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Parent(s):
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fuentes
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Home.py
CHANGED
@@ -16,7 +16,19 @@ class Home(Page):
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{"titulo": "Analysis of Classification by Supervised and Unsupervised Learning",
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"url": "https://www.computer.org/csdl/proceedings-article/iccima/2007/30500280/12OmNzxyiHV"},
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{"titulo": "Implementation of Interval Arithmetic Algorithms on FPGAs",
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"url": "https://dl.acm.org/doi/10.1109/ICCIMA.2007.237"}
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}
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archivos_css = ["main",
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@@ -38,14 +50,11 @@ class Home(Page):
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body="""
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## Clasificación de imágenes
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La
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Consiste en enseñar a una computadora a
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## Recursos
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##
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""")
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for fuente in self.get_global('fuentes'):
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@@ -53,9 +62,7 @@ class Home(Page):
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unsafe_allow_html=False,
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help=None,
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body=f"""
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*Enlace: {fuente.get('url')}*
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"""
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self.builder().sidebar.markdown(
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{"titulo": "Analysis of Classification by Supervised and Unsupervised Learning",
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"url": "https://www.computer.org/csdl/proceedings-article/iccima/2007/30500280/12OmNzxyiHV"},
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{"titulo": "Implementation of Interval Arithmetic Algorithms on FPGAs",
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"url": "https://dl.acm.org/doi/10.1109/ICCIMA.2007.237"},
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{"titulo": "Transformers",
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"url": "https://huggingface.co/docs/transformers/v4.32.1/en/index"},
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{"titulo": "Modelo Google/ViT",
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"url": "https://huggingface.co/google/vit-base-patch16-224"},
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{"titulo": "ImageNet DataSet",
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"url": "https://www.image-net.org/download.php"},
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{"titulo": "ImageNet clases",
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"url": "https://deeplearning.cms.waikato.ac.nz/user-guide/class-maps/IMAGENET/"},
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{"titulo": "PIL",
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"url": "https://pypi.org/project/Pillow/"},
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{"titulo": "requests",
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"url": "https://pypi.org/project/requests/"}]
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}
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archivos_css = ["main",
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body="""
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## Clasificación de imágenes
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La clasificación de imágenes, es una rama esencial de la visión artificial, se refiere a la capacidad de las computadoras para identificar y categorizar objetos en imágenes visuales.
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Consiste en enseñar a una computadora a identificar la categoría general de una fotografía, como "perro" o "coche", en lugar de analizar detalles específicos o ubicar objetos.
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## Recursos
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""")
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for fuente in self.get_global('fuentes'):
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unsafe_allow_html=False,
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help=None,
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body=f"""
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* **{fuente.get('titulo')}** - {fuente.get('url')}
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"""
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self.builder().sidebar.markdown(
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