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Naive Bayes, Clearly Explained!!!

2020-06-03

When most people want to learn about Naive Bayes, they want to learn about the Multinomial Naive Bayes Classifier - which sounds really fancy, but is actually quite simple. This video walks you through it one step at a time and by the end, you'll no longer be naive about Naive Bayes!!! Get the StatQuest Study Guide here: https://statquest.org/statquest-store/ For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:08 Histograms and conditional probabilities 4:22 Classifying "Dear Friend" 7:33 Review of concepts 9:00 Classifying "Lunch Money x 5" 10:54 Pseudocounts 12:35 Why Naive Bayes is Naive #statquest #naivebayes

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Gaussian Naive Bayes, Clearly Explained!!!

2020-06-03

Gaussian Naive Bayes takes are of all your Naive Bayes needs when your training data are continuous. If that sounds fancy, don't sweat it! This StatQuest will clear up all your doubts in a jiffy! NOTE: This StatQuest assumes that you are already familiar with... Multinomial Naive Bayes: https://youtu.be/O2L2Uv9pdDA The Log Function: https://youtu.be/VSi0Z04fWj0 The Normal Distribution: https://youtu.be/rzFX5NWojp0 The difference between Probability and Likelihood: https://youtu.be/pYxNSUDSFH4 Cross Validation: https://youtu.be/fSytzGwwBVw For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:00 Creating Gaussian distributions from Training Data 2:34 Classification example 4:46 Underflow and Log() function 7:27 Some variables have more say than others Corrections: 3:42 I said 10 grams of popcorn, but I should have said 20 grams of popcorn given that they love Troll 2. #statquest #naivebayes

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Decision and Classification Trees, Clearly Explained!!!

2021-04-26

Decision trees are part of the foundation for Machine Learning. Although they are quite simple, they are very flexible and pop up in a very wide variety of situations. This StatQuest covers all the basics and shows you how to create a new tree from scratch, one step at a time. NOTE: This is an updated and revised version of the Decision Tree StatQuest that I made back in 2018. It is my hope that this new version does a better job answering some of the most frequently asked questions people asked about the old one. Note, you may also want to learn about... Regression Trees: https://youtu.be/g9c66TUylZ4 Bias and Variance (and over fitting): https://youtu.be/EuBBz3bI-aA Cross Validation: https://youtu.be/fSytzGwwBVw Pruning Trees: https://youtu.be/D0efHEJsfHo For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 0:18 Basic decision tree concepts 3:16 Building a tree with Gini Impurity 9:15 Numeric and continuous variables 12:35 Adding branches 13:56 Adding leaves 14:32 Defining output values 15:12 Using the tree 15:38 How to prevent overfitting #StatQuest #decisiontree #ML

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StatQuest: Decision Trees, Part 2 - Feature Selection and Missing Data

2018-01-29

This is just a short follow up to last week's StatQuest where we introduced decision trees. Here we show how decision trees deal with variables that don't improve the tree (feature selection) and how they deal with missing data. To learn the basics about Decision Trees, see: https://youtu.be/_L39rN6gz7Y For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buy The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer Correction: 1:35 I mistyped the gini impurity. I wrote 0.29, but it should be 0.19. #statquest #ML #decisiontree

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Regression Trees, Clearly Explained!!!

2019-08-20

Regression Trees are one of the fundamental machine learning techniques that more complicated methods, like Gradient Boost, are based on. They are useful for times when there isn't an obviously linear relationship between what you want to predict, and the things you are using to make the predictions. This StatQuest walks you through the steps required to build Regression Trees so that they are Clearly Explained. NOTE: This StatQuest assumes you already know about... The bias/variance tradeoff: https://youtu.be/EuBBz3bI-aA Decision Trees: https://youtu.be/7VeUPuFGJHk Linear Regression: https://www.youtube.com/watch?v=nk2CQITm_eo ALSO NOTE: This StatQuest is based on the definition of Regression Trees found on page 328 to 331 of the Introduction to Statistical Learning. https://www.statlearning.com/ For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 0:41 Motivation for Regression Trees 2:19 Regression Trees vs Classification Trees 7:11 Building a Regression Tree with one variable 18:59 Building a Regression Tree with multiple variables 20:54 Summary of concepts and main ideas #statquest #regression #tree

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How to Prune Regression Trees, Clearly Explained!!!

2019-11-25

Pruning Regression Trees is one the most important ways we can prevent them from overfitting the Training Data. This video walks you through Cost Complexity Pruning, aka Weakest Link Pruning, step-by-step so that you can learn how it works and see it in action. NOTE: This StatQuest assumes you already know about... Regression Trees: https://youtu.be/g9c66TUylZ4 ALSO NOTE: This StatQuest is based on the Cost Complexity Pruning algorithm found on pages 307 to 309 of the Introduction to Statistical Learning in R: http://faculty.marshall.usc.edu/gareth-james/ISL/ For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 0:59 Motivation for pruning a tree 3:58 Calculating the sum of squared residuals for pruned trees 7:50 Comparing pruned trees with alpha. 11:17 Step 1: Use all of the data to build trees with different alphas 13:05 Step 2: Use cross validation to compare alphas 15:02 Step 3: Select the alpha that, on average, gives the best results 15:27 Step 4: Select the original tree that corresponds to that alpha #statquest #regression #tree

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One-Hot, Label, Target and K-Fold Target Encoding, Clearly Explained!!!

2023-02-13

In theory, discrete variables, or features, are easy to use with machine learning algorithms. However, in practice, it's not always so easy and we often have to transform discrete values, like favorite colors, into numbers. There are lots of ways to do this, and this video walks you through 3 of the most popular methods. English This video has been dubbed using an artificial voice via https://aloud.area120.google.com to increase accessibility. You can change the audio track language in the Settings menu. Spanish Este video ha sido doblado al español con voz artificial con https://aloud.area120.google.com para aumentar la accesibilidad. Puede cambiar el idioma de la pista de audio en el menú Configuración. Portuguese Este vídeo foi dublado para o português usando uma voz artificial via https://aloud.area120.google.com para melhorar sua acessibilidade. Você pode alterar o idioma do áudio no menu Configurações. If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:24 One-Hot Encoding 3:25 Label Encoding 4:39 Target Encoding 6:27 Target Encoding with a Weighted Mean, or Bayesian Target Encoding 9:56 K-Fold Target Encoding #StatQuest #DubbedWithAloud

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Classification Trees in Python from Start to Finish

2020-06-07

NOTE: You can support StatQuest by purchasing the Jupyter Notebook and Python code seen in this video here: https://statquest.gumroad.com/l/tzxoh This webinar was recorded 20200528 at 11:00am (New York time). NOTE: This StatQuest assumes are already familiar with: Decision Trees: https://youtu.be/7VeUPuFGJHk Cross Validation: https://youtu.be/fSytzGwwBVw Confusion Matrices: https://youtu.be/Kdsp6soqA7o Cost Complexity Pruning: https://youtu.be/D0efHEJsfHo Bias and Variance and Overfitting: https://youtu.be/EuBBz3bI-aA For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 5:23 Import Modules 7:40 Import Data 11:18 Missing Data Part 1: Identifying 15:57 Missing Data Part 2: Dealing with it 21:16 Format Data Part 1: X and y 23:33 Format Data Part 2: One-Hot Encoding 37:29 Build Preliminary Tree 46:31 Pruning Part 1: Visualize Alpha 51:22 Pruning Part 2: Cross Validation 56:46 Build and Draw Final Tree #StatQuest #ML #ClassificationTrees

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StatQuest: Random Forests Part 1 - Building, Using and Evaluating

2018-02-05

Random Forests make a simple, yet effective, machine learning method. They are made out of decision trees, but don't have the same problems with accuracy. In this video, I walk you through the steps to build, use and evaluate a random forest. NOTE: Random Forests are made from Decision Trees, so if you don't know about those, here's the Quest: https://youtu.be/_L39rN6gz7Y ALSO NOTE: This StatQuest is based on Leo Breiman's (one of the creators of Random Forests) website: https://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buy The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 0:31 Motivation for using Random Forests 1:17 Step 1, create a bootstrapped dataset 2:23 Step 2, create a decision tree a random subset of variables at each step 4:00 Step 3, repeat steps 1 and 2 a bunch of times 4:40 Classifying a new sample with a Random Forest 5:41 Definition of Bagging 6:03 Evaluating a Random Forest 8:34 Optimizing the Random Forest Corrections: 3:18 I should have said the same feature (or variable) can be selected multiple times in a tree. Every time we select a subset of features to choose from, we choose from the full list of features, even if we have already used some of those features. Thus, a single feature can appear multiple times in a tree. 9:28 I say "square" when I meant to say "square root". #statquest #randomforest #ML

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StatQuest: Random Forests Part 2: Missing data and clustering

2020-01-15

NOTE: This StatQuest is the updated version of the original Random Forests Part 2 and includes two minor corrections. Last time we talked about how to create, use and evaluate random forests. Now it's time to see how they can deal with missing data and how they can be used to cluster samples, even when the data comes from all kinds of crazy sources. NOTE: This StatQuest is based on Leo Breiman's (one of the creators of Random Forests) website: https://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer #statquest #randomforest

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StatQuest: Random Forests in R

2018-02-26

Random Forests are an easy to understand and easy to use machine learning technique that is surprisingly powerful. Here I show you, step by step, how to use them in R. NOTE: There is an error at 13:26. I meant to call "as.dist()" instead of "dist()". The code that I used in this video can be found on the StatQuest GitHub: https://github.com/StatQuest/random_forest_demo/blob/master/random_forest_demo.R If you're new to Random Forests, here's a video that covers the basics... https://youtu.be/J4Wdy0Wc_xQ ... and here's a video that covers missing data and sample clustering... https://youtu.be/nyxTdL_4Q-Q For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Support StatQuest by buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer #statquest #randomforest #ML

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The Chain Rule

2020-07-13

The Chain Rule is a method for finding complex derivatives and is used all the time in Statistics and Machine Learning. This video breaks it down into its two simple pieces and shows you how they easily come together. We then use the Chain Rule to solve a common Machine Learning problem - optimizing the Residual Squared Loss Function. English This video has been dubbed using an artificial voice via https://aloud.area120.google.com to increase accessibility. You can change the audio track language in the Settings menu. Spanish Este video ha sido doblado al español con voz artificial con https://aloud.area120.google.com para aumentar la accesibilidad. Puede cambiar el idioma de la pista de audio en el menú Configuración. Portuguese Este vídeo foi dublado para o português usando uma voz artificial via https://aloud.area120.google.com para melhorar sua acessibilidade. Você pode alterar o idioma do áudio no menu Configurações. For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 2:02 A super simple example 6:32 A slightly more complicated example 9:16 The Chain Rule when the relationship is not obvious 11:47 The Chain Rule for the Residual Sum of Squares Corrections: 13:05 When the residual is negative, the pink circle should be on the left side of the y-axis. And when the residual is positive, the pink circle should be on the right side. #StatQuest #TheChainRule #DubbedWithAloud

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Gradient Descent, Step-by-Step

2019-02-05

Gradient Descent is the workhorse behind most of Machine Learning. When you fit a machine learning method to a training dataset, you're probably using Gradient Descent. It can optimize parameters in a wide variety of settings. Since it's so fundamental to Machine Learning, I decided to make a "step-by-step" video that shows you exactly how it works. NOTE: This video assumes you are already familiar with Least Squares and Linear Regression. If not, here's the link to the Quest: https://youtu.be/PaFPbb66DxQ For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ Sources: There are a ton of websites that describe the math behind Gradient Descent. One of my favorite is the wikipedia article: https://en.wikipedia.org/wiki/Gradient_descent If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:25 Main ideas behind Gradient Descent 5:38 Gradient Descent optimization of a single variable, part 1 9:08 An important note about why we use Gradient Descent 9:40 Gradient Descent optimization of a single variable, part 2 14:48 Review of concepts covered so far 15:48 Gradient Descent optimization of two (or more) variables 21:55 A note about Loss Functions 22:13 Gradient Descent algorithm 23:06 Stochastic Gradient Descent #statquest #gradient #descent #ML

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Stochastic Gradient Descent, Clearly Explained!!!

2019-05-13

Even though Stochastic Gradient Descent sounds fancy, it is just a simple addition to "regular" Gradient Descent. This video sets up the problem that Stochastic Gradient Descent solves and then shows how it does it. Along the way, we discuss situations where Stochastic Gradient Descent is most useful, and some cool features that aren't that obvious. NOTE: There is a small typo at 9:03. The values for the intercept and slope should be the most recent estimates, 0.86 and 0.68, instead of the original random values, 0 and 1. NOTE: This StatQuest assumes you already understand "regular" Gradient Descent. If not, check out the 'Quest: https://youtu.be/sDv4f4s2SB8 When I was researching Stochastic Gradient Descent, I found a ton of cool websites that provided lots of details. Here are some of my favorites: Sebastian Ruder has a nice write-up: http://ruder.io/optimizing-gradient-descent/ ...as the Usupervised Feature Learning and Deep Learning Tutorial: http://deeplearning.stanford.edu/tutorial/supervised/OptimizationStochasticGradientDescent/ For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer Corrections: 9:03. The values for the intercept and slope should be the most recent estimates, 0.86 and 0.68, instead of the original random values, 0 and 1. 9:33 the slope should be 0.7. #statquest #sgd

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AdaBoost, Clearly Explained

2019-01-14

AdaBoost is one of those machine learning methods that seems so much more confusing than it really is. It's really just a simple twist on decision trees and random forests. NOTE: This video assumes you already know about Decision Trees... https://youtu.be/_L39rN6gz7Y ...and Random Forests.... https://youtu.be/J4Wdy0Wc_xQ For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ Sources: The original AdaBoost paper by Robert E. Schapire and Yoav Freund https://www.sciencedirect.com/science/article/pii/S002200009791504X And a follow up by co-created Schapire: http://rob.schapire.net/papers/explaining-adaboost.pdf The idea of using the weights to resample the original dataset comes from Boosting Foundations and Algorithms, by Robert E. Schapire and Yoav Freund https://mitpress.mit.edu/books/boosting Lastly, Chris McCormick's tutorial was super helpful: http://mccormickml.com/2013/12/13/adaboost-tutorial/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 0:56 The three main ideas behind AdaBoost 3:30 Review of the three main ideas 3:58 Building a stump with the GINI index 6:27 Determining the Amount of Say for a stump 10:45 Updating sample weights 14:47 Normalizing the sample weights 15:32 Using the normalized weights to make the second stump 19:06 Using stumps to make classifications 19:51 Review of the three main ideas behind AdaBoost Correction: 10:18. The Amount of Say for Chest Pain = (1/2)*log((1-(3/8))/(3/8)) = 1/2*log(5/8/3/8) = 1/2*log(5/3) = 0.25, not 0.42. #statquest #adaboost

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Gradient Boost Part 1 (of 4): Regression Main Ideas

2019-03-25

Gradient Boost is one of the most popular Machine Learning algorithms in use. And get this, it's not that complicated! This video is the first part in a series that walks through it one step at a time. This video focuses on the main ideas behind using Gradient Boost to predict a continuous value, like someone's weight. We call this, "using Gradient Boost for Regression". In the next video, we'll work through the math to prove that Gradient Boost for Regression really is this simple. In part 3, we'll walk though how Gradient Boost classifies samples into two different categories, and in part 4, we'll go through the math again, this time focusing on classification. This StatQuest assumes that you already understand.... Decision Trees: https://youtu.be/_L39rN6gz7Y Regression Trees: https://youtu.be/g9c66TUylZ4 AdaBoost: https://youtu.be/LsK-xG1cLYA ...and the tradeoff between Bias and Variance that plagues Machine Learning: https://youtu.be/EuBBz3bI-aA For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ This StatQuest is based on the following sources: A 1999 manuscript by Jerome Friedman that introduced Stochastic Gradient Boost: https://statweb.stanford.edu/~jhf/ftp/stobst.pdf The Wikipedia article on Gradient Boosting: https://en.wikipedia.org/wiki/Gradient_boosting The scikit-learn implementation of Gradient Boosting: https://scikit-learn.org/stable/modules/ensemble.html#gradient-boosting If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 2:58 Gradient Boost compared to AdaBoost 5:50 Building the first tree to predict weight 10:37 Building the second tree to predict weight 13:28 Building additional trees to predict weight 13:50 Prediction with Gradient Boost 14:28 Summary of concepts and main ideas #statquest #gradientboost

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Gradient Boost Part 2 (of 4): Regression Details

2019-04-01

Gradient Boost is one of the most popular Machine Learning algorithms in use. And get this, it's not that complicated! This video is the second part in a series that walks through it one step at a time. This video focuses on the original Gradient Boost algorithm used to predict a continuous value, like someone's weight. We call this, "using Gradient Boost for Regression". In part 3, we'll walk though how Gradient Boost classifies samples into two different categories, and in part 4, we'll go through the math again, this time focusing on classification. This StatQuest assumes that you have already watched Part 1: https://youtu.be/3CC4N4z3GJc ...it also assumes that you know about Regression Trees: https://youtu.be/g9c66TUylZ4 ...and, while it required, it might be useful if you understood Gradient Descent: https://youtu.be/sDv4f4s2SB8 For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ This StatQuest is based on the following sources: A 1999 manuscript by Jerome Friedman that introduced Stochastic Gradient Boost: https://jerryfriedman.su.domains/ftp/stobst.pdf The Wikipedia article on Gradient Boosting: https://en.wikipedia.org/wiki/Gradient_boosting NOTE: The key to understanding how the wikipedia article relates to this video is to keep reading past the "pseudo algorithm" section. The very next section in the article called "Gradient Tree Boosting" shows how the algorithm works for trees (which is pretty much the only weak learner people ever use for gradient boost, which is why I focus on it in the video). In that section, you see how the equation is modified so that each leaf from a tree can have a different output value, rather than the entire "weak learner" having a single output value - and this is the exact same equation that I use in the video. Later in the article, in the section called "Shrinkage", they show how the learning rate can be included. Since this is also pretty much always used with gradient boost, I simply included it in the base algorithm that I describe. The scikit-learn implementation of Gradient Boosting: https://scikit-learn.org/stable/modules/ensemble.html#gradient-boosting If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 0:00 Step 0: The data and the loss function 6:30 Step 1: Initialize the model with a constant value 9:10 Step 2: Build M trees 10:01 Step 2.A: Calculate residuals 12:47 Step 2.B: Fit a regression tree to the residuals 14:50 Step 2.C: Optimize leaf output values 20:38 Step 2.D: Update predictions with the new tree 23:19 Step 2: Summary of step 2 24:59 Step 3: Output the final prediction Corrections: 4:27 The sum on the left hand side should be in parentheses to make it clear that the entire sum is multiplied by 1/2, not just the first term. 15:47. It should be R_jm, not R_ij. 16:18, the leaf in the script is R_1,2 and it should be R_2,1. 21:08. With regression trees, the sample will only go to a single leaf, and this summation simply isolates the one output value of interest from all of the others. However, when I first made this video I was thinking that because Gradient Boost is supposed to work with any "weak learner", not just small regression trees, that this summation was a way to add flexibility to the algorithm. 24:15, the header for the residual column should be r_i,2. #statquest #gradientboost

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Gradient Boost Part 3 (of 4): Classification

2019-04-08

This is Part 3 in our series on Gradient Boost. At long last, we are showing how it can be used for classification. This video gives focuses on the main ideas behind this technique. The next video in this series will focus more on the math and how it works with the underlying algorithm. This StatQuest assumes that you have already watched Part 1: https://youtu.be/3CC4N4z3GJc ...and it also assumed that you understand Logistic Regression pretty well. Here are the links for... A general overview of Logistic Regression: https://youtu.be/yIYKR4sgzI8 how to interpret the coefficients: https://youtu.be/vN5cNN2-HWE and how to estimate the coefficients: https://youtu.be/BfKanl1aSG0 Lastly, if you want to learn more about using different probability thresholds for classification, check out the StatQuest on ROC and AUC: https://youtu.be/xugjARegisk For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ This StatQuest is based on the following sources: A 1999 manuscript by Jerome Friedman that introduced Stochastic Gradient Boost: https://statweb.stanford.edu/~jhf/ftp/stobst.pdf The Wikipedia article on Gradient Boosting: https://en.wikipedia.org/wiki/Gradient_boosting The scikit-learn implementation of Gradient Boosting: https://scikit-learn.org/stable/modules/ensemble.html#gradient-boosting If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer #statquest #gradientboost

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Gradient Boost Part 4 (of 4): Classification Details

2019-04-22

At last, part 4 in our series of videos on Gradient Boost. This time we dive deep into the details of how it is used for classification, going through algorithm, and the math behind it, one step at a time. Specifically, we derive the loss function from the log(likelihood) of the data and we derive the functions used to calculate the output values from the leaves in each tree. This one is long, but well worth if you want to know how Gradient Boost works. NOTE: There is a minor error at 7:01. It should just say log(p) - log(1-p) = log(p/(1-p)). And at 19:10 I forgot to put "L" in front of some of the loss functions. However, it should be clear what they are since I point to them say, "This is the loss function". This StatQuest assumes that you have already watched Parts 1, 2 and 3 in this series: Part 1, Regression Main Ideas: https://youtu.be/3CC4N4z3GJc Part 2, Regression Details: https://youtu.be/2xudPOBz-vs Part 3, Classification Main Ideas: https://youtu.be/jxuNLH5dXCs ...and it also assumed that you understand odds, the log(odds) and Logistic Regression pretty well. Here are the links for... The odds: https://youtu.be/ARfXDSkQf1Y A general overview of Logistic Regression: https://youtu.be/yIYKR4sgzI8 how to interpret the coefficients: https://youtu.be/vN5cNN2-HWE and how to estimate the coefficients: https://youtu.be/BfKanl1aSG0 Lastly, if you want to learn more about using different probability thresholds for classification, check out the StatQuest on ROC and AUC: https://youtu.be/xugjARegisk For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ This StatQuest is based on the following sources: A 1999 manuscript by Jerome Friedman that introduced Stochastic Gradient Boost: https://statweb.stanford.edu/~jhf/ftp/stobst.pdf The Wikipedia article on Gradient Boosting: https://en.wikipedia.org/wiki/Gradient_boosting The scikit-learn implementation of Gradient Boosting: https://scikit-learn.org/stable/modules/ensemble.html#gradient-boosting If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer Corrections: 6:58 log(p) - log(1-p) is not equal to log(p)/log(1-p) but equal to log(p/(1-p)). In other words, the result at 7:07, log(p) - log(1-p) = log(odds), is correct, and thus, the error does not propagate beyond it's short, but embarrassing moment. 26:53, my indexing of the variables gets off. This is unfortunate, but you should still be able to follow the concepts. #statquest #gradientboost

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Troll 2, Clearly Explained!!!

2022-04-01

This year's April Fools' (April 1st) StatQuest demystifies one of the most poorly understood datasets in StatQuest videos: The movie Troll 2. Tin this StatQuest, we break down the movie it easy to understand pieces and then walk you through it, one step at a time. BAM! NOTE: This StatQuest assumes you are familiar with... BAM: https://youtu.be/i4iUvjsGCMc For a complete index of all the StatQuest videos, check out... https://app.learney.me/maps/StatQuest ...or... https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://kdp.amazon.com/amazon-dp-action/us/dualbookshelf.marketplacelink/B09ZCKR4H6 Kindle eBook - https://kdp.amazon.com/amazon-dp-action/us/dualbookshelf.marketplacelink/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:12 Random facts about Troll 2 2:55 The Troll 2 story #StatQuest #Troll2 #April1

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XGBoost Part 1 (of 4): Regression

2019-12-16

XGBoost is an extreme machine learning algorithm, and that means it's got lots of parts. In this video, we focus on the unique regression trees that XGBoost uses when applied to Regression problems. NOTE: This StatQuest assumes that you are already familiar with... The main ideas behind Gradient Boost for Regression: https://youtu.be/3CC4N4z3GJc ...and the main ideas behind Regularization: https://youtu.be/Q81RR3yKn30 Also note, this StatQuest is based on the following sources: The original XGBoost manuscript: https://arxiv.org/pdf/1603.02754.pdf And the XGBoost Documentation: https://xgboost.readthedocs.io/en/latest/index.html For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 2:35 The initial prediction 3:11 Building an XGBoost Tree for regression 4:07 Calculating Similarity Scores 8:23 Calculating Gain to evaluate different thresholds 13:02 Pruning an XGBoost Tree 15:15 Building an XGBoost Tree with regularization 19:29 Calculating output values for an XGBoost Tree 21:39 Making predictions with XGBoost 23:54 Summary of concepts and main ideas Corrections: 16:50 I say "66", but I meant to say "62.48". However, either way, the conclusion is the same. 22:03 In the original XGBoost documents they use the epsilon symbol to refer to the learning rate, but in the actual implementation, this is controlled via the "eta" parameter. So, I guess to be consistent with the original documentation, I made the same mistake! :) #statquest #xgboost

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XGBoost Part 2 (of 4): Classification

2020-01-13

In this video we pick up where we left off in part 1 and cover how XGBoost trees are built for Classification. NOTE: This StatQuest assumes that you are already familiar with... XGBoost Part 1: XGBoost Trees for Regression: https://youtu.be/OtD8wVaFm6E ...the main ideas behind Gradient Boost for Classification: https://youtu.be/jxuNLH5dXCs ...Odds and Log(odds): https://youtu.be/ARfXDSkQf1Y ...and how the Logistic Function works: https://youtu.be/BfKanl1aSG0 Also note, this StatQuest is based on the following sources: The original XGBoost manuscript: https://arxiv.org/pdf/1603.02754.pdf The original XGBoost presentation: https://homes.cs.washington.edu/~tqchen/pdf/BoostedTree.pdf And the XGBoost Documentation: https://xgboost.readthedocs.io/en/latest/index.html For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer Corrections: 14:24 I meant to say "larger" instead of "lower. 18:48 In the original XGBoost documents they use the epsilon symbol to refer to the learning rate, but in the actual implementation, this is controlled via the "eta" parameter. So, I guess to be consistent with the original documentation, I made the same mistake! :) #statquest #xgboost

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XGBoost Part 3 (of 4): Mathematical Details

2020-02-10

In this video we dive into the nitty-gritty details of the math behind XGBoost trees. We derive the equations for the Output Values from the leaves as well as the Similarity Score. Then we show how these general equations are customized for Regression or Classification by their respective Loss Functions. If you make it to the end, you will be approximately 22% smarter than you are now! :) NOTE: This StatQuest assumes that you are already familiar with... XGBoost Part 1: XGBoost Trees for Regression: https://youtu.be/OtD8wVaFm6E XGBoost Part 2: XGBoost Trees for Classification: https://youtu.be/8b1JEDvenQU Gradient Boost Part 1: Regression Main Ideas: https://youtu.be/3CC4N4z3GJc Gradient Boost Part 2: Regression Details:https://youtu.be/2xudPOBz-vs Gradient Boost Part 3: Classification Main Ideas: https://youtu.be/jxuNLH5dXCs Gradient Boost Part 4: Classification Details: https://youtu.be/StWY5QWMXCw ...and Ridge Regression: https://youtu.be/Q81RR3yKn30 Also note, this StatQuest is based on the following sources: The original XGBoost manuscript: https://arxiv.org/pdf/1603.02754.pdf The original XGBoost presentation: https://homes.cs.washington.edu/~tqchen/pdf/BoostedTree.pdf And the XGBoost Documentation: https://xgboost.readthedocs.io/en/latest/index.html Last but not least, I want to extend a special thanks to Giuseppe Fasanella and Samuel Judge for thoughtful discussions and helping me understand the math. For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer Corrections: 1:16 The Lambda should be outside of the square brackets. #statquest #xgboost

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XGBoost Part 4 (of 4): Crazy Cool Optimizations

2020-03-02

This video covers all kinds of extra optimizations that XGBoost uses when the training dataset is huge. So we'll talk about the Approximate Greedy Algorithm, Parallel Learning, The Weighted Quantile Sketch, Sparsity-Aware Split Finding (i.e. how XGBoost deals with missing data and uses default paths), Cache-Aware Access and Blocks for Out-of-Core Computation. That's a lot of stuff, but we'll go through it step-by-step and it will be a whole lot of fun. :) NOTE: This StatQuest assumes that you are already familiar with... XGBoost Part 1: XGBoost Trees for Regression: https://youtu.be/OtD8wVaFm6E XGBoost Part 2: XGBoost Trees for Classification: https://youtu.be/8b1JEDvenQU Quantiles and Percentiles: https://youtu.be/IFKQLDmRK0Y For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer #statquest #xgboost

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XGBoost in Python from Start to Finish

2020-08-01

NOTE: You can support StatQuest by purchasing the Jupyter Notebook and Python code seen in this video here: https://statquest.gumroad.com/l/uroxo NOTE: This StatQuest assumes that you are already familiar with: XGBoost for Regression: https://youtu.be/OtD8wVaFm6E XGBoost for Classification: https://youtu.be/8b1JEDvenQU XGBoost: Crazy Cool Optimizations: https://youtu.be/oRrKeUCEbq8 Regularization: https://youtu.be/Q81RR3yKn30 Cross Validation: https://youtu.be/fSytzGwwBVw Confusion Matrices: https://youtu.be/Kdsp6soqA7o For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 2:56 Import Modules 4:34 Import Data 13:43 Missing Data Part 1: Identifying 18:37 Missing Data Part 2: Dealing with it 24:03 Format Data Part 1: X and y 25:55 Format Data Part 2: One-Hot Encoding 33:25 XGBoost - Missing Data and One-Hot Encoding 36:43 Build a Preliminary XGBoost Model 45:01 Optimize Parameters with Cross Validation (GridSearchCV) 49:44 Build and Draw Final XGBoost Model #StatQuest #ML #XGBoost

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Cosine Similarity, Clearly Explained!!!

2023-01-30

The Cosine Similarity is a useful metric for determining, among other things, how similar or different two text phrases are. I'll be honest, the first time I saw the equation for The Cosine Similarity, I was scared. However, it turns out to be really quite simple, and this StatQuest walks you through it, one-step-at-a-time. BAM!!! English This video has been dubbed using an artificial voice via https://aloud.area120.google.com to increase accessibility. You can change the audio track language in the Settings menu. Spanish Este video ha sido doblado al español con voz artificial con https://aloud.area120.google.com para aumentar la accesibilidad. Puede cambiar el idioma de la pista de audio en el menú Configuración. Portuguese Este vídeo foi dublado para o português usando uma voz artificial via https://aloud.area120.google.com para melhorar sua acessibilidade. Você pode alterar o idioma do áudio no menu Configurações. If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:46 Visualizing the Cosine Similarity for two phrases 6:19 The equation for the Cosine Similarity #StatQuest #DubbedWithAloud

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Support Vector Machines Part 1 (of 3): Main Ideas!!!

2019-09-30

Support Vector Machines are one of the most mysterious methods in Machine Learning. This StatQuest sweeps away the mystery to let know how they work. Part 2: The Polynomial Kernel: https://youtu.be/Toet3EiSFcM Part 3: The Radial (RBF) Kernel: https://youtu.be/Qc5IyLW_hns NOTE: This StatQuest assumes you already know about... The bias/variance tradeoff: https://youtu.be/EuBBz3bI-aA Cross Validation: https://youtu.be/fSytzGwwBVw ALSO NOTE: This StatQuest is based on description of Support Vector Machines, and associated concepts, found on pages 337 to 354 of the Introduction to Statistical Learning in R: http://faculty.marshall.usc.edu/gareth-james/ISL/ I also found this blogpost helpful for understanding the Kernel Trick: https://blog.statsbot.co/support-vector-machines-tutorial-c1618e635e93 For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 0:40 Basic concepts and Maximal Margin Classifiers 4:35 Soft Margins (allowing misclassifications) 6:46 Soft Margin and Support Vector Classifiers 12:23 Intuition behind Support Vector Machines 15:25 The polynomial kernel function 17:30 The radial basis function (RBF) kernel 18:32 The kernel trick 19:31 Summary of concepts #statquest #SVM

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Support Vector Machines Part 2: The Polynomial Kernel (Part 2 of 3)

2019-11-04

Support Vector Machines use kernel functions to do all the hard work and this StatQuest dives deep into one of the most popular: The Polynomial Kernel. We talk about the parameter values and how they calculate high-dimensional coordinates via the dot-product and high-dimensional relationships NOTE: This StatQuest assumes you already know about... Support Vector Machines: https://youtu.be/efR1C6CvhmE Cross Validation: https://youtu.be/fSytzGwwBVw ALSO NOTE: This StatQuest is based on... 1) The description of Kernel Functions, and associated concepts on pages 352 to 353 of the Introduction to Statistical Learning in R: http://faculty.marshall.usc.edu/gareth-james/ISL/ 2) The Polynomial Kernel is also based on the Kernel used by scikit-learn: https://scikit-learn.org/stable/modules/svm.html For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer #statquest #SVM #kernel

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Support Vector Machines Part 3: The Radial (RBF) Kernel (Part 3 of 3)

2019-11-04

Support Vector Machines use kernel functions to do all the hard work and this StatQuest dives deep into one of the most popular: The Radial (RBF) Kernel. We talk about the parameter values, how they calculate high-dimensional coordinates and then we'll figure out, step-by-step, how the Radial Kernel works in infinite dimensions. NOTE: This StatQuest assumes you already know about... Support Vector Machines: https://youtu.be/efR1C6CvhmE Cross Validation: https://youtu.be/fSytzGwwBVw The Polynomial Kernel: https://youtu.be/Toet3EiSFcM ALSO NOTE: This StatQuest is based on... 1) The description of Kernel Functions, and associated concepts on pages 352 to 353 of the Introduction to Statistical Learning in R: http://faculty.marshall.usc.edu/gareth-james/ISL/ 2) The derivation of the of the infinite dot product is based on Matthew Bernstein's notes: http://pages.cs.wisc.edu/~matthewb/pages/notes/pdf/svms/RBFKernel.pdf For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer #statquest #SVM #RBF

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Support Vector Machines in Python from Start to Finish.

2020-06-30

NOTE: You can support StatQuest by purchasing the Jupyter Notebook and Python code seen in this video here: http://statquest.gumroad.com/l/iulnea This webinar was recorded 20200609 at 11:00am (New York Time) NOTE: This StatQuest assumes that you are already familiar with: Support Vector Machines: https://youtu.be/efR1C6CvhmE The Radial Basis Function: https://youtu.be/Qc5IyLW_hns Regularization: https://youtu.be/Q81RR3yKn30 Cross Validation: https://youtu.be/fSytzGwwBVw Confusion Matrices: https://youtu.be/Kdsp6soqA7o For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 4:16 Import Modules 6:36 Import Data 11:27 Missing Data Part 1: Identifying 16:57 Missing Data Part 2: Dealing with it 21:04 Downsampling the data 24:35 Format Data Part 1: X and y 26:35 Format Data Part 2: One-Hot Encoding 31:25 Format Data Part 3: Centering and Scaling 32:45 Build a Preliminary SVM 34:55 Optimize Parameters with Cross Validation (GridSearchCV) 37:58 Build and Draw Final SVM #StatQuest #ML #SVM

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The Essential Main Ideas of Neural Networks

2020-08-31

Neural Networks are one of the most popular Machine Learning algorithms, but they are also one of the most poorly understood. Everyone says Neural Networks are "black boxes", but that's not true at all. In this video I break each piece down and show how it works, step-by-step, using simple mathematics that is still true to the algorithm. By the end of this video you will have a deep understanding of what Neural Networks do. English This video has been dubbed using an artificial voice via https://aloud.area120.google.com to increase accessibility. You can change the audio track language in the Settings menu. Spanish Este video ha sido doblado al español con voz artificial con https://aloud.area120.google.com para aumentar la accesibilidad. Puede cambiar el idioma de la pista de audio en el menú Configuración. Portuguese Este vídeo foi dublado para o português usando uma voz artificial via https://aloud.area120.google.com para melhorar sua acessibilidade. Você pode alterar o idioma do áudio no menu Configurações. For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 2:01 A simple dataset and problem 3:37 Description of Neural Networks 7:54 Creating a squiggle from curved lines 15:25 Using the Neural Network to make a prediction 16:38 Some more Neural Network terminology #StatQuest #NeuralNetworks #DubbedWithAloud

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Neural Networks Pt. 2: Backpropagation Main Ideas

2020-10-19

Backpropagation is the method we use to optimize parameters in a Neural Network. The ideas behind backpropagation are quite simple, but there are tons of details. This StatQuest focuses on explaining the main ideas in a way that is easy to understand. NOTE: This StatQuest assumes that you already know the main ideas behind... Neural Networks: https://youtu.be/CqOfi41LfDw The Chain Rule: https://youtu.be/wl1myxrtQHQ Gradient Descent: https://youtu.be/sDv4f4s2SB8 LAST NOTE: When I was researching this 'Quest, I found this page by Sebastian Raschka to be helpful: https://sebastianraschka.com/faq/docs/backprop-arbitrary.html For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 3:55 Fitting the Neural Network to the data 6:04 The Sum of the Squared Residuals 7:23 Testing different values for a parameter 8:38 Using the Chain Rule to calculate a derivative 13:28 Using Gradient Descent 16:05 Summary #StatQuest #NeuralNetworks #Backpropagation

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Backpropagation Details Pt. 1: Optimizing 3 parameters simultaneously.

2020-11-02

The main ideas behind Backpropagation are super simple, but there are tons of details when it comes time to implementing it. This video shows how to optimize three parameters in a Neural Network simultaneously and introduces some Fancy Notation. NOTE: This StatQuest assumes that you already know the main ideas behind Backpropagation: https://youtu.be/IN2XmBhILt4 ...and that also means you should be familiar with... Neural Networks: https://youtu.be/CqOfi41LfDw The Chain Rule: https://youtu.be/wl1myxrtQHQ Gradient Descent: https://youtu.be/sDv4f4s2SB8 LAST NOTE: When I was researching this 'Quest, I found this page by Sebastian Raschka to be helpful: https://sebastianraschka.com/faq/docs/backprop-arbitrary.html For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 3:01 Derivatives do not change when we optimize multiple parameters 6:28 Fancy Notation 10:51 Derivatives with respect to two different weights 15:02 Gradient Descent for three parameters 17:19 Fancy Gradient Descent Animation #StatQuest #NeuralNetworks #Backpropagation

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Backpropagation Details Pt. 2: Going bonkers with The Chain Rule

2020-11-02

This StatQuest picks up right here Part 1 left off, and this time we're going to go totally bonkers with The Chain Rule and optimize every single parameter in this simple Neural Network. BAM!!! NOTE: This StatQuest assumes that you already know the main ideas behind Backpropagation: https://youtu.be/IN2XmBhILt4 ...and that also means you should be familiar with... Neural Networks: https://youtu.be/CqOfi41LfDw The Chain Rule: https://youtu.be/wl1myxrtQHQ Gradient Descent: https://youtu.be/sDv4f4s2SB8 LAST NOTE: When I was researching this 'Quest, I found this page by Sebastian Raschka to be helpful: https://sebastianraschka.com/faq/docs/backprop-arbitrary.html For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:28 The derivative of the weight W1 5:58 The derivative of the bias b1 7:39 The derivatives of W2 and b2 9:21 Gradient Descent for all parameters 11:18 Fancy Gradient Descent Animation #StatQuest #NeuralNetworks #Backpropagation

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Neural Networks Pt. 3: ReLU In Action!!!

2020-11-23

The ReLU activation function is one of the most popular activation functions for Deep Learning and Convolutional Neural Networks. However, the function itself is deceptively simple. This StatQuest walks you through an example, step-by-step, that uses the ReLU activation function so you can see exactly what it does and how it works. NOTE: This StatQuest assumes that you are already familiar with the main ideas behind Neural Networks. If not, check out the 'Quest: https://youtu.be/CqOfi41LfDw For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:45 ReLU in the Hidden Layer 5:35 ReLU right before the Output 7:38 The derivative of ReLU #StatQuest #NeuralNetworks #ReLU

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Neural Networks Pt. 4: Multiple Inputs and Outputs

2021-02-01

So far, this series has explained how very simple Neural Networks, with only 1 input and 1 output, function. This video shows how these exact same concepts generalize to multiple inputs and outputs and provides a context within we can discuss SoftMax and ArgMax for modifying the output data. NOTE: This StatQuest assumes you already know... The main ideas behind Neural Networks: https://youtu.be/CqOfi41LfDw The ReLU Activation Function: https://youtu.be/68BZ5f7P94E For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 2:07 Multiple inputs and outputs 3:57 The blue bent surface for Setosa 6:28 The orange bent surface for Setosa 6:52 The green crinkled surface for Setosa 8:42 Predicting Setosa 9:42 Versicolor 11:11 Virginica #StatQuest #NeuralNetworks

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Neural Networks Part 5: ArgMax and SoftMax

2021-02-08

When your Neural Network has more than one output, then it is very common to train with SoftMax and, once trained, swap SoftMax out for ArgMax. This video give you all the details on these two methods so that you'll know when and why to use ArgMax or SoftMax. NOTE: This StatQuest assumes that you already understand: The main ideas behind Neural Networks: https://youtu.be/CqOfi41LfDw How Neural Networks work with multiple inputs and outputs: https://youtu.be/83LYR-1IcjA For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 2:02 ArgMax 4:21 SoftMax 6:36 SoftMax properties 9:31 SoftMax general equation 10:20 SoftMax derivatives #StatQuest #NeuralNetworks #ArgMax #SoftMax

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The SoftMax Derivative, Step-by-Step!!!

2021-02-08

Here's step-by-step guide that shows you how to take the derivatives of the SoftMax function, as used as a final output layer in a Neural Networks. NOTE: This StatQuest assumes that you already understand the main ideas behind SoftMax. If not, check out the 'Quest: https://youtu.be/KpKog-L9veg For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 0:57 SoftMax derivative with respect to the output of interest 3:58 SoftMax derivative with respect to other outputs #StatQuest #NeuralNetworks #SoftMax

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Neural Networks Part 6: Cross Entropy

2021-03-01

When a Neural Network is used for classification, we usually evaluate how well it fits the data with Cross Entropy. This StatQuest gives you and overview of how to calculate Cross Entropy and Total Cross Entropy. NOTE: This StatQuest assumes that you are already familiar with... The main ideas behind neural networks: https://youtu.be/CqOfi41LfDw The main ideas behind backpropagation: https://youtu.be/IN2XmBhILt4 Neural networks with multiple inputs and outputs: https://youtu.be/83LYR-1IcjA ArgMax and SoftMax: https://youtu.be/KpKog-L9veg For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:48 Cross Entropy defined 2:50 General equation for Cross Entropy 4:11 Calculating Total Cross Entropy 5:41 Why Cross Entropy and not SSR? #StatQuest #NeuralNetworks #CrossEntropy

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Neural Networks Part 7: Cross Entropy Derivatives and Backpropagation

2021-03-01

Here is a step-by-step guide that shows you how to take the derivative of the Cross Entropy function for Neural Networks and then shows you how to use that derivative for Backpropagation. NOTE: This StatQuest assumes that you are already familiar with... The main ideas behind neural networks: https://youtu.be/CqOfi41LfDw The main ideas behind backpropagation: https://youtu.be/IN2XmBhILt4 Neural networks with multiple inputs and outputs: https://youtu.be/aObJUevCVDc ArgMax and SoftMax: https://youtu.be/KpKog-L9veg Cross Entropy: https://youtu.be/6ArSys5qHAU For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 5:47 dCE_setosa with respect to b3 11:19 dCE_virginica with respect to b3 15:03 Other derivatives 16:09 Backpropagation with cross entropy #StatQuest #NeuralNetworks #CrossEntropy

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Neural Networks Part 8: Image Classification with Convolutional Neural Networks (CNNs)

2021-03-08

One of the coolest things that Neural Networks can do is classify images, and this is often done with a type of Neural Network called a Convolutional Neural Network (or CNN for short). In this StatQuest, we walk through how Convolutional Neural Networks work, one step at a time, and highlight the main ideas behind filters and pooling. NOTE: This StatQuest assumes that you are already familiar with... The main ideas behind neural networks: https://youtu.be/CqOfi41LfDw The main ideas behind backpropagation: https://youtu.be/IN2XmBhILt4 Neural networks with multiple inputs and outputs: https://youtu.be/83LYR-1IcjA For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:51 Image classification with a normal Neural Network 4:28 The main ideas of Convolutional Neural Networks 4:59 Creating a Feature Map with a Filter 7:58 Pooling 9:48 Using the Pooled values as input for a Neural Network 11:29 Classifying an image of the letter "X" 13:04 Classifying a shifted image of the letter "X" #StatQuest #NeuralNetworks #Convolution

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Recurrent Neural Networks (RNNs), Clearly Explained!!!

2022-07-11

When you don't always have the same amount of data, like when translating different sentences from one language to another, or making stock market predictions from different companies, Recurrent Neural Networks come to the rescue. In this StatQuest, we'll show you how Recurrent Neural Networks work, one step at a time, and then we'll show you their critical flaw that will lead us to understanding Long Short-Term Memory Networks. English This video has been dubbed using an artificial voice via https://aloud.area120.google.com to increase accessibility. You can change the audio track language in the Settings menu. Spanish Este video ha sido doblado al español con voz artificial con https://aloud.area120.google.com para aumentar la accesibilidad. Puede cambiar el idioma de la pista de audio en el menú Configuración. Portuguese Este vídeo foi dublado para o português usando uma voz artificial via https://aloud.area120.google.com para melhorar sua acessibilidade. Você pode alterar o idioma do áudio no menu Configurações. For a complete index of all the StatQuest videos, check out... https://app.learney.me/maps/StatQuest ...or... https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 4:13 Basic anatomy of a recurrent neural network 5:59 Running data through a recurrent neural network 10:31 Shared weights and biases 11:23 The vanishing/exploding gradient problem. #StatQuest #NeuralNetworks #Deeplearning #DubbedWithAloud

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Long Short-Term Memory (LSTM), Clearly Explained

2022-11-07

Basic recurrent neural networks are great, because they can handle different amounts of sequential data, but even relatively small sequences of data can make them difficult to train. This is where Long Short-Term Memory (LSTM) saves the day. Long Short-Term Memory is a type of recurrent neural network that can handle much larger sequences of data without those pesky exploding/vanishing gradient problems that plague basic recurrent neural networks. Spanish Este video ha sido doblado al español con voz artificial con https://aloud.area120.google.com para aumentar la accesibilidad. Puede cambiar el idioma de la pista de audio en el menú Configuración. Portuguese Este vídeo foi dublado para o português usando uma voz artificial via https://aloud.area120.google.com para melhorar sua acessibilidade. Você pode alterar o idioma do áudio no menu Configurações. For a complete index of all the StatQuest videos, check out... https://app.learney.me/maps/StatQuest ...or... https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song, introduction and main ideas 4:19 The sigmoid and tanh activation functions 5:58 LSTM Stage 1: The percent to remember 9:25 LSTM Stage 2: Update the long-term memory 12:42 LSTM Stage 3:Update the short-term memory 14:33 LSTM in action with real data #StatQuest #LSTM #Dubbedwithaloud

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Word Embedding and Word2Vec, Clearly Explained!!!

2023-03-13

Words are great, but if we want to use them as input to a neural network, we have to convert them to numbers. One of the most popular methods for assigning numbers to words is to use a Neural Network to create Word Embeddings. In this StatQuest, we go through the steps required to create Word Embeddings, and show how we can visualize and validate them. We then talk about one of the most popular Word Embedding tools, word2vec. BAM!!! Note, this StatQuest assumes that you are already familiar with... The Basics of how Neural Networks Work: https://youtu.be/CqOfi41LfDw The Basics of how Backpropagation Works: https://youtu.be/IN2XmBhILt4 How the Softmax function works: https://youtu.be/KpKog-L9veg How Cross Entropy works: https://youtu.be/6ArSys5qHAU If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 4:25 Building a Neural Network to do Word Embedding 8:18 Visualizing and Validating the Word Embedding 10:42 Summary of Main Ideas 11:44 word2vec 13:36 Speeding up training with Negative Sampling #StatQuest #word2vec

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Sequence-to-Sequence (seq2seq) Encoder-Decoder Neural Networks, Clearly Explained!!!

2023-05-08

In this video, we introduce the basics of how Neural Networks translate one language, like English, to another, like Spanish. The ideas is to convert one sequence of things into another sequence of things, and thus, this type of neural network can be applied to all sort so of problems, including translating amino acids into 3-dimensional structures. NOTE: This StatQuest assumes that you are already familiar with... Long, Short-Term Memory (LSTM): https://youtu.be/YCzL96nL7j0 ...and... Word Embedding: https://youtu.be/viZrOnJclY0 Also, if you'd like to go through Ben Trevett's tutorials, see: https://github.com/bentrevett/pytorch-seq2seq/tree/rewrite Finally, here's a link to the original manuscript: https://arxiv.org/abs/1409.3215 If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 3:43 Building the Encoder 8:27 Building the Decoder 12:58 Training The Encoder-Decoder Model 14:40 My model vs the model from the original manuscript #StatQuest #seq2seq #neuralnetwork

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Attention for Neural Networks, Clearly Explained!!!

2023-06-05

Attention is one of the most important concepts behind Transformers and Large Language Models, like ChatGPT. However, it's not that complicated. In this StatQuest, we add Attention to a basic Sequence-to-Sequence (Seq2Seq or Encoder-Decoder) model and walk through how it works and is calculated, one step at a time. BAM!!! NOTE: This StatQuest is based on two manuscripts. 1) The manuscript that originally introduced Attention to Encoder-Decoder Models: Neural Machine Translation by Jointly Learning to Align and Translate: https://arxiv.org/abs/1409.0473 and 2) The manuscript that first used the Dot-Product similarity for Attention in a similar context: Effective Approaches to Attention-based Neural Machine Translation https://arxiv.org/abs/1508.04025 NOTE: This StatQuest assumes that you are already familiar with basic Encoder-Decoder neural networks. If not, check out the 'Quest: https://youtu.be/L8HKweZIOmg If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 3:14 The Main Idea of Attention 5:34 A worked out example of Attention 10:18 The Dot Product Similarity 11:52 Using similarity scores to calculate Attention values 13:27 Using Attention values to predict an output word 14:22 Summary of Attention #StatQuest #neuralnetwork #attention

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Transformer Neural Networks, ChatGPT's foundation, Clearly Explained!!!

2023-07-24

Transformer Neural Networks are the heart of pretty much everything exciting in AI right now. ChatGPT, Google Translate and many other cool things, are based on Transformers. This StatQuest cuts through all the hype and shows you how a Transformer works, one-step-at-a time. NOTE: If you're interested in learning more about Backpropagation, check out these 'Quests: The Chain Rule: https://youtu.be/wl1myxrtQHQ Gradient Descent: https://youtu.be/sDv4f4s2SB8 Backpropagation Main Ideas: https://youtu.be/IN2XmBhILt4 Backpropagation Details Part 1: https://youtu.be/iyn2zdALii8 Backpropagation Details Part 2: https://youtu.be/GKZoOHXGcLo If you're interested in learning more about the SoftMax function, check out: https://youtu.be/KpKog-L9veg If you're interested in learning more about Word Embedding, check out: https://youtu.be/viZrOnJclY0 If you'd like to learn more about calculating similarities in the context of neural networks and the Dot Product, check out: Cosine Similarity: https://youtu.be/e9U0QAFbfLI Attention: https://youtu.be/PSs6nxngL6k If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! paypal: https://www.paypal.me/statquest venmo: @JoshStarmer Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:26 Word Embedding 7:30 Positional Encoding 12:53 Self-Attention 23:37 Encoder and Decoder defined 23:53 Decoder Word Embedding 25:08 Decoder Positional Encoding 25:50 Transformers were designed for parallel computing 27:13 Decoder Self-Attention 27:59 Encoder-Decoder Attention 31:19 Decoding numbers into words 32:23 Decoding the second token 34:13 Extra stuff you can add to a Transformer #StatQuest #Transformer #ChatGPT

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Decoder-Only Transformers, ChatGPTs specific Transformer, Clearly Explained!!!

2023-08-28

Transformers are taking over AI right now, and quite possibly their most famous use is in ChatGPT. ChatGPT uses a specific type of Transformer called a Decoder-Only Transformer, and this StatQuest shows you how they work, one step at a time. And at the end (at 32:14), we talk about the differences between a Normal Transformer and a Decoder-Only Transformer. BAM! NOTE: If you're interested in learning more about Backpropagation, check out these 'Quests: The Chain Rule: https://youtu.be/wl1myxrtQHQ Gradient Descent: https://youtu.be/sDv4f4s2SB8 Backpropagation Main Ideas: https://youtu.be/IN2XmBhILt4 Backpropagation Details Part 1: https://youtu.be/iyn2zdALii8 Backpropagation Details Part 2: https://youtu.be/GKZoOHXGcLo If you're interested in learning more about the SoftMax function, check out: https://youtu.be/KpKog-L9veg If you're interested in learning more about Word Embedding, check out: https://youtu.be/viZrOnJclY0 If you'd like to learn more about calculating similarities in the context of neural networks and the Dot Product, check out: Cosine Similarity: https://youtu.be/e9U0QAFbfLI Attention: https://youtu.be/PSs6nxngL6k If you'd like to learn more about Normal Transformers, see: https://youtu.be/zxQyTK8quyY If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! paypal: https://www.paypal.me/statquest venmo: @JoshStarmer Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:34 Word Embedding 7:26 Position Encoding 10:10 Masked Self-Attention, an Autoregressive method 22:35 Residual Connections 23:00 Generating the next word in the prompt 26:23 Review of encoding and generating the prompt 27:20 Generating the output, Part 1 28:46 Masked Self-Attention while generating the output 30:40 Generating the output, Part 2 32:14 Normal Transformers vs Decoder-Only Transformers #StatQuest

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Tensors for Neural Networks, Clearly Explained!!!

2022-02-28

Tensors are super important for neural networks, but can be confusing because different people use the word "Tensor" differently. In this StatQuest, we clear this up and tell you what the big deal is. BAM! NOTE: If you are not already familiar with Neural Networks, check out the Neural Network playlist: https://www.youtube.com/watch?v=CqOfi41LfDw&list=PLblh5JKOoLUIxGDQs4LFFD--41Vzf-ME1 For a complete index of all the StatQuest videos, check out... https://app.learney.me/maps/StatQuest ...or... https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:34 Why we need Tensors 4:52 Tensors store data 6:51 Tensors have hardware acceleration 7:37 Tensors have automatic differentiation #StatQuest #Tensors #NeuralNetworks

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Essential Matrix Algebra for Neural Networks, Clearly Explained!!!

2023-12-11

Although you don't need to know matrix algebra to understand the ideas behind neural networks, if you want to code them or read the latest manuscripts about the field, then you'll need to understand matrix algebra. This video teaches the essential topics in matrix algebra and shows how a neural network can be written as a matrix equation, and then shows how understand PyTorch documentation, error messages and the equations for Attention, which is the fundamental concept behind ChatGPT. Note: If you want to learn more about neural networks... https://youtu.be/CqOfi41LfDw ...backpropagation... https://youtu.be/IN2XmBhILt4 ...the ReLU activation function... https://youtu.be/68BZ5f7P94E ...tensors... https://youtu.be/L35fFDpwIM4 ...SoftMax... https://youtu.be/KpKog-L9veg ...Transformers and Attention... https://youtu.be/zxQyTK8quyY If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! paypal: https://www.paypal.me/statquest venmo: @JoshStarmer Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 2:35 Introduction to linear transformations 5:57 Linear transformations in matrix notation 7:34 Matrix multiplication 11:03 Matrix multiplication consolidates a sequence of linear transformations 13: 46 Order matters for matrix multiplication 15:18 Transposing a matrix 16:37 Matrix notation and equations 18:51 Using matrix equations to describe a neural network 24:26 nn.Linear() documentation explained 26:38 1-D vs 2-D error messages explained 27:17 The matrix equation for Attention explained #StatQuest #neuralnetworks #matrixalgebra

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The matrix math behind transformer neural networks, one step at a time!!!

2024-04-08

Transformers, the neural network architecture behind ChatGPT, do a lot of math. However, this math can be done quickly using matrix math because GPUs are optimized for it. Matrix math is also used when we code neural networks, so learning how ChatGPT does it will help you code your own. Thus, in this video, we go through the math one step at a time and explain what each step does so that you can use it on your own with confidence. NOTE: This StatQuest assumes that you are already familiar with: Transformers: https://youtu.be/zxQyTK8quyY The essential matrix algebra for neural networks: https://youtu.be/bQ5BoolX9Ag If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! paypal: https://www.paypal.me/statquest venmo: @JoshStarmer Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:43 Word Embedding 3:37 Position Encoding 4:28 Self Attention 12:09 Residual Connections 13:08 Decoder Word Embedding and Position Encoding 15:33 Masked Self Attention 20:18 Encoder-Decoder Attention 21:31 Fully Connected Layer 22:16 SoftMax #StatQuest #Transformer #ChatGPT

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The StatQuest Introduction to PyTorch

2022-04-25

PyTorch is one of the most popular tools for making Neural Networks. This StatQuest walks you through a simple example of how to use PyTorch one step at a time. By the end of this StatQuest, you'll know how to create a new neural network from scratch, make predictions and graph the output, and optimize a parameter using backpropagation. BAM!!! To learn more about Lightning: https://lightning.ai/ The code demonstrated this video can be downloaded here: https://lightning.ai/lightning-ai/studios/statquest-introduction-to-coding-neural-networks-with-pytorch?view=public&section=all This StatQuest assumes that you are already familiar with... Neural Networks: https://youtu.be/CqOfi41LfDw Backpropagation: https://youtu.be/IN2XmBhILt4 The ReLU Activation Function: https://youtu.be/68BZ5f7P94E Tensors: https://youtu.be/L35fFDpwIM4 To install PyTorch see: https://pytorch.org/get-started/locally/ To install matplotlib, see: https://matplotlib.org/stable/users/getting_started/ To install seaborn, see: https://seaborn.pydata.org/installing.html For a complete index of all the StatQuest videos, check out... https://app.learney.me/maps/StatQuest ...or... https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:38 Coding preliminaries 2:15 Creating a neural network in PyTorch 7:54 Graphing the neural network's output 10:47 Optimizing a parameter with backpropagation #StatQuest #NeuralNetworks #PyTorch

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Introduction to Coding Neural Networks with PyTorch and Lightning

2022-09-19

Although we've seen how to code a simple neural network with PyTorch, we can make our lives a lot easier if we add Lightning to the mix. It makes writing the code easier, makes it portable to different computing environments and can even find the learning rate for us! TRIPLE BAM!!!! NOTE: You can download the code here: https://lightning.ai/lightning-ai/studios/statquest-introduction-to-neural-networks-with-pytorch-lightning?view=public&section=all Spanish Este video ha sido doblado al español con voz artificial con https://aloud.area120.google.com para aumentar la accesibilidad. Puede cambiar el idioma de la pista de audio en el menú Configuración. Portuguese Este vídeo foi dublado para o português usando uma voz artificial via https://aloud.area120.google.com para melhorar sua acessibilidade. Você pode alterar o idioma do áudio no menu Configurações. For a complete index of all the StatQuest videos, check out... https://app.learney.me/maps/StatQuest ...or... https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:04 Review of basic PyTorch 2:34 Coding a pretrained neural network with PyTorch + Lightning 7:52 Training a neural network with PyTorch + Lightning 14:05 Using Lightning to find a good Learning Rate 17:25 Taking advantage of GPU acceleration with Lightning #StatQuest #DubbedWithAloud #PyTorch #Lightning

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Long Short-Term Memory with PyTorch + Lightning

2023-01-24

In this StatQuest we'll learn how to code an LSTM unit from scratch and then train it. Then we'll do the same thing with the PyTorch function nn.LSMT(). Along the way we'll learn two cool tricks that Lightning gives us that make our lives easier: 1) How to add more training epochs without starting over and 2) How to easily visualize the training results to determine if you need to do more training or are done. English This video has been dubbed using an artificial voice via https://aloud.area120.google.com to increase accessibility. You can change the audio track language in the Settings menu. Spanish Este video ha sido doblado al español con voz artificial con https://aloud.area120.google.com para aumentar la accesibilidad. Puede cambiar el idioma de la pista de audio en el menú Configuración. Portuguese Este vídeo foi dublado para o português usando uma voz artificial via https://aloud.area120.google.com para melhorar sua acessibilidade. Você pode alterar o idioma do áudio no menu Configurações. If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 4:25 Importing the modules 5:39 An outline of an LSTM class 6:56 init(): Creating and initializing the tensors 9:09 lstm_unit(): Doing the LSTM math 12:25 forward(): Make a forward pass through an unrolled LSTM 13:42 configure_optimizers(): Configure the...optimizers. 14:00 training_step(): Calculate the loss and log progress 16:40 Using and training our homemade LSTM 20:43 Evaluating training with TensorBoard 23:22 Adding more epochs to training 26:18 Using and training PyTorch's nn.lstm() #StatQuest

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Word Embedding in PyTorch + Lightning

2023-11-06

Word embedding is the first step in lots of neural networks, including Transformers (like ChatGPT) and other state of the art models. Here we learn how to code a stand alone word embedding network from scratch and with nn.Linear. We then learn how to load and use pre-trained word embedding values with nn.Embedding. NOTE: This StatQuest assumes that you are already familiar with Word Embedding, if not, check out the 'Quest: https://youtu.be/viZrOnJclY0 If you'd like to support StatQuest, please consider... Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... https://statquest.org/statquest-store/ ...or just donating to StatQuest! paypal: https://www.paypal.me/statquest venmo: @JoshStarmer Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 1:53 Importing modules 2:48 Encoding the training data 6:55 Word Embedding from scratch 16:54 Graphing the embedding values 21:17 Printing out predicted words 20:37 Word Embedding with nn.Linear 28:12 Loading and using pre-trained Embedding values with nn.Embedding #StatQuest #neuralnetworks #transformers

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Decision and Classification Trees, Clearly Explained!!!

2021-04-26

Decision trees are part of the foundation for Machine Learning. Although they are quite simple, they are very flexible and pop up in a very wide variety of situations. This StatQuest covers all the basics and shows you how to create a new tree from scratch, one step at a time. NOTE: This is an updated and revised version of the Decision Tree StatQuest that I made back in 2018. It is my hope that this new version does a better job answering some of the most frequently asked questions people asked about the old one. Note, you may also want to learn about... Regression Trees: https://youtu.be/g9c66TUylZ4 Bias and Variance (and over fitting): https://youtu.be/EuBBz3bI-aA Cross Validation: https://youtu.be/fSytzGwwBVw Pruning Trees: https://youtu.be/D0efHEJsfHo For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 0:18 Basic decision tree concepts 3:16 Building a tree with Gini Impurity 9:15 Numeric and continuous variables 12:35 Adding branches 13:56 Adding leaves 14:32 Defining output values 15:12 Using the tree 15:38 How to prevent overfitting #StatQuest #decisiontree #ML

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StatQuest: Decision Trees, Part 2 - Feature Selection and Missing Data

2018-01-29

This is just a short follow up to last week's StatQuest where we introduced decision trees. Here we show how decision trees deal with variables that don't improve the tree (feature selection) and how they deal with missing data. To learn the basics about Decision Trees, see: https://youtu.be/_L39rN6gz7Y For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buy The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer Correction: 1:35 I mistyped the gini impurity. I wrote 0.29, but it should be 0.19. #statquest #ML #decisiontree

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Regression Trees, Clearly Explained!!!

2019-08-20

Regression Trees are one of the fundamental machine learning techniques that more complicated methods, like Gradient Boost, are based on. They are useful for times when there isn't an obviously linear relationship between what you want to predict, and the things you are using to make the predictions. This StatQuest walks you through the steps required to build Regression Trees so that they are Clearly Explained. NOTE: This StatQuest assumes you already know about... The bias/variance tradeoff: https://youtu.be/EuBBz3bI-aA Decision Trees: https://youtu.be/7VeUPuFGJHk Linear Regression: https://www.youtube.com/watch?v=nk2CQITm_eo ALSO NOTE: This StatQuest is based on the definition of Regression Trees found on page 328 to 331 of the Introduction to Statistical Learning. https://www.statlearning.com/ For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 0:41 Motivation for Regression Trees 2:19 Regression Trees vs Classification Trees 7:11 Building a Regression Tree with one variable 18:59 Building a Regression Tree with multiple variables 20:54 Summary of concepts and main ideas #statquest #regression #tree

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How to Prune Regression Trees, Clearly Explained!!!

2019-11-25

Pruning Regression Trees is one the most important ways we can prevent them from overfitting the Training Data. This video walks you through Cost Complexity Pruning, aka Weakest Link Pruning, step-by-step so that you can learn how it works and see it in action. NOTE: This StatQuest assumes you already know about... Regression Trees: https://youtu.be/g9c66TUylZ4 ALSO NOTE: This StatQuest is based on the Cost Complexity Pruning algorithm found on pages 307 to 309 of the Introduction to Statistical Learning in R: http://faculty.marshall.usc.edu/gareth-james/ISL/ For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying The StatQuest Illustrated Guide to Machine Learning!!! PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 0:59 Motivation for pruning a tree 3:58 Calculating the sum of squared residuals for pruned trees 7:50 Comparing pruned trees with alpha. 11:17 Step 1: Use all of the data to build trees with different alphas 13:05 Step 2: Use cross validation to compare alphas 15:02 Step 3: Select the alpha that, on average, gives the best results 15:27 Step 4: Select the original tree that corresponds to that alpha #statquest #regression #tree

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Classification Trees in Python from Start to Finish

2020-06-07

NOTE: You can support StatQuest by purchasing the Jupyter Notebook and Python code seen in this video here: https://statquest.gumroad.com/l/tzxoh This webinar was recorded 20200528 at 11:00am (New York time). NOTE: This StatQuest assumes are already familiar with: Decision Trees: https://youtu.be/7VeUPuFGJHk Cross Validation: https://youtu.be/fSytzGwwBVw Confusion Matrices: https://youtu.be/Kdsp6soqA7o Cost Complexity Pruning: https://youtu.be/D0efHEJsfHo Bias and Variance and Overfitting: https://youtu.be/EuBBz3bI-aA For a complete index of all the StatQuest videos, check out: https://statquest.org/video-index/ If you'd like to support StatQuest, please consider... Buying my book, The StatQuest Illustrated Guide to Machine Learning: PDF - https://statquest.gumroad.com/l/wvtmc Paperback - https://www.amazon.com/dp/B09ZCKR4H6 Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC Patreon: https://www.patreon.com/statquest ...or... YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join ...a cool StatQuest t-shirt or sweatshirt: https://shop.spreadshirt.com/statquest-with-josh-starmer/ ...buying one or two of my songs (or go large and get a whole album!) https://joshuastarmer.bandcamp.com/ ...or just donating to StatQuest! https://www.paypal.me/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https://twitter.com/joshuastarmer 0:00 Awesome song and introduction 5:23 Import Modules 7:40 Import Data 11:18 Missing Data Part 1: Identifying 15:57 Missing Data Part 2: Dealing with it 21:16 Format Data Part 1: X and y 23:33 Format Data Part 2: One-Hot Encoding 37:29 Build Preliminary Tree 46:31 Pruning Part 1: Visualize Alpha 51:22 Pruning Part 2: Cross Validation 56:46 Build and Draw Final Tree #StatQuest #ML #ClassificationTrees

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