00:05:45,880
+sigma reversible nominal يعني هيكون1.65×260 تطلع
+
+54
+00:05:45,880 --> 00:05:51,180
+429 ميجا
+
+55
+00:05:51,180 --> 00:05:57,380
+باسكال ال SUT كان معطنيها في ال exam ال سابق ال
+
+56
+00:05:57,380 --> 00:05:57,920
+SUT
+
+57
+00:06:04,160 --> 00:06:12,080
+كان معطينا ال STD 690 ميجا بسكال 690 ميجا بسكال
+
+58
+00:06:12,080 --> 00:06:19,340
+لاحظوا
+
+59
+00:06:19,340 --> 00:06:26,160
+ال sigma reversible أكبر
+
+60
+00:06:26,160 --> 00:06:31,520
+من ال endurance limit وأصغر من ال tensile strength
+
+61
+00:06:33,340 --> 00:06:37,740
+ما زالها أكبر من ال SE
+
+62
+00:06:37,740 --> 00:06:47,000
+معناته we have infinite life sigma reversible أكبر
+
+63
+00:06:47,000 --> 00:06:56,920
+من ال SE و أصغر من ال SUT معناته we have finite
+
+64
+00:06:56,920 --> 00:07:00,440
+life
+
+65
+00:07:05,100 --> 00:07:10,480
+ما زال finite life هنستخدم المعادلات اللي هو في
+
+66
+00:07:10,480 --> 00:07:17,580
+المحاضرة السابقة اللي هي finite
+
+67
+00:07:17,580 --> 00:07:18,140
+life
+
+68
+00:07:40,650 --> 00:07:45,090
+أه اللي هي المعادلة الهادئة المعادلة 613 SF نحسب
+
+69
+00:07:45,090 --> 00:07:51,510
+SF بالثوابة
+
+70
+00:07:51,510 --> 00:07:58,970
+A فى N أقصى B و
+
+71
+00:07:58,970 --> 00:08:11,420
+A بسوء F S U T الكل تربية على S Aو ال B بيستوى
+
+72
+00:08:11,420 --> 00:08:25,480
+ناقص تلت log اللي هو F S U T على S A الان واضح ان
+
+73
+00:08:25,480 --> 00:08:32,940
+انا محتاج ال F ال F من هنا بحسبها من
+
+74
+00:08:32,940 --> 00:08:39,700
+figure ستة تمانتاش figure ستة تمانتاش
+
+75
+00:08:44,300 --> 00:08:54,160
+ال ستمية وتسعين ميجا باسكال حوالي ميت كيلو باسكال
+
+76
+00:08:54,160 --> 00:08:59,380
+ستمية وتسعين كيلو هدف بال English unit بتساوي ميت
+
+77
+00:08:59,380 --> 00:09:07,540
+كيلو pound per square inch عند مية عشان احسب ال F
+
+78
+00:09:07,540 --> 00:09:10,940
+من figure ستة تمانتاش هاي المية
+
+79
+00:09:27,940 --> 00:09:41,920
+ال F يعني
+
+80
+00:09:41,920 --> 00:09:49,600
+ممكن أحكي بون تمانية أربعة خمسة تطلع ال F بصابون
+
+81
+00:09:49,600 --> 00:09:51,700
+تمانية أربعة
+
+82
+00:09:53,610 --> 00:10:00,930
+خمسة من figure ستة تمانتاش و أنا بتبقى نحسب ال a
+
+83
+00:10:00,930 --> 00:10:08,930
+هنا حسه bond تمانية أربعة خمسة في ستمية وتسعين
+
+84
+00:10:08,930 --> 00:10:20,510
+الكل تربيع على SE SE اللي هي متين و تمانينوانا
+
+85
+00:10:20,510 --> 00:10:30,450
+بحسب ال A ال B هتكون سوى ناقص تلت log اللي هو ال F
+
+86
+00:10:30,450 --> 00:10:36,690
+اللي هي upon تمانية أربعة خمسة في ستمية وتسعين على
+
+87
+00:10:36,690 --> 00:10:38,530
+الاسم يومتين و تمانين
+
+88
+00:11:00,600 --> 00:11:09,580
+تطلع ألف و متين و أربعة و اتاش وال
+
+89
+00:11:09,580 --> 00:11:23,160
+B point
+
+90
+00:11:23,160 --> 00:11:24,740
+تمانية أربعة و خمسة
+
+91
+00:11:44,610 --> 00:11:50,570
+تقسم تلاتة تطلع minus minus
+
+92
+00:11:50,570 --> 00:11:54,670
+point
+
+93
+00:11:54,670 --> 00:12:00,030
+واحد زيرو ستة اتنين
+
+94
+00:12:15,440 --> 00:12:27,180
+الان الان الان هتساوي sigma reversible على a سواحد
+
+95
+00:12:27,180 --> 00:12:31,520
+على بي يعني هيتساوي sigma reversible يعني حسبناها
+
+96
+00:12:31,520 --> 00:12:34,360
+بعد after applying اللي هو ال stress fatigue
+
+97
+00:12:34,360 --> 00:12:39,080
+stress concentration factor أربعمية و تسعة و عشرين
+
+98
+00:12:39,080 --> 00:12:48,990
+على ال a اللي هي الف و متين و أربعتاشرأس واحد على
+
+99
+00:12:48,990 --> 00:12:58,690
+سالب point واحد ستة اتنين اربعمائة
+
+100
+00:12:58,690 --> 00:13:07,430
+وتسعة وعشرين تقسيم ألف ومتين واربعتاش ساوي أس
+
+101
+00:13:11,030 --> 00:13:19,870
+واحد على سالب point one zero six اتنين
+
+102
+00:13:19,870 --> 00:13:27,690
+تطلع سبعتاشر الف تسعمية
+
+103
+00:13:27,690 --> 00:13:33,190
+و اتنين و اربعين cycle يعني ال shaft هذا هيلف
+
+104
+00:13:33,190 --> 00:13:37,450
+سبعتاشر الف تسعمية و اتنين و اربعين لفة و بعدين
+
+105
+00:13:37,450 --> 00:13:38,050
+هيصير ال failure
+
+106
+00:13:59,550 --> 00:14:05,230
+طيب هيك احنا حسبنا النبر of cycles to failure نشوف
+
+107
+00:14:05,230 --> 00:14:26,890
+مثال تاني مثال 68 طيب
+
+108
+00:14:29,720 --> 00:14:33,060
+a ten fifteen hot rolled steel ال material بتاعت
+
+109
+00:14:33,060 --> 00:14:40,240
+ال bar ال material بتاعته عشرة خمستاش
+
+110
+00:14:40,240 --> 00:14:50,160
+hot rolled steel حديد نفس الكربون في point واحد
+
+111
+00:14:50,160 --> 00:14:55,180
+خمسة ومسحوب على الساخن has been machined to a
+
+112
+00:14:55,180 --> 00:15:05,360
+meter of one inch القطر بتاع ال shaftوحد انش it
+
+113
+00:15:05,360 --> 00:15:09,520
+is to be placed in a reversed axial loading for
+
+114
+00:15:09,520 --> 00:15:13,200
+seventy thousand cycles الان number of cycles
+
+115
+00:15:13,200 --> 00:15:16,260
+سبعين
+
+116
+00:15:16,260 --> 00:15:20,880
+الف to
+
+117
+00:15:20,880 --> 00:15:25,160
+failure in an operating environment of خمس بيه و
+
+118
+00:15:25,160 --> 00:15:30,600
+خمسين Fahrenheit درجة الحرارةخمسمية و خمسين
+
+119
+00:15:30,600 --> 00:15:37,540
+degrees Fahrenheit using
+
+120
+00:15:37,540 --> 00:15:42,160
+ASTM minimum properties and a reliability of
+
+121
+00:15:42,160 --> 00:15:46,960
+ninety-nine percent ال R&D تسعة وتسعين في المية
+
+122
+00:15:46,960 --> 00:15:50,640
+estimate
+
+123
+00:15:50,640 --> 00:15:56,660
+the endurance limit and fatigue strength at يعني
+
+124
+00:15:56,660 --> 00:15:57,800
+بدنا نحسب ال SE
+
+125
+00:16:01,100 --> 00:16:04,980
+و ال SF SFN
+
+126
+00:16:04,980 --> 00:16:09,000
+أول
+
+127
+00:16:09,000 --> 00:16:13,360
+شي مثال زي هيك بدي أطلع الخواص الميكانيكية للمعدن
+
+128
+00:16:13,360 --> 00:16:19,580
+هذا هروح على الجدول هروح على جدول A20 في شجلة هروح
+
+129
+00:16:19,580 --> 00:16:20,680
+على جدول A20
+
+130
+00:16:32,740 --> 00:16:38,580
+هذا ايه عشرين ايه عشرين دي hot rolled steel الف و
+
+131
+00:16:38,580 --> 00:16:46,580
+خمس عشر اللي هو هذا هذا الف و خمس عشر hot rolled
+
+132
+00:16:46,580 --> 00:16:52,320
+معطينة هذه ال tensile strength هذه ال yield
+
+133
+00:16:52,320 --> 00:17:03,050
+strength ال .. ال tensile strengthالو خمسين كيلو
+
+134
+00:17:03,050 --> 00:17:10,970
+pound per square inch ال SUT خمسين
+
+135
+00:17:10,970 --> 00:17:21,410
+كيلو pound per square inch خليني أكبرها شوية
+
+136
+00:17:21,410 --> 00:17:27,190
+هاي
+
+137
+00:17:27,190 --> 00:17:27,390
+ها
+
+138
+00:17:30,280 --> 00:17:38,700
+وهذا ال yield strength والأسواق له مستوى
+
+139
+00:17:38,700 --> 00:17:43,900
+سبعة وعشر و نص كيلو pound per square inch
+
+140
+00:18:05,760 --> 00:18:12,100
+طيب هذا ال table A20
+
+141
+00:18:12,100 --> 00:18:18,140
+أول
+
+142
+00:18:18,140 --> 00:18:24,880
+شي هحسب ال S A prime اللي هي ال S A prime هتكون نص
+
+143
+00:18:24,880 --> 00:18:27,320
+ال S U T
+
+144
+00:18:30,610 --> 00:18:37,970
+في خمسين سواء خمسة وعشرين kilo pound per square
+
+145
+00:18:37,970 --> 00:18:44,930
+inch ال SE هتكون
+
+146
+00:18:44,930 --> 00:18:57,270
+KA KB KC KD KE KF في ال SE primeالـ SE Prime
+
+147
+00:18:57,270 --> 00:18:59,870
+already حصلت لـ 25% الـ KA اللي هو الـ service
+
+148
+00:18:59,870 --> 00:19:00,930
+finish factor
+
+149
+00:19:30,450 --> 00:19:38,730
+الـ K A بالسواء
+
+150
+00:19:38,730 --> 00:19:45,550
+A في S U T AUS B انا
+
+151
+00:19:45,550 --> 00:19:49,610
+عندي hot rolled هاي hot rolled و الوحدات اللي هي
+
+152
+00:19:49,610 --> 00:19:54,630
+انجلزية معناته هتكون عنديا ال A
+
+153
+00:20:01,390 --> 00:20:12,490
+بتساوى أربع تاش point أربع وال
+
+154
+00:20:12,490 --> 00:20:23,810
+بي minus point سبعة واحد تمانية minus على
+
+155
+00:20:23,810 --> 00:20:33,470
+table ستة اتنين هدولتابل ستة اتنين معناته يعني ال
+
+156
+00:20:33,470 --> 00:20:38,650
+K A هيكون ال A اللي هي أربع تاش point أربعة في ال
+
+157
+00:20:38,650 --> 00:20:44,950
+SUT خمسين أس minus point سبعة واحد تمانية
+
+158
+00:21:17,190 --> 00:21:26,490
+فى بيطلع بون تمانية ستة تمانية بون تمانية ستة
+
+159
+00:21:26,490 --> 00:21:35,130
+تمانية ال KB ال
+
+160
+00:21:35,130 --> 00:21:41,130
+size factor ال KB هكون
+
+161
+00:21:41,130 --> 00:21:41,670
+ساوى
+
+162
+00:21:45,670 --> 00:21:54,150
+بون تمانية سبعة تسعة في دي
+
+163
+00:21:54,150 --> 00:22:01,290
+اص minus point one zero seven هيساوي بون تمانية
+
+164
+00:22:01,290 --> 00:22:06,790
+سبعة تسعة في دي اللي هي واحد اص minus point one
+
+165
+00:22:06,790 --> 00:22:07,570
+zero seven
+
+166
+00:22:15,180 --> 00:22:31,540
+واحد أس واحد
+
+167
+00:22:31,540 --> 00:22:40,820
+يعني هاتكون point تمانية سبعة تسعة هاد
+
+168
+00:22:40,820 --> 00:22:41,320
+الكابي
+
+169
+00:22:53,760 --> 00:23:02,980
+الان هو حكالي it is under ال KC هتكون
+
+170
+00:23:02,980 --> 00:23:05,860
+تساوى point تمانية خمسة لأن هو under point تمانية
+
+171
+00:23:05,860 --> 00:23:14,500
+خمسة completely reversed
+
+172
+00:23:14,500 --> 00:23:18,000
+axial loading
+
+173
+00:23:22,090 --> 00:23:26,170
+لأن بالنسبة ل KD اللي هي ال factor بتاع الحرارة
+
+174
+00:23:26,170 --> 00:23:31,550
+الحرارة عندي خمسمية و خمسين فهرام height يعني هكون
+
+175
+00:23:31,550 --> 00:23:39,330
+هنا معناته
+
+176
+00:23:39,330 --> 00:23:47,230
+ال KD او ال ال KD هيكون
+
+177
+00:23:47,230 --> 00:23:50,650
+الساوى ال average value اللي بقون تسعة تسعة خمسة
+
+178
+00:23:53,290 --> 00:24:16,330
+زائد point تسعة ستة تلاتة على اتنين بيطلع
+
+179
+00:24:16,330 --> 00:24:21,210
+point تسعة سبعة تسعة
+
+180
+00:24:23,720 --> 00:24:27,800
+ال reliability عندى تسعة وتسعين في المية هروح احسب
+
+181
+00:24:27,800 --> 00:24:34,120
+ال K E تسعة
+
+182
+00:24:34,120 --> 00:24:38,900
+وتسعين في المية تسعة
+
+183
+00:24:38,900 --> 00:24:43,220
+وتسعين في المية هتكون
+
+184
+00:24:43,220 --> 00:24:44,540
+ال K E
+
+185
+00:24:51,010 --> 00:24:57,490
+بساوة point تمانية واحد اربعة معناته
+
+186
+00:24:57,490 --> 00:25:03,510
+هنا انا هحسب ال SE K A انا already حسبتها اللي هي
+
+187
+00:25:03,510 --> 00:25:13,850
+point تمانية ستة تمانية في KB point تمانية سبعة
+
+188
+00:25:13,850 --> 00:25:25,050
+تسعة في KC point تمانية خمسةفي كد بون تسعة سبعة
+
+189
+00:25:25,050 --> 00:25:33,130
+تسعة في كي بون تمانية واحد اربع في خمسة وعشرين
+
+190
+00:26:07,180 --> 00:26:21,000
+تطلع اتناش بون تسعة اتنين اتناش المعنى
+
+191
+00:26:21,000 --> 00:26:29,700
+اول مطلوب حسبته لان
+
+192
+00:26:29,700 --> 00:26:35,100
+عشان اعيش الف cycle ال sf ال sf
+
+193
+00:26:43,210 --> 00:26:48,810
+الـ S F بالساوية
+
+194
+00:26:48,810 --> 00:27:03,230
+A نقص B الـ A بالساوية F S U T الكول تربيع على S A
+
+195
+00:27:03,230 --> 00:27:10,330
+الـ F هنحسبها الـ S U T عندي خمسين
+
+196
+00:27:31,120 --> 00:27:41,120
+بحد سبعين هنا عندي bond تسعة ال F هتكون تساوي bond
+
+197
+00:27:41,120 --> 00:27:49,740
+تسعة اللي هو figure ستة تمانتاش هتكون عند ال A ال
+
+198
+00:27:49,740 --> 00:27:56,740
+F اللي هي bond تسعة في ال SUT اللي هي خمسين كل
+
+199
+00:27:56,740 --> 00:28:08,560
+تربية على ال SE اللي هي اتناشبون تسعة اتنين هتكون
+
+200
+00:28:08,560 --> 00:28:17,280
+اللي بون تسعة في خمسين يساوي تربيع تقسيم اتناش بون
+
+201
+00:28:17,280 --> 00:28:26,420
+تسعة اتنين تطلع مية و ستة و خمسين بون سبعة مية
+
+202
+00:28:26,420 --> 00:28:28,020
+و ستة و خمسين
+
+203
+00:28:34,160 --> 00:28:45,160
+square inch ال B يكون سوى minus تلت log F sut على
+
+204
+00:28:45,160 --> 00:28:53,100
+S A يكون سوى minus تلت log F
+
+205
+00:28:53,100 --> 00:28:59,220
+الهي bond تسعة فSut خمسين على اتناش bond تسعة
+
+206
+00:28:59,220 --> 00:28:59,640
+اتنين
+
+207
+00:29:41,070 --> 00:29:49,610
+log بونت تسعة في خمسين تقسيم اتناش بونت تسعة اتنين
+
+208
+00:29:49,610 --> 00:29:59,850
+يساوي تقسيم تلاتة سالب بونت
+
+209
+00:29:59,850 --> 00:30:07,390
+واحد تمانية سفر ستة خمسة هذه ال P معناته
+
+210
+00:30:07,390 --> 00:30:08,130
+الأسقف
+
+211
+00:30:10,890 --> 00:30:15,030
+هتكون ال a احنا عسبناها مية و ستة و خمسين point
+
+212
+00:30:15,030 --> 00:30:21,410
+سبعة ال n سبعين الف اص
+
+213
+00:30:21,410 --> 00:30:27,750
+بي اص بي اللي هي minus point واحد تمانية سفر ستة
+
+214
+00:30:27,750 --> 00:30:37,470
+خمسة سبعين
+
+215
+00:30:37,470 --> 00:30:37,870
+الف
+
+216
+00:30:40,780 --> 00:30:48,980
+اس سالب zero point واحد تمانية سفر ستة خمسة يساوي
+
+217
+00:30:48,980 --> 00:30:57,360
+في مية وستة خمسين point سبعة هتكون عشرين point
+
+218
+00:30:57,360 --> 00:31:04,280
+تمانية تمانية تلت عشرين point تسعة kilo
+
+219
+00:31:04,280 --> 00:31:11,380
+pound per square inchيعني at stress amplitude of
+
+220
+00:31:11,380 --> 00:31:16,080
+20.9 kilo pound per square inch ال .. ال .. ال
+
+221
+00:31:16,080 --> 00:31:20,320
+part هيعيش لسبعين الف دورة سبعين الف cycle
+
+222
+00:31:52,410 --> 00:32:17,370
+نشوف مثال تالت نشوف
+
+223
+00:32:17,370 --> 00:32:24,090
+مثال تالتthe figure shows a rotating shaft عندى ال
+
+224
+00:32:24,090 --> 00:32:30,370
+figure مبين دى shaft عموض دوار simply supported in
+
+225
+00:32:30,370 --> 00:32:36,630
+ball bearings at a and d بيلي عند a و بيلي عند d
+
+226
+00:32:36,630 --> 00:32:41,730
+يعني هذه a وهذه
+
+227
+00:32:41,730 --> 00:32:47,310
+d at
+
+228
+00:32:47,310 --> 00:32:53,630
+a and dand loaded by a non-rotating force F قمة 6
+
+229
+00:32:53,630 --> 00:32:59,090
+.8 كيلونيوتن force F قمة
+
+230
+00:32:59,090 --> 00:33:08,450
+6.8 كيلونيوتن using
+
+231
+00:33:08,450 --> 00:33:14,030
+ASTM minimum
+
+232
+00:33:14,030 --> 00:33:18,780
+strengthestimate the life of the part احسب ال life
+
+233
+00:33:18,780 --> 00:33:34,300
+بتاعة ال part يعني انك تحسب ال an طب
+
+234
+00:33:34,300 --> 00:33:39,960
+هين المفروض يعطيني ال ال material بتاعة ال ال
+
+235
+00:33:39,960 --> 00:33:43,300
+shaft خنروح شوف ايش ال material بتاعة ال shaft
+
+236
+00:33:43,300 --> 00:33:47,410
+المفروض معطنيهافي ال example في الكتاب
+
+237
+00:34:21,890 --> 00:34:26,750
+اه هو مفترض ال material مفترض ان ال SUT عنده ستمية
+
+238
+00:34:26,750 --> 00:34:29,510
+وتسعين ميجا باسكال والاسواي خمسمية و تمانية ميجا
+
+239
+00:34:29,510 --> 00:34:34,610
+باسكال ال SUT هذا اللي هو المفروض يكون معطوه ال
+
+240
+00:34:34,610 --> 00:34:42,050
+SUT ستمية وتسعين ميجا باسكال وخمسمية و تمانية
+
+241
+00:34:42,050 --> 00:34:47,790
+ستمية وتسعين ميجا باسكال والاسواي
+
+242
+00:34:52,190 --> 00:34:57,710
+خمسمية و اتمانين ماجي بس كان في حال اتمثال زي هيك
+
+243
+00:34:57,710 --> 00:35:04,590
+اول شي لازم نعمل ما يسمى ال ..
+
+244
+00:35:04,590 --> 00:35:10,510
+نحسب ال reactions عند a و d بعدين نرسم ال shear
+
+245
+00:35:10,510 --> 00:35:16,630
+diagram و ال moment diagram بعدين specify ال
+
+246
+00:35:16,630 --> 00:35:22,050
+critical locationswhile taking care of stress
+
+247
+00:35:22,050 --> 00:35:25,690
+concentrations وهنا احنا هنبدأ في التسلسل اول شي
+
+248
+00:35:25,690 --> 00:35:29,150
+calculate reactions عشان to calculate reactions I
+
+249
+00:35:29,150 --> 00:35:33,650
+have to make a free body diagram بدي اعمل free
+
+250
+00:35:33,650 --> 00:35:39,650
+body diagram او عندي .. عندي هذه A وهذه
+
+251
+00:35:39,650 --> 00:35:48,150
+D عندي هذه 6.8 كيلو نيوتن ده أحس بال reactionsعندي
+
+252
+00:35:48,150 --> 00:35:51,150
+a و d ده احسب r واحد و r اتنين هاخد summation of
+
+253
+00:35:51,150 --> 00:35:59,510
+moment summation of moment عندي بالساوة سفر هعتبر
+
+254
+00:35:59,510 --> 00:36:08,610
+بعكس عقار الساعة موجب هكون ساوة هكون عندي هنا ستة
+
+255
+00:36:08,610 --> 00:36:11,590
+point تمانية في مية زائد مية و خمس و عشرين يعني
+
+256
+00:36:11,590 --> 00:36:13,330
+ميتين و خمس و عشرين ستة point تمانية
+
+257
+00:36:17,570 --> 00:36:22,550
+في متين و خمسة و عشرين ناقص عند ال R واحد في
+
+258
+00:36:22,550 --> 00:36:29,490
+المسافة هذه عند مية
+
+259
+00:36:29,490 --> 00:36:32,750
+زي مية و خمسة و عشرين متين و خمسة و عشرين زي خمسة
+
+260
+00:36:32,750 --> 00:36:41,470
+و سبعين تلت مية زي متين و خمسينكمان والله 125 225
+
+261
+00:36:41,470 --> 00:36:57,410
+300 زاد 250 550 ناقص 550 في R1 ومنها
+
+262
+00:36:57,410 --> 00:37:01,950
+بحسب ال R1 هتكون
+
+263
+00:37:03,790 --> 00:37:12,990
+6.8 في 225 تقسم تطلع
+
+264
+00:37:12,990 --> 00:37:21,150
+2.781 كيلو
+
+265
+00:37:21,150 --> 00:37:22,490
+نيوتن
+
+266
+00:37:25,300 --> 00:37:32,560
+هحكي summation لل FY بالساوية 0 هيكون الساوية R1
+
+267
+00:37:32,560 --> 00:37:42,260
+زائد R2 minus 6.8 ومنها بحسب ال R2 هتكون 6.8 minus
+
+268
+00:37:42,260 --> 00:37:44,200
+2.781
+
+269
+00:37:59,490 --> 00:38:08,490
+بتطلع اربع point او تسعتاش خلي
+
+270
+00:38:08,490 --> 00:38:12,030
+هذا بالنيوتن يعني هتكون الفين و سبعمية واحد تمانية
+
+271
+00:38:12,030 --> 00:38:19,650
+نيوتن هذا هتكون اربع تلاف و تسعتاش نيوتن حسبت R
+
+272
+00:38:19,650 --> 00:38:24,050
+واحد و R اتنين هعمل ال .. ال shear و ال moon
+
+273
+00:38:24,050 --> 00:38:25,570
+diagram ال shear diagram
+
+274
+00:38:46,520 --> 00:38:54,320
+الشير دياجرام انا
+
+275
+00:38:54,320 --> 00:39:06,800
+عند ال R1 اللي هي 2781 هكون شكل
+
+276
+00:39:06,800 --> 00:39:07,500
+الشير دياجرام
+
+277
+00:39:20,590 --> 00:39:28,770
+هذا الشير عندهين
+
+278
+00:39:28,770 --> 00:39:37,350
+ألفين و سبعة مية و واحد و تمانين وهين ناقص أربع
+
+279
+00:39:37,350 --> 00:39:45,690
+تلاف و تسعة عشر ال moment diagram هكون
+
+280
+00:39:45,690 --> 00:39:46,710
+جاي بالشكل هذا
+
+281
+00:39:55,490 --> 00:40:00,610
+عندي هذه هتكون
+
+282
+00:40:00,610 --> 00:40:03,370
+ال area هذه ال area اللي هي هتكون الفين هذه
+
+283
+00:40:03,370 --> 00:40:09,510
+المسافة بيتين و خمسين زيادة خمسين تلت مية و خمسة و
+
+284
+00:40:09,510 --> 00:40:11,030
+عشرين يعني هذه هتكون
+
+285
+00:40:18,710 --> 00:40:22,890
+ألف فى هنا سبعمية واحد تمانين فى تلت مية خمسة و
+
+286
+00:40:22,890 --> 00:40:30,390
+عشرين تقسيم الف تطلع
+
+287
+00:40:30,390 --> 00:40:34,850
+تسعمية و تلاتة point تسعمية و تلاتة point أو
+
+288
+00:40:34,850 --> 00:40:40,730
+تسعمية و أربعة نحكي تسعمية و أربعة نيوتن
+
+289
+00:40:40,730 --> 00:40:43,850
+متر هذا ال moment diagram
+
+290
+00:40:47,940 --> 00:40:52,900
+الـ moment diagram الآن
+
+291
+00:40:52,900 --> 00:41:04,300
+السؤال لحظة القطر هنا عندى القطر هنا 32 والقطر
+
+292
+00:41:04,300 --> 00:41:15,020
+هنا 38 والقطر هنا 35 الآن
+
+293
+00:41:15,020 --> 00:41:23,740
+في عندى نقطة Bو نقطة C لأن القطر صح ال moment هنا
+
+294
+00:41:23,740 --> 00:41:28,040
+maximum لكن عند النقطة هذه مافيش stress
+
+295
+00:41:28,040 --> 00:41:33,400
+concentration الآن معناته ال critical point هتكون
+
+296
+00:41:33,400 --> 00:41:40,440
+يا إما B يا إما C لأن في شغل تاني عند B القطر أصغر
+
+297
+00:41:40,440 --> 00:41:45,850
+من القطر C معناته من ناحية القطرهتكون B is more
+
+298
+00:41:45,850 --> 00:41:53,270
+critical than C بعدين عندك هنا B أقرب على ال load
+
+299
+00:41:53,270 --> 00:41:56,930
+معناته ال moment هنا هتكون أعلى عن B يعني أنت عند
+
+300
+00:41:56,930 --> 00:42:01,770
+B القطر أصغر و ال moment أعلى معناته ال critical
+
+301
+00:42:01,770 --> 00:42:10,630
+point هي نقطة B معناته أنا لازم أنزل هنا و
+
+302
+00:42:10,630 --> 00:42:19,610
+أحسب ال momentand B بمعنى بي بي
+
+303
+00:42:19,610 --> 00:42:27,930
+is the critical location at
+
+304
+00:42:27,930 --> 00:42:32,230
+B
+
+305
+00:42:32,230 --> 00:42:43,330
+و ال moment عن بي هتكون هعمل تشابه مثلثات هذه
+
+306
+00:42:43,330 --> 00:42:53,130
+م بيهذه المسافة كم؟ هذه متين و خمسين متين
+
+307
+00:42:53,130 --> 00:42:58,690
+و خمسين و هذه كلها تلت مية و خمسة و عشرين هذه كلها
+
+308
+00:42:58,690 --> 00:43:01,990
+تلت
+
+309
+00:43:01,990 --> 00:43:08,950
+مية و خمسة و عشرين معناته MB MB
+
+310
+00:43:13,480 --> 00:43:16,660
+على ال .. ال .. ال .. ال moment اللي هنا اللي هي
+
+311
+00:43:16,660 --> 00:43:23,460
+تسعة مية وأربعة من تشابه مثلثات بتساوي متين و
+
+312
+00:43:23,460 --> 00:43:30,240
+خمسين ع تلات مية و خمسة و عشرين منها بحسب ال Mb
+
+313
+00:43:46,950 --> 00:43:52,870
+وبتطلع ستمية و خمسة وتسعين نيوتن
+
+314
+00:43:52,870 --> 00:43:56,070
+متر ال Mb
+
+315
+00:44:06,200 --> 00:44:11,960
+ال .. طبعا انا هنا ه .. ه .. ه .. هحمل اللي هو ال
+
+316
+00:44:11,960 --> 00:44:15,480
+transfers shear stress لأن anyway .. anyway مش
+
+317
+00:44:15,480 --> 00:44:18,240
+هحمله anyway على المحيط ال transfers shear stress
+
+318
+00:44:18,240 --> 00:44:22,560
+بيكون ساوي سفر بيكون maximum في النص ال bend .. ال
+
+319
+00:44:22,560 --> 00:44:24,360
+stress .. ال normal stress due to bending بيكون
+
+320
+00:44:24,360 --> 00:44:28,500
+maximum على المحيط و سفر في النص معناته I will
+
+321
+00:44:28,500 --> 00:44:31,980
+consider only bending في الحال .. الحالة دي ال
+
+322
+00:44:31,980 --> 00:44:39,690
+sigmaعن بي ال normal stress sigma o هتكون السواء م
+
+323
+00:44:39,690 --> 00:44:49,790
+بي في C على I هتكون السواء م بي ال C عبارة عن دي
+
+324
+00:44:49,790 --> 00:44:59,450
+على اتنين وال I باي على اربعة و ستين دي اص اربعة
+
+325
+00:44:59,450 --> 00:45:08,820
+يعني هتكون السواء اتنين و تلاتينم بي على باي دي قص
+
+326
+00:45:08,820 --> 00:45:16,600
+تلاتة يعنى هتساوى اتنين و تلاتين ال م بي اللى هى
+
+327
+00:45:16,600 --> 00:45:25,440
+ستمية و خمسة و تسعين على باي ال دي اللى هتساوى
+
+328
+00:45:25,440 --> 00:45:28,840
+اتنين و تلاتين م بي اللى هتساوى اتنين و تلاتين في
+
+329
+00:45:28,840 --> 00:45:37,650
+بونتأو تلاتة اتنين الكل تكييب عشان احاوله لميجا
+
+330
+00:45:37,650 --> 00:45:47,490
+باسكال حضره في عشرة أسالب ستة هتكون نحسب اتنين و
+
+331
+00:45:47,490 --> 00:45:55,490
+تلاتين في ستمية و خمسة وتسعين تقسيم ال by
+
+332
+00:46:02,920 --> 00:46:07,900
+ع فكرة الالحس بتاعة ابني لسه انا مش متعود عليها
+
+333
+00:46:07,900 --> 00:46:13,420
+خليني تقسيم تلاتة point واحد اربعة تقسيم point O
+
+334
+00:46:13,420 --> 00:46:24,360
+تلاتة اتنين اص تلاتة يساوي اقل تقسيم مليون تقسيم
+
+335
+00:46:24,360 --> 00:46:29,040
+الف يساوي تطلع متين وستاش
+
+336
+00:46:32,950 --> 00:46:39,130
+ميجا باسكال ميجا باسكال ميجا باسكال ميجا باسكال
+
+337
+00:46:39,130 --> 00:46:39,130
+ميجا باسكال ميجا باسكال ميجا باسكال ميجا باسكال
+
+338
+00:46:39,130 --> 00:46:40,790
+ميجا باسكال ميجا باسكال ميجا باسكال ميجا باسكال
+
+339
+00:46:40,790 --> 00:46:40,790
+ميجا باسكال ميجا باسكال ميجا باسكال ميجا باسكال
+
+340
+00:46:40,790 --> 00:46:40,790
+ميجا باسكال ميجا باسكال ميجا باسكال ميجا باسكال
+
+341
+00:46:40,790 --> 00:46:40,950
+ميجا باسكال ميجا باسكال ميجا باسكال ميجا باسكال
+
+342
+00:46:40,950 --> 00:46:50,790
+ميجا باسكال ميجا
+
+343
+00:46:50,790 --> 00:47:02,210
+باسكال ميجا باسكال ميجا باسكال
+
+344
+00:47:04,000 --> 00:47:10,040
+الـ KT هضطر
+
+345
+00:47:10,040 --> 00:47:21,300
+أستخدم ال appendix A A 15 9 هروح ل A 15 9 عشان
+
+346
+00:47:21,300 --> 00:47:26,040
+أحسب ال KT هنشوف ال appendix A 15 9
+
+347
+00:47:43,250 --> 00:47:56,570
+اللي هي دي الحالة طيب
+
+348
+00:47:56,570 --> 00:48:01,610
+عند
+
+349
+00:48:01,610 --> 00:48:08,910
+ال R على D بلزمني أحسب ال R على D بلزمني
+
+350
+00:48:08,910 --> 00:48:16,130
+أحسب ال R على Dالـ R تلاتة على اتنين و تلاتين او
+
+351
+00:48:16,130 --> 00:48:26,730
+احسب ال D capital على D تمانية و تلاتين على
+
+352
+00:48:26,730 --> 00:48:31,930
+اتنين و تلاتين تلاتة
+
+353
+00:48:31,930 --> 00:48:40,670
+تقسيم اتنين و تلاتين تطلع تقريبا point one وهذه
+
+354
+00:48:40,670 --> 00:48:41,490
+تمانية و تلاتين
+
+355
+00:48:46,680 --> 00:48:54,020
+بتطلع واحد point واحد تمانية سبعة خمسة انا عند هنا
+
+356
+00:48:54,020 --> 00:49:01,160
+point واحد بجاء
+
+357
+00:49:01,160 --> 00:49:08,800
+بين التانية التانية و التالت تقرع واحد point ستة
+
+358
+00:49:08,800 --> 00:49:11,800
+واحد point ستة خمسة ال KT
+
+359
+00:49:16,060 --> 00:49:43,280
+1.65 حسبت
+
+360
+00:49:43,280 --> 00:49:58,210
+الكتاب يطلع 1.6خمسة بدي احسب ال .. KF So واحد زاد
+
+361
+00:49:58,210 --> 00:50:05,670
+كيو في KT minus واحد ال KT قرري حسبتها ال كيو هروح
+
+362
+00:50:05,670 --> 00:50:13,410
+على شكل ستة عشرين هنروح في figure ستة عشرين هنشوف
+
+363
+00:50:13,410 --> 00:50:14,510
+figure ستة عشرين
+
+364
+00:50:20,810 --> 00:50:34,930
+عند ال SUT عند ال R تلاتة ملي التلت
+
+365
+00:50:34,930 --> 00:50:46,370
+يعني تقريبا bond two bond two على تلاتة زائد
+
+366
+00:50:46,370 --> 00:50:47,510
+bond تمانية
+
+367
+00:50:51,320 --> 00:50:57,640
+بتطلع تقريبا بون تمانية ستة كيو
+
+368
+00:50:57,640 --> 00:51:00,660
+بس
+
+369
+00:51:00,660 --> 00:51:06,700
+هو بون تمانية ستة خمسة ومنها بحسب الكي أف هتكون
+
+370
+00:51:06,700 --> 00:51:12,520
+واحد زائد بون تمانية ستة خمسة في واحد بون ستة خمسة
+
+371
+00:51:12,520 --> 00:51:13,420
+ناقص واحد
+
+372
+00:51:25,900 --> 00:51:32,000
+واحد point خمسة ستة اتنين واحد point خمسة ستة
+
+373
+00:51:32,000 --> 00:51:38,000
+اتنين معناته ال maximum stress عند ال critical
+
+374
+00:51:38,000 --> 00:51:45,400
+point ال sigma هتكون KF في ال sigma O
+
+375
+00:51:50,420 --> 00:51:56,720
+اللي هي واحد point خمسة ستة اتنين في sigma o اللي
+
+376
+00:51:56,720 --> 00:52:09,200
+هي متين وستاش تطلع
+
+377
+00:52:09,200 --> 00:52:15,620
+تلتمية و سبعة و تلتين ميجا
+
+378
+00:52:15,620 --> 00:52:17,660
+بسكال
+
+379
+00:52:45,730 --> 00:52:52,410
+طيب لأن هحسب ال S A' بسوا
+
+380
+00:52:52,410 --> 00:53:01,970
+نص ال S U T هتسوا نص ال S U T اللي هي ستمية وتسعين
+
+381
+00:53:01,970 --> 00:53:06,670
+ميجا يعني هكون تلاتة
+
+382
+00:53:09,780 --> 00:53:22,480
+تلاتمية و خمسة و اربعين ميجا باسكال طب
+
+383
+00:53:22,480 --> 00:53:29,280
+محتاج اعملها correction لل .. correction لل SE
+
+384
+00:53:29,280 --> 00:53:30,100
+prime
+
+385
+00:53:37,910 --> 00:53:52,510
+بدي أحسب ال K A ال K A so A S U T بص B طبعا هذا it
+
+386
+00:53:52,510 --> 00:53:57,210
+is machined أكيد الشفت هذا مش معمله hot rolling
+
+387
+00:53:57,210 --> 00:53:58,390
+أكيد machined
+
+388
+00:54:06,470 --> 00:54:14,230
+الـ K A مازالوا ماشيين هتكون ال
+
+389
+00:54:14,230 --> 00:54:21,530
+.. ال .. ال K بتاعته ال A أربعة point أربعة point
+
+390
+00:54:21,530 --> 00:54:28,730
+خمسة واحد أربعة ال A هتكون أربعة point خمسة واحد
+
+391
+00:54:28,730 --> 00:54:33,870
+في ال SC2 ستمية وتسعين أص B دي minus point
+
+392
+00:54:36,820 --> 00:54:43,300
+اتنين ستة خمسة ال K.A عندى
+
+393
+00:54:43,300 --> 00:54:51,840
+ستمية وتسعين اقصى minus point اتنين ستة خمسة في
+
+394
+00:54:51,840 --> 00:54:57,900
+اربع point خمسة واحد هيطلع point سبعة تسعة تمانية
+
+395
+00:54:57,900 --> 00:55:01,940
+point سبعة تسعة
+
+396
+00:55:01,940 --> 00:55:05,320
+تمانية هذا ال K.A هذا اللى هى ال surface finish
+
+397
+00:55:05,320 --> 00:55:18,080
+factorال كيبي الكيبي الكيبي هتكون اللي هو ال size
+
+398
+00:55:18,080 --> 00:55:23,640
+factor كيبي بتساوي
+
+399
+00:55:23,640 --> 00:55:28,380
+واحد point اتنين four في
+
+400
+00:55:28,380 --> 00:55:32,620
+دي قصة minus point واحد زير و سبعة يعني واحد point
+
+401
+00:55:32,620 --> 00:55:40,510
+اتنين اربعة القطر عندىاتنين و تلاتين اص minus
+
+402
+00:55:40,510 --> 00:55:46,430
+point واحد سفر سبعة اتنين
+
+403
+00:55:46,430 --> 00:55:55,150
+و تلاتين اص minus zero point واحد سفر سبعة يساوي
+
+404
+00:55:55,150 --> 00:56:01,670
+في واحد point اتنين اربعة تطلع point خمس تمانية
+
+405
+00:56:01,670 --> 00:56:04,790
+خمسة
+
+406
+00:56:04,790 --> 00:56:05,530
+ستة
+
+407
+00:56:22,120 --> 00:56:30,960
+.856 ال loading factor bending معناه كسي بتساوي
+
+408
+00:56:30,960 --> 00:56:38,230
+واحد فش ال temperature effectو مافيش هنا معلومات
+
+409
+00:56:38,230 --> 00:56:43,070
+عن ريابلتي معناته بيساوي ال KD ال KD بيساوي واحد
+
+410
+00:56:43,070 --> 00:56:52,270
+وال KE بيساوي واحد معناته ال SE هتساوي
+
+411
+00:56:52,270 --> 00:57:01,770
+KA اللي هي point 7 تسعة تمانية ال KB اللي هي واحد
+
+412
+00:57:01,770 --> 00:57:10,070
+point تمانية خمسة ستةفي SE Prime اللي هي تلت مية و
+
+413
+00:57:10,070 --> 00:57:16,990
+خمسة و أربعين ميجا يعني
+
+414
+00:57:16,990 --> 00:57:23,530
+عندي بونت سبعة تسعة تمانية في بونت تمانية خمسة ستة
+
+415
+00:57:23,530 --> 00:57:28,970
+في تلت مية و خمسة و أربعين بتطلع متين و خمسة و
+
+416
+00:57:28,970 --> 00:57:33,010
+تلتين ميجا باسكال
+
+417
+00:57:59,930 --> 00:58:07,330
+لنحسب ال life ال life لل .. طبعاً لل SE اللي هي
+
+418
+00:58:07,330 --> 00:58:15,850
+ميتين و خمس تلاتين ميجا باسكال و ال sigma ..
+
+419
+00:58:15,850 --> 00:58:20,190
+لاحظوا ال sigma .. ال sigma .. لاحظوا ال sigma
+
+420
+00:58:20,190 --> 00:58:27,270
+بتاعتي تلت مية و سبعة و تلتين أكبر من ال SE و أصغر
+
+421
+00:58:27,270 --> 00:58:36,940
+من ال SY ال sigmaالـ Sigma أكبر من ال SE و أصغر من
+
+422
+00:58:36,940 --> 00:58:41,500
+ال SY معناته ما زال أكبر من ال .. من ال .. من ال
+
+423
+00:58:41,500 --> 00:58:47,340
+SE معناته finite life و أصغر ال SY معناته مش هصير
+
+424
+00:58:47,340 --> 00:58:50,700
+يعني على الأغلب مش هصير yielding يعني معناته هتكون
+
+425
+00:58:50,700 --> 00:58:56,240
+هذه finite life problem finite life
+
+426
+00:58:56,240 --> 00:58:57,000
+problem
+
+427
+00:59:02,520 --> 00:59:08,020
+الان ما زال finite life problem بدي أحسب ال number
+
+428
+00:59:08,020 --> 00:59:12,000
+of cycles من المعادلة السابقة مرت علينا خلينا نرجع
+
+429
+00:59:12,000 --> 00:59:19,940
+أرجع لورا أيوة
+
+430
+00:59:19,940 --> 00:59:22,060
+اللي هي n بالساوية
+
+431
+00:59:29,990 --> 00:59:35,710
+بالساوية sigma reversible على
+
+432
+00:59:35,710 --> 00:59:43,530
+a أس واحد على بيه
+
+433
+00:59:43,530 --> 00:59:46,970
+طيب نرجع لمسألتنا
+
+434
+00:59:56,940 --> 01:00:03,240
+الان ال A ال A ال
+
+435
+01:00:03,240 --> 01:00:14,720
+A بالسواء F S U T هنكتبها هنا أحسن ال A بالسواء
+
+436
+01:00:14,720 --> 01:00:21,120
+F S U T الكل تربية على ال S E
+
+437
+01:00:28,140 --> 01:00:32,820
+معناته مطلوب ان نحسب ال F مطلوب نحسب ال F ال F
+
+438
+01:00:32,820 --> 01:00:50,220
+هتكون من شكل عند
+
+439
+01:00:50,220 --> 01:00:54,260
+ان ال SUT 690 ميجاباسكال يعني في ال kilo Pascal
+
+440
+01:00:54,260 --> 01:01:05,630
+هقسم علىست مية وتسعين تقسيم ستة point تمانية بتطلع
+
+441
+01:01:05,630 --> 01:01:10,090
+يعني حوالي مية واحد كيلو بسكال يعني حوالي مية كيلو
+
+442
+01:01:10,090 --> 01:01:19,890
+بسكال يعني ان احكي هنا هنا هنا يعني
+
+443
+01:01:19,890 --> 01:01:27,280
+تقريبابونت تمانية اربعة خمسة ال F بالساوية بونت
+
+444
+01:01:27,280 --> 01:01:33,880
+تمانية اربعة خمسة من شكل ستة تمانتاش شكل ستة
+
+445
+01:01:33,880 --> 01:01:39,960
+تمانتاش معناته ال A هتكون تساوية بونت تمانية اربعة
+
+446
+01:01:39,960 --> 01:01:45,480
+خمسة في ال SUT اللي هي ستمائية وتسعين على ال SE
+
+447
+01:01:45,480 --> 01:01:49,840
+اللي هي متين وخمس وتلاتين هتكون تساوية
+
+448
+01:01:53,310 --> 01:01:58,950
+بونت تمانية اربعة خمسة في ستمية وتسعين تقسيم اتنين
+
+449
+01:01:58,950 --> 01:02:08,170
+وخمسة تلاتين تطلع اتنين بونت اربعة تمانية
+
+450
+01:02:08,170 --> 01:02:12,450
+واحد وال B
+
+451
+01:02:15,260 --> 01:02:25,340
+الـ B بالساوية minus تلت log ال F S U T على ال S A
+
+452
+01:02:25,340 --> 01:02:33,820
+يعني هتكون ساوية minus تلت log log ال F عندي اللي
+
+453
+01:02:33,820 --> 01:02:42,000
+هي bond تمانيةاربع خمسة في ستمية وتسعين على متين
+
+454
+01:02:42,000 --> 01:02:49,520
+وخمسة وتلاتين هتكون تساوي log اللي هي bond تمانية
+
+455
+01:02:49,520 --> 01:02:54,700
+اربعة خمسة في ستمية وتسعين تقسيم اتين وخمسة
+
+456
+01:02:54,700 --> 01:03:04,950
+وتلاتين يساوي تقسيم تلاتة هتكون minusبونت واحد
+
+457
+01:03:04,950 --> 01:03:24,770
+تلاتة واحد خمسة طيب
+
+458
+01:03:24,770 --> 01:03:31,170
+معناته
+
+459
+01:03:31,170 --> 01:03:31,630
+الأن
+
+460
+01:03:35,590 --> 01:03:43,330
+الان بساوية sigma reversible على a أسواحد على b
+
+461
+01:03:43,330 --> 01:03:48,390
+سيكون sigma reversible اللي احنا حسبناها اللي هي
+
+462
+01:03:48,390 --> 01:03:51,790
+تلت مية و سبعة و تلتين تلت مية و سبعة و تلتين
+
+463
+01:03:54,250 --> 01:04:00,570
+اندي اتنين point اربعة تمانية واحد اص واحد على
+
+464
+01:04:00,570 --> 01:04:11,090
+minus point واحد تلاتة واحد خمسة نحسبها تلاتمية
+
+465
+01:04:11,090 --> 01:04:15,670
+و سبعة و تلاتين تقسيم
+
+466
+01:04:15,670 --> 01:04:22,050
+اتنين point اربعة تمانية واحد يساوي اص
+
+467
+01:04:27,020 --> 01:04:35,940
+واحد تقسيم minus zero point واحد تلاتة واحد خمسة
+
+468
+01:04:35,940 --> 01:04:41,540
+ايه الساعة؟ مافيه
+
+469
+01:04:41,540 --> 01:04:45,660
+ايش غلط على فكرة عند هنا اه ال a هنا غلط هذا هو
+
+470
+01:04:45,660 --> 01:04:50,040
+التربيع طبعا عرفت ان انا غلط طلع عندى الرقم اشي
+
+471
+01:04:50,040 --> 01:04:53,240
+عشر او اصلاق السبعتاش الرقم مش منطقي بيعني انه فيه
+
+472
+01:04:53,240 --> 01:04:58,340
+غلطلازم يكون عندك حس في الأرقام مانوية هاد ال a
+
+473
+01:04:58,340 --> 01:05:02,360
+غلط عندي هيكون ال a خلنا نحسبها point تمانية أربعة
+
+474
+01:05:02,360 --> 01:05:10,820
+خمسة في ستمية وتسعين يساوي تربيع يساوي تقسيم اتنين
+
+475
+01:05:10,820 --> 01:05:17,780
+وخمسة و تلاتين بتطلع ألف و أربعمية و سبعة و أربعين
+
+476
+01:05:17,780 --> 01:05:21,020
+هاد
+
+477
+01:05:21,020 --> 01:05:23,380
+ال a عشان هيك الأشياء هيختلف
+
+478
+01:05:26,270 --> 01:05:33,770
+ألف أربعمية أُص سبعة وأربعين نحسب تلاتة السبعة
+
+479
+01:05:33,770 --> 01:05:42,590
+تقسيم واحد أربعة أربعة سبعة يساوي أُص واحد تقسيم
+
+480
+01:05:42,590 --> 01:05:50,690
+سالب zero point واحد تلاتة وواحد خمسة يساوى تطلع
+
+481
+01:05:50,690 --> 01:05:57,890
+حوالي أربعة وستين ألفتسعمية و اتنين و تلاتين cycle
+
+482
+01:05:57,890 --> 01:06:03,570
+معناته ال part هذا هيصمد هيعيش حوالي خمسة و ستين
+
+483
+01:06:03,570 --> 01:06:08,550
+الف cycle ل ال loading الموجود اللي هو عنده في
+
+484
+01:06:08,550 --> 01:06:17,750
+النص 6.8 كيلونيوتر نكتفي اليوم بكرا بن .. بنخش على
+
+485
+01:06:17,750 --> 01:06:23,510
+موضوع جديد في ال fatigue designبتفصيل أكتر يعني
+
+486
+01:06:23,510 --> 01:06:27,910
+هكون شغل أكتر من الشغل اللي سوناه لحتى اللحظة
+
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/E30F47W7ioI.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/E30F47W7ioI.srt
new file mode 100644
index 0000000000000000000000000000000000000000..041f60b5e1869a5a88390adf94d41741c91c5c1d
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/E30F47W7ioI.srt
@@ -0,0 +1,1557 @@
+1
+00:00:04,980 --> 00:00:07,400
+بسم الله الرحمن الرحيم السلام عليكم ورحمة الله
+
+2
+00:00:07,400 --> 00:00:10,720
+اليوم هنبدأ chapter جديد اللي هو هيكون على
+
+3
+00:00:10,720 --> 00:00:15,120
+deflection and stiffness of the mechanical elements
+
+4
+00:00:15,120 --> 00:00:18,120
+في الـ chapter  الذي درسنا فيه stress analysis
+
+5
+00:00:18,120 --> 00:00:22,480
+of mechanical elements. اليوم في هذا الـ chapter
+
+6
+00:00:22,480 --> 00:00:26,800
+هندرس  الـ spring rates، و الـ tension، و الـ
+
+7
+00:00:26,800 --> 00:00:31,220
+deflection due to tension, compression and torsion.
+
+8
+00:00:31,220 --> 00:00:34,840
+و أيضا الـ spring rate due to tension, compression,
+
+9
+00:00:34,840 --> 00:00:43,840
+and torsion.  سنتعرف على الـ deflection due to bending,
+
+10
+00:00:43,840 --> 00:00:46,800
+على طرق لحسابات الـ deflection، منها الـ
+
+11
+00:00:46,800 --> 00:00:49,600
+superposition، الـ strain energy، و الـ Castigliano
+
+12
+00:00:49,600 --> 00:00:53,940
+theorem. بعدها سنتعرف على deflection of curved
+
+13
+00:00:53,940 --> 00:00:59,120
+members. بعدها سنتعرف كيف نحل المسائل التي تكون غير
+
+14
+00:00:59,120 --> 00:01:02,180
+قابلة للحل بالطرق التقليدية، وهي statically
+
+15
+00:01:02,180 --> 00:01:06,180
+indeterminate problems. بعدها سندرس ظاهرة الـ
+
+16
+00:01:06,180 --> 00:01:09,220
+buckling أو الـ compression of mechanical members،
+
+17
+00:01:09,960 --> 00:01:15,700
+و هي ظاهرة الانبعاج في الأعمدة نتيجة تعرضها
+
+18
+00:01:15,700 --> 00:01:20,160
+لقوة انضغاط. طبعا قوة الانضغاط قد تكون مركزية،
+
+19
+00:01:20,160 --> 00:01:24,700
+أي تمر في محور العمود، أو غير مركزية، أي لا تمر في
+
+20
+00:01:24,700 --> 00:01:25,240
+المحور.
+
+21
+00:01:28,120 --> 00:01:33,800
+سنبدأ ببعض المفاهيم البسيطة كتقديم لهذا الـ
+
+22
+00:01:33,800 --> 00:01:38,960
+chapter. سنتعرف على الـ elasticity، و سنتعرف على الـ spring،
+
+23
+00:01:38,960 --> 00:01:44,340
+و الـ elasticity أو اليونة للمادة هي خاصية للمادة
+
+24
+00:01:44,340 --> 00:01:49,760
+تمكنها من استرجاع شكلها الأصلي. طبعا أي mechanical
+
+25
+00:01:49,760 --> 00:01:55,520
+element يتعرض لقوة يحدث فيه deformation. If this
+
+26
+00:01:55,520 --> 00:01:59,600
+mechanical element is elastic, then it will regain
+
+27
+00:01:59,600 --> 00:02:03,460
+its original shape before deformation upon
+
+28
+00:02:03,460 --> 00:02:07,220
+removing the load.  يعني هذه هي ظاهرة الـ elasticity،
+
+29
+00:02:07,220 --> 00:02:13,700
+ظاهرة أو خاصية للمادة تمكنها من استرجاع شكلها إذا
+
+30
+00:02:13,700 --> 00:02:19,980
+رفعت الحِمل عنها. فما هو الـ spring؟ الـ spring أو
+
+31
+00:02:19,980 --> 00:02:23,720
+الزنبرك. The spring is a mechanical element that
+
+32
+00:02:23,720 --> 00:02:26,900
+exerts a force when deformed.  يعني إذا ضغطت زنبركا،
+
+33
+00:02:26,900 --> 00:02:32,060
+أكيد سأشعر بقوة ضغط من الزنبرك على يدي. إذا سحبته،
+
+34
+00:02:32,060 --> 00:02:37,020
+سيحاول إرجاعه إلى وضعه الأصلي. معناته due to
+
+35
+00:02:37,020 --> 00:02:44,680
+deforming the spring, it exerts a force. الـ
+
+36
+00:02:44,680 --> 00:02:51,290
+spring rate، من الفيزياء نعرف  k  as a function of
+
+37
+00:02:51,290 --> 00:03:00,310
+y، يساوي dF/dy.  المعنى هو أن الـ spring rate أو الـ
+
+38
+00:03:00,310 --> 00:03:07,450
+spring constant،  يعبر عن how much force I
+
+39
+00:03:07,450 --> 00:03:16,850
+need to deflect ΔY. إذا عندي زنبرك أثرت
+
+40
+00:03:16,850 --> 00:03:18,370
+عليه بقوة F،
+
+41
+00:03:23,190 --> 00:03:27,610
+ماذا سيحدث؟
+
+42
+00:03:27,610 --> 00:03:31,890
+انحراف قيمته
+
+43
+00:03:31,890 --> 00:03:39,630
+ΔY. معناته
+
+44
+00:03:39,630 --> 00:03:46,030
+If I increase the force, then I have to decrease the
+
+45
+00:03:46,030 --> 00:03:50,070
+deflection. أو إذا زدت الانحراف، يجب أن أزيد الـ
+
+46
+00:03:50,070 --> 00:03:55,940
+force. إذا كان هذا الزنبرك خطيا، يعني أن قوة الزنبرك،
+
+47
+00:03:55,940 --> 00:04:04,760
+y و F، تتغير بشكل خطي مع الـ
+
+48
+00:04:04,760 --> 00:04:12,460
+deflection.  يكون k  يساوي
+
+49
+00:04:12,460 --> 00:04:18,400
+F/Y.  هذا لـ linear spring.
+
+50
+00:04:27,570 --> 00:04:32,550
+طبعا كل mechanical element له spring constant، حتى
+
+51
+00:04:32,550 --> 00:04:37,910
+لو لم يكن زنبركا. حساب الـ spring constant يعتمد على
+
+52
+00:04:37,910 --> 00:04:44,110
+طبيعة التحميل. الحالة الأولى التي سنأخذها، إذا كان عندي
+
+53
+00:04:44,110 --> 00:04:50,930
+mechanical element تحت تحميل محوري،
+
+54
+00:04:50,930 --> 00:04:51,450
+axial loading.
+
+55
+00:04:56,040 --> 00:05:14,720
+و هذا في البداية كان طوله L،  و مقطعه
+
+56
+00:05:14,720 --> 00:05:25,080
+العرضي  cross sectional area،
+
+57
+00:05:26,880 --> 00:05:34,140
+يساوي A. نتيجة القوة F،  يحدث فيه stress،
+
+58
+00:05:34,140 --> 00:05:42,060
+و يكون الـ stress  يساوي σ = F/A. الـ
+
+59
+00:05:42,060 --> 00:05:46,020
+F هي القوة المحورية، و الـ A مساحة المقطع. و إذا
+
+60
+00:05:46,020 --> 00:05:52,320
+كنت في المنطقة المرنة، سيكون يساوي E × ε. الـ
+
+61
+00:05:52,320 --> 00:05:54,180
+E هو معامل
+
+62
+00:05:58,780 --> 00:06:10,280
+of elasticity (معامل المرونة)، و ε هي الـ strain،
+
+63
+00:06:10,280 --> 00:06:16,740
+و هذه العلاقة صحيحة
+
+64
+00:06:16,740 --> 00:06:20,900
+فقط
+
+65
+00:06:20,900 --> 00:06:25,720
+في المنطقة المرنة.
+
+66
+00:06:30,760 --> 00:06:44,980
+الـ strain  يساوي ΔL/L، يعني
+
+67
+00:06:44,980 --> 00:06:52,900
+هنا سيكون عندي σ = F/A = E × ΔL/L.
+
+68
+00:06:52,900 --> 00:06:55,420
+ΔL على
+
+69
+00:06:57,200 --> 00:07:05,800
+L. لنسميها ΔL. يعني  سيكون عندنا F/A =
+
+70
+00:07:05,800 --> 00:07:15,540
+E × ΔL/L. يعني
+
+71
+00:07:15,540 --> 00:07:22,840
+سيكون عندنا F = (AE/L) ×
+
+72
+00:07:25,650 --> 00:07:30,310
+ΔL.  سنرى أن...أن...أن...أن...أن...
+
+73
+00:07:30,310 --> 00:07:32,050
+أن...أن...أن...أن...أن...أن...أن...أن...
+
+74
+00:07:32,050 --> 00:07:33,430
+أن...أن...أن...أن...أن...أن...أن...أن...
+
+75
+00:07:33,430 --> 00:07:33,530
+أن...أن...أن...أن...أن...أن...أن...أن...
+
+76
+00:07:33,530 --> 00:07:34,650
+أن...أن...أن...أن...أن...أن...أن...أن...
+
+77
+00:07:34,650 --> 00:07:36,210
+أن...أن...أن...أن...أن...أن...أن...أن...
+
+78
+00:07:36,210 --> 00:07:40,750
+أن...أن...أن...أن...
+
+79
+00:07:40,750 --> 00:07:42,050
+أن...أن...أن...أن...أن...أن...أن...أن...
+
+80
+00:07:42,050 --> 00:07:42,110
+أن...أن...أن...أن...أن...أن...أن...أن...
+
+81
+00:07:42,110 --> 00:07:42,610
+أن...أن...أن...أن...أن...أن...أن...أن...
+
+82
+00:07:42,610 --> 00:07:47,090
+أن...أن...أن...
+
+83
+00:07:47,090 --> 00:07:51,230
+أن...أن...
+
+84
+00:07:55,790 --> 00:08:01,870
+و هذا الـ deflection.
+
+85
+00:08:01,870 --> 00:08:09,070
+معناته هذا الحد
+
+86
+00:08:09,070 --> 00:08:12,930
+هو القوة، و
+
+87
+00:08:12,930 --> 00:08:19,250
+هذا هو الـ deflection. معناته
+
+88
+00:08:19,250 --> 00:08:25,230
+هذا ماذا سيكون؟ k. معناته في mechanical element under
+
+89
+00:08:25,230 --> 00:08:29,370
+axial loading، سواء كان tension أو compression،
+
+90
+00:08:29,370 --> 00:08:41,850
+سيكون F = k × ΔL، حيث k = AE/L.  المعنى هو أنه إذا كان عندي mechanical element
+
+91
+00:08:41,850 --> 00:08:47,190
+تحت تحميل محوري، يمكنني اعتباره زنبركا.  الزنبرك
+
+92
+00:08:47,190 --> 00:08:54,740
+الـ spring rate  يُعطى بالعلاقة AE/L.  الـ A هي
+
+93
+00:08:54,740 --> 00:08:58,600
+مساحة المقطع، الـ E هي modulus of elasticity، و
+
+94
+00:08:58,600 --> 00:09:03,760
+الـ L هي طول الـ mechanical element.  بالنسبة
+
+95
+00:09:03,760 --> 00:09:14,220
+لـ torsion، أي العضو المحمل
+
+96
+00:09:14,220 --> 00:09:18,160
+بالتواء، tortionally loaded member،
+
+97
+00:09:29,160 --> 00:09:34,460
+for a tortionally loaded member، سيكون لديه، لو
+
+98
+00:09:34,460 --> 00:09:53,420
+افترضنا أنه مقطع دائري، و
+
+99
+00:09:53,420 --> 00:10:08,820
+تؤثر عليه عزم دوران T.
+
+100
+00:10:08,820 --> 00:10:17,780
+هذه هي الـ angular deflection θ.
+
+101
+00:10:19,970 --> 00:10:24,470
+لقد حسبنا في الـ chapter الثالث  θ  هذه. فحسبنا θ
+
+102
+00:10:24,470 --> 00:10:37,690
+بتساوي TL/GJ.  يعني T = GJθ/L. الـ G
+
+103
+00:10:37,690 --> 00:10:47,170
+هي  modulus of rigidity،
+
+104
+00:10:50,610 --> 00:10:56,770
+أو
+
+105
+00:10:56,770 --> 00:11:05,010
+يمكن تسميتها shear modulus، shear modulus، و
+
+106
+00:11:05,010 --> 00:11:14,210
+الـ J هو الـ polar moment of
+
+107
+00:11:14,210 --> 00:11:14,750
+inertia،
+
+108
+00:11:18,170 --> 00:11:26,050
+للمقطع العرضي، و
+
+109
+00:11:26,050 --> 00:11:32,990
+الـ L هو
+
+110
+00:11:32,990 --> 00:11:38,690
+الطول، و
+
+111
+00:11:38,690 --> 00:11:45,770
+θ هي الـ angular deflection.
+
+112
+00:12:03,080 --> 00:12:10,980
+سأضعها هنا.  العزم T = GJθ/L. و في حالة التحميل المحوري،
+
+113
+00:12:10,980 --> 00:12:18,080
+axial loading member.  هنا F =
+
+114
+00:12:18,080 --> 00:12:22,180
+AEΔL/L.  في حالة الحركة الخطية، يكون
+
+115
+00:12:22,180 --> 00:12:32,080
+هذا هو القوة.  في حالة وجود دوران، أو التواء، يكون هذا
+
+116
+00:12:32,080 --> 00:12:38,370
+هو العزم أو الـ torque. في
+
+117
+00:12:38,370 --> 00:12:44,830
+حالة الحركة الخطية، يكون عندي انحراف deflection. في
+
+118
+00:12:44,830 --> 00:12:50,490
+حالة الدوران، يكون عندي زاوية angle. مع أن
+
+119
+00:12:50,490 --> 00:12:55,750
+النتائج، هاتان المعادلتان لهما نفس الشكل. معناته الـ
+
+120
+00:12:55,750 --> 00:12:59,290
+torque يساوي
+
+121
+00:12:59,290 --> 00:13:03,290
+k × θ.  k هي الـ stiffness أو
+
+122
+00:13:04,420 --> 00:13:12,540
+k هي الـ spring rate للعضو المحمل بالالتواء.
+
+123
+00:13:12,540 --> 00:13:15,260
+torsionally loaded member.
+
+124
+00:13:17,880 --> 00:13:23,080
+و التي تساوي GJ/L. المعنى أن
+
+125
+00:13:23,080 --> 00:13:26,860
+الـ spring constant أو الـ spring rate  لعضو محمل
+
+126
+00:13:26,860 --> 00:13:30,380
+بالتواء  torsionally loaded member is given by this
+
+127
+00:13:30,380 --> 00:13:35,440
+relation،  GJ/L.  يعني كلما زاد معامل
+
+128
+00:13:35,440 --> 00:13:39,760
+القص shear modulus، أو modulus of rigidity،
+
+129
+00:13:39,760 --> 00:13:44,140
+كلما زاد k، كلما كان المقطع أكبر،
+
+130
+00:13:44,140 --> 00:13:50,210
+يعني يصعب عمل دوران. أيضا، k
+
+131
+00:13:50,210 --> 00:13:54,430
+يتناقص كلما طال الشيء.  أسهل أن أعمل ماذا؟
+
+132
+00:13:54,430 --> 00:14:03,910
+أن أعمل انحرافا deflection. طيب،
+
+133
+00:14:03,910 --> 00:14:15,550
+سندرس الآن الـ deflection due
+
+134
+00:14:15,550 --> 00:14:16,490
+to bending load.
+
+135
+00:14:22,830 --> 00:14:37,950
+يعني لو كان عندي  beam  وعليه
+
+136
+00:14:37,950 --> 00:14:45,990
+مثلا قوة في المنتصف، سيكون
+
+137
+00:14:45,990 --> 00:14:53,750
+له تفاعلان reaction، تفاعل هنا F/2، و تفاعل
+
+138
+00:14:53,750 --> 00:15:00,270
+هنا F/2. لو رسمت  الـ shear diagram،
+
+139
+00:15:00,270 --> 00:15:12,550
+الـ shear diagram سيكون بهذا الشكل.  هذا
+
+140
+00:15:12,550 --> 00:15:20,050
+F/2،  هذا -F/2. و الـ moment
+
+141
+00:15:20,050 --> 00:15:20,550
+diagram،
+
+142
+00:15:30,400 --> 00:15:38,340
+طبعا إذا كان طوله L،  هذا
+
+143
+00:15:38,340 --> 00:15:46,200
+سيكون طوله L/2، هذا
+
+144
+00:15:46,200 --> 00:15:50,880
+سيكون FL/4. هذا الـ moment diagram.
+
+145
+00:15:50,880 --> 00:15:56,720
+هذا الـ moment diagram.
+
+146
+00:16:00,000 --> 00:16:04,300
+و هذا الـ shear diagram.
+
+147
+00:16:04,300 --> 00:16:07,660
+لقد
+
+148
+00:16:07,660 --> 00:16:12,560
+درسنا في الـ chapter الثالث
+
+149
+00:16:12,560 --> 00:16:18,500
+طبعا هذا سيحدث فيه انحراف deflection، سيكون بهذا
+
+150
+00:16:18,500 --> 00:16:24,540
+الشكل.  هذه النقطة هي نصف قطر الانحناء،  هذا ρ.
+
+151
+00:16:24,540 --> 00:16:41,480
+فإن 1/ρ = M/EI.  ρ هو نصف قطر الـ
+
+152
+00:16:41,480 --> 00:16:47,800
+radius of curvature at
+
+153
+00:16:47,800 --> 00:16:53,120
+a given point
+
+154
+00:16:53,120 --> 00:16:57,880
+on the beam، و
+
+155
+00:17:00,040 --> 00:17:07,480
+M هي عزم الانحناء bending moment،
+
+156
+00:17:07,480 --> 00:17:18,000
+at the given section،
+
+157
+00:17:18,000 --> 00:17:21,220
+at
+
+158
+00:17:21,220 --> 00:17:27,980
+the given section.
+
+159
+00:17:32,750 --> 00:17:45,030
+و E هو معامل المرونة Modulus of elasticity، و
+
+160
+00:17:45,030 --> 00:17:49,630
+I هو
+
+161
+00:17:49,630 --> 00:17:58,230
+moment of inertia of
+
+162
+00:17:58,230 --> 00:17:58,930
+the section.
+
+163
+00:18:07,360 --> 00:18:12,720
+الآن، من التفاضل والتكامل calculus، نعرف أن العلاقة بين
+
+164
+00:18:12,720 --> 00:18:16,060
+نصف قطر الانحناء أو...أو 1/ρ
+
+165
+00:18:16,060 --> 00:18:22,060
+تعطى بالعلاقة  d²y/dx² على
+
+166
+00:18:22,060 --> 00:18:31,800
+1 + (dy/dx)².  ³⁄₂  
+
+167
+00:18:31,800 --> 00:18:36,000
+يعني هنا تحتاج لمعرفة تفاصيل أكثر
+
+168
+00:18:38,670 --> 00:18:48,950
+راجع  calculus. يعني
+
+169
+00:18:48,950 --> 00:18:55,010
+إذا كان هذا هو x، و
+
+170
+00:18:55,010 --> 00:19:06,330
+هذا هو y، معناته عند هذه النقطة، هذا هو الميل dy/dx.
+
+171
+00:19:06,330 --> 00:19:17,640
+إذا كان الانحراف صغيرا جدا، for small
+
+172
+00:19:17,640 --> 00:19:21,840
+slopes
+
+173
+00:19:21,840 --> 00:19:34,280
+للـ beam المنحرف، سيكون
+
+174
+00:19:34,280 --> 00:19:37,620
+عندي dy/dx
+
+175
+00:19:43,030 --> 00:19:47,250
+صغيرا. معناته إذا كان dy/dx  مثلا 0.1،
+
+176
+00:19:47,250 --> 00:19:50,790
+معناته (dy/dx)²  ستكون (0.1)²
+
+177
+00:19:50,790 --> 00:19:58,030
+يعني ستكون صغيرة جدا، معناته (dy/dx)²
+
+178
+00:19:58,030 --> 00:20:05,670
+ستكون صغيرة جدا، معناته
+
+179
+00:20:05,670 --> 00:20:12,580
+هذا الحد، إذا dy/dx  صغير، يعني أن تربيعه
+
+180
+00:20:12,580 --> 00:20:19,500
+صغير جدا. في هذه الحالة، تربيعه
+
+181
+00:20:19,500 --> 00:20:26,420
+يكون صغيرا جدا مقارنة
+
+182
+00:20:26,420 --> 00:20:30,680
+بالواحد. في
+
+183
+00:20:30,680 --> 00:20:33,780
+هذه الحالة،
+
+184
+00:20:33,780 --> 00:20:51,780
+يصبح 1/ρ تقريبا d²y/dx².
+
+185
+00:20:51,780 --> 00:21:04,860
+d²y/dx² = M/EI.  معناته هذه هي
+
+186
+00:21:04,860 --> 00:21:11,250
+أهم علاقة. M/EI = d²y/dx²
+
+187
+00:21:11,250 --> 00:21:12,210
+.
+
+188
+00:21:38,530 --> 00:21:43,210
+لقد عرفنا من الـ chapter الثالث أن V =
+
+189
+00:21:43,210 --> 00:21:57,370
+dM/dx.  و dM/dx = ... و Q = ... و V =
+
+190
+00:21:57,370 --> 00:21:58,430
+... و V =
+
+191
+00:22:04,050 --> 00:22:11,630
+و Q = dV/dx. معناته بناء على ذلك، سيكون
+
+192
+00
+
+223
+00:25:39,030 --> 00:25:49,390
+و هذا الـ Y بتاخد على مسافة X بتاخد
+
+224
+00:25:49,390 --> 00:25:55,530
+جزء من الـ beam على مسافة X فين
+
+225
+00:25:55,530 --> 00:26:04,470
+دي هنا كانت force اللي هي 800 pound هذه
+
+226
+00:26:04,470 --> 00:26:05,450
+المسافة X
+
+227
+00:26:11,380 --> 00:26:19,960
+طبعا هيكون في عندي shear force V و في عندي bending
+
+228
+00:26:19,960 --> 00:26:28,820
+moment M و
+
+229
+00:26:28,820 --> 00:26:35,020
+هاي الـ Y direction و هاي الـ X direction
+
+230
+00:26:42,800 --> 00:26:49,640
+طبعا في عندي كمان distributed load
+
+231
+00:26:49,640 --> 00:26:58,260
+لو
+
+232
+00:26:58,260 --> 00:27:03,920
+أخد summation of forces باتجاه الـ Y بالساوِ صفر
+
+233
+00:27:03,920 --> 00:27:07,180
+هيكون عندي
+
+234
+00:27:12,760 --> 00:27:23,940
+الأعلى عندي 800 ناقص عندي هذه 80 ناقص 80 في X لتحت
+
+235
+00:27:23,940 --> 00:27:31,920
+ناقص 80 في X لتحت minus
+
+236
+00:27:31,920 --> 00:27:38,600
+V = 0 معناته
+
+237
+00:27:38,600 --> 00:27:38,980
+الـ V
+
+238
+00:27:45,160 --> 00:27:56,740
+حتساوي ثمانين اكس ناقص ثمانماية أو V بيساوي العكس الـ
+
+239
+00:27:56,740 --> 00:28:02,240
+V بيساوي الثمانماية minus
+
+240
+00:28:02,240 --> 00:28:08,080
+ثمانين اكس هذا الـ V
+
+241
+00:28:13,100 --> 00:28:23,280
+احنا سابقا حكينا الـ V بيساوي dM/dx الـ V بيساوي
+
+242
+00:28:23,280 --> 00:28:39,400
+dM/dx معناه dM = V dx يعني هيساوي الـ V
+
+243
+00:28:39,400 --> 00:28:42,620
+اللي هي 800 - 80 X
+
+244
+00:28:45,620 --> 00:28:51,620
+dx و هنا dM هنا هعمل تكامل الـ M عند الطرف كانت صفر
+
+245
+00:28:51,620 --> 00:28:59,880
+to M و هنا عندي التكامل
+
+246
+00:28:59,880 --> 00:29:07,480
+من صفر لـ X يعني انا هتكون عند الـ M بتساوي
+
+247
+00:29:07,480 --> 00:29:12,000
+ثمانمائة
+
+248
+00:29:12,000 --> 00:29:13,340
+X
+
+249
+00:29:15,610 --> 00:29:28,190
+ناقص اربعين اكس تربيع هذه الـ moment لحظة
+
+250
+00:29:28,190 --> 00:29:33,290
+هو ما أعطانا العلاقة هنا M = Wl/2
+
+251
+00:29:33,290 --> 00:29:40,090
+في X W ثمانين ثمانين والـ L كم؟ عشرين ثمانين في
+
+252
+00:29:40,090 --> 00:29:43,570
+عشرين × 80 = 1600 / 2 = 800 هاي هطلع تاني
+
+253
+00:29:43,570 --> 00:29:47,760
+ثمانمائة عندها و على اتنين و ثمانين ثمانين على
+
+254
+00:29:47,760 --> 00:29:58,780
+اتنين = 400 المناورة للعلاقات and if صحيحة لأن
+
+255
+00:29:58,780 --> 00:30:05,120
+عشان أواجه الـ deflection أنا
+
+256
+00:30:05,120 --> 00:30:14,040
+في عندي relation في علاقة بين الـ M/EI =
+
+257
+00:30:16,640 --> 00:30:25,580
+d²y/dx² يعني
+
+258
+00:30:25,580 --> 00:30:40,920
+أحس أن الـ d/dx لـ dy/dx بتساوي أعوض 1/E
+
+259
+00:30:40,920 --> 00:30:41,540
+في I
+
+260
+00:30:45,950 --> 00:30:52,530
+الـ M اللي هي ثمانمائة ثمانمائة
+
+261
+00:30:52,530 --> 00:31:08,310
+X ناقص أربعين X تربيع بأعمل
+
+262
+00:31:08,310 --> 00:31:12,970
+تكامل لهذه هأحسب عندي D
+
+263
+00:31:16,280 --> 00:31:29,760
+إلى dy/dx بتساوي 1/EI في 800x - 40x
+
+264
+00:31:29,760 --> 00:31:36,540
+تربيع dx و بأعمل تكامل للطرفين
+
+265
+00:31:45,370 --> 00:32:02,030
+حسبنا الـ dy/dx بتساوي 1/EI في مشتقة 800x
+
+266
+00:32:02,030 --> 00:32:10,370
+عبارة عن 400x تربيع ناقص
+
+267
+00:32:10,370 --> 00:32:13,990
+40
+
+268
+00:32:13,990 --> 00:32:20,730
+x تكعيب زائد ثابت واحد constant of
+
+269
+00:32:20,730 --> 00:32:24,710
+integration بأعمل
+
+270
+00:32:24,710 --> 00:32:33,150
+integration كمان مرة integrate هتصير
+
+271
+00:32:33,150 --> 00:32:40,630
+عندي الـ y = 1/EI
+
+272
+00:32:43,270 --> 00:33:00,690
+في 400/3 x تكعيب ناقص 400/3 في 4/12 x
+
+273
+00:33:00,690 --> 00:33:07,650
+أس 4 زائد C1 في x زائد C2
+
+274
+00:33:11,860 --> 00:33:17,960
+لأن I have to find الـ C1 and C2 using the boundary
+
+275
+00:33:17,960 --> 00:33:23,420
+or end conditions find C1
+
+276
+00:33:23,420 --> 00:33:33,240
+and C2 using the boundary conditions
+
+277
+00:33:33,240 --> 00:33:36,940
+عند
+
+278
+00:33:36,940 --> 00:33:40,420
+أنا بعرف deflection يعني عندي y
+
+279
+00:33:42,160 --> 00:33:50,620
+بتساوي صفر at X = صفر يعني لو حطيت هنا صفر
+
+280
+00:33:50,620 --> 00:33:59,580
+هيكون 1/EI طبعا في صفر ناقص صفر زائد C
+
+281
+00:33:59,580 --> 00:34:05,480
+واحد في صفر زائد C اتنين معناته C اتنين تطلع
+
+282
+00:34:05,480 --> 00:34:10,480
+تساوي ايش صفر و برضه عند الـ End التاني ما فيش
+
+283
+00:34:10,480 --> 00:34:19,070
+deflection y = صفر at
+
+284
+00:34:19,070 --> 00:34:25,870
+x = عشرين المعنى أني أحس أن أعوض هنا
+
+285
+00:34:25,870 --> 00:34:34,170
+أحس أن عندي الـ صفر = 1/EI في
+
+286
+00:34:34,170 --> 00:34:47,760
+400/3 في عشرين تكعيب - 400/12 في 20
+
+287
+00:34:47,760 --> 00:34:52,340
+أس 4 زائد
+
+288
+00:34:52,340 --> 00:35:02,240
+C1 في 20 يعني
+
+289
+00:35:02,240 --> 00:35:05,080
+إذا قسمت الطرفين على 20 هأحسب قيمة C1
+
+290
+00:35:07,550 --> 00:35:20,170
+هتكون تساوي 1/EI في
+
+291
+00:35:20,170 --> 00:35:31,010
+400/12 يعني 100/3 في عشرين تكعيب ناقص
+
+292
+00:35:31,010 --> 00:35:35,270
+400
+
+293
+00:35:37,300 --> 00:35:41,540
+/3 في
+
+294
+00:35:41,540 --> 00:35:45,740
+عشرين تربيع
+
+295
+00:35:45,740 --> 00:35:49,340
+يعني
+
+296
+00:35:49,340 --> 00:35:57,620
+إذا أخذتها على مُشترك عشرين تربيع في مائة يعني أخذت
+
+297
+00:35:57,620 --> 00:36:06,620
+ثلاثة برة و أخذت عشرين تربيع اللي هي أربعمائة
+
+298
+00:36:08,470 --> 00:36:14,390
+في عشرين تربيع بتصفي
+
+299
+00:36:14,390 --> 00:36:17,730
+مائة
+
+300
+00:36:17,730 --> 00:36:24,850
+/3 بتروح وعشرين تربيع بتصفي أربعمائة ناقص
+
+301
+00:36:24,850 --> 00:36:29,290
+حد
+
+302
+00:36:29,290 --> 00:36:31,270
+على مائة ناقص أربعة
+
+303
+00:36:37,490 --> 00:36:46,350
+يعني أنا هتكون أربعة
+
+304
+00:36:46,350 --> 00:36:54,130
+أربعة أربعة أربعة واحد اتنين تلاتة أربعة
+
+305
+00:36:54,130 --> 00:37:02,250
+أصفار في ستة عشر / 3 في EI
+
+306
+00:37:08,440 --> 00:37:11,200
+معناته هتصير المعادلة بتاعت الـ deflection الـ Y
+
+307
+00:37:11,200 --> 00:37:14,840
+هتساوي
+
+308
+00:37:14,840 --> 00:37:18,760
+1
+
+309
+00:37:18,760 --> 00:37:34,200
+/EI في 400/3 X تكعيب ناقص 400/12 X أس 4
+
+310
+00:37:36,620 --> 00:37:43,620
+أربعمائة أربعمائة أربعين أربعين ألف في ستة عشر / 3
+
+311
+00:37:43,620 --> 00:37:49,180
+EI في X هذه
+
+312
+00:37:49,180 --> 00:37:57,860
+معادلة الـ deflection الـ slope هيكون dy/dx
+
+313
+00:38:06,040 --> 00:38:13,840
+هيكون 1/EI في
+
+314
+00:38:13,840 --> 00:38:26,440
+أربعمائة X تربيع ناقص أربعمائة / 3 هذه X تربيع
+
+315
+00:38:26,440 --> 00:38:33,380
+هذه X تكعيب زائد
+
+316
+00:38:33,380 --> 00:38:46,040
+أربعمائة في 16 / 3EI طبعا
+
+317
+00:38:46,040 --> 00:38:51,460
+المعادلة هذه بتعطى deflection anywhere and at any
+
+318
+00:38:51,460 --> 00:38:57,600
+x و المعادلة التانية بتعطى slope
+
+319
+00:39:06,320 --> 00:39:13,180
+الـ slope at any x الآن
+
+320
+00:39:13,180 --> 00:39:16,820
+بدي هو الـ deflection at the ends يعني بدي الـ
+
+321
+00:39:16,820 --> 00:39:22,100
+deflection at x = صفر و الـ deflection at x
+
+322
+00:39:22,100 --> 00:39:24,840
+يساوي L اللي هي عشرين at
+
+323
+00:39:33,790 --> 00:39:44,010
+x = صفر هيكون y dy الـ slope dy
+
+324
+00:39:44,010 --> 00:39:50,530
+/dx هتساوي .. هنعوض هنا عن x = صفر
+
+325
+00:39:50,530 --> 00:40:00,030
+صفر هتكون أربعمائة في ستة عشر / E في I طبعا E بنعوض
+
+326
+00:40:00,030 --> 00:40:07,790
+عنها I بنعوض عن هذه عند X = صفر و dy/dx
+
+327
+00:40:07,790 --> 00:40:17,630
+عند X = عشرين هتساوي أعوض
+
+328
+00:40:17,630 --> 00:40:30,520
+1/EI في أربعمائة في عشرين تربيع ناقص أربعمائة في
+
+329
+00:40:30,520 --> 00:40:42,100
+عشرين تكعيب / 3 زائد أربعمائة في ستة عشر /
+
+330
+00:40:42,100 --> 00:40:51,440
+3 EI و بنحسبها الـ maximum deflection one هيكون
+
+331
+00:40:51,440 --> 00:40:59,720
+في النص هذا الـ maximum deflection
+
+332
+00:41:03,310 --> 00:41:11,690
+deflection is maximum
+
+333
+00:41:11,690 --> 00:41:19,650
+at x = L/2 اللي هي = عشرة يعني
+
+334
+00:41:19,650 --> 00:41:25,030
+هتكون y maximum =
+
+335
+00:41:25,030 --> 00:41:28,430
+واحد
+
+336
+00:41:28,430 --> 00:41:41,040
+/EI في 400/3 في عشرة تكعيب ناقص
+
+337
+00:41:41,040 --> 00:41:50,660
+400/12 في عشرة أس 4 زائد
+
+338
+00:42:01,440 --> 00:42:06,140
+هذه في صفرين على فكرة هنا زائد
+
+339
+00:42:06,140 --> 00:42:09,340
+أربعين
+
+340
+00:42:09,340 --> 00:42:19,140
+ألف في ستة عشر / 3 EI في عشرة و بنحسب القيمة
+
+341
+00:42:19,140 --> 00:42:25,360
+أتوقع أنكم تحسبوا الأرقام و تطلعوا أرقام حقيقية
+
+342
+00:42:49,680 --> 00:42:51,080
+ما أعرف كده
+
+343
+00:43:06,670 --> 00:43:10,310
+الآن في أكثر من طريقة لحساب الـ deflections في الـ
+
+344
+00:43:10,310 --> 00:43:13,810
+.. في الـ beams في عندنا superposition method في
+
+345
+00:43:13,810 --> 00:43:16,510
+عندنا moment area method عندنا numerical
+
+346
+00:43:16,510 --> 00:43:20,210
+integration عندنا Castigliano method وعندنا الـ
+
+347
+00:43:20,210 --> 00:43:26,330
+finite element method هنبدأ في الـ .. الـ beam
+
+348
+00:43:26,330 --> 00:43:30,230
+deflection by superposition الـ beam deflection by
+
+349
+00:43:30,230 --> 00:43:33,970
+superposition تعتمد إذا أنا كان beam عليه loading
+
+350
+00:43:35,070 --> 00:43:39,690
+معين متنوع ممكن أجزء الـ effect يعني الـ total
+
+351
+00:43:39,690 --> 00:43:44,250
+effect عبارة عن مجموع individual effects و بأستخدم
+
+352
+00:43:44,250 --> 00:43:47,870
+اللي هي الـ beam deflection formulas من الـ appendix
+
+353
+00:43:47,870 --> 00:43:55,030
+A9 إذا بنفتح الكتاب على الـ appendix
+
+354
+00:43:55,030 --> 00:44:00,570
+A9
+
+355
+00:44:04,060 --> 00:44:11,480
+نفتح الـ appendix هنشوف
+
+356
+00:44:11,480 --> 00:44:19,100
+في عندي beams مختلفة مثلا عندي cantilever beam
+
+357
+00:44:19,100 --> 00:44:23,960
+عليه بيأثر الـ load ومعطيني الـ reaction و الـ moment
+
+358
+00:44:23,960 --> 00:44:31,070
+ومعطيني الـ .. الـ ..shear at any location ومعطيني
+
+359
+00:44:31,070 --> 00:44:34,750
+الـ moment at any location ومعطيني الـ deflection و
+
+360
+00:44:34,750 --> 00:44:38,370
+الـ maximum deflection طبعا عندي مجموعة من الـ beams
+
+361
+00:44:38,370 --> 00:44:46,070
+المختلفة هذا الـ table A9 يعني عندي طرق مختلفة
+
+362
+00:44:46,070 --> 00:44:47,350
+للتحميل الـ beams
+
+363
+00:44:55,260 --> 00:45:00,240
+عندي حوالي عشر حالات، اثنا عشر حالة، ثلاثة عشر،
+
+364
+00:45:00,240 --> 00:45:08,040
+أربعة عشر، خمسة عشر، ستة عشر، حوالي ستة عشر حالة تحميل
+
+365
+00:45:08,040 --> 00:45:12,120
+مختلفة، حوالي ستة عشر حالة تحميل مختلفة
+
+366
+00:45:25,430 --> 00:45:30,190
+إذا بدك تفاصيل أكثر بتروح المرجع هذا Roark's
+
+367
+00:45:30,190 --> 00:45:33,750
+formulas for stress and strain هتشوف حالات و
+
+368
+00:45:33,750 --> 00:45:37,430
+تفاصيل .. يعني هتشوف شغلات أكثر من اللي عرضنا في
+
+369
+00:45:37,430 --> 00:45:43,710
+الـ appendix A9 لأن
+
+370
+00:45:43,710 --> 00:45:51,930
+هنشوف كيف نحل حسابات الـ deflection باستخدام اللي
+
+371
+00:45:51,930 --> 00:45:57,270
+هو الـ superposition واستخدام الجداول نطلع على
+
+372
+00:45:57,270 --> 00:46:01,250
+المثال الحالي consider the uniformly loaded beam
+
+373
+00:46:01,250 --> 00:46:05,670
+with a concentrated force as shown في عند الـ beam
+
+374
+00:46:05,670 --> 00:46:13,600
+فيه بيأثر عليه حمل مركز F على بعد A وفيه برضه بيأثر
+
+375
+00:46:13,600 --> 00:46:20,500
+عليه حمل موزع قيمته W الـ beam طوله L الـ beam is
+
+376
+00:46:20,500 --> 00:46:27,960
+simply supported عند نقطة A عند نقطة C using
+
+377
+00:46:27,960 --> 00:46:31,700
+superposition determine the reactions and
+
+378
+00:46:31,700 --> 00:46:35,100
+deflections as a function of X باستخدام الـ
+
+379
+00:46:35,100 --> 00:46:40,940
+superposition أوجد الـ deflections والـ slopes والـ
+
+380
+00:46:40,940 --> 00:46:43,980
+reactions as a function of x هذه المسألة مركبة
+
+381
+00:46:43,980 --> 00:46:59,940
+يعني عشان أحلها بدي أعتبر أنا عندي P F
+
+382
+00:46:59,940 --> 00:47:07,940
+وعندي هنا R1 وعندي R2
+
+383
+00:47:09,430 --> 00:47:21,410
+وفي كمان distributed load
+
+384
+00:47:21,410 --> 00:47:26,650
+هذا يمكن أن يعتبر عبارة كأنه two beams one beam
+
+385
+00:47:39,690 --> 00:47:50,530
+R1' R2' R2'
+
+386
+00:47:50,550 --> 00:48:03,290
+R2' R2' R2' R2' R2' R2' R2' R2'
+
+387
+00:48:06,210 --> 00:48:11,850
+R2 W' هذه هي الـ beam الأساسي عليه concentrated load
+
+388
+00:48:11,850 --> 00:48:15,870
+at this point F ويعني distributed load all over
+
+389
+00:48:15,870 --> 00:48:21,370
+the beam هذه يكون أعتبره كأنه عبارة عن مجموع and
+
+390
+00:48:21,370 --> 00:48:25,710
+it is مجموع two beams one beam has a concentrated
+
+391
+00:48:25,710 --> 00:48:30,670
+load F another beam has a distributed load W
+
+392
+00:48:33,520 --> 00:48:43,300
+الآن أنا هرجع والـ total reaction R1 بيكون يساوي R1
+
+393
+00:48:43,300 --> 00:48:55,100
+prime زائد R1 double prime و R2 بيكون يساوي R2 prime
+
+394
+00:48:55,100 --> 00:48:57,860
+زائد R2 double prime
+
+395
+00:49:11,920 --> 00:49:21,060
+الحالة الأولى أرجع لبندقية الـ four هذه نحكي هنا
+
+396
+00:49:21,060 --> 00:49:25,120
+refer to
+
+397
+00:49:25,120 --> 00:49:34,540
+appendix Aتسعة ستة هاي A تسعة ستة عبارة تمثل beam
+
+398
+00:49:34,540 --> 00:49:40,760
+تحت تأثير حمل مركز على بعد A وطول الـ beam L
+
+399
+00:49:40,760 --> 00:49:49,020
+معطيني R واحد برايم =
+
+400
+00:49:49,020 --> 00:49:52,060
+FB/L
+
+401
+00:50:01,870 --> 00:50:13,930
+R2' FA/L مُعطيني
+
+402
+00:50:13,930 --> 00:50:21,390
+الـ Deflection YAB
+
+403
+00:50:36,830 --> 00:50:49,950
+YAB' أو يسميها Y prime هتكون
+
+404
+00:50:49,950 --> 00:51:01,490
+عبارة عن جزئين هذا الجزء اللي هو FBX/
+
+405
+00:51:01,490 --> 00:51:17,050
+6EIL في X تربيع زائد B تربيع ناقص L تربيع طبعا
+
+406
+00:51:17,050 --> 00:51:29,820
+هذا X بين A و B X أكبر من أو يساوي صفر وأقل من B و
+
+407
+00:51:29,820 --> 00:51:37,720
+بتساوي من B لـ C FA في
+
+408
+00:51:37,720 --> 00:51:48,360
+L - X / 6EIL في
+
+409
+00:51:48,360 --> 00:51:49
+
+445
+00:57:10,760 --> 00:57:23,590
+على 24EI في 2LX تربيع - X تكعيب - L تكعيب
+
+446
+00:57:23,590 --> 00:57:31,670
+هذا طبعاً X بين B و C أكبر من A و أصغر من L هذا هو
+
+447
+00:57:31,670 --> 00:57:38,530
+الـ total deflection
+
+448
+00:57:38,530 --> 00:57:43,910
+معناته
+
+449
+00:57:43,910 --> 00:57:48,210
+باستخدام الـ source position جزأنا المثلث هذا الـ
+
+450
+00:57:48,210 --> 00:57:53,250
+total loading عبارة عن مجموع two loading conditions
+
+451
+00:57:53,250 --> 00:57:56,170
+الـ loading condition الأولى هي عبارة عن
+
+452
+00:57:56,170 --> 00:57:59,950
+concentrated load at point B و الـ another loading
+
+453
+00:57:59,950 --> 00:58:02,630
+condition عبارة عن distributed load all over the
+
+454
+00:58:02,630 --> 00:58:10,050
+beam. المحاضرة
+
+455
+00:58:10,050 --> 00:58:13,110
+الجاي بنكمل
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/EruFwa8nhZA.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/EruFwa8nhZA.srt
new file mode 100644
index 0000000000000000000000000000000000000000..0337b2b46f727c62d1985c1d5209f7d59ef2248e
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/EruFwa8nhZA.srt
@@ -0,0 +1,2455 @@
+1
+00:00:04,880 --> 00:00:07,420
+بسم الله الرحمن الرحيم السلام عليكم ورحمة الله
+
+2
+00:00:07,420 --> 00:00:12,620
+اليوم هنكمل اللي هو fatigue failure due to dynamic
+
+3
+00:00:12,620 --> 00:00:16,240
+loading في المحاضرات السابقة حكينا عن fatigue
+
+4
+00:00:16,240 --> 00:00:22,280
+criteria for ductile materials اتعرفنا على الـ S
+
+5
+00:00:22,280 --> 00:00:28,080
+-N diagram. الـ S-N diagram. فرضنا أو حددنا مناطق
+
+6
+00:00:28,080 --> 00:00:32,930
+finite life و infinite life. كان في علاقة بين الـ
+
+7
+00:00:32,930 --> 00:00:36,530
+endurance limit والـ tensile strength بشكل عام الـ
+
+8
+00:00:36,530 --> 00:00:41,870
+S<sub>e</sub>' بصفر. نصف الـ S<sub>UT</sub> في
+
+9
+00:00:41,870 --> 00:00:45,270
+حالة الـ finite life. جيبنا معدلات في حالة كانت
+
+10
+00:00:45,270 --> 00:00:50,170
+العمر الـ part من واحد لألف cycle. جيبنا equation
+
+11
+00:00:50,640 --> 00:00:53,680
+وجيبنا equation في حالة كانت الـ life من ألف
+
+12
+00:00:53,680 --> 00:00:59,500
+لمليون cycle. وبعدين بدنا ندرس في الـ infinite ..
+
+13
+00:00:59,500 --> 00:01:03,060
+في الـ design .. fatigue design for infinite life
+
+14
+00:01:03,060 --> 00:01:07,580
+في الحالة دي كان يلزمنا نعمل تعديلات على الـ .. أو
+
+15
+00:01:07,580 --> 00:01:11,940
+تعديلات على الـ endurance limit. لأن الـ endurance
+
+16
+00:01:11,940 --> 00:01:15,560
+limit لما تم قياسه ..  أُقِيمَ قياسه لعينة معيارية
+
+17
+00:01:15,560 --> 00:01:19,520
+بمواصفات شكل أو مقطع هندسي معين، وفي surface finish
+
+18
+00:01:19,520 --> 00:01:23,850
+معين. والـ loading كان completely reversed bending.
+
+19
+00:01:23,850 --> 00:01:27,310
+لكن على أرض الواقع بيكونش نفس الـ surface finish
+
+20
+00:01:27,310 --> 00:01:30,570
+بيكونش نفس الـ .. الـ .. الـ ..  الـ loading
+
+21
+00:01:30,570 --> 00:01:36,030
+مختلف. القطعة ممكن تكون مدورة، ممكن تكون غير مدورة. درجة الحرارة، reliability، كل هذه العوامل لازم
+
+22
+00:01:36,030 --> 00:01:40,450
+نعمل لها modification factor. عشان هيك حكينا S<sub>e</sub>
+
+23
+00:01:40,450 --> 00:01:43,150
+بالساوية K<sub>a</sub> K<sub>b</sub> K<sub>c</sub> K<sub>d</sub> K<sub>e</sub> K<sub>f</sub> في S<sub>e</sub>'
+
+24
+00:01:43,150 --> 00:01:48,730
+.
+
+25
+00:01:53,010 --> 00:01:56,690
+بعدين أخدنا الحالة اللي بتكون عندي اللي هو الـ
+
+26
+00:01:56,690 --> 00:02:03,010
+general fluctuating case. حسبنا الـ alternating
+
+27
+00:02:03,010 --> 00:02:07,310
+stress والـ mean stress. وبعدين we apply design
+
+28
+00:02:07,310 --> 00:02:10,290
+theory. اللي هي modified Goodman theory والـ Gerber
+
+29
+00:02:10,290 --> 00:02:13,190
+theory والـ Soderberg والـ ASME elliptic for
+
+30
+00:02:13,190 --> 00:02:17,770
+fatigue design for yielding. we apply اللي هو الـ
+
+31
+00:02:17,770 --> 00:02:24,140
+Langer line. بعدين أخدنا حالة أكثر عمومية أنه الـ
+
+32
+00:02:24,140 --> 00:02:26,840
+loading ممكن يكون multiple loading conditions. ممكن
+
+33
+00:02:26,840 --> 00:02:30,020
+يكون عندك axial loading مع torsion مع .. مع
+
+34
+00:02:30,020 --> 00:02:35,960
+bending. في الحالة هذه بنحسب .. حسبنا alternating
+
+35
+00:02:35,960 --> 00:02:40,940
+stress والـ mid-range stress.
+
+36
+00:02:40,940 --> 00:02:43,720
+بعدين أخدنا الـ .. الـ .. اللي هو σ<sub>a</sub>' و
+
+37
+00:02:43,720 --> 00:02:46,560
+σ<sub>m</sub>' وapply الـ design theories اللي
+
+38
+00:02:46,560 --> 00:02:49,240
+ذكرناها سابقا. اللي هم الـ Good .. المدفعة
+
+39
+00:02:49,240 --> 00:02:52,430
+Goodman والـ Gerber والـ ASME elliptic والـ Soderberg.
+
+40
+00:02:52,430 --> 00:02:57,670
+حللنا مجموعة من الأمثلة for ductile materials.
+
+41
+00:02:57,670 --> 00:03:01,050
+اليوم هنكمل في fatigue criteria for brittle
+
+42
+00:03:01,050 --> 00:03:07,590
+materials. في حالة الـ brittle materials احنا عشان
+
+43
+00:03:07,590 --> 00:03:15,090
+نعمل design criteria. كان يكون لنا curve. هنا عندي
+
+44
+00:03:15,090 --> 00:03:21,580
+الـ σ<sub>m</sub> على الـ x axis والـ σ<sub>a</sub> على
+
+45
+00:03:21,580 --> 00:03:30,700
+الـ y axis. في حالة brittle materials الـ design
+
+46
+00:03:30,700 --> 00:03:36,060
+theory it will depend on
+
+47
+00:03:36,060 --> 00:03:36,640
+two curves.
+
+48
+00:03:49,330 --> 00:03:51,690
+إذا كان الـ σ<sub>a</sub> والـ σ<sub>m</sub>
+
+49
+00:03:51,690 --> 00:03:56,350
+موجبتين هنكون في الـ first quadrant. إذا كانت الـ
+
+50
+00:03:56,350 --> 00:03:59,150
+σ<sub>m</sub> سالبة والـ σ<sub>a</sub>
+
+51
+00:03:59,150 --> 00:04:02,310
+دائما موجبة. الـ σ<sub>m</sub> ممكن
+
+52
+00:04:02,310 --> 00:04:05,790
+تكون موجبة أو سالبة. إذا كانت الـ σ<sub>m</sub> سالبة
+
+53
+00:04:05,790 --> 00:04:08,970
+يعني هنكون في الربع الثاني. في حال تكون في الربع
+
+54
+00:04:08,970 --> 00:04:16,690
+الأول. في design criteria هنا عندي S<sub>UT</sub> وهنا عندي S<sub>e</sub>
+
+55
+00:04:19,180 --> 00:04:24,100
+في حال كنا في الـ first quadrant. الـ fatigue في الـ
+
+56
+00:04:24,100 --> 00:04:27,900
+criteria follows concave upward. concave upward
+
+57
+00:04:27,900 --> 00:04:33,440
+Smith-Dillon equation. اللي هي given by this
+
+58
+00:04:33,440 --> 00:04:38,120
+equation. المعادلة هذه لأن هذا concave up curve
+
+59
+00:04:38,120 --> 00:04:44,910
+بين الـ S<sub>UT</sub> والـ S<sub>e</sub>. الـ S<sub>a</sub> في الحالة هذه S<sub>a</sub>
+
+60
+00:04:44,910 --> 00:04:57,470
+على S<sub>e</sub> = 1 - S<sub>m</sub>/S<sub>UT</sub>  على 1
+
+61
+00:04:57,470 --> 00:05:03,450
++ S<sub>m</sub>/S<sub>UT</sub>. طبعا هذا الـ loading line بتاعنا
+
+62
+00:05:03,450 --> 00:05:15,600
+هذا الـ load line. إن هي اللي هتكون الـ σ<sub>m</sub> والـ
+
+63
+00:05:15,600 --> 00:05:26,160
+σ<sub>a</sub>. هذه S<sub>m</sub> وهذه S<sub>a</sub>. طبعا
+
+64
+00:05:26,160 --> 00:05:29,160
+هذه المعادلة في حالة إحنا كنا واقعين على الـ failure
+
+65
+00:05:29,160 --> 00:05:35,720
+line. لكن لو حطينا factor of safety حيصير عند هذه
+
+66
+00:05:35,720 --> 00:05:44,900
+حيصير N σ<sub>a</sub>/S<sub>e</sub> = 1 - N σ<sub>m</sub>
+
+67
+00:05:44,900 --> 00:05:55,180
+/S<sub>UT</sub> على 1 + N σ<sub>m</sub>/S<sub>UT</sub>. هذا في الـ
+
+68
+00:05:55,180 --> 00:06:00,300
+first quadrant. في الـ second quadrant أو خلينا نجد
+
+69
+00:06:00,300 --> 00:06:04,960
+نقطة التقاطع هذه. لأن نقطة التقاطع اللي هي خط الـ
+
+70
+00:06:04,960 --> 00:06:09,040
+loading line مع الـ failure line اللي هي تُعطى
+
+71
+00:06:09,040 --> 00:06:19,320
+بمعادلة S<sub>m</sub> وS<sub>a</sub>. والـ slope للـ load line = R. لسه وS<sub>a</sub>
+
+72
+00:06:19,320 --> 00:06:26,780
+على S<sub>m</sub> بتكون
+
+73
+00:06:26,780 --> 00:06:34,430
+الـ S<sub>a</sub> اللي هي هذه تعتبر علاقة S<sub>a</sub> = R S<sub>UT</sub>
+
+74
+00:06:34,430 --> 00:06:38,390
++ S<sub>e</sub>/2 في (-1) + الجذر التربيعي ل 1
+
+75
+00:06:38,390 --> 00:06:43,850
++ 4R S<sub>UT</sub> S<sub>e</sub>  على R S<sub>UT</sub> + S<sub>e</sub><sup>2</sup>
+
+76
+00:06:43,850 --> 00:06:48,670
+والـ R رح ينعطينا = S<sub>a</sub>/S<sub>m</sub>. هذا طبعا في الـ
+
+77
+00:06:48,670 --> 00:06:52,570
+first quadrant. في الـ second quadrant الـ failure
+
+78
+00:06:52,570 --> 00:06:56,890
+criteria is described by a linear line. هذا الـ
+
+79
+00:06:56,890 --> 00:07:07,480
+line. الـ slope بتاع الخط هذا slope of
+
+80
+00:07:07,480 --> 00:07:14,700
+the failure line بيساوي
+
+81
+00:07:14,700 --> 00:07:19,400
+الـ slope of
+
+82
+00:07:19,400 --> 00:07:29,150
+failure line of failure curve and first quadrant
+
+83
+00:07:29,150 --> 00:07:33,310
+عند
+
+84
+00:07:33,310 --> 00:07:42,810
+النقطة اللي هي صفر وS<sub>e</sub>. يعني عند النقطة هذه لأن
+
+85
+00:07:42,810 --> 00:07:50,130
+based on this principle. هتكون عندي معادلة اللي هي
+
+86
+00:07:50,130 --> 00:07:51,330
+second line.
+
+87
+00:07:59,540 --> 00:08:11,820
+اللي هي S<sub>a</sub> هتكون تساوي S<sub>e</sub> + S<sub>e</sub> -
+
+88
+00:08:11,820 --> 00:08:20,740
+S<sub>e</sub>/S<sub>UT</sub> - 1. طبعا الـ load line هذا الـ
+
+89
+00:08:20,740 --> 00:08:24,640
+load line تاني. هذا الـ load line.
+
+90
+00:08:29,270 --> 00:08:35,770
+هذه النقطة هتكون S<sub>m</sub> وهذا S<sub>a</sub>.
+
+91
+00:08:54,500 --> 00:08:57,360
+طب في الـ first quadrant الـ σ<sub>a</sub> والـ
+
+92
+00:08:57,360 --> 00:08:59,720
+σ<sub>m</sub> both positive. في الـ second quadrant
+
+93
+00:08:59,720 --> 00:09:04,300
+σ<sub>a</sub> is positive و σ<sub>m</sub> is negative. لأن
+
+94
+00:09:04,300 --> 00:09:10,560
+Table A-24 في الكتاب بيعطينا الخواص الميكانيكية للـ
+
+95
+00:09:10,560 --> 00:09:14,460
+grey cast iron. من ضمن الخواص اللي هي الـ endurance
+
+96
+00:09:14,460 --> 00:09:21,600
+limit. إذا بنروح على Table A-24 اللي
+
+97
+00:09:21,600 --> 00:09:22,100
+هو هذا.
+
+98
+00:09:28,500 --> 00:09:32,140
+معطين different grades of grey cast iron. اللي هو
+
+99
+00:09:32,140 --> 00:09:35,440
+cast iron عشرين، خمسة وعشرين، ثلاثين، خمسة وثلاثين،
+
+100
+00:09:35,440 --> 00:09:39,860
+أربعين، خمسين، ستين. ومعطين الـ tensile strength والـ
+
+101
+00:09:39,860 --> 00:09:43,320
+compressive strength. الـ S<sub>UC</sub> والـ shear modulus
+
+102
+00:09:43,320 --> 00:09:51,260
+الـ S .. S .. rupture. S<sub>RU</sub> والـ modulus of
+
+103
+00:09:51,260 --> 00:09:55,380
+elasticity in tension وin torsion والـ endurance
+
+104
+00:09:55,380 --> 00:09:56,100
+limit.
+
+105
+00:10:02,600 --> 00:10:09,880
+معطى خواص ثانية طبعا.
+
+106
+00:10:09,880 --> 00:10:19,420
+الـ endurance limit اللي مُعطى في الـ Table A-24 الـ
+
+107
+00:10:19,420 --> 00:10:23,100
+endurance limit اللي معطى في الـ Table A-24 الـ
+
+108
+00:10:23,100 --> 00:10:28,360
+already includes الـ K<sub>a</sub> والـ K<sub>b</sub>. الـ endurance
+
+109
+00:10:28,360 --> 00:10:33,780
+limit given in Table A-24 already includes الـ K<sub>a</sub> والـ
+
+110
+00:10:33,780 --> 00:10:37,660
+K<sub>b</sub>. الـ K<sub>a</sub> اللي هو الـ modification factor for
+
+111
+00:10:37,660 --> 00:10:41,060
+the surface finish والـ K<sub>b</sub> الـ modification factor
+
+112
+00:10:41,060 --> 00:10:42,140
+for size.
+
+113
+00:10:45,110 --> 00:10:49,610
+والـ average value K<sub>c</sub> for axial and torsional
+
+114
+00:10:49,610 --> 00:10:54,370
+loading is 0.9. طبعا في حالة bending بتكون الـ K<sub>c</sub>
+
+115
+00:10:54,370 --> 00:10:59,750
+بيساوي واحد. يعني إحنا في حالة الـ cast iron هنستخدم
+
+116
+00:10:59,750 --> 00:11:05,110
+Table A-24. من Table A-24 بنطلع الـ S .. S .. بنطلع اللي
+
+117
+00:11:05,110 --> 00:11:12,980
+هو الـ S<sub>UT</sub> والـ S<sub>UC</sub> وبنطلع الـ S<sub>e</sub>'. S<sub>e</sub>'
+
+118
+00:11:12,980 --> 00:11:16,340
+already متضمن فيها اللي هو الـ surface finish
+
+119
+00:11:16,340 --> 00:11:20,680
+factor والـ size factor. اللي هو إن في حالة bending
+
+120
+00:11:20,680 --> 00:11:24,780
+load بتكون الـ K<sub>c</sub> = 1. في حالة axial أو
+
+121
+00:11:24,780 --> 00:11:32,200
+torsion load. الـ K<sub>c</sub> هنحطها تسعة من عشرة. نشوف
+
+122
+00:11:32,200 --> 00:11:32,980
+ونحل المثال.
+
+123
+00:11:50,490 --> 00:11:56,130
+A grade thirty grey cast iron. يعني عندي حديد سكَب
+
+124
+00:11:56,130 --> 00:12:06,930
+اللي هو cast iron grade ثلاثين.
+
+125
+00:12:09,610 --> 00:12:13,710
+is subjected to a load applied to a one point by
+
+126
+00:12:13,710 --> 00:12:17,450
+three seven inch cross-section link with a one
+
+127
+00:12:17,450 --> 00:12:20,330
+fourth inch diameter hole drilled in the center.
+
+128
+00:12:20,330 --> 00:12:30,150
+يبين ده شكل. هنا عندي قطعة معدنية مستطيلة المقطع.
+
+129
+00:12:30,150 --> 00:12:32,950
+بتاعها مستطيل. سماكة القطعة ثلاثة على ثمانية انش.
+
+130
+00:12:32,950 --> 00:12:40,470
+وعرض القطعة واحد انش. وفي force, tension force F وفي
+
+131
+00:12:40,470 --> 00:12:52,410
+هنا في النص ثقب قطر ربع انش. قطر ثقب ربع انش. The
+
+132
+00:12:52,410 --> 00:12:56,870
+surfaces are machined. الأسطح machined.
+
+133
+00:13:02,640 --> 00:13:05,980
+in the neighborhood of the hole. على مقربة من الثقب.
+
+134
+00:13:05,980 --> 00:13:10,580
+what is the factor of safety guarding against
+
+135
+00:13:10,580 --> 00:13:13,660
+fatigue failure under the following
+
+136
+00:13:13,660 --> 00:13:19,640
+conditions. بده الـ factor of safety against failure
+
+137
+00:13:19,640 --> 00:13:22,200
+في الحالات التالية. الحالة الأولى.
+
+138
+00:13:25,700 --> 00:13:30,100
+الـ load الـ F =
+
+139
+00:13:30,100 --> 00:13:38,700
+ألف pound steady. steady.
+
+140
+00:13:38,700 --> 00:13:42,820
+يعني ثابتة. يعني في الحالة هذه هتكون عندي الـ F
+
+141
+00:13:42,820 --> 00:13:51,700
+<sub>a</sub> = 0 والـ F<sub>m</sub> = ألف pound.
+
+142
+00:13:51,700 --> 00:13:54,120
+بده الـ factor of safety.
+
+143
+00:14:04,810 --> 00:14:12,670
+يعني .. يعني هذه النقطة هتكون طبعا.
+
+144
+00:14:12,670 --> 00:14:16,230
+عشان أحسب الـ stress .. أول شيء طبعا خلينا أول شيء
+
+145
+00:14:16,230 --> 00:14:21,730
+نطلع .. نطلع الخواص الميكانيكية. أول شيء هو cast iron
+
+146
+00:14:21,730 --> 00:14:26,310
+أول شيء هو cast iron. بمعناه هنروح على الـ Table A-24
+
+147
+00:14:26,310 --> 00:14:29,450
+هو
+
+148
+00:14:29,450 --> 00:14:30,390
+grade 30.
+
+149
+00:14:33,870 --> 00:14:38,430
+جريد ثلاثين. معناته
+
+150
+00:14:38,430 --> 00:14:48,830
+الـ S<sub>UT</sub> نروح على الـ Table A-24 ستكون الـ S<sub>UT</sub> =
+
+151
+00:14:48,830 --> 00:14:53,050
+31 كيلو pound per square inch. 31
+
+152
+00:14:53,050 --> 00:15:01,550
+كيلو pound per square inch. والـ S<sub>UC</sub> 109
+
+153
+00:15:05,160 --> 00:15:17,620
+بس هو 109 كيلو pound per square inch والـ
+
+154
+00:15:17,620 --> 00:15:23,020
+الـ endurance limit عندي الـ S<sub>e</sub>' 14 والـ
+
+155
+00:15:23,020 --> 00:15:28,940
+S<sub>e</sub>' 14
+
+156
+00:15:28,940 --> 00:15:31,780
+كيلو pound per square inch.
+
+157
+00:15:39,450 --> 00:15:45,430
+طيب نرجع لمسألتنا. عرفنا الخواص الميكانيكية
+
+158
+00:15:45,430 --> 00:15:49,990
+الآن.
+
+159
+00:16:07,700 --> 00:16:10,860
+الآن الـ cross-section الـ area .. الـ area بتاعة الـ
+
+160
+00:16:10,860 --> 00:16:17,900
+cross-section المقطع هنا هيكون لو
+
+161
+00:16:17,900 --> 00:16:22,820
+أُخِذَ مقطع عند الثقب.
+
+162
+00:16:38,760 --> 00:16:45,680
+هذه ثلاثة على ثمانية انش.
+
+163
+00:16:45,680 --> 00:16:55,020
+وهذه واحد انش. كلها وهذه
+
+164
+00:16:55,020 --> 00:17:05,480
+ربع انش. معناته
+
+165
+00:17:05,480 --> 00:17:06,160
+هذه ستكون
+
+166
+00:17:24,220 --> 00:17:31,460
+هتكون 1 - 0.25 × 0.75 / 2 = 0.3
+
+167
+00:17:31,460 --> 00:17:40,340
+سبعة خمسة انش. 0.375 انش. معناته مساحة
+
+168
+00:17:40,340 --> 00:17:43,320
+الـ net cross-sectional area هتكون مساحة المستطيل
+
+169
+00:17:43,320 --> 00:17:51,800
+هذا زائد المستطيل هذا. الـ area بتاعة المقطع هتساوي
+
+170
+00:17:53,210 --> 00:17:58,230
+اللي هو ثلاثة على ثمانية ×
+
+171
+00:17:58,230 --> 00:18:03,370
+أو
+
+172
+00:18:03,370 --> 00:18:06,930
+المستطيل هذا كله ناقص المستطيل الصغير اللي هو
+
+173
+00:18:06,930 --> 00:18:16,390
+ثلاثة على ثمانية × واحد ناقص
+
+174
+00:18:16,390 --> 00:18:17,590
+ربع.
+
+175
+00:18:39,620 --> 00:18:45,300
+وبتطلع 0.28125
+
+176
+00:18:45,300 --> 00:18:54,400
+اتنين خمسة انش مربع. معناته
+
+177
+00:18:54,400 --> 00:19:00,620
+الـ mean stress σ<sub>a</sub> هتكون طبعا صفر
+
+178
+00:19:00,620 --> 00:19:06,500
+والـ σ<sub>m</sub> اللي هو الـ nominal هتكون طبعا F<sub>m</sub>
+
+179
+00:19:09,230 --> 00:19:19,290
+F<sub>m</sub> على الـ .. على الـ .. على الـ area. F<sub>m</sub> اللي هي ألف
+
+180
+00:19:19,290 --> 00:19:26,390
+على الـ area اللي هي 0.28125
+
+181
+00:19:26,390 --> 00:19:29,950
+خمسة. طبعا لو دي حوالي كيل
+
+223
+00:26:55,910 --> 00:27:06,490
+هتكون عندي ثلاثة
+
+224
+00:27:06,490 --> 00:27:11,730
+هذا point
+
+225
+00:27:11,730 --> 00:27:17,990
+المطلوب الأول، المطلوب الثاني من نفس الـ factor of
+
+226
+00:27:17,990 --> 00:27:21,230
+safety في حال كان الـ load is repeatedly applied
+
+227
+00:27:24,970 --> 00:27:31,750
+المطلوب الثاني بـ .. الـ load repeatedly applied
+
+228
+00:27:31,750 --> 00:27:37,310
+يعني بتغير بين zero و maximum value  الـ F
+
+229
+00:27:37,310 --> 00:27:46,310
+minimum  بساوي zero والـ F maximum بساوي ألف
+
+230
+00:27:46,310 --> 00:27:51,470
+pound في الحلقة دي هنحس أنه هيطلع عند الـ F mean
+
+231
+00:27:52,900 --> 00:28:01,220
+بساوي F alternating بساوي ألف على اتنين بيطلع
+
+232
+00:28:01,220 --> 00:28:08,540
+خمسمئة pound بالحساب
+
+233
+00:28:08,540 --> 00:28:20,390
+أنا KF هسه واحد زائد Q في KT ناقص واحد، الـ Q في
+
+234
+00:28:20,390 --> 00:28:23,290
+حالة الـ cast iron نعتبرها إيه؟ بساوي اتنين من
+
+235
+00:28:23,290 --> 00:28:27,970
+عشرة، حتة واحدة زائد اتنين من عشرة في KT اللي هي
+
+236
+00:28:27,970 --> 00:28:35,590
+٢.٤٥ ناقص واحد، حتطلع
+
+237
+00:28:48,790 --> 00:28:58,730
+اتنين، نقل اتنين تسعة ستكون
+
+238
+00:28:58,730 --> 00:29:07,530
+دي sigma a سواء sigma M سواء KF في
+
+239
+00:29:07,530 --> 00:29:11,190
+اللي
+
+240
+00:29:11,190 --> 00:29:17,280
+هي F mean أو F alternating على الـ area، يعني هتكون
+
+241
+00:29:17,280 --> 00:29:23,280
+الكافي عندي ١.٢٩ في الـ FM ٥٠٠ والـ
+
+242
+00:29:23,280 --> 00:29:29,680
+A عندي ٢.٢٨١٢
+
+243
+00:29:29,680 --> 00:29:30,760
+خمسة
+
+244
+00:29:35,840 --> 00:29:42,420
+عندي ١.٢٩ في خمسمئة تقسيم ٢.
+
+245
+00:29:42,420 --> 00:29:50,820
+٢٨١٢ خمسة بساوي تطلع ٢
+
+246
+00:29:50,820 --> 00:29:56,120
+.٩
+
+247
+00:29:56,120 --> 00:30:01,600
+ثلاثة kilo pound per square inch الآن بنجي بنعمل
+
+248
+00:30:01,600 --> 00:30:02,400
+plot هنا
+
+249
+00:30:05,290 --> 00:30:10,890
+هتكون نقطة هذه اللي
+
+250
+00:30:10,890 --> 00:30:16,050
+هي عندك ٢.٢٩٣ و ٢.
+
+251
+00:30:16,050 --> 00:30:18,690
+٢٩٣ احنا في first quadrant هذا الـ
+
+252
+00:30:18,690 --> 00:30:29,040
+load line هذا الـ load line في الحالة هذه R بساوي
+
+253
+00:30:29,040 --> 00:30:37,040
+sigma a على sigma m بساوي واحد في حال أنا كنت في الـ
+
+254
+00:30:37,040 --> 00:30:49,340
+first quadrant بستخدم المعادلة اللي هي SA بساوي
+
+255
+00:30:49,340 --> 00:30:53,620
+RSUT زائد SE
+
+256
+00:31:00,910 --> 00:31:08,790
+زائد SE على اتنين في ناقص واحد زائد جزر التربيع
+
+257
+00:31:08,790 --> 00:31:24,510
+لواحد زائد أربعة RSUT SE على RSUT زائد SE
+
+258
+00:31:24,510 --> 00:31:31,270
+لكل تربيع، لحظة أن احنا الـ SE لحد ثاني ما جبناهاش
+
+259
+00:31:31,270 --> 00:31:36,130
+احنا حكينا الـ KA و الـ KB included، معناته هتكون
+
+260
+00:31:36,130 --> 00:31:45,010
+عند الـ SE هتكون ساوي KA KB SE prime هذه included
+
+261
+00:31:45,010 --> 00:31:50,730
+في KC يعني هتكون عندي أنا already طلعت اللي هي SE
+
+262
+00:31:50,730 --> 00:31:57,170
+prime اللي هي أربعة في KC تسعة من عشرة، أنا هكون
+
+263
+00:31:57,170 --> 00:32:04,890
+أربعة في تسعة، وناشرة بيطلع
+
+264
+00:32:04,890 --> 00:32:12,050
+إثناش .٦ kilo pound per square inch معناته
+
+265
+00:32:12,050 --> 00:32:19,490
+الـ SA هتكون ساوي الـ R عندي واحد، الـ SUT عندي
+
+266
+00:32:19,490 --> 00:32:29,340
+واحد، ثلاثين زائد إثناش .٦ على اتنين في ناقص
+
+267
+00:32:29,340 --> 00:32:35,240
+واحد زائد جزر التربيع لواحد زائد أربعة R اللي هي
+
+268
+00:32:35,240 --> 00:32:40,320
+واحد في الـ SUT واحد، ثلاثين في الـ SE إثناش .
+
+269
+00:32:40,320 --> 00:32:47,840
+ستة على اللي هي واحد، ثلاثين زائد إثناش .٦
+
+270
+00:32:47,840 --> 00:32:50,120
+لكل تربيع
+
+271
+00:32:59,970 --> 00:33:09,090
+هتطلع أربعة في واحد، ثلاثين في إثناش .٦
+
+272
+00:33:09,090 --> 00:33:16,250
+تقسيم ثلاثة
+
+273
+00:33:16,250 --> 00:33:20,670
+في ثلاثين .٦ تقسيم
+
+274
+00:33:23,040 --> 00:33:34,440
+ستة، يساوي زائد واحد تحت الجزر، المهم بنحسبها تطلع
+
+275
+00:33:34,440 --> 00:33:42,800
+عندنا الاش بنحسب الـ SA، الـ
+
+276
+00:33:42,800 --> 00:33:45,600
+SA هتطلع عندي سبعة، أربعة، ستة، ثلاثة
+
+277
+00:33:49,150 --> 00:33:54,890
+kilo pound per square inch ومنها بنحسب الـ factor of
+
+278
+00:33:54,890 --> 00:34:01,850
+safety أنه هيكون ساوي SA على Sigma A، SA اللي
+
+279
+00:34:01,850 --> 00:34:10,470
+هي سبعة .٦٣ على Sigma
+
+280
+00:34:10,470 --> 00:34:16,090
+A اللي هي احنا حسبناها ٢.٢٩٣
+
+281
+00:34:16,090 --> 00:34:16,890
+ثلاثة
+
+282
+00:34:29,380 --> 00:34:34,700
+تطلع ثلاثة، بكون ثلاثة، اتنين، ثمانية، ثلاثة، بكون
+
+283
+00:34:34,700 --> 00:34:38,440
+ثلاثة، اتنين، ثمانية، الـ factor of safety هذه الحالة
+
+284
+00:34:38,440 --> 00:34:41,960
+الثانية، الـ
+
+285
+00:34:41,960 --> 00:34:46,560
+case الثالثة، الـ
+
+286
+00:34:46,560 --> 00:34:53,840
+case الثالثة، الـ load fluctuates between minus one
+
+287
+00:34:53,840 --> 00:34:58,180
+thousand and three hundred pounds، الحالة الثالثة
+
+288
+00:35:12,150 --> 00:35:19,630
+الحالة الثالثة، الـ load بترجح بين ناقص ألف و
+
+289
+00:35:19,630 --> 00:35:31,510
+ثلاثمية pound، يعني F minimum، F
+
+290
+00:35:31,510 --> 00:35:40,780
+minimum بيصبح ناقص ألف pound، و F maximum بساوي
+
+291
+00:35:40,780 --> 00:35:49,420
+ثلاثمية pound، معناته الـ F mean هتكون ساوي ناقص
+
+292
+00:35:49,420 --> 00:35:58,420
+ألف زائد ثلاثمية على اتنين، يعني ناقص سبعمية على
+
+293
+00:35:58,420 --> 00:36:05,960
+اتنين، ناقص ثلاثمية و خمسين pound، والـ F alternating
+
+294
+00:36:08,200 --> 00:36:17,820
+هيكون ثلاثمية ناقص ناقص ألف على اتنين، يعني هيكون
+
+295
+00:36:17,820 --> 00:36:30,540
+ألف، ثلاثمية على اتنين، ستمية و خمسين pound، من
+
+296
+00:36:30,540 --> 00:36:40,070
+هنا بنحسب الـ sigma M، ساوي KF في FM على الـ Area
+
+297
+00:36:40,070 --> 00:36:46,930
+الكاف، الرودي احنا حسبنا ١.٢٩ في
+
+298
+00:36:46,930 --> 00:36:59,830
+الـ FM ثلاثمية وخمسين، سالب ثلاثمية وخمسين، ع
+
+299
+00:36:59,830 --> 00:37:06,390
+الـ Area، على ٢.٢٨١٢ خمسة
+
+300
+00:37:07,430 --> 00:37:16,630
+هتكون سالب واحد
+
+301
+00:37:16,630 --> 00:37:26,390
+.٢٩ في ثلاثمية و خمسين تقسيم ٢.
+
+302
+00:37:26,390 --> 00:37:30,910
+٢٨١٢ خمسة، بيطلع ١.
+
+303
+00:37:30,910 --> 00:37:36,270
+ستمية و خمسين، ناقص واحد kilo pound per square
+
+304
+00:37:36,270 --> 00:37:45,290
+inch، الـ Sigma alternating هتكون ساوي KF في F
+
+305
+00:37:45,290 --> 00:37:54,510
+alternating على الـ area، أو بساوي Sigma M، بساوي
+
+306
+00:37:54,510 --> 00:38:06,070
+Sigma M على FM في F alternating، هي هي، هي هتكون
+
+307
+00:38:06,920 --> 00:38:07,460
+١
+
+308
+00:38:07,460 --> 00:38:19,780
+.٦٠٥
+
+309
+00:38:41,440 --> 00:38:45,560
+تطلع ٢.٩٨١٢، ٢.٩
+
+310
+00:38:45,560 --> 00:38:54,940
+ثمانية واحد kilo pound per square inch، نجي نعمل
+
+311
+00:38:54,940 --> 00:39:02,060
+plot، طبعا عند الـ sigma mean سالب، sigma mean سالب
+
+312
+00:39:02,060 --> 00:39:07,080
+اللي
+
+313
+00:39:07,080 --> 00:39:12,780
+هي ناقص واحد .ستمية وخمسين، وانا في الـ
+
+314
+00:39:12,780 --> 00:39:18,640
+second quadrant، و الـ sigma alternating اللي هي
+
+315
+00:39:18,640 --> 00:39:23,600
+٢.٩٨١، طبعا هذا الـ load line
+
+316
+00:39:23,600 --> 00:39:29,220
+وهذا
+
+317
+00:39:29,220 --> 00:39:37,720
+الـ failure line، هذا هتكون S alternating، وهذا هتكون
+
+318
+00:39:40,230 --> 00:39:50,770
+S M، و الـ R سيكون سيجما alternating على سيجما M
+
+319
+00:39:50,770 --> 00:39:57,150
+بساوي اللي هو ٢.٩٨١ على
+
+320
+00:39:57,150 --> 00:40:05,290
+ناقص ١.٦٠٥، عشان
+
+321
+00:40:05,290 --> 00:40:08,810
+نحسب، احنا في second quadrant، ستكون الـ SA
+
+322
+00:40:18,750 --> 00:40:29,330
+الـ الـ SA بتساوي
+
+323
+00:40:29,330 --> 00:40:33,570
+SE زائد
+
+324
+00:40:33,570 --> 00:40:41,370
+SE على SUT ناقص واحد
+
+325
+00:40:45,570 --> 00:40:55,430
+في SM، طبعا
+
+326
+00:40:55,430 --> 00:41:06,710
+الـ R مش ساوي SA برضه على SM، يعني
+
+327
+00:41:06,710 --> 00:41:10,610
+مش
+
+328
+00:41:10,610 --> 00:41:22,150
+ساوي R، معناته عند الـ SM بساوي SA على R، يعني هذه
+
+329
+00:41:22,150 --> 00:41:31,550
+المعادلة اللي حاسبها عندي، SA بساوي SE زائد SE على
+
+330
+00:41:31,550 --> 00:41:41,290
+SUT ناقص واحد في SA على R، ومنها بحسب الـ SA
+
+331
+00:41:42,260 --> 00:41:47,960
+بحسب في الـ SA، هتطلع الـ
+
+332
+00:41:47,960 --> 00:41:54,500
+SA هتطلع ثمانيتاش ونص كيلو
+
+333
+00:41:54,500 --> 00:41:59,640
+pound per square inch، معناته هيكون عندي ثمانيتاش و
+
+334
+00:41:59,640 --> 00:42:05,920
+نص كيلو pound per square inch، معناته الفاكرة الـ
+
+335
+00:42:05,920 --> 00:42:13,160
+safety N هيكون الساوي SA على الـ Sigma A، الـ SA
+
+336
+00:42:13,160 --> 00:42:19,980
+اللي هي اللي هي ثمانيتاش
+
+337
+00:42:19,980 --> 00:42:26,000
+و نص على الـ Sigma A ٢.٩٨١
+
+338
+00:42:26,000 --> 00:42:32,220
+ثمانيتاش
+
+339
+00:42:32,220 --> 00:42:38,760
+و نص تقسيم ٢.٩٨١، تطلع ستة
+
+340
+00:42:38,760 --> 00:42:39,560
+.٢
+
+341
+00:42:43,700 --> 00:42:49,300
+ستة bond، اتنين صفر ستة، factor of ستة، هيكون
+
+342
+00:42:49,300 --> 00:42:50,820
+خلصنا المسألة
+
+343
+00:43:52,480 --> 00:43:58,200
+نكمل على موضوع جديد، نشوف اللي هو مصطلح دي اللي هو
+
+344
+00:43:58,200 --> 00:44:03,080
+torsional fatigue strength، احنا
+
+345
+00:44:03,080 --> 00:44:06,540
+ناخد بعض الملاحظات، أولاً إذا عندي steady stress
+
+346
+00:44:06,540 --> 00:44:09,280
+component has no effect on the endurance limit for
+
+347
+00:44:09,280 --> 00:44:12,660
+torsional loading if the material، إذا كان عندي الـ
+
+348
+00:44:12,660 --> 00:44:18,260
+torsional load is steady، مش هيكون له تأثير على الـ
+
+349
+00:44:18,260 --> 00:44:22,960
+endurance limit، في حال الـ material كانت دكتايل
+
+350
+00:44:22,960 --> 00:44:30,140
+polished، خالية من الخدوش، ومقطعتها مدور، يعني في
+
+351
+00:44:30,140 --> 00:44:35,840
+حال كانت الـ material دكتايل، polished، خالية من
+
+352
+00:44:35,840 --> 00:44:44,680
+الخدوش، ومقطعتها مدور، في الحالة هذه، وكان الـ .. الـ
+
+353
+00:44:44,680 --> 00:44:45,880
+.. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ ..
+
+354
+00:44:45,880 --> 00:44:46,020
+الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ
+
+355
+00:44:46,020 --> 00:44:46,480
+.. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ
+
+356
+00:44:46,480 --> 00:44:47,120
+الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ
+
+357
+00:44:47,120 --> 00:44:47,420
+.. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ
+
+358
+00:44:47,420 --> 00:44:52,360
+.. الـ .. الـ .. الـ .. الـ .. الـ ..
+
+359
+00:44:52,360 --> 00:44:55,960
+الـ ..
+
+360
+00:44:55,960 --> 00:44:57,900
+الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ
+
+361
+00:44:57,900 --> 00:44:57,940
+.. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ ..
+
+362
+00:44:57,940 --> 00:44:57,980
+الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ
+
+363
+00:44:57,980 --> 00:44:58,040
+الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ
+
+364
+00:44:58,040 --> 00:45:03,640
+.. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ .. الـ ..
+
+365
+00:45:03,640 --> 00:45:08,540
+الـ ..
+
+366
+00:45:13,090 --> 00:45:17,850
+for less than perfect surfaces، يعني الـ surface ما
+
+367
+00:45:17,850 --> 00:45:25,310
+كان polished، وممكن كان فيه notches، the modified
+
+368
+00:45:25,310 --> 00:45:27,670
+godman line is more reasonable، الحالة دي نستخدم
+
+369
+00:45:27,670 --> 00:45:32,610
+modified godman line، for pure torsion cases، في حالة
+
+370
+00:45:32,610 --> 00:45:36,410
+عندي الـ mechanical member متعرض لـ pure torsion
+
+371
+00:45:36,410 --> 00:45:42,570
+بنستخدم الـ KC ٠.٥٩ to convert normal endurance
+
+372
+00:45:42,570 --> 00:45:45,430
+strength to sheer endurance strength، يعني أنا عندي
+
+373
+00:45:45,430 --> 00:45:49,930
+SE، وفي
+
+374
+00:45:49,930 --> 00:45:54,670
+عندي SES
+
+375
+00:45:54,670 --> 00:45:57,730
+عشان احسب الـ SES
+
+376
+00:46:02,670 --> 00:46:08,990
+الـ SE هتكون ٠.٥٩ في الـ SE الـ normal
+
+377
+00:46:08,990 --> 00:46:15,770
+for shear، أن احنا .. احنا عندنا في حالة الـ tensile
+
+378
+00:46:15,770 --> 00:46:21,130
+loading، عندنا الـ SUT، في حالة الـ shear عندنا يقابلها
+
+379
+00:46:21,130 --> 00:46:29,130
+اللي هو الـ shear ultimate strength، SSU، الـ SSU
+
+380
+00:46:31,280 --> 00:46:41,020
+بساوي ٠.٦٧ SUT، يعني
+
+381
+00:46:41,020 --> 00:46:45,680
+في حالة torsional fatigue loading it is reasonable
+
+382
+00:46:45,680 --> 00:46:51,360
+to use modified Godman line، استخدم KC to convert
+
+383
+00:46:51,360 --> 00:46:55,160
+from normal endurance strength to sheer endurance
+
+384
+00:46:55,160 --> 00:47:00,760
+strength، هتكون الـ SE S بساوي ٠.٥٩ SE، و
+
+385
+00:47:00,760 --> 00:47:05,320
+convert الـ .. يعني بدك تحول من ultimate tensile
+
+386
+00:47:05,320 --> 00:47:08,880
+strength لـ sheer ultimate strength اللي هو SSU
+
+387
+00:47:08,880 --> 00:47:10,560
+بساوي ٠.٦٧ SUT
+
+388
+00:47:14,630 --> 00:47:21,290
+طيب نيجي للـ combinations of loading modes for
+
+389
+00:47:21,290 --> 00:47:24,590
+combined loading condition، combined loading يعني
+
+390
+00:47:24,590 --> 00:47:27,790
+ممكن يكون عندي axial loading مع bending loading مع
+
+391
+00:47:27,790 --> 00:47:31,750
+torsional loading، هنستخدم الـ distortion energy
+
+392
+00:47:31,750 --> 00:47:37,850
+theorem to combine them، يعني هنحسب von Mises
+
+393
+00:47:37,850 --> 00:47:42,350
+stress، so one can alternating von Mises أو mid
+
+394
+00:47:42,350 --> 00:47:43,390
+range von Mises
+
+395
+00:47:46,760 --> 00:47:54,320
+then we apply KF to each type of stress، في حالة الـ
+
+396
+00:47:54,320 --> 00:47:58,100
+load factor، use KC جوة المعادلة
+
+397
+00:48:01,730 --> 00:48:05,270
+The torsion load factor Kc equal ٠.٥٩
+
+398
+00:48:05,270 --> 00:48:08,190
+is inherently included in the von Mises equations
+
+399
+00:48:08,190 --> 00:48:13,550
+سنستخدم المعادلات التالية، sigma prime A هي von
+
+400
+00:48:13,550 --> 00:48:16,290
+Mises alternating، وعندي معادلة sigma prime M هي
+
+401
+00:48:16,290 --> 00:48:23,130
+von Mises mean، طبعا تفاصيلها بتساوي KF due to
+
+402
+00:48:23,130 --> 00:48:27,670
+bending، في sigma alternating due to bending زائد KF
+
+403
+00:48:27,670 --> 00:48:31,910
+KF due to axial loading، في sigma alternating due
+
+404
+00:48:31,910 --> 00:48:34,910
+to axial loading على ٠.٨٥ الكل تربيع
+
+405
+00:48:34,910 --> 00:48:40,730
+يعني الـ course ده بيحتوي كل الـ normal stress
+
+445
+00:51:58,680 --> 00:52:02,360
+الـ sigma prime maximum بالسواء sigma prime a زي
+
+446
+00:52:02,360 --> 00:52:05,740
+sigma prime m يعني اختصار .. يعني تقريبا مش .. مش
+
+447
+00:52:05,740 --> 00:52:08,620
+يومية صح بس يعني إلى حد ما بتعطينا دقة مناسبة
+
+448
+00:52:08,620 --> 00:52:11,800
+اللي هي sigma prime maximum بالسواء sigma prime a
+
+449
+00:52:11,800 --> 00:52:22,900
+زي sigma prime m طيب
+
+450
+00:52:22,900 --> 00:52:24,860
+خلينا نحل example
+
+451
+00:52:33,130 --> 00:52:43,150
+A rotating shaft is made of 42 x 4 mm AISI 1018
+
+452
+00:52:43,150 --> 00:52:48,550
+cold drawn steel. أولا الشيء الـ material بتاعته الـ
+
+453
+00:52:48,550 --> 00:52:58,870
+material AISI 1018 cold drawn steel
+
+454
+00:53:05,980 --> 00:53:20,380
+الـ shaft عبارة عن أنبوب، الـ tube قطرها
+
+455
+00:53:20,380 --> 00:53:26,180
+الخارجي 42 ملي
+
+456
+00:53:26,180 --> 00:53:34,200
+و الـ thickness بتاعها 4 ملي
+
+457
+00:53:38,800 --> 00:53:44,740
+and has a six millimeter diameter hole.
+
+458
+00:53:44,740 --> 00:53:55,920
+transverse يعني فيه hole قطر
+
+459
+00:53:55,920 --> 00:54:01,320
+الـ hole ستة
+
+460
+00:54:01,320 --> 00:54:01,640
+millimeter
+
+461
+00:54:08,060 --> 00:54:13,060
+estimate the factor of safety guarding against
+
+462
+00:54:13,060 --> 00:54:18,880
+fatigue and static failures using the Gerber and
+
+463
+00:54:18,880 --> 00:54:21,740
+Langer failure criterion for the following loading
+
+464
+00:54:21,740 --> 00:54:24,720
+conditions. من ناحية الـ factor of safety guarding
+
+465
+00:54:24,720 --> 00:54:28,760
+against fatigue loading, guarding against yielding
+
+466
+00:54:28,760 --> 00:54:32,500
+طبعا في حالة الـ fatigue loading هستخدم الـ gerber
+
+467
+00:54:32,500 --> 00:54:43,660
+criteria. أول حالة case a: the shaft. Case a: the
+
+468
+00:54:43,660 --> 00:54:47,220
+shaft is subjected to a completely reversed torque
+
+469
+00:54:47,220 --> 00:54:54,860
+completely reversed torque يعني عندي الـ torque
+
+470
+00:54:54,860 --> 00:54:59,320
+minimum بالسواء
+
+471
+00:54:59,320 --> 00:55:05,380
+ناقص 120 نيوتن متر، والـ
+
+472
+00:55:05,380 --> 00:55:09,760
+torque maximum هو 120 نيوتن متر، يعني
+
+473
+00:55:09,760 --> 00:55:16,840
+بتروح بين negative و positive in phase with a
+
+474
+00:55:16,840 --> 00:55:21,360
+completely reversed bending. in phase with a
+
+475
+00:55:21,360 --> 00:55:25,080
+completely reversed bending. وعندي bending كمان M
+
+476
+00:55:25,080 --> 00:55:33,600
+minimum so minus 150 نيوتن متر، والـ bending
+
+477
+00:55:33,600 --> 00:55:43,030
+maximum M maximum so 150 نيوتن متر. المعنى
+
+478
+00:55:43,030 --> 00:55:51,430
+في الحالة هذه هيكون عنده الـ tau أو الـ T mean بتساوي
+
+479
+00:55:51,430 --> 00:55:58,940
+صفر، الـ T alternating بالسواء 120 نيوتن
+
+480
+00:55:58,940 --> 00:56:06,820
+متر، ونفس الشيء الـ M mean بالسواء صفر، والـ M
+
+481
+00:56:06,820 --> 00:56:17,620
+alternating بالسواء 150 نيوتن متر. طعم
+
+482
+00:56:17,620 --> 00:56:22,570
+الزمن، أنا عندي two stresses، وعندي stress
+
+483
+00:56:22,570 --> 00:56:26,070
+concentration لأن هنروح على الجداول
+
+484
+00:56:58,690 --> 00:57:10,090
+هنستخدم اللي هو appendix A16، آه A16، هاي A16 فيه
+
+485
+00:57:10,090 --> 00:57:15,210
+عندي tube اللي لها الـ القطر الخارجي والقطر الداخلي و
+
+486
+00:57:15,210 --> 00:57:21,990
+فيه ثقب مستعرض، فيه ثقب مستعرض. هذا في حالة الـ .. الـ
+
+487
+00:57:21,990 --> 00:57:22,530
+.. الـ bending
+
+488
+00:57:25,760 --> 00:57:32,520
+الآن احنا، المعطيات اللي معطينا إياها، الـ A نطلع
+
+489
+00:57:32,520 --> 00:57:40,660
+الشكل الـ A اللي
+
+490
+00:57:40,660 --> 00:57:47,580
+هي الـ الثقب اللي هي 6 ميلي، والـ D capital
+
+491
+00:57:47,580 --> 00:57:48,820
+الـ D capital
+
+492
+00:57:52,540 --> 00:57:57,640
+اللي هي 42 ملي، والقطر الداخلي d small
+
+493
+00:57:57,640 --> 00:58:01,040
+دي
+
+494
+00:58:01,040 --> 00:58:05,460
+capital أو القطر الخارجي، القطر الداخلي هيكون 42
+
+495
+00:58:05,460 --> 00:58:08,720
+ناقص 4 ناقص 4 هيكون 42
+
+496
+00:58:08,720 --> 00:58:15,720
+ناقص 8 يعني هيكون 34 ملي متر
+
+497
+00:58:23,030 --> 00:58:30,770
+هو الـ Sigma O بتساوي
+
+498
+00:58:30,770 --> 00:58:44,070
+M على الـ section modulus على الـ Z net الـ
+
+499
+00:58:44,070 --> 00:58:46,130
+M الـ
+
+500
+00:58:49,840 --> 00:58:57,160
+في الجدول تحت معطيني، عندي a على d، بالزمن a على D
+
+501
+00:58:57,160 --> 00:59:14,160
+capital اللي هي 6 على 42 تطلع
+
+502
+00:59:14,160 --> 00:59:15,560
+0.143
+
+503
+00:59:24,400 --> 00:59:27,580
+ومعطينا different values for D على D، أنا D على D
+
+504
+00:59:27,580 --> 00:59:34,060
+أكم عنده D على D الفعلية اللي عندي D small على D
+
+505
+00:59:34,060 --> 00:59:38,720
+capital اللي هي 34 على 42
+
+506
+00:59:38,720 --> 00:59:51,980
+34 على 42 تطلع
+
+507
+00:59:51,980 --> 01:00:04,940
+0.81 تقريبا
+
+508
+01:00:04,940 --> 01:00:13,980
+من
+
+509
+01:00:13,980 --> 01:00:18,580
+الجدول هذا هحسب الـ a والـ kt اللي أنا عندي اللي هو
+
+510
+01:00:18,580 --> 01:00:23,520
+a على d اللي هو 0.143 اللي هي هتكون في
+
+511
+01:00:23,520 --> 01:00:38,700
+المنطقة هذه هي
+
+512
+01:00:38,700 --> 01:00:47,780
+عندي هنا 0.143 و D small على D
+
+513
+01:00:47,780 --> 01:00:49,200
+كابيتال هنا عندي 0.9
+
+514
+01:00:52,610 --> 01:00:57,290
+وهنا عندي 0.6، أنا الـ 0.8 جاي بين
+
+515
+01:00:57,290 --> 01:01:03,410
+الاثنين دول، والـ 0.8 جاي فين؟ بينهم
+
+516
+01:01:03,410 --> 01:01:08,130
+معناته محتاج اعمل double interpolation، double
+
+517
+01:01:08,130 --> 01:01:11,890
+interpolation، يعني الـ interpolation الأول يعني
+
+518
+01:01:11,890 --> 01:01:16,530
+هجيب عن d capital، دي small عن d capital عن 0.9
+
+519
+01:01:16,530 --> 01:01:18,030
+من عشرة دي small
+
+520
+01:01:21,030 --> 01:01:26,790
+على دي capital، هي عندي 0.9 وهي عندي 0.6
+
+521
+01:01:26,790 --> 01:01:35,890
+من عشرة هحسب
+
+522
+01:01:35,890 --> 01:01:42,470
+الـ a والـ
+
+523
+01:01:42,470 --> 01:01:42,910
+kt
+
+524
+01:01:52,610 --> 01:01:56,910
+طيب الـ interpolation الـ a الأولى اللي هتكون خلانا
+
+525
+01:01:56,910 --> 01:02:01,870
+ندعم الواحدة، والباقية تعملوها لحالكو، الـ a اللي
+
+526
+01:02:01,870 --> 01:02:08,110
+جاي هنا يعني، فاندي واحدة هنا وواحدة هنا، طبعا الـ
+
+527
+01:02:08,110 --> 01:02:09,130
+table A 16
+
+528
+01:02:21,860 --> 01:02:25,120
+هتكون الـ a الأولانية اللي عند الـ a عند الـ 0.9 و
+
+529
+01:02:25,120 --> 01:02:29,480
+العشرة هتكون
+
+530
+01:02:29,480 --> 01:02:38,400
+بتساوي 0.82 زائد
+
+531
+01:02:38,400 --> 01:02:45,480
+0.
+
+532
+01:02:45,480 --> 01:02:48,580
+143
+
+533
+01:02:49,370 --> 01:02:56,310
+ناقص 0.125، خدنا
+
+534
+01:02:56,310 --> 01:03:00,470
+نعمل الـ interpolation، نعطيك المعادلة العامة Y
+
+535
+01:03:00,470 --> 01:03:12,630
+بيساوي Y1 زائد X ناقص X1 على X2 ناقص X
+
+536
+01:03:12,630 --> 01:03:19,640
+1 في Y2 ناقص Y1، والأصل بتاع الـ
+
+537
+01:03:19,640 --> 01:03:24,660
+interpolation جاي، أنا عندي بيكون curve عندي هي
+
+538
+01:03:24,660 --> 01:03:33,020
+النقطة هين هي X، وهي Y هين عندي X1 وهين Y1
+
+539
+01:03:33,020 --> 01:03:39,700
+هي النقطة X2 وهين Y2، بحاول اعمل
+
+540
+01:03:39,700 --> 01:03:43,680
+approximation للـ curve بين نقطتين كـ linear، هذه
+
+541
+01:03:43,680 --> 01:03:46,620
+النقطة هتكون X وY
+
+542
+01:03:48,770 --> 01:03:55,690
+السلوك بتاع الخط ده هيكون y2-x2 على y1-x1 بيساوي
+
+543
+01:03:55,690 --> 01:04:03,750
+y-y1 على x-x1 وبعدين تعمل شغل جبر وبتحسب، تحكي الـ
+
+544
+01:04:03,750 --> 01:04:09,710
+y اللي الكمية اللي في النص، بيساوي y1 زائد x-x1 على
+
+545
+01:04:09,710 --> 01:04:16,790
+y2-y1 على x2-x1، طيب based on this equation هتكون
+
+546
+01:04:16,790 --> 01:04:25,980
+الـ a عندي 0.9 بتساوي اللي هي Y1، 0.8
+
+547
+01:04:25,980 --> 01:04:32,540
+2 زائد 0.143 ناقص 0.1
+
+548
+01:04:32,540 --> 01:04:40,180
+25 على x2 اللي هي 0.15
+
+549
+01:04:40,180 --> 01:04:46,220
+ناقص 0.125 في y2 اللي هي
+
+550
+01:04:46,220 --> 01:04:55,580
+0.79 ناقص 0.82، يعني عند
+
+551
+01:04:55,580 --> 01:05:01,580
+0.9، والـ a عند 0.6 من عشرة تنحسب اللي هي
+
+552
+01:05:01,580 --> 01:05:12,150
+هتكون 0.82 على
+
+553
+01:05:12,150 --> 01:05:20,130
+أي حال، الـ a هتكون لحظة
+
+554
+01:05:20,130 --> 01:05:24,970
+الـ a لا تتغير بين الـ 0.9 والـ 0.6 هتكون
+
+555
+01:05:24,970 --> 01:05:31,290
+نفسها عند الـ 0.8، الـ KT
+
+556
+01:05:33,260 --> 01:05:39,840
+عند الـ 0.9 بتساوي 2.41
+
+557
+01:05:39,840 --> 01:05:47,100
+2.41 زائد 0.143
+
+558
+01:05:47,100 --> 01:05:52,500
+ناقص 0.125 على 0.15
+
+559
+01:05:52,500 --> 01:05:58,120
+ناقص 0.125، عند الـ 0.9 من عشرة
+
+560
+01:05:58,120 --> 01:06:05,040
+اللي هي 2.39-2.41 وهي بنحسبها والـ
+
+561
+01:06:05,040 --> 01:06:14,020
+الـ KT عند الـ 0.6 من 10 بتطلع
+
+562
+01:06:15,660 --> 01:06:20,120
+اللي هي 2.32، 2.32 زائد 0.143 ناقص 0.1
+
+563
+01:06:20,120 --> 01:06:25,180
+25 على 0.15 ناقص 0.1
+
+564
+01:06:25,180 --> 01:06:31,380
+25 في اللي هي 2.29 ناقص
+
+565
+01:06:31,380 --> 01:06:38,680
+2.32، من اتنين، حسبنا الـ a الـ a
+
+566
+01:06:45,630 --> 01:07:09,110
+اللي هي عند الـ 0.8 نحسبها، طيب
+
+567
+01:07:09,110 --> 01:07:14,090
+عشان أخش أسلس، نحسب يعني أنا صار عندي قيمتين، وعندي
+
+568
+01:07:14,090 --> 01:07:20,110
+هنا قيمة للـ a، وعندي الـ KT عند 0.9 لها قيمة
+
+569
+01:07:20,110 --> 01:07:26,230
+والـ KT عند 0.6 لها قيمة، الآن أنا بدي الـ
+
+570
+01:07:26,230 --> 01:07:30,830
+D على D اللي هي 0.8، D على D اللي بين
+
+571
+01:07:30,830 --> 01:07:37,500
+الاثنين دول اللي هي 0.8، بعمل second
+
+572
+01:07:37,500 --> 01:07:44,380
+interpolation عشان أحسب الـ a هنا وأحسب الـ kt from
+
+573
+01:07:44,380 --> 01:07:56,180
+اللي هو second interpolation، find
+
+574
+01:07:56,180 --> 01:08:00,320
+a
+
+575
+01:08:00,320 --> 01:08:15,980
+و kt، هيكون عندي الـ a كذا والـ kt كذا، طيب
+
+576
+01:08:15,980 --> 01:08:20,440
+نرجع،
+
+577
+01:08:20,440 --> 01:08:25,800
+الآن صارت أنا عارف الـ a و
+
+578
+01:08:25,800 --> 01:08:30,160
+الـ D capital معروفة والـ D small معروفة، معناته بحسب
+
+579
+01:08:30,160 --> 01:08:38,530
+الـ Z net، الـ Z net، الـ net section modulus Z net
+
+580
+01:08:38,530 --> 01:08:50,630
+بتساوي باي في أربعة على 32 D capital في
+
+581
+01:08:50,630 --> 01:08:56,950
+D أُس أربعة ناقص D small أُس أربعة
+
+582
+01:09:05,970 --> 01:09:13,870
+ومنها باحسب الـ sigma alternating
+
+583
+01:09:13,870 --> 01:09:23,710
+A هتكون بتساوي M على
+
+584
+01:09:23,710 --> 01:09:30,070
+Z net، خلينا نكمل نفس الجدول
+
+585
+01:09:38,300 --> 01:09:44,280
+في الجدول مقسم جزئية جزئية bending وجزئية torsion
+
+586
+01:09:44,280 --> 01:09:50,780
+حالة الـ torsion، اللي هو هذا الجدول، هروح احسب كمان
+
+587
+01:09:50,780 --> 01:09:57,620
+اللي هو الـ J net اللي هو الـ الـ الـ polar moment
+
+588
+01:09:57,620 --> 01:10:03,720
+of inertia للـ cross section، J net ده هنروح على
+
+589
+01:10:03,720 --> 01:10:04,220
+J net
+
+590
+01:10:07,430 --> 01:10:13,170
+بتساوي اللي هي باي في أربعة في
+
+591
+01:10:13,170 --> 01:10:18,210
+دي أُس أربعة ناقص
+
+592
+01:10:18,210 --> 01:10:23,830
+دي small أُس أربعة على 32
+
+593
+01:10:38,050 --> 01:10:44,790
+والـ tau alternating
+
+594
+01:10:44,790 --> 01:10:52,090
+nominal هتكون معطوبة، العلاقة اللي
+
+595
+01:10:52,090 --> 01:11:00,010
+هي T D capital على
+
+596
+01:11:00,010 --> 01:11:01,710
+2 J net
+
+597
+01:11:07,820 --> 01:11:14,180
+برضه من الجدول هذا .. من الجدول هذا أنا
+
+598
+01:11:14,180 --> 01:11:25,420
+a على d، أنا
+
+599
+01:11:25,420 --> 01:11:26,520
+هكون في المنطقة هذه
+
+600
+01:11:37,710 --> 01:11:42,270
+أنا عند الـ دي small على دي capital تمام، 0.8
+
+601
+01:11:42,270 --> 01:11:51,430
+موجودة، بعمل interpolation عشان أحسب الـ a هنا و
+
+602
+01:11:51,430 --> 01:11:56,130
+أحسب الـ kt، الـ
+
+603
+01:11:56,130 --> 01:12:02,330
+a والـ kt يعني
+
+604
+01:12:02,330 --> 01:12:04,830
+معناته بالزمن أحسب kts
+
+605
+01:12:07,790 --> 01:12:16,410
+بنحسبها من الجدول by linear interpolation، طيب،
+
+606
+01:12:16,410 --> 01:12:21,370
+الآن هذه كلها parameters هندسية
+
+607
+01:12:21,370 --> 01:12:29,490
+لأن صرت أنا عارف sigma AO و tau AO، بتروح للمعادلات
+
+608
+01:12:36,890 --> 01:12:57,550
+اللي هي الـ Von Mises equations، بدي
+
+609
+01:12:57,550 --> 01:12:58,070
+أحسب
+
+610
+01:13:09,950 --> 01:13:14,610
+Sigma prime alternating و Sigma prime mean، احنا في
+
+611
+01:13:14,610 --> 01:13:18,790
+الحالة هذه الـ Sigma prime mean هتكون صفر، حتى عند
+
+612
+01:13:18,790 --> 01:13:21,550
+الـ Sigma prime alternating، الـ Sigma prime
+
+613
+01:13:21,550 --> 01:13:26,000
+alternating هتكون كـ  في sigma a للـ bending، في sigma a للـ
+
+614
+01:13:26,000 --> 01:13:30,040
+bending زي كـ في sigma a للـ bending في 0.85
+
+615
+01:13:30,040 --> 01:13:34,080
+زي 3 في KFS torsion في tau alternating
+
+616
+01:13:34,080 --> 01:13:39,560
+torsion، الكل تربيع، قص نص، احنا مش عندنا axial load، إنّه
+
+617
+01:13:39,560 --> 01:13:45,920
+بس bending، معناته هتكون عندنا sigma
+
+618
+01:13:45,920 --> 01:13:49,700
+alternating
+
+619
+01:13:49,700 --> 01:13:58,100
+von Mises هتكون،  الـ Sigma alternating nominal
+
+620
+01:13:58,100 --> 01:14:12,700
+الكل تربيع زائد 3 في KFS torsion في Tau
+
+621
+01:14:12,700 --> 01:14:18,620
+alternating nominal، الكل تربيع، كل هذا أُس نص
+
+622
+01:14:24,090 --> 01:14:31,990
+طيب احنا، رودنا حسبنا sigma a nominal وحسبنا tau a
+
+623
+01:14:31,990 --> 01:14:40,890
+nominal، ضايل احسب KF و KFS، الـ KF بيساوي
+
+624
+01:14:40,890 --> 01:14:51,930
+1 زائد Q في KT ناقص 1، الـ KT already حسبتها
+
+625
+01:14:51,930 --> 01:14:58,570
+ضايل أحسب الـ Q، الـ Q من شكل 16، شكل 16
+
+626
+01:14:58,570 --> 01:15:07,610
+هذا
+
+627
+01:15:07,610 --> 01:15:12,670
+الشكل الـ
+
+628
+01:15:12,670 --> 01:15:16,890
+Notch عندنا يعني
+
+629
+01:15:16,890 --> 01:15:21,300
+أكبر الأربعة من الـ whole وال
+
+667
+01:20:28,160 --> 01:20:34,880
+على SE بالساوية واحد معناته الآن سيكون الساوية SE
+
+668
+01:20:34,880 --> 01:20:52,360
+على Sigma A Prime طيب
+
+669
+01:20:55,530 --> 01:21:00,370
+هذا الـfact of state guarding against yield، نروح
+
+670
+01:21:00,370 --> 01:21:05,730
+هنا للجداول، هذا الجدول لـGodman، هذا الجدول لـ
+
+671
+01:21:05,730 --> 01:21:11,070
+Gerber، أن حكينا الجدول هذا موجود لنقطة تقاطع هذه
+
+672
+01:21:11,070 --> 01:21:19,470
+الـGerber S
+
+673
+01:21:19,470 --> 01:21:29,400
+U، T، و S، E، وهي عندي sy
+
+674
+01:21:29,400 --> 01:21:37,540
+وهي الـload line، السطر
+
+675
+01:21:37,540 --> 01:21:40,560
+هذا بوجد له نقطة تقاطع بين هذا الـload line و
+
+676
+01:21:40,560 --> 01:21:48,040
+Gerber line، بوجد له SM و SA، السطر اللي بعده بوجد
+
+677
+01:21:48,040 --> 01:21:50,960
+له نقطة تقاطع، نقطة تقاطع
+
+678
+01:21:55,160 --> 01:21:58,740
+هنا حكينا احنا... احنا فش... ستكون نقطتنا هنا،
+
+679
+01:21:58,740 --> 01:22:03,940
+معناه نقطتنا هنا سيكون عندي الـ... هذا الـNF طبعا
+
+680
+01:22:03,940 --> 01:22:08,660
+الـNY سيكون
+
+681
+01:22:08,660 --> 01:22:18,520
+SY على Sigma A Prime
+
+682
+01:22:22,870 --> 01:22:27,410
+واضح سيكون الـny أكبر من الـnf، معناته من المتوقع
+
+683
+01:22:27,410 --> 01:22:31,630
+أنه يصير failure by fatigue قبل ما يصير failure by
+
+684
+01:22:31,630 --> 01:22:40,330
+yielding، هذا المطلوب الأول، المطلوب الثاني نرجع
+
+685
+01:22:45,670 --> 01:22:48,670
+The shaft is subjected to a pulsating torque
+
+686
+01:22:48,670 --> 01:22:52,410
+fluctuating from twenty لمية وستين نيوتن متر، and a
+
+687
+01:22:52,410 --> 01:22:59,090
+steady bending moment، case two، الحالة
+
+688
+01:22:59,090 --> 01:23:04,490
+الثانية، الحالة
+
+689
+01:23:04,490 --> 01:23:12,150
+الثانية، الشافت متعرض لـtorque بتغير الـtorque
+
+690
+01:23:12,150 --> 01:23:25,220
+الـT minimum بتساوي عشرين نيوتن متر، والـT
+
+691
+01:23:25,220 --> 01:23:35,360
+maximum بتساوي مئة وستين نيوتن متر، والـbending
+
+692
+01:23:35,360 --> 01:23:46,560
+moment is steady، يعني الـM بساوة M main بالساوية
+
+693
+01:23:46,560 --> 01:23:51,940
+150 نيوتن متر، معناته في الحالة هذه سيكون عندي الـ
+
+694
+01:23:51,940 --> 01:23:58,740
+tau main سيكون عشرين زائد مئة وستين على اثنين، يعني
+
+695
+01:23:58,740 --> 01:24:05,720
+تسعين نيوتن متر، الـT alternating سواء مئة وستين
+
+696
+01:24:05,720 --> 01:24:15,220
+ناقص عشرين على اثنين، سبعين نيوتن متر، والـM mean
+
+697
+01:24:15,220 --> 01:24:21,660
+سواء مئة وخمسين نيوتن متر، والـM alternating
+
+698
+01:24:21,660 --> 01:24:31,680
+بالساوية صفر، I follow the same procedure، أحسب sigma
+
+699
+01:24:31,680 --> 01:24:42,340
+prime alternating، نرجع للمعادلات اللي
+
+700
+01:24:42,340 --> 01:24:48,840
+هي KF للـbending طبعا
+
+701
+01:24:48,840 --> 01:24:54,000
+أنا في الحالة هذه ستكون هذه صفر، صفر ستكون تساوي
+
+702
+01:24:54,000 --> 01:24:57,040
+ثلاثة
+
+703
+01:25:00,360 --> 01:25:13,800
+كفاس في tau alternating nominal الكل تربيع، كله
+
+704
+01:25:13,800 --> 01:25:23,380
+تحت الجذر، والـsigma prime main ستكون تساوي كف
+
+705
+01:25:23,380 --> 01:25:26,620
+sigma
+
+706
+01:25:26,620 --> 01:25:37,700
+main nominal الكل تربيع، زائد ثلاثة في KFS تاو nominal
+
+707
+01:25:37,700 --> 01:25:43,540
+nominal الكل تربيع، الكل أس نص، يعني أنا عندي ستكون
+
+708
+01:25:43,540 --> 01:25:47,600
+عندي sigma alternating born mice sigma prime born
+
+709
+01:25:47,600 --> 01:25:54,920
+mice اللي أنا على فرق كتير عند هاي gear bar، هذه S U
+
+710
+01:25:54,920 --> 01:26:07,480
+T، وهذه S E، وهذه الـload، الـload line، أحسب
+
+711
+01:26:07,480 --> 01:26:18,720
+SM و S alternating، ومنها أحسب الـNF بالساوية
+
+712
+01:26:18,720 --> 01:26:29,850
+اللي هي SM على sigma M، وبرضه مستوى SA على sigma
+
+713
+01:26:29,850 --> 01:26:34,750
+A Prime، هذا
+
+714
+01:26:34,750 --> 01:26:46,470
+في حالة الفتيك، في حالة الـyielding، في
+
+715
+01:26:46,470 --> 01:26:47,390
+حالة الـyielding
+
+716
+01:26:50,660 --> 01:26:54,140
+أحسب الـSA بساوة R أسواع على واحدة زائد R، وبعدين
+
+717
+01:26:54,140 --> 01:26:59,740
+أحكي الـfactor of safety N بساوة SA على Sigma A
+
+718
+01:26:59,740 --> 01:27:03,020
+Prime، هيك بنكون حاليا، أنا طبعا السؤال طويل كثير
+
+719
+01:27:03,020 --> 01:27:08,070
+بتوقع أنكم تتابعوا الفيديو كويس، وتحلو المسائل
+
+720
+01:27:08,070 --> 01:27:12,070
+بالأرقام طبعا، هذا الـexample موجود في الكتاب، تقدر
+
+721
+01:27:12,070 --> 01:27:16,730
+تتبعه من الكتاب، وتقارنه بين الحل اللي أنا حلته و
+
+722
+01:27:16,730 --> 01:27:23,730
+حل الكتاب، يعني احنا هنكون متقاربين جدا من... من
+
+723
+01:27:23,730 --> 01:27:27,990
+بعض، احنا هيك بنكون تقريبا غطينا المادة الـmachine
+
+724
+01:27:27,990 --> 01:27:31,710
+design، واحد، حكينا أن الـcourse الـmachine design
+
+725
+01:27:31,710 --> 01:27:34,660
+اثنين، اللي هو سيكون الـdesign of mechanical
+
+726
+01:27:34,660 --> 01:27:38,240
+components، هنحكي عن design of shafts، عن design
+
+727
+01:27:38,240 --> 01:27:42,040
+of gears، عن design of springs، عن design of
+
+728
+01:27:42,040 --> 01:27:45,020
+screws، عن design of welding، عن design of
+
+729
+01:27:45,020 --> 01:27:53,600
+sprockets، الـ... الـdesign of pulleys، يعني هنت...
+
+730
+01:27:53,600 --> 01:27:56,900
+يعني سيكون شيء specific for specific components، دي
+
+731
+01:27:56,900 --> 01:27:57,260
+كل عالم
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/GdwYlgLJm0Y.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/GdwYlgLJm0Y.srt
new file mode 100644
index 0000000000000000000000000000000000000000..505bfe69abab883457077a97af00e9d6f7d5dcc4
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/GdwYlgLJm0Y.srt
@@ -0,0 +1,2701 @@
+
+1
+00:00:04,890 --> 00:00:07,630
+بسم الله الرحمن الرحيم السلام عليكم ورحمة الله
+
+2
+00:00:07,630 --> 00:00:10,970
+وبركاته اليوم هنستكمل  failures resulting from
+
+3
+00:00:10,970 --> 00:00:15,810
+static loading. المحاضرات الفاتة استعرضنا اللي هي
+
+4
+00:00:15,810 --> 00:00:22,030
+خارطة الطريق للـ .. للـ static .. للـ failure
+
+5
+00:00:22,030 --> 00:00:25,790
+criterion selection. حكينا أول شيء لازم نفحص نشوف
+
+6
+00:00:25,790 --> 00:00:30,600
+المادة هل هي ductile ولا brittle. الـ ductility or
+
+7
+00:00:30,600 --> 00:00:33,820
+brittleness is examined via الـ .. الـ .. الـ .. هو
+
+8
+00:00:33,820 --> 00:00:36,600
+الـ εf. إذا الـ εf أكبر من أو يساوي 0.05
+
+9
+00:00:36,600 --> 00:00:39,520
+معناته المادة is ductile. إذا الـ εf أقل
+
+10
+00:00:39,520 --> 00:00:42,360
+من 0.05 معناته المادة is brittle.
+
+11
+00:00:42,360 --> 00:00:47,980
+الآن الجهة هذه ductile, الجهة هذه إيش؟ brittle. أول
+
+12
+00:00:48,800 --> 00:00:51,720
+check for ductile material. I want to check إذا كان
+
+13
+00:00:51,720 --> 00:00:54,280
+الـ yield strength in tension بيستوي yield strength
+
+14
+00:00:54,280 --> 00:00:56,360
+in compression. إذا كان yield strength in tension
+
+15
+00:00:56,360 --> 00:01:00,500
+بيستوي yield strength in compression, معناته ياما
+
+16
+00:01:00,500 --> 00:01:04,300
+بدي أحصل على conservative calculations أو more
+
+17
+00:01:04,300 --> 00:01:07,040
+accurate, less conservative calculations. if I'm
+
+18
+00:01:07,040 --> 00:01:11,560
+interested in more conservative, less risky
+
+19
+00:01:11,560 --> 00:01:14,380
+calculations, ممكن أستخدم الـ maximum shear stress
+
+20
+00:01:14,380 --> 00:01:19,960
+theory. إذا أنا يعني إذا أنا في الـ .. الـ ..
+
+21
+00:01:19,960 --> 00:01:24,580
+اللي هي more accurate results, less conservative.
+
+22
+00:01:24,580 --> 00:01:27,840
+ممكن أستخدم اللي هي الـ distortion energy theory.
+
+23
+00:01:27,840 --> 00:01:33,320
+طيب السؤال بيطرح نفسه: طيب ما زال اللي هو الـ .. الـ
+
+24
+00:01:33,320 --> 00:01:36,220
+.. الـ .. الآن في حالة الـ conservative theories
+
+25
+00:01:36,220 --> 00:01:39,620
+عندها عنصر مخاطرة، الحسابات أقل، ليش ما أشتغل دائمًا
+
+26
+00:01:39,620 --> 00:01:43,910
+conservative؟ لأن أنا مثلاً أنا بدي أنتج من الـ ..
+
+27
+00:01:43,910 --> 00:01:47,710
+الـ mechanical part. بدي أنتج مثلاً عشر قطع، مئة قطع،
+
+28
+00:01:47,710 --> 00:01:51,970
+ألف قطع، الكمية هذه صغيرة، في الحالة هذه بفضل
+
+29
+00:01:51,970 --> 00:01:55,910
+أشتغل according to conservative calculations. لكن
+
+30
+00:01:55,910 --> 00:02:02,030
+أنا لو بدي أنتج .. أنتج قطع موجودة في السيارة مثلاً
+
+31
+00:02:02,030 --> 00:02:08,190
+بدي أعمل screw أو برغي. عدد البراغي في السيارة في
+
+32
+00:02:08,190 --> 00:02:12,270
+الـ .. في مثلاً عندي مئة برغي من نفس النوع، وافترض أن
+
+33
+00:02:12,270 --> 00:02:16,830
+الشركة بتنتج كل يوم عشرة آلاف سيارة، عشرة آلاف
+
+34
+00:02:16,830 --> 00:02:20,750
+ثلاثمئة خمسين ستين، فتخيل كم قطع هنتج! ملايين القطع.
+
+35
+00:02:20,750 --> 00:02:24,790
+معناته أنا لما تكون الـ calculation more
+
+36
+00:02:24,790 --> 00:02:28,910
+conservative, معناته هستخدم مواد أكثر، هستهلك مواد
+
+37
+00:02:28,910 --> 00:02:32,910
+أكثر، فالتكلفة هتكون بترتفع. في الحالة هذه، ألجأ
+
+38
+00:02:32,910 --> 00:02:36,970
+لاستخدم more accurate أو more accurate
+
+39
+00:02:38,240 --> 00:02:42,280
+calculations, أو فأستخدم مثلاً theories اللي هي more
+
+40
+00:02:42,280 --> 00:02:45,580
+accurate theories. في الحالات اللي بوفر في المواد و
+
+41
+00:02:45,580 --> 00:02:49,740
+في الـ materials. في حالة إنتاج huge mass .. mass
+
+42
+00:02:49,740 --> 00:02:54,690
+production. معناته في حالة ductile material وكانت الـ
+
+43
+00:02:54,690 --> 00:02:56,790
+yield strength in tension بيستوي yield strength in
+
+44
+00:02:56,790 --> 00:03:00,090
+compression, if I need conservative calculations, I
+
+45
+00:03:00,090 --> 00:03:02,770
+use the maximum shear stress theory. if I need more
+
+46
+00:03:02,770 --> 00:03:05,550
+accurate, less conservative calculations, I use the
+
+47
+00:03:05,550 --> 00:03:08,610
+distortion energy theory. الآن إذا كانت الـ yield
+
+48
+00:03:08,610 --> 00:03:10,570
+strength in tension بيستوي yield strength in
+
+49
+00:03:10,570 --> 00:03:13,210
+compression, بأستخدم ductile column theory. في حالة
+
+50
+00:03:13,210 --> 00:03:18,100
+الـ ductile material. الآن الجهة تمثل الـ brittle
+
+51
+00:03:18,100 --> 00:03:21,780
+material. إذا كانت الـ material brittle, if I want
+
+52
+00:03:21,780 --> 00:03:26,300
+conservative, less risky calculations, I use brittle
+
+53
+00:03:26,300 --> 00:03:31,500
+column theory. if I need more accurate, more
+
+54
+00:03:31,500 --> 00:03:36,200
+risky calculations, I use modified Mohr theory. الآن
+
+55
+00:03:36,200 --> 00:03:38,500
+حكينا عن الـ maximum normal stress theory, الـ
+
+56
+00:03:38,500 --> 00:03:40,420
+maximum .. الـ maximum normal stress theory بتحكي
+
+57
+00:03:40,420 --> 00:03:44,500
+أن الـ yielding أو الـ failure ببدأ لما الـ maximum
+
+58
+00:03:44,500 --> 00:03:47,900
+principal stress في الـ mechanical element بيكون
+
+59
+00:03:47,900 --> 00:03:51,120
+أكبر من أو يساوي الـ yield strength للـ material.
+
+60
+00:03:51,120 --> 00:03:54,740
+يعني الـ .. احنا الـ principal stresses بنحسبها من
+
+61
+00:03:54,740 --> 00:03:57,400
+مورسلك. بنحسب σ1, σ2, و σ3. يعني
+
+62
+00:03:57,400 --> 00:04:00,360
+إذا كان σ1 أكبر من أو يساوي σy بيصير عندي
+
+63
+00:04:00,360 --> 00:04:04,800
+yielding, بيصير عندي failure. الـ maximum طبعًا الـ
+
+64
+00:04:04,800 --> 00:04:06,820
+maximum normal stress theory is not conservative
+
+65
+00:04:06,820 --> 00:04:12,460
+in the fourth quadrant, لأن
+
+66
+00:04:12,460 --> 00:04:17,520
+الـ maximum normal stress theory ممكن تحكي لي أن الـ
+
+67
+00:04:17,520 --> 00:04:21,780
+part is not failing while actually it fails. يعني
+
+68
+00:04:21,780 --> 00:04:25,000
+بتحكي لي أن الـ part مش failure لكن في الواقع
+
+69
+00:04:25,000 --> 00:04:33,130
+failure. عشان هيك but يعني .. يعني أنا عن نفسي شخصيًا
+
+70
+00:04:33,130 --> 00:04:35,650
+وعالميًا ما بأستخدم الـ maximum normal stress theory
+
+71
+00:04:35,650 --> 00:04:40,510
+for .. for design calculations. الـ maximum shear
+
+72
+00:04:40,510 --> 00:04:43,490
+stress .. stress theory بتحكي أن الـ yielding ببدأ
+
+73
+00:04:43,490 --> 00:04:47,490
+لما الـ maximum shear stress .. الـ maximum shear
+
+74
+00:04:47,490 --> 00:04:51,070
+stress في stress element اللي هو بالحقيقة بتكون
+
+75
+00:04:51,070 --> 00:04:54,850
+أكبر من أو يساوي الـ maximum shear stress في tensile
+
+76
+00:04:54,850 --> 00:05:00,380
+test specimen. بمعنى أنه بيصير failure لما الـ τ
+
+77
+00:05:00,380 --> 00:05:04,400
+maximum تكون أكبر من أو تساوي σy / 2. واحنا في الـ
+
+78
+00:05:04,400 --> 00:05:06,480
+.. لما كنا عند multi-state of stress كنا نحسب
+
+79
+00:05:06,480 --> 00:05:10,140
+σ1 و σ2 و σ3 و نرتبهم. بيصير σ1
+
+80
+00:05:10,140 --> 00:05:13,220
+أكبر من σ2 أكبر من σ3. و الـ τ maximum
+
+81
+00:05:13,220 --> 00:05:17,560
+كان يساوي (σ1 - σ2) / 2. فـ according to
+
+82
+00:05:17,560 --> 00:05:20,960
+maximum shear stress theory بيكون عندي الـ .. الـ ..
+
+83
+00:05:21,740 --> 00:05:25,240
+τ maximum = (σ1 - σ3) / 2. بيصير failure لما τ maximum يكون أكبر من أو
+
+84
+00:05:25,240 --> 00:05:27,940
+يساوي σy / 2. أخذنا
+
+85
+00:05:27,940 --> 00:05:33,220
+two-D states of stress و رسمنا اللي هو inferior
+
+86
+00:05:33,220 --> 00:05:37,500
+contour لـ maximum shear stress theory. عندنا case
+
+87
+00:05:37,500 --> 00:05:41,240
+one. هذه case one: أن σa أكبر من σb أكبر من
+
+88
+00:05:41,240 --> 00:05:45,820
+صفر. يعني σa و σb موجبات. في الحالة هذه بيكون
+
+89
+00:05:45,820 --> 00:05:50,090
+عندي .. بيصير failure لما σa تكون أكبر من أو
+
+90
+00:05:50,090 --> 00:05:54,050
+تساوي σy. case two: أن σa موجبة و σb
+
+91
+00:05:54,050 --> 00:05:59,650
+سالبة. في الحالة هذه (σa - σb) بتكون
+
+92
+00:05:59,650 --> 00:06:05,410
+أكبر من أو تساوي σy. الـ case الثالثة: both σa
+
+93
+00:06:10,010 --> 00:06:14,030
+and σb are negative. بيصير failure لما σb
+
+94
+00:06:14,030 --> 00:06:19,400
+تكون أقل من أو تساوي -σy. if we compare الـ
+
+95
+00:06:19,400 --> 00:06:21,940
+maximum shear stress theory with empirical أو
+
+96
+00:06:21,940 --> 00:06:26,060
+experimental data, بنلاحظ أنه بتعطيني conservative
+
+97
+00:06:26,060 --> 00:06:29,640
+results. أن الـ maximum shear stress theory
+
+98
+00:06:29,640 --> 00:06:34,180
+predicts failure before actually it fails. عشان كده
+
+99
+00:06:34,180 --> 00:06:37,180
+بأسميها conservative theory. طبعًا في كل quadrant
+
+100
+00:06:37,180 --> 00:06:39,800
+سواء كان في الـ quadrant الأول أو الـ quadrant
+
+101
+00:06:39,800 --> 00:06:44,600
+الرابع. we predict failure before failure actually
+
+102
+00:06:44,600 --> 00:06:50,620
+happens. الآن اليوم هنحكي على نظرية جديدة اللي هي
+
+103
+00:06:50,620 --> 00:06:55,220
+distortion energy theory. distortion energy theory
+
+104
+00:06:55,220 --> 00:06:58,000
+distortion energy theory. في كثير من الكتب
+
+105
+00:06:58,000 --> 00:07:02,860
+بيستخدموا أسماء مختلفة لها. أسماء أخرى للنظرية في
+
+106
+00:07:02,860 --> 00:07:05,740
+كتب ثانية ممكن تلاحظوها، اللي هي octahedral shear
+
+107
+00:07:05,740 --> 00:07:06,540
+stress theory,
+
+108
+00:07:09,110 --> 00:07:13,770
+الـ shear energy theory. هذا اسم ثاني. اسم ثالث: Von
+
+109
+00:07:13,770 --> 00:07:18,950
+Mises Theory. اسم رابع: اللي هي Von Mises-Hencky
+
+110
+00:07:18,950 --> 00:07:22,370
+Theory. معناته هذه إذا تروح لمراجع ثانية ممكن
+
+111
+00:07:22,370 --> 00:07:26,090
+تلاحظوا فيها أسماء متداولة، أسماء مختلفة اللي هي
+
+112
+00:07:26,090 --> 00:07:29,330
+octahedral shear stress theory, shear energy theory,
+
+113
+00:07:29,330 --> 00:07:32,590
+Von Mises Theory, و Von Mises-Hencky Theory.
+
+114
+00:07:36,750 --> 00:07:43,070
+الآن تقديم أو تحضير للـ .. للـ theory هذا. أول ملاحظة:
+
+115
+00:07:43,070 --> 00:07:45,690
+لاحظوا: ductile materials stressed hydrostatically
+
+116
+00:07:45,690 --> 00:07:48,330
+exhibit yield strength greatly in excess of
+
+117
+00:07:48,330 --> 00:07:51,590
+expected values. يعني لو حطيت أنا قطعة تحت سطح
+
+118
+00:07:51,590 --> 00:07:58,550
+البحر، مكعب في مياه
+
+119
+00:08:04,990 --> 00:08:11,530
+hydrostatic stress. معناته بتتعرض
+
+120
+00:08:11,530 --> 00:08:23,090
+لضغط من كل الجهات. الآن
+
+121
+00:08:23,090 --> 00:08:25,690
+إذا بيكون الـ mechanical element، العالم افترض أنه
+
+122
+00:08:25,690 --> 00:08:30,030
+على شكل مكعب، متعرض
+
+123
+00:08:30,030 --> 00:08:33,030
+لـ hydrostatic pressure أو hydrostatic state of
+
+124
+00:08:33,030 --> 00:08:33,450
+stress.
+
+125
+00:08:36,120 --> 00:08:40,660
+معناته due to Poisson effect. لو أخدت الـ σ هذه
+
+126
+00:08:40,660 --> 00:08:43,740
+الـ σ هذه بتحاول إيش؟ تضغط، بتحاول تكبر الـ
+
+127
+00:08:43,740 --> 00:08:47,460
+dimensions في الاتجاهات الثانية الأخرى. الـ
+
+128
+00:08:47,460 --> 00:08:50,280
+σ هذه بتحاول تعكس الـ effect تاعتها. ده يعني هذه
+
+129
+00:08:50,280 --> 00:08:54,500
+بتحاول تتضغط زي هيك، وتكبر الجهة الثانية هذه.
+
+130
+00:08:54,500 --> 00:08:56,940
+بتحاول تتضغط هيك، وتكبر الجهة الثانية. فهذه بتعكس
+
+131
+00:08:56,940 --> 00:09:00,640
+هذه، وهذه بتعكس هذه. يعني بتعاكس، وفي بعض. فالـ
+
+132
+00:09:00,640 --> 00:09:04,180
+material بتتحمل yield strength عالي جدًا جدًا في
+
+133
+00:09:04,180 --> 00:09:10,850
+حالة الـ hydrostatic loading condition. معناته
+
+134
+00:09:10,850 --> 00:09:15,390
+ممكن أعتبر أنه في حالة hydrostatic loading
+
+135
+00:09:15,390 --> 00:09:18,790
+condition أن المادة ممكن تتحمل infinite state of
+
+136
+00:09:18,790 --> 00:09:21,350
+stress. يعني ممكن يكون الـ stress very very very
+
+137
+00:09:21,350 --> 00:09:30,730
+huge. وهذا بالحقيقة، هذا الآن الـ .. في الواقع ما بيكونش
+
+138
+00:09:30,730 --> 00:09:35,050
+الـ mechanical element under a pure hydrostatic
+
+139
+00:09:35,050 --> 00:09:38,810
+loading condition. ما بيكونش الـ σ زي هذه متساوية.
+
+140
+00:09:38,810 --> 00:09:43,330
+بيكون عندي σ1, σ2, و σ3. يعني
+
+141
+00:09:43,330 --> 00:09:47,010
+σ1 مختلفة قيمتها عن σ2, مختلفة عن σ3.
+
+142
+00:09:47,010 --> 00:09:51,030
+طالما أن σ1 و σ2 و σ3. الآن الـ due to
+
+143
+00:09:51,030 --> 00:09:54,190
+σ1 و σ2 و σ3, بيصير تشوه للمادة،
+
+144
+00:09:54,190 --> 00:09:57,750
+بيصير في عندي strain. الـ strain energy ممكن أقسمها
+
+145
+00:09:57,750 --> 00:10:04,150
+لجزئين: جزء بيعمل لي volume change, بيغير الحجم. إذا
+
+146
+00:10:04,150 --> 00:10:07,930
+أنا مضغطها من كل جهات، بيحاول إيش؟ يصغر حجمها. وجزء
+
+147
+00:10:07,930 --> 00:10:13,890
+الثاني بيحاول إيش؟ يشوهها، يغير الشكل، to distorted.
+
+148
+00:10:13,890 --> 00:10:19,710
+معناته strain energy ممكن تكون تاخذ شكلين: شكل
+
+149
+00:10:19,710 --> 00:10:23,790
+بيغير في الحجم، وجزء بيغير
+
+150
+00:10:23,790 --> 00:10:29,950
+بالشكل، اللي هو angular distortion energy. yielding
+
+151
+00:10:29,950 --> 00:10:34,710
+احنا حكينا: الجزئية بتغير الحجم هي جزئية due to
+
+152
+00:10:34,710 --> 00:10:38,730
+hydrostatic state of stress، وهذه ما بتعمل yielding.
+
+153
+00:10:38,730 --> 00:10:43,100
+yielding primarily is affected by the distortion
+
+154
+00:10:43,100 --> 00:10:48,440
+energy part, اللي هو الجزء اللي بيغير شكل الـ
+
+155
+00:10:48,440 --> 00:10:56,360
+mechanical part. الآن
+
+156
+00:10:56,360 --> 00:10:59,620
+الـ distortion energy failure theory بتحكي التالي:
+
+157
+00:10:59,620 --> 00:11:02,760
+بتحكي: yielding occurs, بتحكي yielding أو failure
+
+158
+00:11:02,760 --> 00:11:09,130
+بيصير لما الـ distortion energy في جزء من الـ  element
+
+159
+00:11:09,130 --> 00:11:15,710
+الـ mechanical تحت الدراسة تصل إلى distortion energy
+
+160
+00:11:15,710 --> 00:11:21,730
+في جزء من الـ  element للـ tensile test specimen
+
+161
+00:11:23,320 --> 00:11:26,320
+having the same material. معناته distortion energy
+
+162
+00:11:26,320 --> 00:11:29,000
+theory بتحكي أنه بيصير failure أو بيصير yielding
+
+163
+00:11:29,000 --> 00:11:33,800
+لما distortion strain energy per unit volume in
+
+164
+00:11:33,800 --> 00:11:38,160
+the mechanical element under study reaches the
+
+165
+00:11:38,160 --> 00:11:43,360
+distortion strain energy per unit volume of a
+
+166
+00:11:43,360 --> 00:11:46,600
+tensile test specimen of the same material. في
+
+167
+00:11:46,600 --> 00:11:49,520
+الحالة هذه بيصير إيش؟ عنده yielding أو بيصير
+
+168
+00:11:49,520 --> 00:11:54,730
+failure. أنا باين عندي هنا mechanical element، و آخذ
+
+169
+00:11:54,730 --> 00:11:58,030
+الـ principal state of stress element. يعني عندي هنا
+
+170
+00:11:58,030 --> 00:12:06,630
+σ1 وهنا σ2 وهنا σ3. ممكن
+
+171
+00:12:06,630 --> 00:12:14,330
+أحكي هذا بيساوي التالي: this element, الـ equivalent
+
+172
+00:12:14,330 --> 00:12:17,810
+للـ element هذا و الـ element هذا. الـ
+
+173
+00:12:17,810 --> 00:12:23,340
+element هذا متعرض لـ σ average. σ average و
+
+174
+00:12:23,340 --> 00:12:32,820
+σ average. σ average = (σ1
+
+175
+00:12:32,820 --> 00:12:40,220
++ σ2 + σ3) / 3. زائد
+
+176
+00:12:40,220 --> 00:12:43,880
+another element وهو عبارة عن (σ1 -
+
+177
+00:12:43,880 --> 00:12:48,840
+σ average). وهنا (σ2 - σ average).
+
+178
+00:12:49,790 --> 00:12:53,770
+وهنا (σ3 - σ average). يعني لو
+
+179
+00:12:53,770 --> 00:12:57,690
+جمعت هذا مع هذا، هتروح σ average مع σ
+
+180
+00:12:57,690 --> 00:13:00,550
+average. بيبقى عندي σ1. لو جمعت هذا مع هذا،
+
+181
+00:13:00,550 --> 00:13:02,330
+بتروح σ average مع σ average. بيبقى عندي
+
+182
+00:13:02,330 --> 00:13:06,170
+σ2. لو جمعت هذا اللي هو σ هذا، بتروح
+
+183
+00:13:06,170 --> 00:13:08,090
+σ average مع σ average. بيبقى عندي σ
+
+184
+00:13:08,090 --> 00:13:10,590
+3. معناته هذا الـ element equivalent to these
+
+185
+00:13:10,590 --> 00:13:11,510
+
+223
+00:17:50,990 --> 00:17:57,730
+element في الحالة هذي بتكون sigma 1 بيساوي sigma 2
+
+224
+00:17:57,730 --> 00:18:01,960
+بيساوي sigma 3 بيساوي sigma average هيصير عندي هنا
+
+225
+00:18:01,960 --> 00:18:10,700
+الـ U اللي هي الـ U هايدروستاتك اتش هتسميها هتكون
+
+226
+00:18:10,700 --> 00:18:20,380
+واحد على اتنين E فيه هتكون هنا عندي هيطلع عندي
+
+227
+00:18:20,380 --> 00:18:25,460
+sigma average تربيع سيجما افرج سيجما افرج سيجما
+
+228
+00:18:25,460 --> 00:18:29,840
+افرج سيجما افرج في
+
+229
+00:18:29,840 --> 00:18:30,740
+واحد
+
+230
+00:18:38,610 --> 00:18:42,510
+-2ν خلّيني أعملها بطوطين
+
+231
+00:18:45,590 --> 00:18:50,250
+في sigma average تسمى تلاتة تلاتة sigma average
+
+232
+00:18:50,250 --> 00:18:59,090
+تربيع ناقص اتنين ν في تلاتة sigma average تربيع
+
+233
+00:18:59,090 --> 00:19:08,710
+يعني هتكون تساوي تلاتة sigma average تربيع على
+
+234
+00:19:08,710 --> 00:19:13,910
+اتنين E في واحد ناقص اتنين ν
+
+235
+00:19:17,350 --> 00:19:19,790
+و الـ sigma average احنا حكينا بيساوي sigma 1 زي
+
+236
+00:19:19,790 --> 00:19:25,030
+sigma 2 زي sigma 3 على 3 اللي أنا إذا بعوض عن
+
+237
+00:19:25,030 --> 00:19:32,530
+sigma average و simplify الـ U volume هتعطي
+
+238
+00:19:32,530 --> 00:19:37,030
+بالعلاقة هذه اللي هي واحد ناقص اتنين
+
+239
+00:19:45,520 --> 00:19:48,280
+هتكون واحد نقص اتنين على ستة E في سيجما واحد تربيع
+
+240
+00:19:48,280 --> 00:19:50,660
+زي سيجما اتنين تربيع زي سيجما تلاتة تربيع زي اتنين سيجما
+
+241
+00:19:50,660 --> 00:19:53,480
+واحد سيجما اتنين زي اتنين سيجما اتنين سيجما تلاتة وزي
+
+242
+00:19:53,480 --> 00:19:56,660
+اتنين سيجما تلاتة سيجما واحد الان الـ total energy U
+
+243
+00:19:58,780 --> 00:20:02,580
+بيساوي U due to volume change زي U due to
+
+244
+00:20:02,580 --> 00:20:11,180
+distortion بيساوي U-Uv أنا عارف U وعارف Uv بحسب الـ
+
+245
+00:20:11,180 --> 00:20:15,440
+U distortion بحكي U distortion بيساوي U-Uv بعوض و
+
+246
+00:20:15,440 --> 00:20:19,180
+بعمل تبسيط بيصير الـ U due to distortion بيساوي
+
+247
+00:20:19,180 --> 00:20:22,820
+واحد زي الـ U على التلاتة E في سيجما واحد ناقص سيجما
+
+248
+00:20:22,820 --> 00:20:25,100
+اتنين لكل تربيع زي سيجما اتنين ناقص سيجما تلاتة لكل
+
+249
+00:20:25,100 --> 00:20:33,280
+تربيع زي سيجما تلاتة ناقص سيجما واحد لكل تربيع الان
+
+250
+00:20:33,280 --> 00:20:46,120
+for for
+
+251
+00:20:46,120 --> 00:20:51,660
+a tensile test specimen for a tensile
+
+252
+00:20:55,070 --> 00:21:03,350
+test specimen بيكون عندي يعني هاي عند الـ stress
+
+253
+00:21:03,350 --> 00:21:08,450
+element بيكون عليه إيه إيش سيجما واحد سيجما واحد
+
+254
+00:21:08,450 --> 00:21:12,270
+بيكون عندي سيجما اتنين بيساوي سيجما تلاتة بيساوي
+
+255
+00:21:12,270 --> 00:21:17,210
+صفر معناته الـ U distortion for a tensile specimen
+
+256
+00:21:17,210 --> 00:21:22,450
+اللي هو خلينا نحكي الـ yielding UY
+
+257
+00:21:24,180 --> 00:21:32,320
+ساحوض واحد زائد ν على تلاتة E في ستكون هذه صفر
+
+258
+00:21:32,320 --> 00:21:43,060
+صفر و صفر يعني ستكون عندي  sigma
+
+259
+00:21:43,060 --> 00:21:47,140
+واحد sigma
+
+260
+00:21:47,140 --> 00:21:52,920
+واحد تربيع sigma
+
+261
+00:21:52,920 --> 00:22:03,910
+واحدتربيع اللي هي هذه زي الـ sigma واحد تربيع
+
+262
+00:22:03,910 --> 00:22:13,130
+على اتنين لأنها تكون تساوي واحد زي الـ U على تلاتة A
+
+263
+00:22:13,130 --> 00:22:19,190
+في sigma واحد تربيع
+
+264
+00:22:27,350 --> 00:22:31,110
+و الـ tensile test specimen yields لما sigma 1 يساوي
+
+265
+00:22:31,110 --> 00:22:38,010
+sigma Sy يعني الـ U الـ yielding for a tensile test
+
+266
+00:22:38,010 --> 00:22:44,910
+specimen هتكون واحد زائد الـ U في Sy تربيع على تلاتة
+
+267
+00:22:44,910 --> 00:22:50,850
+E الـ distortion اللي بيحكي بيصير failure أو
+
+268
+00:22:50,850 --> 00:22:53,270
+بيصير yielding لما
+
+269
+00:22:55,850 --> 00:22:58,670
+لما الـ U distortion للـ mechanical element تحت
+
+270
+00:22:58,670 --> 00:23:03,830
+الدراسة يكون أكبر أو يساوي الـ U distortion for a
+
+271
+00:23:03,830 --> 00:23:09,890
+tensile test specimen يعني هتكون U distortion اللي
+
+272
+00:23:09,890 --> 00:23:14,230
+هي ..
+
+273
+00:23:14,230 --> 00:23:19,870
+اللي هي .. اللي هي هذه المعادلة اللي هي واحد زائد
+
+274
+00:23:19,870 --> 00:23:27,040
+U على تلاتة E في (سيجما واحد ناقص سيجما اتنين) لكل
+
+275
+00:23:27,040 --> 00:23:33,560
+تربيع زي (سيجما اتنين ناقص سيجما تلاتة) لكل تربيع
+
+276
+00:23:33,560 --> 00:23:39,700
+زي (سيجما تلاتة ناقص سيجما واحد) لكل تربيع على
+
+277
+00:23:39,700 --> 00:23:54,870
+اتنين تكون أكبر أو يساوي واحد زي ν في Sy تربيع على
+
+278
+00:23:54,870 --> 00:24:03,770
+تلاتة E يعني
+
+279
+00:24:03,770 --> 00:24:08,230
+هيرجع عندي واحد زائد ν  على تلاتة
+
+280
+00:24:08,230 --> 00:24:15,690
+E مع تلاتة E يعني بيصير failure لما سيجما واحد
+
+281
+00:24:15,690 --> 00:24:22,630
+ناقص سيجما اتنين الكل تربيع زي سيجما اتنين ناقص سيجما
+
+282
+00:24:22,630 --> 00:24:26,890
+تلاتة الكل تربيع زي سيجما تلاتة ناقص سيجما واحد الكل
+
+283
+00:24:26,890 --> 00:24:31,890
+تربيع على اتنين
+
+284
+00:24:31,890 --> 00:24:42,070
+طبعا هذا الكل تحت الجذر يكون أكبر أو يساوي Sy
+
+285
+00:24:42,070 --> 00:24:47,710
+معناته الـ distortion theory predicts failure لما
+
+286
+00:24:47,710 --> 00:24:51,150
+distortion energy per unit volume of the
+
+287
+00:24:51,150 --> 00:24:55,230
+mechanical element under study exceeds the
+
+288
+00:24:55,230 --> 00:24:59,170
+distortion energy
+
+289
+00:24:59,170 --> 00:25:03,070
+of a tensile test specimen اللي هي هذه المعادلة
+
+290
+00:25:03,070 --> 00:25:05,930
+(سيجما 1 ناقص سيجما 2) الكل تربيع زي (سيجما 2 ناقص
+
+291
+00:25:05,930 --> 00:25:09,070
+سيجما 3) الكل تربيع زي (سيجما 3 ناقص سيجما 1) الكل
+
+292
+00:25:09,070 --> 00:25:11,930
+تربيع على 2 تحت الجذر أكبر أو يساوي Sy
+
+293
+00:25:15,860 --> 00:25:21,920
+الان ممكن أعرف الـ term هذا واحد اسمه Von Mises سمى
+
+294
+00:25:21,920 --> 00:25:26,720
+كل term هذا سمى sigma prime أو von Mises stress
+
+295
+00:25:26,720 --> 00:25:34,560
+هذا الـ term هذا كله sigma prime يعني ممكن أحكي الـ
+
+296
+00:25:34,560 --> 00:25:38,260
+distortion energy theory صياغة تانية لما الـ von
+
+297
+00:25:38,260 --> 00:25:41,240
+Mises stress اللي هو sigma prime exceeds الـ yield
+
+298
+00:25:41,240 --> 00:25:47,060
+strength yielding begins يعني yielding لما الـ sigma
+
+299
+00:25:47,060 --> 00:25:51,560
+prime أكبر أو يساوي Sy اللي هو الـ sigma prime
+
+300
+00:25:51,560 --> 00:25:54,260
+اللي هي الـ von Mises stress اللي هو معطى
+
+301
+00:25:54,260 --> 00:25:55,960
+العلاقة هذه الـ von Mises stress اللي هو sigma
+
+302
+00:25:55,960 --> 00:25:58,380
+واحد ناقص سيجما اتنين الكل تربيع زي سيجما اتنين
+
+303
+00:25:58,380 --> 00:26:01,420
+ناقص سيجما تلاتة الكل تربيع زي سيجما تلاتة ناقص
+
+304
+00:26:01,420 --> 00:26:03,900
+سيجما واحد الكل تربيع على اتنين أقصد نص هذا هو
+
+305
+00:26:03,900 --> 00:26:09,040
+sigma prime أو الـ von Mises stress for a plain
+
+306
+00:26:09,040 --> 00:26:12,780
+state of stress هيكون واحد من stress بيساوي صفر
+
+307
+00:26:12,780 --> 00:26:18,030
+يعني لو هذا هذا هيكون صفر هذا صفر بتصف الـ volume
+
+308
+00:26:18,030 --> 00:26:21,170
+minus stress sigma prime بسهولة sigma a تربيع بقى
+
+309
+00:26:21,170 --> 00:26:24,350
+أنا sigma a sigma b زي أنا sigma b تربيع الكل تحت الجذر
+
+310
+00:26:24,350 --> 00:26:30,550
+نص إذا أنت ممكن تحصل stress مباشرة بدون ما تحصل الـ
+
+311
+00:26:30,550 --> 00:26:34,250
+principal stress بس أنا بفضل أحسب الـ principal
+
+312
+00:26:34,250 --> 00:26:38,510
+stress بعدين أحصل stress من المعادلة هذه باستخدام
+
+313
+00:26:38,510 --> 00:26:43,150
+الـ principal stress لكن ممكن إذا أنت تاخد الـ
+
+314
+00:26:43,150 --> 00:26:46,710
+stress element الأصلي اللي بيكون فيه sigma x sigma
+
+315
+00:26:46,710 --> 00:26:52,170
+y sigma z τxy τxz τyz و أحسب stress من
+
+316
+00:26:52,170 --> 00:26:58,220
+هذه المعادلة رياضيا المعادلة هذه نفس المعادلة هذه
+
+317
+00:26:58,220 --> 00:26:59,160
+تماماً
+
+318
+00:27:07,910 --> 00:27:12,150
+Von Mises stress is a single effective stress for
+
+319
+00:27:12,150 --> 00:27:14,570
+the entire general state of stress in a stress
+
+320
+00:27:14,570 --> 00:27:20,470
+.معناته Von Mises stress هو مثّل stress كأنه واحدة
+
+321
+00:27:20,470 --> 00:27:25,870
+بتمثل المجموع العام للـ state of stress for a
+
+322
+00:27:25,870 --> 00:27:27,390
+mechanical element under stress
+
+323
+00:27:30,420 --> 00:27:34,840
+احنا في الـ distortion energy theory ببساطة بتقارن
+
+324
+00:27:34,840 --> 00:27:36,420
+الـ Von Mises stress مع الـ yielding strength
+
+325
+00:27:36,420 --> 00:27:39,040
+إذا كان الـ Von Mises stress أكبر بيساوي الـ
+
+326
+00:27:39,040 --> 00:27:44,620
+Sy الـ yielding begins if I incorporate a factor of
+
+327
+00:27:44,620 --> 00:27:52,960
+safety بيساوي sigma prime بيساوي Sy على N طبعاً
+
+328
+00:27:52,960 --> 00:27:56,780
+لو أخدت 2D state of stress هيكون دي sigma prime
+
+329
+00:28:01,240 --> 00:28:10,140
+for a 2D state of stress ناخذها كحالة دراسية سيكون
+
+330
+00:28:10,140 --> 00:28:16,720
+لدي الـ sigma prime بيساوي سيجما a تربيع زائد
+
+331
+00:28:16,720 --> 00:28:22,520
+سيجما a سيجما b زائد سيجما b تربيع الكل تحت الجذر اللي هي
+
+332
+00:28:22,520 --> 00:28:30,020
+المعادلة هذه أو هي ناقص هنا هذه ناقص
+
+333
+00:28:38,570 --> 00:28:46,230
+هذه المعادلة إذا ترجع لرياضيات الـ calculus هذه
+
+334
+00:28:46,230 --> 00:28:53,190
+معادلة ellipse مائل بزاوية 45 يعني عندك هاي الـ X و
+
+335
+00:28:53,190 --> 00:29:01,670
+هاي الـ Y هذا بزاوية 45 درجة هذا هو الـ ellipse
+
+336
+00:29:05,090 --> 00:29:12,050
+هذه معادلة الـ ellipse مائل بزاوية 45 درجة الان
+
+337
+00:29:12,050 --> 00:29:21,350
+لدي هنا sigma 1 على Sy هنا sigma 2 على Sy وهذا الـ
+
+338
+00:29:21,350 --> 00:29:27,340
+failure contour وهذه الـ Experimental Data لحظة الـ
+
+339
+00:29:27,340 --> 00:29:34,600
+Distortion Energy Theory تتوقع
+
+340
+00:29:34,600 --> 00:29:40,610
+الحقيقة لكن الـ maximum shear stress theory it
+
+341
+00:29:40,610 --> 00:29:45,230
+predicts failure before failure actually happens
+
+342
+00:29:45,230 --> 00:29:49,430
+بتتوقع الـ failure ولسه ما صارش failure اللي هي الـ
+
+343
+00:29:49,430 --> 00:29:52,010
+maximum shear stress theory لكن الـ distortion
+
+344
+00:29:52,010 --> 00:29:57,030
+energy theory predicts failure accurately يعني فيه
+
+345
+00:29:57,030 --> 00:30:01,170
+دقة معناته الدقة في حالة distortion energy theory
+
+346
+00:30:01,170 --> 00:30:06,990
+أعلى لكنها less conservative يعني أنصر المخاطرة في
+
+347
+00:30:06,990 --> 00:30:11,830
+الحسابات عليك كمصمم بيكون إيش؟ أعلى في حالة
+
+348
+00:30:11,830 --> 00:30:15,390
+distortion energy theory لكنه بده أنا عشان أوفر
+
+349
+00:30:15,390 --> 00:30:19,610
+material في حالة الـ mass production بفضل استخدام
+
+350
+00:30:19,610 --> 00:30:22,650
+distortion energy theory أو Von Mises معظم الـ
+
+351
+00:30:22,650 --> 00:30:26,710
+software زي الـ ... الـ ansys abacus الـ ... الـ حتة الـ
+
+352
+00:30:26,710 --> 00:30:30,430
+solid work لما تعمل finite element analysis و تعمل
+
+353
+00:30:30,430 --> 00:30:34,190
+stress contour بيحسب الـ Von Mises stress طبعاً أنت
+
+354
+00:30:34,190 --> 00:30:36,390
+مخير تحكيله أنا بدي أستخدم الـ maximum shear stress
+
+355
+00:30:36,390 --> 00:30:40,230
+theory بس الـ default عنده بيستخدم الـ distortion
+
+356
+00:30:40,230 --> 00:30:41,550
+energy theory
+
+357
+00:30:59,510 --> 00:31:06,450
+طيب لأن هنشوف الـ shear strength predictions كيف
+
+358
+00:31:06,450 --> 00:31:11,050
+نتوقع الـ shear strength لـ material طبقا لـ maximum
+
+359
+00:31:11,050 --> 00:31:14,290
+shear strength theory و طبقا لـ distortion energy
+
+360
+00:31:14,290 --> 00:31:18,990
+theory إذا أخدت أنا mechanical element و عملت عليه
+
+361
+00:31:19,860 --> 00:31:24,280
+Torsion أزيد torque torque لحد ما صار failure أو
+
+362
+00:31:24,280 --> 00:31:30,880
+صار yielding الان الـ stress element في 2D هيكون 2D
+
+363
+00:31:30,880 --> 00:31:37,100
+stress element هيكون عندي
+
+364
+00:31:37,100 --> 00:31:45,780
+τ هيكون Mohr circle بالشكل هذا Mohr circle هذا الـ
+
+365
+00:31:45,780 --> 00:31:56,490
+sigma و هذه سيجما اتنين و هذه τmax
+
+366
+00:31:56,490 --> 00:32:03,630
+τmax ستكون تساوي سيجما واحد ناقص سيجما
+
+367
+00:32:03,630 --> 00:32:09,390
+اتنين على اتنين يعني سيجما واحد موجب و سيجما اتنين سالبة
+
+368
+00:32:09,390 --> 00:32:13,850
+معناته
+
+369
+00:32:13,850 --> 00:32:15,610
+أنا عندي هنا سيجما A
+
+370
+00:32:18,580 --> 00:32:25,200
+وهنا عندي sigma b في
+
+371
+00:32:25,200 --> 00:32:30,540
+حالة الـ maximum shear stress theory هاي
+
+372
+00:32:30,540 --> 00:32:40,180
+الـ maximum shear stress theory و
+
+373
+00:32:40,180 --> 00:32:47,260
+أخذت mechanical element that is under pure torsion
+
+374
+00:32:47,260 --> 00:32:54,940
+لحد الـ failure الـ load line هيكون بالشكل هذا هذا الـ
+
+375
+00:32:54,940 --> 00:33:06,400
+load line at
+
+376
+00:33:06,400 --> 00:33:06,880
+failure
+
+377
+00:33:11,480 --> 00:33:19,460
+هذه النقطة هذه نقطة الـ failure هذه failure point
+
+378
+00:33:19,460 --> 00:33:28,120
+احنا واضح إنه يعني أنا هنا عندي sigma a أو sigma b
+
+379
+00:33:28,120 --> 00:33:35,060
+أنا واضح في الربع الرابع عندي يعني sigma a
+
+380
+00:33:38,840 --> 00:33:45,240
+أكبر أو يساوي sigma b لأن sigma a أكبر أو يساوي
+
+381
+00:33:45,240 --> 00:33:51,000
+صفر و الصفر أكبر أو يساوي sigma b معناته هذه تمثل
+
+382
+00:33:51,000 --> 00:33:57,120
+sigma 1 هذه sigma 2 وهذه sigma 3 معناته
+
+383
+00:33:57,120 --> 00:34:05,960
+τmax ماكسيموم أكبر أو يساوي sigma 1 ناقص
+
+384
+00:34:05,960 --> 00:34:18,350
+sigma 3 على اتنين هيساوي
+
+385
+00:34:18,350 --> 00:34:23,890
+سيجما واحد ناقص سيجما اتنين بيساوي ناقص سيجما
+
+386
+00:34:23,890 --> 00:34:34,530
+واحد على اتنين يعني بيساوي سيجما واحد على 2  الـ
+
+387
+00:34:34,530 --> 00:34:40,390
+yielding الـ yielding أنا عندي هنا سيكون عندي sigma
+
+388
+00:34:40,390 --> 00:34:52,710
+a سيجما a ناقص سيجما b أكبر أو يساوي إيش Sy هنا
+
+389
+00:34:52,710 --> 00:35:00,910
+عند الـ yielding هل نسميها S
+
+390
+00:35:00,910 --> 00:35:09,410
+Sy اللي هي yielding strength in shear و هذه Sy
+
+391
+00:35:09,410 --> 00:35:17,950
+وهنا حكينا هذه sigma a وهذه ناقص sigma a من تشابه
+
+392
+00:35:17,950 --> 00:35:24,410
+المثلثات أو معادلة الخط هذا المستقيم معادلة الخط
+
+393
+00:35:24,410 --> 00:35:29,550
+المستقيم هذا عبارة عن sigma b هذا الخط الـ load
+
+394
+00:35:29,550 --> 00:35:34,150
+line equation
+
+395
+00:35:36,020 --> 00:35:43,520
+اللي هتكون عند سيجما b تساوي ناقص سيجما a هذه
+
+396
+00:35:43,520 --> 00:35:50,720
+معادلة معادلة الخط الثاني في تلات نقاط Sy و صفر
+
+397
+00:35:50,720 --> 00:35:55,220
+وعند
+
+398
+00:35:55,220 --> 00:36:03,020
+صفر و ناقص Sy عند نقطة هنا اللي
+
+399
+00:36:03,020 --> 00:36:03,320
+هي
+
+400
+00:36:07,020 --> 00:36:16,220
+بدي أسميها Ssy Ssy
+
+401
+00:36:16,220 --> 00:36:25,520
+و Ssy الـ slope بتاع الخط هذا هيكون عندي
+
+402
+00:36:25,520 --> 00:36:31,860
+الـ load on sigma A بيساوي ناقص سيجما B النقطة
+
+403
+00:36:31,860 --> 00:36:4
+
+445
+00:40:37,590 --> 00:40:40,150
+اعبر
+
+446
+00:40:42,400 --> 00:40:45,720
+عن الـ failure طبقا للـ maximum shear stress theory
+
+447
+00:40:45,720 --> 00:40:49,640
+أو طبقا للـ distortion theory بنفس الشكل بس باختلاف
+
+448
+00:40:49,640 --> 00:40:53,700
+التفاصيل يعني أحكي أن failure according to
+
+449
+00:40:53,700 --> 00:40:57,680
+maximum shear stress theory happens لما tau
+
+450
+00:40:57,680 --> 00:41:01,680
+maximum تكون أكبر أو يساوي  τ<sub>y</sub> اللي هي
+
+451
+00:41:01,680 --> 00:41:04,960
+yield strength in shear وبرضه ممكن أعبر عن الـ
+
+452
+00:41:04,960 --> 00:41:08,450
+failure according to الـ distortion energy theory
+
+453
+00:41:08,450 --> 00:41:11,750
+بأحكي اللي هو بيصير failure لما الـ tau maximum تكون
+
+454
+00:41:11,750 --> 00:41:15,570
+برضه أكبر أو يساوي SSY اللي بيختلف الـ definition
+
+455
+00:41:15,570 --> 00:41:19,690
+تاع SSY، الـ SSY في حالة الـ maximum shear stress
+
+456
+00:41:19,690 --> 00:41:24,170
+theory بيساوي 0.5 SY في حالة الـ distortion
+
+457
+00:41:24,170 --> 00:41:29,270
+energy theory بيساوي 0.577 SY
+
+458
+00:41:31,410 --> 00:41:36,090
+هذا مهم كتير لأنه بيسهل حلّ و فهم المسائل بشكل أعمق
+
+459
+00:41:36,090 --> 00:41:40,950
+نشوف مثال
+
+460
+00:41:40,950 --> 00:41:52,230
+هذا
+
+461
+00:41:52,230 --> 00:41:58,350
+المثال هيكون مثال حساب، نعتبره تدريب على استخدام أو
+
+462
+00:41:58,350 --> 00:42:05,990
+يعني زي calculation exercise. A hot rolled steel
+
+463
+00:42:05,990 --> 00:42:10,490
+has a yield strength of SYT بيساوي SYC بيساوي
+
+464
+00:42:10,490 --> 00:42:14,070
+100 كيلو باوند لكل بوصة مربعة. يعني hot
+
+465
+00:42:14,070 --> 00:42:18,330
+rolled steel yield strength SYT، yield strength
+
+466
+00:42:18,330 --> 00:42:21,330
+in tension بيساوي yield strength in compression
+
+467
+00:42:21,330 --> 00:42:26,000
+بيساوي 100 كيلو باوند لكل بوصة مربعة، وهسميه as
+
+468
+00:42:26,000 --> 00:42:31,920
+well لأنهم متساويين، and a true strain at a
+
+469
+00:42:31,920 --> 00:42:36,500
+fracture، ε<sub>f</sub>، بيساوي 0.55. هذا أكبر من 0.05
+
+470
+00:42:36,500 --> 00:42:43,120
+أو 0.5، معناته المادة بتاعتها ductile material.
+
+471
+00:42:43,120 --> 00:42:50,440
+estimate the factor of safety for the
+
+472
+00:42:50,440 --> 00:42:55,550
+following principal stress states. احسب الـ factor
+
+473
+00:42:55,550 --> 00:42:59,010
+of safety للحالات التالية. a) σ
+
+474
+00:42:59,010 --> 00:43:05,030
+x بيساوي 70 كيلو باوند لكل بوصة مربعة، و
+
+475
+00:43:05,030 --> 00:43:11,910
+σy بيساوي 70 كيلو باوند لكل بوصة مربعة، و
+
+476
+00:43:11,910 --> 00:43:22,090
+τ<sub>xy</sub> بيساوي صفر. أوتوماتيك لما نطلع حالة
+
+477
+00:43:22,090 --> 00:43:27,430
+الشير stress بصفر، معناته هدول بيمثلوا إيش؟
+
+478
+00:43:27,430 --> 00:43:34,990
+principal stresses عند الـ principal planes بيكونش
+
+479
+00:43:34,990 --> 00:43:38,490
+فيه شير. ففي هذه الحالة بنعمل calculation على طول. σ
+
+480
+00:43:38,490 --> 00:43:42,150
+واحد في الحالة دي. σ<sub>1</sub> because لأنه
+
+481
+00:43:42,150 --> 00:43:46,930
+τ<sub>xy</sub> بيساوي صفر.
+
+482
+00:43:49,530 --> 00:43:56,410
+ما أن σx and σy are
+
+483
+00:43:56,410 --> 00:44:00,910
+principal stresses.
+
+484
+00:44:00,910 --> 00:44:08,330
+معناته σ<sub>1</sub> بيساوي 70 كيلو باوند لكل بوصة مربعة
+
+485
+00:44:08,330 --> 00:44:12,850
+و σ<sub>2</sub> بيساوي برضه 70 كيلو باوند لكل بوصة مربعة
+
+486
+00:44:12,850 --> 00:44:20,090
+و σ<sub>3</sub> بيساوي صفر. لأن
+
+487
+00:44:20,090 --> 00:44:24,590
+في عندي حلتين. بنستخدم مرة الـ maximum shear stress
+
+488
+00:44:24,590 --> 00:44:28,670
+theory ومرة اللي هي distortion energy theory
+
+489
+00:44:28,670 --> 00:44:33,970
+according
+
+490
+00:44:33,970 --> 00:44:37,850
+to maximum shear stress theory بتحكي بيصير failure
+
+491
+00:44:37,850 --> 00:44:39,010
+لما الـ τ<sub>max</sub>
+
+492
+00:44:45,170 --> 00:44:54,010
+أكبر أو يساوي SSY أو بيساوي SSY / N يعني
+
+493
+00:44:54,010 --> 00:45:03,210
+N هتساوي SSY / τ<sub>max</sub>  و الـ SSY في حالة
+
+494
+00:45:03,210 --> 00:45:08,970
+maximum shear stress theory بيساوي نص الـ SY اللي
+
+495
+00:45:08,970 --> 00:45:15,560
+هي نص في 100، نصف 100 بيطلع 50 كيلو باوند
+
+496
+00:45:15,560 --> 00:45:20,140
+لكل بوصة مربعة. طيب
+
+497
+00:45:20,140 --> 00:45:28,140
+الـ τ<sub>max</sub> بيساوي (σ<sub>1</sub> - σ<sub>3</sub>) / 2 يعني هتكون (70 - 0) / 2 = 35
+
+498
+00:45:28,140 --> 00:45:35,120
+كيلو باوند لكل بوصة مربعة. معناته N
+
+499
+00:45:35,120 --> 00:45:39,420
+هتكون تساوي الـ SSY اللي هي 50 / 35 = 1.43
+
+500
+00:45:40,920 --> 00:45:48,920
+في حالة الـ distortion theory
+
+501
+00:45:48,920 --> 00:45:55,620
+في حالة الـ maximum shear... في حالة الـ
+
+502
+00:45:55,620 --> 00:45:59,820
+distortion energy theory بيصير failure لما τ<sub>max</sub>
+
+503
+00:45:59,820 --> 00:46:04,940
+أكبر أو يساوي SSY أو τ<sub>max</sub> بيساوي SSY / N
+
+504
+00:46:06,790 --> 00:46:09,450
+يعني N بتساوي SSY / τ<sub>max</sub>. طيب الـ SSY إيش
+
+505
+00:46:09,450 --> 00:46:14,730
+بتساوي؟ في حالة الـ distortion energy بتساوي 0.577
+
+506
+00:46:14,730 --> 00:46:18,530
+SY يعني هتساوي 0.577 في
+
+507
+00:46:18,530 --> 00:46:23,570
+100 يعني هتساوي 57.7 كيلو باوند لكل بوصة مربعة. هذا according to
+
+508
+00:46:23,570 --> 00:46:35,150
+distortion energy theory.
+
+509
+00:46:35,150 --> 00:46:40,250
+طيب و الـ τ<sub>max</sub> already حسبناها. الـ τ<sub>max</sub>
+
+510
+00:46:40,250 --> 00:46:51,590
+بتساوي 35 يعني هتكون اللي هي 57.7 / 35 = 1.65
+
+511
+00:46:51,590 --> 00:46:57,730
+لاحظوا الـ margin of safety في حالة الـ distortion energy theory
+
+512
+00:46:57,730 --> 00:47:01,570
+أعلى من الـ maximum shear stress theory لأن احنا
+
+513
+00:47:01,570 --> 00:47:05,010
+بداية حكينا أن maximum shear stress theory gives
+
+514
+00:47:10,930 --> 00:47:14,910
+اللي هو more conservative results. يعني وعنصر
+
+515
+00:47:10,930 --> 00:47:14,820
+المخاطر أقل. بيحكيلك أنه .. أنه أنا بحكيلك أنه فيه
+
+516
+00:47:14,820 --> 00:47:19,160
+failure ولسه ما صارش failure. هذه طلع الـ factor of
+
+517
+00:47:19,160 --> 00:47:25,930
+safety أعلى لأنه it fits the experimental data أكثر
+
+518
+00:47:25,930 --> 00:47:30,730
+من الـ maximum shear stress theory. الآن طريقة حساب الـ
+
+519
+00:47:30,730 --> 00:47:33,210
+factors of safety باستخدام نفس المعادلة. τ<sub>max</sub> = S<sub>sy</sub> / N،  و الـ τ<sub>max</sub> = S<sub>sy</sub>
+
+520
+00:47:33,210 --> 00:47:37,450
+/ N. نفس الاستخدام بس اللي اختلف الـ definition
+
+521
+00:47:37,450 --> 00:47:39,790
+بتاع S<sub>sy</sub>. لكن لو أنا بدي أحسب الـ von Mises stress، لو دي حسبناها يعني، هنلاحظ .. هنصل لنفس .. نفس ..
+
+522
+00:47:39,790 --> 00:47:47,530
+نفس النتيجة. σ' هتكون √(σ<sub>a</sub>² - σ<sub>a</sub>σ<sub>b</sub> + σ<sub>b</sub>²)
+
+523
+00:47:47,530 --> 00:47:54,010
+يعني هتكون تساوي هذا .. هذا حل ثاني. σ<sub>a</sub> اللي عندي
+
+524
+00:47:54,010 --> 00:48:09,410
+أكام اللي هي 70 تربيع - 70 × 70 + 70 تربيع، تطلع 70 كيلو باوند لكل بوصة مربعة. هذا
+
+525
+00:48:09,410 --> 00:48:13,800
+σ' و
+
+526
+00:48:13,800 --> 00:48:16,000
+according to the distortion energy theory بيصير failure
+
+527
+00:48:16,000 --> 00:48:21,200
+لما σ' أكبر أو يساوي SY يعني σ'
+
+528
+00:48:23,390 --> 00:48:31,890
+بيساوي SY / N يعني N بتساوي SY / σ'، SY الـ SY هي 100 / 70
+
+529
+00:48:31,890 --> 00:48:37,370
+= 1.43. طيب نشوف مثال تاني
+
+530
+00:48:42,730 --> 00:48:46,270
+نحله
+
+531
+00:48:46,270 --> 00:48:51,350
+باستخدام اللي هي σ' مرة ومرة حلّو
+
+532
+00:48:51,350 --> 00:49:03,470
+باستخدام اللي هي الـ SSY لحظة
+
+533
+00:49:03,470 --> 00:49:10,410
+خليني أرجع لنفس السؤال. نفس السؤال أوضح إذا كنت في
+
+534
+00:49:10,410 --> 00:49:14,350
+الربع الثالث، إذا كنت في الربع الرابع.
+
+535
+00:49:17,510 --> 00:49:28,550
+If state of stress is in the fourth quadrant. هذا
+
+536
+00:49:28,550 --> 00:49:33,390
+تصحيح لأن صار عندي خربشة. أنا fourth quadrant معناته
+
+537
+00:49:33,390 --> 00:49:39,730
+σa أكبر من أو يساوي الصفر، أكبر من أو يساوي الـ σb. يعني واحد موجب وواحد سالب. في الحالة هذه in this
+
+538
+00:49:39,730 --> 00:49:49,200
+case بأحكي أن الـ N بتساوي SSY / τ<sub>max</sub> هذا
+
+539
+00:49:49,200 --> 00:49:54,760
+في حالة الـ distortion energy theory وفي حالة الـ
+
+540
+00:49:54,760 --> 00:49:58,380
+maximum shear stress theory. لكن في حالة الـ
+
+541
+00:49:58,380 --> 00:50:01,780
+distortion energy theory بتكون عندي الـ SSY
+
+542
+00:50:01,780 --> 00:50:08,420
+بيساوي 0.577 SY و الـ SSY في حالة الـ
+
+543
+00:50:08,420 --> 00:50:12,220
+maximum shear stress theory بتكون بيساوي 0.5 SY.
+
+544
+00:50:13,930 --> 00:50:19,030
+معناته الحل السابق ينطبق في الـ fourth quadrant لكن
+
+545
+00:50:19,030 --> 00:50:23,870
+أنا وين طلعت؟ عندي σa موجبة و σb موجبة.
+
+546
+00:50:23,870 --> 00:50:28,610
+أنا في الـ first quadrant. معناته this is not valid.
+
+547
+00:50:28,610 --> 00:50:36,830
+يعني if state of stress is
+
+548
+00:50:36,830 --> 00:50:42,090
+in the first quadrant.
+
+549
+00:50:44,790 --> 00:50:50,630
+معناته بدنا نحكي في الحالة هذه نحكي أنه الـ
+
+550
+00:50:50,630 --> 00:50:56,450
+σ' بيساوي SY / N في حالة الـ
+
+551
+00:50:56,450 --> 00:51:02,350
+distortion energy theory وفي
+
+552
+00:51:02,350 --> 00:51:05,110
+حالة الـ maximum shear stress theory هنحكي أنه ..
+
+553
+00:51:05,110 --> 00:51:17,650
+أنه .. أنه σa بيساوي SY / n في حالة الـ
+
+554
+00:51:17,650 --> 00:51:22,570
+maximum shear stress theory. احنا في المسألة
+
+555
+00:51:22,570 --> 00:51:27,150
+السابقة احنا كنا في الـ first quadrant معناته
+
+556
+00:51:27,150 --> 00:51:33,530
+ما نفعش .. ما نفعش نستخدم المعادلة هذه في الـ first
+
+557
+00:51:33,530 --> 00:51:40,950
+.. في الـ first quadrant. طيب نشوف مسألة ثانية أو
+
+558
+00:51:40,950 --> 00:51:44,170
+فرع ثاني هذا للتوضيح
+
+559
+00:51:52,010 --> 00:51:56,050
+نشوف حالة ثانية. عندي σx بيساوي 60
+
+560
+00:51:56,050 --> 00:52:01,810
+σx بيساوي 60 كيلو باوند لكل بوصة مربعة
+
+561
+00:52:01,810 --> 00:52:09,370
+و σy بيساوي 40 كيلو باوند لكل بوصة مربعة
+
+562
+00:52:09,370 --> 00:52:16,000
+و τ<sub>xy</sub> بيساوي -15 كيلو باوند لكل بوصة مربعة. أول شيء بنعمله لازم نوجد الـ
+
+563
+00:52:16,000 --> 00:52:21,160
+principal stresses. find principal
+
+564
+00:52:21,160 --> 00:52:24,660
+stresses.
+
+565
+00:52:24,660 --> 00:52:30,040
+يعني نوجد σ<sub>1</sub>، σ<sub>2</sub>، σ<sub>3</sub> هنا طبعا هستخدم Mohr circle. Mohr circle
+
+566
+00:52:37,740 --> 00:52:45,200
+أنا هستخدم عندي هنا هنا counter clockwise موجب
+
+567
+00:52:45,200 --> 00:52:50,840
+وهنا clockwise سالب. معناته هتكون عندي هنا σ<sub>max</sub>
+
+568
+00:52:50,840 --> 00:52:54,580
+اللي هي 60 و15 clockwise هتكون 60
+
+569
+00:52:54,580 --> 00:53:01,400
+أنا عندي 10، 20، 30، 40، 50، 60 هنا
+
+570
+00:53:01,400 --> 00:53:03,500
+10، 20،
+
+571
+00:53:06,150 --> 00:53:14,810
+هذه 10، 20، 30، 40، 50، 60. هذا
+
+572
+00:53:14,810 --> 00:53:21,710
+أول نقطة اللي هي σx اللي هي 60 و15
+
+573
+00:53:21,710 --> 00:53:27,570
+clockwise سالب. النقطة الثانية اللي هي 40
+
+574
+00:53:27,570 --> 00:53:35,150
+40 هذه -10، -20،
+
+575
+00:53:42,160 --> 00:53:49,680
+هذه ستكون 40 و15 counter clockwise. هوصل
+
+576
+00:53:49,680 --> 00:53:53,800
+بينهم وارسم
+
+577
+00:53:53,800 --> 00:54:03,860
+Mohr circle هذه.
+
+578
+00:54:03,860 --> 00:54:11,530
+Mohr circle. معناته هذه ستكون σ<sub>1</sub> وهذا الـ
+
+579
+00:54:11,530 --> 00:54:20,610
+σ<sub>2</sub> وهذا الـ σ<sub>3</sub>. طيب هذا هو الـ center. هذا
+
+580
+00:54:20,610 --> 00:54:29,170
+الـ center  الـ C بيساوي
+
+581
+00:54:29,170 --> 00:54:37,750
+(σx + σy) / 2 اللي هي (60 + 40) / 2
+
+582
+00:54:37,750 --> 00:54:44,770
+اللي هو 50 كيلو باوند لكل بوصة مربعة. هذه
+
+583
+00:54:44,770 --> 00:54:52,110
+المسافة هذه σ
+
+584
+00:54:52,110 --> 00:55:00,450
+x أو τ<sub>xy</sub>
+
+585
+00:55:08,320 --> 00:55:17,800
+وهذا (σx - σy) / 2. الـ radius هذا
+
+586
+00:55:17,800 --> 00:55:24,020
+الـ R، الـ radius بتاع Mohr circle كله. الـ radius بيساوي
+
+587
+00:55:24,020 --> 00:55:31,580
+الجذر التربيعي لـ [(σx - σy) / 2]² + τ<sub>xy</sub>² يعني هيكون الجذر التربيعي
+
+588
+00:55:31,580 --> 00:55:37,340
+لـ (60 - 40) / 2 الكل تربيع
+
+589
+00:55:37,340 --> 00:55:43,100
+زائد τ<sub>xy</sub> اللي هي 15 تربيع. يعني هيكون
+
+590
+00:55:43,100 --> 00:55:49,420
+عندي (60 - 40) = 20 / 2 = 10، ربعها
+
+591
+00:55:49,420 --> 00:55:52,460
+هيكون عندي 100 + 225 = 325 تحت الجذر
+
+592
+00:56:01,220 --> 00:56:11,100
+بيطلع 18.03 كيلو باوند لكل بوصة مربعة. هذا الـ radius. σ
+
+593
+00:56:11,100 --> 00:56:19,300
+<sub>1</sub> هتكون الـ C زائد الـ radius. الـ C اللي هي 50
+
+594
+00:56:19,300 --> 00:56:24,920
+زائد 18.03 = 68.03 كيلو باوند لكل بوصة مربعة، و الـ σ
+
+595
+00:56:24,920 --> 00:56:31,820
+<sub>2</sub> هتكون اللي هي C - الـ radius اللي هي
+
+596
+00:56:31,820 --> 00:56:36,580
+50 - 18.03 = 31.97
+
+597
+00:56:36,580 --> 00:56:42,240
+كيلو باوند لكل بوصة مربعة. هذا الـ σ<sub>2</sub> و
+
+598
+00:56:42,240 --> 00:56:53,200
+σ<sub>3</sub> هتكون تساوي صفر. طيب
+
+599
+00:56:53,200 --> 00:56:58,680
+واضح
+
+600
+00:56:58,680 --> 00:57:04,310
+أن σ<sub>1</sub> موجب، و σ<sub>2</sub> موجب، و σ<sub>3</sub>
+
+601
+00:57:04,310 --> 00:57:07,730
+صفر. معناه أن أنا في الربع الأول. في الربع
+
+602
+00:57:07,730 --> 00:57:12,570
+الأول. الآن في حتة الـ maximum shear stress theory
+
+603
+00:57:12,570 --> 00:57:19,130
+أنا في الـ first quadrant. عندي
+
+604
+00:57:19,130 --> 00:57:25,050
+σa بتساوي 68.03 كيلو باوند لكل بوصة مربعة، و σb بيساوي 31.97
+
+605
+00:57:25,050 --> 00:57:29,050
+كيلو باوند لكل بوصة مربعة. الـ
+
+606
+00:57:29,050 --> 00:57:34,870
+factor of safety N في الحالة هذه هيكون SY / σa
+
+607
+00:57:34,870 --> 00:57:39,130
+according to maximum shear stress theory. الـ SY
+
+608
+00:57:39,130 --> 00:57:43,690
+عندي 100 /
+
+609
+00:57:43,690 --> 00:57:49,050
+68.03 بيطلع
+
+610
+00:58:00,990 --> 00:58:09,990
+100 ÷ 68.03 بيساوي 1.47. هذا طبقا للـ
+
+611
+00:58:09,990 --> 00:58:15,370
+maximum shear stress theory. طبقا للـ distortion
+
+612
+00:58:15,370 --> 00:58:16,630
+energy theory
+
+613
+00:58:21,990 --> 00:58:25,830
+طبق الـ distortion energy theory، لازم نحسب الـ
+
+614
+00:58:25,830 --> 00:58:33,050
+von Mises stress σ' بيساوي √(σa² - σaσb + σb²)
+
+615
+00:58:33,050 --> 00:58:41,310
+يعني حيث بيساوي σa اللي هي 68.03
+
+616
+00:58:41,310 --> 00:58:41,810
+تربيع
+
+617
+00:59:00,410 --> 00:59:08,950
+الكل تربيع يعني
+
+618
+00:59:08,950 --> 00:59:27,810
+
+667
+01:04:09,050 --> 01:04:12,430
+stress theory لأن أحنا حكينا سابقا أن الـ maximum
+
+668
+01:04:12,430 --> 01:04:14,910
+shear stress theory is more conservative than اللي
+
+669
+01:04:14,910 --> 01:04:19,970
+هو distortion energy theory. خليني
+
+670
+01:04:19,970 --> 01:04:28,230
+أَسْحِب كمان فرع للتوضيح لأنه مهم جداً. خليني آخذ
+
+671
+01:04:28,230 --> 01:04:28,830
+الحالة
+
+672
+01:04:45,550 --> 01:04:55,310
+نأخذ الحالة الثالثة سيجما
+
+673
+01:04:55,310 --> 01:05:01,430
+واحد سيجما
+
+674
+01:05:01,430 --> 01:05:07,290
+واحد بتساوي ثلاثين kilo pound per square inch
+
+675
+01:05:07,290 --> 01:05:11,350
+وسيجما
+
+676
+01:05:11,350 --> 01:05:14,310
+اثنين بتساوي برضه ثلاثين
+
+677
+01:05:18,090 --> 01:05:28,730
+وسيجما ثلاثة هذه
+
+678
+01:05:28,730 --> 01:05:31,430
+لاحظوا سيجما واحد بيساوي سيجما اثنين بيساوي سيجما
+
+679
+01:05:31,430 --> 01:05:35,950
+ثلاثة. ما أنا حابب أُمثّل هذه hydrostatic هذه
+
+680
+01:05:35,950 --> 01:05:48,050
+hydrostatic state of stress. نطبّق لـ maximum shear
+
+681
+01:05:48,050 --> 01:05:51,330
+stress theory. طبعاً واضح هيطلع الـ factor safety
+
+682
+01:05:51,330 --> 01:05:55,110
+بمقدار أنه infinity. من غير حل يعني هتكون يعني الـ
+
+683
+01:05:55,110 --> 01:06:06,390
+τ<sub>max</sub> هيكون الساوي أو هيكون
+
+684
+01:06:06,390 --> 01:06:13,850
+عندي اللي هو σ<sub>1</sub> - σ<sub>3</sub> / 2 هيكون
+
+685
+01:06:13,850 --> 01:06:20,880
+إيه؟ شو الساوي؟ بس صفر يعني
+
+686
+01:06:20,880 --> 01:06:23,780
+أنا لو بدي أرسمها هذه هتكون هذاهي ستيت أوف ستريس
+
+687
+01:06:23,780 --> 01:06:27,180
+هتكون
+
+688
+01:06:27,180 --> 01:06:31,800
+الـ .. الـ .. الـ .. في حالة لو أنا كنت في الربع
+
+689
+01:06:31,800 --> 01:06:34,080
+الأول عندي سيجما واحد سيجما اثنين و سيجما ثلاثة و
+
+690
+01:06:34,080 --> 01:06:40,000
+مقصودهم هتكون ساوي ثلاثين ناقص ثلاثين صفر
+
+691
+01:06:45,500 --> 01:06:54,180
+الآن الآن هيكون الـ SSY / τ<sub>max</sub> هيطلع إيش؟
+
+692
+01:06:54,180 --> 01:07:00,240
+Infinity. تقسمها على صفر على اثنين هذه في حالة
+
+693
+01:07:00,240 --> 01:07:04,560
+distortion energy theory. في حالة distortion energy
+
+694
+01:07:04,560 --> 01:07:12,640
+هيكون الـ σ' بيساوي σ<sub>1</sub> -
+
+695
+01:07:12,640 --> 01:07:17,530
+σ<sub>2</sub> الكل تربيع زائد σ<sub>2</sub> - σ<sub>3</sub>
+
+696
+01:07:17,530 --> 01:07:22,630
+الكل تربيع زائد σ<sub>3</sub> - σ<sub>1</sub> الكل تربيع
+
+697
+01:07:22,630 --> 01:07:27,770
+/ 2.  أصله نصف طبعاً هذه بيساوي هذه، يعني عندما هذه
+
+698
+01:07:27,770 --> 01:07:34,850
+بيساوي إيش؟ صفر والـ factor of safety N بيساوي
+
+699
+01:07:34,850 --> 01:07:42,070
+اللي هو SY / σ' اللي هو هيكون SY / 0
+
+700
+01:07:42,070 --> 01:07:49,660
+Infinity يعني بيكون Infinity يعني very large state
+
+701
+01:07:49,660 --> 01:07:59,740
+of stress. خليني أدخل حالة رقم .. رقم
+
+702
+01:07:59,740 --> 01:08:06,620
+C لأن فيها فكرة رقم C. حالة رابعة
+
+703
+01:08:15,310 --> 01:08:22,350
+سيجما X هذه حالة ثانية أو رابعة. سيجما X بيساوي
+
+704
+01:08:22,350 --> 01:08:30,430
+صفر
+
+705
+01:08:30,430 --> 01:08:34,630
+و
+
+706
+01:08:34,630 --> 01:08:39,930
+سيجما Y بيساوي أربعين و
+
+707
+01:08:39,930 --> 01:08:43,090
+τ<sub>XY</sub> بيساوي خمسة وأربعين
+
+708
+01:08:48,910 --> 01:08:51,870
+أول شيء طبعاً هأجد الـ principal stresses. أرسم more
+
+709
+01:08:51,870 --> 01:09:01,690
+circle. more circle اللي عند السفق عندها هي عشرة
+
+710
+01:09:01,690 --> 01:09:10,090
+عشرين ثلاثين أربعين خمسين. عشرة عشرين ثلاثين أربعين
+
+711
+01:09:10,090 --> 01:09:18,090
+خمسين. عندي عشرة عشرين ثلاثين أربعين خمسين عند سيجما
+
+712
+01:09:18,090 --> 01:09:23,210
+X صفر و τ<sub>XY</sub> خمسة وأربعين. هي عشرة عشرين ثلاثين
+
+713
+01:09:23,210 --> 01:09:29,390
+أربعين خمسين. هي نقطة نقطة ثانية عند أربعين وعشرة
+
+714
+01:09:29,390 --> 01:09:36,470
+عشرين ثلاثين أربعين وسالب خمسة وأربعين. عشرين
+
+715
+01:09:36,470 --> 01:09:41,590
+ثلاثين أربعين سالب خمسة وأربعين. معناته أوصل بينهم
+
+716
+01:09:44,680 --> 01:09:49,200
+وهذه more circle
+
+717
+01:09:49,200 --> 01:09:53,560
+طبعاً الـ center الـ center يعني more circle هذا
+
+718
+01:09:53,560 --> 01:09:58,400
+الـ center C
+
+719
+01:09:58,400 --> 01:10:02,840
+هيساوي
+
+720
+01:10:02,840 --> 01:10:11,320
+σ<sub>X</sub> + σ<sub>Y</sub> / 2 يعني 0 + 40 / 2
+
+721
+01:10:11,320 --> 01:10:17,120
+بيساوي عشرين kilo pound per square inch. هذه المسافة
+
+722
+01:10:17,120 --> 01:10:23,400
+عبارة عن σ<sub>X</sub> - σ<sub>Y</sub> / 2 يعني هذه
+
+723
+01:10:23,400 --> 01:10:32,440
+المسافة عبارة عن أربعين برضه. عشرين وهذه عبارة عن
+
+724
+01:10:32,440 --> 01:10:37,720
+τ<sub>XY</sub> اللي هي خمسة وأربعين. معناته أنا already استعملت
+
+725
+01:10:37,720 --> 01:10:46,180
+circle R. استعملت جذر التربيع لعشرين تربيع زائد خمسة و
+
+726
+01:10:46,180 --> 01:10:51,400
+أربعين تربيع. عشرين تربيع زائد خمسة وأربعين تربيع
+
+727
+01:10:51,400 --> 01:11:04,420
+بيطلع
+
+728
+01:11:04,420 --> 01:11:10,620
+تسعة وأربعين فاصلة 24 تسعة وأربعين kilo
+
+729
+01:11:10,620 --> 01:11:16,370
+pound per square inch. معناته هذه سيجما واحد هذه في
+
+730
+01:11:16,370 --> 01:11:21,290
+المحصلة. سيجما اثنين وهذه سيجما ثلاثة. سيجما واحد
+
+731
+01:11:21,290 --> 01:11:32,850
+هتكون تساوي C + R اللي عشرين زائد تسعة
+
+732
+01:11:32,850 --> 01:11:38,110
+وأربعين يساوي تسعة وستين فاصلة 24 kilo
+
+733
+01:11:38,110 --> 01:11:43,590
+pound per square inch. وسيجما اثنين صفر والـ سيجما
+
+734
+01:11:43,590 --> 01:11:49,910
+ثلاثة اللي هي C - R اللي هي عشرين ناقص تسعة و
+
+735
+01:11:49,910 --> 01:11:55,170
+أربعين فاصلة 24 يعني الـ سيجما ثلاثة هتكون
+
+736
+01:11:55,170 --> 01:12:02,190
+تساوي سالب تسعة
+
+737
+01:12:02,190 --> 01:12:10,530
+وعشرين فاصلة 24 kilo
+
+738
+01:12:10,530 --> 01:12:15,820
+pound. واضح أنه عندي واحدة موجبة و
+
+739
+01:12:15,820 --> 01:12:19,400
+واحدة إيش؟ سالبة. معناته أن أنا في أي ربع؟ أنا في
+
+740
+01:12:19,400 --> 01:12:23,020
+الربع الرابع. الرابع. يعني لو رسمت الـ load line المرة هذه
+
+741
+01:12:23,020 --> 01:12:27,740
+هرسم هي
+
+742
+01:12:27,740 --> 01:12:37,440
+الـ σ<sub>a</sub> و σ<sub>b</sub>. أنا الـ load line تبعي 69
+
+743
+01:12:37,440 --> 01:12:41,020
+و -9 -29 يعني جاي الـ load line بالشكل هذا
+
+744
+01:12:44,210 --> 01:12:49,030
+الآن بدي أحكي هذا الـ maximum shear stress theory
+
+745
+01:12:49,030 --> 01:12:57,170
+هذا
+
+746
+01:12:57,170 --> 01:13:00,090
+الـ maximum shear stress theory والـ distortion
+
+747
+01:13:00,090 --> 01:13:01,650
+energy theory هتيجي بشكل هذا
+
+748
+01:13:13,290 --> 01:13:17,810
+هذه الأسود اللي هي الـ maximum which هي الـ stress
+
+749
+01:13:17,810 --> 01:13:22,550
+theory. وهذه الـ distortion energy theory. هذه الـ SY
+
+750
+01:13:22,550 --> 01:13:32,090
+اللي معطيني إياها هي 100 وهنا 100 وهنا سالب 100 وهنا
+
+751
+01:13:32,090 --> 01:13:39,390
+سالب 100. الـ load line تبعي 69 هذه النقطة هذه
+
+752
+01:13:42,180 --> 01:13:53,040
+تسعة وستين وأربع وعشرين وهذا سالب تسعة وعشرين وأربع
+
+753
+01:13:53,040 --> 01:13:56,760
+وعشرين
+
+754
+01:13:56,760 --> 01:14:01,400
+الآن
+
+755
+01:14:01,400 --> 01:14:07,160
+طبقاً لـ maximum shear stress theory. maximum shear
+
+756
+01:14:07,160 --> 01:14:08,800
+stress theory. هيكون
+
+757
+01:14:10,970 --> 01:14:17,330
+يساوي سيجما واحد ناقص سيجما ثلاثة على اثنين اللي
+
+758
+01:14:17,330 --> 01:14:22,790
+هتساوي الـ radius هتساوي اللي هو الـ radius بتاع مور
+
+759
+01:14:22,790 --> 01:14:28,410
+circle اللي هتكون تسعة وأربعين فاصلة 24
+
+760
+01:14:28,410 --> 01:14:38,210
+kilo pound per square inch. الـ
+
+761
+01:14:38,210 --> 01:14:45,740
+SSY بيساوي نصف الـ SY يعني هتكون خمسين كيلو pound per
+
+762
+01:14:45,740 --> 01:14:55,260
+square inch. الـ N بيساوي SSY / τ<sub>max</sub>. الـ SSY
+
+763
+01:14:55,260 --> 01:15:02,080
+اللي هي خمسين على تسعة وأربعين فاصلة 24 أو
+
+764
+01:15:02,080 --> 01:15:05,040
+almost واحد. تقريباً خمسين
+
+765
+01:15:06,840 --> 01:15:10,480
+تقسيم تسعة وأربعين فاصلة 24. تقسيم تسعة
+
+766
+01:15:10,480 --> 01:15:12,280
+وأربعين فاصلة 24. تقسيم تسعة وأربعين فاصلة
+
+767
+01:15:12,280 --> 01:15:14,400
+24. تقسيم تسعة وأربع. تقسيم تسعة وأربع. تقسيم
+
+768
+01:15:14,400 --> 01:15:20,900
+تسعة وأربع. تقسيم تسعة وأربع. تقسيم تسعة وأربع. تقسيم
+
+769
+01:15:20,900 --> 01:15:23,680
+تسعة وأربع. تقسيم تسعة وأربع. تقسيم تسعة وأربع. تقسيم
+
+770
+01:15:23,680 --> 01:15:27,880
+تسعة وأربع. تقسيم تسعة وأربع. تقسيم تسعة وأربع. تقسيم
+
+771
+01:15:27,880 --> 01:15:34,840
+تسعة وأربع. تقسيم تسعة وأربع. تقسيم تسعة وأربع. تقسيم
+
+772
+01:15:34,840 --> 01:15:43,160
+تسعة وأربع. سيجما a اللي هي تسعة وستين وأربع وعشرين
+
+773
+01:15:43,160 --> 01:15:46,940
+ناقص
+
+774
+01:15:46,940 --> 01:15:53,000
+سيجما b اللي هي تسعة وستين وأربع وعشرين فيه
+
+775
+01:15:53,000 --> 01:15:58,580
+سيجما b سالب تسعة وعشرين فاصلة 24 زائد
+
+776
+01:15:58,580 --> 01:16:04,160
+تسعة وعشرين فاصلة 24 تربيع الكل تحت الجذر. نصف منها
+
+777
+01:16:04,160 --> 01:16:05,280
+بنحسب سيجما prime
+
+778
+01:16:08,080 --> 01:16:12,760
+اللي هتكون تسعة
+
+779
+01:16:12,760 --> 01:16:18,580
+وستين فاصلة 24 تربيع زائد تسعة وستين
+
+780
+01:16:18,580 --> 01:16:22,480
+فاصلة 24 في تسعة وعشرين فاصلة 24
+
+781
+01:16:22,480 --> 01:16:28,720
+زائد تسعة وعشرين فاصلة 24 تربيع يساوي
+
+782
+01:16:28,720 --> 01:16:31,160
+تطلع سبعة وثمانين فاصلة 6
+
+783
+01:16:38,540 --> 01:16:47,580
+الآن هيكون متساوي SY / σ' . SY اللي هي
+
+784
+01:16:47,580 --> 01:17:00,500
+مئة على سبعة وثمانين فاصلة 6 مئة تطلع
+
+785
+01:17:00,500 --> 01:17:06,320
+واحد فاصلة 142
+
+786
+01:17:10,940 --> 01:17:14,000
+ممكن أحكي برضه N في الـ .. أنا .. أنا حالياً أنا ..
+
+787
+01:17:14,000 --> 01:17:16,200
+أنا في الـ fourth quadrant. أنا في الـ fourth
+
+788
+01:17:16,200 --> 01:17:21,280
+quadrant. ممكن
+
+789
+01:17:21,280 --> 01:17:29,560
+أحكي أنه برضه الـ N بيساوي SSY / τ<sub>max</sub>. SSY
+
+790
+01:17:29,560 --> 01:17:36,660
+اللي هي خمسين. الـ
+
+791
+01:17:36,660 --> 01:17:38,400
+SSY في الحالة هتبقى إيش بيساوي؟
+
+792
+01:17:40,740 --> 01:17:44,200
+الـ SSY في distortion energy theory. SSY
+
+793
+01:17:44,200 --> 01:17:50,080
+سبعة وخمسة وسبعة وسبعة SSY يعني هتكون سبعة وخمسين
+
+794
+01:17:50,080 --> 01:17:53,720
+فاصلة سبعة كيلو pound per square inch. يعني هتكون S
+
+795
+01:17:53,720 --> 01:17:57,940
+SY بيساوي سبعة وخمسين فاصلة سبعة على τ
+
+796
+01:17:57,940 --> 01:18:01,900
+<sub>max</sub> اللي هي حسبناها تسعة وأربعين فاصلة 24. سبعة وخمسين
+
+797
+01:18:01,900 --> 01:18:03,620
+فاصلة سبعة
+
+798
+01:18:11,060 --> 01:18:23,300
+لا واحد فاصلة سبعة واحد. طيب المحاضرة
+
+799
+01:18:23,300 --> 01:18:29,360
+الجاية بنكمل .. المحاضرة الجاية بنكمل بنحل مسائل
+
+800
+01:18:29,360 --> 01:18:34,760
+ثانية أو بنتعرف على new theory اللي هي more theory
+
+801
+01:18:34,760 --> 01:18:38,560
+وهنحل مسائل كلها more theory
+
+802
+01:18:42,860 --> 01:18:47,120
+هنحل مسألة خمسة اثنين وخمسة ثلاثة وخمسة أربعة
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/GdwYlgLJm0Y_postprocess.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/GdwYlgLJm0Y_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..ff77e085965669737ce879016fd275cf382b7148
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/GdwYlgLJm0Y_postprocess.srt
@@ -0,0 +1,3208 @@
+1
+00:00:04,890 --> 00:00:07,630
+بسم الله الرحمن الرحيم السلام عليكم ورحمة الله
+
+2
+00:00:07,630 --> 00:00:10,970
+وبركاته اليوم هنستكمل الهو failures resulting from
+
+3
+00:00:10,970 --> 00:00:15,810
+static loading المحاضرات الفاتة استعرضتنا اللي هي
+
+4
+00:00:15,810 --> 00:00:22,030
+خارطة الطريق لل .. لل static .. لل failure
+
+5
+00:00:22,030 --> 00:00:25,790
+criterion selection حكينا أول شيء لازم نفحص نشوف
+
+6
+00:00:25,790 --> 00:00:30,600
+المادة هل هي ductile ولا brittleالـ ductility or
+
+7
+00:00:30,600 --> 00:00:33,820
+brittleness is examined via ال .. ال .. ال .. هو
+
+8
+00:00:33,820 --> 00:00:36,600
+ال epsilon f إذا ال epsilon f أكبر يستوى point oh
+
+9
+00:00:36,600 --> 00:00:39,520
+five معناته المثير is ductile إذا ال epsilon f أقل
+
+10
+00:00:39,520 --> 00:00:42,360
+من أكبر من point oh five معناته المثير is brittle
+
+11
+00:00:42,360 --> 00:00:47,980
+الآن الجهة هذه ductile الجهة هذه إيش brittle أول
+
+12
+00:00:48,800 --> 00:00:51,720
+check for ductile material I want to check إذا كان
+
+13
+00:00:51,720 --> 00:00:54,280
+ال yield strength in tension بيستوى yield strength
+
+14
+00:00:54,280 --> 00:00:56,360
+in compression إذا كان yield strength in tension
+
+15
+00:00:56,360 --> 00:01:00,500
+بيستوى yield strength in compression معناته ياما
+
+16
+00:01:00,500 --> 00:01:04,300
+بدي أحصل على conservative calculations أو more
+
+17
+00:01:04,300 --> 00:01:07,040
+accurate less conservative calculations if I'm
+
+18
+00:01:07,040 --> 00:01:11,560
+interested in more conservative less risky
+
+19
+00:01:11,560 --> 00:01:14,380
+calculations ممكن أستخدم ال maximum shear stress
+
+20
+00:01:14,380 --> 00:01:19,960
+theory إذا أنا يعني إذا أنامعنى في ال .. ال ..
+
+21
+00:01:19,960 --> 00:01:24,580
+اللي هي more accurate results less conservative
+
+22
+00:01:24,580 --> 00:01:27,840
+ممكن أستخدم اللي هي ال distortion energy theory
+
+23
+00:01:27,840 --> 00:01:33,320
+طيب السؤال بيطرح نفسه طيب ما زال اللي هو ال .. ال
+
+24
+00:01:33,320 --> 00:01:36,220
+.. ال .. الآن في حالة ال conservative theories
+
+25
+00:01:36,220 --> 00:01:39,620
+عنده عنصر مخاطب الحسابات أقل ليش ماشتغل دايما
+
+26
+00:01:39,620 --> 00:01:43,910
+conservative لألو انا مثلا انا بدي أنتج من ال ..
+
+27
+00:01:43,910 --> 00:01:47,710
+ال mechanical ان بدي أنتج مثلا عشر قطع، مية قطع،
+
+28
+00:01:47,710 --> 00:01:51,970
+الف قطع، الكمية هادة، صغيرة، في الحالة هادة بفضل
+
+29
+00:01:51,970 --> 00:01:55,910
+اشتغل according to conservative calculations لكن
+
+30
+00:01:55,910 --> 00:02:02,030
+انا لو بدي أنتج .. أنتج قطع موجودة في السيارة مثلا
+
+31
+00:02:02,030 --> 00:02:08,190
+بدي اعمل screw او برغة عدد البراغي في السيارة في
+
+32
+00:02:08,190 --> 00:02:12,270
+ال .. في مثلا عندي مية برغة من نفس النوعوفترض ان
+
+33
+00:02:12,270 --> 00:02:16,830
+الشركة بتنتج كل يوم عشر تلاف سيارة عشر تلاف
+
+34
+00:02:16,830 --> 00:02:20,750
+تلاتمية خمس ستين فتخيل اكم قطع هنتج ملايين القطع
+
+35
+00:02:20,750 --> 00:02:24,790
+معناته انا لما تكون ال calculation more
+
+36
+00:02:24,790 --> 00:02:28,910
+conservative معناته هستخدم مواد اكتر هستهلك مواد
+
+37
+00:02:28,910 --> 00:02:32,910
+اكتر فالتكلفة هتكون بترتفع في الحالة هذه بلجأ
+
+38
+00:02:32,910 --> 00:02:36,970
+لاستخدام more accurate او more accurate
+
+39
+00:02:38,240 --> 00:02:42,280
+calculations او فبستخدم مثلا theories اللي هي more
+
+40
+00:02:42,280 --> 00:02:45,580
+accurate theories في الحالات اللي بوفر في المواد و
+
+41
+00:02:45,580 --> 00:02:49,740
+في ال materials في حالة اندي huge mass .. mass
+
+42
+00:02:49,740 --> 00:02:54,690
+productionمعناته في حالة ductile material وكانت ال
+
+43
+00:02:54,690 --> 00:02:56,790
+yield strength in tension بستوي yield strength in
+
+44
+00:02:56,790 --> 00:03:00,090
+compression if I need conservative calculations I
+
+45
+00:03:00,090 --> 00:03:02,770
+use the maximum shear stress theory if I need more
+
+46
+00:03:02,770 --> 00:03:05,550
+accurate less conservative calculations I use the
+
+47
+00:03:05,550 --> 00:03:08,610
+distortion energy theory الآن إذا كانت ال yield
+
+48
+00:03:08,610 --> 00:03:10,570
+strength in tension بستوي yield strength in
+
+49
+00:03:10,570 --> 00:03:13,210
+compression بستخدم ductile columnar theory في حالة
+
+50
+00:03:13,210 --> 00:03:18,100
+ال ductile material الآن الجهة تمثل الالـ brittle
+
+51
+00:03:18,100 --> 00:03:21,780
+material إذا كانت ال material brittle if I want
+
+52
+00:03:21,780 --> 00:03:26,300
+conservative less risky calculations I use brittle
+
+53
+00:03:26,300 --> 00:03:31,500
+column more theory if I need more accurate more
+
+54
+00:03:31,500 --> 00:03:36,200
+risky calculations I use modified more theoryالان
+
+55
+00:03:36,200 --> 00:03:38,500
+حكينا عن ال maximum normal stress theory ال
+
+56
+00:03:38,500 --> 00:03:40,420
+maximum .. ال maximum normal stress theory بتحكي
+
+57
+00:03:40,420 --> 00:03:44,500
+انه ال yielding او ال failure ببدأ لما ال maximum
+
+58
+00:03:44,500 --> 00:03:47,900
+principal stress في ال mechanical element بيكون
+
+59
+00:03:47,900 --> 00:03:51,120
+اكبر او يساوي ال yield strength ده ال material
+
+60
+00:03:51,120 --> 00:03:54,740
+يعني ال .. احنا ال principal stresses بنحسبها من
+
+61
+00:03:54,740 --> 00:03:57,400
+مورسلك بنحسب سجن واحد سجن اتنين و سجن تلاتي يعني
+
+62
+00:03:57,400 --> 00:04:00,360
+اذا كان سجن واحد اكبر أو يساوي اسواء يصير اندي
+
+63
+00:04:00,360 --> 00:04:04,800
+yielding يصير اندي failureال maximum طبعا ال
+
+64
+00:04:04,800 --> 00:04:06,820
+maximum normal stress theory is not conservative
+
+65
+00:04:06,820 --> 00:04:12,460
+in the fourth quadrant لأن
+
+66
+00:04:12,460 --> 00:04:17,520
+ال maximum normal stress theory ممكن تحكيلي ان ال
+
+67
+00:04:17,520 --> 00:04:21,780
+part is not failing while actually it fails يعني
+
+68
+00:04:21,780 --> 00:04:25,000
+بتحكيلي ان ال part مش failure لكن في الواقع
+
+69
+00:04:25,000 --> 00:04:33,130
+failure عشان هيكbut يعني .. يعني انا عن نفسي شخصيا
+
+70
+00:04:33,130 --> 00:04:35,650
+و عالميا ما بستخدم ال maximum normal stress theory
+
+71
+00:04:35,650 --> 00:04:40,510
+for .. for design calculations ال maximum shear
+
+72
+00:04:40,510 --> 00:04:43,490
+stress .. stress theory بتحكي ان ال yielding ببدأ
+
+73
+00:04:43,490 --> 00:04:47,490
+لما ال maximum shear stress .. ال maximum shear
+
+74
+00:04:47,490 --> 00:04:51,070
+stress في stress element اللي هو الحقيقة بتكون
+
+75
+00:04:51,070 --> 00:04:54,850
+أكبر او يساوي ال maximum shear stress في tensile
+
+76
+00:04:54,850 --> 00:05:00,380
+test specimen بمعنىانه بيصير failure لما ال tau
+
+77
+00:05:00,380 --> 00:05:04,400
+maximum تكون اكبر او يساوي as y على 2 و احنا في ال
+
+78
+00:05:04,400 --> 00:05:06,480
+.. لما كنا عندى multistate of stress كنا نحسس
+
+79
+00:05:06,480 --> 00:05:10,140
+sigma 1 و sigma 2 و sigma 3 و الرتبهم بيحس sigma 1
+
+80
+00:05:10,140 --> 00:05:13,220
+اكبر من sigma 2 اكبر من sigma 3 و ال tau maximum
+
+81
+00:05:13,220 --> 00:05:17,560
+كان يساوي as sigma 1 minus sigma 2 ف according to
+
+82
+00:05:17,560 --> 00:05:20,960
+maximum shear stress theory بيكون عندى ال .. ال ..
+
+83
+00:05:21,740 --> 00:05:25,240
+تاو ماكسوم يستوى سجما واحد ناقصه سجما تلاته على
+
+84
+00:05:25,240 --> 00:05:27,940
+اتنين بيصير failure لما تاو ماكسوم يكون اكبر او
+
+85
+00:05:27,940 --> 00:05:33,220
+يستوى اس و اي على اتنين اخدنا
+
+86
+00:05:33,220 --> 00:05:37,500
+two D states of stress و رسمنا اللي هو inferior
+
+87
+00:05:37,500 --> 00:05:41,240
+contour ل maximum shear stress theory عندنا case
+
+88
+00:05:41,240 --> 00:05:45,820
+one هذه case one ان سجما a اكبر من سجما b اكبر من
+
+89
+00:05:45,820 --> 00:05:50,090
+صفر يعني سجما a و سجما b موجبات في الحالة هذهبيكون
+
+90
+00:05:50,090 --> 00:05:54,050
+عندي .. بيصير failure لما sigma a تكون أكبر أو
+
+91
+00:05:54,050 --> 00:05:59,650
+يساوي as y case two ان sigma ا موجة و sigma b
+
+92
+00:05:59,650 --> 00:06:05,410
+سالبة في الحالة هذه sigma a minus sigma b بتكون
+
+93
+00:06:05,410 --> 00:06:10,010
+أكبر أو يساوي as y ال case التالتة both sigma a
+
+94
+00:06:10,010 --> 00:06:14,030
+and sigma b are negative بيصير failure لما sigma b
+
+95
+00:06:14,030 --> 00:06:19,400
+تكون أقل أو يساوم سالب as yif we compare ال
+
+96
+00:06:19,400 --> 00:06:21,940
+maximum shear stress theory with empirical او
+
+97
+00:06:21,940 --> 00:06:26,060
+experimental data بنلاحظ انه بتعطيني conservative
+
+98
+00:06:26,060 --> 00:06:29,640
+results انه ال maximum shear stress theory
+
+99
+00:06:29,640 --> 00:06:34,180
+predicts failure before actually it fails عشان كده
+
+100
+00:06:34,180 --> 00:06:37,180
+بسميها conservative theory طبعا في كل quadrant
+
+101
+00:06:37,180 --> 00:06:39,800
+سواء كان في ال quadrant الأول او ال quadrant
+
+102
+00:06:39,800 --> 00:06:44,600
+الرابع we predict failure before failure actually
+
+103
+00:06:44,600 --> 00:06:50,620
+happensالان اليوم هنحكي على نظرية جديدة اللي هي
+
+104
+00:06:50,620 --> 00:06:55,220
+distortion energy theory distortion energy theory
+
+105
+00:06:55,220 --> 00:06:58,000
+distortion energy theory في كتير من الكتب
+
+106
+00:06:58,000 --> 00:07:02,860
+بيستخدموا أسماء مختلفة لها أسماء أخرى للنظرية في
+
+107
+00:07:02,860 --> 00:07:05,740
+كتب تانية ماكنت تلاحظوها اللي هي octahedral shear
+
+108
+00:07:05,740 --> 00:07:06,540
+stress theory
+
+109
+00:07:09,110 --> 00:07:13,770
+الـ shear energy theory هذا اسم تاني اسم تالت Von
+
+110
+00:07:13,770 --> 00:07:18,950
+Mises Theory اسم رابع اللي هي Von Mises-Henke
+
+111
+00:07:18,950 --> 00:07:22,370
+Theory معناته هذه إذا تروح لمراجع تانية ممكن
+
+112
+00:07:22,370 --> 00:07:26,090
+تلاحظوا إليها أسماء متداولة أسماء مختلفة اللي هي
+
+113
+00:07:26,090 --> 00:07:29,330
+octahedral shear stress theory shear energy theory
+
+114
+00:07:29,330 --> 00:07:32,590
+Von Mises Theory و Von Mises-Henke Theory
+
+115
+00:07:36,750 --> 00:07:43,070
+الان تقديم او تحضير لل .. لل theory هذا اول ملاحظة
+
+116
+00:07:43,070 --> 00:07:45,690
+لاحظوا tactile materials stressed hydrostatically
+
+117
+00:07:45,690 --> 00:07:48,330
+exhibit yield strength greatly in excess of
+
+118
+00:07:48,330 --> 00:07:51,590
+expected values يعني لو حطيت انا قطعة تحت سطح
+
+119
+00:07:51,590 --> 00:07:58,550
+البحر مكعب في مياه
+
+120
+00:08:04,990 --> 00:08:11,530
+hydrostatic stress معناته بتعرض
+
+121
+00:08:11,530 --> 00:08:23,090
+لضغط من كل الجهات الآن
+
+122
+00:08:23,090 --> 00:08:25,690
+إذا بيكون ال mechanical element العالم افترض انه
+
+123
+00:08:25,690 --> 00:08:30,030
+على شكل مكعب متعرض
+
+124
+00:08:30,030 --> 00:08:33,030
+لهydrostatic pressure او hydrostatic state of
+
+125
+00:08:33,030 --> 00:08:33,450
+stress
+
+126
+00:08:36,120 --> 00:08:40,660
+معناته due to poison effect لو أخدت ال sigma هذه
+
+127
+00:08:40,660 --> 00:08:43,740
+ال sigma هذه بتحاول ايش تضغط بتحاول تكبر ال
+
+128
+00:08:43,740 --> 00:08:47,460
+dimensions في الاتجاهات التانية التانية الأخرين ال
+
+129
+00:08:47,460 --> 00:08:50,280
+sigma هذه بتحاول تعكس ال effect تاعتها ده يعني هذه
+
+130
+00:08:50,280 --> 00:08:54,500
+بتحاول تتزغر زي هيك و تكبر الجهة التانية هذه
+
+131
+00:08:54,500 --> 00:08:56,940
+بتحاول تزغر هيك و تكبر الجهة التانية فهذه بتعكس
+
+132
+00:08:56,940 --> 00:09:00,640
+هذه و هذه بتعكس هذه يعني بعكس و في بعض فال
+
+133
+00:09:00,640 --> 00:09:04,180
+material بتتحمل yield strength عالي جدا جدا في
+
+134
+00:09:04,180 --> 00:09:10,850
+حالةاللي هو hydrostatic loading condition معناته
+
+135
+00:09:10,850 --> 00:09:15,390
+ممكن اعتبر انه في حالة hydrostatic loading
+
+136
+00:09:15,390 --> 00:09:18,790
+condition انه المادية ممكن تتحمل infinite state of
+
+137
+00:09:18,790 --> 00:09:21,350
+stress يعني ممكن يكون ال stress very very very
+
+138
+00:09:21,350 --> 00:09:30,730
+huge وهذا حقيقة هذا الآن ال ..في الواقع مايكونش
+
+139
+00:09:30,730 --> 00:09:35,050
+الـ mechanical element under a pure hydrostatic
+
+140
+00:09:35,050 --> 00:09:38,810
+loading condition مايكونش ال sigma زي هذه متساومة
+
+141
+00:09:38,810 --> 00:09:43,330
+بيكون ان دي sigma واحدو sigma 2 و sigma 3 يعني
+
+142
+00:09:43,330 --> 00:09:47,010
+sigma 1 مختلفة قيمتها عن sigma 2 مختلفة عن sigma 3
+
+143
+00:09:47,010 --> 00:09:51,030
+طالما ان sigma 1 و sigma 2 و sigma 3 الان ال duty
+
+144
+00:09:51,030 --> 00:09:54,190
+sigma 1 و sigma 2 و sigma 3 بيصير تشوه للمادة
+
+145
+00:09:54,190 --> 00:09:57,750
+بيصير في عندى strain ال strain energy ممكن اقسمها
+
+146
+00:09:57,750 --> 00:10:04,150
+لجزءين جزء بيعمل لي volume change بيغير الحجم اذا
+
+147
+00:10:04,150 --> 00:10:07,930
+انا مضغطه من كل جهات بيحاول ايش اصغر حجمها وجزء
+
+148
+00:10:07,930 --> 00:10:13,890
+التاني بيحاول ايشيشوّهها يغير الشكل ت distorted
+
+149
+00:10:13,890 --> 00:10:19,710
+معناته strain energy ممكن تكون تاخد شكلين شكل
+
+150
+00:10:19,710 --> 00:10:23,790
+بيغير في الحجم جزء بيغير في الحجم وجزء بيغير
+
+151
+00:10:23,790 --> 00:10:29,950
+بالشكل اللي هو angular distortion energy yielding
+
+152
+00:10:29,950 --> 00:10:34,710
+احنا حكينا جزئية بتغير الحجم هي جزئية due to
+
+153
+00:10:34,710 --> 00:10:38,730
+hydrostatic state of stress وهذه ما بتعمل yielding
+
+154
+00:10:38,730 --> 00:10:43,100
+yielding primarilyis affected by the distortion
+
+155
+00:10:43,100 --> 00:10:48,440
+energy part اللي هو الجزء اللي بيغير شكل ال
+
+156
+00:10:48,440 --> 00:10:56,360
+mechanical part الان
+
+157
+00:10:56,360 --> 00:10:59,620
+ال distortion energy failure theory بتحكي التالت
+
+158
+00:10:59,620 --> 00:11:02,760
+بتحكي yielding occurs بتحكي yielding او failure
+
+159
+00:11:02,760 --> 00:11:09,130
+بيصير لماالدستورشن دمج طاقة على جزء من الوزياء
+
+160
+00:11:09,130 --> 00:11:15,710
+للأشياء الميكانية تحت التدريب تصل إلى دستورشن دمج
+
+161
+00:11:15,710 --> 00:11:21,730
+طاقة على جزء من الوزياء للدفع في مجلة تنسيل بسيطة
+
+162
+00:11:23,320 --> 00:11:26,320
+having the same material معناته distortion energy
+
+163
+00:11:26,320 --> 00:11:29,000
+theory بتحكي انه بيصير failure او بيصير yielding
+
+164
+00:11:29,000 --> 00:11:33,800
+لما distortion strain energy per unit volume in
+
+165
+00:11:33,800 --> 00:11:38,160
+the mechanical element under study reaches the
+
+166
+00:11:38,160 --> 00:11:43,360
+distortion strain energy per unit volume of a
+
+167
+00:11:43,360 --> 00:11:46,600
+tensile test specimen of the same material في
+
+168
+00:11:46,600 --> 00:11:49,520
+الحالة هذه بيصير ايش عنده yielding او بيصير
+
+169
+00:11:49,520 --> 00:11:54,730
+failureأنا باين عندي هنا mechanical element و ماخد
+
+170
+00:11:54,730 --> 00:11:58,030
+ال principle state stress element يعني عندي هنا
+
+171
+00:11:58,030 --> 00:12:06,630
+سجما واحد و هنا سجما اتنين و هنا سجما تلاتة ممكن
+
+172
+00:12:06,630 --> 00:12:14,330
+احكي هذا بيساوي التالي this element ال equivalent
+
+173
+00:12:14,330 --> 00:12:17,810
+للمجموعة ال element هذا و ال element هذا ال
+
+174
+00:12:17,810 --> 00:12:23,340
+element هذا متعرض لسجما averageSigma Average و
+
+175
+00:12:23,340 --> 00:12:32,820
+Sigma Average Sigma Average بالساوية سيجما واحد
+
+176
+00:12:32,820 --> 00:12:40,220
+زائد سيجما اتنين زائد سيجما تلاتة على تلاتة زائد
+
+177
+00:12:40,220 --> 00:12:43,880
+another element وهو عبارة عن سيجما واحد minus
+
+178
+00:12:43,880 --> 00:12:48,840
+sigma average وهين sigma اتنين minus sigma average
+
+179
+00:12:49,790 --> 00:12:53,770
+وهنا sigma تلاتة minus sigma average يعني لو
+
+180
+00:12:53,770 --> 00:12:57,690
+جمعتين هذا مع هذا هتروح sigma average مع sigma
+
+181
+00:12:57,690 --> 00:13:00,550
+average بيبقى لعندي sigma واحد لو جماعة هذا مع هذا
+
+182
+00:13:00,550 --> 00:13:02,330
+بتروح sigma average مع sigma average بيبقى لعندي
+
+183
+00:13:02,330 --> 00:13:06,170
+sigma اتنين لو جماعة هذا اللي هو sigma هذا بتروح
+
+184
+00:13:06,170 --> 00:13:08,090
+sigma average مع sigma average بيبقى لعندي sigma
+
+185
+00:13:08,090 --> 00:13:10,590
+تلاتة معناته هذا ال element equivalent to these
+
+186
+00:13:10,590 --> 00:13:11,510
+two elements
+
+187
+00:13:18,890 --> 00:13:23,930
+الـ Strain Energy Per Unit Volume من Chapter 4 الـ
+
+188
+00:13:23,930 --> 00:13:34,350
+U لكل واحدة حجم بتساوي اللي هي نص في
+
+189
+00:13:34,350 --> 00:13:40,570
+أبسلون واحد سجن واحد زاد أبسلون اتنين سجن اتنين
+
+190
+00:13:40,570 --> 00:13:44,630
+زاد أبسلون تلاتة سجن تلاتة
+
+191
+00:13:47,460 --> 00:13:54,420
+و أبسلون واحد بيصيح واحد على ايه في سجن واحد ناقص
+
+192
+00:13:54,420 --> 00:13:59,560
+ال U في سجن اتنين زائد سجن تلاتة هذا شفتر أربعة و
+
+193
+00:13:59,560 --> 00:14:05,240
+أبسلون اتنين بيصيح واحد على ايه في سجن اتنين minus
+
+194
+00:14:05,240 --> 00:14:12,160
+U في سجن واحد زائد سجن تلاتة و أبسلون تلاتة بيصيح
+
+195
+00:14:12,160 --> 00:14:14,600
+واحد على ايه في
+
+196
+00:14:18,950 --> 00:14:29,570
+سيجما تلاتة minus U في سيجما واحد زائد سيجما اتنين
+
+197
+00:14:29,570 --> 00:14:35,650
+الان اللي عوضنا عن في المعادلة هذه عن أبسل واحد
+
+198
+00:14:35,650 --> 00:14:38,470
+اقصى اتنين اقصى تلاتة بس ال U ال total distortion
+
+199
+00:14:38,470 --> 00:14:44,510
+ال U per unit volume بسعة نص فيه
+
+200
+00:14:44,510 --> 00:14:57,060
+أبسل واحدوحد على ايه في سجما واحد minus in you في
+
+201
+00:14:57,060 --> 00:15:04,500
+سجما اتنين زائد سجما تلاتة زائد
+
+202
+00:15:04,500 --> 00:15:16,120
+واحد على ايه في طبعا هنا في سجما واحد زائد سجما
+
+203
+00:15:16,120 --> 00:15:26,080
+اتنينعلى E في Sigma 2 minus U في Sigma 1 زائد
+
+204
+00:15:26,080 --> 00:15:39,040
+Sigma 3 زائد Sigma 3 على E في Sigma 3 minus U في
+
+205
+00:15:39,040 --> 00:15:41,420
+Sigma 1 زائد Sigma 2
+
+206
+00:15:46,310 --> 00:15:55,490
+هطلع طبعا هطلع واحد على اتنين اي عامل مشترك بيصير
+
+207
+00:15:55,490 --> 00:16:03,510
+هنا دي سجم واحد تربيع خلصت من هذه minus
+
+208
+00:16:03,510 --> 00:16:10,470
+new يعني هجمعهم مع بعض هاخد هذه سجم واحد تربيع زي
+
+209
+00:16:10,470 --> 00:16:18,330
+سجم اتنين تربيعزائر سيجما تلاتة تربيع يعني خلصت من
+
+210
+00:16:18,330 --> 00:16:32,370
+هذه وهذه وهذه minus in you في عند
+
+211
+00:16:32,370 --> 00:16:39,870
+سيجما واحد سيجما اتنين زائر سيجما واحد سيجما تلاتة
+
+212
+00:16:41,020 --> 00:16:49,080
+زاد سجما واحد سجما اتنين زاد سجما اتنين سجما تلاتة
+
+213
+00:16:49,080 --> 00:16:58,740
+زاد سجما واحد سجما تلاتة زاد سجما اتنين سجما تلاتة
+
+214
+00:16:58,740 --> 00:17:07,490
+خسيرا دي واحد على اتنين E فيسيجما واحد تربيع زائر
+
+215
+00:17:07,490 --> 00:17:11,810
+سيجما اتنين تربيع زائر سيجما تلاتة تربيع minus ال
+
+216
+00:17:11,810 --> 00:17:19,130
+U في اتنين ال U في سيجما
+
+217
+00:17:19,130 --> 00:17:24,490
+واحد سيجما اتنين زائر سيجما واحد سيجما تلاتة زائر
+
+218
+00:17:24,490 --> 00:17:30,210
+سيجما اتنين سيجما تلاتة هذا ال total distortion
+
+219
+00:17:30,210 --> 00:17:36,570
+energyلأن إذا بدى أحسب ال distortion energy per
+
+220
+00:17:36,570 --> 00:17:40,510
+unit volume due to static loading يعني due to
+
+221
+00:17:40,510 --> 00:17:44,810
+sigma average if for
+
+222
+00:17:44,810 --> 00:17:50,990
+a hydrostatic
+
+223
+00:17:50,990 --> 00:17:57,730
+element في الحالة هذي بتكون sigma 1 بيساوي sigma 2
+
+224
+00:17:57,730 --> 00:18:01,960
+بيساوي sigma 3 بيساوي sigma averageهيصير عندى هنا
+
+225
+00:18:01,960 --> 00:18:10,700
+ال U اللى هى ال U هايدروستاتك اتش هتسميها هتكون
+
+226
+00:18:10,700 --> 00:18:20,380
+واحد على اتنين E فيه هتكون هنا عندى هيطلع عندى
+
+227
+00:18:20,380 --> 00:18:25,460
+sigma average تربية سيجما افرج سيجما افرج سيجما
+
+228
+00:18:25,460 --> 00:18:29,840
+افرج سيجما افرج في
+
+229
+00:18:29,840 --> 00:18:30,740
+واحد
+
+230
+00:18:38,610 --> 00:18:42,510
+-2NU خلّيني أعملها بطوطين
+
+231
+00:18:45,590 --> 00:18:50,250
+في sigma average تسمى تلاتة تلاتة sigma average
+
+232
+00:18:50,250 --> 00:18:59,090
+تربيع ناقص اتنين in U في تلاتة sigma average تربيع
+
+233
+00:18:59,090 --> 00:19:08,710
+يعني هتكون تساوي تلاتة sigma average تربيع على
+
+234
+00:19:08,710 --> 00:19:13,910
+اتنين E في واحد ناقص اتنين in U
+
+235
+00:19:17,350 --> 00:19:19,790
+و ال sigma average احنا حكينا بيساوي sigma 1 زي
+
+236
+00:19:19,790 --> 00:19:25,030
+sigma 2 زي sigma 3 على 3 اللي انا اذا بعوض عن
+
+237
+00:19:25,030 --> 00:19:32,530
+sigma average و simplify ال U volume هتعطي
+
+238
+00:19:32,530 --> 00:19:37,030
+بالعلاقة هذه اللي هي واحد ناقص اتنين
+
+239
+00:19:45,520 --> 00:19:48,280
+هتكون واحد نقص اتنين على ستة ايه في سجن واحد تربيع
+
+240
+00:19:48,280 --> 00:19:50,660
+زي سجن اتنين تربيع زي سجن تلات تربيع زي اتنين سجن
+
+241
+00:19:50,660 --> 00:19:53,480
+واحد سجن اتنين زي اتنين سجن اتنين سجن تلاتة وزي
+
+242
+00:19:53,480 --> 00:19:56,660
+اتنين سجن تلاتة سجن واحد الان ال total energy U
+
+243
+00:19:58,780 --> 00:20:02,580
+بستوي U due to volume change زي U due to
+
+244
+00:20:02,580 --> 00:20:11,180
+distortion بيستوي U-UV انا عارف U وعارف UV بحسو ال
+
+245
+00:20:11,180 --> 00:20:15,440
+U distortion بحكي U distortion بيستوي U-UV بعوض و
+
+246
+00:20:15,440 --> 00:20:19,180
+بعمل تبسيط بيصير ال U due to distortion بيستوي
+
+247
+00:20:19,180 --> 00:20:22,820
+واحد زي ال U على التلاتة E في سجن واحدمينا سجن
+
+248
+00:20:22,820 --> 00:20:25,100
+اتنين لكل تربيع زي سجن اتنين نقص سجن تلاتي لكل
+
+249
+00:20:25,100 --> 00:20:33,280
+تربيع زي سجن تلاتي من سجن واحد لكل تربيع الان
+
+250
+00:20:33,280 --> 00:20:46,120
+for for
+
+251
+00:20:46,120 --> 00:20:51,660
+a tensile test specimen for a tensile
+
+252
+00:20:55,070 --> 00:21:03,350
+test specimen بيكون عندي يعني هاي عند ال stress
+
+253
+00:21:03,350 --> 00:21:08,450
+element بيكون عليه إيه إيش سيجما واحد سيجما واحد
+
+254
+00:21:08,450 --> 00:21:12,270
+بيكون عندي سيجما اتنين بيساوي سيجما تلاتة بيساوي
+
+255
+00:21:12,270 --> 00:21:17,210
+صفر معناته ال U distortion for a tensile specimen
+
+256
+00:21:17,210 --> 00:21:22,450
+اللي هو خلينا نحكي ال yielding UY
+
+257
+00:21:24,180 --> 00:21:32,320
+سأحوض واحد زائد new ع تلاتة اي في ستكون هذه صفر
+
+258
+00:21:32,320 --> 00:21:43,060
+صفر و صفر يعني ستكون عندهين sigma
+
+259
+00:21:43,060 --> 00:21:47,140
+واحد sigma
+
+260
+00:21:47,140 --> 00:21:52,920
+واحد تربيع sigma
+
+261
+00:21:52,920 --> 00:22:03,910
+واحدتربيع اللي هي هذه زي ال sigma واحد تربيع
+
+262
+00:22:03,910 --> 00:22:13,130
+على اتنين لأنها تكون تساوي واحد زي ال U ع تلاتة A
+
+263
+00:22:13,130 --> 00:22:19,190
+في sigma واحد تربيع
+
+264
+00:22:27,350 --> 00:22:31,110
+و ال tensile test specimen yields لما sigma 1 سوى
+
+265
+00:22:31,110 --> 00:22:38,010
+sigma Sy يعني ال U ال yielding for a tensile test
+
+266
+00:22:38,010 --> 00:22:44,910
+specimen هتكون واحد زاد ال U في Sy تربية على تلاتة
+
+267
+00:22:44,910 --> 00:22:50,850
+ايه ال distortion اللي بيحكي بيصير failure او
+
+268
+00:22:50,850 --> 00:22:53,270
+بيصير yielding لما
+
+269
+00:22:55,850 --> 00:22:58,670
+لما ال U distortion لل mechanical element تحت
+
+270
+00:22:58,670 --> 00:23:03,830
+الدراسة يكون أكبر أو يساوي ال U distortion for a
+
+271
+00:23:03,830 --> 00:23:09,890
+tensile test specimen يعني هتكون U distortion اللي
+
+272
+00:23:09,890 --> 00:23:14,230
+هي ..
+
+273
+00:23:14,230 --> 00:23:19,870
+اللي هي .. اللي هي هذه المعادلة اللي هي واحد زائد
+
+274
+00:23:19,870 --> 00:23:27,040
+U ع تلاتة E فيسيجما واحد minus سيجما اتنين لكل
+
+275
+00:23:27,040 --> 00:23:33,560
+تربيع زي سيجما اتنين minus سيجما تلاتة لكل تربيع
+
+276
+00:23:33,560 --> 00:23:39,700
+زي سيجما تلاتة minus سيجما واحد لكل تربيع على
+
+277
+00:23:39,700 --> 00:23:54,870
+اتنين تكون اكبر او يساوي واحد زي نيوفي SY تربية ع
+
+278
+00:23:54,870 --> 00:24:03,770
+تلاتة اي يعني
+
+279
+00:24:03,770 --> 00:24:08,230
+هيروح عندهين واحد زائد نيو واحد زائد نيو و تلاتة
+
+280
+00:24:08,230 --> 00:24:15,690
+اي مع تلاتة اي يعني بيصير failureلما سجم واحد
+
+281
+00:24:15,690 --> 00:24:22,630
+minus سجم اتنين الكل تربية زي سجم اتنين minus سجم
+
+282
+00:24:22,630 --> 00:24:26,890
+اتلات الكل تربية زي سجم اتلات minus سجم واحد الكل
+
+283
+00:24:26,890 --> 00:24:31,890
+تربية على اتنين
+
+284
+00:24:31,890 --> 00:24:42,070
+طبعا هذا كل اص نص الكل اص نص يكون اكبر او يساوي as
+
+285
+00:24:42,070 --> 00:24:47,710
+yمعناته ال distortion theory predicts failure لما
+
+286
+00:24:47,710 --> 00:24:51,150
+distortion energy per unit volume of the
+
+287
+00:24:51,150 --> 00:24:55,230
+mechanical element under study exceeds the
+
+288
+00:24:55,230 --> 00:24:59,170
+distortion energy
+
+289
+00:24:59,170 --> 00:25:03,070
+of a tensile test specimen اللي هي هذه المعادلة
+
+290
+00:25:03,070 --> 00:25:05,930
+sigma 1 معناه sigma 2 الكل تربيع زي sigma 2 معناه
+
+291
+00:25:05,930 --> 00:25:09,070
+sigma 3 الكل تربيع زي sigma 3 معناه sigma 1 الكل
+
+292
+00:25:09,070 --> 00:25:11,930
+تربيع على 2 نقص نص أكبر يستوي S Y
+
+293
+00:25:15,860 --> 00:25:21,920
+الان ممكن اعرف ال term هذا واحد اسمه Von Mises سمى
+
+294
+00:25:21,920 --> 00:25:26,720
+كل term هذا سمى sigma prime او von Mises stress
+
+295
+00:25:26,720 --> 00:25:34,560
+هذا ال term هذا كله sigma prime يعني ممكن احكي ال
+
+296
+00:25:34,560 --> 00:25:38,260
+distortion energy theory صياغة تانية لما ال von
+
+297
+00:25:38,260 --> 00:25:41,240
+Mises stress اللي هو sigma prime exceeds ال yield
+
+298
+00:25:41,240 --> 00:25:47,060
+strength yielding beginsيعني yielding لما ال sigma
+
+299
+00:25:47,060 --> 00:25:51,560
+prime أكبر أو يساوي as y اللي هو ال sigma prime
+
+300
+00:25:51,560 --> 00:25:54,260
+اللي هي ال von meissens stress اللي هو معطوب
+
+301
+00:25:54,260 --> 00:25:55,960
+العلاقة هذه ال von meissens stress اللي هو sigma
+
+302
+00:25:55,960 --> 00:25:58,380
+واحد معناه sigma اتنين لكل تربيع زي sigma اتنين
+
+303
+00:25:58,380 --> 00:26:01,420
+معناه sigma تلاته لكل تربيع زي sigma تلاته معناه
+
+304
+00:26:01,420 --> 00:26:03,900
+sigma واحد لكل تربيع على اتنين اقصد نص هذا هو
+
+305
+00:26:03,900 --> 00:26:09,040
+sigma prime او ال von meissens stress for a plain
+
+306
+00:26:09,040 --> 00:26:12,780
+state of stress هيكون واحد من stress بيساوي صفر
+
+307
+00:26:12,780 --> 00:26:18,030
+يعني لو هذا هذا هيكون صفرهذا سفر بتصف ال volume
+
+308
+00:26:18,030 --> 00:26:21,170
+minus stress sigma prime بسهولة sigma a تربية بقى
+
+309
+00:26:21,170 --> 00:26:24,350
+انا sigma a sigma b زي انا sigma b تربية الكل مصد
+
+310
+00:26:24,350 --> 00:26:30,550
+نصإذا انت ممكن تحصل stress مباشرة بدون ما تحصل ال
+
+311
+00:26:30,550 --> 00:26:34,250
+principle stress بس انا بفضل احسب ال principle
+
+312
+00:26:34,250 --> 00:26:38,510
+stress بعدين احصل stress من المعادلة هذه باستخدام
+
+313
+00:26:38,510 --> 00:26:43,150
+ال principle stress لكن ممكن إذا انت تاخد ال
+
+314
+00:26:43,150 --> 00:26:46,710
+stress element الأصلي اللي بيكون فيه sigma x sigma
+
+315
+00:26:46,710 --> 00:26:52,170
+y sigma z tau xy tau xz tau yz و أحسب stress من
+
+316
+00:26:52,170 --> 00:26:58,220
+هذه المعادلةرياضية المعادلة هذه نفس المعادلة هذه
+
+317
+00:26:58,220 --> 00:26:59,160
+تماما
+
+318
+00:27:07,910 --> 00:27:12,150
+Volmeis stress is a single effective stress for
+
+319
+00:27:12,150 --> 00:27:14,570
+the entire general state of stress in a stress
+
+320
+00:27:14,570 --> 00:27:20,470
+.معناة volmeis stress هو مثلة stress كيما واحدة
+
+321
+00:27:20,470 --> 00:27:25,870
+بتمثل المجموع العام لل state of stress for a
+
+322
+00:27:25,870 --> 00:27:27,390
+mechanical element under stress
+
+323
+00:27:30,420 --> 00:27:34,840
+أحنا في ال distortion energy theory ببساطة بتقارن
+
+324
+00:27:34,840 --> 00:27:36,420
+ال volume minus ال stress مع ال yielding strength
+
+325
+00:27:36,420 --> 00:27:39,040
+إذا كان ال volume minus ال stress أكبر بيستوى ال
+
+326
+00:27:39,040 --> 00:27:44,620
+SY ال yielding begins if I incorporate a factor of
+
+327
+00:27:44,620 --> 00:27:52,960
+safety بيستوى sigma prime بيستوى SY على N طبعا
+
+328
+00:27:52,960 --> 00:27:56,780
+لو أخدت 2D state of stress هيكون دي sigma prime
+
+329
+00:28:01,240 --> 00:28:10,140
+for a 2D state of stress ناخدها كحالة دراسية سيكون
+
+330
+00:28:10,140 --> 00:28:16,720
+لدي ال sigma prime بالساوية sigma a تربيع زائد
+
+331
+00:28:16,720 --> 00:28:22,520
+sigma a sigma b زائد sigma b تربيع اصل نص اللي هي
+
+332
+00:28:22,520 --> 00:28:30,020
+المعادلة هذه او هي minus هنا هذه minus
+
+333
+00:28:38,570 --> 00:28:46,230
+هذه المعادلة إذا ترجع لرياضيات لل calculus هذه
+
+334
+00:28:46,230 --> 00:28:53,190
+معادلة ellipse مائل بزاوية 45 يعني عندك هاي ال X و
+
+335
+00:28:53,190 --> 00:29:01,670
+هاي ال Y هذا بزاوية 45 درجة هذا هو ال ellipse
+
+336
+00:29:05,090 --> 00:29:12,050
+هذه معادلة اللبس مائل بزاوية 45 درجة الان
+
+337
+00:29:12,050 --> 00:29:21,350
+لدي هنا sigma 1 على SY هنا sigma 2 على SY وهذا ال
+
+338
+00:29:21,350 --> 00:29:27,340
+failure contourوهذه الـ Experimental Data لحظة الـ
+
+339
+00:29:27,340 --> 00:29:34,600
+Distortion Energy Theory تتوقع
+
+340
+00:29:34,600 --> 00:29:40,610
+الحقيقةلكن ال maximum shear stress theory it
+
+341
+00:29:40,610 --> 00:29:45,230
+predicts failure before failure actually happens
+
+342
+00:29:45,230 --> 00:29:49,430
+بتتوقع الفيلير و لسه ماصارش failure اللي هي ال
+
+343
+00:29:49,430 --> 00:29:52,010
+maximum shear stress theory لكن ال distortion
+
+344
+00:29:52,010 --> 00:29:57,030
+energy theory predicts failure accurately يعني فيه
+
+345
+00:29:57,030 --> 00:30:01,170
+دقة معناتهالدقة في حالة distortion energy theory
+
+346
+00:30:01,170 --> 00:30:06,990
+أعلى لكنها less conservative يعني أنصر المخاطرة في
+
+347
+00:30:06,990 --> 00:30:11,830
+الحسابات عليك كمصمم بيكون ايش؟ أعلى في حالة
+
+348
+00:30:11,830 --> 00:30:15,390
+distortion energy theory لكنه بده انا عشان اوفر
+
+349
+00:30:15,390 --> 00:30:19,610
+materialفي حالة ال mass production بفضل استخدام
+
+350
+00:30:19,610 --> 00:30:22,650
+distortion energy theory او Von Mises معظم ال
+
+351
+00:30:22,650 --> 00:30:26,710
+software زي ال .. ال ansys abacus ال .. ال حتة ال
+
+352
+00:30:26,710 --> 00:30:30,430
+solid work لما تعمل finite element analysis و تعمل
+
+353
+00:30:30,430 --> 00:30:34,190
+stress contour بيحسب ال Von Mises stress طبعا انت
+
+354
+00:30:34,190 --> 00:30:36,390
+مخير تحكيله انا بدي استخدم ال maximum shear stress
+
+355
+00:30:36,390 --> 00:30:40,230
+theory بس ال default عنده بيستخدم ال distortion
+
+356
+00:30:40,230 --> 00:30:41,550
+energy theory
+
+357
+00:30:59,510 --> 00:31:06,450
+طيب لان هنشوف ال shear strength predictions كيف
+
+358
+00:31:06,450 --> 00:31:11,050
+نتوقع ال shear strength ل material طبقا ل maximum
+
+359
+00:31:11,050 --> 00:31:14,290
+shear strength theory و طبقا ل distortion energy
+
+360
+00:31:14,290 --> 00:31:18,990
+theory اذا خدت انا mechanical element و عملت عليه
+
+361
+00:31:19,860 --> 00:31:24,280
+Torsion دلت ازود تورك تورك لحد ما صار failure او
+
+362
+00:31:24,280 --> 00:31:30,880
+صار yielding الان ال stress element فى 2D هكون 2D
+
+363
+00:31:30,880 --> 00:31:37,100
+stress element هكون عندى
+
+364
+00:31:37,100 --> 00:31:45,780
+tau هكون more circle بالشكل هذا more circle هذا ال
+
+365
+00:31:45,780 --> 00:31:56,490
+sigma واحدهذه سيجما اتنين وهذه تاو ماكس
+
+366
+00:31:56,490 --> 00:32:03,630
+تاو ماكس ستكون تساوي سيجما واحد بالساوي سالب سيجما
+
+367
+00:32:03,630 --> 00:32:09,390
+اتنين يعني سيجما واحد موجب وسيجما اتنين سالبة
+
+368
+00:32:09,390 --> 00:32:13,850
+معناته
+
+369
+00:32:13,850 --> 00:32:15,610
+انا عندي هنا سيجما A
+
+370
+00:32:18,580 --> 00:32:25,200
+وهنا عنده sigma b في
+
+371
+00:32:25,200 --> 00:32:30,540
+حالة ال maximum shear stress theory هاي
+
+372
+00:32:30,540 --> 00:32:40,180
+ال maximum shear stress theory و
+
+373
+00:32:40,180 --> 00:32:47,260
+أخدتmechanical element that is under pure torsion
+
+374
+00:32:47,260 --> 00:32:54,940
+لحد الفيلير ال load line هيكون بشكل هذا هذا ال
+
+375
+00:32:54,940 --> 00:33:06,400
+load line at
+
+376
+00:33:06,400 --> 00:33:06,880
+failure
+
+377
+00:33:11,480 --> 00:33:19,460
+هذه النقطة هذه نقطة ال failure هذه failure point
+
+378
+00:33:19,460 --> 00:33:28,120
+احنا واضح انه يعني انا هنا عندي sigma a او sigma b
+
+379
+00:33:28,120 --> 00:33:35,060
+انا واضح في الرابع الرابع عندي يعني sigma a
+
+380
+00:33:38,840 --> 00:33:45,240
+أكبر أو يساوي sigma b لأن sigma a أكبر أو يساوي
+
+381
+00:33:45,240 --> 00:33:51,000
+صفر و الصفر أكبر أو يساوي sigma b معناته هذه تمثل
+
+382
+00:33:51,000 --> 00:33:57,120
+sigma واحد هذه sigma اتنين وهذه sigma تلاتة معناته
+
+383
+00:33:57,120 --> 00:34:05,960
+تاوم ماكسيم ماكسيمان أكبر ساوية sigma واحد minus
+
+384
+00:34:05,960 --> 00:34:18,350
+sigma تلاتة علىعلى اتنين هيساوي
+
+385
+00:34:18,350 --> 00:34:23,890
+سيجمه واحد minus سيجمه تانى بيساوي minus سيجمه
+
+386
+00:34:23,890 --> 00:34:34,530
+واحد على اتنين يعني بيساوي سيجمه واحد to max ال
+
+387
+00:34:34,530 --> 00:34:40,390
+yielding ال yieldingأنا عندى هنا سيكون عندى sigma
+
+388
+00:34:40,390 --> 00:34:52,710
+a sigma a minus sigma b أكبر أو يساوي ايش S Y هنا
+
+389
+00:34:52,710 --> 00:35:00,910
+عند ال yielding هل بسميها S
+
+390
+00:35:00,910 --> 00:35:09,410
+S Y اللي هي yielding strength and shearوهذه as y
+
+391
+00:35:09,410 --> 00:35:17,950
+وهنا حكينا هذه sigma a وهذه minus sigma a من تشابه
+
+392
+00:35:17,950 --> 00:35:24,410
+المثلثات او معادلة الخط هذا المستقيم معادلة الخط
+
+393
+00:35:24,410 --> 00:35:29,550
+المستقيم هذا عبارة عن sigma b هذا الخط ال load
+
+394
+00:35:29,550 --> 00:35:34,150
+line equation
+
+395
+00:35:36,020 --> 00:35:43,520
+اللي هتكون عند سيجما بي بصوا minus sigma a هذه
+
+396
+00:35:43,520 --> 00:35:50,720
+معادلة معادلة الخط التاني في تلت نقاط SY و صفر
+
+397
+00:35:50,720 --> 00:35:55,220
+وعند
+
+398
+00:35:55,220 --> 00:36:03,020
+صفر و minus SY عند نقطة هنا اللي
+
+399
+00:36:03,020 --> 00:36:03,320
+هي
+
+400
+00:36:07,020 --> 00:36:16,220
+بدي أسميها SSY SSY
+
+401
+00:36:16,220 --> 00:36:25,520
+و SSY ال slope بتاع الخط هذا هيكون عنده
+
+402
+00:36:25,520 --> 00:36:31,860
+ال load on sigma A بيستوى minus sigma B النقطة
+
+403
+00:36:31,860 --> 00:36:41,080
+هادةat point a بيكون
+
+404
+00:36:41,080 --> 00:36:51,020
+عندى sigma b minus sigma a بيكون as as y اللي عملت
+
+405
+00:36:51,020 --> 00:36:56,380
+شغل مثلثات بتطلع as as y بتطلع
+
+406
+00:36:56,380 --> 00:37:01,920
+سوى نص as y معناته ال maximum shear stress theory
+
+407
+00:37:01,920 --> 00:37:07,830
+predictsال yield strength in shear according to
+
+408
+00:37:07,830 --> 00:37:10,230
+this equation as as why بتستوى نص ال yield
+
+409
+00:37:10,230 --> 00:37:13,730
+strength معناته ال yield strength in shear
+
+410
+00:37:13,730 --> 00:37:18,970
+according to maximum shear stress theory بتستوى نص
+
+411
+00:37:18,970 --> 00:37:25,010
+as why معناته انا ممكن اعبر عن ال failure ال
+
+412
+00:37:25,010 --> 00:37:28,270
+failure according to maximum shear stress I بحكي
+
+413
+00:37:28,270 --> 00:37:31,390
+انه failure according according
+
+414
+00:37:34,230 --> 00:37:41,910
+to maximum shear stress theory failure occurs
+
+415
+00:37:41,910 --> 00:37:52,630
+when tau maximum أكبر أو يساوي SSY هذا according
+
+416
+00:37:52,630 --> 00:37:57,650
+to maximum shear stress theory اللي هو SSY بيساوي
+
+417
+00:37:57,650 --> 00:38:04,480
+نص SSY هذا في حالةالـ maximum shear stress theory
+
+418
+00:38:04,480 --> 00:38:10,040
+بنفس الأسلوب في حالة ال distortion energy theory
+
+419
+00:38:10,040 --> 00:38:18,500
+هذا هو ال load line هذا ال load line for a pure
+
+420
+00:38:18,500 --> 00:38:24,460
+shear load line عندي هنا S Y وهنا عندي Sigma B
+
+421
+00:38:24,460 --> 00:38:30,310
+وهنا S Yلأن according to distortion اللي بيصير
+
+422
+00:38:30,310 --> 00:38:38,090
+failure لما هذا ال stress condition هذه النقطة او
+
+423
+00:38:38,090 --> 00:38:41,110
+ال loading ال load condition هي هذه هذه sigma a
+
+424
+00:38:41,110 --> 00:38:50,470
+sigma a وهذه minus sigma a الآن هذه النقطة وقعت
+
+425
+00:38:50,470 --> 00:38:55,630
+تتقاطع خط مستقيم ميل بزاوية سالب خمسة واربعين
+
+426
+00:38:55,630 --> 00:38:59,690
+وتقاطع اللبسيعني لو سوين ال equation بتاعة ال
+
+427
+00:38:59,690 --> 00:39:02,150
+ellipse with equation of load line at this point
+
+428
+00:39:02,150 --> 00:39:08,610
+بيطلع عند ال S S Y بيطلع بوند خمسة سبعة سبعة S Y
+
+429
+00:39:08,610 --> 00:39:14,790
+بوند خمسة سبعة سبعة S Y هذا في حال distortion
+
+430
+00:39:14,790 --> 00:39:19,170
+theory بقى أنا ممكن أعبر عن distortion theory
+
+431
+00:39:19,170 --> 00:39:24,130
+بطريقة تانية أحكي والله according to according to
+
+432
+00:39:29,050 --> 00:39:34,610
+distortion energy theory failure occurs
+
+433
+00:39:34,610 --> 00:39:46,860
+when tau maximum أكبر أو يساوي SSY يعنيأنا وحدت
+
+434
+00:39:46,860 --> 00:39:51,440
+نفس المفهوم في حالة two theories .. في حالة two
+
+435
+00:39:51,440 --> 00:39:57,800
+theories بس بختلف تعريف ال S S Y في حالة maximum
+
+436
+00:39:57,800 --> 00:40:02,620
+share of the state بيسوا point five S .. بيسوا
+
+437
+00:40:02,620 --> 00:40:06,570
+point five S Yفي حال تدل ال sociology theory بتكون
+
+438
+00:40:06,570 --> 00:40:11,570
+الtaa ال sxy بيساوون خمسة سبعة سبعة s y يعني اذا
+
+439
+00:40:11,570 --> 00:40:14,890
+كانت الtaa maximum بيساوي اكبر او بيساوي s y
+
+440
+00:40:14,890 --> 00:40:18,150
+والtaa maximum انا من ال more circle بحسب ال sigma
+
+441
+00:40:18,150 --> 00:40:20,770
+واحد و sigma اتنين و sigma تلاتة و برتبهم بحيث
+
+442
+00:40:20,770 --> 00:40:24,290
+sigma واحد اكبر من sigma اتنين اكبر من sigma تلاتة
+
+443
+00:40:24,290 --> 00:40:26,930
+و بعدين احكي الtaa maximum بالساوية
+
+444
+00:40:30,470 --> 00:40:37,590
+بستوى سيجما واحد minus سيجما تلاتة على اتنين ممكن
+
+445
+00:40:37,590 --> 00:40:40,150
+اعبر
+
+446
+00:40:42,400 --> 00:40:45,720
+عن ال failure طبقا لل maximum shear stress theory
+
+447
+00:40:45,720 --> 00:40:49,640
+او طبقا لل distortion theory بنفس الشكل بس باختلاف
+
+448
+00:40:49,640 --> 00:40:53,700
+التفاصيل يعني احكي انه failure according to
+
+449
+00:40:53,700 --> 00:40:57,680
+maximum shear stress theory happens لما tau
+
+450
+00:40:57,680 --> 00:41:01,680
+maximum تكون اكبر او يساوي as y as as y اللي هي
+
+451
+00:41:01,680 --> 00:41:04,960
+yield strength in shear وبرضه ممكن اعبر عن ال
+
+452
+00:41:04,960 --> 00:41:08,450
+failure according toالـ distortion energy theory
+
+453
+00:41:08,450 --> 00:41:11,750
+بحكي اللي هو بيصير failure لما ال tau maximum تكون
+
+454
+00:41:11,750 --> 00:41:15,570
+برضه أكبر أو يساوي SSY اللي بيختلف ال definition
+
+455
+00:41:15,570 --> 00:41:19,690
+تاع SSY ال SSY في حالة ال maximum shear stress
+
+456
+00:41:19,690 --> 00:41:24,170
+theory بيساوي bond 5SY في حالة ال distortion
+
+457
+00:41:24,170 --> 00:41:29,270
+energy theory بيساوي bond 577SY
+
+458
+00:41:31,410 --> 00:41:36,090
+هذا مهم كتير لأنه بسهل حل و فهم المسائل بشكل أعمق
+
+459
+00:41:36,090 --> 00:41:40,950
+نشوف مثال
+
+460
+00:41:40,950 --> 00:41:52,230
+هذا
+
+461
+00:41:52,230 --> 00:41:58,350
+المثال هكون مثال حسابينعتبره تدريب على استخدام او
+
+462
+00:41:58,350 --> 00:42:05,990
+يعني زي calculation exercise a hot rolled steel
+
+463
+00:42:05,990 --> 00:42:10,490
+has a yield strength of S Y T بساوي S Y C بساوي
+
+464
+00:42:10,490 --> 00:42:14,070
+one hundred kilo pound per square inch يعني hot
+
+465
+00:42:14,070 --> 00:42:18,330
+rolled steel yield strength S Y T yield strength
+
+466
+00:42:18,330 --> 00:42:21,330
+in tension بساوي yield strength in compression
+
+467
+00:42:21,330 --> 00:42:26,000
+بساوي مية kilo poundper square inch و هسميه as
+
+468
+00:42:26,000 --> 00:42:31,920
+well لأنهم متساويين and a true strain at a
+
+469
+00:42:31,920 --> 00:42:36,500
+fracture epsilon f بالساعة
+
+470
+00:42:36,500 --> 00:42:43,120
+point خمسة خمسة هذا أكبر من ايش point
+
+471
+00:42:43,120 --> 00:42:50,440
+او خمسة معناته المادة الشمالها duck tile duck tile
+
+472
+00:42:50,440 --> 00:42:55,550
+materialestimate the factor of safety for the
+
+473
+00:42:55,550 --> 00:42:59,010
+following principal stress states احسب ال factor
+
+474
+00:42:59,010 --> 00:43:05,030
+of safety للحالات التالية a sigma
+
+475
+00:43:05,030 --> 00:43:11,910
+x بالساوية سبعين kilo pound per square inch و
+
+476
+00:43:11,910 --> 00:43:22,090
+sigma y بالساوية سبعين kilo pound per square inchو
+
+477
+00:43:22,090 --> 00:43:27,430
+τاو اكس واي بالثاوزيرو اوتوماتيك لما نطلع حالة
+
+478
+00:43:27,430 --> 00:43:34,990
+الشير stress بالثاوز سفر معناته هدول بيمثل ايش؟
+
+479
+00:43:34,990 --> 00:43:38,490
+principal stresses عند ال principal planes بيكونش
+
+480
+00:43:38,490 --> 00:43:42,150
+فيه شير ففي الشي ده يعمل calculation على طول سيجما
+
+481
+00:43:42,150 --> 00:43:46,930
+واحد في الحالة دي سيجما واحد because لأنه
+
+482
+00:43:49,530 --> 00:43:56,410
+tau xy بالساوية 0 ما أن sigma x and sigma y are
+
+483
+00:43:56,410 --> 00:44:00,910
+principal stresses
+
+484
+00:44:00,910 --> 00:44:08,330
+معناته sigma 1 بالساوية 70 kilo pound per square
+
+485
+00:44:08,330 --> 00:44:12,850
+inch و sigma 2 بالساوية برضه 70 kilo pound per
+
+486
+00:44:12,850 --> 00:44:20,090
+square inch و sigma 3 بالساوية حالها دياشر سفرلأن
+
+487
+00:44:20,090 --> 00:44:24,590
+في عندى حلتين بتستخدم مرة ال maximum shear stress
+
+488
+00:44:24,590 --> 00:44:28,670
+theory ومرة اللى هى distortion energy theory
+
+489
+00:44:28,670 --> 00:44:33,970
+according
+
+490
+00:44:33,970 --> 00:44:37,850
+to maximum shear stress theory بتحكى بيصير failure
+
+491
+00:44:37,850 --> 00:44:39,010
+لما ال tau maximum
+
+492
+00:44:45,170 --> 00:44:54,010
+أكبر هو يساوي SSY أو بيساوي SSY على N يعني
+
+493
+00:44:54,010 --> 00:45:03,210
+N هتساوي SSY على TAU maximum و ال SSY في حالة
+
+494
+00:45:03,210 --> 00:45:08,970
+maximum shear stress theory بيساوي نص ال SY اللي
+
+495
+00:45:08,970 --> 00:45:15,560
+هي نص في أكام فمية نصفي مية بيطلع خمسين kilo pound
+
+496
+00:45:15,560 --> 00:45:20,140
+per square inch طيب
+
+497
+00:45:20,140 --> 00:45:28,140
+ال tau maximum بيساوي sigma واحد minus sigma تلاتة
+
+498
+00:45:28,140 --> 00:45:35,120
+على اتنين يعني هتكون سبعين ناقص سفر على اتنين خمسة
+
+499
+00:45:35,120 --> 00:45:39,420
+و تلاتين kilo pound per square inch معناه تلان
+
+500
+00:45:40,920 --> 00:45:48,920
+هتكون تساوي الـ SSY اللي هي .. اللي هي خمسين على
+
+501
+00:45:48,920 --> 00:45:55,620
+خمسة و تلاتين خمسين
+
+502
+00:45:55,620 --> 00:45:59,820
+تقسيم خمسة و تلاتين بتطلع one point four three one
+
+503
+00:45:59,820 --> 00:46:04,940
+point four three هذا في حالة ال distortion theory
+
+504
+00:46:06,790 --> 00:46:09,450
+في حالة .. في حالة ال maximum series .. في حالة
+
+505
+00:46:09,450 --> 00:46:14,730
+distortion energy theory بيصير failure لما tau
+
+506
+00:46:14,730 --> 00:46:18,530
+maximum تكون
+
+507
+00:46:18,530 --> 00:46:23,570
+أكبر بيستوي SSY أو tau maximum بيستوي SSY على N
+
+508
+00:46:23,570 --> 00:46:35,150
+يعني N بتساوي SSY على tau maximum طيب ال SSY ايش
+
+509
+00:46:35,150 --> 00:46:40,250
+بتساوي؟في حالتي distortion energy بتسوي point خمسة
+
+510
+00:46:40,250 --> 00:46:51,590
+سبعة سبعة أسواي يعني هتسوي point خمسة سبعة سبعة في
+
+511
+00:46:51,590 --> 00:46:57,730
+أسواي اللي هي مية يعني هتسوي سبعة خمسين point سبعة
+
+512
+00:46:57,730 --> 00:47:01,570
+كيلو pound per square inch هذا according to
+
+513
+00:47:01,570 --> 00:47:05,010
+distortion energy theory
+
+514
+00:47:10,930 --> 00:47:14,910
+طيب و ال tau maximum already حسبناها ال tau
+
+515
+00:47:14,910 --> 00:47:19,870
+maximum بتساوي
+
+516
+00:47:19,870 --> 00:47:27,610
+عليها خمسة و تلاتين يعني هين هتكون اللي هي سبعة و
+
+517
+00:47:27,610 --> 00:47:37,270
+خمسين point سبعة على tau maximum اللي هي خمسة و
+
+518
+00:47:37,270 --> 00:47:43,020
+تلاتينيعني بيطلع ال factor of safety اللي هو سبعة
+
+519
+00:47:43,020 --> 00:47:48,540
+خمسين point سبعة تقسيم خمسة و تلاتين بيطلع واحد
+
+520
+00:47:48,540 --> 00:47:54,320
+point ستة خمسة لاحظوا
+
+521
+00:47:54,320 --> 00:47:58,240
+ال margin of safety في حد distortion energy theory
+
+522
+00:47:58,240 --> 00:48:01,520
+أعلى من ال maximum shear stress theory لأن احنا
+
+523
+00:48:01,520 --> 00:48:05,780
+بداية حكينا ان maximum shear stress theory gives
+
+524
+00:48:07,020 --> 00:48:10,440
+اللي هو more conservative results يعني وعنصر
+
+525
+00:48:10,440 --> 00:48:14,820
+المخاطر أقل بيحكيلك انه .. انه انا بحكيلك انه فيه
+
+526
+00:48:14,820 --> 00:48:19,160
+failure و لسه ماصارش failure هذه طلع ال factor of
+
+527
+00:48:19,160 --> 00:48:25,930
+safety أعلى لأنهit fits the experimental data أكتر
+
+528
+00:48:25,930 --> 00:48:30,730
+من ال maximum shear risk theory الآن طريقة حصة ال
+
+529
+00:48:30,730 --> 00:48:33,210
+factors safety باستخدام نفس المعادلة Tau maximum
+
+530
+00:48:33,210 --> 00:48:37,450
+سواء S أسواء على N وهن ال Tau maximum سواء S أسواء
+
+531
+00:48:37,450 --> 00:48:39,790
+على N نفس استخدامك بس اللي اختلف ال definition
+
+532
+00:48:39,790 --> 00:48:42,730
+بتاع S أسواء لكن لو أنا بدي أحسب ال volume of mice
+
+533
+00:48:42,730 --> 00:48:47,530
+stressلو دي حسب يعني هلاحظ .. هنصل لنفس .. نفس ..
+
+534
+00:48:47,530 --> 00:48:54,010
+نفس النتيجة sigma prime هتكون sigma a تربية minus
+
+535
+00:48:54,010 --> 00:49:00,010
+sigma a sigma b زائد sigma b تربية أس نص يعني
+
+536
+00:49:00,010 --> 00:49:03,810
+هتكون تستوى هذا .. هذا حل تاني sigma a اللي عندي
+
+537
+00:49:03,810 --> 00:49:09,410
+أكم اللي
+
+538
+00:49:09,410 --> 00:49:16,960
+هي سبعينتربيع ماينس سبعين في سبعين زائد سبعين
+
+539
+00:49:16,960 --> 00:49:22,440
+تربيع تطلعش سبعين كيلو pound per square inch هذا
+
+540
+00:49:22,440 --> 00:49:26,800
+sigma prime و
+
+541
+00:49:26,800 --> 00:49:28,820
+according to the stationary theory بيصير failure
+
+542
+00:49:28,820 --> 00:49:34,040
+لما sigma prime أكبر ويستوي as y يعني sigma prime
+
+543
+00:49:36,210 --> 00:49:44,710
+بالساوية as y على n يعني n بساوية as y على ال
+
+544
+00:49:44,710 --> 00:49:59,050
+sigma prime as y ال hand هي مية على سبعين مية
+
+545
+00:49:59,050 --> 00:50:04,570
+على سبعين سبعين تربيع سبعين سبعين اقصد نص
+
+546
+00:50:09,490 --> 00:50:18,290
+هيش غلط عندنا هنا sigma x نرجع
+
+547
+00:50:18,290 --> 00:50:32,210
+لمعادلة نظبط sigma prime بيستوى Sy على N اه
+
+548
+00:50:34,580 --> 00:50:37,920
+ف ال sigma prime بيستوى SY على N و ال N بيستوى SY
+
+549
+00:50:37,920 --> 00:50:44,440
+على sigma prime و منها بحسب اللي هو SY عند 100 و
+
+550
+00:50:44,440 --> 00:50:48,700
+ال sigma prime تطلع 70 100 على 70 المفروض تطلع
+
+551
+00:50:48,700 --> 00:51:00,380
+حسبوليها 100 قصيم 70 تطلع 1.43 طيب خنشوف مثال تاني
+
+552
+00:51:00,380 --> 00:51:03,120
+انحله
+
+553
+00:51:05,500 --> 00:51:10,580
+باستخدام اللي هي sigma prime مرة و مرة حلو
+
+554
+00:51:10,580 --> 00:51:22,700
+باستخدام اللي هي ال SSY لحظة
+
+555
+00:51:22,700 --> 00:51:29,640
+خليني ارجع لنفس السؤال نفس السؤال اوضح اذا كنت في
+
+556
+00:51:29,640 --> 00:51:33,580
+الربع التالت اذا كنت في الربع الرابع
+
+557
+00:51:36,730 --> 00:51:47,770
+if state of stress is in the fourth quadrant هذا
+
+558
+00:51:47,770 --> 00:51:52,610
+تصحيح لأن صار عندي خربش انا fourth quadrant معناته
+
+559
+00:51:52,610 --> 00:51:58,950
+sigma a أكبر أو يساوي الصفر أكبر أو يساوي ال sigma
+
+560
+00:51:58,950 --> 00:52:03,950
+b يعني واحد موجة و واحد سالب في الحالة هذه in this
+
+561
+00:52:03,950 --> 00:52:13,420
+caseبحكي أن الـ N بستواء SSY على TAU maximum هذا
+
+562
+00:52:13,420 --> 00:52:18,980
+في حالةالـ distortion energy theory وفي حالة ال
+
+563
+00:52:18,980 --> 00:52:22,600
+maximum shear stress theory لكن في حالة ال
+
+564
+00:52:22,600 --> 00:52:26,000
+distortion energy theory بتكون عند ال S S Y
+
+565
+00:52:26,000 --> 00:52:32,640
+بيسوابون خمسة سبعة سبعة S Y و ال S S Y في حالة ال
+
+566
+00:52:32,640 --> 00:52:36,440
+maximum shear stress theory بتكون سوابون مصر S Y
+
+567
+00:52:38,150 --> 00:52:43,250
+معناته الحل السابق ينطبق في ال fourth quadrant لكن
+
+568
+00:52:43,250 --> 00:52:48,010
+انا وين طلعت عندي sigma a موجبة و sigma b موجبة
+
+569
+00:52:48,010 --> 00:52:52,850
+انا في ال first quadrant معناته this is not valid
+
+570
+00:52:52,850 --> 00:53:01,070
+يعني if state of stress is
+
+571
+00:53:01,070 --> 00:53:06,330
+in the first quadrant
+
+572
+00:53:09,930 --> 00:53:15,770
+معناته بدنا نحكي في الحالة هاذي نحكي نحكي انه ال
+
+573
+00:53:15,770 --> 00:53:21,590
+sigma ال prime بيسوى S Y على N في حالة ال
+
+574
+00:53:21,590 --> 00:53:27,490
+distortion energy theory وفي
+
+575
+00:53:27,490 --> 00:53:30,250
+حالة ال maximum shear stress theory هنحكي انه ..
+
+576
+00:53:30,250 --> 00:53:42,790
+انه .. انه sigma A بيسوى S Yعلى n في حالة ال
+
+577
+00:53:42,790 --> 00:53:47,710
+maximum shear stress theory احنا في المسألة
+
+578
+00:53:47,710 --> 00:53:52,290
+السابقة احنا كنا في ال first quadrant معناته
+
+579
+00:53:52,290 --> 00:53:58,670
+مانفعش .. مانفعش استخدم المعادلة هذه في ال first
+
+580
+00:53:58,670 --> 00:54:06,090
+.. في ال first quadrant طيب نشوف مسألة تانية أو
+
+581
+00:54:06,090 --> 00:54:09,310
+فرعة تانية هذا للتوضيح
+
+582
+00:54:16,250 --> 00:54:20,290
+نشوف حالة تانية بي عندي سيجما X بالساوية ستين
+
+583
+00:54:20,290 --> 00:54:26,050
+سيجما X بالساوية ستين kilo pound per square inch
+
+584
+00:54:26,050 --> 00:54:34,610
+وسيجما Y بالساوية اربعين kilo pound per square
+
+585
+00:54:34,610 --> 00:54:41,270
+inch وTau XY بالساوية ماينس خمستاشر kilo pound per
+
+586
+00:54:41,270 --> 00:54:45,950
+square inchأول الشيء مغادر نظرتي لازم اوجد ال
+
+587
+00:54:45,950 --> 00:54:51,110
+principal stresses find principal
+
+588
+00:54:51,110 --> 00:54:54,610
+stresses
+
+589
+00:54:54,610 --> 00:54:59,990
+يعني عندك توجد سجم واحد و سجم اتنين و سجم تلاتة
+
+590
+00:54:59,990 --> 00:55:06,070
+هنا طبعا هستخدم more circle more circle
+
+591
+00:55:13,760 --> 00:55:21,220
+أنا هستخدم عندي هنا هنا counter clockwise موجة
+
+592
+00:55:21,220 --> 00:55:26,860
+وهنا clockwise سالف معناته هتكون عندي هنا سيج ماكس
+
+593
+00:55:26,860 --> 00:55:30,620
+اللي هي ستين ستين وخمستاشر clockwise هتكون ستين
+
+594
+00:55:30,620 --> 00:55:37,440
+انا عندي عشرة عشرين تلاتين اربعين خمسين ستين هنا
+
+595
+00:55:37,440 --> 00:55:39,540
+عشرة عشرين
+
+596
+00:55:42,290 --> 00:55:50,950
+هذه عشرة عشرين تلاتين أربعين خمسين ستين هذا
+
+597
+00:55:50,950 --> 00:55:57,850
+أول نقطة اللي هي sigma X اللي هي ستين وخمستاش
+
+598
+00:55:57,850 --> 00:56:03,730
+clockwise سالب النقطة التانية اللي هي أربعين
+
+599
+00:56:03,730 --> 00:56:11,310
+أربعين هذه سالب عشرة سالب عشرين
+
+600
+00:56:18,320 --> 00:56:25,840
+هذه ستكون اربعين وخمستاش counter clockwise هوصل
+
+601
+00:56:25,840 --> 00:56:29,960
+بينهم و
+
+602
+00:56:29,960 --> 00:56:40,020
+ارسم more circle هذه
+
+603
+00:56:40,020 --> 00:56:47,690
+more circle معناته هذه ستكون sigma واحدو هاد ال
+
+604
+00:56:47,690 --> 00:56:56,770
+sigma 2 و هاد ال sigma 3 طيب هذا هو ال center هذا
+
+605
+00:56:56,770 --> 00:57:05,310
+ال center تعمار circle ال C بسوة
+
+606
+00:57:05,310 --> 00:57:13,890
+sigma X زي sigma Y على 2 اللي هي 60 زي 40على اتنين
+
+607
+00:57:13,890 --> 00:57:20,830
+اللي هو خمسين kilo pound per square inch هذه
+
+608
+00:57:20,830 --> 00:57:27,850
+المسافة هذه sigma
+
+609
+00:57:27,850 --> 00:57:36,190
+x او tau xy
+
+610
+00:57:47,560 --> 00:57:57,040
+وهذا sigma x minus sigma y على اتنين ال radius هذا
+
+611
+00:57:57,040 --> 00:58:03,260
+ال R ال radius بتاع مورسيا كله ال radius بالثواب
+
+612
+00:58:03,260 --> 00:58:08,720
+جزر التربيع ل sigma x minus sigma y على اتنين لكل
+
+613
+00:58:08,720 --> 00:58:15,280
+تربيع زي ال tau xy تربيع يعني هيكونالجزر التربيعى
+
+614
+00:58:15,280 --> 00:58:21,540
+ل سيجما اكس ستين ماينوس اربعين على اتنين لكل تربيع
+
+615
+00:58:21,540 --> 00:58:27,300
+زائد تاو اكس واي اللى هى خمستاش تربيع يعني هكون
+
+616
+00:58:27,300 --> 00:58:33,620
+عندى ستين نقص اربعين عشرين على اتنين عشرة ربعها
+
+617
+00:58:33,620 --> 00:58:36,660
+هكون عندى مية زائد متين وخمسة عشرين تلت مية وخمسة
+
+618
+00:58:36,660 --> 00:58:40,540
+وعشرين تلت مية وخمسة وعشرين تحت الجدر
+
+619
+00:58:50,450 --> 00:59:00,330
+تطلع تمانتاش point O تلاتة
+
+620
+00:59:00,330 --> 00:59:05,590
+kilo pound per square inch هذا ال radius سيجما
+
+621
+00:59:05,590 --> 00:59:13,790
+واحد هتكون ال C زاد ال radius ال C اللي هي خمسين
+
+622
+00:59:14,970 --> 00:59:19,590
+زائد تمانتاش point O تلاتة سواء تمانية ستين point
+
+623
+00:59:19,590 --> 00:59:24,530
+O تلاتة kilo pound per square inch و ال sigma
+
+624
+00:59:24,530 --> 00:59:31,430
+اتنين هتكون اللي هي C minus ال radius اللي هي
+
+625
+00:59:31,430 --> 00:59:36,670
+خمسين ناقص تمانتاش point O تلاتة خمسين ناقص
+
+626
+00:59:36,670 --> 00:59:40,350
+تمانتاش اتنين وتلاتين واحد تلاتين point تسعة سبعة
+
+627
+00:59:40,350 --> 00:59:46,010
+kilo pound per square inch هذا ال sigma اتنينو
+
+628
+00:59:46,010 --> 00:59:56,970
+سجبه تلاته هتكون تساوي سفر طيب
+
+629
+00:59:56,970 --> 01:00:02,410
+واضح
+
+630
+01:00:02,410 --> 01:00:08,040
+انهسيجما واحد موجب و سيجما اتنين موجب و سيجما
+
+631
+01:00:08,040 --> 01:00:11,460
+تلاتة سفر معناه ان انا في الربع الاول في الربع
+
+632
+01:00:11,460 --> 01:00:16,220
+الاول الان في حتة ال maximum shear stress theory
+
+633
+01:00:16,220 --> 01:00:22,780
+انا في ال first اكوادران عندي
+
+634
+01:00:22,780 --> 01:00:28,940
+سيجما A بتساوي تمانية و ستين point O تلاتة kilo
+
+635
+01:00:28,940 --> 01:00:33,960
+pound per square inch و سيجما Bبالساوية واحد
+
+636
+01:00:33,960 --> 01:00:37,960
+تلاتين point تسعة سبعة kilo pound per square inch
+
+637
+01:00:37,960 --> 01:00:41,380
+ال
+
+638
+01:00:41,380 --> 01:00:47,200
+factor of safety n في الحلقة ده هكون S y على sigma
+
+639
+01:00:47,200 --> 01:00:51,460
+a according to maximum shear stress theory ال S y
+
+640
+01:00:51,460 --> 01:00:56,040
+عندي مية على
+
+641
+01:00:56,040 --> 01:01:01,400
+تمانية و ستين point او تلاتة بطلع
+
+642
+01:01:07,120 --> 01:01:16,220
+مية تقسيم تمانية ستين point او تلاتة بيطلع one
+
+643
+01:01:16,220 --> 01:01:25,020
+point اربعة سبعة one point اربعة سبعة هذا طبقا لل
+
+644
+01:01:25,020 --> 01:01:30,400
+maximum shear stress theory طبقا لل distortion
+
+645
+01:01:30,400 --> 01:01:31,660
+energy theory
+
+646
+01:01:38,220 --> 01:01:42,060
+طبق الـ distortion energy theory بلزم نحسب ال
+
+647
+01:01:42,060 --> 01:01:49,280
+volume minus ال stress sigma prime بالساوية sigma
+
+648
+01:01:49,280 --> 01:01:57,540
+a تربية minus sigma a sigma b زي sigma b تربية اص
+
+649
+01:01:57,540 --> 01:02:05,940
+نص يعني حيث ساوية ال sigma a اللي هي 68 point O
+
+650
+01:02:05,940 --> 01:02:06,440
+تلاتة
+
+651
+01:02:22,770 --> 01:02:31,210
+الكل اص نص يعني
+
+652
+01:02:31,210 --> 01:02:50,050
+68.O3Square root لـ 68.03 تربيع زائد او ناقص 68.03
+
+653
+01:02:50,050 --> 01:02:58,570
+في 31.97 زائد 31.97 تربيع
+
+654
+01:03:01,150 --> 01:03:05,990
+يساوي بطلع تمانية و خمسين point تسعة خمسة تمانية و
+
+655
+01:03:05,990 --> 01:03:09,670
+خمسين point
+
+656
+01:03:09,670 --> 01:03:12,810
+تسعة خمسة kilo pound per square inch هذا ال sigma
+
+657
+01:03:12,810 --> 01:03:18,630
+prime according to max to distortion theory بيصير
+
+658
+01:03:18,630 --> 01:03:21,590
+failure لما ال sigma prime بيساوي SY يعني ال sigma
+
+659
+01:03:21,590 --> 01:03:30,370
+prime بيساوي SY على N يعني N هتساوي SYعلى sigma
+
+660
+01:03:30,370 --> 01:03:35,310
+prime أسوأ عندي مية على تمانية و خمسين bond تسعة
+
+661
+01:03:35,310 --> 01:03:42,050
+خمسة هيكون
+
+662
+01:03:42,050 --> 01:03:50,730
+عندي مية ع تبني بطلع ال factor of safety مية تقسيم
+
+663
+01:03:50,730 --> 01:03:57,230
+تمانية و خمسين bond تسعة خمسة بالساوية واحد bond
+
+664
+01:03:57,230 --> 01:03:59,230
+سبعة
+
+665
+01:04:02,390 --> 01:04:04,830
+واضح ال factor of safety في حالة ال distortion
+
+666
+01:04:04,830 --> 01:04:09,050
+energy theory اعلى منه في حالة ال maximum shear
+
+667
+01:04:09,050 --> 01:04:12,430
+stress theory لان احنا حكينا سابقا ان ال maximum
+
+668
+01:04:12,430 --> 01:04:14,910
+shear stress theory is more conservative than اللي
+
+669
+01:04:14,910 --> 01:04:19,970
+هو distortion energy theory خليني
+
+670
+01:04:19,970 --> 01:04:28,230
+بسحل كمان فرع للتوضيح لانه مهم جدا خليني اخد
+
+671
+01:04:28,230 --> 01:04:28,830
+الحالة
+
+672
+01:04:45,550 --> 01:04:55,310
+خناخد الحالة حالة تالتة سجما
+
+673
+01:04:55,310 --> 01:05:01,430
+واحد سجما
+
+674
+01:05:01,430 --> 01:05:07,290
+واحد بتساوي تلاتين kilo pound per square inch
+
+675
+01:05:07,290 --> 01:05:11,350
+وسجما
+
+676
+01:05:11,350 --> 01:05:14,310
+اتنين بتساوي برضه تلاتين
+
+677
+01:05:18,090 --> 01:05:28,730
+و سيجما تلاتة هذه
+
+678
+01:05:28,730 --> 01:05:31,430
+لاحظوا سيجما واحد بيساوي سيجما اتنين بيساوي سيجما
+
+679
+01:05:31,430 --> 01:05:35,950
+تلاتة ما انا حابب اتمثل هذه hydrostatic هذه
+
+680
+01:05:35,950 --> 01:05:48,050
+hydrostatic state of stressطبق لـ maximum shear
+
+681
+01:05:48,050 --> 01:05:51,330
+stress theory طبعا واضح هيطلع ال factor safety
+
+682
+01:05:51,330 --> 01:05:55,110
+بمقال انها infinity من غير حل يعنى هتكون يعني ال
+
+683
+01:05:55,110 --> 01:06:06,390
+tau max هيكون الساوي او هيكون
+
+684
+01:06:06,390 --> 01:06:13,850
+عندي اللي هو sigma 1 minus sigma 3 على 2 هيكون
+
+685
+01:06:13,850 --> 01:06:20,880
+ايه؟ شو الساوي؟بس الصفر يعني
+
+686
+01:06:20,880 --> 01:06:23,780
+انا لو بدى ارسمها هادى هتكون هادر سكستيتو استرس
+
+687
+01:06:23,780 --> 01:06:27,180
+هتكون
+
+688
+01:06:27,180 --> 01:06:31,800
+ال .. ال .. ال .. في حالة لو انا كنت في الرابع
+
+689
+01:06:31,800 --> 01:06:34,080
+الأول عندى سجن واحد سجن اتنين و سجن اتنين تلاتة و
+
+690
+01:06:34,080 --> 01:06:40,000
+ماقصدهم هتكون ساوى تلاتين ناقص تلاتين صفر
+
+691
+01:06:45,500 --> 01:06:54,180
+الان الان هيكون ال SSY على TAU MAX هيطلع ايش
+
+692
+01:06:54,180 --> 01:07:00,240
+Infinity تقسمها على صفر على اتنين هذه في حالة
+
+693
+01:07:00,240 --> 01:07:04,560
+distortion energy theory في حالة distortion energy
+
+694
+01:07:04,560 --> 01:07:12,640
+هيكون ال sigma prime بالساوية sigma واحد minus
+
+695
+01:07:12,640 --> 01:07:17,530
+sigma اتنين لكل تربيعزاية sigma 2 minus sigma 3
+
+696
+01:07:17,530 --> 01:07:22,630
+الكل تربية زاية sigma 3 minus sigma 1 الكل تربية
+
+697
+01:07:22,630 --> 01:07:27,770
+على 2 أص نص طبعا هذه بيستوى هذه، يعني عندما هذي
+
+698
+01:07:27,770 --> 01:07:34,850
+هستوى إيش؟ سفر وال factor of safety N بيستوى
+
+699
+01:07:34,850 --> 01:07:42,070
+اللي هو SY على sigma prime اللي هو هيكون SY على 0
+
+700
+01:07:42,070 --> 01:07:49,660
+infinityيعني بيكون infinity يعني very large state
+
+701
+01:07:49,660 --> 01:07:59,740
+of stress خليني ادحل حالة رقم .. رقم
+
+702
+01:07:59,740 --> 01:08:06,620
+C لأن فيها فكرة رقم C حالة رابعة
+
+703
+01:08:15,310 --> 01:08:22,350
+سيجما X هذه حالة تانتة أو رابعة سيجما X بالساوية
+
+704
+01:08:22,350 --> 01:08:30,430
+سفر
+
+705
+01:08:30,430 --> 01:08:34,630
+و
+
+706
+01:08:34,630 --> 01:08:39,930
+سيجما Y بالساوية أربعين و
+
+707
+01:08:39,930 --> 01:08:43,090
+تاو XY بالساوية خمسة وأربعين
+
+708
+01:08:48,910 --> 01:08:51,870
+أول اش طبعا هاجد ال principal stresses هرسم more
+
+709
+01:08:51,870 --> 01:09:01,690
+circle more circle اللي عند السفق عندها هي عشرة
+
+710
+01:09:01,690 --> 01:09:10,090
+عشرين تلاتين اربعين خمسين عشرة عشرين تلاتين اربعين
+
+711
+01:09:10,090 --> 01:09:18,090
+خمسين عندي عشرة عشرينتلاتين اربعين خمسين عند sigma
+
+712
+01:09:18,090 --> 01:09:23,210
+x صفر و tau x y خمس واربعين هي عشرة عشرين تلاتين
+
+713
+01:09:23,210 --> 01:09:29,390
+اربعين خمسين هي نقطة نقطة تانية عند اربعين عشر
+
+714
+01:09:29,390 --> 01:09:36,470
+عشرين تلاتين اربعين و سالب خمس واربعين عشرين
+
+715
+01:09:36,470 --> 01:09:41,590
+تلاتين اربعين سالب خمس واربعين معناته هوصل بينهم
+
+716
+01:09:44,680 --> 01:09:49,200
+وها دي more circle
+
+717
+01:09:49,200 --> 01:09:53,560
+طبعا ال center لأ ال center تعني more circle هاد
+
+718
+01:09:53,560 --> 01:09:58,400
+ال center C
+
+719
+01:09:58,400 --> 01:10:02,840
+هيساوة
+
+720
+01:10:02,840 --> 01:10:11,320
+sigma x زي sigma y على 2 يعني 0 زي 40 على 2
+
+721
+01:10:11,320 --> 01:10:17,120
+بالساوة 20 kilo pound per square inchهذه المسافة
+
+722
+01:10:17,120 --> 01:10:23,400
+عبارة عن sigma x من sigma y على اتنين يعني هذه
+
+723
+01:10:23,400 --> 01:10:32,440
+المسافة عبارة عن اربعين برضه عشرين وهذه عبارة عن
+
+724
+01:10:32,440 --> 01:10:37,720
+tau xy اللي هي خمسة واربعين معناه ت already أستعمر
+
+725
+01:10:37,720 --> 01:10:46,180
+circle R أستعمر جزر التربيهلعشرين تربيع زاد خمس و
+
+726
+01:10:46,180 --> 01:10:51,400
+أربعين تربيع عشرين تربيع زاد خمس و أربعين تربيع
+
+727
+01:10:51,400 --> 01:11:04,420
+بيطلع
+
+728
+01:11:04,420 --> 01:11:10,620
+تسعة و أربعين point اتنين اربعة تسعة و أربعين kilo
+
+729
+01:11:10,620 --> 01:11:16,370
+pound per square inchمعناته هذه سجما واحد هين في
+
+730
+01:11:16,370 --> 01:11:21,290
+المص صفر سجما اتنين وهين سجما تلاتة سجما واحد
+
+731
+01:11:21,290 --> 01:11:32,850
+هتكون تساوي C زائد R اللي عشرين زائد تسعة
+
+732
+01:11:32,850 --> 01:11:38,110
+واربعين سوى تسعة وستين pound اتنين اربعة kilo
+
+733
+01:11:38,110 --> 01:11:43,590
+pound per square inch وسجما اتنين صفرو ال sigma
+
+734
+01:11:43,590 --> 01:11:49,910
+تلاتة اللي هي c minus r اللي هي عشرين minus تسعة و
+
+735
+01:11:49,910 --> 01:11:55,170
+أربعين point اتنين اربعة يعني ال sigma تلاتة هتكون
+
+736
+01:11:55,170 --> 01:12:02,190
+تساوي سالب تسعة
+
+737
+01:12:02,190 --> 01:12:10,530
+و عشرين point اتنين اربعة kilo
+
+738
+01:12:10,530 --> 01:12:15,820
+poundParis Correction واضح انه عندي واحدة موجبة و
+
+739
+01:12:15,820 --> 01:12:19,400
+واحدة ايش سالبة معناته ان انا في انهيات ربع انا في
+
+740
+01:12:19,400 --> 01:12:23,020
+الرابع الرابع يعني لو رسمت ال load line المرة هذه
+
+741
+01:12:23,020 --> 01:12:27,740
+هرسم هي
+
+742
+01:12:27,740 --> 01:12:37,440
+ال sigma a و sigma b انا ال load line تبعي 69
+
+743
+01:12:37,440 --> 01:12:41,020
+و 9 سالب 29 يعني جاي ال load line بالشكل هذا
+
+744
+01:12:44,210 --> 01:12:49,030
+الان بده احكي هاد ال maximum shear stress theory
+
+745
+01:12:49,030 --> 01:12:57,170
+هاد
+
+746
+01:12:57,170 --> 01:13:00,090
+ال maximum shear stress theory و ال distortion
+
+747
+01:13:00,090 --> 01:13:01,650
+energy theory هتيجي بشكل هذا
+
+748
+01:13:13,290 --> 01:13:17,810
+هذه الأسود اللي هي ال maximum which هي ال stress
+
+749
+01:13:17,810 --> 01:13:22,550
+theory وهذه ال distortion energy theory هذه ال SY
+
+750
+01:13:22,550 --> 01:13:32,090
+اللي معطنية هي 100 وهنا 100 وهنا سالب 100 وهنا
+
+751
+01:13:32,090 --> 01:13:39,390
+سالب 100 ال load line بتاعي 69 هذه النفطة هذه
+
+752
+01:13:42,180 --> 01:13:53,040
+تسعة ستين واربع وعشرين وهذا سالب تسعة وعشرين واربع
+
+753
+01:13:53,040 --> 01:13:56,760
+وعشرين
+
+754
+01:13:56,760 --> 01:14:01,400
+الان
+
+755
+01:14:01,400 --> 01:14:07,160
+طبقا ل maximum shear stress theory maximum shear
+
+756
+01:14:07,160 --> 01:14:08,800
+stress theory هكون
+
+757
+01:14:10,970 --> 01:14:17,330
+سوى سيجما واحد مانس سيجما تلاتة على اتنين اللى
+
+758
+01:14:17,330 --> 01:14:22,790
+هتساوي ال radius هتساوي اللى هو ال radius بتاع مور
+
+759
+01:14:22,790 --> 01:14:28,410
+سيركل اللى هتكون تسعة و اربعين point اتنين اربعة
+
+760
+01:14:28,410 --> 01:14:38,210
+kilo pound per square inch ال
+
+761
+01:14:38,210 --> 01:14:45,740
+SSYبساوة نص ال S Y يعني هتكون خمسين كيلو pound per
+
+762
+01:14:45,740 --> 01:14:55,260
+square inch ال N بساوة S S Y على Tau Max ال S S Y
+
+763
+01:14:55,260 --> 01:15:02,080
+اللي هي خمسين على تسعة واربعين point اتنين اربع أو
+
+764
+01:15:02,080 --> 01:15:05,040
+almost واحد تقريبا خمسين
+
+765
+01:15:06,840 --> 01:15:10,480
+تقسيم تسعة واربعين point اتنين اربعة تقسيم تسعة
+
+766
+01:15:10,480 --> 01:15:12,280
+واربعين point اتنين اربعة تقسيم تسعة واربعين point
+
+767
+01:15:12,280 --> 01:15:14,400
+اتنين اربع تقسيم تسعة واربع تقسيم تسعة واربع تقسيم
+
+768
+01:15:14,400 --> 01:15:20,900
+تسعة واربع تقسيم تسعة واربع تقسيم تسعة واربع تقسيم
+
+769
+01:15:20,900 --> 01:15:23,680
+تسعة واربع تقسيم تسعة واربع تقسيم تسعة واربع تقسيم
+
+770
+01:15:23,680 --> 01:15:27,880
+تسعة واربع تقسيم تسعة واربع تقسيم تسعة واربع تقسيم
+
+771
+01:15:27,880 --> 01:15:34,840
+تسعة واربع تقسيم تسعة واربع تقسيم تسعة واربع تقسيم
+
+772
+01:15:34,840 --> 01:15:43,160
+تسعة واربسيجما ايه اللي هي تسعة وستين واربع وعشرين
+
+773
+01:15:43,160 --> 01:15:46,940
+minus
+
+774
+01:15:46,940 --> 01:15:53,000
+سيجما ايه اللي هي تسعة وستين واربع وعشرين فيه
+
+775
+01:15:53,000 --> 01:15:58,580
+سيجما بيه سالب تسعة وعشرين point اتنين اربع زائد
+
+776
+01:15:58,580 --> 01:16:04,160
+تسعة وعشرين point اتنين اربع تربيع لكل أص نص منها
+
+777
+01:16:04,160 --> 01:16:05,280
+بنحسب سيجما prime
+
+778
+01:16:08,080 --> 01:16:12,760
+اللي هتكون تسعة
+
+779
+01:16:12,760 --> 01:16:18,580
+و ستين point اتنين اربع تربيع زائد تسعة و ستين
+
+780
+01:16:18,580 --> 01:16:22,480
+point اتنين اربع في تسعة و عشرين point اتنين اربع
+
+781
+01:16:22,480 --> 01:16:28,720
+زائد تسعة و عشرين point اتنين اربع تربيع يساوي
+
+782
+01:16:28,720 --> 01:16:31,160
+تطلع سبعة و تمانين point ستة
+
+783
+01:16:38,540 --> 01:16:47,580
+الان حيكون متساوي SY على Sigma Prime SY اللي هي
+
+784
+01:16:47,580 --> 01:17:00,500
+مية على سبعة تمانين point ستة مية تطلع
+
+785
+01:17:00,500 --> 01:17:06,320
+one point واحد اربع اتنين
+
+786
+01:17:10,940 --> 01:17:14,000
+ممكن احكي برضه N في ال .. انا .. انا حاليا انا ..
+
+787
+01:17:14,000 --> 01:17:16,200
+انا في ال fourth quadrant انا في ال fourth
+
+788
+01:17:16,200 --> 01:17:21,280
+quadrant ممكن
+
+789
+01:17:21,280 --> 01:17:29,560
+احكي انه برضه ال N بالسواء SSY على tau max SSY
+
+790
+01:17:29,560 --> 01:17:36,660
+اللي هي خمسين ال
+
+791
+01:17:36,660 --> 01:17:38,400
+SSY في الحالة هتبقى ايش بالساوية؟
+
+792
+01:17:40,740 --> 01:17:44,200
+الاس اس واي في حدث torch energy theory اس اس واي
+
+793
+01:17:44,200 --> 01:17:50,080
+سبعة خمسة سبعة سبعة اس واي يعني هتكون سبعة وخمسين
+
+794
+01:17:50,080 --> 01:17:53,720
+بونت سبعة كيلو pound per square inch يعني هتكون اس
+
+795
+01:17:53,720 --> 01:17:57,940
+اس واي بالساوي سبعة وخمسين بونت سبعة على tau
+
+796
+01:17:57,940 --> 01:18:01,900
+maximum اللي هي حسبناها تسعة واربعين بونت اتنين
+
+797
+01:18:01,900 --> 01:18:03,620
+اربعة سبعة وخمسين
+
+798
+01:18:11,060 --> 01:18:23,300
+لا واحد point سبعة واحد طيب المحاضرة
+
+799
+01:18:23,300 --> 01:18:29,360
+الجاية بنكمل .. المحاضرة الجاية بنكمل بنحل مسائل
+
+800
+01:18:29,360 --> 01:18:34,760
+تانية او بنتعرف على new theory اللي هي more theory
+
+801
+01:18:34,760 --> 01:18:38,560
+و هنحل مسائل كلهم more theory
+
+802
+01:18:42,860 --> 01:18:47,120
+هنحل مسألة خمسة اتنين و خمسة تلاتة و خمسة أربعة
+
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/GdwYlgLJm0Y_raw.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/GdwYlgLJm0Y_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..ff77e085965669737ce879016fd275cf382b7148
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/GdwYlgLJm0Y_raw.srt
@@ -0,0 +1,3208 @@
+1
+00:00:04,890 --> 00:00:07,630
+بسم الله الرحمن الرحيم السلام عليكم ورحمة الله
+
+2
+00:00:07,630 --> 00:00:10,970
+وبركاته اليوم هنستكمل الهو failures resulting from
+
+3
+00:00:10,970 --> 00:00:15,810
+static loading المحاضرات الفاتة استعرضتنا اللي هي
+
+4
+00:00:15,810 --> 00:00:22,030
+خارطة الطريق لل .. لل static .. لل failure
+
+5
+00:00:22,030 --> 00:00:25,790
+criterion selection حكينا أول شيء لازم نفحص نشوف
+
+6
+00:00:25,790 --> 00:00:30,600
+المادة هل هي ductile ولا brittleالـ ductility or
+
+7
+00:00:30,600 --> 00:00:33,820
+brittleness is examined via ال .. ال .. ال .. هو
+
+8
+00:00:33,820 --> 00:00:36,600
+ال epsilon f إذا ال epsilon f أكبر يستوى point oh
+
+9
+00:00:36,600 --> 00:00:39,520
+five معناته المثير is ductile إذا ال epsilon f أقل
+
+10
+00:00:39,520 --> 00:00:42,360
+من أكبر من point oh five معناته المثير is brittle
+
+11
+00:00:42,360 --> 00:00:47,980
+الآن الجهة هذه ductile الجهة هذه إيش brittle أول
+
+12
+00:00:48,800 --> 00:00:51,720
+check for ductile material I want to check إذا كان
+
+13
+00:00:51,720 --> 00:00:54,280
+ال yield strength in tension بيستوى yield strength
+
+14
+00:00:54,280 --> 00:00:56,360
+in compression إذا كان yield strength in tension
+
+15
+00:00:56,360 --> 00:01:00,500
+بيستوى yield strength in compression معناته ياما
+
+16
+00:01:00,500 --> 00:01:04,300
+بدي أحصل على conservative calculations أو more
+
+17
+00:01:04,300 --> 00:01:07,040
+accurate less conservative calculations if I'm
+
+18
+00:01:07,040 --> 00:01:11,560
+interested in more conservative less risky
+
+19
+00:01:11,560 --> 00:01:14,380
+calculations ممكن أستخدم ال maximum shear stress
+
+20
+00:01:14,380 --> 00:01:19,960
+theory إذا أنا يعني إذا أنامعنى في ال .. ال ..
+
+21
+00:01:19,960 --> 00:01:24,580
+اللي هي more accurate results less conservative
+
+22
+00:01:24,580 --> 00:01:27,840
+ممكن أستخدم اللي هي ال distortion energy theory
+
+23
+00:01:27,840 --> 00:01:33,320
+طيب السؤال بيطرح نفسه طيب ما زال اللي هو ال .. ال
+
+24
+00:01:33,320 --> 00:01:36,220
+.. ال .. الآن في حالة ال conservative theories
+
+25
+00:01:36,220 --> 00:01:39,620
+عنده عنصر مخاطب الحسابات أقل ليش ماشتغل دايما
+
+26
+00:01:39,620 --> 00:01:43,910
+conservative لألو انا مثلا انا بدي أنتج من ال ..
+
+27
+00:01:43,910 --> 00:01:47,710
+ال mechanical ان بدي أنتج مثلا عشر قطع، مية قطع،
+
+28
+00:01:47,710 --> 00:01:51,970
+الف قطع، الكمية هادة، صغيرة، في الحالة هادة بفضل
+
+29
+00:01:51,970 --> 00:01:55,910
+اشتغل according to conservative calculations لكن
+
+30
+00:01:55,910 --> 00:02:02,030
+انا لو بدي أنتج .. أنتج قطع موجودة في السيارة مثلا
+
+31
+00:02:02,030 --> 00:02:08,190
+بدي اعمل screw او برغة عدد البراغي في السيارة في
+
+32
+00:02:08,190 --> 00:02:12,270
+ال .. في مثلا عندي مية برغة من نفس النوعوفترض ان
+
+33
+00:02:12,270 --> 00:02:16,830
+الشركة بتنتج كل يوم عشر تلاف سيارة عشر تلاف
+
+34
+00:02:16,830 --> 00:02:20,750
+تلاتمية خمس ستين فتخيل اكم قطع هنتج ملايين القطع
+
+35
+00:02:20,750 --> 00:02:24,790
+معناته انا لما تكون ال calculation more
+
+36
+00:02:24,790 --> 00:02:28,910
+conservative معناته هستخدم مواد اكتر هستهلك مواد
+
+37
+00:02:28,910 --> 00:02:32,910
+اكتر فالتكلفة هتكون بترتفع في الحالة هذه بلجأ
+
+38
+00:02:32,910 --> 00:02:36,970
+لاستخدام more accurate او more accurate
+
+39
+00:02:38,240 --> 00:02:42,280
+calculations او فبستخدم مثلا theories اللي هي more
+
+40
+00:02:42,280 --> 00:02:45,580
+accurate theories في الحالات اللي بوفر في المواد و
+
+41
+00:02:45,580 --> 00:02:49,740
+في ال materials في حالة اندي huge mass .. mass
+
+42
+00:02:49,740 --> 00:02:54,690
+productionمعناته في حالة ductile material وكانت ال
+
+43
+00:02:54,690 --> 00:02:56,790
+yield strength in tension بستوي yield strength in
+
+44
+00:02:56,790 --> 00:03:00,090
+compression if I need conservative calculations I
+
+45
+00:03:00,090 --> 00:03:02,770
+use the maximum shear stress theory if I need more
+
+46
+00:03:02,770 --> 00:03:05,550
+accurate less conservative calculations I use the
+
+47
+00:03:05,550 --> 00:03:08,610
+distortion energy theory الآن إذا كانت ال yield
+
+48
+00:03:08,610 --> 00:03:10,570
+strength in tension بستوي yield strength in
+
+49
+00:03:10,570 --> 00:03:13,210
+compression بستخدم ductile columnar theory في حالة
+
+50
+00:03:13,210 --> 00:03:18,100
+ال ductile material الآن الجهة تمثل الالـ brittle
+
+51
+00:03:18,100 --> 00:03:21,780
+material إذا كانت ال material brittle if I want
+
+52
+00:03:21,780 --> 00:03:26,300
+conservative less risky calculations I use brittle
+
+53
+00:03:26,300 --> 00:03:31,500
+column more theory if I need more accurate more
+
+54
+00:03:31,500 --> 00:03:36,200
+risky calculations I use modified more theoryالان
+
+55
+00:03:36,200 --> 00:03:38,500
+حكينا عن ال maximum normal stress theory ال
+
+56
+00:03:38,500 --> 00:03:40,420
+maximum .. ال maximum normal stress theory بتحكي
+
+57
+00:03:40,420 --> 00:03:44,500
+انه ال yielding او ال failure ببدأ لما ال maximum
+
+58
+00:03:44,500 --> 00:03:47,900
+principal stress في ال mechanical element بيكون
+
+59
+00:03:47,900 --> 00:03:51,120
+اكبر او يساوي ال yield strength ده ال material
+
+60
+00:03:51,120 --> 00:03:54,740
+يعني ال .. احنا ال principal stresses بنحسبها من
+
+61
+00:03:54,740 --> 00:03:57,400
+مورسلك بنحسب سجن واحد سجن اتنين و سجن تلاتي يعني
+
+62
+00:03:57,400 --> 00:04:00,360
+اذا كان سجن واحد اكبر أو يساوي اسواء يصير اندي
+
+63
+00:04:00,360 --> 00:04:04,800
+yielding يصير اندي failureال maximum طبعا ال
+
+64
+00:04:04,800 --> 00:04:06,820
+maximum normal stress theory is not conservative
+
+65
+00:04:06,820 --> 00:04:12,460
+in the fourth quadrant لأن
+
+66
+00:04:12,460 --> 00:04:17,520
+ال maximum normal stress theory ممكن تحكيلي ان ال
+
+67
+00:04:17,520 --> 00:04:21,780
+part is not failing while actually it fails يعني
+
+68
+00:04:21,780 --> 00:04:25,000
+بتحكيلي ان ال part مش failure لكن في الواقع
+
+69
+00:04:25,000 --> 00:04:33,130
+failure عشان هيكbut يعني .. يعني انا عن نفسي شخصيا
+
+70
+00:04:33,130 --> 00:04:35,650
+و عالميا ما بستخدم ال maximum normal stress theory
+
+71
+00:04:35,650 --> 00:04:40,510
+for .. for design calculations ال maximum shear
+
+72
+00:04:40,510 --> 00:04:43,490
+stress .. stress theory بتحكي ان ال yielding ببدأ
+
+73
+00:04:43,490 --> 00:04:47,490
+لما ال maximum shear stress .. ال maximum shear
+
+74
+00:04:47,490 --> 00:04:51,070
+stress في stress element اللي هو الحقيقة بتكون
+
+75
+00:04:51,070 --> 00:04:54,850
+أكبر او يساوي ال maximum shear stress في tensile
+
+76
+00:04:54,850 --> 00:05:00,380
+test specimen بمعنىانه بيصير failure لما ال tau
+
+77
+00:05:00,380 --> 00:05:04,400
+maximum تكون اكبر او يساوي as y على 2 و احنا في ال
+
+78
+00:05:04,400 --> 00:05:06,480
+.. لما كنا عندى multistate of stress كنا نحسس
+
+79
+00:05:06,480 --> 00:05:10,140
+sigma 1 و sigma 2 و sigma 3 و الرتبهم بيحس sigma 1
+
+80
+00:05:10,140 --> 00:05:13,220
+اكبر من sigma 2 اكبر من sigma 3 و ال tau maximum
+
+81
+00:05:13,220 --> 00:05:17,560
+كان يساوي as sigma 1 minus sigma 2 ف according to
+
+82
+00:05:17,560 --> 00:05:20,960
+maximum shear stress theory بيكون عندى ال .. ال ..
+
+83
+00:05:21,740 --> 00:05:25,240
+تاو ماكسوم يستوى سجما واحد ناقصه سجما تلاته على
+
+84
+00:05:25,240 --> 00:05:27,940
+اتنين بيصير failure لما تاو ماكسوم يكون اكبر او
+
+85
+00:05:27,940 --> 00:05:33,220
+يستوى اس و اي على اتنين اخدنا
+
+86
+00:05:33,220 --> 00:05:37,500
+two D states of stress و رسمنا اللي هو inferior
+
+87
+00:05:37,500 --> 00:05:41,240
+contour ل maximum shear stress theory عندنا case
+
+88
+00:05:41,240 --> 00:05:45,820
+one هذه case one ان سجما a اكبر من سجما b اكبر من
+
+89
+00:05:45,820 --> 00:05:50,090
+صفر يعني سجما a و سجما b موجبات في الحالة هذهبيكون
+
+90
+00:05:50,090 --> 00:05:54,050
+عندي .. بيصير failure لما sigma a تكون أكبر أو
+
+91
+00:05:54,050 --> 00:05:59,650
+يساوي as y case two ان sigma ا موجة و sigma b
+
+92
+00:05:59,650 --> 00:06:05,410
+سالبة في الحالة هذه sigma a minus sigma b بتكون
+
+93
+00:06:05,410 --> 00:06:10,010
+أكبر أو يساوي as y ال case التالتة both sigma a
+
+94
+00:06:10,010 --> 00:06:14,030
+and sigma b are negative بيصير failure لما sigma b
+
+95
+00:06:14,030 --> 00:06:19,400
+تكون أقل أو يساوم سالب as yif we compare ال
+
+96
+00:06:19,400 --> 00:06:21,940
+maximum shear stress theory with empirical او
+
+97
+00:06:21,940 --> 00:06:26,060
+experimental data بنلاحظ انه بتعطيني conservative
+
+98
+00:06:26,060 --> 00:06:29,640
+results انه ال maximum shear stress theory
+
+99
+00:06:29,640 --> 00:06:34,180
+predicts failure before actually it fails عشان كده
+
+100
+00:06:34,180 --> 00:06:37,180
+بسميها conservative theory طبعا في كل quadrant
+
+101
+00:06:37,180 --> 00:06:39,800
+سواء كان في ال quadrant الأول او ال quadrant
+
+102
+00:06:39,800 --> 00:06:44,600
+الرابع we predict failure before failure actually
+
+103
+00:06:44,600 --> 00:06:50,620
+happensالان اليوم هنحكي على نظرية جديدة اللي هي
+
+104
+00:06:50,620 --> 00:06:55,220
+distortion energy theory distortion energy theory
+
+105
+00:06:55,220 --> 00:06:58,000
+distortion energy theory في كتير من الكتب
+
+106
+00:06:58,000 --> 00:07:02,860
+بيستخدموا أسماء مختلفة لها أسماء أخرى للنظرية في
+
+107
+00:07:02,860 --> 00:07:05,740
+كتب تانية ماكنت تلاحظوها اللي هي octahedral shear
+
+108
+00:07:05,740 --> 00:07:06,540
+stress theory
+
+109
+00:07:09,110 --> 00:07:13,770
+الـ shear energy theory هذا اسم تاني اسم تالت Von
+
+110
+00:07:13,770 --> 00:07:18,950
+Mises Theory اسم رابع اللي هي Von Mises-Henke
+
+111
+00:07:18,950 --> 00:07:22,370
+Theory معناته هذه إذا تروح لمراجع تانية ممكن
+
+112
+00:07:22,370 --> 00:07:26,090
+تلاحظوا إليها أسماء متداولة أسماء مختلفة اللي هي
+
+113
+00:07:26,090 --> 00:07:29,330
+octahedral shear stress theory shear energy theory
+
+114
+00:07:29,330 --> 00:07:32,590
+Von Mises Theory و Von Mises-Henke Theory
+
+115
+00:07:36,750 --> 00:07:43,070
+الان تقديم او تحضير لل .. لل theory هذا اول ملاحظة
+
+116
+00:07:43,070 --> 00:07:45,690
+لاحظوا tactile materials stressed hydrostatically
+
+117
+00:07:45,690 --> 00:07:48,330
+exhibit yield strength greatly in excess of
+
+118
+00:07:48,330 --> 00:07:51,590
+expected values يعني لو حطيت انا قطعة تحت سطح
+
+119
+00:07:51,590 --> 00:07:58,550
+البحر مكعب في مياه
+
+120
+00:08:04,990 --> 00:08:11,530
+hydrostatic stress معناته بتعرض
+
+121
+00:08:11,530 --> 00:08:23,090
+لضغط من كل الجهات الآن
+
+122
+00:08:23,090 --> 00:08:25,690
+إذا بيكون ال mechanical element العالم افترض انه
+
+123
+00:08:25,690 --> 00:08:30,030
+على شكل مكعب متعرض
+
+124
+00:08:30,030 --> 00:08:33,030
+لهydrostatic pressure او hydrostatic state of
+
+125
+00:08:33,030 --> 00:08:33,450
+stress
+
+126
+00:08:36,120 --> 00:08:40,660
+معناته due to poison effect لو أخدت ال sigma هذه
+
+127
+00:08:40,660 --> 00:08:43,740
+ال sigma هذه بتحاول ايش تضغط بتحاول تكبر ال
+
+128
+00:08:43,740 --> 00:08:47,460
+dimensions في الاتجاهات التانية التانية الأخرين ال
+
+129
+00:08:47,460 --> 00:08:50,280
+sigma هذه بتحاول تعكس ال effect تاعتها ده يعني هذه
+
+130
+00:08:50,280 --> 00:08:54,500
+بتحاول تتزغر زي هيك و تكبر الجهة التانية هذه
+
+131
+00:08:54,500 --> 00:08:56,940
+بتحاول تزغر هيك و تكبر الجهة التانية فهذه بتعكس
+
+132
+00:08:56,940 --> 00:09:00,640
+هذه و هذه بتعكس هذه يعني بعكس و في بعض فال
+
+133
+00:09:00,640 --> 00:09:04,180
+material بتتحمل yield strength عالي جدا جدا في
+
+134
+00:09:04,180 --> 00:09:10,850
+حالةاللي هو hydrostatic loading condition معناته
+
+135
+00:09:10,850 --> 00:09:15,390
+ممكن اعتبر انه في حالة hydrostatic loading
+
+136
+00:09:15,390 --> 00:09:18,790
+condition انه المادية ممكن تتحمل infinite state of
+
+137
+00:09:18,790 --> 00:09:21,350
+stress يعني ممكن يكون ال stress very very very
+
+138
+00:09:21,350 --> 00:09:30,730
+huge وهذا حقيقة هذا الآن ال ..في الواقع مايكونش
+
+139
+00:09:30,730 --> 00:09:35,050
+الـ mechanical element under a pure hydrostatic
+
+140
+00:09:35,050 --> 00:09:38,810
+loading condition مايكونش ال sigma زي هذه متساومة
+
+141
+00:09:38,810 --> 00:09:43,330
+بيكون ان دي sigma واحدو sigma 2 و sigma 3 يعني
+
+142
+00:09:43,330 --> 00:09:47,010
+sigma 1 مختلفة قيمتها عن sigma 2 مختلفة عن sigma 3
+
+143
+00:09:47,010 --> 00:09:51,030
+طالما ان sigma 1 و sigma 2 و sigma 3 الان ال duty
+
+144
+00:09:51,030 --> 00:09:54,190
+sigma 1 و sigma 2 و sigma 3 بيصير تشوه للمادة
+
+145
+00:09:54,190 --> 00:09:57,750
+بيصير في عندى strain ال strain energy ممكن اقسمها
+
+146
+00:09:57,750 --> 00:10:04,150
+لجزءين جزء بيعمل لي volume change بيغير الحجم اذا
+
+147
+00:10:04,150 --> 00:10:07,930
+انا مضغطه من كل جهات بيحاول ايش اصغر حجمها وجزء
+
+148
+00:10:07,930 --> 00:10:13,890
+التاني بيحاول ايشيشوّهها يغير الشكل ت distorted
+
+149
+00:10:13,890 --> 00:10:19,710
+معناته strain energy ممكن تكون تاخد شكلين شكل
+
+150
+00:10:19,710 --> 00:10:23,790
+بيغير في الحجم جزء بيغير في الحجم وجزء بيغير
+
+151
+00:10:23,790 --> 00:10:29,950
+بالشكل اللي هو angular distortion energy yielding
+
+152
+00:10:29,950 --> 00:10:34,710
+احنا حكينا جزئية بتغير الحجم هي جزئية due to
+
+153
+00:10:34,710 --> 00:10:38,730
+hydrostatic state of stress وهذه ما بتعمل yielding
+
+154
+00:10:38,730 --> 00:10:43,100
+yielding primarilyis affected by the distortion
+
+155
+00:10:43,100 --> 00:10:48,440
+energy part اللي هو الجزء اللي بيغير شكل ال
+
+156
+00:10:48,440 --> 00:10:56,360
+mechanical part الان
+
+157
+00:10:56,360 --> 00:10:59,620
+ال distortion energy failure theory بتحكي التالت
+
+158
+00:10:59,620 --> 00:11:02,760
+بتحكي yielding occurs بتحكي yielding او failure
+
+159
+00:11:02,760 --> 00:11:09,130
+بيصير لماالدستورشن دمج طاقة على جزء من الوزياء
+
+160
+00:11:09,130 --> 00:11:15,710
+للأشياء الميكانية تحت التدريب تصل إلى دستورشن دمج
+
+161
+00:11:15,710 --> 00:11:21,730
+طاقة على جزء من الوزياء للدفع في مجلة تنسيل بسيطة
+
+162
+00:11:23,320 --> 00:11:26,320
+having the same material معناته distortion energy
+
+163
+00:11:26,320 --> 00:11:29,000
+theory بتحكي انه بيصير failure او بيصير yielding
+
+164
+00:11:29,000 --> 00:11:33,800
+لما distortion strain energy per unit volume in
+
+165
+00:11:33,800 --> 00:11:38,160
+the mechanical element under study reaches the
+
+166
+00:11:38,160 --> 00:11:43,360
+distortion strain energy per unit volume of a
+
+167
+00:11:43,360 --> 00:11:46,600
+tensile test specimen of the same material في
+
+168
+00:11:46,600 --> 00:11:49,520
+الحالة هذه بيصير ايش عنده yielding او بيصير
+
+169
+00:11:49,520 --> 00:11:54,730
+failureأنا باين عندي هنا mechanical element و ماخد
+
+170
+00:11:54,730 --> 00:11:58,030
+ال principle state stress element يعني عندي هنا
+
+171
+00:11:58,030 --> 00:12:06,630
+سجما واحد و هنا سجما اتنين و هنا سجما تلاتة ممكن
+
+172
+00:12:06,630 --> 00:12:14,330
+احكي هذا بيساوي التالي this element ال equivalent
+
+173
+00:12:14,330 --> 00:12:17,810
+للمجموعة ال element هذا و ال element هذا ال
+
+174
+00:12:17,810 --> 00:12:23,340
+element هذا متعرض لسجما averageSigma Average و
+
+175
+00:12:23,340 --> 00:12:32,820
+Sigma Average Sigma Average بالساوية سيجما واحد
+
+176
+00:12:32,820 --> 00:12:40,220
+زائد سيجما اتنين زائد سيجما تلاتة على تلاتة زائد
+
+177
+00:12:40,220 --> 00:12:43,880
+another element وهو عبارة عن سيجما واحد minus
+
+178
+00:12:43,880 --> 00:12:48,840
+sigma average وهين sigma اتنين minus sigma average
+
+179
+00:12:49,790 --> 00:12:53,770
+وهنا sigma تلاتة minus sigma average يعني لو
+
+180
+00:12:53,770 --> 00:12:57,690
+جمعتين هذا مع هذا هتروح sigma average مع sigma
+
+181
+00:12:57,690 --> 00:13:00,550
+average بيبقى لعندي sigma واحد لو جماعة هذا مع هذا
+
+182
+00:13:00,550 --> 00:13:02,330
+بتروح sigma average مع sigma average بيبقى لعندي
+
+183
+00:13:02,330 --> 00:13:06,170
+sigma اتنين لو جماعة هذا اللي هو sigma هذا بتروح
+
+184
+00:13:06,170 --> 00:13:08,090
+sigma average مع sigma average بيبقى لعندي sigma
+
+185
+00:13:08,090 --> 00:13:10,590
+تلاتة معناته هذا ال element equivalent to these
+
+186
+00:13:10,590 --> 00:13:11,510
+two elements
+
+187
+00:13:18,890 --> 00:13:23,930
+الـ Strain Energy Per Unit Volume من Chapter 4 الـ
+
+188
+00:13:23,930 --> 00:13:34,350
+U لكل واحدة حجم بتساوي اللي هي نص في
+
+189
+00:13:34,350 --> 00:13:40,570
+أبسلون واحد سجن واحد زاد أبسلون اتنين سجن اتنين
+
+190
+00:13:40,570 --> 00:13:44,630
+زاد أبسلون تلاتة سجن تلاتة
+
+191
+00:13:47,460 --> 00:13:54,420
+و أبسلون واحد بيصيح واحد على ايه في سجن واحد ناقص
+
+192
+00:13:54,420 --> 00:13:59,560
+ال U في سجن اتنين زائد سجن تلاتة هذا شفتر أربعة و
+
+193
+00:13:59,560 --> 00:14:05,240
+أبسلون اتنين بيصيح واحد على ايه في سجن اتنين minus
+
+194
+00:14:05,240 --> 00:14:12,160
+U في سجن واحد زائد سجن تلاتة و أبسلون تلاتة بيصيح
+
+195
+00:14:12,160 --> 00:14:14,600
+واحد على ايه في
+
+196
+00:14:18,950 --> 00:14:29,570
+سيجما تلاتة minus U في سيجما واحد زائد سيجما اتنين
+
+197
+00:14:29,570 --> 00:14:35,650
+الان اللي عوضنا عن في المعادلة هذه عن أبسل واحد
+
+198
+00:14:35,650 --> 00:14:38,470
+اقصى اتنين اقصى تلاتة بس ال U ال total distortion
+
+199
+00:14:38,470 --> 00:14:44,510
+ال U per unit volume بسعة نص فيه
+
+200
+00:14:44,510 --> 00:14:57,060
+أبسل واحدوحد على ايه في سجما واحد minus in you في
+
+201
+00:14:57,060 --> 00:15:04,500
+سجما اتنين زائد سجما تلاتة زائد
+
+202
+00:15:04,500 --> 00:15:16,120
+واحد على ايه في طبعا هنا في سجما واحد زائد سجما
+
+203
+00:15:16,120 --> 00:15:26,080
+اتنينعلى E في Sigma 2 minus U في Sigma 1 زائد
+
+204
+00:15:26,080 --> 00:15:39,040
+Sigma 3 زائد Sigma 3 على E في Sigma 3 minus U في
+
+205
+00:15:39,040 --> 00:15:41,420
+Sigma 1 زائد Sigma 2
+
+206
+00:15:46,310 --> 00:15:55,490
+هطلع طبعا هطلع واحد على اتنين اي عامل مشترك بيصير
+
+207
+00:15:55,490 --> 00:16:03,510
+هنا دي سجم واحد تربيع خلصت من هذه minus
+
+208
+00:16:03,510 --> 00:16:10,470
+new يعني هجمعهم مع بعض هاخد هذه سجم واحد تربيع زي
+
+209
+00:16:10,470 --> 00:16:18,330
+سجم اتنين تربيعزائر سيجما تلاتة تربيع يعني خلصت من
+
+210
+00:16:18,330 --> 00:16:32,370
+هذه وهذه وهذه minus in you في عند
+
+211
+00:16:32,370 --> 00:16:39,870
+سيجما واحد سيجما اتنين زائر سيجما واحد سيجما تلاتة
+
+212
+00:16:41,020 --> 00:16:49,080
+زاد سجما واحد سجما اتنين زاد سجما اتنين سجما تلاتة
+
+213
+00:16:49,080 --> 00:16:58,740
+زاد سجما واحد سجما تلاتة زاد سجما اتنين سجما تلاتة
+
+214
+00:16:58,740 --> 00:17:07,490
+خسيرا دي واحد على اتنين E فيسيجما واحد تربيع زائر
+
+215
+00:17:07,490 --> 00:17:11,810
+سيجما اتنين تربيع زائر سيجما تلاتة تربيع minus ال
+
+216
+00:17:11,810 --> 00:17:19,130
+U في اتنين ال U في سيجما
+
+217
+00:17:19,130 --> 00:17:24,490
+واحد سيجما اتنين زائر سيجما واحد سيجما تلاتة زائر
+
+218
+00:17:24,490 --> 00:17:30,210
+سيجما اتنين سيجما تلاتة هذا ال total distortion
+
+219
+00:17:30,210 --> 00:17:36,570
+energyلأن إذا بدى أحسب ال distortion energy per
+
+220
+00:17:36,570 --> 00:17:40,510
+unit volume due to static loading يعني due to
+
+221
+00:17:40,510 --> 00:17:44,810
+sigma average if for
+
+222
+00:17:44,810 --> 00:17:50,990
+a hydrostatic
+
+223
+00:17:50,990 --> 00:17:57,730
+element في الحالة هذي بتكون sigma 1 بيساوي sigma 2
+
+224
+00:17:57,730 --> 00:18:01,960
+بيساوي sigma 3 بيساوي sigma averageهيصير عندى هنا
+
+225
+00:18:01,960 --> 00:18:10,700
+ال U اللى هى ال U هايدروستاتك اتش هتسميها هتكون
+
+226
+00:18:10,700 --> 00:18:20,380
+واحد على اتنين E فيه هتكون هنا عندى هيطلع عندى
+
+227
+00:18:20,380 --> 00:18:25,460
+sigma average تربية سيجما افرج سيجما افرج سيجما
+
+228
+00:18:25,460 --> 00:18:29,840
+افرج سيجما افرج في
+
+229
+00:18:29,840 --> 00:18:30,740
+واحد
+
+230
+00:18:38,610 --> 00:18:42,510
+-2NU خلّيني أعملها بطوطين
+
+231
+00:18:45,590 --> 00:18:50,250
+في sigma average تسمى تلاتة تلاتة sigma average
+
+232
+00:18:50,250 --> 00:18:59,090
+تربيع ناقص اتنين in U في تلاتة sigma average تربيع
+
+233
+00:18:59,090 --> 00:19:08,710
+يعني هتكون تساوي تلاتة sigma average تربيع على
+
+234
+00:19:08,710 --> 00:19:13,910
+اتنين E في واحد ناقص اتنين in U
+
+235
+00:19:17,350 --> 00:19:19,790
+و ال sigma average احنا حكينا بيساوي sigma 1 زي
+
+236
+00:19:19,790 --> 00:19:25,030
+sigma 2 زي sigma 3 على 3 اللي انا اذا بعوض عن
+
+237
+00:19:25,030 --> 00:19:32,530
+sigma average و simplify ال U volume هتعطي
+
+238
+00:19:32,530 --> 00:19:37,030
+بالعلاقة هذه اللي هي واحد ناقص اتنين
+
+239
+00:19:45,520 --> 00:19:48,280
+هتكون واحد نقص اتنين على ستة ايه في سجن واحد تربيع
+
+240
+00:19:48,280 --> 00:19:50,660
+زي سجن اتنين تربيع زي سجن تلات تربيع زي اتنين سجن
+
+241
+00:19:50,660 --> 00:19:53,480
+واحد سجن اتنين زي اتنين سجن اتنين سجن تلاتة وزي
+
+242
+00:19:53,480 --> 00:19:56,660
+اتنين سجن تلاتة سجن واحد الان ال total energy U
+
+243
+00:19:58,780 --> 00:20:02,580
+بستوي U due to volume change زي U due to
+
+244
+00:20:02,580 --> 00:20:11,180
+distortion بيستوي U-UV انا عارف U وعارف UV بحسو ال
+
+245
+00:20:11,180 --> 00:20:15,440
+U distortion بحكي U distortion بيستوي U-UV بعوض و
+
+246
+00:20:15,440 --> 00:20:19,180
+بعمل تبسيط بيصير ال U due to distortion بيستوي
+
+247
+00:20:19,180 --> 00:20:22,820
+واحد زي ال U على التلاتة E في سجن واحدمينا سجن
+
+248
+00:20:22,820 --> 00:20:25,100
+اتنين لكل تربيع زي سجن اتنين نقص سجن تلاتي لكل
+
+249
+00:20:25,100 --> 00:20:33,280
+تربيع زي سجن تلاتي من سجن واحد لكل تربيع الان
+
+250
+00:20:33,280 --> 00:20:46,120
+for for
+
+251
+00:20:46,120 --> 00:20:51,660
+a tensile test specimen for a tensile
+
+252
+00:20:55,070 --> 00:21:03,350
+test specimen بيكون عندي يعني هاي عند ال stress
+
+253
+00:21:03,350 --> 00:21:08,450
+element بيكون عليه إيه إيش سيجما واحد سيجما واحد
+
+254
+00:21:08,450 --> 00:21:12,270
+بيكون عندي سيجما اتنين بيساوي سيجما تلاتة بيساوي
+
+255
+00:21:12,270 --> 00:21:17,210
+صفر معناته ال U distortion for a tensile specimen
+
+256
+00:21:17,210 --> 00:21:22,450
+اللي هو خلينا نحكي ال yielding UY
+
+257
+00:21:24,180 --> 00:21:32,320
+سأحوض واحد زائد new ع تلاتة اي في ستكون هذه صفر
+
+258
+00:21:32,320 --> 00:21:43,060
+صفر و صفر يعني ستكون عندهين sigma
+
+259
+00:21:43,060 --> 00:21:47,140
+واحد sigma
+
+260
+00:21:47,140 --> 00:21:52,920
+واحد تربيع sigma
+
+261
+00:21:52,920 --> 00:22:03,910
+واحدتربيع اللي هي هذه زي ال sigma واحد تربيع
+
+262
+00:22:03,910 --> 00:22:13,130
+على اتنين لأنها تكون تساوي واحد زي ال U ع تلاتة A
+
+263
+00:22:13,130 --> 00:22:19,190
+في sigma واحد تربيع
+
+264
+00:22:27,350 --> 00:22:31,110
+و ال tensile test specimen yields لما sigma 1 سوى
+
+265
+00:22:31,110 --> 00:22:38,010
+sigma Sy يعني ال U ال yielding for a tensile test
+
+266
+00:22:38,010 --> 00:22:44,910
+specimen هتكون واحد زاد ال U في Sy تربية على تلاتة
+
+267
+00:22:44,910 --> 00:22:50,850
+ايه ال distortion اللي بيحكي بيصير failure او
+
+268
+00:22:50,850 --> 00:22:53,270
+بيصير yielding لما
+
+269
+00:22:55,850 --> 00:22:58,670
+لما ال U distortion لل mechanical element تحت
+
+270
+00:22:58,670 --> 00:23:03,830
+الدراسة يكون أكبر أو يساوي ال U distortion for a
+
+271
+00:23:03,830 --> 00:23:09,890
+tensile test specimen يعني هتكون U distortion اللي
+
+272
+00:23:09,890 --> 00:23:14,230
+هي ..
+
+273
+00:23:14,230 --> 00:23:19,870
+اللي هي .. اللي هي هذه المعادلة اللي هي واحد زائد
+
+274
+00:23:19,870 --> 00:23:27,040
+U ع تلاتة E فيسيجما واحد minus سيجما اتنين لكل
+
+275
+00:23:27,040 --> 00:23:33,560
+تربيع زي سيجما اتنين minus سيجما تلاتة لكل تربيع
+
+276
+00:23:33,560 --> 00:23:39,700
+زي سيجما تلاتة minus سيجما واحد لكل تربيع على
+
+277
+00:23:39,700 --> 00:23:54,870
+اتنين تكون اكبر او يساوي واحد زي نيوفي SY تربية ع
+
+278
+00:23:54,870 --> 00:24:03,770
+تلاتة اي يعني
+
+279
+00:24:03,770 --> 00:24:08,230
+هيروح عندهين واحد زائد نيو واحد زائد نيو و تلاتة
+
+280
+00:24:08,230 --> 00:24:15,690
+اي مع تلاتة اي يعني بيصير failureلما سجم واحد
+
+281
+00:24:15,690 --> 00:24:22,630
+minus سجم اتنين الكل تربية زي سجم اتنين minus سجم
+
+282
+00:24:22,630 --> 00:24:26,890
+اتلات الكل تربية زي سجم اتلات minus سجم واحد الكل
+
+283
+00:24:26,890 --> 00:24:31,890
+تربية على اتنين
+
+284
+00:24:31,890 --> 00:24:42,070
+طبعا هذا كل اص نص الكل اص نص يكون اكبر او يساوي as
+
+285
+00:24:42,070 --> 00:24:47,710
+yمعناته ال distortion theory predicts failure لما
+
+286
+00:24:47,710 --> 00:24:51,150
+distortion energy per unit volume of the
+
+287
+00:24:51,150 --> 00:24:55,230
+mechanical element under study exceeds the
+
+288
+00:24:55,230 --> 00:24:59,170
+distortion energy
+
+289
+00:24:59,170 --> 00:25:03,070
+of a tensile test specimen اللي هي هذه المعادلة
+
+290
+00:25:03,070 --> 00:25:05,930
+sigma 1 معناه sigma 2 الكل تربيع زي sigma 2 معناه
+
+291
+00:25:05,930 --> 00:25:09,070
+sigma 3 الكل تربيع زي sigma 3 معناه sigma 1 الكل
+
+292
+00:25:09,070 --> 00:25:11,930
+تربيع على 2 نقص نص أكبر يستوي S Y
+
+293
+00:25:15,860 --> 00:25:21,920
+الان ممكن اعرف ال term هذا واحد اسمه Von Mises سمى
+
+294
+00:25:21,920 --> 00:25:26,720
+كل term هذا سمى sigma prime او von Mises stress
+
+295
+00:25:26,720 --> 00:25:34,560
+هذا ال term هذا كله sigma prime يعني ممكن احكي ال
+
+296
+00:25:34,560 --> 00:25:38,260
+distortion energy theory صياغة تانية لما ال von
+
+297
+00:25:38,260 --> 00:25:41,240
+Mises stress اللي هو sigma prime exceeds ال yield
+
+298
+00:25:41,240 --> 00:25:47,060
+strength yielding beginsيعني yielding لما ال sigma
+
+299
+00:25:47,060 --> 00:25:51,560
+prime أكبر أو يساوي as y اللي هو ال sigma prime
+
+300
+00:25:51,560 --> 00:25:54,260
+اللي هي ال von meissens stress اللي هو معطوب
+
+301
+00:25:54,260 --> 00:25:55,960
+العلاقة هذه ال von meissens stress اللي هو sigma
+
+302
+00:25:55,960 --> 00:25:58,380
+واحد معناه sigma اتنين لكل تربيع زي sigma اتنين
+
+303
+00:25:58,380 --> 00:26:01,420
+معناه sigma تلاته لكل تربيع زي sigma تلاته معناه
+
+304
+00:26:01,420 --> 00:26:03,900
+sigma واحد لكل تربيع على اتنين اقصد نص هذا هو
+
+305
+00:26:03,900 --> 00:26:09,040
+sigma prime او ال von meissens stress for a plain
+
+306
+00:26:09,040 --> 00:26:12,780
+state of stress هيكون واحد من stress بيساوي صفر
+
+307
+00:26:12,780 --> 00:26:18,030
+يعني لو هذا هذا هيكون صفرهذا سفر بتصف ال volume
+
+308
+00:26:18,030 --> 00:26:21,170
+minus stress sigma prime بسهولة sigma a تربية بقى
+
+309
+00:26:21,170 --> 00:26:24,350
+انا sigma a sigma b زي انا sigma b تربية الكل مصد
+
+310
+00:26:24,350 --> 00:26:30,550
+نصإذا انت ممكن تحصل stress مباشرة بدون ما تحصل ال
+
+311
+00:26:30,550 --> 00:26:34,250
+principle stress بس انا بفضل احسب ال principle
+
+312
+00:26:34,250 --> 00:26:38,510
+stress بعدين احصل stress من المعادلة هذه باستخدام
+
+313
+00:26:38,510 --> 00:26:43,150
+ال principle stress لكن ممكن إذا انت تاخد ال
+
+314
+00:26:43,150 --> 00:26:46,710
+stress element الأصلي اللي بيكون فيه sigma x sigma
+
+315
+00:26:46,710 --> 00:26:52,170
+y sigma z tau xy tau xz tau yz و أحسب stress من
+
+316
+00:26:52,170 --> 00:26:58,220
+هذه المعادلةرياضية المعادلة هذه نفس المعادلة هذه
+
+317
+00:26:58,220 --> 00:26:59,160
+تماما
+
+318
+00:27:07,910 --> 00:27:12,150
+Volmeis stress is a single effective stress for
+
+319
+00:27:12,150 --> 00:27:14,570
+the entire general state of stress in a stress
+
+320
+00:27:14,570 --> 00:27:20,470
+.معناة volmeis stress هو مثلة stress كيما واحدة
+
+321
+00:27:20,470 --> 00:27:25,870
+بتمثل المجموع العام لل state of stress for a
+
+322
+00:27:25,870 --> 00:27:27,390
+mechanical element under stress
+
+323
+00:27:30,420 --> 00:27:34,840
+أحنا في ال distortion energy theory ببساطة بتقارن
+
+324
+00:27:34,840 --> 00:27:36,420
+ال volume minus ال stress مع ال yielding strength
+
+325
+00:27:36,420 --> 00:27:39,040
+إذا كان ال volume minus ال stress أكبر بيستوى ال
+
+326
+00:27:39,040 --> 00:27:44,620
+SY ال yielding begins if I incorporate a factor of
+
+327
+00:27:44,620 --> 00:27:52,960
+safety بيستوى sigma prime بيستوى SY على N طبعا
+
+328
+00:27:52,960 --> 00:27:56,780
+لو أخدت 2D state of stress هيكون دي sigma prime
+
+329
+00:28:01,240 --> 00:28:10,140
+for a 2D state of stress ناخدها كحالة دراسية سيكون
+
+330
+00:28:10,140 --> 00:28:16,720
+لدي ال sigma prime بالساوية sigma a تربيع زائد
+
+331
+00:28:16,720 --> 00:28:22,520
+sigma a sigma b زائد sigma b تربيع اصل نص اللي هي
+
+332
+00:28:22,520 --> 00:28:30,020
+المعادلة هذه او هي minus هنا هذه minus
+
+333
+00:28:38,570 --> 00:28:46,230
+هذه المعادلة إذا ترجع لرياضيات لل calculus هذه
+
+334
+00:28:46,230 --> 00:28:53,190
+معادلة ellipse مائل بزاوية 45 يعني عندك هاي ال X و
+
+335
+00:28:53,190 --> 00:29:01,670
+هاي ال Y هذا بزاوية 45 درجة هذا هو ال ellipse
+
+336
+00:29:05,090 --> 00:29:12,050
+هذه معادلة اللبس مائل بزاوية 45 درجة الان
+
+337
+00:29:12,050 --> 00:29:21,350
+لدي هنا sigma 1 على SY هنا sigma 2 على SY وهذا ال
+
+338
+00:29:21,350 --> 00:29:27,340
+failure contourوهذه الـ Experimental Data لحظة الـ
+
+339
+00:29:27,340 --> 00:29:34,600
+Distortion Energy Theory تتوقع
+
+340
+00:29:34,600 --> 00:29:40,610
+الحقيقةلكن ال maximum shear stress theory it
+
+341
+00:29:40,610 --> 00:29:45,230
+predicts failure before failure actually happens
+
+342
+00:29:45,230 --> 00:29:49,430
+بتتوقع الفيلير و لسه ماصارش failure اللي هي ال
+
+343
+00:29:49,430 --> 00:29:52,010
+maximum shear stress theory لكن ال distortion
+
+344
+00:29:52,010 --> 00:29:57,030
+energy theory predicts failure accurately يعني فيه
+
+345
+00:29:57,030 --> 00:30:01,170
+دقة معناتهالدقة في حالة distortion energy theory
+
+346
+00:30:01,170 --> 00:30:06,990
+أعلى لكنها less conservative يعني أنصر المخاطرة في
+
+347
+00:30:06,990 --> 00:30:11,830
+الحسابات عليك كمصمم بيكون ايش؟ أعلى في حالة
+
+348
+00:30:11,830 --> 00:30:15,390
+distortion energy theory لكنه بده انا عشان اوفر
+
+349
+00:30:15,390 --> 00:30:19,610
+materialفي حالة ال mass production بفضل استخدام
+
+350
+00:30:19,610 --> 00:30:22,650
+distortion energy theory او Von Mises معظم ال
+
+351
+00:30:22,650 --> 00:30:26,710
+software زي ال .. ال ansys abacus ال .. ال حتة ال
+
+352
+00:30:26,710 --> 00:30:30,430
+solid work لما تعمل finite element analysis و تعمل
+
+353
+00:30:30,430 --> 00:30:34,190
+stress contour بيحسب ال Von Mises stress طبعا انت
+
+354
+00:30:34,190 --> 00:30:36,390
+مخير تحكيله انا بدي استخدم ال maximum shear stress
+
+355
+00:30:36,390 --> 00:30:40,230
+theory بس ال default عنده بيستخدم ال distortion
+
+356
+00:30:40,230 --> 00:30:41,550
+energy theory
+
+357
+00:30:59,510 --> 00:31:06,450
+طيب لان هنشوف ال shear strength predictions كيف
+
+358
+00:31:06,450 --> 00:31:11,050
+نتوقع ال shear strength ل material طبقا ل maximum
+
+359
+00:31:11,050 --> 00:31:14,290
+shear strength theory و طبقا ل distortion energy
+
+360
+00:31:14,290 --> 00:31:18,990
+theory اذا خدت انا mechanical element و عملت عليه
+
+361
+00:31:19,860 --> 00:31:24,280
+Torsion دلت ازود تورك تورك لحد ما صار failure او
+
+362
+00:31:24,280 --> 00:31:30,880
+صار yielding الان ال stress element فى 2D هكون 2D
+
+363
+00:31:30,880 --> 00:31:37,100
+stress element هكون عندى
+
+364
+00:31:37,100 --> 00:31:45,780
+tau هكون more circle بالشكل هذا more circle هذا ال
+
+365
+00:31:45,780 --> 00:31:56,490
+sigma واحدهذه سيجما اتنين وهذه تاو ماكس
+
+366
+00:31:56,490 --> 00:32:03,630
+تاو ماكس ستكون تساوي سيجما واحد بالساوي سالب سيجما
+
+367
+00:32:03,630 --> 00:32:09,390
+اتنين يعني سيجما واحد موجب وسيجما اتنين سالبة
+
+368
+00:32:09,390 --> 00:32:13,850
+معناته
+
+369
+00:32:13,850 --> 00:32:15,610
+انا عندي هنا سيجما A
+
+370
+00:32:18,580 --> 00:32:25,200
+وهنا عنده sigma b في
+
+371
+00:32:25,200 --> 00:32:30,540
+حالة ال maximum shear stress theory هاي
+
+372
+00:32:30,540 --> 00:32:40,180
+ال maximum shear stress theory و
+
+373
+00:32:40,180 --> 00:32:47,260
+أخدتmechanical element that is under pure torsion
+
+374
+00:32:47,260 --> 00:32:54,940
+لحد الفيلير ال load line هيكون بشكل هذا هذا ال
+
+375
+00:32:54,940 --> 00:33:06,400
+load line at
+
+376
+00:33:06,400 --> 00:33:06,880
+failure
+
+377
+00:33:11,480 --> 00:33:19,460
+هذه النقطة هذه نقطة ال failure هذه failure point
+
+378
+00:33:19,460 --> 00:33:28,120
+احنا واضح انه يعني انا هنا عندي sigma a او sigma b
+
+379
+00:33:28,120 --> 00:33:35,060
+انا واضح في الرابع الرابع عندي يعني sigma a
+
+380
+00:33:38,840 --> 00:33:45,240
+أكبر أو يساوي sigma b لأن sigma a أكبر أو يساوي
+
+381
+00:33:45,240 --> 00:33:51,000
+صفر و الصفر أكبر أو يساوي sigma b معناته هذه تمثل
+
+382
+00:33:51,000 --> 00:33:57,120
+sigma واحد هذه sigma اتنين وهذه sigma تلاتة معناته
+
+383
+00:33:57,120 --> 00:34:05,960
+تاوم ماكسيم ماكسيمان أكبر ساوية sigma واحد minus
+
+384
+00:34:05,960 --> 00:34:18,350
+sigma تلاتة علىعلى اتنين هيساوي
+
+385
+00:34:18,350 --> 00:34:23,890
+سيجمه واحد minus سيجمه تانى بيساوي minus سيجمه
+
+386
+00:34:23,890 --> 00:34:34,530
+واحد على اتنين يعني بيساوي سيجمه واحد to max ال
+
+387
+00:34:34,530 --> 00:34:40,390
+yielding ال yieldingأنا عندى هنا سيكون عندى sigma
+
+388
+00:34:40,390 --> 00:34:52,710
+a sigma a minus sigma b أكبر أو يساوي ايش S Y هنا
+
+389
+00:34:52,710 --> 00:35:00,910
+عند ال yielding هل بسميها S
+
+390
+00:35:00,910 --> 00:35:09,410
+S Y اللي هي yielding strength and shearوهذه as y
+
+391
+00:35:09,410 --> 00:35:17,950
+وهنا حكينا هذه sigma a وهذه minus sigma a من تشابه
+
+392
+00:35:17,950 --> 00:35:24,410
+المثلثات او معادلة الخط هذا المستقيم معادلة الخط
+
+393
+00:35:24,410 --> 00:35:29,550
+المستقيم هذا عبارة عن sigma b هذا الخط ال load
+
+394
+00:35:29,550 --> 00:35:34,150
+line equation
+
+395
+00:35:36,020 --> 00:35:43,520
+اللي هتكون عند سيجما بي بصوا minus sigma a هذه
+
+396
+00:35:43,520 --> 00:35:50,720
+معادلة معادلة الخط التاني في تلت نقاط SY و صفر
+
+397
+00:35:50,720 --> 00:35:55,220
+وعند
+
+398
+00:35:55,220 --> 00:36:03,020
+صفر و minus SY عند نقطة هنا اللي
+
+399
+00:36:03,020 --> 00:36:03,320
+هي
+
+400
+00:36:07,020 --> 00:36:16,220
+بدي أسميها SSY SSY
+
+401
+00:36:16,220 --> 00:36:25,520
+و SSY ال slope بتاع الخط هذا هيكون عنده
+
+402
+00:36:25,520 --> 00:36:31,860
+ال load on sigma A بيستوى minus sigma B النقطة
+
+403
+00:36:31,860 --> 00:36:41,080
+هادةat point a بيكون
+
+404
+00:36:41,080 --> 00:36:51,020
+عندى sigma b minus sigma a بيكون as as y اللي عملت
+
+405
+00:36:51,020 --> 00:36:56,380
+شغل مثلثات بتطلع as as y بتطلع
+
+406
+00:36:56,380 --> 00:37:01,920
+سوى نص as y معناته ال maximum shear stress theory
+
+407
+00:37:01,920 --> 00:37:07,830
+predictsال yield strength in shear according to
+
+408
+00:37:07,830 --> 00:37:10,230
+this equation as as why بتستوى نص ال yield
+
+409
+00:37:10,230 --> 00:37:13,730
+strength معناته ال yield strength in shear
+
+410
+00:37:13,730 --> 00:37:18,970
+according to maximum shear stress theory بتستوى نص
+
+411
+00:37:18,970 --> 00:37:25,010
+as why معناته انا ممكن اعبر عن ال failure ال
+
+412
+00:37:25,010 --> 00:37:28,270
+failure according to maximum shear stress I بحكي
+
+413
+00:37:28,270 --> 00:37:31,390
+انه failure according according
+
+414
+00:37:34,230 --> 00:37:41,910
+to maximum shear stress theory failure occurs
+
+415
+00:37:41,910 --> 00:37:52,630
+when tau maximum أكبر أو يساوي SSY هذا according
+
+416
+00:37:52,630 --> 00:37:57,650
+to maximum shear stress theory اللي هو SSY بيساوي
+
+417
+00:37:57,650 --> 00:38:04,480
+نص SSY هذا في حالةالـ maximum shear stress theory
+
+418
+00:38:04,480 --> 00:38:10,040
+بنفس الأسلوب في حالة ال distortion energy theory
+
+419
+00:38:10,040 --> 00:38:18,500
+هذا هو ال load line هذا ال load line for a pure
+
+420
+00:38:18,500 --> 00:38:24,460
+shear load line عندي هنا S Y وهنا عندي Sigma B
+
+421
+00:38:24,460 --> 00:38:30,310
+وهنا S Yلأن according to distortion اللي بيصير
+
+422
+00:38:30,310 --> 00:38:38,090
+failure لما هذا ال stress condition هذه النقطة او
+
+423
+00:38:38,090 --> 00:38:41,110
+ال loading ال load condition هي هذه هذه sigma a
+
+424
+00:38:41,110 --> 00:38:50,470
+sigma a وهذه minus sigma a الآن هذه النقطة وقعت
+
+425
+00:38:50,470 --> 00:38:55,630
+تتقاطع خط مستقيم ميل بزاوية سالب خمسة واربعين
+
+426
+00:38:55,630 --> 00:38:59,690
+وتقاطع اللبسيعني لو سوين ال equation بتاعة ال
+
+427
+00:38:59,690 --> 00:39:02,150
+ellipse with equation of load line at this point
+
+428
+00:39:02,150 --> 00:39:08,610
+بيطلع عند ال S S Y بيطلع بوند خمسة سبعة سبعة S Y
+
+429
+00:39:08,610 --> 00:39:14,790
+بوند خمسة سبعة سبعة S Y هذا في حال distortion
+
+430
+00:39:14,790 --> 00:39:19,170
+theory بقى أنا ممكن أعبر عن distortion theory
+
+431
+00:39:19,170 --> 00:39:24,130
+بطريقة تانية أحكي والله according to according to
+
+432
+00:39:29,050 --> 00:39:34,610
+distortion energy theory failure occurs
+
+433
+00:39:34,610 --> 00:39:46,860
+when tau maximum أكبر أو يساوي SSY يعنيأنا وحدت
+
+434
+00:39:46,860 --> 00:39:51,440
+نفس المفهوم في حالة two theories .. في حالة two
+
+435
+00:39:51,440 --> 00:39:57,800
+theories بس بختلف تعريف ال S S Y في حالة maximum
+
+436
+00:39:57,800 --> 00:40:02,620
+share of the state بيسوا point five S .. بيسوا
+
+437
+00:40:02,620 --> 00:40:06,570
+point five S Yفي حال تدل ال sociology theory بتكون
+
+438
+00:40:06,570 --> 00:40:11,570
+الtaa ال sxy بيساوون خمسة سبعة سبعة s y يعني اذا
+
+439
+00:40:11,570 --> 00:40:14,890
+كانت الtaa maximum بيساوي اكبر او بيساوي s y
+
+440
+00:40:14,890 --> 00:40:18,150
+والtaa maximum انا من ال more circle بحسب ال sigma
+
+441
+00:40:18,150 --> 00:40:20,770
+واحد و sigma اتنين و sigma تلاتة و برتبهم بحيث
+
+442
+00:40:20,770 --> 00:40:24,290
+sigma واحد اكبر من sigma اتنين اكبر من sigma تلاتة
+
+443
+00:40:24,290 --> 00:40:26,930
+و بعدين احكي الtaa maximum بالساوية
+
+444
+00:40:30,470 --> 00:40:37,590
+بستوى سيجما واحد minus سيجما تلاتة على اتنين ممكن
+
+445
+00:40:37,590 --> 00:40:40,150
+اعبر
+
+446
+00:40:42,400 --> 00:40:45,720
+عن ال failure طبقا لل maximum shear stress theory
+
+447
+00:40:45,720 --> 00:40:49,640
+او طبقا لل distortion theory بنفس الشكل بس باختلاف
+
+448
+00:40:49,640 --> 00:40:53,700
+التفاصيل يعني احكي انه failure according to
+
+449
+00:40:53,700 --> 00:40:57,680
+maximum shear stress theory happens لما tau
+
+450
+00:40:57,680 --> 00:41:01,680
+maximum تكون اكبر او يساوي as y as as y اللي هي
+
+451
+00:41:01,680 --> 00:41:04,960
+yield strength in shear وبرضه ممكن اعبر عن ال
+
+452
+00:41:04,960 --> 00:41:08,450
+failure according toالـ distortion energy theory
+
+453
+00:41:08,450 --> 00:41:11,750
+بحكي اللي هو بيصير failure لما ال tau maximum تكون
+
+454
+00:41:11,750 --> 00:41:15,570
+برضه أكبر أو يساوي SSY اللي بيختلف ال definition
+
+455
+00:41:15,570 --> 00:41:19,690
+تاع SSY ال SSY في حالة ال maximum shear stress
+
+456
+00:41:19,690 --> 00:41:24,170
+theory بيساوي bond 5SY في حالة ال distortion
+
+457
+00:41:24,170 --> 00:41:29,270
+energy theory بيساوي bond 577SY
+
+458
+00:41:31,410 --> 00:41:36,090
+هذا مهم كتير لأنه بسهل حل و فهم المسائل بشكل أعمق
+
+459
+00:41:36,090 --> 00:41:40,950
+نشوف مثال
+
+460
+00:41:40,950 --> 00:41:52,230
+هذا
+
+461
+00:41:52,230 --> 00:41:58,350
+المثال هكون مثال حسابينعتبره تدريب على استخدام او
+
+462
+00:41:58,350 --> 00:42:05,990
+يعني زي calculation exercise a hot rolled steel
+
+463
+00:42:05,990 --> 00:42:10,490
+has a yield strength of S Y T بساوي S Y C بساوي
+
+464
+00:42:10,490 --> 00:42:14,070
+one hundred kilo pound per square inch يعني hot
+
+465
+00:42:14,070 --> 00:42:18,330
+rolled steel yield strength S Y T yield strength
+
+466
+00:42:18,330 --> 00:42:21,330
+in tension بساوي yield strength in compression
+
+467
+00:42:21,330 --> 00:42:26,000
+بساوي مية kilo poundper square inch و هسميه as
+
+468
+00:42:26,000 --> 00:42:31,920
+well لأنهم متساويين and a true strain at a
+
+469
+00:42:31,920 --> 00:42:36,500
+fracture epsilon f بالساعة
+
+470
+00:42:36,500 --> 00:42:43,120
+point خمسة خمسة هذا أكبر من ايش point
+
+471
+00:42:43,120 --> 00:42:50,440
+او خمسة معناته المادة الشمالها duck tile duck tile
+
+472
+00:42:50,440 --> 00:42:55,550
+materialestimate the factor of safety for the
+
+473
+00:42:55,550 --> 00:42:59,010
+following principal stress states احسب ال factor
+
+474
+00:42:59,010 --> 00:43:05,030
+of safety للحالات التالية a sigma
+
+475
+00:43:05,030 --> 00:43:11,910
+x بالساوية سبعين kilo pound per square inch و
+
+476
+00:43:11,910 --> 00:43:22,090
+sigma y بالساوية سبعين kilo pound per square inchو
+
+477
+00:43:22,090 --> 00:43:27,430
+τاو اكس واي بالثاوزيرو اوتوماتيك لما نطلع حالة
+
+478
+00:43:27,430 --> 00:43:34,990
+الشير stress بالثاوز سفر معناته هدول بيمثل ايش؟
+
+479
+00:43:34,990 --> 00:43:38,490
+principal stresses عند ال principal planes بيكونش
+
+480
+00:43:38,490 --> 00:43:42,150
+فيه شير ففي الشي ده يعمل calculation على طول سيجما
+
+481
+00:43:42,150 --> 00:43:46,930
+واحد في الحالة دي سيجما واحد because لأنه
+
+482
+00:43:49,530 --> 00:43:56,410
+tau xy بالساوية 0 ما أن sigma x and sigma y are
+
+483
+00:43:56,410 --> 00:44:00,910
+principal stresses
+
+484
+00:44:00,910 --> 00:44:08,330
+معناته sigma 1 بالساوية 70 kilo pound per square
+
+485
+00:44:08,330 --> 00:44:12,850
+inch و sigma 2 بالساوية برضه 70 kilo pound per
+
+486
+00:44:12,850 --> 00:44:20,090
+square inch و sigma 3 بالساوية حالها دياشر سفرلأن
+
+487
+00:44:20,090 --> 00:44:24,590
+في عندى حلتين بتستخدم مرة ال maximum shear stress
+
+488
+00:44:24,590 --> 00:44:28,670
+theory ومرة اللى هى distortion energy theory
+
+489
+00:44:28,670 --> 00:44:33,970
+according
+
+490
+00:44:33,970 --> 00:44:37,850
+to maximum shear stress theory بتحكى بيصير failure
+
+491
+00:44:37,850 --> 00:44:39,010
+لما ال tau maximum
+
+492
+00:44:45,170 --> 00:44:54,010
+أكبر هو يساوي SSY أو بيساوي SSY على N يعني
+
+493
+00:44:54,010 --> 00:45:03,210
+N هتساوي SSY على TAU maximum و ال SSY في حالة
+
+494
+00:45:03,210 --> 00:45:08,970
+maximum shear stress theory بيساوي نص ال SY اللي
+
+495
+00:45:08,970 --> 00:45:15,560
+هي نص في أكام فمية نصفي مية بيطلع خمسين kilo pound
+
+496
+00:45:15,560 --> 00:45:20,140
+per square inch طيب
+
+497
+00:45:20,140 --> 00:45:28,140
+ال tau maximum بيساوي sigma واحد minus sigma تلاتة
+
+498
+00:45:28,140 --> 00:45:35,120
+على اتنين يعني هتكون سبعين ناقص سفر على اتنين خمسة
+
+499
+00:45:35,120 --> 00:45:39,420
+و تلاتين kilo pound per square inch معناه تلان
+
+500
+00:45:40,920 --> 00:45:48,920
+هتكون تساوي الـ SSY اللي هي .. اللي هي خمسين على
+
+501
+00:45:48,920 --> 00:45:55,620
+خمسة و تلاتين خمسين
+
+502
+00:45:55,620 --> 00:45:59,820
+تقسيم خمسة و تلاتين بتطلع one point four three one
+
+503
+00:45:59,820 --> 00:46:04,940
+point four three هذا في حالة ال distortion theory
+
+504
+00:46:06,790 --> 00:46:09,450
+في حالة .. في حالة ال maximum series .. في حالة
+
+505
+00:46:09,450 --> 00:46:14,730
+distortion energy theory بيصير failure لما tau
+
+506
+00:46:14,730 --> 00:46:18,530
+maximum تكون
+
+507
+00:46:18,530 --> 00:46:23,570
+أكبر بيستوي SSY أو tau maximum بيستوي SSY على N
+
+508
+00:46:23,570 --> 00:46:35,150
+يعني N بتساوي SSY على tau maximum طيب ال SSY ايش
+
+509
+00:46:35,150 --> 00:46:40,250
+بتساوي؟في حالتي distortion energy بتسوي point خمسة
+
+510
+00:46:40,250 --> 00:46:51,590
+سبعة سبعة أسواي يعني هتسوي point خمسة سبعة سبعة في
+
+511
+00:46:51,590 --> 00:46:57,730
+أسواي اللي هي مية يعني هتسوي سبعة خمسين point سبعة
+
+512
+00:46:57,730 --> 00:47:01,570
+كيلو pound per square inch هذا according to
+
+513
+00:47:01,570 --> 00:47:05,010
+distortion energy theory
+
+514
+00:47:10,930 --> 00:47:14,910
+طيب و ال tau maximum already حسبناها ال tau
+
+515
+00:47:14,910 --> 00:47:19,870
+maximum بتساوي
+
+516
+00:47:19,870 --> 00:47:27,610
+عليها خمسة و تلاتين يعني هين هتكون اللي هي سبعة و
+
+517
+00:47:27,610 --> 00:47:37,270
+خمسين point سبعة على tau maximum اللي هي خمسة و
+
+518
+00:47:37,270 --> 00:47:43,020
+تلاتينيعني بيطلع ال factor of safety اللي هو سبعة
+
+519
+00:47:43,020 --> 00:47:48,540
+خمسين point سبعة تقسيم خمسة و تلاتين بيطلع واحد
+
+520
+00:47:48,540 --> 00:47:54,320
+point ستة خمسة لاحظوا
+
+521
+00:47:54,320 --> 00:47:58,240
+ال margin of safety في حد distortion energy theory
+
+522
+00:47:58,240 --> 00:48:01,520
+أعلى من ال maximum shear stress theory لأن احنا
+
+523
+00:48:01,520 --> 00:48:05,780
+بداية حكينا ان maximum shear stress theory gives
+
+524
+00:48:07,020 --> 00:48:10,440
+اللي هو more conservative results يعني وعنصر
+
+525
+00:48:10,440 --> 00:48:14,820
+المخاطر أقل بيحكيلك انه .. انه انا بحكيلك انه فيه
+
+526
+00:48:14,820 --> 00:48:19,160
+failure و لسه ماصارش failure هذه طلع ال factor of
+
+527
+00:48:19,160 --> 00:48:25,930
+safety أعلى لأنهit fits the experimental data أكتر
+
+528
+00:48:25,930 --> 00:48:30,730
+من ال maximum shear risk theory الآن طريقة حصة ال
+
+529
+00:48:30,730 --> 00:48:33,210
+factors safety باستخدام نفس المعادلة Tau maximum
+
+530
+00:48:33,210 --> 00:48:37,450
+سواء S أسواء على N وهن ال Tau maximum سواء S أسواء
+
+531
+00:48:37,450 --> 00:48:39,790
+على N نفس استخدامك بس اللي اختلف ال definition
+
+532
+00:48:39,790 --> 00:48:42,730
+بتاع S أسواء لكن لو أنا بدي أحسب ال volume of mice
+
+533
+00:48:42,730 --> 00:48:47,530
+stressلو دي حسب يعني هلاحظ .. هنصل لنفس .. نفس ..
+
+534
+00:48:47,530 --> 00:48:54,010
+نفس النتيجة sigma prime هتكون sigma a تربية minus
+
+535
+00:48:54,010 --> 00:49:00,010
+sigma a sigma b زائد sigma b تربية أس نص يعني
+
+536
+00:49:00,010 --> 00:49:03,810
+هتكون تستوى هذا .. هذا حل تاني sigma a اللي عندي
+
+537
+00:49:03,810 --> 00:49:09,410
+أكم اللي
+
+538
+00:49:09,410 --> 00:49:16,960
+هي سبعينتربيع ماينس سبعين في سبعين زائد سبعين
+
+539
+00:49:16,960 --> 00:49:22,440
+تربيع تطلعش سبعين كيلو pound per square inch هذا
+
+540
+00:49:22,440 --> 00:49:26,800
+sigma prime و
+
+541
+00:49:26,800 --> 00:49:28,820
+according to the stationary theory بيصير failure
+
+542
+00:49:28,820 --> 00:49:34,040
+لما sigma prime أكبر ويستوي as y يعني sigma prime
+
+543
+00:49:36,210 --> 00:49:44,710
+بالساوية as y على n يعني n بساوية as y على ال
+
+544
+00:49:44,710 --> 00:49:59,050
+sigma prime as y ال hand هي مية على سبعين مية
+
+545
+00:49:59,050 --> 00:50:04,570
+على سبعين سبعين تربيع سبعين سبعين اقصد نص
+
+546
+00:50:09,490 --> 00:50:18,290
+هيش غلط عندنا هنا sigma x نرجع
+
+547
+00:50:18,290 --> 00:50:32,210
+لمعادلة نظبط sigma prime بيستوى Sy على N اه
+
+548
+00:50:34,580 --> 00:50:37,920
+ف ال sigma prime بيستوى SY على N و ال N بيستوى SY
+
+549
+00:50:37,920 --> 00:50:44,440
+على sigma prime و منها بحسب اللي هو SY عند 100 و
+
+550
+00:50:44,440 --> 00:50:48,700
+ال sigma prime تطلع 70 100 على 70 المفروض تطلع
+
+551
+00:50:48,700 --> 00:51:00,380
+حسبوليها 100 قصيم 70 تطلع 1.43 طيب خنشوف مثال تاني
+
+552
+00:51:00,380 --> 00:51:03,120
+انحله
+
+553
+00:51:05,500 --> 00:51:10,580
+باستخدام اللي هي sigma prime مرة و مرة حلو
+
+554
+00:51:10,580 --> 00:51:22,700
+باستخدام اللي هي ال SSY لحظة
+
+555
+00:51:22,700 --> 00:51:29,640
+خليني ارجع لنفس السؤال نفس السؤال اوضح اذا كنت في
+
+556
+00:51:29,640 --> 00:51:33,580
+الربع التالت اذا كنت في الربع الرابع
+
+557
+00:51:36,730 --> 00:51:47,770
+if state of stress is in the fourth quadrant هذا
+
+558
+00:51:47,770 --> 00:51:52,610
+تصحيح لأن صار عندي خربش انا fourth quadrant معناته
+
+559
+00:51:52,610 --> 00:51:58,950
+sigma a أكبر أو يساوي الصفر أكبر أو يساوي ال sigma
+
+560
+00:51:58,950 --> 00:52:03,950
+b يعني واحد موجة و واحد سالب في الحالة هذه in this
+
+561
+00:52:03,950 --> 00:52:13,420
+caseبحكي أن الـ N بستواء SSY على TAU maximum هذا
+
+562
+00:52:13,420 --> 00:52:18,980
+في حالةالـ distortion energy theory وفي حالة ال
+
+563
+00:52:18,980 --> 00:52:22,600
+maximum shear stress theory لكن في حالة ال
+
+564
+00:52:22,600 --> 00:52:26,000
+distortion energy theory بتكون عند ال S S Y
+
+565
+00:52:26,000 --> 00:52:32,640
+بيسوابون خمسة سبعة سبعة S Y و ال S S Y في حالة ال
+
+566
+00:52:32,640 --> 00:52:36,440
+maximum shear stress theory بتكون سوابون مصر S Y
+
+567
+00:52:38,150 --> 00:52:43,250
+معناته الحل السابق ينطبق في ال fourth quadrant لكن
+
+568
+00:52:43,250 --> 00:52:48,010
+انا وين طلعت عندي sigma a موجبة و sigma b موجبة
+
+569
+00:52:48,010 --> 00:52:52,850
+انا في ال first quadrant معناته this is not valid
+
+570
+00:52:52,850 --> 00:53:01,070
+يعني if state of stress is
+
+571
+00:53:01,070 --> 00:53:06,330
+in the first quadrant
+
+572
+00:53:09,930 --> 00:53:15,770
+معناته بدنا نحكي في الحالة هاذي نحكي نحكي انه ال
+
+573
+00:53:15,770 --> 00:53:21,590
+sigma ال prime بيسوى S Y على N في حالة ال
+
+574
+00:53:21,590 --> 00:53:27,490
+distortion energy theory وفي
+
+575
+00:53:27,490 --> 00:53:30,250
+حالة ال maximum shear stress theory هنحكي انه ..
+
+576
+00:53:30,250 --> 00:53:42,790
+انه .. انه sigma A بيسوى S Yعلى n في حالة ال
+
+577
+00:53:42,790 --> 00:53:47,710
+maximum shear stress theory احنا في المسألة
+
+578
+00:53:47,710 --> 00:53:52,290
+السابقة احنا كنا في ال first quadrant معناته
+
+579
+00:53:52,290 --> 00:53:58,670
+مانفعش .. مانفعش استخدم المعادلة هذه في ال first
+
+580
+00:53:58,670 --> 00:54:06,090
+.. في ال first quadrant طيب نشوف مسألة تانية أو
+
+581
+00:54:06,090 --> 00:54:09,310
+فرعة تانية هذا للتوضيح
+
+582
+00:54:16,250 --> 00:54:20,290
+نشوف حالة تانية بي عندي سيجما X بالساوية ستين
+
+583
+00:54:20,290 --> 00:54:26,050
+سيجما X بالساوية ستين kilo pound per square inch
+
+584
+00:54:26,050 --> 00:54:34,610
+وسيجما Y بالساوية اربعين kilo pound per square
+
+585
+00:54:34,610 --> 00:54:41,270
+inch وTau XY بالساوية ماينس خمستاشر kilo pound per
+
+586
+00:54:41,270 --> 00:54:45,950
+square inchأول الشيء مغادر نظرتي لازم اوجد ال
+
+587
+00:54:45,950 --> 00:54:51,110
+principal stresses find principal
+
+588
+00:54:51,110 --> 00:54:54,610
+stresses
+
+589
+00:54:54,610 --> 00:54:59,990
+يعني عندك توجد سجم واحد و سجم اتنين و سجم تلاتة
+
+590
+00:54:59,990 --> 00:55:06,070
+هنا طبعا هستخدم more circle more circle
+
+591
+00:55:13,760 --> 00:55:21,220
+أنا هستخدم عندي هنا هنا counter clockwise موجة
+
+592
+00:55:21,220 --> 00:55:26,860
+وهنا clockwise سالف معناته هتكون عندي هنا سيج ماكس
+
+593
+00:55:26,860 --> 00:55:30,620
+اللي هي ستين ستين وخمستاشر clockwise هتكون ستين
+
+594
+00:55:30,620 --> 00:55:37,440
+انا عندي عشرة عشرين تلاتين اربعين خمسين ستين هنا
+
+595
+00:55:37,440 --> 00:55:39,540
+عشرة عشرين
+
+596
+00:55:42,290 --> 00:55:50,950
+هذه عشرة عشرين تلاتين أربعين خمسين ستين هذا
+
+597
+00:55:50,950 --> 00:55:57,850
+أول نقطة اللي هي sigma X اللي هي ستين وخمستاش
+
+598
+00:55:57,850 --> 00:56:03,730
+clockwise سالب النقطة التانية اللي هي أربعين
+
+599
+00:56:03,730 --> 00:56:11,310
+أربعين هذه سالب عشرة سالب عشرين
+
+600
+00:56:18,320 --> 00:56:25,840
+هذه ستكون اربعين وخمستاش counter clockwise هوصل
+
+601
+00:56:25,840 --> 00:56:29,960
+بينهم و
+
+602
+00:56:29,960 --> 00:56:40,020
+ارسم more circle هذه
+
+603
+00:56:40,020 --> 00:56:47,690
+more circle معناته هذه ستكون sigma واحدو هاد ال
+
+604
+00:56:47,690 --> 00:56:56,770
+sigma 2 و هاد ال sigma 3 طيب هذا هو ال center هذا
+
+605
+00:56:56,770 --> 00:57:05,310
+ال center تعمار circle ال C بسوة
+
+606
+00:57:05,310 --> 00:57:13,890
+sigma X زي sigma Y على 2 اللي هي 60 زي 40على اتنين
+
+607
+00:57:13,890 --> 00:57:20,830
+اللي هو خمسين kilo pound per square inch هذه
+
+608
+00:57:20,830 --> 00:57:27,850
+المسافة هذه sigma
+
+609
+00:57:27,850 --> 00:57:36,190
+x او tau xy
+
+610
+00:57:47,560 --> 00:57:57,040
+وهذا sigma x minus sigma y على اتنين ال radius هذا
+
+611
+00:57:57,040 --> 00:58:03,260
+ال R ال radius بتاع مورسيا كله ال radius بالثواب
+
+612
+00:58:03,260 --> 00:58:08,720
+جزر التربيع ل sigma x minus sigma y على اتنين لكل
+
+613
+00:58:08,720 --> 00:58:15,280
+تربيع زي ال tau xy تربيع يعني هيكونالجزر التربيعى
+
+614
+00:58:15,280 --> 00:58:21,540
+ل سيجما اكس ستين ماينوس اربعين على اتنين لكل تربيع
+
+615
+00:58:21,540 --> 00:58:27,300
+زائد تاو اكس واي اللى هى خمستاش تربيع يعني هكون
+
+616
+00:58:27,300 --> 00:58:33,620
+عندى ستين نقص اربعين عشرين على اتنين عشرة ربعها
+
+617
+00:58:33,620 --> 00:58:36,660
+هكون عندى مية زائد متين وخمسة عشرين تلت مية وخمسة
+
+618
+00:58:36,660 --> 00:58:40,540
+وعشرين تلت مية وخمسة وعشرين تحت الجدر
+
+619
+00:58:50,450 --> 00:59:00,330
+تطلع تمانتاش point O تلاتة
+
+620
+00:59:00,330 --> 00:59:05,590
+kilo pound per square inch هذا ال radius سيجما
+
+621
+00:59:05,590 --> 00:59:13,790
+واحد هتكون ال C زاد ال radius ال C اللي هي خمسين
+
+622
+00:59:14,970 --> 00:59:19,590
+زائد تمانتاش point O تلاتة سواء تمانية ستين point
+
+623
+00:59:19,590 --> 00:59:24,530
+O تلاتة kilo pound per square inch و ال sigma
+
+624
+00:59:24,530 --> 00:59:31,430
+اتنين هتكون اللي هي C minus ال radius اللي هي
+
+625
+00:59:31,430 --> 00:59:36,670
+خمسين ناقص تمانتاش point O تلاتة خمسين ناقص
+
+626
+00:59:36,670 --> 00:59:40,350
+تمانتاش اتنين وتلاتين واحد تلاتين point تسعة سبعة
+
+627
+00:59:40,350 --> 00:59:46,010
+kilo pound per square inch هذا ال sigma اتنينو
+
+628
+00:59:46,010 --> 00:59:56,970
+سجبه تلاته هتكون تساوي سفر طيب
+
+629
+00:59:56,970 --> 01:00:02,410
+واضح
+
+630
+01:00:02,410 --> 01:00:08,040
+انهسيجما واحد موجب و سيجما اتنين موجب و سيجما
+
+631
+01:00:08,040 --> 01:00:11,460
+تلاتة سفر معناه ان انا في الربع الاول في الربع
+
+632
+01:00:11,460 --> 01:00:16,220
+الاول الان في حتة ال maximum shear stress theory
+
+633
+01:00:16,220 --> 01:00:22,780
+انا في ال first اكوادران عندي
+
+634
+01:00:22,780 --> 01:00:28,940
+سيجما A بتساوي تمانية و ستين point O تلاتة kilo
+
+635
+01:00:28,940 --> 01:00:33,960
+pound per square inch و سيجما Bبالساوية واحد
+
+636
+01:00:33,960 --> 01:00:37,960
+تلاتين point تسعة سبعة kilo pound per square inch
+
+637
+01:00:37,960 --> 01:00:41,380
+ال
+
+638
+01:00:41,380 --> 01:00:47,200
+factor of safety n في الحلقة ده هكون S y على sigma
+
+639
+01:00:47,200 --> 01:00:51,460
+a according to maximum shear stress theory ال S y
+
+640
+01:00:51,460 --> 01:00:56,040
+عندي مية على
+
+641
+01:00:56,040 --> 01:01:01,400
+تمانية و ستين point او تلاتة بطلع
+
+642
+01:01:07,120 --> 01:01:16,220
+مية تقسيم تمانية ستين point او تلاتة بيطلع one
+
+643
+01:01:16,220 --> 01:01:25,020
+point اربعة سبعة one point اربعة سبعة هذا طبقا لل
+
+644
+01:01:25,020 --> 01:01:30,400
+maximum shear stress theory طبقا لل distortion
+
+645
+01:01:30,400 --> 01:01:31,660
+energy theory
+
+646
+01:01:38,220 --> 01:01:42,060
+طبق الـ distortion energy theory بلزم نحسب ال
+
+647
+01:01:42,060 --> 01:01:49,280
+volume minus ال stress sigma prime بالساوية sigma
+
+648
+01:01:49,280 --> 01:01:57,540
+a تربية minus sigma a sigma b زي sigma b تربية اص
+
+649
+01:01:57,540 --> 01:02:05,940
+نص يعني حيث ساوية ال sigma a اللي هي 68 point O
+
+650
+01:02:05,940 --> 01:02:06,440
+تلاتة
+
+651
+01:02:22,770 --> 01:02:31,210
+الكل اص نص يعني
+
+652
+01:02:31,210 --> 01:02:50,050
+68.O3Square root لـ 68.03 تربيع زائد او ناقص 68.03
+
+653
+01:02:50,050 --> 01:02:58,570
+في 31.97 زائد 31.97 تربيع
+
+654
+01:03:01,150 --> 01:03:05,990
+يساوي بطلع تمانية و خمسين point تسعة خمسة تمانية و
+
+655
+01:03:05,990 --> 01:03:09,670
+خمسين point
+
+656
+01:03:09,670 --> 01:03:12,810
+تسعة خمسة kilo pound per square inch هذا ال sigma
+
+657
+01:03:12,810 --> 01:03:18,630
+prime according to max to distortion theory بيصير
+
+658
+01:03:18,630 --> 01:03:21,590
+failure لما ال sigma prime بيساوي SY يعني ال sigma
+
+659
+01:03:21,590 --> 01:03:30,370
+prime بيساوي SY على N يعني N هتساوي SYعلى sigma
+
+660
+01:03:30,370 --> 01:03:35,310
+prime أسوأ عندي مية على تمانية و خمسين bond تسعة
+
+661
+01:03:35,310 --> 01:03:42,050
+خمسة هيكون
+
+662
+01:03:42,050 --> 01:03:50,730
+عندي مية ع تبني بطلع ال factor of safety مية تقسيم
+
+663
+01:03:50,730 --> 01:03:57,230
+تمانية و خمسين bond تسعة خمسة بالساوية واحد bond
+
+664
+01:03:57,230 --> 01:03:59,230
+سبعة
+
+665
+01:04:02,390 --> 01:04:04,830
+واضح ال factor of safety في حالة ال distortion
+
+666
+01:04:04,830 --> 01:04:09,050
+energy theory اعلى منه في حالة ال maximum shear
+
+667
+01:04:09,050 --> 01:04:12,430
+stress theory لان احنا حكينا سابقا ان ال maximum
+
+668
+01:04:12,430 --> 01:04:14,910
+shear stress theory is more conservative than اللي
+
+669
+01:04:14,910 --> 01:04:19,970
+هو distortion energy theory خليني
+
+670
+01:04:19,970 --> 01:04:28,230
+بسحل كمان فرع للتوضيح لانه مهم جدا خليني اخد
+
+671
+01:04:28,230 --> 01:04:28,830
+الحالة
+
+672
+01:04:45,550 --> 01:04:55,310
+خناخد الحالة حالة تالتة سجما
+
+673
+01:04:55,310 --> 01:05:01,430
+واحد سجما
+
+674
+01:05:01,430 --> 01:05:07,290
+واحد بتساوي تلاتين kilo pound per square inch
+
+675
+01:05:07,290 --> 01:05:11,350
+وسجما
+
+676
+01:05:11,350 --> 01:05:14,310
+اتنين بتساوي برضه تلاتين
+
+677
+01:05:18,090 --> 01:05:28,730
+و سيجما تلاتة هذه
+
+678
+01:05:28,730 --> 01:05:31,430
+لاحظوا سيجما واحد بيساوي سيجما اتنين بيساوي سيجما
+
+679
+01:05:31,430 --> 01:05:35,950
+تلاتة ما انا حابب اتمثل هذه hydrostatic هذه
+
+680
+01:05:35,950 --> 01:05:48,050
+hydrostatic state of stressطبق لـ maximum shear
+
+681
+01:05:48,050 --> 01:05:51,330
+stress theory طبعا واضح هيطلع ال factor safety
+
+682
+01:05:51,330 --> 01:05:55,110
+بمقال انها infinity من غير حل يعنى هتكون يعني ال
+
+683
+01:05:55,110 --> 01:06:06,390
+tau max هيكون الساوي او هيكون
+
+684
+01:06:06,390 --> 01:06:13,850
+عندي اللي هو sigma 1 minus sigma 3 على 2 هيكون
+
+685
+01:06:13,850 --> 01:06:20,880
+ايه؟ شو الساوي؟بس الصفر يعني
+
+686
+01:06:20,880 --> 01:06:23,780
+انا لو بدى ارسمها هادى هتكون هادر سكستيتو استرس
+
+687
+01:06:23,780 --> 01:06:27,180
+هتكون
+
+688
+01:06:27,180 --> 01:06:31,800
+ال .. ال .. ال .. في حالة لو انا كنت في الرابع
+
+689
+01:06:31,800 --> 01:06:34,080
+الأول عندى سجن واحد سجن اتنين و سجن اتنين تلاتة و
+
+690
+01:06:34,080 --> 01:06:40,000
+ماقصدهم هتكون ساوى تلاتين ناقص تلاتين صفر
+
+691
+01:06:45,500 --> 01:06:54,180
+الان الان هيكون ال SSY على TAU MAX هيطلع ايش
+
+692
+01:06:54,180 --> 01:07:00,240
+Infinity تقسمها على صفر على اتنين هذه في حالة
+
+693
+01:07:00,240 --> 01:07:04,560
+distortion energy theory في حالة distortion energy
+
+694
+01:07:04,560 --> 01:07:12,640
+هيكون ال sigma prime بالساوية sigma واحد minus
+
+695
+01:07:12,640 --> 01:07:17,530
+sigma اتنين لكل تربيعزاية sigma 2 minus sigma 3
+
+696
+01:07:17,530 --> 01:07:22,630
+الكل تربية زاية sigma 3 minus sigma 1 الكل تربية
+
+697
+01:07:22,630 --> 01:07:27,770
+على 2 أص نص طبعا هذه بيستوى هذه، يعني عندما هذي
+
+698
+01:07:27,770 --> 01:07:34,850
+هستوى إيش؟ سفر وال factor of safety N بيستوى
+
+699
+01:07:34,850 --> 01:07:42,070
+اللي هو SY على sigma prime اللي هو هيكون SY على 0
+
+700
+01:07:42,070 --> 01:07:49,660
+infinityيعني بيكون infinity يعني very large state
+
+701
+01:07:49,660 --> 01:07:59,740
+of stress خليني ادحل حالة رقم .. رقم
+
+702
+01:07:59,740 --> 01:08:06,620
+C لأن فيها فكرة رقم C حالة رابعة
+
+703
+01:08:15,310 --> 01:08:22,350
+سيجما X هذه حالة تانتة أو رابعة سيجما X بالساوية
+
+704
+01:08:22,350 --> 01:08:30,430
+سفر
+
+705
+01:08:30,430 --> 01:08:34,630
+و
+
+706
+01:08:34,630 --> 01:08:39,930
+سيجما Y بالساوية أربعين و
+
+707
+01:08:39,930 --> 01:08:43,090
+تاو XY بالساوية خمسة وأربعين
+
+708
+01:08:48,910 --> 01:08:51,870
+أول اش طبعا هاجد ال principal stresses هرسم more
+
+709
+01:08:51,870 --> 01:09:01,690
+circle more circle اللي عند السفق عندها هي عشرة
+
+710
+01:09:01,690 --> 01:09:10,090
+عشرين تلاتين اربعين خمسين عشرة عشرين تلاتين اربعين
+
+711
+01:09:10,090 --> 01:09:18,090
+خمسين عندي عشرة عشرينتلاتين اربعين خمسين عند sigma
+
+712
+01:09:18,090 --> 01:09:23,210
+x صفر و tau x y خمس واربعين هي عشرة عشرين تلاتين
+
+713
+01:09:23,210 --> 01:09:29,390
+اربعين خمسين هي نقطة نقطة تانية عند اربعين عشر
+
+714
+01:09:29,390 --> 01:09:36,470
+عشرين تلاتين اربعين و سالب خمس واربعين عشرين
+
+715
+01:09:36,470 --> 01:09:41,590
+تلاتين اربعين سالب خمس واربعين معناته هوصل بينهم
+
+716
+01:09:44,680 --> 01:09:49,200
+وها دي more circle
+
+717
+01:09:49,200 --> 01:09:53,560
+طبعا ال center لأ ال center تعني more circle هاد
+
+718
+01:09:53,560 --> 01:09:58,400
+ال center C
+
+719
+01:09:58,400 --> 01:10:02,840
+هيساوة
+
+720
+01:10:02,840 --> 01:10:11,320
+sigma x زي sigma y على 2 يعني 0 زي 40 على 2
+
+721
+01:10:11,320 --> 01:10:17,120
+بالساوة 20 kilo pound per square inchهذه المسافة
+
+722
+01:10:17,120 --> 01:10:23,400
+عبارة عن sigma x من sigma y على اتنين يعني هذه
+
+723
+01:10:23,400 --> 01:10:32,440
+المسافة عبارة عن اربعين برضه عشرين وهذه عبارة عن
+
+724
+01:10:32,440 --> 01:10:37,720
+tau xy اللي هي خمسة واربعين معناه ت already أستعمر
+
+725
+01:10:37,720 --> 01:10:46,180
+circle R أستعمر جزر التربيهلعشرين تربيع زاد خمس و
+
+726
+01:10:46,180 --> 01:10:51,400
+أربعين تربيع عشرين تربيع زاد خمس و أربعين تربيع
+
+727
+01:10:51,400 --> 01:11:04,420
+بيطلع
+
+728
+01:11:04,420 --> 01:11:10,620
+تسعة و أربعين point اتنين اربعة تسعة و أربعين kilo
+
+729
+01:11:10,620 --> 01:11:16,370
+pound per square inchمعناته هذه سجما واحد هين في
+
+730
+01:11:16,370 --> 01:11:21,290
+المص صفر سجما اتنين وهين سجما تلاتة سجما واحد
+
+731
+01:11:21,290 --> 01:11:32,850
+هتكون تساوي C زائد R اللي عشرين زائد تسعة
+
+732
+01:11:32,850 --> 01:11:38,110
+واربعين سوى تسعة وستين pound اتنين اربعة kilo
+
+733
+01:11:38,110 --> 01:11:43,590
+pound per square inch وسجما اتنين صفرو ال sigma
+
+734
+01:11:43,590 --> 01:11:49,910
+تلاتة اللي هي c minus r اللي هي عشرين minus تسعة و
+
+735
+01:11:49,910 --> 01:11:55,170
+أربعين point اتنين اربعة يعني ال sigma تلاتة هتكون
+
+736
+01:11:55,170 --> 01:12:02,190
+تساوي سالب تسعة
+
+737
+01:12:02,190 --> 01:12:10,530
+و عشرين point اتنين اربعة kilo
+
+738
+01:12:10,530 --> 01:12:15,820
+poundParis Correction واضح انه عندي واحدة موجبة و
+
+739
+01:12:15,820 --> 01:12:19,400
+واحدة ايش سالبة معناته ان انا في انهيات ربع انا في
+
+740
+01:12:19,400 --> 01:12:23,020
+الرابع الرابع يعني لو رسمت ال load line المرة هذه
+
+741
+01:12:23,020 --> 01:12:27,740
+هرسم هي
+
+742
+01:12:27,740 --> 01:12:37,440
+ال sigma a و sigma b انا ال load line تبعي 69
+
+743
+01:12:37,440 --> 01:12:41,020
+و 9 سالب 29 يعني جاي ال load line بالشكل هذا
+
+744
+01:12:44,210 --> 01:12:49,030
+الان بده احكي هاد ال maximum shear stress theory
+
+745
+01:12:49,030 --> 01:12:57,170
+هاد
+
+746
+01:12:57,170 --> 01:13:00,090
+ال maximum shear stress theory و ال distortion
+
+747
+01:13:00,090 --> 01:13:01,650
+energy theory هتيجي بشكل هذا
+
+748
+01:13:13,290 --> 01:13:17,810
+هذه الأسود اللي هي ال maximum which هي ال stress
+
+749
+01:13:17,810 --> 01:13:22,550
+theory وهذه ال distortion energy theory هذه ال SY
+
+750
+01:13:22,550 --> 01:13:32,090
+اللي معطنية هي 100 وهنا 100 وهنا سالب 100 وهنا
+
+751
+01:13:32,090 --> 01:13:39,390
+سالب 100 ال load line بتاعي 69 هذه النفطة هذه
+
+752
+01:13:42,180 --> 01:13:53,040
+تسعة ستين واربع وعشرين وهذا سالب تسعة وعشرين واربع
+
+753
+01:13:53,040 --> 01:13:56,760
+وعشرين
+
+754
+01:13:56,760 --> 01:14:01,400
+الان
+
+755
+01:14:01,400 --> 01:14:07,160
+طبقا ل maximum shear stress theory maximum shear
+
+756
+01:14:07,160 --> 01:14:08,800
+stress theory هكون
+
+757
+01:14:10,970 --> 01:14:17,330
+سوى سيجما واحد مانس سيجما تلاتة على اتنين اللى
+
+758
+01:14:17,330 --> 01:14:22,790
+هتساوي ال radius هتساوي اللى هو ال radius بتاع مور
+
+759
+01:14:22,790 --> 01:14:28,410
+سيركل اللى هتكون تسعة و اربعين point اتنين اربعة
+
+760
+01:14:28,410 --> 01:14:38,210
+kilo pound per square inch ال
+
+761
+01:14:38,210 --> 01:14:45,740
+SSYبساوة نص ال S Y يعني هتكون خمسين كيلو pound per
+
+762
+01:14:45,740 --> 01:14:55,260
+square inch ال N بساوة S S Y على Tau Max ال S S Y
+
+763
+01:14:55,260 --> 01:15:02,080
+اللي هي خمسين على تسعة واربعين point اتنين اربع أو
+
+764
+01:15:02,080 --> 01:15:05,040
+almost واحد تقريبا خمسين
+
+765
+01:15:06,840 --> 01:15:10,480
+تقسيم تسعة واربعين point اتنين اربعة تقسيم تسعة
+
+766
+01:15:10,480 --> 01:15:12,280
+واربعين point اتنين اربعة تقسيم تسعة واربعين point
+
+767
+01:15:12,280 --> 01:15:14,400
+اتنين اربع تقسيم تسعة واربع تقسيم تسعة واربع تقسيم
+
+768
+01:15:14,400 --> 01:15:20,900
+تسعة واربع تقسيم تسعة واربع تقسيم تسعة واربع تقسيم
+
+769
+01:15:20,900 --> 01:15:23,680
+تسعة واربع تقسيم تسعة واربع تقسيم تسعة واربع تقسيم
+
+770
+01:15:23,680 --> 01:15:27,880
+تسعة واربع تقسيم تسعة واربع تقسيم تسعة واربع تقسيم
+
+771
+01:15:27,880 --> 01:15:34,840
+تسعة واربع تقسيم تسعة واربع تقسيم تسعة واربع تقسيم
+
+772
+01:15:34,840 --> 01:15:43,160
+تسعة واربسيجما ايه اللي هي تسعة وستين واربع وعشرين
+
+773
+01:15:43,160 --> 01:15:46,940
+minus
+
+774
+01:15:46,940 --> 01:15:53,000
+سيجما ايه اللي هي تسعة وستين واربع وعشرين فيه
+
+775
+01:15:53,000 --> 01:15:58,580
+سيجما بيه سالب تسعة وعشرين point اتنين اربع زائد
+
+776
+01:15:58,580 --> 01:16:04,160
+تسعة وعشرين point اتنين اربع تربيع لكل أص نص منها
+
+777
+01:16:04,160 --> 01:16:05,280
+بنحسب سيجما prime
+
+778
+01:16:08,080 --> 01:16:12,760
+اللي هتكون تسعة
+
+779
+01:16:12,760 --> 01:16:18,580
+و ستين point اتنين اربع تربيع زائد تسعة و ستين
+
+780
+01:16:18,580 --> 01:16:22,480
+point اتنين اربع في تسعة و عشرين point اتنين اربع
+
+781
+01:16:22,480 --> 01:16:28,720
+زائد تسعة و عشرين point اتنين اربع تربيع يساوي
+
+782
+01:16:28,720 --> 01:16:31,160
+تطلع سبعة و تمانين point ستة
+
+783
+01:16:38,540 --> 01:16:47,580
+الان حيكون متساوي SY على Sigma Prime SY اللي هي
+
+784
+01:16:47,580 --> 01:17:00,500
+مية على سبعة تمانين point ستة مية تطلع
+
+785
+01:17:00,500 --> 01:17:06,320
+one point واحد اربع اتنين
+
+786
+01:17:10,940 --> 01:17:14,000
+ممكن احكي برضه N في ال .. انا .. انا حاليا انا ..
+
+787
+01:17:14,000 --> 01:17:16,200
+انا في ال fourth quadrant انا في ال fourth
+
+788
+01:17:16,200 --> 01:17:21,280
+quadrant ممكن
+
+789
+01:17:21,280 --> 01:17:29,560
+احكي انه برضه ال N بالسواء SSY على tau max SSY
+
+790
+01:17:29,560 --> 01:17:36,660
+اللي هي خمسين ال
+
+791
+01:17:36,660 --> 01:17:38,400
+SSY في الحالة هتبقى ايش بالساوية؟
+
+792
+01:17:40,740 --> 01:17:44,200
+الاس اس واي في حدث torch energy theory اس اس واي
+
+793
+01:17:44,200 --> 01:17:50,080
+سبعة خمسة سبعة سبعة اس واي يعني هتكون سبعة وخمسين
+
+794
+01:17:50,080 --> 01:17:53,720
+بونت سبعة كيلو pound per square inch يعني هتكون اس
+
+795
+01:17:53,720 --> 01:17:57,940
+اس واي بالساوي سبعة وخمسين بونت سبعة على tau
+
+796
+01:17:57,940 --> 01:18:01,900
+maximum اللي هي حسبناها تسعة واربعين بونت اتنين
+
+797
+01:18:01,900 --> 01:18:03,620
+اربعة سبعة وخمسين
+
+798
+01:18:11,060 --> 01:18:23,300
+لا واحد point سبعة واحد طيب المحاضرة
+
+799
+01:18:23,300 --> 01:18:29,360
+الجاية بنكمل .. المحاضرة الجاية بنكمل بنحل مسائل
+
+800
+01:18:29,360 --> 01:18:34,760
+تانية او بنتعرف على new theory اللي هي more theory
+
+801
+01:18:34,760 --> 01:18:38,560
+و هنحل مسائل كلهم more theory
+
+802
+01:18:42,860 --> 01:18:47,120
+هنحل مسألة خمسة اتنين و خمسة تلاتة و خمسة أربعة
+
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@@ -0,0 +1,3110 @@
+
+1
+00:00:04,980 --> 00:00:08,020
+السلام عليكم ورحمة الله وبركاته، اليوم سنبدأ
+
+2
+00:00:08,020 --> 00:00:11,900
+الفصل الجديد الذي هو Fatigue failure resulting
+
+3
+00:00:11,900 --> 00:00:16,280
+from variable loading، الذي هو انهيارات أو فشل في
+
+4
+00:00:16,280 --> 00:00:21,240
+القطع الميكانيكية الناتجة عن الأحمال المتغيرة، في
+
+5
+00:00:21,240 --> 00:00:26,800
+الفصل الخامس غطينا الانهيارات في القطع الميكانيكية
+
+6
+00:00:26,800 --> 00:00:32,860
+الناتجة عن الأحمال الثابتة. الموضوعات التي سنغطيها
+
+7
+00:00:32,860 --> 00:00:36,880
+في هذا الفصل هي: مقدمة وتعريفات متعلقة
+
+8
+00:00:36,880 --> 00:00:41,360
+بالإجهاد المتواتر في المعادن، Fatigue in
+
+9
+00:00:41,360 --> 00:00:46,060
+metals. The methodological approach to fatigue
+
+10
+00:00:46,060 --> 00:00:51,120
+failure في عملية التحليل والتصميم، طرق حسابات
+
+11
+00:00:51,120 --> 00:00:54,500
+الإجهاد المتواتر، fatigue life method، التي هي stress
+
+12
+00:00:54,500 --> 00:00:57,500
+life method، وstrain life method، وlinear elastic
+
+13
+00:00:57,500 --> 00:01:02,950
+fracture mechanics method. سنتعرف على الـendurance
+
+14
+00:01:02,950 --> 00:01:07,930
+limit، الـ fatigue strength، وبعدين how to modify
+
+15
+00:01:07,930 --> 00:01:14,290
+the endurance limit of a standard fatigue specimen، لكي
+
+16
+00:01:14,290 --> 00:01:18,330
+نأخذ بعين الاعتبار المتغيرات الأخرى الواقعية، وبالتالي
+
+17
+00:01:18,330 --> 00:01:22,450
+سنتطرق إلى endurance limit modifying factors، سنتعرف
+
+18
+00:01:22,450 --> 00:01:27,110
+على التركيز الإجهادي وحساسية المادة للخدوش.
+
+19
+00:01:34,250 --> 00:01:38,810
+بعدين سنتعرف،  سناخذ ما هو بشكل عام الـ how
+
+20
+00:01:38,810 --> 00:01:43,170
+to characterize the variability في
+
+21
+00:01:43,170 --> 00:01:47,650
+الـloading.  ممكن نوع الـloading يكون عندي، يكون
+
+22
+00:01:47,650 --> 00:01:50,350
+عندي tensile loading أو bending loading أو
+
+23
+00:01:50,350 --> 00:01:53,230
+torsional loading أو أي combination، how to
+
+24
+00:01:53,230 --> 00:01:57,610
+characterize the loading into one stress component
+
+25
+00:01:57,610 --> 00:02:00,710
+مع استخدام ما هي design theories.
+
+26
+00:02:03,880 --> 00:02:08,720
+سنبدأ أولًا، الذي هو تقديم أو بعض التقديم لـ fatigue
+
+27
+00:02:08,720 --> 00:02:19,700
+in metals. أول ملاحظة: الـloading ممكن يكون متغير أو
+
+28
+00:02:19,700 --> 00:02:26,380
+متكرر. يعني مثلًا لو أخذت أنا الزنبركات في السيارة
+
+29
+00:02:26,380 --> 00:02:31,880
+في هذه السيارة، هذه
+
+30
+00:02:31,880 --> 00:02:38,010
+العجلات، وفي عندي نظام التعليق. سنعمل صورة، رسمًا
+
+31
+00:02:38,010 --> 00:02:52,270
+أكبر، وهي
+
+32
+00:02:52,270 --> 00:02:58,930
+عندي هنا دولاب، هو دولاب، هو محور x، وفي عندي نظام
+
+33
+00:02:58,930 --> 00:03:00,170
+التعليق، زنبركات.
+
+34
+00:03:04,730 --> 00:03:10,810
+الآن، السيارة وهي ماشية، الـloading أو التحميل على
+
+35
+00:03:10,810 --> 00:03:15,990
+الزنبركات بيكون متغير. الآن أنا ممكن أكون ماشيًا على
+
+36
+00:03:15,990 --> 00:03:20,750
+أرضٍ سهلية، ممكن أطلع مطبًا، ممكن أنزل حفرة. فهذه
+
+37
+00:03:20,750 --> 00:03:27,130
+الاهتزازات تزاد، وتعمل تغييرًا على الأحمال على الزنبركات.
+
+38
+00:03:27,130 --> 00:03:34,000
+فممكن الأحمال ما تكونش ثابتة، تكون متغيرة. هذا يسمى
+
+39
+00:03:34,000 --> 00:03:41,880
+variable loading. مثال آخر، ممكن لو أخذنا
+
+40
+00:03:41,880 --> 00:03:49,940
+عضلة قلب الإنسان، عضلة قلب الإنسان، التحميل عليها
+
+41
+00:03:49,940 --> 00:03:53,460
+متغير، وممكن نعمل شيء زي هذا.
+
+42
+00:03:59,370 --> 00:04:06,550
+واضح أن الـloading variable.
+
+43
+00:04:06,550 --> 00:04:10,530
+فمعناته
+
+44
+00:04:10,530 --> 00:04:15,370
+التحميل ليس ثابتًا، طبعًا في أمثلة كثيرة في الـengine
+
+45
+00:04:15,370 --> 00:04:26,970
+بتاع السيارة، عند الـslider crank mechanism، عند
+
+46
+00:04:26,970 --> 00:04:31,090
+هنا الـpiston بتاع السيارة، لو أخذت الـconnecting
+
+47
+00:04:31,090 --> 00:04:36,690
+rod، الـconnecting rod،
+
+48
+00:04:36,690 --> 00:04:42,390
+طبعًا الـangular velocity والـangular acceleration للـ
+
+49
+00:04:42,390 --> 00:04:48,070
+connecting rod متغيرة، معناته الـinertia forces على
+
+50
+00:04:48,070 --> 00:04:51,510
+الـconnecting rod متغيرة، معناته الـloading متغيرة.
+
+51
+00:04:51,510 --> 00:04:55,550
+فهيكون التحميل على الـconnecting rod متغير.
+
+52
+00:04:58,310 --> 00:05:02,750
+لأن في حالة القطع الميكانيكية المتعرضة لأحمال
+
+53
+00:05:02,750 --> 00:05:07,550
+متغيرة، ممكن يصير الـfailure للـmechanical element
+
+54
+00:05:07,550 --> 00:05:13,950
+عند stress أقل من الـyield strength، لأن الـfailure
+
+55
+00:05:13,950 --> 00:05:19,830
+بيصير بعد تكرار،  بعد عدد كبير من الـcycles of
+
+56
+00:05:19,830 --> 00:05:27,490
+variable loading. الـfailure عادةً بيكون بالنسبة لنا
+
+57
+00:05:27,490 --> 00:05:33,050
+بيصير كسرًا مفاجئًا، ولا يعطينا تحذيرًا مسبقًا أنه سيصير
+
+58
+00:05:33,050 --> 00:05:35,810
+كسرًا، ولكن في الحقيقة بيكون فيه الـfailure فترة
+
+59
+00:05:35,810 --> 00:05:42,410
+زمنية،  أنا اللي أشوفه كمستخدم أشوف فجأة أنه صار
+
+60
+00:05:42,410 --> 00:05:52,330
+عندي كسر أو failure بدون إنذار مسبق. الـ
+
+61
+00:05:52,330 --> 00:05:54,990
+fatigue failure يمر بثلاث مراحل
+
+62
+00:06:00,250 --> 00:06:07,050
+التي هي three stages of
+
+63
+00:06:07,050 --> 00:06:14,210
+fatigue failure. أولًا
+
+64
+00:06:14,210 --> 00:06:23,530
+مرحلة، التي هي crack initiation، ثم
+
+65
+00:06:23,530 --> 00:06:25,310
+crack propagation،
+
+66
+00:06:29,630 --> 00:06:39,030
+ثم final ultimate fracture.
+
+67
+00:06:39,030 --> 00:06:44,730
+يعني
+
+68
+00:06:44,730 --> 00:06:51,160
+في البداية، نتيجة الـrepeated stress عند نقطة معينة، ممكن
+
+69
+00:06:51,160 --> 00:06:54,360
+محليًا، أدخل الـplastic range محليًا، أدخل الـ
+
+70
+00:06:54,360 --> 00:06:59,920
+plastic range. يعني أنا رسمت الـmaterial، الـstress
+
+71
+00:06:59,920 --> 00:07:04,580
+versus الـstrain لحديد معين، ممكن يكون الشكل هذا.
+
+72
+00:07:04,580 --> 00:07:09,640
+ممكن أنا محليًا أكون في هذه المنطقة، أدخل، أدخل الذي
+
+73
+00:07:09,640 --> 00:07:14,040
+هو في الـplastic عند نقطة معينة. إذا دخلت إلى plastic
+
+74
+00:07:14,040 --> 00:07:17,740
+range عند نقطة معينة، يبدأ يصير تشقق، يبدأ يصير
+
+75
+00:07:17,740 --> 00:07:21,160
+عنده تشقق، مع repetition of loading، يبدأ يصير
+
+76
+00:07:21,160 --> 00:07:25,140
+تشقق. في المرحلة التي أسميها، التي هي بداية التشقق أو
+
+77
+00:07:25,140 --> 00:07:29,860
+crack initiation. طبعًا الـstress cycling مستمر،
+
+78
+00:07:29,860 --> 00:07:34,980
+فيبدأ الـcrack ماذا؟ يتسع، يكبر، يزيد شوي شوي شوي
+
+79
+00:07:34,980 --> 00:07:37,540
+شوي شوي شوي شوي شوي شوي شوي شوي شوي شوي شوي
+
+80
+00:07:37,540 --> 00:07:39,570
+شوي شوي شوي شوي شوي شوي شوي شوي شوي، حتى الـ
+
+81
+00:07:39,570 --> 00:07:43,130
+material، الذي يحمل الـload، أو المقطع الحقيقي
+
+82
+00:07:43,130 --> 00:07:47,570
+يقل حجمه، حتى الـcross section يضعف بشكل كبير، و
+
+83
+00:07:47,570 --> 00:07:55,350
+يصير failure من خلال أن الـstress وصل إلى الـ
+
+84
+00:07:55,350 --> 00:07:58,330
+ultimate stress في الـmaterial، لأن الـarea قلت، و
+
+85
+00:07:58,330 --> 00:08:06,130
+الـstress، sigma، يساوي F على A، يعني كل ما
+
+86
+00:08:06,130 --> 00:08:14,290
+تقل A، كل ما يزداد الـstress.  في هذه الحالة يزداد، فيصل إلى مرحلة
+
+87
+00:08:14,290 --> 00:08:18,410
+أن الـcross section area صغر كثيرًا، فنصل إلى الـ
+
+88
+00:08:18,410 --> 00:08:26,150
+ultimate strength، فيصير sudden failure. أنا
+
+89
+00:08:26,150 --> 00:08:29,430
+عندي هنا أمثلة على fatigue failure، في عندي shaft،
+
+90
+00:08:29,430 --> 00:08:34,230
+عمود، وفي عندي هنا key way، عند الـkey way، في عندي
+
+91
+00:08:34,230 --> 00:08:37,150
+sudden change في الـcross section، معناته سيصير
+
+92
+00:08:37,150 --> 00:08:40,370
+عندي stress concentration، stress concentration،
+
+93
+00:08:40,370 --> 00:08:44,110
+يعني الـstress level عند الـdiscontinuity سيرتفع
+
+94
+00:08:44,110 --> 00:08:48,810
+بشكل كبير، يعني سيكون عندي الـstress بعيدًا عن النقطة
+
+95
+00:08:48,810 --> 00:08:53,910
+هذه مثلًا يكون 100 ميجا، لكن عندي stress
+
+96
+00:08:53,910 --> 00:08:57,710
+concentration factor هنا ثلاثة، معناته محليًا سيكون
+
+97
+00:08:57,710 --> 00:09:03,540
+الـstress 300 ميجا، معناته أنا ممكن أكون دخلت الـ
+
+98
+00:09:03,540 --> 00:09:08,340
+plastic region، فتبدأ عند هنا بيصير ماذا؟ الـcrack، الـ
+
+99
+00:09:08,340 --> 00:09:10,980
+crack، تنتشر شوية شوية شوية شوية شوية شوية شوية
+
+100
+00:09:10,980 --> 00:09:14,820
+شوية، حتى الـcross section يصغر بشكل كبير جدًا،
+
+101
+00:09:14,820 --> 00:09:18,760
+يرفع الـstress level بشكل مفاجئ، ويصير كسر، by
+
+102
+00:09:18,760 --> 00:09:22,380
+ultimate، by ultimate tensile failure.
+
+103
+00:09:30,050 --> 00:09:36,050
+الآن في عندي الـthree major fatigue life models، في
+
+104
+00:09:36,050 --> 00:09:41,290
+عندي ثلاثة models لتحليل الإجهادات المتواترة، هذه
+
+105
+00:09:41,290 --> 00:09:48,570
+الطرق، الـmethods، تتوقع عمر القطعة بالـcycles for
+
+106
+00:09:48,570 --> 00:09:53,770
+a certain loading level، يعني كل هذه الطرق تتوقع
+
+107
+00:09:53,770 --> 00:10:01,450
+عمر القطع الميكانيكية، ولتحميل معين، مثلًا عند مئة
+
+108
+00:10:01,450 --> 00:10:07,150
+ميجا باسكال، ممكن القطعة ستعيش مثلًا مليون، مليون
+
+109
+00:10:07,150 --> 00:10:13,590
+cycle، عند مئة ميجا باسكال ممكن تعيش مليون ألف
+
+110
+00:10:13,590 --> 00:10:14,790
+cycle، وهكذا.
+
+111
+00:10:23,230 --> 00:10:25,710
+الآن، الـfatigue life method، يعني الـstress life
+
+112
+00:10:25,710 --> 00:10:28,290
+method، والـstrain life method، والـlinear elastic
+
+113
+00:10:28,290 --> 00:10:32,450
+fracture mechanics method. نحن في هذه المادة
+
+114
+00:10:32,450 --> 00:10:35,830
+سنتطرق، أو سنتناول الطريقة الأولى، والطريقة
+
+115
+00:10:35,830 --> 00:10:38,970
+الثانية، التي هي الـstress life method، والـstrain
+
+116
+00:10:38,970 --> 00:10:44,570
+life method. في
+
+117
+00:10:44,570 --> 00:10:50,710
+الـstress life method، نحضر عينة معيارية، التي لها
+
+118
+00:10:50,710 --> 00:10:56,760
+شكل معين، أبعاد معينة، ونعرضها لـrepeating stress
+
+119
+00:10:56,760 --> 00:11:01,080
+while counting cycles to failure. نعرضها إلى
+
+120
+00:11:01,080 --> 00:11:07,200
+building stress. الـbuilding، طبعًا،  أشمله متغير، نضع
+
+121
+00:11:07,200 --> 00:11:11,840
+نعملها building ونعد number of cycles، حتى
+
+122
+00:11:11,840 --> 00:11:19,340
+العينة تنكسر. طبعًا طبيعة الـloading completely
+
+123
+00:11:19,340 --> 00:11:21,440
+reverse stress cycling.  ماذا يعني completely
+
+124
+00:11:21,440 --> 00:11:22,560
+reversed؟ يعني
+
+125
+00:11:30,070 --> 00:11:41,930
+يعني أنا أخذت fiber هنا، المقطع هنا سيكون دائريًا، في
+
+126
+00:11:41,930 --> 00:11:44,370
+لحظة معينة، أنا ممكن يكون عندي هنا الـfiber هذه
+
+127
+00:11:44,370 --> 00:11:49,820
+بالشكل هذا، عندي سيكون عليها شد، tension، هنا tension.
+
+128
+00:11:49,820 --> 00:11:54,240
+إذا لففت تسعين درجة، النقطة هذه ستصير هنا، ستصير عندي
+
+129
+00:11:54,240 --> 00:11:59,580
+الـstress صفر، ألفّ كمان تسعين درجة، تصبح النقطة تلفّ
+
+130
+00:11:59,580 --> 00:12:06,140
+تحت، تصبح عليها compression، انضغاط، ألفّ كمان تسعين
+
+131
+00:12:06,140 --> 00:12:09,460
+درجة، صفر، كمان تسعين درجة، tension، بمعنى أن عندي
+
+132
+00:12:09,460 --> 00:12:13,840
+tension is zero، tension is zero، compression is
+
+133
+00:12:13,840 --> 00:12:17,620
+zero، tension is zero، compression، وهكذا، بمعنى
+
+134
+00:12:17,620 --> 00:12:21,880
+complete reverse، ممكن نفس الـfiber يكون على مرة في
+
+135
+00:12:21,880 --> 00:12:24,920
+لحظة ما tension، في لحظة ما compression، لأنه بيكون
+
+136
+00:12:24,920 --> 00:12:30,160
+عندي bending بالشكل هذا، طبعًا
+
+137
+00:12:30,160 --> 00:12:38,600
+أغير الـloading، طبعًا في setup للجهاز الذي، للـ
+
+138
+00:12:38,600 --> 00:12:41,660
+fatigue tensile test، طبعًا هذا الـfatigue tensile
+
+139
+00:12:41,660 --> 00:12:45,120
+test، تعرّفنا عليه من خلال مادة material
+
+140
+00:12:45,120 --> 00:12:48,640
+science، ومادة mechanics of material،  تعرضنا
+
+141
+00:12:48,640 --> 00:12:57,540
+بالتفصيل كيف نعمل الفحص. طبعًا، عندي هنا العينة، عندي
+
+142
+00:12:57,540 --> 00:13:00,880
+هنا العينة، أو في عندي one setup، عندي هنا العينة
+
+143
+00:13:00,880 --> 00:13:06,070
+مثبتة، فأنا هنا main bearing، هنا main bearing، وهنا
+
+144
+00:13:06,070 --> 00:13:10,150
+لدي flexible coupling، توصل هذا العمود مع الموتور
+
+145
+00:13:10,150 --> 00:13:14,690
+الذي يدور، لأن هنا في وزن، يكون تحميل على الـbearing
+
+146
+00:13:14,690 --> 00:13:18,010
+هذه، والـbearing هذا، لأن نتيجة تحميل الشد لتحت
+
+147
+00:13:18,010 --> 00:13:22,850
+سيكون عندي الـfiber هنا عليها compression، وهنا
+
+148
+00:13:22,850 --> 00:13:30,090
+tension، لأن الـshaft يدور، معناته هذه كانت
+
+149
+00:13:30,090 --> 00:13:32,350
+في اللحظة الـcompression، لما يدور مئة وثمانين درجة يصير
+
+150
+00:13:32,350 --> 00:13:35,750
+الـtension، كمان مئة وثمانين درجة، compression، tension،
+
+151
+00:13:35,750 --> 00:13:37,890
+compression، tension، compression، tension، وهكذا.
+
+152
+00:13:37,890 --> 00:13:42,870
+فيصير نفس الـfiber، الـstress level is completely
+
+153
+00:13:42,870 --> 00:13:49,450
+reversed bending، الذي هو بالشكل هذا. هذا one setup.
+
+154
+00:13:49,450 --> 00:13:58,970
+another setup، العينة تمسك من طرف بالعمود بتاع
+
+155
+00:13:58,970 --> 00:14:03,170
+الموتور، فإني هنا موتور، وإني هنا bearing، و
+
+156
+00:14:03,170 --> 00:14:07,550
+فيندي bearing، الآن العمود، العينة موجودة في bearing،
+
+157
+00:14:07,550 --> 00:14:11,650
+والـbearing، أنا اسمح لها أن تسير، وهنا أكون حاطط
+
+158
+00:14:11,650 --> 00:14:15,230
+load عليها، لأن نتيجة الـload أحس أن عند هذه المنطقة
+
+159
+00:14:15,230 --> 00:14:15,530
+هذه
+
+160
+00:14:18,330 --> 00:14:23,490
+tension, bending, stress. إذا بقي يدور تسعين درجة،
+
+161
+00:14:23,490 --> 00:14:26,650
+يعني إذا بقي يدور، الـfiber ستبقى تحت، ستصبح
+
+162
+00:14:26,650 --> 00:14:30,150
+compression، فهو يدور، مرة tension، compression،
+
+163
+00:14:30,150 --> 00:14:32,290
+tension، compression، tension، compression، وهكذا،
+
+164
+00:14:32,290 --> 00:14:38,240
+فهيكون completely reversed bending stress حتى الكسر.
+
+165
+00:14:38,240 --> 00:14:41,680
+طبعًا أنا في التجربة أغير الـload، مثلًا أحط أولًا 200
+
+166
+00:14:41,680 --> 00:14:47,220
+كيلو، أحط مثلًا خمسة، مثلًا عشرة kilogram، وألفّ الموتور
+
+167
+00:14:47,220 --> 00:14:51,820
+حتى حدّ العينة ما تنكسر، أجيب عينة ثانية، أحط الـload
+
+168
+00:14:51,820 --> 00:14:58,900
+مثلًا مئة، ألفّ العينة حتى بعد number of cycles، حتى
+
+169
+00:14:58,900 --> 00:15:05,410
+الكسر، أحط عينة ثالثة، أحط load مثلًا مئتين، عينة رابعة
+
+170
+00:15:05,410 --> 00:15:08,850
+أحط load، ثلاثمائة، أربعمائة، يعني معناته أنا
+
+171
+00:15:08,850 --> 00:15:13,310
+أحط الـload مثلًا
+
+172
+00:15:13,310 --> 00:15:23,290
+خمسين، مئة، مئتين، ثلاثمائة، وأحسب count cycles to failure.
+
+173
+00:15:30,450 --> 00:15:35,610
+وبعدين أحسب الـ fatigue strength، الـ
+
+174
+00:15:35,610 --> 00:15:41,090
+fatigue strength. إذا عندي cantilever، وعندي
+
+175
+00:15:41,090 --> 00:15:47,730
+shaft، وفي load هنا F، هذه المسافة L.
+
+176
+00:15:50,580 --> 00:15:55,880
+الـmoment سيكون ماذا؟ الـmoment سيساوي F L.
+
+177
+00:15:55,880 --> 00:16:02,640
+والمقطع عندي مدوّر، معناته الـsigma ستكون تساوي M
+
+178
+00:16:02,640 --> 00:16:12,770
+في C على I. الـM عندي F L، والـC D على 2، قطر العمود
+
+179
+00:16:12,770 --> 00:16:18,270
+على اثنين، والـI باي على أربعة، D أس أربعة.
+
+180
+00:16:18,270 --> 00:16:26,190
+يعني الـsigma ستكون تساوي اث
+
+223
+00:19:52,850 --> 00:19:57,030
+هنا لهنا وعندي
+
+224
+00:20:00,030 --> 00:20:11,070
+هنا عندي high cycle fatigue low
+
+225
+00:20:11,070 --> 00:20:16,130
+cycle fatigue بيصير failure أو المنطقة اللي بيكون
+
+226
+00:20:16,130 --> 00:20:19,210
+عدد الـ number of cycles to failure أقل من ألف
+
+227
+00:20:19,210 --> 00:20:24,940
+بأسميها low cycle fatigue إذا كان عدد الـ
+
+228
+00:20:24,940 --> 00:20:28,780
+cycles to failure أكثر من ألف أسميه high cycle
+
+229
+00:20:28,780 --> 00:20:32,820
+fatigue هذه الطريقة لأنه لو عندي low cycle fatigue
+
+230
+00:20:32,820 --> 00:20:35,880
+وعندي high cycle fatigue، low cycle fatigue الـ
+
+231
+00:20:35,880 --> 00:20:39,800
+number of cycles to failure أقل من ألف، high cycle
+
+232
+00:20:39,800 --> 00:20:45,960
+fatigue، الـ cycles to failure أكثر من ألف، ممكن
+
+233
+00:20:45,960 --> 00:20:46,840
+تصنيف ثاني
+
+234
+00:21:07,460 --> 00:21:20,080
+ممكن أحكي finite life fatigue، واللي هو high أو
+
+235
+00:21:20,080 --> 00:21:25,600
+infinite life
+
+236
+00:21:25,600 --> 00:21:29,460
+fatigue يعني
+
+237
+00:21:31,750 --> 00:21:36,050
+لحد مليون cycle بعتبر أن القطعة لها عمر محدود
+
+238
+00:21:36,050 --> 00:21:42,470
+finite life يعني، إذا تجاوزت المليون cycle تقريبًا
+
+239
+00:21:42,470 --> 00:21:45,690
+بعتبر أن حياتها infinite life، لو اعتبرت حياتها
+
+240
+00:21:45,690 --> 00:21:51,050
+infinite life الآن
+
+241
+00:21:51,050 --> 00:21:56,790
+لو نأخذ مثال على عدد الضربات أو عدد التغيرات لقطعة
+
+242
+00:21:56,790 --> 00:22:00,670
+ميكانيكية معينة، خذ مثلًا عضلة القلب، عضلة القلب
+
+243
+00:22:05,460 --> 00:22:10,200
+عضلة القلب تعمل سبعين ضربة في الدقيقة، سبعين ضربة
+
+244
+00:22:10,200 --> 00:22:16,460
+في الدقيقة يعني
+
+245
+00:22:16,460 --> 00:22:22,680
+في الساعة، كم في الساعة؟ في الساعة يكون سبعين في
+
+246
+00:22:22,680 --> 00:22:29,360
+ستين، بيطلع أربعة آلاف ومئتان ضربة أو cycle في اليوم
+
+247
+00:22:32,920 --> 00:22:37,720
+بيكون عنده اللي هو أربعة آلاف ومئتان في أربعة وعشرين
+
+248
+00:22:37,720 --> 00:22:45,640
+أربعة آلاف ومئتان في
+
+249
+00:22:45,640 --> 00:22:51,220
+أربعة وعشرين بيطلع
+
+250
+00:22:51,220 --> 00:22:59,760
+مائة وتسعة وسبعون ألفًا ومئتان ضربة، هذا في اليوم، في
+
+251
+00:22:59,760 --> 00:23:00,260
+السنة
+
+252
+00:23:03,930 --> 00:23:08,510
+هتكون عندنا مئة وتسعة وسبعون ألفًا ومئتان في ثلاثمئة وخمسة وستين يوم في
+
+253
+00:23:08,510 --> 00:23:13,410
+ثلاثمئة وخمسة وستين بيطلع خمسة
+
+254
+00:23:13,410 --> 00:23:21,790
+و ستين مليونًا وأربعمائة وثمانية آلاف cycle هذه في سنة
+
+255
+00:23:21,790 --> 00:23:28,490
+و ستين مليونًا وأربعمائة وثمانية آلاف cycle هذه في سنة
+
+256
+00:23:31,510 --> 00:23:37,150
+لو بدأ يعيش سبعين سنة، في سبعين سنة مثلًا متوسط
+
+257
+00:23:37,150 --> 00:23:44,370
+العمر تقريبًا سبعين سنة، هيكون خمسة وستون مليونًا
+
+258
+00:23:44,370 --> 00:23:49,770
+وأربعمائة وثمانية آلاف في سبعين
+
+259
+00:24:01,170 --> 00:24:04,490
+ضربات في واحد ساعة مش مشكلة بيطلع تقريبًا، خليني أحط
+
+260
+00:24:04,490 --> 00:24:10,630
+صفر، سبعة، سبعة، سبعة، ثمانية، ستة
+
+261
+00:24:10,630 --> 00:24:19,570
+تسعة، ثمانية، ستة، تسعة، ثلاثة، أربعة، ستة، فاصلة
+
+262
+00:24:19,570 --> 00:24:26,370
+أربعة، يعني لشخص، نحكي أكثر من ثلاثة ستة
+
+263
+00:24:26,370 --> 00:24:35,520
+تسعة، يعني تقريبًا نحكي حوالي خمسة مليارات ضربة لشخص
+
+264
+00:24:35,520 --> 00:24:38,520
+يعيش حياة طبيعية في حدود سبعين وواحد وسبعين سنة
+
+265
+00:24:38,520 --> 00:24:44,400
+بدرب لحوالي خمسة مليارات cycle يعني كم
+
+266
+00:24:44,400 --> 00:24:52,280
+عشرة يعني خمسة في عشرة أس تسعة، تخيلوا أيش الـ
+
+267
+00:24:52,280 --> 00:24:56,620
+fatigue loading اللي موجود على عضلة، عضلة القلب
+
+268
+00:25:00,960 --> 00:25:05,360
+معناته الـ fatigue loading موجود، معناته عضلة القلب
+
+269
+00:25:05,360 --> 00:25:10,200
+لازم يكون لها مواصفات تتحمل الـ cycles هذه لحد ما
+
+270
+00:25:10,200 --> 00:25:13,440
+يصير، ما يصير failure، ما يصير فيها ضعف أو يصير
+
+271
+00:25:13,440 --> 00:25:20,970
+عندها تصلب أو أي مشكلة ثانية، طيب أنا عندي حكيت
+
+272
+00:25:20,970 --> 00:25:23,470
+عندي low cycle fatigue إذا كان number of cycles to
+
+273
+00:25:23,470 --> 00:25:25,930
+failure أقل من ألف، وعندي high cycle fatigue إذا
+
+274
+00:25:25,930 --> 00:25:28,330
+كان الـ cycles to failure أكثر من ألف، في عندي
+
+275
+00:25:28,330 --> 00:25:32,190
+finite life fatigue إذا كان الـ cycles to، إذا
+
+276
+00:25:32,190 --> 00:25:35,930
+كان الـ life، الـ cycles to، to failure أقل من
+
+277
+00:25:35,930 --> 00:25:39,610
+مليون، إذا أكبر من مليون بيكون عندي infinite
+
+278
+00:25:39,610 --> 00:25:43,550
+life، اللحظة في عندي stress level هنا، بسميه
+
+279
+00:25:43,550 --> 00:25:45,050
+stress level
+
+280
+00:25:47,780 --> 00:25:54,000
+بسميه SE، SE هذه هي الـ endurance limit، الـ endurance
+
+281
+00:25:54,000 --> 00:26:00,940
+limit هي الـ stress level below which the specimen
+
+282
+00:26:00,940 --> 00:26:04,760
+will not fail، يعني هو الـ stress level اللي تحته
+
+283
+00:26:04,760 --> 00:26:09,000
+العينة والقطعة لن تنكسر، ستظل عايشة إلى ما لانهاية
+
+284
+00:26:09,000 --> 00:26:13,120
+معناته if we apply a stress level below the
+
+285
+00:26:13,120 --> 00:26:18,170
+endurance limit the specimen will not fail، معناته
+
+286
+00:26:18,170 --> 00:26:23,990
+تعريف الـ endurance limit، الـ SE هي الـ stress
+
+287
+00:26:23,990 --> 00:26:29,130
+level below which the specimen will not fail
+
+288
+00:26:29,130 --> 00:26:36,010
+معناته it will endure، endure، هيعيش إلى ما لا نهاية
+
+289
+00:26:36,010 --> 00:26:42,050
+هذا
+
+290
+00:26:42,050 --> 00:26:48,520
+طبعًا الشكل اللي شفناه في حالة اللي هو السبائك
+
+291
+00:26:48,520 --> 00:26:52,580
+الحديدية، لكن في حالة اللي هي السبائك الغير حديدية اللي
+
+292
+00:26:52,580 --> 00:26:59,140
+هي nonferrous metals، it does not show endurance
+
+293
+00:26:59,140 --> 00:27:05,840
+limit، هيكون
+
+294
+00:27:05,840 --> 00:27:10,080
+الـ S-N دايران بالشكل هذا، يعني بيبقوا نازل على طول
+
+295
+00:27:10,080 --> 00:27:16,830
+ما فيهوش ثبات، ما بيصير flat، في الحالة هذه I define
+
+296
+00:27:16,830 --> 00:27:20,990
+fatigue strength for a specified number of cycles
+
+297
+00:27:20,990 --> 00:27:25,370
+يعني إذا كان الـ، الـ، for a stress level مئة
+
+298
+00:27:25,370 --> 00:27:30,590
+ميجا هيعيش مليون، for a stress level مئتان ميجا
+
+299
+00:27:30,590 --> 00:27:36,490
+هيعيش لـ مئتي ألف cycle، يعني الـ life أو عمر القطعة
+
+300
+00:27:36,490 --> 00:27:40,170
+مرتبطة بالـ stress level، كل ما زاد الـ stress level
+
+301
+00:27:40,170 --> 00:27:42,290
+كل ما عمر القطعة كان أقل
+
+302
+00:27:50,240 --> 00:27:55,760
+معناته نلخص في الـ stress life method، أنا باخد عينة
+
+303
+00:27:55,760 --> 00:28:01,360
+من المادة، عينة معيارية، بعمل tensile test، برسم الـ S
+
+304
+00:28:01,360 --> 00:28:08,440
+-N diagram وبعرف الـ number of cycles to failure
+
+305
+00:28:10,870 --> 00:28:15,470
+depending على الـ loading أو قيمة التحميل على القطعة
+
+306
+00:28:15,470 --> 00:28:18,830
+الميكانيكية، الطريقة الثانية هي الـ strain life
+
+307
+00:28:18,830 --> 00:28:21,510
+method، الـ strain life method، في الـ strain life
+
+308
+00:28:21,510 --> 00:28:24,870
+method بعمل detailed analysis of the plastic
+
+309
+00:28:24,870 --> 00:28:28,650
+deformation at localized regions، الآن في الـ strain
+
+310
+00:28:28,650 --> 00:28:32,290
+life method بقدر اللي هو الـ deformations اللي
+
+311
+00:28:32,290 --> 00:28:38,670
+بيصير locally عند نقاط معينة في القطعة الميكانيكية
+
+312
+00:28:42,060 --> 00:28:47,020
+عادة الـ fatigue failure بيبدا at a local discontinuity
+
+313
+00:28:47,020 --> 00:28:52,220
+يعني إذا عندي sudden change، إذا عندي هاي shaft والـ
+
+314
+00:28:52,220 --> 00:28:57,540
+القطر بتاعه إيش مصدر هنا
+
+315
+00:28:57,540 --> 00:29:03,380
+ممكن يصير عندي، الآن أدخل local يعني نقطة هنا، أدخل
+
+316
+00:29:03,380 --> 00:29:04,340
+الـ plastic range
+
+317
+00:29:09,530 --> 00:29:11,970
+لما أدخلت الـ plastic range بيصير عندي plastic
+
+318
+00:29:11,970 --> 00:29:15,730
+deformation locally وشوية شوية بتبدأ تصير عندي تشقق
+
+319
+00:29:15,730 --> 00:29:18,870
+التشقق بيكبر شوية شوية شوية شوية لحد ما يصير عندي
+
+320
+00:29:18,870 --> 00:29:23,030
+sudden failure، يعني وين في عندي اللي هو local
+
+321
+00:29:23,030 --> 00:29:26,050
+discontinuity عندي stress concentration أو حالة
+
+322
+00:29:26,050 --> 00:29:34,050
+ثانية عند هذه القطعة وفيه ثقب ممكن تصير failure
+
+323
+00:29:34,050 --> 00:29:37,830
+عند النقطة هذه، عند، عند الثقب هنا عندي stress
+
+324
+00:29:43,810 --> 00:29:49,470
+concentration، يعني وين في عندي اللي هو تغير مفاجئ
+
+325
+00:29:49,470 --> 00:29:51,370
+في الـ cross section بيكون عندي stress
+
+326
+00:29:51,370 --> 00:29:54,910
+concentration، بيصير locally، local يعني هذه نقطة
+
+327
+00:29:54,910 --> 00:29:59,670
+هذيه الـ stress level ممكن أدخل الـ plastic range
+
+328
+00:29:59,670 --> 00:30:03,290
+دخلت الـ plastic range بتبدأ تشقق، صار تشقق، والتشقق
+
+329
+00:30:03,290 --> 00:30:05,970
+بيصير أكبر شوية شوية لحد ما يصير عندي صدع انفجار
+
+330
+00:30:19,910 --> 00:30:25,230
+طيب الآن عند discontinuity يعني مثلًا عندي، عندي
+
+331
+00:30:25,230 --> 00:30:33,990
+fillet أو عندي ثقب، ورحت رسمت الـ stress مع الـ
+
+332
+00:30:33,990 --> 00:30:38,990
+strain، الآن بدأ الـ strain تزيد شوية شوية لحد ما locally
+
+333
+00:30:41,890 --> 00:30:47,090
+الـ stress بيزيد شوية شوية لحد ما locally هذا الـ
+
+334
+00:30:47,090 --> 00:30:52,130
+first reversal، دخلت في الـ plastic range، طبعًا دي
+
+335
+00:30:52,130 --> 00:30:57,950
+قطعة بتدور تتحرك، تتحرك، معناته بيبدأ الـ loading يعكس
+
+336
+00:30:57,950 --> 00:31:00,990
+هيبدأ الـ stress level ينزل
+
+337
+00:31:13,290 --> 00:31:16,790
+بيصير بالعكس، عندي هي الـ second، هي الـ first، هي
+
+338
+00:31:16,790 --> 00:31:20,750
+الرقم واحد، هذا الـ second reverse، صارت stress
+
+339
+00:31:20,750 --> 00:31:24,570
+باتجاه المعاكس، مثلًا هنا هي كانت tension صار
+
+340
+00:31:24,570 --> 00:31:29,250
+إيش compression ودخلت برضه لـ plastic range لأن
+
+341
+00:31:29,250 --> 00:31:34,570
+استمر القطعة والشافت في الدوران، هيبدأ الـ stress
+
+342
+00:31:34,570 --> 00:31:41,990
+يزيد، يزيد، يزيد لحد ما يصير failure بعدين هيبدأ يرفع ثاني
+
+343
+00:31:47,530 --> 00:31:54,570
+هذه الـ third reversal، صار بالموجب، القطعة
+
+344
+00:31:54,570 --> 00:32:00,110
+الميكانيكية بتلف، هيبدأ
+
+345
+00:32:00,110 --> 00:32:04,810
+تلف، يبدأ الـ stress level يقل، يقل، يقل بعدين بيصير
+
+346
+00:32:04,810 --> 00:32:07,630
+يزيد باتجاه المعاكس، مثلًا هنا كان tension بيبدأ
+
+347
+00:32:07,630 --> 00:32:11,150
+يدخل في الـ compression، compression، compression لحد
+
+348
+00:32:11,150 --> 00:32:13,370
+ما بدأ يدخل الـ plastic range لأن بدأ يدخل الـ
+
+349
+00:32:13,370 --> 00:32:19,740
+plastic range، لحد ما وصلنا هنا، هذه الرابعة، لحظة كل
+
+350
+00:32:19,740 --> 00:32:24,160
+ما لها الـ strength للقطعة الميكانيكية كل ما لها بتقل
+
+351
+00:32:24,160 --> 00:32:31,660
+الآن بيلف الـ shaft بيصير الـ stress الـ negative
+
+352
+00:32:31,660 --> 00:32:33,640
+stress أو الـ compression stress بتقل شوية شوية
+
+353
+00:32:33,640 --> 00:32:38,360
+شوية لحد ما يصير zero بعدين بيصير يتحول لإيش؟ بدخل
+
+354
+00:32:38,360 --> 00:32:42,380
+على الـ tension بيزيد بيزيد لحد دخلت الـ plastic range
+
+355
+00:32:45,710 --> 00:32:51,450
+هذه الخامسة، هي اللي كانت إيش الرابعة، لحظة كل ما
+
+356
+00:32:51,450 --> 00:32:56,910
+لها الـ strength بتقل، لو قررت هتصير أشي زي هيك عندها
+
+357
+00:32:56,910 --> 00:33:03,290
+هذه
+
+358
+00:33:03,290 --> 00:33:12,970
+السادسة، السابعة،
+
+359
+00:33:15,250 --> 00:33:20,790
+كلما الـ strain تزيد لها بتقل الـ strength بتاعتها لحد ما
+
+360
+00:33:20,790 --> 00:33:25,270
+يصير عندي sudden failure، واضح أن الـ stress is
+
+361
+00:33:25,270 --> 00:33:28,370
+cycling between tension and compression، tension
+
+362
+00:33:28,370 --> 00:33:30,310
+and compression، يعني في عندي completely reversed
+
+363
+00:33:30,310 --> 00:33:36,730
+completely reversed cycling، بين، طبعًا أنا في كل
+
+364
+00:33:36,730 --> 00:33:40,280
+حالة locally بدخل الـ، هنا دخلت الـ plastic range
+
+365
+00:33:40,280 --> 00:33:42,320
+وهنا دخلت الـ plastic range، بس هنا دخلت الـ plastic
+
+366
+00:33:42,320 --> 00:33:46,540
+range while tension بيكون موجود، هنا دخلت الـ
+
+367
+00:33:46,540 --> 00:33:49,860
+plastic range while compression، يعني هنا الـ
+
+368
+00:33:49,860 --> 00:33:56,200
+plastic tension، هنا الـ plastic compression، طبعًا
+
+369
+00:33:56,200 --> 00:34:02,740
+القطعة بتضعف أو بـ Serial Crack Propagation لحد ما
+
+370
+00:34:02,740 --> 00:34:06,360
+الـ cross section يقل ويصبح لديه sudden failure
+
+371
+00:34:06,360 --> 00:34:15,160
+طبعًا في كل الأحوال هذا هو الـ total strain، هذا
+
+372
+00:34:15,160 --> 00:34:20,180
+دلتا إبسيلون، دلتا إبسيلون، جزئين هناخدها هنا من بره
+
+373
+00:35:05,490 --> 00:35:16,870
+خلينا نستخدم لونان، هذا
+
+374
+00:35:16,870 --> 00:35:16,910
+هتكون
+
+375
+00:35:32,950 --> 00:35:41,030
+الـ delta epsilon elastic على اثنين وهذا الـ delta
+
+376
+00:35:41,030 --> 00:35:51,670
+epsilon plastic على اثنين، وهنا بالعكس الـ
+
+377
+00:35:51,670 --> 00:35:55,030
+delta epsilon elastic على اثنين وهذا الـ delta
+
+378
+00:35:55,030 --> 00:35:57,010
+epsilon plastic على اثنين
+
+379
+00:36:03,860 --> 00:36:10,400
+delta epsilon على اثنين بالموجب وهنا هتكون delta
+
+380
+00:36:10,400 --> 00:36:18,200
+epsilon على اثنين، واضح فيه أن أنا ممكن أسمي الـ
+
+381
+00:36:18,200 --> 00:36:21,940
+delta epsilon على اثنين هي الـ total strain
+
+382
+00:36:21,940 --> 00:36:27,520
+amplitude، لأن الـ strain يعني بتتغير بالشكل هذا، الـ
+
+383
+00:36:27,520 --> 00:36:27,860
+strain
+
+384
+00:36:31,200 --> 00:36:36,460
+فهذا الـ strain، الـ strain amplitude، الـ strain
+
+385
+00:36:36,460 --> 00:36:41,640
+amplitude مكوّن من
+
+386
+00:36:41,640 --> 00:36:45,360
+جزئين اللي هو reversible strain اللي هو الـ
+
+387
+00:36:45,360 --> 00:36:50,320
+elastic strain، دلتا إبسيلون إلاستك على اثنين زائد
+
+388
+00:36:50,320 --> 00:36:53,620
+اللي هو الـ permanent اللي هي الـ plastic، دلتا إبسيلون
+
+389
+00:36:53,620 --> 00:36:56,300
+plastic على اثنين
+
+390
+00:37:12,630 --> 00:37:18,950
+الآن بنجمع الـ strain، أنا من cycles of strain لحد
+
+391
+00:37:18,950 --> 00:37:23,690
+ما يصير failure، لحد ما يصير failure، إذا عملت plot
+
+392
+00:37:23,690 --> 00:37:28,910
+إذا عملت plot على log log scale، يعني هنا عندي الـ
+
+393
+00:37:28,910 --> 00:37:34,530
+reversals to failure أنا، وهنا عندي الـ strain
+
+394
+00:37:34,530 --> 00:37:35,510
+amplitude
+
+395
+00:37:37,540 --> 00:37:40,780
+strain amplitude، طبعًا إحنا حكينا الـ strain
+
+396
+00:37:40,780 --> 00:37:44,660
+amplitude مكوّن من elastic part و plastic part، هذا
+
+397
+00:37:44,660 --> 00:37:54,060
+الجزء اللي
+
+398
+00:37:54,060 --> 00:38:01,540
+هو delta elastic على اثنين، هذا الجزء
+
+399
+00:38:09,180 --> 00:38:14,380
+اللي هو delta epsilon plastic على اثنين، والـ curve
+
+400
+00:38:14,380 --> 00:38:21,560
+هذا، هذا
+
+401
+00:38:21,560 --> 00:38:26,340
+هو الـ total delta
+
+402
+00:38:26,340 --> 00:38:33,020
+الـ epsilon على اثنين، total strain amplitude، هنا
+
+403
+00:38:33,020 --> 00:38:39,080
+عندي عشر أو اثني عشر، أقصى أربعة عشر، أقصى ناقص ثلاثة عشر
+
+404
+00:38:
+
+445
+00:42:59,340 --> 00:43:03,360
+strain amplitude والـ number of cycles أو الـ
+
+446
+00:43:03,360 --> 00:43:07,760
+reversals to failure as a power law يعني بدكم تحكوا
+
+447
+00:43:07,760 --> 00:43:15,380
+دلتا إبسيلون البلاستيكية على 2 حتكون إبسيلون إف برايم
+
+448
+00:43:16,000 --> 00:43:21,600
+في اتنين N قوسي C والـ دلتا إبسيلون الإيلاستيكية على
+
+449
+00:43:21,600 --> 00:43:28,080
+اتنين حتكون اللي هي سيجما إف برايم على E في اتنين N
+
+450
+00:43:28,080 --> 00:43:28,980
+قوسي B
+
+451
+00:43:38,390 --> 00:43:41,570
+لو أخدت الـ log للطرفين حتطلع علاقة إيش linear
+
+452
+00:43:41,570 --> 00:43:46,770
+حتطلع linear بين الـ log دلتا إبسيلون مع الـ cycle الـ
+
+453
+00:43:46,770 --> 00:44:01,010
+number of reversals طيب
+
+454
+00:44:11,570 --> 00:44:14,750
+الـ Total Strain Amplitude اللي هي دلتا إبسيلون
+
+455
+00:44:14,750 --> 00:44:20,250
+على 2 حتكون مجموع الـ Elastic Strain Amplitude مع
+
+456
+00:44:20,250 --> 00:44:24,930
+الـ Plastic Strain Amplitude وحنعوض عند الـ
+
+457
+00:44:24,930 --> 00:44:31,690
+Elastic اللي هي سيجما إف برايم على E في 2N أس B
+
+458
+00:44:31,690 --> 00:44:38,710
+زائد اللي هي إبسيلون إف برايم في 2N أس C
+
+459
+00:44:48,810 --> 00:44:54,790
+طيب في الكتاب روحوا appendix A23
+
+460
+00:44:56,720 --> 00:45:01,680
+بيعطيني values of coefficients اللي هي B و C اللي
+
+461
+00:45:01,680 --> 00:45:09,000
+هو appendix a ثلاثة و عشرين في كتاب شغلي بيعطيني
+
+462
+00:45:09,000 --> 00:45:17,900
+اللي هو B أو C وإبسيلون إف برايم أو سيجما إف
+
+463
+00:45:17,900 --> 00:45:26,520
+برايم خلّينا نشوف هنا الـ table نتأكد
+
+464
+00:45:38,710 --> 00:45:41,850
+هذا table A23 زي ما أنتم شايفين الـ headings
+
+465
+00:45:41,850 --> 00:45:46,090
+اطلعوا على أقصى يمين الـ table عند الـ fatigue
+
+466
+00:45:46,090 --> 00:45:50,770
+strength exponent B موجود والـ fatigue ductility
+
+467
+00:45:50,770 --> 00:45:55,250
+exponent C موجود والـ fatigue ductility
+
+468
+00:45:55,250 --> 00:45:59,290
+coefficient إف برايم موجود يعني عندها هي سيجما إف
+
+469
+00:45:59,290 --> 00:46:04,450
+برايم والـ B والـ إبسيلون إف برايم والـ C لسبائك
+
+470
+00:46:04,450 --> 00:46:08,550
+مختلفة من سبائك الحديد يعني هنا عند العملي الأول
+
+471
+00:46:08,550 --> 00:46:14,690
+ليه رقم سبكة الحديد والـ description تاعتها ومعطية
+
+472
+00:46:14,690 --> 00:46:17,810
+الـ hardness ونصفها الـ strength والـ ductility in
+
+473
+00:46:17,810 --> 00:46:22,110
+terms of reduction in area والـ true strain at
+
+474
+00:46:22,110 --> 00:46:25,730
+fracture اللي بيمثل برضه التعبير عن الـ ductility والـ
+
+475
+00:46:25,730 --> 00:46:30,250
+الـ modulus والـ STE والـ سيجما إف برايم والـ B والـ S
+
+476
+00:46:30,250 --> 00:46:34,830
+إف برايم والـ C هذا كله موجود في table A23 for
+
+477
+00:46:34,830 --> 00:46:41,350
+different alloys of steel الآن الـ equation هذه اللي
+
+478
+00:46:41,350 --> 00:46:45,270
+أنتم شايفينها دلتا إبسيلون على اتنين بيساوي
+
+479
+00:46:45,270 --> 00:46:47,990
+سيجما إف برايم على E في اتنين N أس B زي اتنين
+
+480
+00:46:47,990 --> 00:46:52,270
+إبسيلون على اتنين N أس C has limited use in design
+
+481
+00:46:52,270 --> 00:46:56,730
+لأنه ببساطة قيم الـ total strain عندي الـ
+
+482
+00:46:56,730 --> 00:47:01,510
+discontinuity الصعب أنك مش موجودة المعلومات هذه و
+
+483
+00:47:01,510 --> 00:47:08,850
+صعب قياسها وحسابها معناته حنشوف نفكر بطريقة
+
+484
+00:47:08,850 --> 00:47:13,590
+ثانية فاكرين
+
+485
+00:47:13,590 --> 00:47:23,950
+الـ S-N diagram أو احنا الآن أخدنا اللي صار أخذه
+
+486
+00:47:23,950 --> 00:47:30,060
+different materials مثلاً دي material واحد material
+
+487
+00:47:30,060 --> 00:47:34,140
+اتنين material تلاتة طبعاً سبائك للحديد
+
+488
+00:47:34,140 --> 00:47:40,000
+material أربعة material خمسة و... وأنا بعرف الـ
+
+489
+00:47:40,000 --> 00:47:42,860
+tensile strength لـ material واحد واتنين وتلاتة و
+
+490
+00:47:42,860 --> 00:47:47,900
+أربعة وخمسة وبعرف الـ endurance limit للعينات
+
+491
+00:47:47,900 --> 00:47:57,000
+معيارية SE برايم الآن عملنا plot بين الـ SA' والـ
+
+492
+00:47:57,000 --> 00:48:01,620
+SUT يعني هنا عندي على المحور الأفقي SUT وعندي
+
+493
+00:48:01,620 --> 00:48:08,780
+هنا SA' اطلعوا على الـ trend بتاع البيانات كيف
+
+494
+00:48:08,780 --> 00:48:15,220
+البيانات بتتصرف لاحظوا تقريباً في علاقة خطية بعدين
+
+495
+00:48:15,220 --> 00:48:18,820
+بيصير ثابتة يعني لاحظوا البيانات كيف هذه
+
+496
+00:48:18,820 --> 00:48:24,750
+experimental data عندي تقريباً في تغير خطي بين الـ SE
+
+497
+00:48:24,750 --> 00:48:30,030
+برايم لحد الـ ultimate strength معين بعدين بيبدأ
+
+498
+00:48:30,030 --> 00:48:35,900
+يصير ثابتة بتثبت قيمة الـ SE برايم لاحظوا عندي تلات
+
+499
+00:48:35,900 --> 00:48:40,840
+خطوط عند خط في النص وخط أعلى خط في النص مكتوب عليه
+
+500
+00:48:40,840 --> 00:48:45,620
+بوينت فايف وخط في النص اللي هو SE على SE برايم على
+
+501
+00:48:45,620 --> 00:48:49,440
+SE بيساوي بوينت فايف وهنا عندي SE برايم على SA
+
+502
+00:48:49,440 --> 00:48:53,900
+اللي هي بوينت ستة وهنا عندي SE برايم على SU
+
+503
+00:48:53,900 --> 00:49:01,120
+بيساو بوينت أربعة الخط اللي في النص بيمثّل
+
+504
+00:49:02,770 --> 00:49:07,950
+خمسين في المئة reliability للبيانات خمسين في المئة
+
+505
+00:49:07,950 --> 00:49:11,370
+reliability للـ data يعني إيش يعني خمسين في المئة؟
+
+506
+00:49:11,370 --> 00:49:18,290
+معناته experimentally أو هذا الخط بيمثّل أن هذا جاية
+
+507
+00:49:18,290 --> 00:49:22,930
+واقع في النص ممكن تكون القيم الحقيقية احتمال تكون
+
+508
+00:49:22,930 --> 00:49:25,750
+خمسين في المئة أعلى أو أقل خمسين في المئة أعلى أو
+
+509
+00:49:25,750 --> 00:49:34,790
+أقل الـ curve fitting بين الـ SE برايم والـ SUT for
+
+510
+00:49:34,790 --> 00:49:40,030
+50% reliability of data بيعطينا علاقة هذه SE برايم
+
+511
+00:49:40,030 --> 00:49:44,330
+بيساوي نص SUT إذا كانت SUT أقل من 200 كيلو pound
+
+512
+00:49:44,330 --> 00:49:48,450
+per square inch وبتساوي 100 كيلو pound per square
+
+513
+00:49:48,450 --> 00:49:51,130
+inch إذا كانت SUT أكبر من 200 كيلو pound per
+
+514
+00:49:51,130 --> 00:49:55,430
+square inch نرجع ثاني للـ curve عندنا هيّا تقريباً
+
+515
+00:49:58,250 --> 00:50:05,350
+يعني تقريباً جاية في حدود اللي عندها المئة ومية و
+
+516
+00:50:05,350 --> 00:50:09,670
+عشرة تقريباً مئة وخمسة هذا الخط اللي في النص يعني
+
+517
+00:50:09,670 --> 00:50:16,170
+هنا عند ميتين ميجا لحد ميتين ميجا هاي ميتين ميجا
+
+518
+00:50:16,170 --> 00:50:20,990
+تقريباً
+
+519
+00:50:20,990 --> 00:50:26,250
+حتكون علاقة خطية اللي في النص
+
+520
+00:50:30,480 --> 00:50:36,740
+يعني إذا كانت الـ SUT أقل من 200 كيلو pound per
+
+521
+00:50:36,740 --> 00:50:40,360
+square inch بتكون الـ SE برايم بيساوي نص الـ SUT
+
+522
+00:50:40,360 --> 00:50:45,660
+إذا كانت الـ SUT أكبر من 200 بتصير الـ SE برايم
+
+523
+00:50:45,660 --> 00:50:50,200
+بتثبت الـ SE برايم بتثبت معناته في علاقة بين الـ
+
+524
+00:50:50,200 --> 00:50:55,330
+tensile strength والـ SE برايم هي الـ endurance
+
+525
+00:50:55,330 --> 00:50:59,770
+limit لـ standard tensile specimen standard tensile
+
+526
+00:50:59,770 --> 00:51:03,050
+specimen يعني التجربة انعملت for the case of
+
+527
+00:51:03,050 --> 00:51:12,910
+completely reversed bending loading طيب
+
+528
+00:51:12,910 --> 00:51:13,030
+for design
+
+529
+00:51:25,000 --> 00:51:28,340
+an approximation of the idealized S-N diagram is
+
+530
+00:51:28,340 --> 00:51:35,780
+needed لحسابات التصميم محتاجين نعمل تقريب للـ ideal
+
+531
+00:51:35,780 --> 00:51:42,680
+S-N diagram عشان
+
+532
+00:51:42,680 --> 00:51:50,040
+نـ estimate fatigue
+
+533
+00:51:50,040 --> 00:51:53,900
+strength عند عشرة أس تلاتة أو استلاتة نرجع للـ S-N diagram
+
+534
+00:51:59,760 --> 00:52:09,380
+هذا الـ S-N diagram هرسمه هنا برا اللي حقيقه هنا
+
+535
+00:52:09,380 --> 00:52:16,120
+عندي عدد سايكلز عشرة أس تلاتة وهنا عشرة أس ستة
+
+536
+00:52:16,120 --> 00:52:23,860
+وهنا حتكون عندي SUT وهنا عشرة أس صفر يعني واحد
+
+537
+00:52:28,590 --> 00:52:31,790
+لاحظوا الـ curve ممكن أنا أقسمه لـ 3 مناطق عند
+
+538
+00:52:31,790 --> 00:52:37,330
+المنطقة هذه العلاقة خطية slope بين واحد وألف وبين
+
+539
+00:52:37,330 --> 00:52:42,250
+ألف ومليون برضه علاقة خطية بس بـ slope مختلف الآن
+
+540
+00:52:42,250 --> 00:52:47,890
+حنتبع
+
+541
+00:52:47,890 --> 00:52:52,230
+مع بعض الآن احنا حكينا الـ total strain amplitude
+
+542
+00:52:52,230 --> 00:52:55,970
+مكون من جزئين elastic strain amplitude وplastic
+
+543
+00:52:55,970 --> 00:52:59,830
+strain amplitude الـ elastic strain amplitude دلتا
+
+544
+00:52:59,830 --> 00:53:05,970
+إبسيلون الإيلاستيكية على اتنين بيساوي سيجما إف برايم
+
+545
+00:53:05,970 --> 00:53:12,610
+على E السابق إن حكينا في اتنين N أس B
+
+546
+00:53:19,630 --> 00:53:23,450
+define specimen fatigue strength at a specified
+
+547
+00:53:23,450 --> 00:53:36,710
+number of cycles يعني حنسمي هذا حنسميه SF  SF'
+
+548
+00:53:38,290 --> 00:53:41,990
+N وهذه إيش N
+
+549
+00:53:43,330 --> 00:53:48,090
+for a specified number of cycle أو for a given
+
+550
+00:53:48,090 --> 00:53:52,910
+stress amplitude sf n برايم حيعيش N cycles حيكون
+
+551
+00:53:52,910 --> 00:53:56,570
+الـ sf برايم
+
+552
+00:53:56,570 --> 00:54:04,330
+N بيساوي E في دلتا إبسيلون الإيلاستيكية على اتنين من
+
+553
+00:54:04,330 --> 00:54:09,250
+أين أجت هذه؟ أجت هذه من هنا إذا أنا دخلت الـ
+
+554
+00:54:09,250 --> 00:54:10,110
+plastic range
+
+555
+00:54:13,310 --> 00:54:20,890
+ونزلت عملت unloading هذا بيظهر عنده اللي هو الـ
+
+556
+00:54:20,890 --> 00:54:26,570
+دلتا إبسيلون البلاستيكية على اتنين وهذا
+
+557
+00:54:26,570 --> 00:54:33,410
+الـ دلتا إبسيلون الإيلاستيكية على اتنين وهذا عاش الـ
+
+558
+00:54:33,410 --> 00:54:43,960
+slope سيجما وهذا سوف تكون أسفل في الـ prime فهذا
+
+559
+00:54:43,960 --> 00:54:50,740
+إيش يا عزيزي؟ هذا موضح في الشكل هذا خط الـ slope
+
+560
+00:54:50,740 --> 00:55:00,140
+بتاع إيش؟ يعني خط المثلث هذا حتكون
+
+561
+00:55:00,140 --> 00:55:06,030
+الـ slope is إيش؟ يعني حتكون أسفل في الـ prime حتكون
+
+562
+00:55:06,030 --> 00:55:10,090
+بساو E في دلتا إبسيلون الإيلاستيكية على 2 من هنا جاءت
+
+563
+00:55:10,090 --> 00:55:15,530
+العلاقة هذه اللي
+
+564
+00:55:15,530 --> 00:55:21,990
+حنعوض حتكون بيساوي E في الـ دلتا إبسيلون الإيلاستيكية
+
+565
+00:55:21,990 --> 00:55:29,550
+على 2 اللي هي هذه سيجما إف برايم على E في 2N  أس B
+
+566
+00:55:29,550 --> 00:55:38,100
+حتروح E مع E حتصفي بيساوي سيجما إف برايم في 2N أس B
+
+567
+00:55:38,100 --> 00:55:41,840
+اللي هي الـ fatigue strength for a specified number of
+
+568
+00:55:41,840 --> 00:55:44,140
+cycles is given by this equal to سيجما إف برايم
+
+569
+00:55:44,140 --> 00:55:51,700
+بيساو 2N أس B لو
+
+570
+00:55:51,700 --> 00:55:57,720
+كانت الـ N عشرة أس تلاتة يعني ألف حتكون الـ fatigue
+
+571
+00:55:57,720 --> 00:56:03,200
+strength SF برايم لعمر عشرة أس تلاتة يعني لعمر ألف
+
+572
+00:56:03,200 --> 00:56:10,220
+cycle حتكون بيساوي سيجما إف برايم في اتنين في عشرة أس
+
+573
+00:56:10,220 --> 00:56:19,840
+تلاتة أس B هذه
+
+574
+00:56:19,840 --> 00:56:23,660
+حتساوي F
+
+575
+00:56:23,660 --> 00:56:26,860
+في SUT
+
+576
+00:56:37,130 --> 00:56:40,550
+يعني هذا اللي بحكي لما أنا أحكي اللي هو الـ
+
+577
+00:56:40,550 --> 00:56:44,330
+fatigue strength لألف cycle بيساوي سيجما إف برايم
+
+578
+00:56:44,330 --> 00:56:48,720
+في اتنين في عشرة تلاتة أس B اللي له قيمة معينة
+
+579
+00:56:48,720 --> 00:56:55,140
+أنا مش حعرفها هي عبارة عن some fraction of SUT
+
+580
+00:56:55,140 --> 00:57:00,160
+ممكن تكون يعني بوينت 75 SUT ممكن تكون بوينت 8 SUT
+
+581
+00:57:00,160 --> 00:57:03,320
+ممكن تكون بوينت 5 SUT ممكن one point one SUT
+
+582
+00:57:03,320 --> 00:57:07,360
+معناته اللي بحكي أنه بغض النظر على قيمة الـ fatigue
+
+583
+00:57:07,360 --> 00:57:10,920
+strength for one thousand cycle it will be some
+
+584
+00:57:10,920 --> 00:57:14,240
+fraction of the tensile strength of the specimen
+
+585
+00:57:15,750 --> 00:57:21,430
+يعني في الحالة هذه الـ F حيكون بيساوي سيجما إف في
+
+586
+00:57:21,430 --> 00:57:27,670
+برايم في اتنين في عشرة أس تلاتة أس B على SUT
+
+587
+00:57:27,670 --> 00:57:38,390
+طيب
+
+588
+00:57:38,390 --> 00:57:41,550
+الـ
+
+589
+00:57:41,550 --> 00:57:47,200
+SAE اللي هي Society of Automotive Engineers Society
+
+590
+00:57:47,200 --> 00:57:49,620
+of Automotive Engineers عملت له approximation
+
+591
+00:57:49,620 --> 00:57:52,940
+للـ سيجما إف برايم  موضحة علاقة للسيجما إف برايم
+
+592
+00:57:52,940 --> 00:57:55,820
+بساوِي SUT في حالة الوحدات الإنجليزية بساوي SUT
+
+593
+00:57:55,820 --> 00:58:01,410
+زائد خمسين أو في حالة الوحدات المترية الـ سيجما إف
+
+594
+00:58:01,410 --> 00:58:04,690
+برايم بيساوي SUT زائد 345 ميجا بس كده هذه الـ
+
+595
+00:58:04,690 --> 00:58:08,310
+equation is given by society of automotive
+
+596
+00:58:08,310 --> 00:58:14,330
+engineer في حالة كانت الـ hardness  برايم للـ material
+
+597
+00:58:14,330 --> 00:58:16,130
+تحت الدراسة أقل من 500
+
+598
+00:58:30,470 --> 00:58:34,670
+الآن ممكن تكون عندي هاي هذه كمان ممكن أي نقطة هذه
+
+599
+00:58:34,670 --> 00:58:45,250
+هذه هذه SFN' هذه N الآن عند النقطة هذه عند هذه N
+
+600
+00:58:45,250 --> 00:58:53,890
+NE وهنا الـ stress level إيش بيكون SE'
+
+601
+00:58:55,540 --> 00:59:01,580
+SE' يعني at the endurance limit at الـ endurance
+
+602
+00:59:01,580 --> 00:59:05,500
+limit
+
+603
+00:59:05,500 --> 00:59:16,680
+بتكون دي الـ SF' بيساوي SE' والـ N بيساوي NE معناته
+
+604
+00:59:16,680 --> 00:59:21,740
+لما نعوّض في هذه المعادلة هذه المعادلة حنلاقي دي SE'
+
+605
+00:59:25,380 --> 00:59:32,540
+بساوِي سيجما إف برايم في 2N عند الـ endurance limit E
+
+606
+00:59:32,540 --> 00:59:40,400
+أس B لو أخدت log للطرفين  حيكون عندي log خلّيني أقسم
+
+607
+00:59:40,400 --> 00:59:47,300
+الطرفين على سيجما إف برايم حيكون عندي SE برايم على
+
+608
+00:59:47,300 --> 00:59:53,560
+سيجما إف برايم بيساوي 2N E أس B أخد log للطرفين
+
+609
+00:59:53,560 --> 00:59:59,740
+حيكون عندي log الـ SA برايم على الـ سيجما إف برايم
+
+610
+00:59:59,740 --> 01:00:07,440
+حتكون بيساوي B في log 2N
+
+611
+01:00:07,440 --> 01:00:18,640
+معناته B حتكون بيساوي log الـ SA برايم على الـ
+
+612
+01:00:18,640 --> 01:00:26,650
+سيجما إف برايم على log الاتنين و إيش طبعاً هنا عامل
+
+613
+01:00:26,650 --> 01:00:31,310
+ناقص في الكتاب بس انتبهوا هنا عنده مش أنا عامل
+
+614
+01:00:31,310 --> 01:00:34,730
+هنا SE برايم على سيجما إف برايم هو عامل هنا العكس
+
+615
+01:00:34,730 --> 01:00:38,210
+سيجما إف برايم على SE برايم اللي هي بيساوي ناقص
+
+616
+01:00:38,210 --> 01:00:42,650
+ناقص log سيجما SE برايم على سيجما إف برايم فهذه
+
+617
+01:00:42,650 --> 01:00:46,170
+صحيحة وهذه إيش وهذه صحيحة بس انتبهوا هنا عنده SE
+
+618
+01:00:46,170 --> 01:00:48,810
+برايم على سيجما إف برايم هنا عنده سيجما إف برايم على
+
+619
+01:00:48,810 --> 01:00:54,450
+SE برايم لأن هنا عنده log scale معناته الـ B معطى بـ
+
+620
+01:00:54,450 --> 01:01:00,670
+الـ equation 612 الصفحة هذه تلخيص الكلام اللي
+
+621
+01:01:00,670 --> 01:01:01,190
+حكيناه
+
+62
+
+667
+01:05:41,690 --> 01:05:49,630
+semi log scale هتكون الأسقف في الفترة من عشر أس
+
+668
+01:05:49,630 --> 01:06:00,630
+ثلاثة عشر أس ستة بالسوء A في N أس B طيب
+
+669
+01:06:00,630 --> 01:06:08,000
+في عندي نقطتين يعني النقطة الأولى at عشرة أس ثلاثة
+
+670
+01:06:08,000 --> 01:06:14,400
+يعني N بالسوية عشرة أس ثلاثة، ال N بالسوية عشرة أس
+
+671
+01:06:14,400 --> 01:06:22,500
+ثلاثة كون أندي الـ S F بالسوية F S U T يعني نعوض
+
+672
+01:06:22,500 --> 01:06:34,630
+هنا عندي F S U T بتساوي A في عشرة أس ثلاثة أس B
+
+673
+01:06:34,630 --> 01:06:42,870
+هاي معادلة واحدة و at n بالساوية عشرة أس ستة
+
+674
+01:06:42,870 --> 01:06:48,770
+بتكون الـ S F بالساوية S E prime أو S E كده
+
+675
+01:06:48,770 --> 01:06:53,530
+نسميها S E يعني حيكون حنعود أن S F بـ S E
+
+676
+01:06:53,530 --> 01:07:03,450
+بساوي A في عشرة أس ستة أس B هاي معادلة اثنين
+
+677
+01:07:06,810 --> 01:07:14,070
+يعني لو قسمت اثنين على .. على أو واحد على اثنين
+
+678
+01:07:14,070 --> 01:07:23,330
+يعني نحكي divide واحد على اثنين، هيكون عندي F S U T
+
+679
+01:07:23,330 --> 01:07:34,730
+على S E، هتروح A مع A هتكون عشر أقصد ثلاثة أقصد B
+
+680
+01:07:35,840 --> 01:07:44,080
+على عشرة أس ستة أس B، المنطقة هتكون عشرة أس
+
+681
+01:07:44,080 --> 01:07:49,580
+ثلاثة على عشرة أس ستة، هتكون عشرة أس سالب ثلاثة
+
+682
+01:07:49,580 --> 01:07:59,060
+أس B يعني هتساوي عشرة أس سالب ثلاثة B، يعني لو
+
+683
+01:07:59,060 --> 01:08:11,080
+أخدت log الطرفين، هيكون دي log الـ F S U T على S A
+
+684
+01:08:11,080 --> 01:08:14,100
+بتساوي
+
+685
+01:08:14,100 --> 01:08:21,940
+ناقص ثلاثة B log العشرة، log العشرة بيساوي واحد
+
+686
+01:08:21,940 --> 01:08:28,780
+يعني هذا معناته هتساوي minus ثلاثة B، يعني B هتساوي
+
+687
+01:08:28,780 --> 01:08:49,310
+minus ثلث الـ log F S U T على S E طيب
+
+688
+01:08:49,310 --> 01:08:53,830
+معناته الـ B بتساوي ناقص ثلث الـ log F S U T على S E
+
+689
+01:09:08,780 --> 01:09:19,580
+إذا كان عندي إذا كان عندي إذا كان عندي إذا
+
+690
+01:09:19,580 --> 01:09:19,820
+كان عندي إذا كان عندي إذا كان عندي إذا كان عندي
+
+691
+01:09:19,820 --> 01:09:20,280
+إذا كان عندي إذا كان عندي إذا كان عندي إذا كان
+
+692
+01:09:20,280 --> 01:09:20,340
+كان عندي إذا كان عندي إذا كان عندي إذا كان عندي
+
+693
+01:09:20,340 --> 01:09:21,140
+إذا كان عندي إذا كان عندي إذا كان عندي إذا كان
+
+694
+01:09:21,140 --> 01:09:21,760
+عندي إذا كان عندي إذا كان عندي إذا كان عندي إذا
+
+695
+01:09:21,760 --> 01:09:22,480
+كان عندي إذا كان عندي إذا كان عندي إذا كان عندي
+
+696
+01:09:22,480 --> 01:09:25,560
+إذا كان عندي إذا كان عندي إذا كان عندي إذا كان
+
+697
+01:09:25,560 --> 01:09:25,580
+عندي إذا كان عندي إذا كان عندي إذا كان عندي إذا
+
+698
+01:09:25,580 --> 01:09:25,680
+كان عندي إذا كان عندي إذا كان عندي إذا كان عندي
+
+699
+01:09:25,680 --> 01:09:36,000
+إذا كان عندي إذا كان عندي إذا كان عندي إذا كان
+
+700
+01:09:36,000 --> 01:09:42,620
+عندي إذا كان عندي اسمه يعني هتكون الـ sigma
+
+701
+01:09:42,620 --> 01:09:58,300
+reversal، هيكون
+
+702
+01:09:58,300 --> 01:10:03,360
+الـ sigma reversal، على
+
+703
+01:10:03,360 --> 01:10:09,780
+A بتساوي N أس B، لو أخدت log الطرفين، هيكون log sigma
+
+704
+01:10:09,780 --> 01:10:17,740
+reversible على A بتساوي B، أو ممكن أحكي أنه مباشرة
+
+705
+01:10:17,740 --> 01:10:23,020
+عارف أنه نجرب أخد الـ log إن الـ N بتساوي sigma
+
+706
+01:10:23,020 --> 01:10:30,750
+reversible على A أس واحد على B، و B إحنا حسبناها اللي
+
+707
+01:10:30,750 --> 01:10:39,870
+هي ناقص ثلث الـ log اللي هي F S U T على الـ S
+
+708
+01:10:43,860 --> 01:10:47,060
+طبعاً الـ typical S N underground is only applicable
+
+709
+01:10:47,060 --> 01:10:51,580
+for a completely reversed stress situation، لأن هو
+
+710
+01:10:51,580 --> 01:10:55,720
+هي كان عمل لما أنا عملت جبت الـ standard specimen
+
+711
+01:10:55,720 --> 01:10:59,000
+كان متعرض لـ completely reversed stress، completely
+
+712
+01:10:59,000 --> 01:11:03,880
+reversed stress، وبالتالي الـ equations هذه is
+
+713
+01:11:03,880 --> 01:11:06,180
+applicable for a completely reversed stress
+
+714
+01:11:06,180 --> 01:11:10,370
+situation، for other stress situations لحالات stress
+
+715
+01:11:10,370 --> 01:11:13,810
+situations اللي الـ stress بيكونش completely
+
+716
+01:11:13,810 --> 01:11:17,530
+reversed، a completely reversed stress with the
+
+717
+01:11:17,530 --> 01:11:21,510
+same life expectancy must be used on the S
+
+718
+01:11:21,510 --> 01:11:24,930
+N underground، بدنا نحسب اللي هو equivalent
+
+719
+01:11:24,930 --> 01:11:30,150
+equivalent completely reversed stress اللي بيعطي
+
+720
+01:11:30,150 --> 01:11:35,430
+نفس العمر للـ stress level الحقيقي أو الـ loading
+
+721
+01:11:35,430 --> 01:11:36,070
+الحقيقي
+
+722
+01:11:40,640 --> 01:11:45,060
+إحنا so far عملنا المعادلة بين عشرة أس ثلاثة
+
+723
+01:11:45,060 --> 01:11:51,290
+وعشرة أس ستة برضه في الفترة العمر بين واحد و 10 أس
+
+724
+01:11:51,290 --> 01:11:56,930
+ثلاثة، ممكن أعمل معادلة خطية بنفس الـ logic السابق، هتطلع
+
+725
+01:11:56,930 --> 01:12:06,330
+المعادلة، الـ S F بيساوي S U T في N أس log F على ثلاثة هذا
+
+726
+01:12:06,330 --> 01:12:12,830
+في حالة، طبعاً المعادلة هتتم اشتقاقها based on two
+
+727
+01:12:12,830 --> 01:12:17,940
+points، اللي هي one point اللي هي هذه واحدة و S U T و
+
+728
+01:12:17,940 --> 01:12:21,900
+النقطة الثانية اللي هي عشرة أس ثلاثة و F S U T
+
+729
+01:12:21,900 --> 01:12:26,820
+عملت linear fit بين النقطتين هدول وحسبت اللي هي S
+
+730
+01:12:26,820 --> 01:12:42,500
+F بتساوي S U T في N أس log F على ثلاثة، شوف
+
+731
+01:12:42,500 --> 01:12:42,920
+example
+
+732
+01:13:03,010 --> 01:13:11,730
+given a 1050 hot rolled steel، حديد رقمه عشرة خمسين
+
+733
+01:13:11,730 --> 01:13:15,670
+hot rolled، عشرة خمسين، نسبة الكربون فيه نصف بالمية
+
+734
+01:13:15,670 --> 01:13:20,810
+point five percent، estimate the rotating beam
+
+735
+01:13:20,810 --> 01:13:31,810
+endurance limit، بده أحسب الـ S E prime الآن
+
+736
+01:13:32,930 --> 01:13:37,510
+الـ S E Prime، نرجع
+
+737
+01:13:37,510 --> 01:13:44,050
+للمعادلات، هي
+
+738
+01:13:44,050 --> 01:13:50,530
+هذه، الـ S E Prime بتساوي، في حتة الـ English net
+
+739
+01:13:50,530 --> 01:14:00,450
+بتساوي نص الـ S U T، إذا كانت الـ S U T
+
+740
+01:14:03,000 --> 01:14:07,480
+أقل أو يساوي 200 كيلو pound per square inch، اللي
+
+741
+01:14:07,480 --> 01:14:13,500
+هي عبارة عن 1400 ميجاباسكال، أو
+
+742
+01:14:13,500 --> 01:14:20,620
+بيساوي 100 كيلو pound per square inch، لو تكون الـ
+
+743
+01:14:20,620 --> 01:14:29,360
+S U T أكبر من 200 كيلو pound per square inch، أو بالـ
+
+744
+01:14:29,360 --> 01:14:35,240
+metric units اللي هي عبارة عن 700 ميجاباسكال، لما
+
+745
+01:14:35,240 --> 01:14:42,180
+الـ S U T أكبر من 1400 ميجاباسكال، هذه الأسئلة
+
+746
+01:14:42,180 --> 01:14:47,060
+الإبراهيمية، ما أنا أتبَع الزمن، إيش أشوف
+
+747
+01:14:47,060 --> 01:14:52,360
+الـ S U T، الـ S U T ما هو اللي هجيبه، هجيبه من
+
+748
+01:14:52,360 --> 01:14:55,940
+الجداول، نروح على الـ appendix في الكتاب
+
+749
+01:15:01,980 --> 01:15:09,580
+هناك كده لنا اللي هو الـ
+
+750
+01:15:09,580 --> 01:15:14,940
+ألف وخمسين ألف
+
+751
+01:15:14,940 --> 01:15:17,500
+وخمسين إيه؟
+
+752
+01:15:28,290 --> 01:15:32,870
+معناته من تابل A واحد وعشرين، تابل A واحد و
+
+753
+01:15:32,870 --> 01:15:40,070
+عشرين، هو حاكيه ليه الحديد
+
+754
+01:15:40,070 --> 01:15:54,250
+عند ألف وخمسين خينا
+
+755
+01:15:54,250 --> 01:15:56,010
+نطلع على الـ end notes
+
+756
+01:16:15,340 --> 01:16:21,520
+عندي ألف وخمسين hot
+
+757
+01:16:21,520 --> 01:16:22,720
+rolled
+
+758
+01:16:24,900 --> 01:16:31,620
+steel، طالع عندي هنا في جدول، عندي ألف وخمسين في
+
+759
+01:16:31,620 --> 01:16:34,840
+quenched and tempered، في ثلاثة أنواع، quenched and
+
+760
+01:16:34,840 --> 01:16:41,160
+tempered، هين
+
+761
+01:16:41,160 --> 01:16:47,720
+معطيني درجة الحرارة، هين
+
+762
+01:16:47,720 --> 01:16:51,840
+عندي normalized، عندي annealed
+
+763
+01:16:53,500 --> 01:16:57,480
+و هي المعطلة الـ tensile و tensile strength، خليني
+
+764
+01:16:57,480 --> 01:17:18,580
+بس أعلم على المنطقة هذه، خليني
+
+765
+01:17:18,580 --> 01:17:19,600
+أعلم على المنطقة هذه
+
+766
+01:17:23,890 --> 01:17:27,390
+لاحظوا quenched and tempered، عند أربعمائة فيهران
+
+767
+01:17:27,390 --> 01:17:30,950
+.. عند متين وخمس فيهران، هاي بتعطينا الـ .. الـ .. الـ
+
+768
+01:17:30,950 --> 01:17:33,710
+.. الـ ultimate tensile strength، ألف ومية وعشرين
+
+769
+01:17:33,710 --> 01:17:37,030
+عند أربعمائة وخمسة وعشر فيهران، هاي بتعطينا ألف
+
+770
+01:17:37,030 --> 01:17:42,190
+وتسعين، عند سبعمية وسبعتاشر بيعطينا الـ .. الـ tensile
+
+771
+01:17:42,190 --> 01:17:46,210
+strength، سبعمية وسبعة عشر، normalized سبعمية وثمانية
+
+772
+01:17:46,210 --> 01:17:51,720
+وأربعين، and yield ستمية وستة وثلاثين، واضح أن عندنا
+
+773
+01:17:51,720 --> 01:17:57,580
+في المعلومات في نقص، الآن الحديد الـ ألف وخمسين
+
+774
+01:17:57,580 --> 01:18:01,220
+خواصه الميكانيكية بتعتمد على المعالجة الحرارية اللي
+
+775
+01:18:01,220 --> 01:18:04,640
+بتستعمل، يعني واضح أن عندي هنا معالجات مختلفة هنا
+
+776
+01:18:04,640 --> 01:18:10,580
+عم أعمل quenching and tempering، يعني صار تبريد مفاجئ
+
+777
+01:18:10,580 --> 01:18:14,200
+من الـ austenite range، يعني حوالي تسعمائة درجة لحد
+
+778
+01:18:14,200 --> 01:18:18,360
+حوالي متين وخمسة، طبعاً أكيد هيكون الحديد قاسي، إذا
+
+779
+01:18:18,360 --> 01:18:23,180
+بتروحوا على الـ الـ الـ eutectoid steel الـ T-T diagram
+
+780
+01:18:23,180 --> 01:18:30,040
+في الـ material science، بيكون
+
+781
+01:18:30,040 --> 01:18:35,880
+عنده جراين
+
+782
+01:18:35,880 --> 01:18:36,540
+زي هيك
+
+783
+01:18:41,370 --> 01:18:45,030
+أنت بتحكي في حدود اللي هو الـ temper، لحجم 2 و5
+
+784
+01:18:45,030 --> 01:18:48,470
+يعني في الـ range هذا، يعني على الأغلب هيكونش
+
+785
+01:18:48,470 --> 01:18:54,610
+عندهين .. هين، بـ fine و هين عندنا perlite .. هين
+
+786
+01:18:54,610 --> 01:19:04,450
+.. هين .. هين .. هين عند course perlite هذا
+
+787
+01:19:04,450 --> 01:19:08,470
+material science، و هذا fine perlite
+
+788
+01:19:11,370 --> 01:19:16,510
+طب من ناحية strength، البداية أقوى من الـ fine per
+
+789
+01:19:16,510 --> 01:19:19,670
+lite، و الـ fine perlite أقوى من الـ coarse per
+
+790
+01:19:19,670 --> 01:19:23,090
+lite، فمعناته الـ strength بتاعة الحديد، إن أنا مثلاً
+
+791
+01:19:23,090 --> 01:19:26,310
+ببدأ من الـ austenite range و ببرد مثلاً لدرجة حرارة
+
+792
+01:19:26,310 --> 01:19:31,210
+بعدين ببرد الغرفة، أو مثلاً ممكن أجي زي هيك
+
+793
+01:19:34,230 --> 01:19:37,550
+فبعتمد على نوع الخواص الميكانيكية بتعتمد على نوع
+
+794
+01:19:37,550 --> 01:19:41,030
+المعالجات الحرارية، أنا ما عنديش اللي معلومات كافية، فبغض
+
+795
+01:19:41,030 --> 01:19:43,950
+النظر، أفرض أن هو الحديد الأول هذا، أفرض أن هو
+
+796
+01:19:43,950 --> 01:19:48,110
+quenched and tempered، يعني كانت الـ S U T عنده الـ
+
+797
+01:19:48,110 --> 01:19:53,270
+S U T بتساوي
+
+798
+01:19:53,270 --> 01:19:57,770
+مئة
+
+799
+01:19:57,770 --> 01:19:58,890
+وثلاثة وستين
+
+800
+01:20:02,370 --> 01:20:05,810
+kilo pound per square inch، هذا واضح أقل من 200
+
+801
+01:20:05,810 --> 01:20:13,790
+معناته الـ S E prime بتساوي نص الـ S U T، هتطلع واحد
+
+802
+01:20:13,790 --> 01:20:21,490
+وثمانين ونص kilo pound per square inch، نفس
+
+803
+01:20:21,490 --> 01:20:25,110
+المعدن، نفس المعدن، يعني أنا بملاحظة درسته في الـ
+
+804
+01:20:25,110 --> 01:20:27,590
+material science، نفس المعدن
+
+805
+01:20:31,400 --> 01:20:38,100
+يعني ممكن أوصله بالمعالجة الحرارية يمكن يعني من
+
+806
+01:20:38,100 --> 01:20:41,460
+خمسة لعشرة أضعاف الـ strength، بس أعمل معالجة حرارية
+
+807
+01:20:41,460 --> 01:20:45,680
+معينة، معناته بالمعالجات، السيناريوهات .. السيناريوهات
+
+808
+01:20:45,680 --> 01:20:49,640
+المعالجات الحرارية المختلفة، ممكن أحصل على infinite
+
+809
+01:20:49,640 --> 01:20:53,020
+number of properties للحديد، فكيف أنا بعمل معالجة
+
+810
+01:20:53,020 --> 01:20:57,060
+حرارية، كيف بحسّ .. كيف بتحكم خواص الحديد سواء في ..
+
+811
+01:20:57,060 --> 01:21:00,460
+من ناحية التقسية أو من ناحية الـ .. الـ .. الـ .. الـ
+
+812
+01:21:00,460 --> 01:21:04,340
+.. الـ annealing أو التطرية للحديد، يمكن أقصّ الحديد أو
+
+813
+01:21:04,340 --> 01:21:09,520
+أطرّيه من خلال معالجات حرارية معينة، هذا درسته
+
+814
+01:21:09,520 --> 01:21:15,300
+بالتفصيل في course of material science، هذا المطلوب
+
+815
+01:21:15,300 --> 01:21:19,540
+الأول، المطلوب الثاني، المطلوب الثاني، the endurance
+
+816
+01:21:19,540 --> 01:21:22,640
+strength of a polished rotating beam specimen
+
+817
+01:21:22,640 --> 01:21:27,660
+corresponding to 10 أس أربعة cycles to failure، بده الـ
+
+818
+01:21:27,660 --> 01:21:30,340
+S F، المطلوب الثاني
+
+819
+01:21:35,600 --> 01:21:41,020
+إذا كانت عندي الـ cycles في الـ N بتساوي عشرة أس
+
+820
+01:21:41,020 --> 01:21:52,720
+أربعة، بده الـ S F prime، أكمل هو الـ S F نرجع
+
+821
+01:21:52,720 --> 01:22:00,680
+للـ curve بتاعنا، فاكرين إحنا الـ curve جزّأناها لمناطق
+
+822
+01:22:02,200 --> 01:22:06,200
+المنطقة هذه من N بتساوي واحد لعشرة أس ثلاثة
+
+823
+01:22:06,200 --> 01:22:10,280
+و الخط هذا من عشرة أس ثلاثة لعشرة أس ستة، معناته
+
+824
+01:22:10,280 --> 01:22:15,000
+إحنا هنستخدم معادلة for N من عشرة أس ثلاثة لعشرة
+
+825
+01:22:15,000 --> 01:22:19,920
+أس ستة، معناته بتلزمنى معادلة الخط هذا اللي هي اللي هي
+
+826
+01:22:19,920 --> 01:22:28,300
+هذا الخط اللي هي S F، عندها الـ S F بتساوي A N أس B
+
+827
+01:22:28,300 --> 01:22:31,120
+طيب
+
+828
+01:22:33,400 --> 01:22:37,940
+الـ A بيساوي
+
+829
+01:22:37,940 --> 01:22:50,380
+F S U T الكل تربيع على S E طيب
+
+830
+01:22:50,380 --> 01:22:58,420
+ما أنا مطلوب أن أحسب إيه؟ الـ F، الـ S U T كانت عندي
+
+831
+01:22:58,420 --> 01:23:00,220
+مئة وثلاثة وستين
+
+832
+01:23:08,250 --> 01:23:13,890
+تقريباً هادي عندي point سبعة، ثمانية، point ثمانية
+
+833
+01:23:13,890 --> 01:23:20,810
+يعني تقريباً point سبعة وتلاتين
+
+834
+01:23:20,810 --> 01:23:28,510
+ها point سبعة، تسعة، ثلاثة، يعني ممكن أحكي F من
+
+835
+01:23:28,510 --> 01:23:38,860
+figure، F بتساوي الـ F بتساوي point سبعة، تسعة،
+
+836
+01:23:38,860 --> 01:23:46,840
+ثلاثة، من figure ستة، ثمانية عشر منها
+
+837
+01:23:46,840 --> 01:23:51,660
+بحسب الـ A هتكون بتساوي اللي هي point سبعة، تسعة،
+
+838
+01:23:51,660 --> 01:24:00,020
+ثلاثة، في الـ S U T مئة وثلاثة وستين الكل تربيع على
+
+839
+01:24:00,020 --> 01:24:06,180
+S E اللي هي واحد وثمانين ونص، بحسب الـ A
+
+840
+01:24:10,700 --> 01:24:17,380
+point سبعة، point
+
+841
+01:24:17,380 --> 01:24:28,520
+سبعة، تسعة، ثلاثة في مئة وثلاثة وستين، تقسيم
+
+842
+01:24:28,520 --> 01:24:31,740
+واحد
+
+843
+01:24:31,740 --> 01:24:36,520
+وثمانين و
+
+844
+01:24:36,520 --> 01:24:36,840
+نص
+
+
+889
+01:29:28,530 --> 01:29:32,730
+fatigue test بتطلب standard  أعينة معيارية الأعينة
+
+890
+01:29:32,730 --> 01:29:36,130
+المعيارية لها شكل معين و لها Polish بتكون
+
+891
+01:29:36,130 --> 01:29:39,930
+نعمة جدا رقم واحد ال loading بتاعها بيكون
+
+892
+01:29:39,930 --> 01:29:44,090
+completely reversed completely reversed bending
+
+893
+01:29:44,090 --> 01:29:49,170
+loading  الآن القطع الميكانيكية التي على أرض الواقع
+
+894
+01:29:49,170 --> 01:29:55,390
+بتكون مواصفاتها غير مطابقة للعينة المعيارية من حيث
+
+895
+01:29:55,390 --> 01:30:00,810
+الشكل الهندسي و من حيث ال finish و من حيث ال
+
+896
+01:30:00,810 --> 01:30:07,050
+loading و من حيث الظروف المحيطة، درجة الحرارة من
+
+897
+01:30:07,050 --> 01:30:11,110
+حيث ال reliability، فالظروف الحقيقية مختلفة عن
+
+898
+01:30:11,110 --> 01:30:16,050
+الظروف المعيارية. هذا يقودنا إلى أنه لو اختلفت.. لو
+
+899
+01:30:16,050 --> 01:30:19,030
+كانت الظروف الحقيقية أو القطع الميكانيكية تحت
+
+900
+01:30:19,030 --> 01:30:24,490
+الدراسة مختلفة عن الظروف المعيارية، فحص الإجهاد
+
+901
+01:30:24,490 --> 01:30:28,910
+التوتر، ال fatigue test، معناته we have to modify
+
+902
+01:30:29,780 --> 01:30:34,260
+القيمة التي حصلنا عليها من ال standard fatigue
+
+903
+01:30:34,260 --> 01:30:37,040
+test specimen.  كذلك، ال standard test
+
+904
+01:30:37,040 --> 01:30:42,780
+standard fatigue test بيصير لعينة معيارية التي لها
+
+905
+01:30:42,780 --> 01:30:46,100
+شكل معين، التي لها surface finish معينة، ال loading
+
+906
+01:30:46,100 --> 01:30:49,320
+بيكون completely reverse bending. على أرض الواقع ممكن
+
+907
+01:30:49,320 --> 01:30:52,940
+يكون ال loading torsional، ممكن يكون axial، ممكن
+
+908
+01:30:52,940 --> 01:30:57,420
+يكون bending، ممكن يكون combination بين axial أو
+
+909
+01:30:57,420 --> 01:31:00,400
+bending، بين bending و torsion، أو بين bending و  يطلع
+
+910
+01:31:00,400 --> 01:31:04,700
+نتائج.  في متغيرات كثيرة، الحجم، ال size، القطر تاع
+
+911
+01:31:04,700 --> 01:31:07,700
+القطعة الميكانيكية مختلف عن العينة المعيارية، its
+
+912
+01:31:07,700 --> 01:31:14,000
+surface finish مختلف، درجة الحرارة مختلفة، ممكن يكون
+
+913
+01:31:14,000 --> 01:31:17,400
+ال stress concentration.  في ظروف حقيقية مختلفة عن
+
+914
+01:31:17,400 --> 01:31:22,440
+الظروف المعيارية. هذا يتطلب أن أقوم بـ to modify
+
+915
+01:31:22,440 --> 01:31:24,880
+the endurance limit، to modify ال endurance limit، I
+
+916
+01:31:24,880 --> 01:31:30,400
+need some modification factors. معناته أحتاج أعدل
+
+917
+01:31:30,400 --> 01:31:36,000
+سأستخدم معادلة SE = K<sub>A</sub> K<sub>B</sub> K<sub>C</sub> K<sub>D</sub> K<sub>E</sub> K<sub>F</sub> S<sub>E</sub>'
+
+918
+01:31:36,000 --> 01:31:41,400
+الـ S<sub>E</sub>' هي ال endurance limit for a
+
+919
+01:31:41,400 --> 01:31:44,900
+standard tensile specimen under completely
+
+920
+01:31:44,900 --> 01:31:51,060
+reversed bending loading. ال K<sub>A</sub> factor بيعمل
+
+921
+01:31:51,060 --> 01:31:53,960
+correction لل surface condition، ال roughness
+
+922
+01:31:53,960 --> 01:31:59,070
+مختلفة، أو ال finish مختلف. ال K<sub>B</sub> بيعمل correction ل
+
+923
+01:31:59,070 --> 01:32:05,710
+ال size، القطر مثلاً في العينة المعيارية نصف إنش،  في قطعة
+
+924
+01:32:05,710 --> 01:32:10,450
+يمكن يكون إنش. ال K<sub>C</sub> بيعمل correction لل load
+
+925
+01:32:10,450 --> 01:32:14,920
+factor، ال load في حالة العينة المعيارية، الذي هو
+
+926
+01:32:14,920 --> 01:32:17,520
+bending، completely reversed bending، ممكن تكون
+
+927
+01:32:17,520 --> 01:32:22,020
+completely reversed… completely reversed torsion،
+
+928
+01:32:22,020 --> 01:32:24,900
+أو تكون axial loading، أو combination بين هذه
+
+929
+01:32:24,900 --> 01:32:29,520
+الأنواع من التحميلات المختلفة. الآن، العينة المعيارية تم
+
+930
+01:32:29,520 --> 01:32:33,140
+فحصها عند درجة حرارة الغرفة، لكن القطعة الميكانيكية
+
+931
+01:32:33,140 --> 01:32:39,730
+ممكن تكون قطعة في بيئة حرارتها مرتفعة مثلاً،
+
+932
+01:32:39,730 --> 01:32:45,130
+وبالتالي أحتاج أعدل البيانات. عندما  قلت S<sub>E</sub>'
+
+933
+01:32:45,130 --> 01:32:50,150
+بساهمت بنصف، ال S<sub>E</sub>' كانت for a fifty percent
+
+934
+01:32:50,150 --> 01:32:55,570
+reliability of the data. what if إذا كانت
+
+935
+01:32:55,570 --> 01:32:57,710
+reliability تسعين في المائة، أو خمسين في المائة،
+
+936
+01:32:57,710 --> 01:33:02,260
+أو تسعة في المائة. الـ K<sub>F</sub> موصول من
+
+937
+01:33:02,260 --> 01:33:05,400
+miscellaneous effects factor، يعني عامل تعديل
+
+938
+01:33:05,400 --> 01:33:10,180
+لشغلات كثيرة، يعني… يعني غير متوقع، ممكن يكون… هل
+
+939
+01:33:10,180 --> 01:33:13,720
+القطعة ممكن تشتغل في بيئة… في بيئة بحرية، يعني
+
+940
+01:33:13,720 --> 01:33:18,200
+عندك ملوحة عالية، ممكن تشتغل في بيئة كيميائية، ممكن
+
+941
+01:33:18,200 --> 01:33:24,500
+في عندك إجهادات residual stresses، ممكن تشتغل في
+
+942
+01:33:24,500 --> 01:33:29,210
+بيئة فيها إشعاع. ف… هذه التي يأخذ قرار فيها
+
+943
+01:33:29,210 --> 01:33:34,930
+المصمم، هو بيقدر أنه I need، أحتاج أنا أعدل
+
+944
+01:33:34,930 --> 01:33:39,850
+modification بنسبة ٥٠٪، بنسبة ٦٠٪، to take other
+
+945
+01:33:39,850 --> 01:33:45,510
+effects. المحاضرة القادمة سندرس ال factors هذه
+
+946
+01:33:45,510 --> 01:33:51,550
+بالتفصيل، كيف حساب كل factor على حدة، بهدف الوصول إلى
+
+947
+01:33:51,550 --> 01:33:55,330
+endurance limit للقطع الميكانيكية التي هي موجودة
+
+948
+01:33:55,330 --> 01:33:56,570
+على أرض الواقع
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/Y3Um_iLIIhU_postprocess.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/Y3Um_iLIIhU_postprocess.srt
new file mode 100644
index 0000000000000000000000000000000000000000..299bb79349daaa84307c4e5cd635f0b5b16f6d7f
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/Y3Um_iLIIhU_postprocess.srt
@@ -0,0 +1,3792 @@
+1
+00:00:04,980 --> 00:00:08,020
+السلام عليكم بسم الله الرحمن الرحيم اليوم هنبدأ
+
+2
+00:00:08,020 --> 00:00:11,900
+chapter جديد اللي هو fatigue failure resulting
+
+3
+00:00:11,900 --> 00:00:16,280
+from variable loading اللي هو انهيارات او فشل في
+
+4
+00:00:16,280 --> 00:00:21,240
+القطع الميكانيكية الناتجة عن الأحمال المتغيرة في
+
+5
+00:00:21,240 --> 00:00:26,800
+chapter خمسة غطينا الانهيارات في القطع الميكانيكية
+
+6
+00:00:26,800 --> 00:00:32,860
+الناتجة عن الأحمال الثابتةالموضوعات اللى هنغطيها
+
+7
+00:00:32,860 --> 00:00:36,880
+فى ال chapter هذا اللى هى مقدمة و تعريفات متعلقة
+
+8
+00:00:36,880 --> 00:00:41,360
+بالاجهاد المتواتر فى المعادن اللى هو fatigue in
+
+9
+00:00:41,360 --> 00:00:46,060
+metals ال methodological approach to fatigue
+
+10
+00:00:46,060 --> 00:00:51,120
+failure فى عملية التحليل و التصميم طرق حسابات
+
+11
+00:00:51,120 --> 00:00:54,500
+لاجهاد المتواتر fatigue life method اللى هى stress
+
+12
+00:00:54,500 --> 00:00:57,500
+life method و strain life method و linear elastic
+
+13
+00:00:57,500 --> 00:01:02,950
+fracture mechanics methodهنتعرف على ال endurance
+
+14
+00:01:02,950 --> 00:01:07,930
+limit الفتيك strength و بعدين how to modify
+
+15
+00:01:07,930 --> 00:01:14,290
+endurance limit of a standard فتيك specimen عشان
+
+16
+00:01:14,290 --> 00:01:18,330
+اخد فعل اعتبار المتغيرات الأخرى الواقعية وبالتالي
+
+17
+00:01:18,330 --> 00:01:22,450
+هنتطرق لل endurance limit modifying factors هنتعرف
+
+18
+00:01:22,450 --> 00:01:27,110
+على التركيز الإجهادي وحساسية المادة للخدوش
+
+19
+00:01:34,250 --> 00:01:38,810
+بعدين هنتعرف ناخد اللى هو بشكل عام ال .. ال .. how
+
+20
+00:01:38,810 --> 00:01:43,170
+to characterize ال .. ال .. ال variability فى ال
+
+21
+00:01:43,170 --> 00:01:47,650
+loading ممكن نوع ال loading يكون عندى ال .. يكون
+
+22
+00:01:47,650 --> 00:01:50,350
+عندى tensile loading أو bending loading أو
+
+23
+00:01:50,350 --> 00:01:53,230
+torsional loading أو any combination how to
+
+24
+00:01:53,230 --> 00:01:57,610
+characterize ال loading into one stress component
+
+25
+00:01:57,610 --> 00:02:00,710
+مع استخدام اللى هى ال design theories
+
+26
+00:02:03,880 --> 00:02:08,720
+نبدأ اولش اللي هو تقديم او بعض التقديم لل fatigue
+
+27
+00:02:08,720 --> 00:02:19,700
+in metals اول ملاحظة ال loading ممكن يكون متغير او
+
+28
+00:02:19,700 --> 00:02:26,380
+متكرر يعني مثلا لو اخدت انا الزنبارك في السيارة
+
+29
+00:02:26,380 --> 00:02:31,880
+عند هذه السيارة هذه
+
+30
+00:02:31,880 --> 00:02:38,010
+العجلاتو فى عندى هى نظام التعليق هنعمل صورة رسمها
+
+31
+00:02:38,010 --> 00:02:52,270
+أكبر وهى
+
+32
+00:02:52,270 --> 00:02:58,930
+عندى هى دولاب هى دولاب هى أكس و فى عندى نظام
+
+33
+00:02:58,930 --> 00:03:00,170
+التعليق زمبركات
+
+34
+00:03:04,730 --> 00:03:10,810
+الان السيارة و هي ماشية ال loading او التحميل على
+
+35
+00:03:10,810 --> 00:03:15,990
+الزنبارك بيكون متغير الان انا ممكن اكون ماشي على
+
+36
+00:03:15,990 --> 00:03:20,750
+أرض سهلية ممكن اطلع مطاب ممكن انزل عجورة فهذه
+
+37
+00:03:20,750 --> 00:03:27,130
+السلحة تزاد و بتعمل تغيير على الأحمال على الزنبارك
+
+38
+00:03:27,130 --> 00:03:34,000
+فممكن الأحمال ماتكونش ثابتةتكون متغيرة هذا يسمى
+
+39
+00:03:34,000 --> 00:03:41,880
+variable variable loading مثال تاني ممكن لو أخدنا
+
+40
+00:03:41,880 --> 00:03:49,940
+عضلة قلب الإنسان عضل قلب الإنسان التحميل عليها
+
+41
+00:03:49,940 --> 00:03:53,460
+متغير و ممكن نعمل إشي زي هيك
+
+42
+00:03:59,370 --> 00:04:06,550
+واضح انه ال loading variable
+
+43
+00:04:06,550 --> 00:04:10,530
+فمعناته
+
+44
+00:04:10,530 --> 00:04:15,370
+التحميل مش ثابت طبعا في امثلة كتير في ال engine
+
+45
+00:04:15,370 --> 00:04:26,970
+بتاع السيارة عند ال slider crank mechanism عند
+
+46
+00:04:26,970 --> 00:04:31,090
+هناالـ Piston بتاع السيارة لو أخدت ال connecting
+
+47
+00:04:31,090 --> 00:04:36,690
+rod ال connecting rod
+
+48
+00:04:36,690 --> 00:04:42,390
+طبعا ال anger velocity و ال anger acceleration لل
+
+49
+00:04:42,390 --> 00:04:48,070
+connecting rod متغيرة معناته ال inertia forces على
+
+50
+00:04:48,070 --> 00:04:51,510
+ال connecting rod متغيرة معناته ال loading متغيرة
+
+51
+00:04:51,510 --> 00:04:55,550
+فهيكون التحميل على ال connecting rod متغير
+
+52
+00:04:58,310 --> 00:05:02,750
+لأن في حالة القطع الميكانيكية المتعرضة لأحمال
+
+53
+00:05:02,750 --> 00:05:07,550
+متغيرة ممكن يصير ال failure ال mechanical element
+
+54
+00:05:07,550 --> 00:05:13,950
+عند stress أقل من ال lead strength لأن ال failure
+
+55
+00:05:13,950 --> 00:05:19,830
+بيصير بعد تكرار اكتئع عدد كبير من ال cycles of
+
+56
+00:05:19,830 --> 00:05:27,490
+variable loading ال failure عادة بيكونبالنسبة لنا
+
+57
+00:05:27,490 --> 00:05:33,050
+بيصيرنا كسر مفاجئ ومابيعطينيش تحذير مسبق انه هيصير
+
+58
+00:05:33,050 --> 00:05:35,810
+كسر بس وفي الحقيقة بيكون فيه ال failure اللي فترة
+
+59
+00:05:35,810 --> 00:05:42,410
+بدي بس انا اللي بشوفه كمستخدم بشوف فجأة انه صار
+
+60
+00:05:42,410 --> 00:05:52,330
+عندى كسر او failure بدون انظار مسبق ال
+
+61
+00:05:52,330 --> 00:05:54,990
+fatigue failure بيمرر تلت مراحل
+
+62
+00:06:00,250 --> 00:06:07,050
+اللي هو عندي three stages of
+
+63
+00:06:07,050 --> 00:06:14,210
+fatigue failure أول
+
+64
+00:06:14,210 --> 00:06:23,530
+مرحلة اللي هي crack initiation بعدين
+
+65
+00:06:23,530 --> 00:06:25,310
+crack propagation
+
+66
+00:06:29,630 --> 00:06:39,030
+بعدين اللي هو final ultimate fracture
+
+67
+00:06:39,030 --> 00:06:44,730
+يعني
+
+68
+00:06:44,730 --> 00:06:51,160
+في الأول تجدال repeated stress عن نقطة معينة ممكن
+
+69
+00:06:51,160 --> 00:06:54,360
+locally ادخل ال plastic range locally ادخل ال
+
+70
+00:06:54,360 --> 00:06:59,920
+plastic range يعني انا رسمت ال material ال stress
+
+71
+00:06:59,920 --> 00:07:04,580
+versus ال strain لحديد معين ممكن يكون الشكل هذا
+
+72
+00:07:04,580 --> 00:07:09,640
+ممكن انا local اكون في المنطقة هذه ادخل ادخل اللي
+
+73
+00:07:09,640 --> 00:07:14,040
+هو في ال plasticعن نقطة معينة إذا خدت لـ plastic
+
+74
+00:07:14,040 --> 00:07:17,740
+range عن نقطة معينة بيبدأ يصير تشقق بيبدأ يصير
+
+75
+00:07:17,740 --> 00:07:21,160
+عنده تشقق مع ال repetition of loading بيبدأ يصير
+
+76
+00:07:21,160 --> 00:07:25,140
+تشقق فالمرحلة اللي بسميها اللي هي بداية التشقق أو
+
+77
+00:07:25,140 --> 00:07:29,860
+crack initiation طبعا ال stress cycling مستمر
+
+78
+00:07:29,860 --> 00:07:34,980
+فبيبدأ ال crack ايش؟ توسع، تكبر، تزيد شوي شوي شوي
+
+79
+00:07:34,980 --> 00:07:37,540
+شوي شوي شوي شوي شوي شوي شوي شوي شوي شوي شوي شوي
+
+80
+00:07:37,540 --> 00:07:39,570
+شوي شوي شوي شوي شوي شوي شوي شوي شوي شويلحد ما ال
+
+81
+00:07:39,570 --> 00:07:43,130
+material اللي حقيقة حمض ال load او المقطع الحقيقي
+
+82
+00:07:43,130 --> 00:07:47,570
+بيقل حجمه لحد ما ال cross section يضعف شكل كبير و
+
+83
+00:07:47,570 --> 00:07:55,350
+يصير failure من خلال انه ال stress وصل ل ال
+
+84
+00:07:55,350 --> 00:07:58,330
+ultimate stress في ال material لان ال area ما لها
+
+85
+00:07:58,330 --> 00:08:06,130
+قلت و ال stress sigma بيساوي F على A يعني كل ما
+
+86
+00:08:06,130 --> 00:08:14,290
+تقل Aكل ما اتقل ال stress اشماله بزيد فحتصل مرحلة
+
+87
+00:08:14,290 --> 00:08:18,410
+انه ال cross section area صغر كتير فبنوصل ل ال
+
+88
+00:08:18,410 --> 00:08:26,150
+ultimate strength فبصير sudden failure انا
+
+89
+00:08:26,150 --> 00:08:29,430
+عندي هنا امثلة على fatigue failure في عندى shaft
+
+90
+00:08:29,430 --> 00:08:34,230
+عمودو فى عندى هنا key way عند ال key way فى عندى
+
+91
+00:08:34,230 --> 00:08:37,150
+sudden change فى ال cross section معناته هيصير
+
+92
+00:08:37,150 --> 00:08:40,370
+عندى stress concentration stress concentration
+
+93
+00:08:40,370 --> 00:08:44,110
+يعني ال stress level عند ال discontinuity هيرفع
+
+94
+00:08:44,110 --> 00:08:48,810
+بشكل كبير يعني هكون عندى ال stress بعيد عن النقطة
+
+95
+00:08:48,810 --> 00:08:53,910
+هذه مثلا يكون 100 ميجا لكن عندى stress
+
+96
+00:08:53,910 --> 00:08:57,710
+concentration factor هنا تلاتة معناته locally هكون
+
+97
+00:08:57,710 --> 00:09:03,540
+ال stress 300300 ميجا معناته انا ممكن اكون دخلت ال
+
+98
+00:09:03,540 --> 00:09:08,340
+plastic region فتبدأ عند هنا بيصير ايش ال crack ال
+
+99
+00:09:08,340 --> 00:09:10,980
+crack بتنتشر شوية شوية شوية شوية شوية شوية شوية
+
+100
+00:09:10,980 --> 00:09:14,820
+شوية لحد ما ال cross section يصغر بشكل كبير كتير
+
+101
+00:09:14,820 --> 00:09:18,760
+برفع ال stress level بشكل مفاجئ و بيصير كسر by
+
+102
+00:09:18,760 --> 00:09:22,380
+ultimate by ultimate tensile failure
+
+103
+00:09:30,050 --> 00:09:36,050
+الان في عندى ال three major fatigue life models في
+
+104
+00:09:36,050 --> 00:09:41,290
+عندى تلاتة models لتحليل الإجهادات المتواترة هذه
+
+105
+00:09:41,290 --> 00:09:48,570
+الطرق ال methods بتتوقع عمر القطعة بال cycles for
+
+106
+00:09:48,570 --> 00:09:53,770
+a certain loading level يعني كل الطرق هذهبتتوقع
+
+107
+00:09:53,770 --> 00:10:01,450
+عمر القطع الميكانيكية and لتحميل معين مثلا عند ميت
+
+108
+00:10:01,450 --> 00:10:07,150
+ميجا باسكال ممكن القطع هتتعيش مثلا مليون .. مليون
+
+109
+00:10:07,150 --> 00:10:13,590
+cycle عند متين ميجا باسكال ممكن تعيش تلتميت ألف
+
+110
+00:10:13,590 --> 00:10:14,790
+cycle و هكذا
+
+111
+00:10:23,230 --> 00:10:25,710
+الان ال fatigue life method يعني ال stress life
+
+112
+00:10:25,710 --> 00:10:28,290
+method و ال strain life method و ال linear elastic
+
+113
+00:10:28,290 --> 00:10:32,450
+fracture mechanics method احنا في ال course هذا
+
+114
+00:10:32,450 --> 00:10:35,830
+هنتعطى .. او هنتطرق للطريقة الأولى و الطريقة
+
+115
+00:10:35,830 --> 00:10:38,970
+التانية اللي هي ال stress life method و ال strain
+
+116
+00:10:38,970 --> 00:10:44,570
+life method في
+
+117
+00:10:44,570 --> 00:10:50,710
+ال stress life method بحضر عينة معيارية اللي لها
+
+118
+00:10:50,710 --> 00:10:56,760
+شكل معين ابعاد معينةوبعرضها ل repeating stress
+
+119
+00:10:56,760 --> 00:11:01,080
+while counting cycles to failure بعرضها دي ل
+
+120
+00:11:01,080 --> 00:11:07,200
+building stress ال building طبعا أشمله متغير بضع
+
+121
+00:11:07,200 --> 00:11:11,840
+نعملها building و أعد number of cycles لحد ما
+
+122
+00:11:11,840 --> 00:11:19,340
+العينة تنكسر طبعا طبيعة ال loading completely
+
+123
+00:11:19,340 --> 00:11:21,440
+reverse stress cycling ايش يعني completely
+
+124
+00:11:21,440 --> 00:11:22,560
+reversed يعني
+
+125
+00:11:30,070 --> 00:11:41,930
+يعني انا اخدت fiber هنا المقطع هنا هكون دائر في
+
+126
+00:11:41,930 --> 00:11:44,370
+لحظة معينة انا ممكن يكون عندي هنا ال fiber هذه
+
+127
+00:11:44,370 --> 00:11:49,820
+بالشكل هذاعندي هكون عليها شد tension هان tension
+
+128
+00:11:49,820 --> 00:11:54,240
+إذا بلف تسعين درجة النقطة هادي هصير هان هصير عندي
+
+129
+00:11:54,240 --> 00:11:59,580
+ال stress zero بلف كمان تسعين درجة بصير نقطة بتلف
+
+130
+00:11:59,580 --> 00:12:06,140
+تحت بصير عليها compression انضغاطبلف كمان تسعين
+
+131
+00:12:06,140 --> 00:12:09,460
+درجة zero كمان تسعين درجة tension بمعناته ان عندي
+
+132
+00:12:09,460 --> 00:12:13,840
+tension is zero tension is zero compression is
+
+133
+00:12:13,840 --> 00:12:17,620
+zero tension is zero compression وهكذا بمعناته
+
+134
+00:12:17,620 --> 00:12:21,880
+complete reverse ممكن نفس ال fiber يكون على مرة في
+
+135
+00:12:21,880 --> 00:12:24,920
+لحظة ما tension في لحظة ما compression لأنه بيكون
+
+136
+00:12:24,920 --> 00:12:30,160
+عندي bending بالشكل هذا طبعا
+
+137
+00:12:30,160 --> 00:12:38,600
+بغير ال loading طبعا في setupلجهاز اللى .. لل
+
+138
+00:12:38,600 --> 00:12:41,660
+fatigue tensile test طبعا هذا ال fatigue tensile
+
+139
+00:12:41,660 --> 00:12:45,120
+test اتعرفنا عليه من خلال course ال material
+
+140
+00:12:45,120 --> 00:12:48,640
+science و ال course mechanics of material اتعرضنا
+
+141
+00:12:48,640 --> 00:12:57,540
+بالتفصيل كيف نعمل الفحص طبعا عندي هى العينة عندي
+
+142
+00:12:57,540 --> 00:13:00,880
+هى العينة او في عندي one set up عندي هى العينة
+
+143
+00:13:00,880 --> 00:13:06,070
+مثبتة فاندي هنا main bearingهنا main bearing وهنا
+
+144
+00:13:06,070 --> 00:13:10,150
+لدي flexible coupling بتوصل العمود هذا مع الموتور
+
+145
+00:13:10,150 --> 00:13:14,690
+اللي بلف لأن هنا في وزن بيكون تحميل على ال bearing
+
+146
+00:13:14,690 --> 00:13:18,010
+هذه و ال bearing هذا لأن نتيجة تحميل الشد لتحت
+
+147
+00:13:18,010 --> 00:13:22,850
+هصير عندي ال fiber هنا عليها compression وهنا
+
+148
+00:13:22,850 --> 00:13:30,090
+tension لأن ال shaft بيكونهي دور معناته هذه كانت
+
+149
+00:13:30,090 --> 00:13:32,350
+في اللحظة ال compression لما يلف مئتين درجة بيصير
+
+150
+00:13:32,350 --> 00:13:35,750
+ال tension كمان مئتين درجة compression tension
+
+151
+00:13:35,750 --> 00:13:37,890
+compression tension compression tension و هكذا
+
+152
+00:13:37,890 --> 00:13:42,870
+فبصير نفس ال fiber ال stress level is completely
+
+153
+00:13:42,870 --> 00:13:49,450
+reversed bending اللي هو بالشكل هذا هذا one setup
+
+154
+00:13:49,450 --> 00:13:58,970
+another setup العينة تمسكمن طرف بالعمود بتاع
+
+155
+00:13:58,970 --> 00:14:03,170
+الموتور فيندي هنا موتور و فيندي هنا bearing و
+
+156
+00:14:03,170 --> 00:14:07,550
+فيندي bearing الان العمود العينة موجودة في bearing
+
+157
+00:14:07,550 --> 00:14:11,650
+و ال bearing انا سامحلها ت slide و هنا بكون حاطط
+
+158
+00:14:11,650 --> 00:14:15,230
+load عليها لأن نتيجة ال load حاسس ان عند المنطقة
+
+159
+00:14:15,230 --> 00:14:15,530
+هذه
+
+160
+00:14:18,330 --> 00:14:23,490
+Tension, bending, stress إذا بقى لف تسعين درجة
+
+161
+00:14:23,490 --> 00:14:26,650
+يعني إذا بقى لف ال fiber هتبصير تحت هتصير
+
+162
+00:14:26,650 --> 00:14:30,150
+compression فهو الشخص بدور مرة tension compression
+
+163
+00:14:30,150 --> 00:14:32,290
+tension compression tension compression وكذا
+
+164
+00:14:32,290 --> 00:14:38,240
+فهيكون completely reversed bendingstress لحد الكسر
+
+165
+00:14:38,240 --> 00:14:41,680
+طبعا انا في التجربة بغير ال load مثلا بحط أول 200
+
+166
+00:14:41,680 --> 00:14:47,220
+kilo بحط مثلا خمس مثلا عشرة kilogram و بلف الموتور
+
+167
+00:14:47,220 --> 00:14:51,820
+لما حد العينة ما تنكسر بجيب عينة تانية بحط ال load
+
+168
+00:14:51,820 --> 00:14:58,900
+مثلا مية بلف العينة لحد بعد number of cycles لحد
+
+169
+00:14:58,900 --> 00:15:05,410
+الكسر بحطعينة تالتة بحط load مثلا متين عينة رابعة
+
+170
+00:15:05,410 --> 00:15:08,850
+بحط load اربع تلات مية اربع مية يعني ماناتي انا
+
+171
+00:15:08,850 --> 00:15:13,310
+بحط ال load مثلا
+
+172
+00:15:13,310 --> 00:15:23,290
+سفر مية متين تلات مية و ا count cycles to failure
+
+173
+00:15:30,450 --> 00:15:35,610
+و بعدين بحسب ال .. ال .. ال fatigue strength ال
+
+174
+00:15:35,610 --> 00:15:41,090
+fatigue strength اذا عندي cantilever انا و عندي
+
+175
+00:15:41,090 --> 00:15:47,730
+shaft و في load هنا F هذه المسافة L
+
+176
+00:15:50,580 --> 00:15:55,880
+الـ moment هيكون ايش اساوي؟ الـ moment هيساوي F L
+
+177
+00:15:55,880 --> 00:16:02,640
+و المقطع عندى مدور معناته ال sigma هتكون اساوي M
+
+178
+00:16:02,640 --> 00:16:12,770
+في C على I ال M عندى F L و ال C D على 2قطر العمود
+
+179
+00:16:12,770 --> 00:16:18,270
+على اتنين وال I باي على اربع ستين في دي اص اربعة
+
+180
+00:16:18,270 --> 00:16:26,190
+يعني ال sigma هتكون ساوية اتنين و تلاتين FL على
+
+181
+00:16:26,190 --> 00:16:31,590
+باي دي تكيب هذا هي basically هذا ال stress او تسمي
+
+182
+00:16:31,590 --> 00:16:35,850
+ال stress amplitude لان ال stress هيتغير بالشكل
+
+183
+00:16:35,850 --> 00:16:39,230
+هذا هذا ال stress
+
+184
+00:16:43,680 --> 00:16:48,200
+amplitude انا اللي بقيس بقيس ال force و اعرف
+
+185
+00:16:48,200 --> 00:16:53,940
+المسافة هذه بحسب ال moment و بعدين بحسب من ما
+
+186
+00:16:53,940 --> 00:16:57,340
+عرفتي ده ال force و ال L و نصف و القطر بحسب ال
+
+187
+00:16:57,340 --> 00:17:02,320
+stress level طبعا بكون معرض القطع او العينة ل
+
+188
+00:17:02,320 --> 00:17:06,620
+certain load F و بعد ال cycles to failure بعدين
+
+189
+00:17:06,620 --> 00:17:07,400
+بعمل plot
+
+190
+00:17:10,770 --> 00:17:15,670
+اللي هو ال .. ال .. ال fatigue strength مع ال
+
+191
+00:17:15,670 --> 00:17:19,430
+cycles to failure بعمل plot على log .. log scale
+
+192
+00:17:19,430 --> 00:17:22,770
+يعني دي هين log scale و هين دي log scale يعني مثلا
+
+193
+00:17:22,770 --> 00:17:26,150
+دي هين عشر قص سفر عشر قص واحد عشر قص اتنين عشر قص
+
+194
+00:17:26,150 --> 00:17:29,870
+تلاتة عشر قص أربع عشر قص خمسة قص ستة قص سبعة و هين
+
+195
+00:17:29,870 --> 00:17:33,570
+عندي لأ semi log scale يعني هين ال .. ال .. ال ..
+
+196
+00:17:33,570 --> 00:17:37,230
+المحر أفق log scale و هين عشر linear scale عندي
+
+197
+00:17:37,230 --> 00:17:50,520
+هين مثلا خمسينمية و هكذا لللحظة
+
+198
+00:17:50,520 --> 00:17:56,720
+هلو سمي ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+199
+00:17:56,720 --> 00:17:59,180
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+200
+00:17:59,180 --> 00:18:01,980
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+201
+00:18:01,980 --> 00:18:03,320
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+202
+00:18:03,320 --> 00:18:03,500
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+203
+00:18:03,500 --> 00:18:03,560
+ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال ال
+
+204
+00:18:03,560 --> 00:18:08,150
+ال ال ال ال الاللي هي number of stress cycles على
+
+205
+00:18:08,150 --> 00:18:12,250
+المحور الرأسي الاسفة ال fatigue strength ال
+
+206
+00:18:12,250 --> 00:18:17,990
+fatigue strength هلاحظ انه لل .. لل .. لل ..
+
+207
+00:18:17,990 --> 00:18:24,710
+للحديد هكون شكل ال stress strain curve بالشكل هذا
+
+208
+00:18:24,710 --> 00:18:34,040
+بشكل عام .. بشكل عام كل ما بزيد ال stress levelكل
+
+209
+00:18:34,040 --> 00:18:39,920
+ما اكيد محتاج ل number of cycles to failure اقل او
+
+210
+00:18:39,920 --> 00:18:43,820
+بمعنى كل ما بقل ال stress level كل ما ال cycles to
+
+211
+00:18:43,820 --> 00:18:47,200
+failure اشملها بزيد يعني اذا بزيد ال stress level
+
+212
+00:18:47,200 --> 00:18:53,000
+او ال load level ال cycles to failure بتقل او لو
+
+213
+00:18:53,000 --> 00:18:57,180
+بدي احكيها بالعكس كل ما قل ال stress level كل ما
+
+214
+00:18:57,180 --> 00:19:00,080
+ال cycles to failure بزيد
+
+215
+00:19:03,000 --> 00:19:08,840
+الان في عندى لحظة هذه عشرة اقصد تلاتة هذه الف هنا
+
+216
+00:19:08,840 --> 00:19:15,320
+تقريبا عشرة اقصد ستة هنا عشرة اقصد سبعة عشرة اقصد
+
+217
+00:19:15,320 --> 00:19:19,020
+تمانية عشرة اقصد ستة يعني مليون cycle عشرة اقصد
+
+218
+00:19:19,020 --> 00:19:21,340
+سبعة عشرة مليون cycle عشرة اقصد تمانية اللى هو ميت
+
+219
+00:19:21,340 --> 00:19:24,860
+مليون cycle عشرة اقصد تلاتة الف cycle
+
+220
+00:19:29,270 --> 00:19:34,350
+الان انا ممكن اصنف او اعمل تصنيفات على ال curve
+
+221
+00:19:34,350 --> 00:19:42,310
+بطرق مختلفة ممكن to define low cycle fatigue يعني
+
+222
+00:19:42,310 --> 00:19:52,850
+عندي هنا low cycle fatigue من
+
+223
+00:19:52,850 --> 00:19:57,030
+هنا لهنا وعندي
+
+224
+00:20:00,030 --> 00:20:11,070
+هنا عندي high cycle fatigue low
+
+225
+00:20:11,070 --> 00:20:16,130
+cycle fatigue بيصير failure او المنطقة اللى بيكون
+
+226
+00:20:16,130 --> 00:20:19,210
+عدد ال number of cycles to failure اقل من الف
+
+227
+00:20:19,210 --> 00:20:24,940
+حياتي بتسميها low cycle fatigue اذا كانعدد ال
+
+228
+00:20:24,940 --> 00:20:28,780
+cycles to failure أكتر من ألف أسميه high cycle
+
+229
+00:20:28,780 --> 00:20:32,820
+fatigue هاي الطريقة لأنه لو عندي low cycle fatigue
+
+230
+00:20:32,820 --> 00:20:35,880
+وعندي high cycle fatigue low cycle fatigue ال
+
+231
+00:20:35,880 --> 00:20:39,800
+number of cycles to failure أقل من ألف high cycle
+
+232
+00:20:39,800 --> 00:20:45,960
+fatigue ال cycles to failure أكتر من ألف ممكن
+
+233
+00:20:45,960 --> 00:20:46,840
+تصنيف تاني
+
+234
+00:21:07,460 --> 00:21:20,080
+ممكن احكي finite life fatigue وهين اللي هو high او
+
+235
+00:21:20,080 --> 00:21:25,600
+infinite life
+
+236
+00:21:25,600 --> 00:21:29,460
+fatigue يعني
+
+237
+00:21:31,750 --> 00:21:36,050
+لحد مليون cycle بعتبر ان القطع لها عمر محدود
+
+238
+00:21:36,050 --> 00:21:42,470
+finite life يعني اذا تجاوزت المليون cycle تقريب
+
+239
+00:21:42,470 --> 00:21:45,690
+بعتبر ان حياتها infinite life لو اعتبر حياتها
+
+240
+00:21:45,690 --> 00:21:51,050
+infinite life الان
+
+241
+00:21:51,050 --> 00:21:56,790
+لو نخد مثال على عدد الضربات او عدد التغير لقطع
+
+242
+00:21:56,790 --> 00:22:00,670
+ميكانيكية معينة خد مثلا عضلة القلب عضلة القلب
+
+243
+00:22:05,460 --> 00:22:10,200
+عضة القلب تعمل سبعين ضربة في الدقيقة .. سبعين ضربة
+
+244
+00:22:10,200 --> 00:22:16,460
+في الدقيقة يعني
+
+245
+00:22:16,460 --> 00:22:22,680
+في الساعة .. كم في الساعة؟ في الساعة يكون سبعين في
+
+246
+00:22:22,680 --> 00:22:29,360
+ستين بيطلع أربع تلاف و متين ضربة أو cycle في اليوم
+
+247
+00:22:32,920 --> 00:22:37,720
+بيكون عنده اللي هو أربعة آلاف و متين في أربعة و
+
+248
+00:22:37,720 --> 00:22:45,640
+عشرين أربعة آلاف و متين في
+
+249
+00:22:45,640 --> 00:22:51,220
+أربعة و عشرين بيطلع
+
+250
+00:22:51,220 --> 00:22:59,760
+مية و تسعة و سبعين ألف و متين ضربة هذا في اليوم في
+
+251
+00:22:59,760 --> 00:23:00,260
+السنة
+
+252
+00:23:03,930 --> 00:23:08,510
+هتكون عند مية و تسعة و سبعين ألف و متين في تلت مية
+
+253
+00:23:08,510 --> 00:23:13,410
+و خمس و ستين يوم في
+
+254
+00:23:13,410 --> 00:23:21,790
+تلت مية و خمس و ستين بيطلع خمسة
+
+255
+00:23:21,790 --> 00:23:28,490
+و ستين مليون اربعمية و تمانية الف سايكل هذه في سنة
+
+256
+00:23:31,510 --> 00:23:37,150
+لو بدى يعيشله سبعين سنة في سبعين سنة مثلا متوسط
+
+257
+00:23:37,150 --> 00:23:44,370
+العمارة تقريبا سبعين سنة هيكون خمسة ستين مليون
+
+258
+00:23:44,370 --> 00:23:49,770
+واربعمية او تمانية الف في سبعين
+
+259
+00:24:01,170 --> 00:24:04,490
+ضلت في واحد ساعة مش مشكلة بطلع تقريبا .. خليني أحط
+
+260
+00:24:04,490 --> 00:24:10,630
+صفار .. سفر .. سفر .. سفر .. هاي .. تمانية .. ستة
+
+261
+00:24:10,630 --> 00:24:19,570
+.. تسعة ..تمانى ستة تسعة تلاتة أربعة ستة فاصلة
+
+262
+00:24:19,570 --> 00:24:26,370
+أربعة يعني لشخص .. نحكي أكتر من دهان تلاتة ستة
+
+263
+00:24:26,370 --> 00:24:35,520
+تسعة يعني تقريبا تحكي حوالي خمسة مليار ضربةلشخص
+
+264
+00:24:35,520 --> 00:24:38,520
+بيعيش حياة طبيعية في حدود سبعين و واحد و سبعين سنة
+
+265
+00:24:38,520 --> 00:24:44,400
+بدرب لحوالي خمس مليون .. خمس مليار cycle يعني أكم
+
+266
+00:24:44,400 --> 00:24:52,280
+عشرة يعني خمسة في عشرة plus تسعة فتخيلوا أيش ال
+
+267
+00:24:52,280 --> 00:24:56,620
+fatigue loading اللي موجود على عضلة .. عضلة القلب
+
+268
+00:25:00,960 --> 00:25:05,360
+معناته ال fatigue loading موجود معناته عضلة القلب
+
+269
+00:25:05,360 --> 00:25:10,200
+لازم يكون لها مواصفات تتحمل ال cycles هذه لحد ما
+
+270
+00:25:10,200 --> 00:25:13,440
+يصير .. مايصير failure، مايصير فيها ضعف أو يصير
+
+271
+00:25:13,440 --> 00:25:20,970
+عنده تصلب او اي مشكلة تانيةطيب، انا في عند حكيت
+
+272
+00:25:20,970 --> 00:25:23,470
+عندي low cycle fatigue إذا كان number of cycles to
+
+273
+00:25:23,470 --> 00:25:25,930
+failure أقل من ألف وعندي high cycle fatigue إذا
+
+274
+00:25:25,930 --> 00:25:28,330
+كان ال cycles to failure أكتر من ألف، في عندي
+
+275
+00:25:28,330 --> 00:25:32,190
+finite life fatigue إذا كان ال cycles to .. إذا
+
+276
+00:25:32,190 --> 00:25:35,930
+كان ال life .. ال cycles to .. to failure أقل من
+
+277
+00:25:35,930 --> 00:25:39,610
+.. من مليون، إذا أكبر مليون بيكون عندي infinite
+
+278
+00:25:39,610 --> 00:25:43,550
+life، اللحظة في عندي stress level هنا، بسميه
+
+279
+00:25:43,550 --> 00:25:45,050
+stress level
+
+280
+00:25:47,780 --> 00:25:54,000
+بسميه SE SE هذه هي ال endurance limit ال endurance
+
+281
+00:25:54,000 --> 00:26:00,940
+limit هي ال stress level below which the specimen
+
+282
+00:26:00,940 --> 00:26:04,760
+will not fail يعني هو ال stress level اللي تحته
+
+283
+00:26:04,760 --> 00:26:09,000
+العينة و العمر هتنكسر هتظل عايشة لما لإنهاية
+
+284
+00:26:09,000 --> 00:26:13,120
+معناته if we apply a stress level below the
+
+285
+00:26:13,120 --> 00:26:18,170
+endurance limit the specimen will not failمعناته
+
+286
+00:26:18,170 --> 00:26:23,990
+definition ال endurance limit ال S E هي ال stress
+
+287
+00:26:23,990 --> 00:26:29,130
+level below which the specimen will not fail
+
+288
+00:26:29,130 --> 00:26:36,010
+معناته it will endure، endure هيعيش لماله نهاية
+
+289
+00:26:36,010 --> 00:26:42,050
+هذا
+
+290
+00:26:42,050 --> 00:26:48,520
+طبعا الشكل اللي شفناه في حالةاللي هو السبائك
+
+291
+00:26:48,520 --> 00:26:52,580
+الحديد لكن في حال اللي هي السبائك الغير حددية اللي
+
+292
+00:26:52,580 --> 00:26:59,140
+هي nonferrous metals it does not show endurance
+
+293
+00:26:59,140 --> 00:27:05,840
+limit هيكون
+
+294
+00:27:05,840 --> 00:27:10,080
+الاس ان دايران بالشكل هذا يعني بيبقوا نازل على طول
+
+295
+00:27:10,080 --> 00:27:16,830
+مافيش بصالش انه بيصير flatفي الحالة هذه I define
+
+296
+00:27:16,830 --> 00:27:20,990
+fatigue strength for a specified number of cycles
+
+297
+00:27:20,990 --> 00:27:25,370
+يعني إذا كان ال .. ال .. for a stress level مائة
+
+298
+00:27:25,370 --> 00:27:30,590
+ميجا هيعيش مليون for a stress level متين ميجا
+
+299
+00:27:30,590 --> 00:27:36,490
+هيعيش ل متين ألف cycle يعني ال life أو عمر القطة
+
+300
+00:27:36,490 --> 00:27:40,170
+مرتبطة بال stress level كل ما زاد ال stress level
+
+301
+00:27:40,170 --> 00:27:42,290
+كل ما عمر القطة كان أقل
+
+302
+00:27:50,240 --> 00:27:55,760
+معناه تلخص في ال stress life method انا باخد عينة
+
+303
+00:27:55,760 --> 00:28:01,360
+من المادة عينة ميارية بعمل tensile test بارسم ال S
+
+304
+00:28:01,360 --> 00:28:08,440
+-N diagram و بعرف ال number of cycles to failure
+
+305
+00:28:10,870 --> 00:28:15,470
+depending على ال loading أو قيمة التحميل على القطع
+
+306
+00:28:15,470 --> 00:28:18,830
+الميكانيكية الطريقة التانية هي ال strain life
+
+307
+00:28:18,830 --> 00:28:21,510
+method ال strain life method في ال strain life
+
+308
+00:28:21,510 --> 00:28:24,870
+method بعمل detailed analysis of the plastic
+
+309
+00:28:24,870 --> 00:28:28,650
+deformation at localized regions الآن في ال strain
+
+310
+00:28:28,650 --> 00:28:32,290
+life method بقدرس اللي هو ال deformations اللي
+
+311
+00:28:32,290 --> 00:28:38,670
+بيصير locally عند نقاط معينة في القطع الميكانيكية
+
+312
+00:28:42,060 --> 00:28:47,020
+عادة الفتيك فيلير ببدأ at a local discontinuity
+
+313
+00:28:47,020 --> 00:28:52,220
+يعني إذا عندي sudden change إذا عندي هاي شافت و
+
+314
+00:28:52,220 --> 00:28:57,540
+القطر بتاعه إيش مصدر هنا
+
+315
+00:28:57,540 --> 00:29:03,380
+ممكن يصير عندي الآن أدخل local يعني نقطة هنا أدخل
+
+316
+00:29:03,380 --> 00:29:04,340
+ال plastic range
+
+317
+00:29:09,530 --> 00:29:11,970
+لما ادخلت ال plastic range بيصير عندى plastic
+
+318
+00:29:11,970 --> 00:29:15,730
+deformation لوكالي و شوي شوي بتبدأ تصير عندى تشقق
+
+319
+00:29:15,730 --> 00:29:18,870
+التشقق بيكبر شوي شوي شوي شوي لحد ما يصير عندى
+
+320
+00:29:18,870 --> 00:29:23,030
+sudden failure يعني وين في عندى اللي هو local
+
+321
+00:29:23,030 --> 00:29:26,050
+discontinuity عندى stress concentration او حالة
+
+322
+00:29:26,050 --> 00:29:34,050
+تانية عند هذه القطعة و فيها ثقب ممكن تصير failure
+
+323
+00:29:34,050 --> 00:29:37,830
+عند النقطة هذه عند .. عند الثقب هنا عندى stress
+
+324
+00:29:43,810 --> 00:29:49,470
+concentration يعني وين في عندى اللى هو تغير مفاجئ
+
+325
+00:29:49,470 --> 00:29:51,370
+فى ال cross section بيكون عندى stress
+
+326
+00:29:51,370 --> 00:29:54,910
+concentration بيصير locally .. local يعني ده نقطة
+
+327
+00:29:54,910 --> 00:29:59,670
+هدى ال stress level ممكن ادخل ال plastic range
+
+328
+00:29:59,670 --> 00:30:03,290
+دخلت ال plastic range بتبدأ تشقق صار تشقق و التشقق
+
+329
+00:30:03,290 --> 00:30:05,970
+بيصير اكبر شوية شوية لحد ما يصير عندى صدر انفريال
+
+330
+00:30:19,910 --> 00:30:25,230
+طيب الان عند discontinuity يعني مثلا عندي .. عندي
+
+331
+00:30:25,230 --> 00:30:33,990
+fillet او عندي ثقب و روحت رسمت ال stress مع ال
+
+332
+00:30:33,990 --> 00:30:38,990
+strain الان بدأ اللغة تزيد شوي شوي لحد ما locally
+
+333
+00:30:41,890 --> 00:30:47,090
+ال stress بزيد شوية شوية لحد ما locally هاد ال
+
+334
+00:30:47,090 --> 00:30:52,130
+first reversal دخلت في ال plastic range طبعا دي
+
+335
+00:30:52,130 --> 00:30:57,950
+قطع بتدور تتحرك تتحرك معناته بيبدأ ال loading يعكس
+
+336
+00:30:57,950 --> 00:31:00,990
+هيبدأ ال stress level ينزل
+
+337
+00:31:13,290 --> 00:31:16,790
+بيصير بالعكس عندى هى ال second هى ال first هى
+
+338
+00:31:16,790 --> 00:31:20,750
+الرقم واحد هاد ال second reverse صارت stress
+
+339
+00:31:20,750 --> 00:31:24,570
+بالاتجاه المعاكس مثلا هنا هى كانت ال tension صار
+
+340
+00:31:24,570 --> 00:31:29,250
+ايش compression ودخلت برضه ل plastic range لان
+
+341
+00:31:29,250 --> 00:31:34,570
+استمر القطع و الشات في الدوران هيبدأ ال stress
+
+342
+00:31:34,570 --> 00:31:41,990
+يزيد يزيد يزيد لحد ما يسفر بعدين هيبدأ يرفع تانى
+
+343
+00:31:47,530 --> 00:31:54,570
+هذه الـ third reversal صار بالموجب القطع
+
+344
+00:31:54,570 --> 00:32:00,110
+الميكانيكية بتلف هيبدأ
+
+345
+00:32:00,110 --> 00:32:04,810
+تلف يبدأ ال stress level بقل بقل بقل بعدين بيصير
+
+346
+00:32:04,810 --> 00:32:07,630
+يزيد باتجاه المعاكس مثلا هنا كان tension بيبدأ
+
+347
+00:32:07,630 --> 00:32:11,150
+يدخل في ال compression compression compression لحد
+
+348
+00:32:11,150 --> 00:32:13,370
+ما بدأ يدخل ال plastic range لأن بدأ يدخل ال
+
+349
+00:32:13,370 --> 00:32:19,740
+plastic rangeلحد موصلنا هنا هاي الرابع لحظة كل
+
+350
+00:32:19,740 --> 00:32:24,160
+مالها ال strength للقطع الميكانيكية كل مالها بتقل
+
+351
+00:32:24,160 --> 00:32:31,660
+الان بلف ال shaft بيصير ال stress ال negative
+
+352
+00:32:31,660 --> 00:32:33,640
+stress او ال compression stress بتتقل شوية شوية
+
+353
+00:32:33,640 --> 00:32:38,360
+شوية لحد ما يصير zero بعدين بيصير يتحول لإيش بدخل
+
+354
+00:32:38,360 --> 00:32:42,380
+على ال tension بزيد بزيد لحد دخلت ال plastic range
+
+355
+00:32:45,710 --> 00:32:51,450
+هاي الخامسة هي اللي كانت إيش الرابعة لحظة كل ما
+
+356
+00:32:51,450 --> 00:32:56,910
+لها ال strength بتقل لو قررت هتصير أشي زي هيك عنده
+
+357
+00:32:56,910 --> 00:33:03,290
+هذه
+
+358
+00:33:03,290 --> 00:33:12,970
+السادسة سبعة
+
+359
+00:33:15,250 --> 00:33:20,790
+كلما الاسترنك تشبع لها بتقل التام نوعها كذا لحد ما
+
+360
+00:33:20,790 --> 00:33:25,270
+يصير عندى sudden failure واضح ان ال stress is
+
+361
+00:33:25,270 --> 00:33:28,370
+cycling between tension and compression tension
+
+362
+00:33:28,370 --> 00:33:30,310
+and compression يعني في عندى completely reversed
+
+363
+00:33:30,310 --> 00:33:36,730
+.. completely reversed cycling بين طبعا انا في كل
+
+364
+00:33:36,730 --> 00:33:40,280
+حوالlocally بدخل ال .. هنا دخلت ال plastic range
+
+365
+00:33:40,280 --> 00:33:42,320
+وهنا دخلت ال plastic range بس هنا دخلت ال plastic
+
+366
+00:33:42,320 --> 00:33:46,540
+range while tension بيكون مجدود هنا دخلت ال
+
+367
+00:33:46,540 --> 00:33:49,860
+plastic range while compression يعني هنا ال
+
+368
+00:33:49,860 --> 00:33:56,200
+plastic tension هنا ال plastic compression طبعا
+
+369
+00:33:56,200 --> 00:34:02,740
+القطع بتضعفأو بـ Serial Crack Propagation لحد ما
+
+370
+00:34:02,740 --> 00:34:06,360
+الـ cross section يقل و يصبح لديه sudden failure
+
+371
+00:34:06,360 --> 00:34:15,160
+طبعا في كل الأحوال هذا هو الـ total strain هذا
+
+372
+00:34:15,160 --> 00:34:20,180
+دلتا أبسلون دلتا أبسلون جزئين هناخدها هنا من برا
+
+373
+00:35:05,490 --> 00:35:16,870
+خلنا نستخدم لونان هذا
+
+374
+00:35:16,870 --> 00:35:16,910
+هتكون
+
+375
+00:35:32,950 --> 00:35:41,030
+الـ delta epsilon elastic على اتنين وهذا الـ delta
+
+376
+00:35:41,030 --> 00:35:51,670
+epsilon plastic على اتنين وهنا بالعكس الـ
+
+377
+00:35:51,670 --> 00:35:55,030
+delta epsilon elastic على اتنين وهذا الـ delta
+
+378
+00:35:55,030 --> 00:35:57,010
+epsilon plastic على اتنين
+
+379
+00:36:03,860 --> 00:36:10,400
+delta epsilon على اتنين بالموجب وهنا هتكون delta
+
+380
+00:36:10,400 --> 00:36:18,200
+epsilon على اتنين فواضح فيه ان انا ممكن اسمي ال
+
+381
+00:36:18,200 --> 00:36:21,940
+delta epsilon على اتنين هي ال total strain
+
+382
+00:36:21,940 --> 00:36:27,520
+amplitude لان ال strain يعني بتتغير بالشكل هذا ال
+
+383
+00:36:27,520 --> 00:36:27,860
+strain
+
+384
+00:36:31,200 --> 00:36:36,460
+فهذا الـ strain الـ strain amplitude الـ strain
+
+385
+00:36:36,460 --> 00:36:41,640
+amplitude مكوّم
+
+386
+00:36:41,640 --> 00:36:45,360
+جزئين اللي هو reversible strain اللي هو الـ
+
+387
+00:36:45,360 --> 00:36:50,320
+elastic strain دلتا أبسرن إلاستك على اتنين زائد
+
+388
+00:36:50,320 --> 00:36:53,620
+اللي هو ال permanent اللي هي ال plastic دلتا أبسرن
+
+389
+00:36:53,620 --> 00:36:56,300
+plastic على اتنين
+
+390
+00:37:12,630 --> 00:37:18,950
+الان بيضالوا ال strain انا من cycles of strain لحد
+
+391
+00:37:18,950 --> 00:37:23,690
+ما يصير failure لحد ما يصير failure اذا عملت plot
+
+392
+00:37:23,690 --> 00:37:28,910
+اذا عملت plot على log log scale يعني هنا عندي ال
+
+393
+00:37:28,910 --> 00:37:34,530
+reversals to failure انا و هنا عندي ال strain
+
+394
+00:37:34,530 --> 00:37:35,510
+amplitude
+
+395
+00:37:37,540 --> 00:37:40,780
+strain amplitude طبعا احنا حكينا ال strain
+
+396
+00:37:40,780 --> 00:37:44,660
+amplitude مكوّن من elastic part و plastic part هذا
+
+397
+00:37:44,660 --> 00:37:54,060
+الجزء اللي
+
+398
+00:37:54,060 --> 00:38:01,540
+هو delta elastic على اتنين هذا الجزء
+
+399
+00:38:09,180 --> 00:38:14,380
+اللي هو delta epsilon plastic على اتنين وال curve
+
+400
+00:38:14,380 --> 00:38:21,560
+هذا هذا
+
+401
+00:38:21,560 --> 00:38:26,340
+هو ال total delta
+
+402
+00:38:26,340 --> 00:38:33,020
+ال epsilon على اتنين total strain amplitude هنا
+
+403
+00:38:33,020 --> 00:38:39,080
+عندي عشر او اثنان اقصى اربعةعشر أقص ناقص ثلاثة عشر
+
+404
+00:38:39,080 --> 00:38:44,020
+أقص ناقص اتنين عشر أقص ناقص واحد عشر أقص سفر هي
+
+405
+00:38:44,020 --> 00:38:46,660
+عشر أقص سفر عشر أقص واحد عشر أقص اتنين عشر أقص
+
+406
+00:38:46,660 --> 00:38:51,680
+تلاتة عشر أقص أربعة عشر أقص خمسة عشر أقص ستة لأن
+
+407
+00:38:51,680 --> 00:38:55,220
+لاحظوا delta absolute elastic على اتنين بالساوية
+
+408
+00:38:55,220 --> 00:38:57,620
+ال elastic external amplitude زي ال plastic
+
+409
+00:38:57,620 --> 00:39:00,160
+external amplitude لكن انا عندي هاي هذا elastic
+
+410
+00:39:00,160 --> 00:39:04,230
+external amplitude وهي plastic external amplitudeو
+
+411
+00:39:04,230 --> 00:39:08,850
+ال total strain مجموهم لأن ممكن البعض يعتقد ان هذا
+
+412
+00:39:08,850 --> 00:39:11,030
+ال curve مش صح المفروض يعمله shift لعله لأ هذا
+
+413
+00:39:11,030 --> 00:39:14,170
+صحيح بس تذكروا انا على الجهة ايه برسم على log
+
+414
+00:39:14,170 --> 00:39:16,470
+scale برسم على log scale
+
+415
+00:39:21,500 --> 00:39:27,760
+طيب الآن ال slope هذا في slope لل ال elastic
+
+416
+00:39:27,760 --> 00:39:31,840
+strain amplitude يسمى B وفي slope لل plastic
+
+417
+00:39:31,840 --> 00:39:36,640
+strain amplitude اللي هو C وفي عند النقطة هذه
+
+418
+00:39:36,640 --> 00:39:42,620
+epsilon F في ال prime وهنا عندي sigma F في ال
+
+419
+00:39:42,620 --> 00:39:58,190
+prime على E هذا ايشالـ slope هذا ايش يمثل ايه
+
+420
+00:39:58,190 --> 00:40:05,890
+هذا
+
+421
+00:40:05,890 --> 00:40:11,570
+برضه ايه وهي اللي عندي هنا delta epsilon elastic
+
+422
+00:40:11,570 --> 00:40:17,970
+على اتنين وهذه هتكون سيجما
+
+423
+00:40:21,260 --> 00:40:27,900
+أف في الـ prime و هذه
+
+424
+00:40:27,900 --> 00:40:31,360
+النقطة بالذات اللي هي أبسلون أف في ال prime
+
+425
+00:40:31,360 --> 00:40:37,580
+الأبسلون
+
+426
+00:40:37,580 --> 00:40:40,420
+أف في ال prime هي ال true strain at which fracture
+
+427
+00:40:40,420 --> 00:40:45,800
+occurs in one reversal الأبسلون
+
+428
+00:40:45,800 --> 00:40:49,730
+أف في ال prime هي قيمة ال strainاللي بيصير عندها
+
+429
+00:40:49,730 --> 00:40:52,210
+failure من أول reversal لحد ما يصل لهذه من
+
+430
+00:40:52,210 --> 00:40:56,290
+reversal رقم واحد بيصير كسر هي هذه أبسلون F الـ
+
+431
+00:40:56,290 --> 00:41:03,470
+Prime وال Sigma F Prime هي ال stress level اللي
+
+432
+00:41:03,470 --> 00:41:06,930
+بيصير عندها كسر من أول reversal، يعني النقطة هذه،
+
+433
+00:41:06,930 --> 00:41:14,450
+هذه Sigma F Prime والـ
+
+434
+00:41:14,450 --> 00:41:20,100
+Bالـ slope للـ elastic strain والـ C ال slope لل
+
+435
+00:41:20,100 --> 00:41:25,240
+.. ال B ال slope لل elastic strain curve والـ C ال
+
+436
+00:41:25,240 --> 00:41:33,440
+slope لل plastic strain curve الآن
+
+437
+00:42:00,580 --> 00:42:08,060
+لاحظوا ال .. ال .. عندي ال slope للإيلاس B بي اللي
+
+438
+00:42:08,060 --> 00:42:18,220
+هي ال slope of ال elastic strain line وال
+
+439
+00:42:18,220 --> 00:42:26,740
+C هي ال slope of plastic strain line
+
+440
+00:42:30,130 --> 00:42:33,910
+و هدا ال intercept اللي هي epsilon F prime و هدا
+
+441
+00:42:33,910 --> 00:42:43,110
+sigma F prime على E معناته واضح ان العلاقة على log
+
+442
+00:42:43,110 --> 00:42:50,410
+log scale is linear و العلاقة لل elastic لل
+
+443
+00:42:50,410 --> 00:42:54,330
+plastic strain line is linear لل elastic strain
+
+444
+00:42:54,330 --> 00:42:59,340
+line is linear معناته ممكن اعبر على العلاقة بينالـ
+
+445
+00:42:59,340 --> 00:43:03,360
+strain amplitude و ال number of cycles او ال
+
+446
+00:43:03,360 --> 00:43:07,760
+reversals to failure as a power law يعني بدكن احكي
+
+447
+00:43:07,760 --> 00:43:15,380
+delta epsilon plastic على 2 هتكون epsilon f prime
+
+448
+00:43:16,000 --> 00:43:21,600
+فى اتنين N قصى C و ال Delta Epsilon Elastic على
+
+449
+00:43:21,600 --> 00:43:28,080
+اتنين هتكون اللى هى Sigma F Prime على E فى اتنين N
+
+450
+00:43:28,080 --> 00:43:28,980
+قصى B
+
+451
+00:43:38,390 --> 00:43:41,570
+لو أخدت ال log للطرفين هتطلع علاقة إيش linear
+
+452
+00:43:41,570 --> 00:43:46,770
+هتطلع linear بين ال log دلت أبسترون مع ال cycle ال
+
+453
+00:43:46,770 --> 00:44:01,010
+number of reversals طيب
+
+454
+00:44:11,570 --> 00:44:14,750
+الـ Total Strain Amplitude اللي هي Delta Epsilon
+
+455
+00:44:14,750 --> 00:44:20,250
+على 2 هتكون مجموع الـ Elastic Strain Amplitude مع
+
+456
+00:44:20,250 --> 00:44:24,930
+الـ Plastic Strain Amplitude و هنعوض عند الـ
+
+457
+00:44:24,930 --> 00:44:31,690
+Elastic اللي هي Sigma F Prime على E في 2N أُس B
+
+458
+00:44:31,690 --> 00:44:38,710
+زائد اللي هي Epsilon F Prime في 2N أُس C
+
+459
+00:44:48,810 --> 00:44:54,790
+طيب في الكتاب روحوا appendix A23
+
+460
+00:44:56,720 --> 00:45:01,680
+بيعطيني values of coefficients اللي هي بي بي اللي
+
+461
+00:45:01,680 --> 00:45:09,000
+هو appendix a تلاتة و عشرين في كتاب شغلي بيعطيني
+
+462
+00:45:09,000 --> 00:45:17,900
+اللي هو بي او سي و أبسلن اف برايم او سيجما اف
+
+463
+00:45:17,900 --> 00:45:26,520
+برايم خلنا نشوف هنا ال table نتأكد
+
+464
+00:45:38,710 --> 00:45:41,850
+هذا table A23 زي ما انتوا شايفين ال headings
+
+465
+00:45:41,850 --> 00:45:46,090
+اتطلعوا على أقصى يمين ال table عند ال fatigue
+
+466
+00:45:46,090 --> 00:45:50,770
+strength exponent B موجود و ال fatigue ductility
+
+467
+00:45:50,770 --> 00:45:55,250
+exponent C موجود و ال fatigue ductility
+
+468
+00:45:55,250 --> 00:45:59,290
+coefficient F prime موجوديعني عندها هي sigma f
+
+469
+00:45:59,290 --> 00:46:04,450
+prime و ال b و ال epsilon f prime و ال c لسبائك
+
+470
+00:46:04,450 --> 00:46:08,550
+مختلفة من سبائك الحديد يعني هنا عند العملي الأول
+
+471
+00:46:08,550 --> 00:46:14,690
+ليه رقم سبكة الحديد و ال description تاعة ومعطية
+
+472
+00:46:14,690 --> 00:46:17,810
+ال hardness تنصفها ال strength و ال ductility in
+
+473
+00:46:17,810 --> 00:46:22,110
+terms of reduction in areaو ال true strain at
+
+474
+00:46:22,110 --> 00:46:25,730
+fracture اللي بيمثل برضه التعبير عن ال ductility و
+
+475
+00:46:25,730 --> 00:46:30,250
+ال modulus و ال STE و ال sigma F prime و ال B و S
+
+476
+00:46:30,250 --> 00:46:34,830
+F prime و C هذا كله موجود في تابل A23 for
+
+477
+00:46:34,830 --> 00:46:41,350
+different alloys of steelالان ال equation هذه اللي
+
+478
+00:46:41,350 --> 00:46:45,270
+انتوا شايفينها دلتا أبسطران على اتنين بيساو
+
+479
+00:46:45,270 --> 00:46:47,990
+سيجنافه برايم على E في اتنين أنوس P زي اتنين
+
+480
+00:46:47,990 --> 00:46:52,270
+أبسطران على اتنين أنوس C has limited use in design
+
+481
+00:46:52,270 --> 00:46:56,730
+لأنه ببساطة قيم ال total strain عندي ال
+
+482
+00:46:56,730 --> 00:47:01,510
+discontinuity الصعب انك مش موجودة المعلومات هذه و
+
+483
+00:47:01,510 --> 00:47:08,850
+صعب قياسها و حسابها انا معناته هنشوفنفكر بطريقة
+
+484
+00:47:08,850 --> 00:47:13,590
+تانية فاكرين
+
+485
+00:47:13,590 --> 00:47:23,950
+ال S-and diagram او احنا الان اخد اللي صار اخده
+
+486
+00:47:23,950 --> 00:47:30,060
+different materials مثلا دي material واحدmaterial
+
+487
+00:47:30,060 --> 00:47:34,140
+اتنين material تلاتة طبعا سباق للحدد للحديد
+
+488
+00:47:34,140 --> 00:47:40,000
+material اربع material خمسة و .. و انا بعرف ال
+
+489
+00:47:40,000 --> 00:47:42,860
+tensile strength ل material واحد و اتنين و تلاتة و
+
+490
+00:47:42,860 --> 00:47:47,900
+اربع و خمسة و بعرف ال endurance limit للعينات
+
+491
+00:47:47,900 --> 00:47:57,000
+معيارية SE prime الآن عملنا plot بينالـ S A' و الـ
+
+492
+00:47:57,000 --> 00:48:01,620
+S U T يعني هنا عندي على المحور الأفقي S U T وعندي
+
+493
+00:48:01,620 --> 00:48:08,780
+هنا S A' اتطلع على ال trend بتاع البيانات كيف
+
+494
+00:48:08,780 --> 00:48:15,220
+البيانات بتتصرف لاحظوا تقريبا في علاقة خطية بعدين
+
+495
+00:48:15,220 --> 00:48:18,820
+بيصير ثابتة يعني لاحظوا البيانات كيف هذه
+
+496
+00:48:18,820 --> 00:48:24,750
+experimental dataعندي تقريبا في تغير خط بين ال SE
+
+497
+00:48:24,750 --> 00:48:30,030
+prime لحد ال ultimate strength معين بعدين بيبدأ
+
+498
+00:48:30,030 --> 00:48:35,900
+يصير ash بتثبت قيمة ال SE primeلاحظوا عندى تلت
+
+499
+00:48:35,900 --> 00:48:40,840
+خطوط عند خط فى النص وخط اعلى خط فى النص مكتوب عليه
+
+500
+00:48:40,840 --> 00:48:45,620
+point five وخط فى النص اللى هو SE على SE prime على
+
+501
+00:48:45,620 --> 00:48:49,440
+SE بالساوية point five وهنا عندى SE prime على SA
+
+502
+00:48:49,440 --> 00:48:53,900
+اللى هي point six وهنا عندى SE prime على SU
+
+503
+00:48:53,900 --> 00:49:01,120
+بالساوية point أربعة الخط اللى فى النص بيبثله
+
+504
+00:49:02,770 --> 00:49:07,950
+خمسين في المية reliability للبيانات خمسين في المية
+
+505
+00:49:07,950 --> 00:49:11,370
+reliability لل data يعني ايش يعني خمسين في المية؟
+
+506
+00:49:11,370 --> 00:49:18,290
+معناته experimentally او هذا الخط بيمثل ان هذا جهة
+
+507
+00:49:18,290 --> 00:49:22,930
+واقع في النص ممكن تكون القيم الحقيقية احتمال تكون
+
+508
+00:49:22,930 --> 00:49:25,750
+خمسين في المية اعلى او اقل خمسين في المية اعلى او
+
+509
+00:49:25,750 --> 00:49:34,790
+اقلالـ curve fitting بين الـ SE prime و ال SUT for
+
+510
+00:49:34,790 --> 00:49:40,030
+50% reliability of data بيعطينا علاقة هذه SE prime
+
+511
+00:49:40,030 --> 00:49:44,330
+بيستوى نص SUT إذا كانت SUT أقل من 200 kilo pound
+
+512
+00:49:44,330 --> 00:49:48,450
+per square inch و بتستوى 100 kilo pound per square
+
+513
+00:49:48,450 --> 00:49:51,130
+inch إذا كانت SUT أكبر من 200 kilo pound per
+
+514
+00:49:51,130 --> 00:49:55,430
+square inch نرجع تاني لل curve عندنا هيها تقريبا
+
+515
+00:49:58,250 --> 00:50:05,350
+يعني تقريبا جاية في حدود اللي عندها المية مية و
+
+516
+00:50:05,350 --> 00:50:09,670
+عشر تقريبا مية و خمسة هذا الخط اللي في النص يعني
+
+517
+00:50:09,670 --> 00:50:16,170
+هنا عند ميتين ميجا لحد ميتين ميجا هاي ميتين ميجا
+
+518
+00:50:16,170 --> 00:50:20,990
+تقريبا
+
+519
+00:50:20,990 --> 00:50:26,250
+هكون علاقة خطية اللي في النص
+
+520
+00:50:30,480 --> 00:50:36,740
+يعني إذا كانت ال S.U.T أقل من 200 كيلو pound per
+
+521
+00:50:36,740 --> 00:50:40,360
+square inch بتكون ال S.E. prime بيستوى نص ال S.U.T
+
+522
+00:50:40,360 --> 00:50:45,660
+إذا كانت ال S.U.T أكبر من 200 بتصير ال S.E. prime
+
+523
+00:50:45,660 --> 00:50:50,200
+بتثبت ال S.E. prime بتثبت معناته في علاقة بين ال
+
+524
+00:50:50,200 --> 00:50:55,330
+tensile strength و ال S.E. primeهي ال endurance
+
+525
+00:50:55,330 --> 00:50:59,770
+limit ل standard tensile specimen standard tensile
+
+526
+00:50:59,770 --> 00:51:03,050
+specimen يعني التجربة انعملت for the case of
+
+527
+00:51:03,050 --> 00:51:12,910
+completely reversed bending loading طيب
+
+528
+00:51:12,910 --> 00:51:13,030
+for design
+
+529
+00:51:25,000 --> 00:51:28,340
+an approximation of the idealized S-N diagram is
+
+530
+00:51:28,340 --> 00:51:35,780
+needed لحسابات التصميم محتاجين نعمل تقريب لل ideal
+
+531
+00:51:35,780 --> 00:51:42,680
+S-N diagram عشان
+
+532
+00:51:42,680 --> 00:51:50,040
+ت estimate fatigue
+
+533
+00:51:50,040 --> 00:51:53,900
+strength عند عشر أو استلاتة نرجع لل S-N diagram
+
+534
+00:51:59,760 --> 00:52:09,380
+هذا الاس اندراجرام هرسمه هنا برا اللي حقله هنا
+
+535
+00:52:09,380 --> 00:52:16,120
+عندي عدد سايكلز عشرة أس تلاتة وهنا عشرة أس ستة
+
+536
+00:52:16,120 --> 00:52:23,860
+وهنا هتكون عندي S U T وهنا عشرة أس صفر يعني واحد
+
+537
+00:52:28,590 --> 00:52:31,790
+لاحظوا ال care ممكن انا اقسمه ل 3 مناطق عند
+
+538
+00:52:31,790 --> 00:52:37,330
+المنطقة هذه العلاقة خطية سفق بين واحد و ألف و بين
+
+539
+00:52:37,330 --> 00:52:42,250
+ألف و مليون برضه علاقة خطية بس بسلوب مختلف الآن
+
+540
+00:52:42,250 --> 00:52:47,890
+هنتبع
+
+541
+00:52:47,890 --> 00:52:52,230
+مع بعضالان احنا حكينا ال total strain amplitude
+
+542
+00:52:52,230 --> 00:52:55,970
+مكون من جزئين elastic strain amplitude و plastic
+
+543
+00:52:55,970 --> 00:52:59,830
+strain amplitude ال elastic strain amplitude delta
+
+544
+00:52:59,830 --> 00:53:05,970
+epsilon elastic على اتنين بالساوية sigma f prime
+
+545
+00:53:05,970 --> 00:53:12,610
+على a السابق ان حكينا في اتنين ان اص بي
+
+546
+00:53:19,630 --> 00:53:23,450
+define specimen fatigue strength at a specified
+
+547
+00:53:23,450 --> 00:53:36,710
+number of cycles يعني هين هذا هسميها SF SF'
+
+548
+00:53:38,290 --> 00:53:41,990
+N و هذه ايش N
+
+549
+00:53:43,330 --> 00:53:48,090
+for a specified number of cycle او for a given
+
+550
+00:53:48,090 --> 00:53:52,910
+stress amplitude sf n prime هيعيش n cycles فهيكون
+
+551
+00:53:52,910 --> 00:53:56,570
+ال sf prime
+
+552
+00:53:56,570 --> 00:54:04,330
+n بالسوء E في delta epsilon elastic على اتنين من
+
+553
+00:54:04,330 --> 00:54:09,250
+اين اجت هذه؟ اجت هذه من هنا اذا انا دخلت ال
+
+554
+00:54:09,250 --> 00:54:10,110
+plastic range
+
+555
+00:54:13,310 --> 00:54:20,890
+و نزلت عملت unloading هذا بيظهر عنده اللي هو ال
+
+556
+00:54:20,890 --> 00:54:26,570
+delta epsilon plastic على اتنين وهذا
+
+557
+00:54:26,570 --> 00:54:33,410
+ال delta epsilon elastic على اتنين وهذا عاش ال
+
+558
+00:54:33,410 --> 00:54:43,960
+slope sigma وهذاسوف تكون أسف في الـ prime فهذا
+
+559
+00:54:43,960 --> 00:54:50,740
+ايه يا عزيزي؟ هذا موضلة في ال city هذا خط ال slope
+
+560
+00:54:50,740 --> 00:55:00,140
+بتاعه ايه؟ يعني خط المثلث هذا ستكون
+
+561
+00:55:00,140 --> 00:55:06,030
+ال slope is ايه؟ يعني ستكون أسف في ال primeهتكون
+
+562
+00:55:06,030 --> 00:55:10,090
+سواء E في delta epsilon elastic على 2 من هنا جاءت
+
+563
+00:55:10,090 --> 00:55:15,530
+العلاقة هذه اللي
+
+564
+00:55:15,530 --> 00:55:21,990
+هنحاوض هتكون سواء E في ال delta epsilon elastic
+
+565
+00:55:21,990 --> 00:55:29,550
+على 2 اللي هي هذه sigma F prime على E في 2N plus B
+
+566
+00:55:29,550 --> 00:55:38,100
+هتروح E مع E هتصفي السواء sigma F prime في 2NSB
+
+567
+00:55:38,100 --> 00:55:41,840
+الهي ال fatigue strength for a specified number of
+
+568
+00:55:41,840 --> 00:55:44,140
+cycles is given by this equal to sigma F prime
+
+569
+00:55:44,140 --> 00:55:51,700
+بيستوى 2N أصبى لو
+
+570
+00:55:51,700 --> 00:55:57,720
+كانت ال N عشر أس تلاتة يعني ألف هتكون ال fatigue
+
+571
+00:55:57,720 --> 00:56:03,200
+strength SF prime لعمر عشر أس تلاتة يعني لعمر ألف
+
+572
+00:56:03,200 --> 00:56:10,220
+cycle هتكون سوى sigma F primeفى اتنين فى عشرة أُس
+
+573
+00:56:10,220 --> 00:56:19,840
+تلاتة أُس بى هذه
+
+574
+00:56:19,840 --> 00:56:23,660
+هتساوي F
+
+575
+00:56:23,660 --> 00:56:26,860
+فى S U T
+
+576
+00:56:37,130 --> 00:56:40,550
+يعني هذا اللي بحكيه لما انا احكي اللي هو ال
+
+577
+00:56:40,550 --> 00:56:44,330
+fatigue strength لألف cycle بسواء sigma في prime
+
+578
+00:56:44,330 --> 00:56:48,720
+في اتنين في عشرة ثلاث في اص بياللي له قيمة معينة
+
+579
+00:56:48,720 --> 00:56:55,140
+أنا مش هعرفها هي عبارة عن some fraction of SUT
+
+580
+00:56:55,140 --> 00:57:00,160
+ممكن تكون يعني point 7 5 SUT ممكن تكون point 8 SUT
+
+581
+00:57:00,160 --> 00:57:03,320
+ممكن تكون point 5 SUT ممكن one point one SUT
+
+582
+00:57:03,320 --> 00:57:07,360
+معناته اللي بحكي أنه بغض النظر على قيمة ال fatigue
+
+583
+00:57:07,360 --> 00:57:10,920
+strength for one thousand cycle it will be some
+
+584
+00:57:10,920 --> 00:57:14,240
+fraction of the tensile strength of the specimen
+
+585
+00:57:15,750 --> 00:57:21,430
+يعني في الحالة هذه ال F هيكون ساوية Sigma F في
+
+586
+00:57:21,430 --> 00:57:27,670
+Prime في اتنين في عشر عقص تلاتة عقص B على S U T
+
+587
+00:57:27,670 --> 00:57:38,390
+طيب
+
+588
+00:57:38,390 --> 00:57:41,550
+ال
+
+589
+00:57:41,550 --> 00:57:47,200
+S A E ال هي Society of Automotive EngineersSociety
+
+590
+00:57:47,200 --> 00:57:49,620
+of Automated Engineers عملت ليه approximation
+
+591
+00:57:49,620 --> 00:57:52,940
+للسيجما اف برايم مواطول علاقة للسيجما اف برايم
+
+592
+00:57:52,940 --> 00:57:55,820
+بسلاوة S في حالة الوحدات الإنجليزية بسلاوة S U T
+
+593
+00:57:55,820 --> 00:58:01,410
+زائد خمسينأو في حالة الوحدات المترية ال sigma في
+
+594
+00:58:01,410 --> 00:58:04,690
+ال prime بيستوى sut زي 345 ميجا بس كده هذه ال
+
+595
+00:58:04,690 --> 00:58:08,310
+equation is given by society of automotive
+
+596
+00:58:08,310 --> 00:58:14,330
+engineer في حالة كانت ال harness brine لل material
+
+597
+00:58:14,330 --> 00:58:16,130
+تحت الدراسة أقل من 500
+
+598
+00:58:30,470 --> 00:58:34,670
+الان ممكن تكون عندى هاي هذى كمان ممكن اي نقطة هذى
+
+599
+00:58:34,670 --> 00:58:45,250
+هذى هذى SFN' هذى N الان عند النقطة هذى عند هذى N
+
+600
+00:58:45,250 --> 00:58:53,890
+NE وهين ال stress level ايش بيكون SE'
+
+601
+00:58:55,540 --> 00:59:01,580
+SE' يعني at the endurance limit at ال endurance
+
+602
+00:59:01,580 --> 00:59:05,500
+limit
+
+603
+00:59:05,500 --> 00:59:16,680
+بتكون دي ال SF' بيستوى SE' و ال N بيستوى NE معناته
+
+604
+00:59:16,680 --> 00:59:21,740
+لما نعوض في هذه المعادلة هذه المعادلة حسينا دي SE'
+
+605
+00:59:25,380 --> 00:59:32,540
+بساوة sigma F prime فى 2N عند ال endurance limit E
+
+606
+00:59:32,540 --> 00:59:40,400
+أُس B لو أخدت log الطرفين هشير عندي log خلّين أقسم
+
+607
+00:59:40,400 --> 00:59:47,300
+الطرفين على sigma F prime هشير عندي SE prime على
+
+608
+00:59:47,300 --> 00:59:53,560
+sigma F prime بساوة 2N E أُس B أخد log الطرفين
+
+609
+00:59:53,560 --> 00:59:59,740
+هشير عندي logالـ S A Prime على الـ Sigma F Prime
+
+610
+00:59:59,740 --> 01:00:07,440
+هتكون ساوية B في Log 2NA
+
+611
+01:00:07,440 --> 01:00:18,640
+معناة B هتكون تساوية Log الـ S A Prime على الـ
+
+612
+01:00:18,640 --> 01:00:26,650
+Sigma F Prime على Logالاتنين and ايه طبعا هنا عامل
+
+613
+01:00:26,650 --> 01:00:31,310
+minus في الكتاب بس انتبهوا هنا عنده مش أنا عامل
+
+614
+01:00:31,310 --> 01:00:34,730
+هنا se prime على sigma f prime هو عامل هنا العكس
+
+615
+01:00:34,730 --> 01:00:38,210
+sigma f prime على se prime اللي هي بيساوي minus
+
+616
+01:00:38,210 --> 01:00:42,650
+minus log sigma se prime على sigma f prime فهذه
+
+617
+01:00:42,650 --> 01:00:46,170
+صحيحة وهذه أش وهذه صحيحة بس انتبهوا هنا عنده se
+
+618
+01:00:46,170 --> 01:00:48,810
+prime على sigma f prime هنا عنده sigma f prime على
+
+619
+01:00:48,810 --> 01:00:54,450
+se prime لأن هنا عنده log scaleمعناته الـ B معطبع
+
+620
+01:00:54,450 --> 01:01:00,670
+الـ equation 612 الصفحة هذه تلخيص الكلام اللي
+
+621
+01:01:00,670 --> 01:01:01,190
+حكيناه
+
+622
+01:01:17,130 --> 01:01:23,250
+SF'n بيسوأ لـSF
+
+623
+01:01:23,250 --> 01:01:28,810
+'n هي الـfatigue strength for a standard fatigue
+
+624
+01:01:28,810 --> 01:01:33,330
+specimen for a given number of cycles and مُعطُب
+
+625
+01:01:33,330 --> 01:01:33,770
+العلاقات
+
+626
+01:01:40,920 --> 01:01:44,500
+الـ F اللي هي هتكون سيجما في الـ prime على S U T
+
+627
+01:01:44,500 --> 01:01:47,800
+في اتنين في عشر عشرة أس تلاتة أس بي والسيجما في
+
+628
+01:01:47,800 --> 01:01:51,500
+الـ prime as given by S Society of Automotive
+
+629
+01:01:51,500 --> 01:01:54,440
+Engineers في معادل ال English unit وفي معادل ال
+
+630
+01:01:54,440 --> 01:01:56,980
+metric unit بالسواء S U T زائد خمسين في حالة ال
+
+631
+01:01:56,980 --> 01:01:59,260
+English unit والسيجما في ال prime بالسواء S U T
+
+632
+01:01:59,260 --> 01:02:01,400
+زائد تلاتمية وخمسة الميجا بس كان في حالة ال metric
+
+633
+01:02:01,400 --> 01:02:08,850
+unit والـ B اللي هي هذهis given by minus log sigma
+
+634
+01:02:08,850 --> 01:02:18,710
+F prime على S A prime على log 2 N A طيب
+
+635
+01:02:18,710 --> 01:02:22,650
+احنا هنعوض في المعادلة هذه sigma F prime بنحسبه من
+
+636
+01:02:22,650 --> 01:02:27,170
+المعادلة هذه و ال B بنحسبه من المعادلة هذه يعني
+
+637
+01:02:27,170 --> 01:02:30,470
+عندي ال sigma F prime من هذه المعادلة و ال B من
+
+638
+01:02:30,470 --> 01:02:33,890
+هذه المعادلة منها بحسب ال S F و S F prime for a
+
+639
+01:02:33,890 --> 01:02:36,050
+specified number of cycles
+
+640
+01:02:44,990 --> 01:02:48,350
+ممكن المعادلة هي دي F بسوة سجما في البرانو على S U
+
+641
+01:02:48,350 --> 01:02:55,150
+T بسوة اتنين في عشر عقل تلاتة اص B هعملها على شكل
+
+642
+01:02:55,150 --> 01:02:59,650
+curve as
+
+643
+01:02:59,650 --> 01:03:02,730
+a function of S U T يعني دي هي ال S U T على المحور
+
+644
+01:03:02,730 --> 01:03:07,410
+الأفقي وعلى المحور الرأسي ايش ال Fو من ال curve
+
+645
+01:03:07,410 --> 01:03:11,890
+هذا اذا انا عارف ال tensile strength بطلع ال .. ال
+
+646
+01:03:11,890 --> 01:03:21,050
+.. ال F اللي هو figure 618 طيب
+
+647
+01:03:21,050 --> 01:03:27,030
+نرجع لل S-undagram كمان مرة ال S-undagram زي اللي
+
+648
+01:03:27,030 --> 01:03:31,730
+انتوا شايفين ممكن يتقسم لتلت مراحل المرحلة اللي
+
+649
+01:03:31,730 --> 01:03:37,300
+لها هي عبارة مرحلة من هنا SUTيعني خلّيني أحط
+
+650
+01:03:37,300 --> 01:03:47,000
+الإحداثيات بتاعة النقاط هذه عبارة عن واحد و S U T
+
+651
+01:03:47,000 --> 01:03:58,000
+وهنا النقطة التانية عبارة عن عشر أقل ثلاثة
+
+652
+01:03:58,000 --> 01:04:05,040
+و S F Prime
+
+653
+01:04:06,860 --> 01:04:19,760
+و هى عندى عشرة أقل ستة و S A prime معناته
+
+654
+01:04:19,760 --> 01:04:25,980
+احنا في حالة finite life fatigue حكينا two
+
+655
+01:04:25,980 --> 01:04:31,930
+equations equation من N equal واحد لألفEquation من
+
+656
+01:04:31,930 --> 01:04:36,630
+un equal الف لحد مليون يعني لأن ميل الخط هذا مختلف
+
+657
+01:04:36,630 --> 01:04:39,510
+عن ميل الخط هذا معناته اندي معدل تاني الخط هذا له
+
+658
+01:04:39,510 --> 01:04:45,690
+معدلة والخط هذا له معدلة نبدأ
+
+659
+01:04:45,690 --> 01:04:51,150
+في المرحلة الأولى اللى هى الان من واحد لألف او او
+
+660
+01:04:51,150 --> 01:04:57,050
+او ناخد التانى اللى من الف لمليون من الف لمليون
+
+661
+01:05:01,610 --> 01:05:09,630
+هنا لما عدد ال cycles ألف هتكون هنا هذه ساوية F S
+
+662
+01:05:09,630 --> 01:05:14,750
+U T وعند عشر أقصى ستة بتكون عشر أقصى ستة و S E
+
+663
+01:05:14,750 --> 01:05:21,870
+Prime يعني هذه النقطة هذه اللي هي عشر أقصى ثلاثة و
+
+664
+01:05:21,870 --> 01:05:30,370
+F S U T و النقطة هذه عبارة عن عشر أقصى ستة و S E
+
+665
+01:05:30,370 --> 01:05:30,670
+Prime
+
+666
+01:05:37,030 --> 01:05:41,690
+هذه على log .. log scale أو على ال .. ال .. على ال
+
+667
+01:05:41,690 --> 01:05:49,630
+semi log scale هتكون الأسقف في الفترة من عشر أُس
+
+668
+01:05:49,630 --> 01:06:00,630
+ثلاثة عشر أُس ستة بالسوء A في N أُس B طيب
+
+669
+01:06:00,630 --> 01:06:08,000
+في عندى نقطتين يعني النقطة الأولى atعشرة أس تلاتة
+
+670
+01:06:08,000 --> 01:06:14,400
+يعني N بالسوية عشرة أس تلاتة ال N بالسوية عشرة أس
+
+671
+01:06:14,400 --> 01:06:22,500
+تلاتة كون أندي ال S F بالسوية F S U T يعني نعوض
+
+672
+01:06:22,500 --> 01:06:34,630
+هنا عندي F S U T بتسوية A في عشرة أس تلاتةاس بي
+
+673
+01:06:34,630 --> 01:06:42,870
+هاي معادلة اياش واحد و at n بالساوية عشرة اقل ستة
+
+674
+01:06:42,870 --> 01:06:48,770
+بتكون الاس اف بالساوية اس اي prime او اس اي كده
+
+675
+01:06:48,770 --> 01:06:53,530
+نسميها اس اي يعني حيكون حنعود ان اس اف باس اي
+
+676
+01:06:53,530 --> 01:07:03,450
+بالساوية اي في عشرة اقل ستة اس بي هاي معادلة اتنين
+
+677
+01:07:06,810 --> 01:07:14,070
+يعني لو قسمت اتنين على .. على او واحد على اتنين
+
+678
+01:07:14,070 --> 01:07:23,330
+يعني نحكي divide واحد على اتنين هكون عندي F S U T
+
+679
+01:07:23,330 --> 01:07:34,730
+على S E هتروح A مع A هتكون عشر أقصد تلاتة أقصد B
+
+680
+01:07:35,840 --> 01:07:44,080
+على عشرة اقص ستة اقص بي المنطقة هتكون عشرة اقص
+
+681
+01:07:44,080 --> 01:07:49,580
+تلاتة على عشرة اقص ستة هتكون عشرة اقص سالب تلاتة
+
+682
+01:07:49,580 --> 01:07:59,060
+اقص بي يعني هتساوي عشرة اقص سالب تلاتة بي يعني لو
+
+683
+01:07:59,060 --> 01:08:11,080
+أخدت log الطرفين هكون دي logالـ F S U T على S A
+
+684
+01:08:11,080 --> 01:08:14,100
+بيستوى
+
+685
+01:08:14,100 --> 01:08:21,940
+ناقص تلاتة B log العشرة log العشرة مش بيستوى واحد
+
+686
+01:08:21,940 --> 01:08:28,780
+يعني هذا معناته هتستوى minus تلاتة B يعني B هتستوى
+
+687
+01:08:28,780 --> 01:08:49,310
+minus تلتلغ ال F S U T على S A طيب
+
+688
+01:08:49,310 --> 01:08:53,830
+معناته ال B بسواه ناقص لغ ال F S U T على S E
+
+689
+01:09:08,780 --> 01:09:19,580
+إذا كان عندي إذا كان عندي إذا كان عندي إذا
+
+690
+01:09:19,580 --> 01:09:19,820
+كان عندي إذا كان عندي إذا كان عندي إذا كان عندي
+
+691
+01:09:19,820 --> 01:09:20,280
+إذا كان عندي إذا كان عندي إذا كان عندي إذا كان
+
+692
+01:09:20,280 --> 01:09:20,340
+كان عندي إذا كان عندي إذا كان عندي إذا كان عندي
+
+693
+01:09:20,340 --> 01:09:21,140
+إذا كان عندي إذا كان عندي إذا كان عندي إذا كان
+
+694
+01:09:21,140 --> 01:09:21,760
+عندي إذا كان عندي إذا كان عندي إذا كان عندي إذا
+
+695
+01:09:21,760 --> 01:09:22,480
+كان عندي إذا كان عندي إذا كان عندي إذا كان عندي
+
+696
+01:09:22,480 --> 01:09:25,560
+إذا كان عندي إذا كان عندي إذا كان عندي إذا كان
+
+697
+01:09:25,560 --> 01:09:25,580
+عندي إذا كان عندي إذا كان عندي إذا كان عندي إذا
+
+698
+01:09:25,580 --> 01:09:25,680
+كان عندي إذا كان عندي إذا كان عندي إذا كان عندي
+
+699
+01:09:25,680 --> 01:09:36,000
+إذا كان عندي إذا كان عندي إذا كان عندي إذا كان
+
+700
+01:09:36,000 --> 01:09:42,620
+عندي إذا كان عنان اسمي يعني هتكون ال sigma
+
+701
+01:09:42,620 --> 01:09:58,300
+reversal على هكون
+
+702
+01:09:58,300 --> 01:10:03,360
+ال sigma reversal على
+
+703
+01:10:03,360 --> 01:10:09,780
+aبساوة N أُس B لأخذت log الطرفين هكون log sigma
+
+704
+01:10:09,780 --> 01:10:17,740
+reversible على A بساوة B أو ممكن أحكي انه مباشرة
+
+705
+01:10:17,740 --> 01:10:23,020
+عارف انه نجرب أخد ال log ان ال N بساوة sigma
+
+706
+01:10:23,020 --> 01:10:30,750
+reversible على A أُس 1 على Bو B احنا حاسبينها اللي
+
+707
+01:10:30,750 --> 01:10:39,870
+هي ناقص تلت ال log اللي هي F S U T على ال S
+
+708
+01:10:43,860 --> 01:10:47,060
+طبعا ال typical S underground is only applicable
+
+709
+01:10:47,060 --> 01:10:51,580
+for a completely reversed stress situation لأن هو
+
+710
+01:10:51,580 --> 01:10:55,720
+هي كان عمل لما أنا عملت جبت ال standard specimen
+
+711
+01:10:55,720 --> 01:10:59,000
+كان متعرض ل completely reversed stress completely
+
+712
+01:10:59,000 --> 01:11:03,880
+reversed stress وبالتالي ال equations هذه is
+
+713
+01:11:03,880 --> 01:11:06,180
+applicable for a completely reversed stress
+
+714
+01:11:06,180 --> 01:11:10,370
+situationfor other stress situations لحالات stress
+
+715
+01:11:10,370 --> 01:11:13,810
+situations اللي ال stress بيكونش completely
+
+716
+01:11:13,810 --> 01:11:17,530
+reversed a completely reversed stress with the
+
+717
+01:11:17,530 --> 01:11:21,510
+same life expectancy must be used on the S
+
+718
+01:11:21,510 --> 01:11:24,930
+underground بدنا نحسب اللي هو equivalent
+
+719
+01:11:24,930 --> 01:11:30,150
+equivalent completely reversed stress اللي بيعطي
+
+720
+01:11:30,150 --> 01:11:35,430
+نفس العمر لل stress level الحقيقي أو ال loading
+
+721
+01:11:35,430 --> 01:11:36,070
+الحقيقي
+
+722
+01:11:40,640 --> 01:11:45,060
+احنا so far عملنا المعادلة بين العشرة أس تلاتة
+
+723
+01:11:45,060 --> 01:11:51,290
+وعشرة أس ستة برضه في الفترة العمر بين واحدو10 اقص
+
+724
+01:11:51,290 --> 01:11:56,930
+3 ممكن اعمل معادلة خطية بنفس ال logic السابق هتطلع
+
+725
+01:11:56,930 --> 01:12:06,330
+المعادلة ال sf بيساوي sut في n اقص log f على 3 هذا
+
+726
+01:12:06,330 --> 01:12:12,830
+في حالة طبعا المعادلة هتتم اشتقاقها based on two
+
+727
+01:12:12,830 --> 01:12:17,940
+points اللي هي one point اللي هي هذهواحد و S U T و
+
+728
+01:12:17,940 --> 01:12:21,900
+النقطة التانية اللي هي عشر عقوس تلاتة و F S U T
+
+729
+01:12:21,900 --> 01:12:26,820
+عملت linear fit بين النقطتين هدول و حسبت اللي هي S
+
+730
+01:12:26,820 --> 01:12:42,500
+F بسوا و S U T في N أسلوك F على تلاتة شوف
+
+731
+01:12:42,500 --> 01:12:42,920
+example
+
+732
+01:13:03,010 --> 01:13:11,730
+given a 1050 hot rolled steel حديد رقمه عشرة خمسين
+
+733
+01:13:11,730 --> 01:13:15,670
+hot rolled عشرة خمسين نسبة الكربون في نصف بالمية
+
+734
+01:13:15,670 --> 01:13:20,810
+point five percent estimate the rotating beam
+
+735
+01:13:20,810 --> 01:13:31,810
+endurance limit بده احسب ال SE prime الان
+
+736
+01:13:32,930 --> 01:13:37,510
+الـ SE Prime نرجع
+
+737
+01:13:37,510 --> 01:13:44,050
+للمعادلات هي
+
+738
+01:13:44,050 --> 01:13:50,530
+هذه ال SE Prime بتساوي في حتة ال English net
+
+739
+01:13:50,530 --> 01:14:00,450
+بتساوي نص ال SUT إذا كانت ال SUT
+
+740
+01:14:03,000 --> 01:14:07,480
+أقل أو يساوي 200 كيلو pound per square inch اللي
+
+741
+01:14:07,480 --> 01:14:13,500
+هي عبارة عن 1400 ميجاباسكالة أو
+
+742
+01:14:13,500 --> 01:14:20,620
+بيساوي 100 كيلو pound per square inch لو تكون ال
+
+743
+01:14:20,620 --> 01:14:29,360
+SUT أكبر من 200 كيلو pound per square inchأو بالـ
+
+744
+01:14:29,360 --> 01:14:35,240
+metric units اللي هي عبارة عن 700 ميجا بسكال لما
+
+745
+01:14:35,240 --> 01:14:42,180
+ال SUT أكبر من 1400 ميجا بسكال هذه الاسئلة
+
+746
+01:14:42,180 --> 01:14:47,060
+الابراهية مانا اتبع الزمن ايش اشوف
+
+747
+01:14:47,060 --> 01:14:52,360
+ال SUT ال SUT ما هو اللي هاجيبها هاجيبها من
+
+748
+01:14:52,360 --> 01:14:55,940
+الجداول نروح على ال appendix في الكتاب
+
+749
+01:15:01,980 --> 01:15:09,580
+هناك كده لنا اللي هو الف
+
+750
+01:15:09,580 --> 01:15:14,940
+و خمسين الف
+
+751
+01:15:14,940 --> 01:15:17,500
+و خمسين ايه؟
+
+752
+01:15:28,290 --> 01:15:32,870
+معناته من تابل A A واحد و عشرين تابل A واحد و
+
+753
+01:15:32,870 --> 01:15:40,070
+عشرين هو حكيها ليه الحديد
+
+754
+01:15:40,070 --> 01:15:54,250
+عند ألف و خمسين خينا
+
+755
+01:15:54,250 --> 01:15:56,010
+نطلع على ال end notes
+
+756
+01:16:15,340 --> 01:16:21,520
+عندي الف و خمسين hot
+
+757
+01:16:21,520 --> 01:16:22,720
+rolled
+
+758
+01:16:24,900 --> 01:16:31,620
+steel طالع عندى هنا في جدول عندى الف و خمسين في
+
+759
+01:16:31,620 --> 01:16:34,840
+quenched and timbered في تلت أنواع quenched and
+
+760
+01:16:34,840 --> 01:16:41,160
+timbered هين
+
+761
+01:16:41,160 --> 01:16:47,720
+معطيني درجة الحرارة هين
+
+762
+01:16:47,720 --> 01:16:51,840
+عندى normalized عندين annealed
+
+763
+01:16:53,500 --> 01:16:57,480
+و هى المعطلة ال tensile and tensile strength خلينى
+
+764
+01:16:57,480 --> 01:17:18,580
+بس أعلم على المنطقة هذه خلينى
+
+765
+01:17:18,580 --> 01:17:19,600
+أعلم على المنطقة هذه
+
+766
+01:17:23,890 --> 01:17:27,390
+لاحظوا quenched and tempered عند أربعمائة فيهران
+
+767
+01:17:27,390 --> 01:17:30,950
+.. عند متين وخمس فيهرانهاي بتعطينا ال .. ال .. ال
+
+768
+01:17:30,950 --> 01:17:33,710
+.. ال ultimate tensile strength الف ومية وعشرين
+
+769
+01:17:33,710 --> 01:17:37,030
+عند أربعمائة وخمسة وعشر فيهرانهاي بتعطينا الف
+
+770
+01:17:37,030 --> 01:17:42,190
+وتسعين عند سبعمية وسبعتاش بيعطينا ال .. ال tensile
+
+771
+01:17:42,190 --> 01:17:46,210
+strength سبعمية وسبعتاش normalized سبعمية و تمانية
+
+772
+01:17:46,210 --> 01:17:51,720
+واربعين and yield ستمية وستةو تلاتين واضح ان عندنا
+
+773
+01:17:51,720 --> 01:17:57,580
+في المعلومات في نقص الآن الحديد ال ال الف و خمسين
+
+774
+01:17:57,580 --> 01:18:01,220
+خواصه الميكانيكية بتعتمد على المعالج الحراري اللي
+
+775
+01:18:01,220 --> 01:18:04,640
+بتستويله يعني واضح ان عندي هنا معالجات مختلفة هنا
+
+776
+01:18:04,640 --> 01:18:10,580
+عم اعمل equation and temperingيعني صار تبريد مفاجئ
+
+777
+01:18:10,580 --> 01:18:14,200
+من ال astonite range يعني حوالي تسعمائة درجة لحد
+
+778
+01:18:14,200 --> 01:18:18,360
+حوالي متين و خمسة طبعا أكيد هكون الحديد قاسي إذا
+
+779
+01:18:18,360 --> 01:18:23,180
+بتروحوا على ال ال ال utectoid steel ال TT دياجرام
+
+780
+01:18:23,180 --> 01:18:30,040
+في ال material science بيكون
+
+781
+01:18:30,040 --> 01:18:35,880
+عنده جائش
+
+782
+01:18:35,880 --> 01:18:36,540
+زي هيك
+
+783
+01:18:41,370 --> 01:18:45,030
+انت بتحكي في حدود اللي هو ال temper لحجم 2 و 5
+
+784
+01:18:45,030 --> 01:18:48,470
+يعني في ال range هذا يعني على الأغلب هتكوّنش
+
+785
+01:18:48,470 --> 01:18:54,610
+عندهين .. هين ب night و هين عندنا per light .. هين
+
+786
+01:18:54,610 --> 01:19:04,450
+.. هين .. هين .. هين عند course per light هذا
+
+787
+01:19:04,450 --> 01:19:08,470
+material science و هذا fine per light
+
+788
+01:19:11,370 --> 01:19:16,510
+طب من ناحية strength البداية أقوى من ال fine per
+
+789
+01:19:16,510 --> 01:19:19,670
+light و ال fine per light أقوى من ال coarse per
+
+790
+01:19:19,670 --> 01:19:23,090
+light فمعناته ال strength بتاعة الحديد ان انا مثلا
+
+791
+01:19:23,090 --> 01:19:26,310
+ببدأ من ال astronaut range و ببرد مثلا لدرجة حرارة
+
+792
+01:19:26,310 --> 01:19:31,210
+بعدين ببرد الغرفة او مثلا ممكن اجي زي هيك
+
+793
+01:19:34,230 --> 01:19:37,550
+فبعتمد على نوع الخواص الميكانيكي بتعتمد على نوع
+
+794
+01:19:37,550 --> 01:19:41,030
+المعارج الحريري انا مافيش اللي معلومات كافية فبغض
+
+795
+01:19:41,030 --> 01:19:43,950
+النظر افرض ان هو الحديد الاول هذا افرض ان هو
+
+796
+01:19:43,950 --> 01:19:48,110
+equenched and tempered يعني كانت ال SUT عنده ال
+
+797
+01:19:48,110 --> 01:19:53,270
+SUT بساوي
+
+798
+01:19:53,270 --> 01:19:57,770
+مية
+
+799
+01:19:57,770 --> 01:19:58,890
+و تلاتة ستين
+
+800
+01:20:02,370 --> 01:20:05,810
+kilo pound per square inch هذا واضح اقل من 200
+
+801
+01:20:05,810 --> 01:20:13,790
+معناته ال SE prime بسواء نص ال SUT هتطلع واحد
+
+802
+01:20:13,790 --> 01:20:21,490
+تمانين و نص kilo pound per square inch نفس
+
+803
+01:20:21,490 --> 01:20:25,110
+المعدن نفس المعدن يعني انا بملاحظة درسته في ال
+
+804
+01:20:25,110 --> 01:20:27,590
+material science نفس المعدن
+
+805
+01:20:31,400 --> 01:20:38,100
+يعني ممكن اوصله بالمعالجة الحرارية يمكن يعني من
+
+806
+01:20:38,100 --> 01:20:41,460
+خمسة لعشر أضعاف ال strength بس عمله معالجة حرارية
+
+807
+01:20:41,460 --> 01:20:45,680
+معينة معناته بالمعالجات السيناريات .. السيناريهات
+
+808
+01:20:45,680 --> 01:20:49,640
+المعالجات الحرارية المختلفة ممكن أحصل على infinite
+
+809
+01:20:49,640 --> 01:20:53,020
+number of properties للحديد فكيف انا بعمل معالجة
+
+810
+01:20:53,020 --> 01:20:57,060
+حرارية كيف بحس .. كيف بتحكم خواص الحديد سواء في ..
+
+811
+01:20:57,060 --> 01:21:00,460
+من ناحية التقسية او من ناحية ال .. ال .. ال .. ال
+
+812
+01:21:00,460 --> 01:21:04,340
+.. ال kneelingأو التطرية للحديد يمكن اقص الحديد او
+
+813
+01:21:04,340 --> 01:21:09,520
+اطريه من خلال معالجات حرارية معينة هذا درسته
+
+814
+01:21:09,520 --> 01:21:15,300
+بالتفصيل في course of material science هذا المطلوب
+
+815
+01:21:15,300 --> 01:21:19,540
+الأول المطلوب التاني المطلوب التاني the endurance
+
+816
+01:21:19,540 --> 01:21:22,640
+strength of a polished rotating beam specimen
+
+817
+01:21:22,640 --> 01:21:27,660
+corresponding to 10 او 4 cycles to failure بده ال
+
+818
+01:21:27,660 --> 01:21:30,340
+sf المطلوب التاني
+
+819
+01:21:35,600 --> 01:21:41,020
+إذا كانت عندي ال cycles في ال N بالساوية عشر أقصى
+
+820
+01:21:41,020 --> 01:21:52,720
+أربعة بده ال sf prime أكمل هو ال sf نرجع
+
+821
+01:21:52,720 --> 01:22:00,680
+لل care بتاعنا فاكرين احنا ال care جزئناها لمناطق
+
+822
+01:22:02,200 --> 01:22:06,200
+المنطقة هذه من n بالساوية واحد لعشرة اقصى ثلاثة
+
+823
+01:22:06,200 --> 01:22:10,280
+والخط هذا من عشرة اقصى ثلاثة لعشرة اقصى ستة معناته
+
+824
+01:22:10,280 --> 01:22:15,000
+احنا هنستخدم معادلة for n من عشر اقصى ثلاثة عشرة
+
+825
+01:22:15,000 --> 01:22:19,920
+ستة معناته بتلزمنا معادلة الخط هذا اللي هي اللي هي
+
+826
+01:22:19,920 --> 01:22:28,300
+هذا الخط اللي هي SF عنده ال SF بالساوية a n اقصى b
+
+827
+01:22:28,300 --> 01:22:31,120
+طيب
+
+828
+01:22:33,400 --> 01:22:37,940
+ال A بيساوي
+
+829
+01:22:37,940 --> 01:22:50,380
+F S U T الكل تربية على S E طيب
+
+830
+01:22:50,380 --> 01:22:58,420
+مانا مطلوب ان احسب ايه؟ ال F ال S U T كانت عندى
+
+831
+01:22:58,420 --> 01:23:00,220
+مية و تلاتة و ستين
+
+832
+01:23:08,250 --> 01:23:13,890
+تقريبا هادي عندى point سبعة تمانية point تمانية
+
+833
+01:23:13,890 --> 01:23:20,810
+يعني تقريبا point سبعة تلتين
+
+834
+01:23:20,810 --> 01:23:28,510
+ها point سبعة تسعة تلاتة يعني ممكن احكي F من
+
+835
+01:23:28,510 --> 01:23:38,860
+figure F بالساوية ال F بالساوية pointسبعة تسعة
+
+836
+01:23:38,860 --> 01:23:46,840
+تلاتة من figure ستة تمانتاش منها
+
+837
+01:23:46,840 --> 01:23:51,660
+بحسب ال A هتكون تساوي اللي هي point سبعة تسعة
+
+838
+01:23:51,660 --> 01:24:00,020
+تلاتة في ال SUT مية و تلاتة و ستين الكل تربيع على
+
+839
+01:24:00,020 --> 01:24:06,180
+SE اللي هي واحد تمانين و نص بحسب ال A
+
+840
+01:24:10,700 --> 01:24:17,380
+point سبعة point
+
+841
+01:24:17,380 --> 01:24:28,520
+سبعة تسعة تلاتة في مية و تلاتة و ستين تقسيم
+
+842
+01:24:28,520 --> 01:24:31,740
+واحد
+
+843
+01:24:31,740 --> 01:24:36,520
+تمانين و
+
+844
+01:24:36,520 --> 01:24:36,840
+نص
+
+845
+01:24:41,840 --> 01:24:52,800
+طيب كمان مرة point سبعة تسعة تلاتة في مية و تلاتة
+
+846
+01:24:52,800 --> 01:24:58,060
+و ستين يساوي في
+
+847
+01:25:15,210 --> 01:25:25,570
+تقسيم واحد تمانين و نص بتطلع اتنين و خمسة
+
+848
+01:25:25,570 --> 01:25:33,770
+kilo pound per square inch هذه ال a هذه ايش ال a
+
+849
+01:25:33,770 --> 01:25:40,150
+ال b ال
+
+850
+01:25:40,150 --> 01:25:40,450
+b
+
+851
+01:25:43,570 --> 01:25:51,310
+سواء ناقص تلت log fsut
+
+852
+01:25:51,310 --> 01:26:03,230
+على sa ستكون سواء ناقص تلت log بنسبة تسعة تلتة في
+
+853
+01:26:03,230 --> 01:26:08,610
+مية و تلتة و ستين على sa اللي هي واحد تمانين و نص
+
+854
+01:26:08,610 --> 01:26:11,850
+و
+
+855
+01:26:11,850 --> 01:26:17,350
+بنحسبهااللي أنا حسبت a و b بروح أعوض عن a هنا
+
+856
+01:26:17,350 --> 01:26:22,390
+بيعوض عن a اللي هي هذه بيعوض عن b اللي هي هذه و
+
+857
+01:26:22,390 --> 01:26:31,330
+اللي أنا بستوى عشر قصر أربعة بحسب الأسافر
+
+858
+01:26:31,330 --> 01:26:36,670
+المطلوب
+
+859
+01:26:36,670 --> 01:26:43,400
+التالت the expected lifeof a polished rotating
+
+860
+01:26:43,400 --> 01:26:48,580
+beam specimen under a completely reversed stress
+
+861
+01:26:48,580 --> 01:26:57,160
+of 55 kilopound per square inch بدو
+
+862
+01:26:57,160 --> 01:26:59,780
+ال expected life of a polished rotating beam
+
+863
+01:26:59,780 --> 01:27:02,360
+specimen under a completely reversed stress of 55
+
+864
+01:27:02,360 --> 01:27:05,380
+kilopound per square inch
+
+865
+01:27:09,540 --> 01:27:15,900
+ال SE عندنا اكهن طلعت واحد تمانين وانص كيلو pound
+
+866
+01:27:15,900 --> 01:27:23,680
+per square inch بده ال life لما نكون ال .. ال ..
+
+867
+01:27:23,680 --> 01:27:28,660
+ال specimen تحت تأثير complete reverse stress of
+
+868
+01:27:28,660 --> 01:27:31,940
+fifty five kilo pound per square inch لحظوا الخمسة
+
+869
+01:27:31,940 --> 01:27:32,840
+خمسين اشمالها
+
+870
+01:27:35,280 --> 01:27:39,720
+أقل من واحد تمانية نص اللي هي ال endurance limit و
+
+871
+01:27:39,720 --> 01:27:43,680
+احنا عرفنا ال endurance limit هي ال stress level
+
+872
+01:27:43,680 --> 01:27:49,590
+stress amplitude level below whichthe part will
+
+873
+01:27:49,590 --> 01:27:54,950
+endure forever هو ال stress level اللي تحته القطع
+
+874
+01:27:54,950 --> 01:27:57,530
+هتعيش لمال نهاية معناته ال expected مافيش داعي
+
+875
+01:27:57,530 --> 01:28:03,590
+أحسب لأنه ال stress amplitude level is below ال SE
+
+876
+01:28:03,590 --> 01:28:09,030
+معناته هذا هعيش لمال نهاية معناته عمره لمال نهاية
+
+877
+01:28:09,030 --> 01:28:12,970
+لكن لو حكيتلك والله ال stress level تسعين kilo
+
+878
+01:28:12,970 --> 01:28:19,700
+pound التسعين أكبرمن الواحد تمانين و نص مانعة ما
+
+879
+01:28:19,700 --> 01:28:23,760
+زالت سن أكبر واحد و نص مانعة متوقع أن أعيش حياة
+
+880
+01:28:23,760 --> 01:28:28,360
+أطول أعيش
+
+881
+01:28:28,360 --> 01:28:32,520
+حياة أقصر طبعا او نحكي finite life بحسبها من نفس
+
+882
+01:28:32,520 --> 01:28:37,840
+المعادلة هذه أنا رودي حسبت ال A حسبت ال B و الأسأف
+
+883
+01:28:37,840 --> 01:28:40,520
+معطاة عندي و منها بحسب H ال N
+
+884
+01:29:01,850 --> 01:29:05,910
+طيب الان ال endurance limit اللي .. اللي .. اللي
+
+885
+01:29:05,910 --> 01:29:10,170
+احنا بنعرفها لحد اللحظة اللي هي ال S A prime is
+
+886
+01:29:10,170 --> 01:29:13,910
+for carefully prepared test specimen يعني ال S A
+
+887
+01:29:13,910 --> 01:29:22,250
+prime هدى تمقياسة و حسابها أو تم قياسة و حسابها من
+
+888
+01:29:22,250 --> 01:29:28,530
+خلال اللي هو ال standard fatigue test ال standard
+
+889
+01:29:28,530 --> 01:29:32,730
+fatigue test بتطلب standard أعينة معيارية الأعينة
+
+890
+01:29:32,730 --> 01:29:36,130
+المعيارية إلها شكل معين و إلها ال Polish بتكون
+
+891
+01:29:36,130 --> 01:29:39,930
+نعمة جدا رقم واحد ال loading بتاعها بيكون
+
+892
+01:29:39,930 --> 01:29:44,090
+completely reversed completely reversed bending
+
+893
+01:29:44,090 --> 01:29:49,170
+loadingالان القطع الميكانيكية اللى على أرض الواقع
+
+894
+01:29:49,170 --> 01:29:55,390
+بتكونش مواصفاتها مطابقة للعينة الميارية من حيث
+
+895
+01:29:55,390 --> 01:30:00,810
+الشكل الجيومتري و من حيث ال finish و من حيث ال
+
+896
+01:30:00,810 --> 01:30:07,050
+loading و من حيث الظروف المحيطة لدرجته الحرارةمن
+
+897
+01:30:07,050 --> 01:30:11,110
+حيث ال reliability فالظروف الحقيقية مختلفة عن
+
+898
+01:30:11,110 --> 01:30:16,050
+الظروف المعيارية هذا بيقودنا انه لو اختلفت .. لو
+
+899
+01:30:16,050 --> 01:30:19,030
+كانت الظروف الحقيقية او القطع الميكانيكية تحت
+
+900
+01:30:19,030 --> 01:30:24,490
+الدراسة مختلفة عن الظروف المعيارية فحص الإجهاد
+
+901
+01:30:24,490 --> 01:30:28,910
+التوتر ال fatigue test معناته we have to modify
+
+902
+01:30:29,780 --> 01:30:34,260
+القيمة اللى حصلنا عليها من ال standard fatigue
+
+903
+01:30:34,260 --> 01:30:37,040
+test specimen كمان مرة ال standard test test
+
+904
+01:30:37,040 --> 01:30:42,780
+standard fatigue test بيصير لعينة معيارية اللى لها
+
+905
+01:30:42,780 --> 01:30:46,100
+شكل معين اللى لها surface finish معينة ال loading
+
+906
+01:30:46,100 --> 01:30:49,320
+بيكون completely reverse bending أرض الواقع ممكن
+
+907
+01:30:49,320 --> 01:30:52,940
+يكون ال loading torsional ممكن يكون axial ممكن
+
+908
+01:30:52,940 --> 01:30:57,420
+يكون bending ممكن يكونcombination بين axel او
+
+909
+01:30:57,420 --> 01:31:00,400
+bending بين bending و torsion او بين bending و طلع
+
+910
+01:31:00,400 --> 01:31:04,700
+نتشير ففي متغيرات كتير الحجم ال size القطر تاع
+
+911
+01:31:04,700 --> 01:31:07,700
+القطع الميكانيكي مختلف عن العين المعيارية its
+
+912
+01:31:07,700 --> 01:31:14,000
+surface finish مختلفدرجة الحرارة مختلفة ممكن يكون
+
+913
+01:31:14,000 --> 01:31:17,400
+ال stress concentration ففي ظروف حقيقية مختلفة عن
+
+914
+01:31:17,400 --> 01:31:22,440
+الظروف الميارية هذا بتطلب ان اعمل انا to modify
+
+915
+01:31:22,440 --> 01:31:24,880
+the endurance limit to modify ال endurance limit I
+
+916
+01:31:24,880 --> 01:31:30,400
+need some modification factors معناتهبحتاج اعدل
+
+917
+01:31:30,400 --> 01:31:36,000
+هستخدم معادلة SE بيساوي K A K B K C K D K E K F S
+
+918
+01:31:36,000 --> 01:31:41,400
+E prime ال S E prime هي ال endurance limit for a
+
+919
+01:31:41,400 --> 01:31:44,900
+standard tensile specimen under completely
+
+920
+01:31:44,900 --> 01:31:51,060
+reversed bending loading ال K A factor بيعمل
+
+921
+01:31:51,060 --> 01:31:53,960
+correction لل surface condition ال roughness
+
+922
+01:31:53,960 --> 01:31:59,070
+مختلفة او ال finish مختلفال KB بيعمل correction ل
+
+923
+01:31:59,070 --> 01:32:05,710
+ال size القطر مثلا في العين المعيارية نص انش عطب
+
+924
+01:32:05,710 --> 01:32:10,450
+يمكن يكون واحد انش ال KC بيعمل correction لل load
+
+925
+01:32:10,450 --> 01:32:14,920
+factor ال load في حالة العين المعياريةاللي هو
+
+926
+01:32:14,920 --> 01:32:17,520
+bending .. completely reversed bending ممكن تكون
+
+927
+01:32:17,520 --> 01:32:22,020
+completely reversed .. completely reversed torsion
+
+928
+01:32:22,020 --> 01:32:24,900
+او تكون axial loading او combination بين هذه
+
+929
+01:32:24,900 --> 01:32:29,520
+الأنواع التحميلات المختلفة الآن العين المعيرية تم
+
+930
+01:32:29,520 --> 01:32:33,140
+فحصها عند درجة حرارة الغرفة لكن القطعة الميكانيكية
+
+931
+01:32:33,140 --> 01:32:39,730
+ممكن تكون قطعةفي بيئة الحرارة بتاعتها مرتفعة مثلا
+
+932
+01:32:39,730 --> 01:32:45,130
+وبالتالي محتاج اعمل تعديل البيانات عندما حكيت SE
+
+933
+01:32:45,130 --> 01:32:50,150
+prime بساهم نص ال SET كانت for a fifty percent
+
+934
+01:32:50,150 --> 01:32:55,570
+reliability of the data what if اذا كانت
+
+935
+01:32:55,570 --> 01:32:57,710
+reliability تسعين في المية او خمسين سنين في المية
+
+936
+01:32:57,710 --> 01:33:02,260
+او تسعة سنين في الميةالـ KF موصليني من
+
+937
+01:33:02,260 --> 01:33:05,400
+miscellaneous effects factor يعني عامل تعديل
+
+938
+01:33:05,400 --> 01:33:10,180
+لشغلات كتير يعني .. يعني غير متوقع ممكن يكون .. هل
+
+939
+01:33:10,180 --> 01:33:13,720
+القطع ممكن تشتغل في بيئة .. في بيئة بحرية يعني
+
+940
+01:33:13,720 --> 01:33:18,200
+عندك ملوحة عالية ممكن تشتغل في بيئة كيميائية ممكن
+
+941
+01:33:18,200 --> 01:33:24,500
+في عندك إجهادات residual stresses ممكن تشتغل في
+
+942
+01:33:24,500 --> 01:33:29,210
+بيئة فيها إشعاع ف ..هذه اللي بتاخذ قرار فيها
+
+943
+01:33:29,210 --> 01:33:34,930
+المصمم هو بيقدر انه I need محتاج انا اعمل
+
+944
+01:33:34,930 --> 01:33:39,850
+modification بنسبة 50% بنسبة 60% to take other
+
+945
+01:33:39,850 --> 01:33:45,510
+effects المحاضرة الجاي هندرس ال factors هدول
+
+946
+01:33:45,510 --> 01:33:51,550
+بالتفصيل كيف حساب كل factor على حدة بهدف الوصول ل
+
+947
+01:33:51,550 --> 01:33:55,330
+endurance limit للقطع الميكانيكية اللي هي موجودة
+
+948
+01:33:55,330 --> 01:33:56,570
+على أرض الواقع
+
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/cZA5kLPfQUI_raw.json b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/cZA5kLPfQUI_raw.json
new file mode 100644
index 0000000000000000000000000000000000000000..0ba6c21a992acac84e561ffb48255a82db7c8ff7
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/cZA5kLPfQUI_raw.json
@@ -0,0 +1 @@
+{"segments": [{"id": 1, "seek": 3240, "start": 4.94, "end": 32.4, "text": "بسم الله الرحمن الرحيم السلام عليكم اليوم هنكمل المحاضرة الرابعة في ال .. او الخامسة في ال fatigue .. fatigue failure for variable loading اليوم هنشوف how to characterize fluctuating stress خلينا نعمل بعض الملاحظات كتقديم الان ال S and diagram اللي هو ناتج عن فحص الفتيك المعياري", "tokens": [3555, 38251, 21984, 34892, 5016, 27842, 34892, 5016, 32640, 21136, 37440, 25894, 24793, 45595, 20498, 8032, 1863, 24793, 1211, 9673, 5016, 46958, 25720, 34892, 16758, 27884, 8978, 2423, 4386, 1975, 2407, 33962, 10943, 3794, 3660, 8978, 2423, 20574, 4386, 20574, 7763, 337, 7006, 15114, 45595, 20498, 8032, 1863, 8592, 38688, 577, 281, 38463, 23448, 32438, 4244, 16490, 20292, 8315, 8717, 25957, 1211, 45030, 11242, 9673, 15040, 5016, 19913, 9307, 9122, 2655, 4587, 16254, 2304, 2423, 7649, 2423, 318, 293, 10686, 13672, 1829, 31439, 8717, 9307, 7435, 18871, 6156, 5016, 9381, 27188, 31371, 4117, 9673, 3615, 1829, 9640, 1829], "avg_logprob": -0.14401831500457996, "compression_ratio": 1.6719367588932805, "no_speech_prob": 1.7881393432617188e-07, "words": [{"start": 4.94, "end": 5.3, "word": "بسم", "probability": 0.837646484375}, {"start": 5.3, "end": 5.56, "word": " الله", "probability": 0.970703125}, {"start": 5.56, "end": 5.84, "word": " الرحمن", "probability": 0.94677734375}, {"start": 5.84, "end": 6.22, "word": " الرحيم", "probability": 0.9899088541666666}, {"start": 6.22, "end": 6.72, "word": " السلام", "probability": 0.93310546875}, {"start": 6.72, "end": 7.28, "word": " عليكم", "probability": 0.95166015625}, {"start": 7.28, "end": 7.74, "word": " اليوم", "probability": 0.920654296875}, {"start": 7.74, "end": 8.4, "word": " هنكمل", "probability": 0.9676513671875}, {"start": 8.4, "end": 9.38, "word": " المحاضرة", "probability": 0.9840087890625}, {"start": 9.38, "end": 10.72, "word": " الرابعة", "probability": 0.8697916666666666}, {"start": 10.72, "end": 10.94, "word": " في", "probability": 0.43359375}, {"start": 10.94, "end": 11.4, "word": " ال", "probability": 0.55810546875}, {"start": 11.4, "end": 11.6, "word": " ..", "probability": 0.80029296875}, {"start": 11.6, "end": 11.8, "word": " او", "probability": 0.804931640625}, {"start": 11.8, "end": 12.5, "word": " الخامسة", "probability": 0.955078125}, {"start": 12.5, "end": 12.68, "word": " في", "probability": 0.94677734375}, {"start": 12.68, "end": 13.02, "word": " ال", "probability": 0.6298828125}, {"start": 13.02, "end": 13.44, "word": " fatigue", "probability": 0.94677734375}, {"start": 13.44, "end": 13.98, "word": " ..", "probability": 0.5966796875}, {"start": 13.98, "end": 16.1, "word": " fatigue", "probability": 0.88427734375}, {"start": 16.1, "end": 16.66, "word": " failure", "probability": 0.9287109375}, {"start": 16.66, "end": 17.38, "word": " for", "probability": 0.95556640625}, {"start": 17.38, "end": 17.7, "word": " variable", "probability": 0.95849609375}, {"start": 17.7, "end": 18.18, "word": " loading", "probability": 0.92724609375}, {"start": 18.18, "end": 19.4, "word": " اليوم", "probability": 0.96826171875}, {"start": 19.4, "end": 19.8, "word": " هنشوف", "probability": 0.9656982421875}, {"start": 19.8, "end": 20.06, "word": " how", "probability": 0.8779296875}, {"start": 20.06, "end": 20.28, "word": " to", "probability": 0.9873046875}, {"start": 20.28, "end": 20.9, "word": " characterize", "probability": 0.8818359375}, {"start": 20.9, "end": 21.88, "word": " fluctuating", "probability": 0.94580078125}, {"start": 21.88, "end": 22.84, "word": " stress", "probability": 0.94873046875}, {"start": 22.84, "end": 23.34, "word": " خلينا", "probability": 0.6844075520833334}, {"start": 23.34, "end": 23.48, "word": " نعمل", "probability": 0.9949544270833334}, {"start": 23.48, "end": 23.7, "word": " بعض", "probability": 0.95751953125}, {"start": 23.7, "end": 24.44, "word": " الملاحظات", "probability": 0.98671875}, {"start": 24.44, "end": 25.26, "word": " كتقديم", "probability": 0.960546875}, {"start": 25.26, "end": 26.5, "word": " الان", "probability": 0.621826171875}, {"start": 26.5, "end": 26.72, "word": " ال", "probability": 0.96826171875}, {"start": 26.72, "end": 26.98, "word": " S", "probability": 0.315185546875}, {"start": 26.98, "end": 27.26, "word": " and", "probability": 0.2158203125}, {"start": 27.26, "end": 27.88, "word": " diagram", "probability": 0.61474609375}, {"start": 27.88, "end": 29.08, "word": " اللي", "probability": 0.916259765625}, {"start": 29.08, "end": 29.26, "word": " هو", "probability": 0.98681640625}, {"start": 29.26, "end": 29.6, "word": " ناتج", "probability": 0.98486328125}, {"start": 29.6, "end": 29.78, "word": " عن", "probability": 0.9296875}, {"start": 29.78, "end": 30.4, "word": " فحص", "probability": 0.97802734375}, {"start": 30.4, "end": 31.66, "word": " الفتيك", "probability": 0.822265625}, {"start": 31.66, "end": 32.4, "word": " المعياري", "probability": 0.89072265625}], "temperature": 1.0}, {"id": 2, "seek": 5700, "start": 33.02, "end": 57.0, "text": "يطبق في حالة ال load كان completely reversed bending stress other stress situations اللي بتكون مش completely reversed بنفعش استخدم ال as underground معناته لازم اشوف طريقة how to characterize fluctuating stresses", "tokens": [1829, 9566, 3555, 4587, 8978, 11331, 6027, 3660, 2423, 3677, 25961, 2584, 30563, 22487, 4244, 661, 4244, 6851, 13672, 1829, 39894, 30544, 37893, 2584, 30563, 44945, 5172, 3615, 8592, 44713, 9778, 40448, 2423, 382, 14977, 20449, 8315, 47395, 5296, 31377, 2304, 1975, 8592, 38688, 23032, 16572, 28671, 577, 281, 38463, 23448, 32438, 27732], "avg_logprob": -0.1931423572478471, "compression_ratio": 1.40625, "no_speech_prob": 0.0, "words": [{"start": 33.02, "end": 33.96, "word": "يطبق", "probability": 0.9483642578125}, {"start": 33.96, "end": 34.1, "word": " في", "probability": 0.95751953125}, {"start": 34.1, "end": 34.58, "word": " حالة", "probability": 0.9957682291666666}, {"start": 34.58, "end": 34.9, "word": " ال", "probability": 0.8515625}, {"start": 34.9, "end": 35.26, "word": " load", "probability": 0.80908203125}, {"start": 35.26, "end": 35.84, "word": " كان", "probability": 0.81591796875}, {"start": 35.84, "end": 36.92, "word": " completely", "probability": 0.673828125}, {"start": 36.92, "end": 37.6, "word": " reversed", "probability": 0.89306640625}, {"start": 37.6, "end": 38.28, "word": " bending", "probability": 0.3740234375}, {"start": 38.28, "end": 38.96, "word": " stress", "probability": 0.97314453125}, {"start": 38.96, "end": 41.1, "word": " other", "probability": 0.7109375}, {"start": 41.1, "end": 41.66, "word": " stress", "probability": 0.97705078125}, {"start": 41.66, "end": 43.24, "word": " situations", "probability": 0.83837890625}, {"start": 43.24, "end": 43.52, "word": " اللي", "probability": 0.9541015625}, {"start": 43.52, "end": 43.86, "word": " بتكون", "probability": 0.888427734375}, {"start": 43.86, "end": 43.96, "word": " مش", "probability": 0.60009765625}, {"start": 43.96, "end": 44.26, "word": " completely", "probability": 0.8076171875}, {"start": 44.26, "end": 44.8, "word": " reversed", "probability": 0.9345703125}, {"start": 44.8, "end": 48.7, "word": " بنفعش", "probability": 0.8245849609375}, {"start": 48.7, "end": 49.32, "word": " استخدم", "probability": 0.8671875}, {"start": 49.32, "end": 49.52, "word": " ال", "probability": 0.89013671875}, {"start": 49.52, "end": 49.74, "word": " as", "probability": 0.1300048828125}, {"start": 49.74, "end": 50.2, "word": " underground", "probability": 0.578125}, {"start": 50.2, "end": 50.76, "word": " معناته", "probability": 0.8223470052083334}, {"start": 50.76, "end": 52.5, "word": " لازم", "probability": 0.9837239583333334}, {"start": 52.5, "end": 53.44, "word": " اشوف", "probability": 0.8671875}, {"start": 53.44, "end": 54.0, "word": " طريقة", "probability": 0.9886067708333334}, {"start": 54.0, "end": 54.48, "word": " how", "probability": 0.931640625}, {"start": 54.48, "end": 54.74, "word": " to", "probability": 0.98291015625}, {"start": 54.74, "end": 55.3, "word": " characterize", "probability": 0.8701171875}, {"start": 55.3, "end": 56.36, "word": " fluctuating", "probability": 0.969970703125}, {"start": 56.36, "end": 57.0, "word": " stresses", "probability": 0.65576171875}], "temperature": 1.0}, {"id": 3, "seek": 7728, "start": 59.82, "end": 77.28, "text": "الباقي عندي مجموعة من الأمثلة، عندي مثلا هنا stress بتغير من هذا الزمن، فيش fight or rebel، عندي هاي حالة تانية، هاي حالة تالتة، ممكن تكون أي curve، ممكن تكون إشي زي هيك", "tokens": [6027, 3555, 995, 38436, 18871, 16254, 3714, 7435, 2304, 2407, 27884, 9154, 16247, 2304, 12984, 37977, 12399, 18871, 16254, 50113, 15040, 34105, 4244, 39894, 17082, 13546, 9154, 23758, 6024, 110, 27842, 12399, 8978, 8592, 2092, 420, 28293, 12399, 18871, 16254, 8032, 47302, 11331, 6027, 3660, 6055, 7649, 10632, 12399, 8032, 47302, 11331, 6027, 3660, 6055, 6027, 2655, 3660, 12399, 3714, 43020, 6055, 30544, 36632, 7605, 12399, 3714, 43020, 6055, 30544, 11933, 8592, 1829, 30767, 1829, 39896, 4117], "avg_logprob": -0.17407852353957984, "compression_ratio": 1.6745562130177514, "no_speech_prob": 0.0, "words": [{"start": 59.82, "end": 60.16, "word": "الباقي", "probability": 0.54974365234375}, {"start": 60.16, "end": 60.34, "word": " عندي", "probability": 0.81689453125}, {"start": 60.34, "end": 60.64, "word": " مجموعة", "probability": 0.88046875}, {"start": 60.64, "end": 60.78, "word": " من", "probability": 0.98388671875}, {"start": 60.78, "end": 61.66, "word": " الأمثلة،", "probability": 0.89443359375}, {"start": 61.66, "end": 61.92, "word": " عندي", "probability": 0.9345703125}, {"start": 61.92, "end": 62.2, "word": " مثلا", "probability": 0.984375}, {"start": 62.2, "end": 62.48, "word": " هنا", "probability": 0.4072265625}, {"start": 62.48, "end": 63.7, "word": " stress", "probability": 0.94140625}, {"start": 63.7, "end": 64.38, "word": " بتغير", "probability": 0.9217122395833334}, {"start": 64.38, "end": 64.5, "word": " من", "probability": 0.9853515625}, {"start": 64.5, "end": 64.64, "word": " هذا", "probability": 0.482177734375}, {"start": 64.64, "end": 66.18, "word": " الزمن،", "probability": 0.8782958984375}, {"start": 66.18, "end": 66.64, "word": " فيش", "probability": 0.675048828125}, {"start": 66.64, "end": 66.82, "word": " fight", "probability": 0.8134765625}, {"start": 66.82, "end": 66.94, "word": " or", "probability": 0.74365234375}, {"start": 66.94, "end": 68.68, "word": " rebel،", "probability": 0.64208984375}, {"start": 68.68, "end": 68.98, "word": " عندي", "probability": 0.833984375}, {"start": 68.98, "end": 69.14, "word": " هاي", "probability": 0.74755859375}, {"start": 69.14, "end": 69.76, "word": " حالة", "probability": 0.9900716145833334}, {"start": 69.76, "end": 71.52, "word": " تانية،", "probability": 0.9566650390625}, {"start": 71.52, "end": 71.74, "word": " هاي", "probability": 0.917724609375}, {"start": 71.74, "end": 72.16, "word": " حالة", "probability": 0.9943033854166666}, {"start": 72.16, "end": 73.32, "word": " تالتة،", "probability": 0.97138671875}, {"start": 73.32, "end": 73.52, "word": " ممكن", "probability": 0.98486328125}, {"start": 73.52, "end": 73.86, "word": " تكون", "probability": 0.991455078125}, {"start": 73.86, "end": 74.98, "word": " أي", "probability": 0.6533203125}, {"start": 74.98, "end": 76.0, "word": " curve،", "probability": 0.810302734375}, {"start": 76.0, "end": 76.2, "word": " ممكن", "probability": 0.98193359375}, {"start": 76.2, "end": 76.44, "word": " تكون", "probability": 0.763671875}, {"start": 76.44, "end": 76.74, "word": " إشي", "probability": 0.82080078125}, {"start": 76.74, "end": 76.94, "word": " زي", "probability": 0.9921875}, {"start": 76.94, "end": 77.28, "word": " هيك", "probability": 0.9609375}], "temperature": 1.0}, {"id": 4, "seek": 11086, "start": 85.44, "end": 110.86, "text": "هذا is fluctuating لا هو sinusoid ولا هو repeated ولا هو completely reversed الآن خليني أعمل بعض ال definitions عندي هنا الزمن وهنا ال stress", "tokens": [3224, 15730, 307, 23448, 32438, 20193, 31439, 41503, 17079, 49429, 31439, 10477, 49429, 31439, 2584, 30563, 6024, 48506, 16490, 1211, 9957, 1829, 5551, 25957, 1211, 45030, 11242, 2423, 21988, 18871, 16254, 34105, 6024, 110, 27842, 37037, 8315, 2423, 4244], "avg_logprob": -0.17460937276482583, "compression_ratio": 1.3566433566433567, "no_speech_prob": 0.0, "words": [{"start": 85.44, "end": 85.74, "word": "هذا", "probability": 0.899169921875}, {"start": 85.74, "end": 85.92, "word": " is", "probability": 0.7275390625}, {"start": 85.92, "end": 86.78, "word": " fluctuating", "probability": 0.956787109375}, {"start": 86.78, "end": 87.1, "word": " لا", "probability": 0.529296875}, {"start": 87.1, "end": 87.48, "word": " هو", "probability": 0.9833984375}, {"start": 87.48, "end": 88.9, "word": " sinusoid", "probability": 0.7103271484375}, {"start": 88.9, "end": 89.14, "word": " ولا", "probability": 0.8447265625}, {"start": 89.14, "end": 89.58, "word": " هو", "probability": 0.98681640625}, {"start": 89.58, "end": 90.18, "word": " repeated", "probability": 0.9658203125}, {"start": 90.18, "end": 90.54, "word": " ولا", "probability": 0.9560546875}, {"start": 90.54, "end": 91.0, "word": " هو", "probability": 0.982421875}, {"start": 91.0, "end": 92.32, "word": " completely", "probability": 0.83984375}, {"start": 92.32, "end": 92.92, "word": " reversed", "probability": 0.92919921875}, {"start": 92.92, "end": 99.16, "word": " الآن", "probability": 0.74853515625}, {"start": 99.16, "end": 99.56, "word": " خليني", "probability": 0.8016357421875}, {"start": 99.56, "end": 99.82, "word": " أعمل", "probability": 0.8400065104166666}, {"start": 99.82, "end": 100.14, "word": " بعض", "probability": 0.98486328125}, {"start": 100.14, "end": 100.24, "word": " ال", "probability": 0.9482421875}, {"start": 100.24, "end": 100.78, "word": " definitions", "probability": 0.9736328125}, {"start": 100.78, "end": 105.98, "word": " عندي", "probability": 0.812255859375}, {"start": 105.98, "end": 106.2, "word": " هنا", "probability": 0.5537109375}, {"start": 106.2, "end": 106.94, "word": " الزمن", "probability": 0.9158528645833334}, {"start": 106.94, "end": 110.04, "word": " وهنا", "probability": 0.8720703125}, {"start": 110.04, "end": 110.4, "word": " ال", "probability": 0.810546875}, {"start": 110.4, "end": 110.86, "word": " stress", "probability": 0.9345703125}], "temperature": 1.0}, {"id": 5, "seek": 13772, "start": 113.09, "end": 137.73, "text": "و ال stress بتغير طبقا لل curve هذا هذا ال value اللي هي sigma minimum و هذه sigma maximum بدي اعرف ال stress range اللي هي sigma R", "tokens": [2407, 2423, 4244, 39894, 17082, 13546, 23032, 3555, 4587, 995, 24976, 7605, 23758, 23758, 2423, 2158, 13672, 1829, 39896, 12771, 7285, 4032, 29538, 12771, 6674, 4724, 16254, 1975, 3615, 28480, 2423, 4244, 3613, 13672, 1829, 39896, 12771, 497], "avg_logprob": -0.23978365384615385, "compression_ratio": 1.390625, "no_speech_prob": 0.0, "words": [{"start": 113.09, "end": 113.29, "word": "و", "probability": 0.82421875}, {"start": 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"word": " sigma", "probability": 0.763671875}, {"start": 120.39, "end": 120.95, "word": " minimum", "probability": 0.95947265625}, {"start": 120.95, "end": 124.25, "word": " و", "probability": 0.67138671875}, {"start": 124.25, "end": 124.63, "word": " هذه", "probability": 0.488037109375}, {"start": 124.63, "end": 128.51, "word": " sigma", "probability": 0.9111328125}, {"start": 128.51, "end": 130.93, "word": " maximum", "probability": 0.96875}, {"start": 130.93, "end": 132.69, "word": " بدي", "probability": 0.5467529296875}, {"start": 132.69, "end": 132.93, "word": " اعرف", "probability": 0.8567708333333334}, {"start": 132.93, "end": 133.09, "word": " ال", "probability": 0.9560546875}, {"start": 133.09, "end": 133.41, "word": " stress", "probability": 0.9853515625}, {"start": 133.41, "end": 133.99, "word": " range", "probability": 0.92236328125}, {"start": 133.99, "end": 136.89, "word": " اللي", "probability": 0.958740234375}, {"start": 136.89, "end": 137.03, "word": " هي", "probability": 0.919921875}, {"start": 137.03, "end": 137.37, "word": " sigma", "probability": 0.9052734375}, {"start": 137.37, "end": 137.73, "word": " R", "probability": 0.611328125}], "temperature": 1.0}, {"id": 6, "seek": 16866, "start": 141.88, "end": 168.66, "text": "بسوة sigma max minus sigma minimum بتعرف لسه ال mean stress هذه sigma mean او ال mid range stress sigma mean بسوة sigma max زائد sigma minimum على اتنين ال average value", "tokens": [3555, 3794, 2407, 3660, 12771, 11469, 3175, 12771, 7285, 39894, 3615, 28480, 5296, 3794, 3224, 2423, 914, 4244, 29538, 12771, 914, 1975, 2407, 2423, 2062, 3613, 4244, 12771, 914, 4724, 3794, 2407, 3660, 12771, 11469, 30767, 16373, 3215, 12771, 7285, 15844, 1975, 2655, 1863, 9957, 2423, 4274, 2158], "avg_logprob": -0.3322704178946359, "compression_ratio": 1.5182481751824817, "no_speech_prob": 0.0, "words": [{"start": 141.88, "end": 142.4, "word": "بسوة", "probability": 0.49066162109375}, {"start": 142.4, "end": 142.7, "word": " sigma", 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Sigma M nominal هذا a few design بحيث أنك تتجنب تدخل ل plastic range عند نقطة ال stress concentration", "tokens": [6027, 39184, 591, 37, 3714, 43020, 727, 312, 6456, 5296, 39184, 36595, 316, 4032, 36595, 376, 37495, 22653, 4724, 4587, 7578, 48812, 25513, 591, 37, 8978, 36595, 40062, 13672, 1829, 39896, 41641, 4032, 591, 37, 8978, 36595, 376, 41641, 23758, 257, 1326, 1715, 4724, 5016, 1829, 12984, 14739, 4117, 6055, 2655, 7435, 1863, 3555, 6055, 3215, 9778, 1211, 5296, 5900, 3613, 43242, 8717, 47432, 3660, 2423, 4244, 9856], "avg_logprob": -0.19304801329322482, "compression_ratio": 1.3203883495145632, "no_speech_prob": 0.0, "words": [{"start": 376.63, "end": 376.99, "word": "الـ", "probability": 0.73876953125}, {"start": 376.99, "end": 377.41, "word": " KF", "probability": 0.744384765625}, {"start": 377.41, "end": 378.15, "word": " ممكن", "probability": 0.954345703125}, {"start": 378.15, "end": 378.53, "word": " could", "probability": 0.2958984375}, {"start": 378.53, "end": 378.67, 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"end": 2214.82, "word": " الفتيك", "probability": 0.8095703125}, {"start": 2214.82, "end": 2215.86, "word": " مانعته", "probability": 0.62493896484375}, {"start": 2215.86, "end": 2216.42, "word": " ال", "probability": 0.95703125}, {"start": 2216.42, "end": 2216.98, "word": " potential", "probability": 0.9541015625}, {"start": 2216.98, "end": 2217.84, "word": " for", "probability": 0.9443359375}, {"start": 2217.84, "end": 2218.34, "word": " fatigue", "probability": 0.966796875}, {"start": 2218.34, "end": 2218.82, "word": " failure", "probability": 0.89306640625}, {"start": 2218.82, "end": 2219.46, "word": " أعلى", "probability": 0.9182942708333334}, {"start": 2219.46, "end": 2220.44, "word": " من", "probability": 0.98779296875}, {"start": 2220.44, "end": 2221.36, "word": " ال", "probability": 0.8916015625}, {"start": 2221.36, "end": 2221.82, "word": " potential", "probability": 0.93994140625}, {"start": 2221.82, "end": 2222.26, "word": " for", "probability": 0.96875}, {"start": 2222.26, 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{"start": 2232.58, "end": 2232.98, "word": " الفرع", "probability": 0.9788411458333334}, {"start": 2232.98, "end": 2233.34, "word": " الأول", "probability": 0.967041015625}, {"start": 2233.34, "end": 2233.6, "word": " بس", "probability": 0.9697265625}, {"start": 2233.6, "end": 2234.16, "word": " هستخدم", "probability": 0.994384765625}, {"start": 2234.16, "end": 2234.54, "word": " نظري", "probability": 0.85107421875}, {"start": 2234.54, "end": 2234.8, "word": " تاني", "probability": 0.9607747395833334}, {"start": 2234.8, "end": 2235.32, "word": " ازمة", "probability": 0.3731282552083333}, {"start": 2235.32, "end": 2235.86, "word": " elliptic", "probability": 0.7278645833333334}, {"start": 2235.86, "end": 2236.2, "word": " fatigue", "probability": 0.927734375}, {"start": 2236.2, "end": 2236.52, "word": " line", "probability": 0.953125}, {"start": 2236.52, "end": 2236.96, "word": " نفس", "probability": 0.979248046875}, {"start": 2236.96, "end": 2237.32, "word": " الحال", "probability": 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2249.55, "end": 2249.71, "word": " هو", "probability": 0.9541015625}, {"start": 2249.71, "end": 2250.17, "word": " fatigue", "probability": 0.93603515625}, {"start": 2250.17, "end": 2251.29, "word": " criteria", "probability": 0.67431640625}, {"start": 2251.29, "end": 2251.59, "word": " for", "probability": 0.96728515625}, {"start": 2251.59, "end": 2251.99, "word": " brittle", "probability": 0.9697265625}, {"start": 2251.99, "end": 2252.65, "word": " materials", "probability": 0.82470703125}, {"start": 2252.65, "end": 2253.63, "word": " اعطيكوا", "probability": 0.7555338541666666}, {"start": 2253.63, "end": 2253.93, "word": " العفو", "probability": 0.7882486979166666}], "temperature": 1.0}], "language": "ar", "language_probability": 1.0, "duration": 2255.1916875, "duration_after_vad": 1960.4474999999925}
\ No newline at end of file
diff --git a/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/cZA5kLPfQUI_raw.srt b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/cZA5kLPfQUI_raw.srt
new file mode 100644
index 0000000000000000000000000000000000000000..0b57bcfe94c51c6fa63b4857ecddd8ceda0e7f0f
--- /dev/null
+++ b/PL9fwy3NUQKwZqK3_UxZG78URbnIyFx5tq/cZA5kLPfQUI_raw.srt
@@ -0,0 +1,1380 @@
+1
+00:00:04,940 --> 00:00:08,400
+بسم الله الرحمن الرحيم السلام عليكم اليوم هنكمل
+
+2
+00:00:08,400 --> 00:00:13,440
+المحاضرة الرابعة في ال .. او الخامسة في ال fatigue
+
+3
+00:00:13,440 --> 00:00:19,400
+.. fatigue failure for variable loading اليوم
+
+4
+00:00:19,400 --> 00:00:23,340
+هنشوف how to characterize fluctuating stress خلينا
+
+5
+00:00:23,340 --> 00:00:27,880
+نعمل بعض الملاحظات كتقديم الان ال S and diagram
+
+6
+00:00:27,880 --> 00:00:34,900
+اللي هو ناتج عن فحص الفتيك المعيارييطبق في حالة ال
+
+7
+00:00:34,900 --> 00:00:41,100
+load كان completely reversed bending stress other
+
+8
+00:00:41,100 --> 00:00:44,260
+stress situations اللي بتكون مش completely
+
+9
+00:00:44,260 --> 00:00:48,700
+reversed بنفعش
+
+10
+00:00:48,700 --> 00:00:54,000
+استخدم ال as underground معناته لازم اشوف طريقة
+
+11
+00:00:54,000 --> 00:00:57,000
+how to characterize fluctuating stresses
+
+12
+00:00:59,820 --> 00:01:02,480
+الباقي عندي مجموعة من الأمثلة، عندي مثلا هنا
+
+13
+00:01:02,480 --> 00:01:08,680
+stress بتغير من هذا الزمن، فيش fight or rebel،
+
+14
+00:01:08,680 --> 00:01:14,980
+عندي هاي حالة تانية، هاي حالة تالتة، ممكن تكون أي
+
+15
+00:01:14,980 --> 00:01:17,280
+curve، ممكن تكون إشي زي هيك
+
+16
+00:01:25,440 --> 00:01:30,180
+هذا is fluctuating لا هو sinusoid ولا هو repeated
+
+17
+00:01:30,180 --> 00:01:39,160
+ولا هو completely reversed الآن
+
+18
+00:01:39,160 --> 00:01:45,980
+خليني أعمل بعض ال definitions عندي
+
+19
+00:01:45,980 --> 00:01:50,040
+هنا الزمن وهنا
+
+20
+00:01:50,040 --> 00:01:57,510
+ال stressو ال stress بتغير طبقا لل curve هذا هذا
+
+21
+00:01:57,510 --> 00:02:04,250
+ال value اللي هي sigma minimum و
+
+22
+00:02:04,250 --> 00:02:08,510
+هذه sigma
+
+23
+00:02:08,510 --> 00:02:17,730
+maximum بدي اعرف ال stress range اللي هي sigma R
+
+24
+00:02:21,880 --> 00:02:29,080
+بسوة sigma max minus sigma minimum بتعرف
+
+25
+00:02:29,080 --> 00:02:35,040
+لسه ال mean stress هذه sigma
+
+26
+00:02:35,040 --> 00:02:42,340
+mean او ال mid range stress sigma mean بسوة sigma
+
+27
+00:02:42,340 --> 00:02:50,220
+max زائد sigma minimum على اتنين ال average valueو
+
+28
+00:02:50,220 --> 00:02:54,420
+في ال stress amplitude اللي هو ال stress level
+
+29
+00:02:54,420 --> 00:03:02,780
+above ال average sigma a ال sigma a بسواس sigma r
+
+30
+00:03:02,780 --> 00:03:08,580
+على اتنين يعني بسواس sigma max minus sigma minimum
+
+31
+00:03:08,580 --> 00:03:16,240
+على اتنين هذا ال general case
+
+32
+00:03:19,580 --> 00:03:24,740
+case في حالات خاصة اول شي completely reverse
+
+33
+00:03:24,740 --> 00:03:28,960
+stress completely reversed يعني ال sigma M في ال
+
+34
+00:03:28,960 --> 00:03:33,920
+completely reverse يكون ال sigma M بالساوية سفر
+
+35
+00:03:33,920 --> 00:03:38,020
+هذه
+
+36
+00:03:38,020 --> 00:03:47,150
+sigma alternating وهذه sigmaAlternating فى
+
+37
+00:03:47,150 --> 00:03:50,710
+repeated stress توش يعني ال stress يعني بتروح بين
+
+38
+00:03:50,710 --> 00:03:54,710
+zero و maximum maximum zero maximum zero maximum
+
+39
+00:03:54,710 --> 00:04:04,050
+بيكون هذا ال sigma مين ال sigma minimum بيستوى سفر
+
+40
+00:04:04,050 --> 00:04:16,380
+و هاد ال sigma max هاد ال sigmaمين وهد ال sigma
+
+41
+00:04:16,380 --> 00:04:23,320
+alternating في الحال هد ال sigma alternating بستوى
+
+42
+00:04:23,320 --> 00:04:38,900
+ال sigma مين بستوى ال sigma max على اتنين في
+
+43
+00:04:38,900 --> 00:04:39,960
+ال stress ratio
+
+44
+00:04:50,340 --> 00:04:55,160
+هكذا هذا هو sigma max هذا
+
+45
+00:04:55,160 --> 00:05:00,460
+sigma minimum هذا sigma alternating sigma
+
+46
+00:05:00,460 --> 00:05:05,740
+alternating هذا sigma mean هذا sigma R ال sigma
+
+47
+00:05:05,740 --> 00:05:08,000
+mean اللي هي ال average value اللي ال maximum و ال
+
+48
+00:05:08,000 --> 00:05:10,680
+minimum ال sigma alternating اللي هو ال stress
+
+49
+00:05:10,680 --> 00:05:12,380
+amplitude ال maximum و النقص و ال minimum على
+
+50
+00:05:12,380 --> 00:05:17,250
+اتنينوال stress ratio هي ال ratio بين ال minimum
+
+51
+00:05:17,250 --> 00:05:20,330
+stress وال maximum stress level وال amplitude
+
+52
+00:05:20,330 --> 00:05:23,170
+ratio هي ال ratio بين ال stress amplitude sigma a
+
+53
+00:05:23,170 --> 00:05:24,510
+على sigma m
+
+54
+00:05:44,320 --> 00:05:48,280
+and how to apply ال KF for fluctuating stresses
+
+55
+00:05:48,280 --> 00:05:49,160
+case
+
+56
+00:05:52,480 --> 00:05:55,760
+for fluctuating loads at points with stress
+
+57
+00:05:55,760 --> 00:05:59,880
+concentration, the best approach is to design to
+
+58
+00:05:59,880 --> 00:06:02,960
+avoid all localized plastic streams بدك تعمل
+
+59
+00:06:02,960 --> 00:06:07,020
+design ل ال mechanical part بحيث عند ال stress
+
+60
+00:06:07,020 --> 00:06:10,420
+concentration مادخلش ل plastic range بحيث مادخلش ل
+
+61
+00:06:10,420 --> 00:06:14,320
+plastic range في الحالة هذه إذا أنت مصمم بحيث
+
+62
+00:06:14,320 --> 00:06:19,190
+مادخلش ل plastic rangeالـ KF ممكن could be applied
+
+63
+00:06:19,190 --> 00:06:25,790
+لـ Sigma A و Sigma M يعني بقى ضرب KF في Sigma
+
+64
+00:06:25,790 --> 00:06:31,730
+alternating اللي هي nominal و KF في Sigma M
+
+65
+00:06:31,730 --> 00:06:37,330
+nominal هذا a few design بحيث أنك تتجنب تدخل ل
+
+66
+00:06:37,330 --> 00:06:41,470
+plastic range عند نقطة ال stress concentration
+
+67
+00:06:46,520 --> 00:06:51,820
+when localized strain does occur لما عندي أدخل ل
+
+68
+00:06:51,820 --> 00:06:57,040
+plastic range some methods بعض الطرق recommend
+
+69
+00:06:57,040 --> 00:07:02,760
+applying KF only to sigma alternating يعني بعض
+
+70
+00:07:02,760 --> 00:07:09,520
+الطرق بيحكيلك استخدم KF مع sigma alternating فقط
+
+71
+00:07:09,520 --> 00:07:15,080
+ما تستخدموش مع ال sigma meanفي طريقة اللي اسمها
+
+72
+00:07:15,080 --> 00:07:19,500
+Dowling method Dowling
+
+73
+00:07:19,500 --> 00:07:25,520
+method في Dowling method you apply KF to Sigma A
+
+74
+00:07:25,520 --> 00:07:32,720
+you applied KFM to Sigma M طبعا ال KFM معطب
+
+75
+00:07:32,720 --> 00:07:40,110
+المعادلة هذه KFM بيستوى KFفي حال كان دي KF في ال
+
+76
+00:07:40,110 --> 00:07:45,870
+nominal maximum stress كانت أقل من ال SY يعني إذا
+
+77
+00:07:45,870 --> 00:07:51,910
+ما دخلتش locally ل plastic range بتكون ال KF M
+
+78
+00:07:51,910 --> 00:07:59,230
+بيساوي ال KF أو ال KF M بيساوي SY minus KF في
+
+79
+00:07:59,230 --> 00:08:02,410
+sigma alternating nominal على sigma mean nominal
+
+80
+00:08:02,410 --> 00:08:10,350
+في حال ان KF في حال دخلت إيش؟لـ plastic range يعني
+
+81
+00:08:10,350 --> 00:08:13,350
+كف في ال maximum of nominal stress أكبر من ال SY
+
+82
+00:08:13,350 --> 00:08:19,710
+أو
+
+83
+00:08:19,710 --> 00:08:24,610
+الكف M بيستوى Zero لما كانت كف في القيمة المطلقة ل
+
+84
+00:08:24,610 --> 00:08:27,550
+maximum of nominal stress minus ال minimum of
+
+85
+00:08:27,550 --> 00:08:32,730
+nominal stress أكبر من 2SY طبعا ال Sigma AO و
+
+86
+00:08:32,730 --> 00:08:38,140
+Sigma MO هي nominal stressesintroduced by the laws
+
+87
+00:08:38,140 --> 00:08:43,400
+FA and FM without applying stress concentration
+
+88
+00:08:43,400 --> 00:08:47,720
+يعني أنا هذا ال stress اللي بحسبها قبل ما استخدم
+
+89
+00:08:47,720 --> 00:08:50,420
+ال stress concentration factors
+
+90
+00:08:57,720 --> 00:09:01,620
+معناته إذا أنا صممت بحيث أتجنب أدخل ل plastic
+
+91
+00:09:01,620 --> 00:09:05,620
+range عند ال .. عند ال notch هحط ال sigma
+
+92
+00:09:05,620 --> 00:09:08,700
+alternating بيساوي KF في sigma alternating nominal
+
+93
+00:09:08,700 --> 00:09:13,940
+و sigma mean بيساوي KF في sigma MO nominal إذا
+
+94
+00:09:13,940 --> 00:09:19,280
+دخلت ماقدرش أتجنب و locally دخلت ل plastic range
+
+95
+00:09:19,280 --> 00:09:21,200
+بستخدم
+
+96
+00:09:22,370 --> 00:09:27,170
+معادلة سابق بستخدم dowling equation او اذا بدى
+
+97
+00:09:27,170 --> 00:09:31,590
+اكون محافظ بحط ال sigma a بيساوي kf في sigma a
+
+98
+00:09:31,590 --> 00:09:40,730
+nominal و بحط kfm بيساوي واحد كف بيساوي واحد يعني
+
+99
+00:09:40,730 --> 00:09:44,270
+يا بستخدم هذه او بستخدم معادلة 3639 اللي هي
+
+100
+00:09:44,270 --> 00:09:50,210
+dowling equation لان
+
+101
+00:09:50,210 --> 00:09:56,590
+نيجي ل design theoriesهنبدأ في ال modified godman
+
+102
+00:09:56,590 --> 00:10:01,950
+theory لأن to set up a fatigue design theory
+
+103
+00:10:01,950 --> 00:10:07,810
+graphically بأرسم محاور المحور الأفقي بيمثلي ال
+
+104
+00:10:07,810 --> 00:10:13,510
+sigma M والمحور
+
+105
+00:10:13,510 --> 00:10:18,430
+الرأسي بيمثل ال sigma alternating
+
+106
+00:10:20,370 --> 00:10:26,730
+ع نفس ال figure بدي احط ال yield criteria و ال
+
+107
+00:10:26,730 --> 00:10:31,510
+fatigue criteria to define لي ال criteria انا عندي
+
+108
+00:10:31,510 --> 00:10:36,870
+اللي هو ال S Y و
+
+109
+00:10:36,870 --> 00:10:45,620
+ال S Y for any loading conditionكانت واقعة على
+
+110
+00:10:45,620 --> 00:10:49,380
+الخط هذا انا ببدأ يصير اندي ييلدنج الان ال fatigue
+
+111
+00:10:49,380 --> 00:10:57,320
+condition عند ال SUT في حالة المدفعات Godman وهنا
+
+112
+00:10:57,320 --> 00:10:58,280
+عند ال SA
+
+113
+00:11:07,150 --> 00:11:12,130
+إذا ال loading condition sigma m و sigma a أي نقطة
+
+114
+00:11:12,130 --> 00:11:15,750
+واقعة هتمثل ليه failure يعني هيك failure جوا safe
+
+115
+00:11:15,750 --> 00:11:23,010
+برا failure جوا safe طبعا
+
+116
+00:11:23,010 --> 00:11:27,170
+انا في عندي هتعامل
+
+117
+00:11:27,170 --> 00:11:36,750
+مع أربعة theoriesعندي هذه الـ SY الـ SUT و الـ SE
+
+118
+00:11:36,750 --> 00:11:45,430
+و الـ SY هذا الخط المتقطع بيمثل ال yield line الخط
+
+119
+00:11:45,430 --> 00:11:49,850
+هذا اللي واصل بين SE و SE بيمثل الفتيك فيلر line
+
+120
+00:11:49,850 --> 00:11:57,170
+اللي هو تسمى ال soda berg line جاي بين SY و SEالخط
+
+121
+00:11:57,170 --> 00:12:01,930
+العدل اللي جاء بين SUT و SE بمثل Modified Godman
+
+122
+00:12:01,930 --> 00:12:08,130
+Fatigue Lineالخط ال curved اللي جاء بين S Y بين S
+
+123
+00:12:08,130 --> 00:12:13,050
+Y و S E مثلي الأزم Elliptic Fatigue Failure Theory
+
+124
+00:12:13,050 --> 00:12:18,810
+ال curved line بين S U T و S E مثلي ال Gerber Line
+
+125
+00:12:18,810 --> 00:12:25,610
+Fatigue Theory و الخط هذا مثلي ال load line هذه
+
+126
+00:12:27,910 --> 00:12:35,370
+هذه ممكن تكون عندي .. عندي sigma mean وهذه sigma
+
+127
+00:12:35,370 --> 00:12:40,670
+alternating لأن لما نمد الخط هذا هيتقطع لو افترضت
+
+128
+00:12:40,670 --> 00:12:45,970
+انا ال .. ال .. ال design theory اللي هي modified
+
+129
+00:12:45,970 --> 00:12:52,090
+code بمعنى ان هذه هتكون SM وهذه
+
+130
+00:12:53,330 --> 00:12:57,450
+S A و ال factor of state في الحالة هذه اللي هو NF
+
+131
+00:12:57,450 --> 00:13:13,050
+بساوي SM على سيجما M بساوية S A على سيجما A يعني
+
+132
+00:13:13,050 --> 00:13:17,630
+اللحظ المحور هذا بمثل ال case عندها S يعني هنا
+
+133
+00:13:17,630 --> 00:13:19,890
+النقطة هذه هذه النقطة
+
+134
+00:13:24,650 --> 00:13:30,170
+و سفر يعني مافيش alternation مافيش fluctuation هنا
+
+135
+00:13:30,170 --> 00:13:40,290
+النقطة هذه بتمثل سفر و أس إيه يعني complete هذه
+
+136
+00:13:40,290 --> 00:13:45,520
+complete reversed case وهذه النقطة تمثلاللي هي ال
+
+137
+00:13:45,520 --> 00:13:48,420
+steady state case يعني مافيش عندى alternation أو
+
+138
+00:13:48,420 --> 00:13:51,700
+مافيش عندى fluctuation يعني ال load ثابت يعني هذه
+
+139
+00:13:51,700 --> 00:13:56,380
+ال static case وهذه ال static case وهذه ال
+
+140
+00:13:56,380 --> 00:14:01,520
+completely reversed case الآن if any point in
+
+141
+00:14:01,520 --> 00:14:07,180
+betweenاللي هي .. اللي هي جزء منها في عندى mean
+
+142
+00:14:07,180 --> 00:14:10,380
+stress component و في عندى ال alternating stress
+
+143
+00:14:10,380 --> 00:14:15,240
+component is defined by this line اذا استخدمت
+
+144
+00:14:15,240 --> 00:14:19,660
+modified Godman or this curve اذا استخدمت Gerber
+
+145
+00:14:19,660 --> 00:14:24,080
+criteria او this curve اذا استخدمت اللي هو asthma
+
+146
+00:14:24,080 --> 00:14:28,060
+elliptic criteria او this line اذا استخدمت
+
+147
+00:14:28,060 --> 00:14:29,100
+Soderberg criteria
+
+148
+00:14:47,300 --> 00:14:51,440
+الان ال design theories sigma alternating في حياة
+
+149
+00:14:51,440 --> 00:14:55,400
+صدربرج صدربرج جاي بين ال SE و ال SY دايما ال SE
+
+150
+00:14:55,400 --> 00:14:59,020
+بيجي معاها sigma alternating و ال SY او ال SUT
+
+151
+00:14:59,020 --> 00:15:02,140
+بيجي معاها sigma M يعني هنا sigma A جاي بين ال SE
+
+152
+00:15:02,140 --> 00:15:05,640
+و ال SY sigma A على SE زي sigma M على SE بيستوى
+
+153
+00:15:05,640 --> 00:15:08,710
+واحدة لان هو ال factor of safetyModified Godman
+
+154
+00:15:08,710 --> 00:15:12,550
+جاي بين SE و SUT سجما A على SE زي سجما M على SUT
+
+155
+00:15:12,550 --> 00:15:15,690
+بالساوية واحدة ل N الجيربار الجاي ال non linear
+
+156
+00:15:15,690 --> 00:15:21,230
+بين SE و SUT هتكون N سجما A على SE زي N سجما M على
+
+157
+00:15:21,230 --> 00:15:24,350
+SUT الكتر بيه بالساوية واحد الأزمة اللي بتكن non
+
+158
+00:15:24,350 --> 00:15:28,270
+linear جاي بين SE و SY N سجما alternating على SE
+
+159
+00:15:28,270 --> 00:15:31,170
+الكتر بيه زي N سجما M على SY الكتر بيه بالساوية
+
+160
+00:15:31,170 --> 00:15:32,050
+واحدة
+
+161
+00:15:38,100 --> 00:15:45,240
+الان هنتطلع ال table 6 6 ل 6 8 يعني عندي 6 6 6 7 6
+
+162
+00:15:45,240 --> 00:15:51,460
+8 ال table 6 6 معطيني الحسابات للمدفعات جودمان
+
+163
+00:15:51,460 --> 00:15:57,440
+المدفعات جودمان احنا حكينا جاية بين عندي جاية بين
+
+164
+00:15:57,440 --> 00:16:05,460
+هذا
+
+165
+00:16:05,460 --> 00:16:13,550
+ال yield ال yieldline هنا عندي sy هنا sut هنا sy
+
+166
+00:16:13,550 --> 00:16:25,170
+هنا sa وهذا ال load line ال load line وهذا ال
+
+167
+00:16:25,170 --> 00:16:29,310
+critical ال
+
+168
+00:16:29,310 --> 00:16:32,930
+critical load
+
+169
+00:16:32,930 --> 00:16:35,030
+line
+
+170
+00:16:47,620 --> 00:16:54,620
+هذا الخط ال filler line معرفه ليه علاقة اللي هي SA
+
+171
+00:16:54,620 --> 00:17:09,560
+على SE زائد SM على SUT بساوي واحد وال
+
+172
+00:17:09,560 --> 00:17:13,040
+yield line هذا معدلته SA
+
+173
+00:17:14,520 --> 00:17:25,380
+على SY زاد SM على SY بساوي واحد وهذا ال load line
+
+174
+00:17:25,380 --> 00:17:39,860
+هذا sigma M وهذا sigma A النقطة قاطعة دول SM
+
+175
+00:17:43,530 --> 00:17:51,350
+و S A و
+
+176
+00:17:51,350 --> 00:17:55,150
+ال slope بتاعها ده اللي هو ال line اللي هو R R
+
+177
+00:17:55,150 --> 00:18:12,210
+بالسواء S M على S A S A على S M بالسواء
+
+178
+00:18:12,210 --> 00:18:12,890
+سجما A
+
+179
+00:18:17,590 --> 00:18:22,790
+السطر الأول من الجدول يوجد نقطة التقاطع load line
+
+180
+00:18:22,790 --> 00:18:29,770
+مع fatigue line يعني النقطة هذه السطر الأول هذا
+
+181
+00:18:29,770 --> 00:18:35,650
+يوجد نقطة التقاطع load line مع fatigue line اللي
+
+182
+00:18:35,650 --> 00:18:43,950
+هي بيحسبلي ال S A بستوار R S E S U Tزاد R S U T ال
+
+183
+00:18:43,950 --> 00:18:47,610
+S A بيسوا R S E S U T على R S U T زاد S E و ال S M
+
+184
+00:18:47,610 --> 00:18:55,190
+بيسوا S E على R السطر التاني بوجود التقاطع ال load
+
+185
+00:18:55,190 --> 00:19:05,010
+line مع ال yield line هذه نقطة واحد هذه واحد اتنين
+
+186
+00:19:05,010 --> 00:19:07,990
+اللي هي النقطة هذه
+
+187
+00:19:11,180 --> 00:19:16,500
+معناته نقطة اتنين بتمثلي
+
+188
+00:19:16,500 --> 00:19:25,060
+تقاطع ال load line مع ال yield line السطر
+
+189
+00:19:25,060 --> 00:19:37,080
+التالت بوجود تقاطع ال fatigue line مع ال yield
+
+190
+00:19:37,080 --> 00:19:39,120
+line يعني هذه النقطة
+
+191
+00:19:45,160 --> 00:19:51,440
+معناه في سطر التالت بوجود تقاطع ال fatigue line مع
+
+192
+00:19:51,440 --> 00:19:57,300
+ال yield line و ال factor of safety enough هيكون
+
+193
+00:19:57,300 --> 00:20:00,940
+موضوع العلاقة هذه enough بس واحد على sigma a زاد
+
+194
+00:20:00,940 --> 00:20:05,360
+.. واحد على sigma a على s e زاد sigma m على s u t
+
+195
+00:20:05,360 --> 00:20:10,880
+طبعا
+
+196
+00:20:12,050 --> 00:20:16,530
+الجدول هذا مكرر لل other design theories يعني مكرر
+
+197
+00:20:16,530 --> 00:20:21,950
+بالنسبة لإيش لgerber fatigue theory و ال asthma
+
+198
+00:20:21,950 --> 00:20:23,470
+elliptic fatigue theory
+
+199
+00:20:52,130 --> 00:20:59,230
+طيب نشوف ال example a واحد و نص انش diameter bar
+
+200
+00:20:59,230 --> 00:21:08,070
+عند القطر يعني دي بس واحد و نص انش has been
+
+201
+00:21:08,070 --> 00:21:15,610
+machined from
+
+202
+00:21:15,610 --> 00:21:23,380
+an AISIالف و خمسين cold drawn bar ال material عشرة
+
+203
+00:21:23,380 --> 00:21:30,600
+خمسين cold drawn steel this
+
+204
+00:21:30,600 --> 00:21:35,380
+part is هذا ال part is to withstand a fluctuating
+
+205
+00:21:35,380 --> 00:21:40,300
+tensile load varying from zero to sixteen kilo
+
+206
+00:21:40,300 --> 00:21:46,280
+pound يعني هيكون عليه ال F minimum
+
+207
+00:21:48,010 --> 00:21:56,270
+بساوي zero وال F maximum بساوي ستاشر kilo pound
+
+208
+00:22:05,180 --> 00:22:08,720
+because of the ends and fillet radius a fatigue
+
+209
+00:22:08,720 --> 00:22:12,560
+stress concentration factor KF يعني هو من الأطراف
+
+210
+00:22:12,560 --> 00:22:15,140
+واضح أن في عنده stress concentration فأخد فين
+
+211
+00:22:15,140 --> 00:22:18,720
+اعتبار fatigue stress concentration factor KF
+
+212
+00:22:18,720 --> 00:22:26,920
+بيساوي واحد point تمانية خمسة for عشر أو ستة or
+
+213
+00:22:26,920 --> 00:22:34,700
+larger lifefind S A and S M and the factor of
+
+214
+00:22:34,700 --> 00:22:40,160
+safety guarding against fatigue and first cycle
+
+215
+00:22:40,160 --> 00:22:44,060
+yielding using Gerber fatigue line Gerber fatigue
+
+216
+00:22:44,060 --> 00:22:54,700
+line طيب ال Gerber fatigue line جايبين
+
+217
+00:22:57,080 --> 00:23:05,940
+عند ال S U T عند هنا S Y عند هنا S E و جاي non
+
+218
+00:23:05,940 --> 00:23:10,000
+-linear و
+
+219
+00:23:10,000 --> 00:23:15,340
+ال S Y هذا
+
+220
+00:23:15,340 --> 00:23:17,840
+ال yield هذا Gerber
+
+221
+00:23:21,920 --> 00:23:26,200
+أول شي انا ال steel عندى عشرة خمسين و انا اتوح
+
+222
+00:23:26,200 --> 00:23:47,160
+اروح على appendix A عشرين appendix
+
+223
+00:23:47,160 --> 00:23:50,860
+A عشرين و الحديد الف و خمسين
+
+224
+00:23:54,850 --> 00:24:02,050
+cauldron اللي عندنا اللي هو ال SUT بتاعته مية هذه
+
+225
+00:24:02,050 --> 00:24:08,530
+الف و خمسين ال
+
+226
+00:24:08,530 --> 00:24:15,330
+SUT بتاعته سوميت
+
+227
+00:24:15,330 --> 00:24:21,770
+كيلو pound per square inch و ال SY بالساوي
+
+228
+00:24:23,900 --> 00:24:28,780
+اربعة تمانين كيلو
+
+229
+00:24:28,780 --> 00:24:41,360
+pound per square inch هذه A عشرين طيب
+
+230
+00:25:10,450 --> 00:25:17,310
+طيب هو معطيني ان ال .. ال .. ال .. ال .. ال .. ال
+
+231
+00:25:17,310 --> 00:25:17,470
+.. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال ..
+
+232
+00:25:17,470 --> 00:25:17,530
+ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال
+
+233
+00:25:17,530 --> 00:25:17,570
+.. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال ..
+
+234
+00:25:17,570 --> 00:25:17,870
+ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال
+
+235
+00:25:17,870 --> 00:25:19,350
+.. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال ..
+
+236
+00:25:19,350 --> 00:25:19,550
+ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال
+
+237
+00:25:19,550 --> 00:25:19,550
+.. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال ..
+
+238
+00:25:19,550 --> 00:25:19,550
+ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال
+
+239
+00:25:19,550 --> 00:25:21,070
+.. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال ..
+
+240
+00:25:21,070 --> 00:25:21,070
+ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال
+
+241
+00:25:21,070 --> 00:25:26,150
+.. ال .. ال .. ال .. ال ..
+
+242
+00:25:26,150 --> 00:25:26,170
+ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال .. ال
+
+243
+00:25:26,170 --> 00:25:29,470
+.. ال ..
+
+244
+00:25:29,470 --> 00:25:34,470
+ال .. ال ..
+
+245
+00:25:34,470 --> 00:25:35,990
+ال
+
+246
+00:25:44,270 --> 00:25:51,030
+الان ال .. بار قطره الان ال stress sigma بشكل عام
+
+247
+00:25:51,030 --> 00:25:57,490
+sigma alternating بالساوية F alternating على ال A
+
+248
+00:25:57,490 --> 00:26:07,110
+بالساوية أربعة F alternating على باي D تربيع طبعا
+
+249
+00:26:07,110 --> 00:26:14,900
+هتساوي ال sigma M برضه في الحالة هذه هتساوياربع في
+
+250
+00:26:14,900 --> 00:26:27,100
+تمانية kilo pound على by في واحد و نص تربية يعني
+
+251
+00:26:27,100 --> 00:26:35,700
+هكون انه تلاتين تقسم تلاتة point واحد اربع تقسم
+
+252
+00:26:35,700 --> 00:26:40,360
+واحد و نص تقسم واحد و نص يساوي
+
+253
+00:26:42,670 --> 00:26:49,410
+بطلع أربعة point خمسة تلاتة أربعة point خمسة تلاتة
+
+254
+00:26:49,410 --> 00:26:53,490
+kilo pound per square inch هذا ال sigma main و
+
+255
+00:26:53,490 --> 00:26:54,110
+sigma alternative
+
+256
+00:27:13,000 --> 00:27:18,960
+الان احنا هاي الرصبة عندى ال S U T مية ال S U T
+
+257
+00:27:18,960 --> 00:27:28,000
+مية هده مية هد ال S U T و ال S Y أربعة و تمانين و
+
+258
+00:27:28,000 --> 00:27:31,500
+ال S E طبعا .. و اللي هين عندى هين اربعة و تمانين
+
+259
+00:27:31,500 --> 00:27:37,080
+ال S Y مطلوب احسب ايش ال S E فى الأول ده احسب ال S
+
+260
+00:27:37,080 --> 00:27:44,780
+Eالـ prime هستوى نص ال SUT هتكون نص في مية هتكون
+
+261
+00:27:44,780 --> 00:27:50,160
+خمسين كيلو pound per square inch الان هو حكى لي
+
+262
+00:27:50,160 --> 00:27:53,360
+machined معناه بتحسب ال K A بتعمل modification
+
+263
+00:27:53,360 --> 00:28:04,360
+factors K A ال
+
+264
+00:28:04,360 --> 00:28:18,940
+K Aالـ K A هو A S U T أُس B هو Machined هتكون
+
+265
+00:28:18,940 --> 00:28:26,400
+ال A اتنين point سبعة اتنين point سبعة في مية ال B
+
+266
+00:28:26,400 --> 00:28:30,120
+هتكون minus point اتنين ستة خمسة
+
+267
+00:28:38,450 --> 00:28:43,930
+مية اقصى minus يساوي
+
+268
+00:28:43,930 --> 00:28:50,670
+في اتنين bond سبعة تطلع bond سبعة تسعة تمانية bond
+
+269
+00:28:50,670 --> 00:29:02,290
+سبعة تسعة تمانية هذه ال K A ال size factor ال KB
+
+270
+00:29:07,490 --> 00:29:10,350
+في حالة axial loading انا عندي axial loading KB
+
+271
+00:29:10,350 --> 00:29:21,570
+هتكون تساوي واحد ال
+
+272
+00:29:21,570 --> 00:29:32,670
+KC for axial loading KC سابون تمانية خمسة ال KD و
+
+273
+00:29:32,670 --> 00:29:41,460
+ال KE معناته هتكون سوا KDبساوي KE بساوي واحد ومنها
+
+274
+00:29:41,460 --> 00:29:51,220
+بحسب ال SE هتكون KA اللي هي bond 7 تسعة تمانية في
+
+275
+00:29:51,220 --> 00:29:56,280
+KB واحد في KC bond تمانية خمسة في ال SE prime اللي
+
+276
+00:29:56,280 --> 00:29:58,040
+هي خمسين
+
+277
+00:30:01,240 --> 00:30:08,180
+بونت سبعة تسعة تمانية في بونت تمانية خمسة في خمسين
+
+278
+00:30:08,180 --> 00:30:13,360
+تتطلع تلاتة ثلاثين بونت تسعة اتنين تلاتة ثلاثين
+
+279
+00:30:13,360 --> 00:30:19,300
+بونت تسعة اتنين كيلو pound per square inch هذا ال
+
+280
+00:30:19,300 --> 00:30:19,720
+S
+
+281
+00:30:53,520 --> 00:30:58,140
+الان سيجمه مين هذه nominal وهذه عشان nominal يعني
+
+282
+00:30:58,140 --> 00:31:04,760
+سيجمه مين سوى سيجمه A حسب سوى KFفي ال sigma ايه
+
+283
+00:31:04,760 --> 00:31:08,760
+كيف معطني واحد point تمانية خمسة في أربع point
+
+284
+00:31:08,760 --> 00:31:13,780
+خمسة تلاتة عندي
+
+285
+00:31:13,780 --> 00:31:18,380
+واحد point تمانية خمسة في أربع point خمسة تلاتة
+
+286
+00:31:18,380 --> 00:31:23,560
+بطلع تمانية point تلاتة تمانية تمانية point تلاتة
+
+287
+00:31:23,560 --> 00:31:28,000
+تمانية kilo
+
+288
+00:31:28,000 --> 00:31:33,510
+pound per square inch معناه يقول عندي هناتمانية
+
+289
+00:31:33,510 --> 00:31:39,830
+point تلاتة تمانية اللي هي هذه ال sigma mean وعندي
+
+290
+00:31:39,830 --> 00:31:43,270
+هي تمانية point تلاتة تمانية اللي هي sigma
+
+291
+00:31:43,270 --> 00:31:52,550
+alternating معناته هذا هو ال load line تبعي هذا ال
+
+292
+00:31:52,550 --> 00:31:58,430
+load line تبعي لأن
+
+293
+00:31:58,430 --> 00:32:00,970
+عشان اوجد ال fatigue factor of safety
+
+294
+00:32:10,730 --> 00:32:17,850
+هذه ستكون SM وهذه SA
+
+295
+00:32:17,850 --> 00:32:26,790
+SM و SA واضح سلوب الخط هذا ال R بيساوي احد لأن
+
+296
+00:32:26,790 --> 00:32:29,330
+sigma M بيساوي sigma ال alternating معنى السلوب
+
+297
+00:32:29,330 --> 00:32:35,150
+ايش بيساوي واحد احنا بدنا جيربار criteria
+
+298
+00:32:40,330 --> 00:32:47,430
+معنى طبيعي احنا هنا هتكون عندى S A S A S
+
+299
+00:32:47,430 --> 00:32:59,590
+A هتكون تساوي تابع ست سابع هتكون R Square S U T
+
+300
+00:32:59,590 --> 00:33:11,310
+Square على اتنين S E في minus واحدزاد جزر التربيع
+
+301
+00:33:11,310 --> 00:33:26,990
+لواحد زاد اتنين SE على RSUT لكل
+
+302
+00:33:26,990 --> 00:33:33,590
+تربيع يعني انا هاكون عندى واحد في ال SUT اللي هي
+
+303
+00:33:33,590 --> 00:33:37,170
+مية في
+
+304
+00:33:37,170 --> 00:33:50,090
+ميةتربيع على اتنين في SE تربيع
+
+305
+00:33:50,090 --> 00:33:53,250
+على اتنين في SE تربيع على اتنين في SE تربيع على
+
+306
+00:33:53,250 --> 00:33:54,490
+اتنين في SE تربيع على اتنين في SE تربيع على اتنين
+
+307
+00:33:54,490 --> 00:33:54,490
+في SE تربيع على اتنين في SE تربيع على اتنين في SE
+
+308
+00:33:54,490 --> 00:33:54,530
+تربيع على اتنين في SE تربيع على اتنين في SE تربيع
+
+309
+00:33:54,530 --> 00:33:55,830
+على اتنين في SE تربيع على اتنين في SE تربيع على
+
+310
+00:33:55,830 --> 00:33:56,470
+اتنين في SE تربيع على اتنين في SE تربيع على اتنين
+
+311
+00:33:56,470 --> 00:33:56,890
+في SE تربيع على اتنين في SE تربيع على اتنين في SE
+
+312
+00:33:56,890 --> 00:34:00,370
+تربيع على اتنين في SE تربيع على اتنين في SE تربيع
+
+313
+00:34:00,370 --> 00:34:05,430
+على اتنين في SE تربيع
+
+314
+00:34:09,030 --> 00:34:17,730
+هتطلع ال S A هندى ال S A هتطلع تلاتين بون سبعة
+
+315
+00:34:17,730 --> 00:34:22,450
+كيلو
+
+316
+00:34:22,450 --> 00:34:26,530
+pound per square inch معناه ان ال fatigue factor
+
+317
+00:34:26,530 --> 00:34:34,970
+of safety ال un fatigue هيكون ساوى S A على سيجما A
+
+318
+00:34:35,880 --> 00:34:41,640
+الاس ايه اللي هي عند ال تلاتين point سبعة على سجن
+
+319
+00:34:41,640 --> 00:34:52,440
+ايه اللي هي تمانية point تلاتة تمانية تلاتين
+
+320
+00:34:52,440 --> 00:34:58,160
+point سبعة تقصير تمانية point تلات تمانية يساوي
+
+321
+00:35:00,510 --> 00:35:19,690
+تطلع تلاتة point ستة ستة تلاتة point ستة ستة عشان
+
+322
+00:35:19,690 --> 00:35:25,230
+احسب الny لازم هذا نقطة واحد لازم اوجد احتثيات
+
+323
+00:35:25,230 --> 00:35:32,990
+النقطة اتنين خدني ضحك هاداسمه SM تاعة ال yield
+
+324
+00:35:32,990 --> 00:35:41,590
+وهذه SM SA تاعة ال yield وهذا ال load line ماله
+
+325
+00:35:41,590 --> 00:35:45,890
+خمس واربعين درجة ومعناته ال R بالساوية واحد نرجع
+
+326
+00:35:45,890 --> 00:35:56,630
+للجدول Gerber اللي هو ال SA هتكون تساوية ال SA
+
+327
+00:35:58,900 --> 00:36:06,900
+هتكون R في S Y على واحد زائد R يعني هتكون واحد في
+
+328
+00:36:06,900 --> 00:36:10,980
+أربعة و تمانين على واحد زائد واحد يعني اربعة و
+
+329
+00:36:10,980 --> 00:36:14,740
+تمانين على اتنين اتنين و اربعين kilo pound per
+
+330
+00:36:14,740 --> 00:36:19,680
+square inch معنى
+
+331
+00:36:19,680 --> 00:36:20,180
+ال NY
+
+332
+00:36:23,220 --> 00:36:28,520
+هيكون ساوى اللي هو S A على Sigma A اللي هي اتنين و
+
+333
+00:36:28,520 --> 00:36:37,260
+اربعين على تمانية point تلاتة تمانية اتنين
+
+334
+00:36:37,260 --> 00:36:44,040
+و اربعين تقسيم تمانية point تلات تمانية بيطلع خمسة
+
+335
+00:36:44,040 --> 00:36:45,860
+point او واحد خمسة
+
+336
+00:36:49,880 --> 00:36:52,760
+واضح ال factor of safety في حالة ال yielding أعلى
+
+337
+00:36:52,760 --> 00:36:56,420
+من ال factor of safety في حالة الفتيك مانعته ال
+
+338
+00:36:56,420 --> 00:37:01,820
+potential for fatigue failure أعلى من ال potential
+
+339
+00:37:01,820 --> 00:37:04,720
+for yielding يعني هيصيرله fatigue failure before
+
+340
+00:37:04,720 --> 00:37:11,600
+it yields طبعا
+
+341
+00:37:11,600 --> 00:37:14,800
+الفرع التاني نفس الفرع الأول بس هستخدم نظري تاني
+
+342
+00:37:14,800 --> 00:37:17,800
+ازمة elliptic fatigue line نفس الحال تماما
+
+343
+00:37:20,730 --> 00:37:26,730
+محاضرة الجاية بن .. بنكمل بتكون ان شاء الله اخر
+
+344
+00:37:26,730 --> 00:37:31,590
+محاضرة في chapter 6 اللي هو fatigue criteria for
+
+345
+00:37:31,590 --> 00:37:33,930
+brittle materials اعطيكوا العفو
+