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04_pytorch_custom_datasets.ipynb

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"Training a model on this *artificially* altered dataset hopefully results in a model that is capable of better *generalization* (the patterns it learns are more robust to future unseen examples).\n",
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"\n",
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"You can see many different examples of data augmentation performed on images using `torchvision.transforms` in PyTorch's [Illustration of Transforms example](https://pytorch.org/vision/stable/auto_examples/plot_transforms.html#illustration-of-transforms).\n",
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"You can see many different examples of data augmentation performed on images using `torchvision.transforms` in PyTorch's [Illustration of Transforms example](https://pytorch.org/vision/main/auto_examples/transforms/plot_transforms_illustrations.html).\n",
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"But let's try one out ourselves.\n",
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"* To practice your knowledge of PyTorch `Dataset`'s and `DataLoader`'s through PyTorch [datasets and dataloaders tutorial notebook](https://pytorch.org/tutorials/beginner/basics/data_tutorial.html).\n",
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"* Spend 10-minutes reading the [PyTorch `torchvision.transforms` documentation](https://pytorch.org/vision/stable/transforms.html).\n",
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" * You can see demos of transforms in action in the [illustrations of transforms tutorial](https://pytorch.org/vision/stable/auto_examples/plot_transforms.html#illustration-of-transforms). \n",
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" * You can see demos of transforms in action in the [illustrations of transforms tutorial](https://pytorch.org/vision/main/auto_examples/transforms/plot_transforms_illustrations.html). \n",
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"* Spend 10-minutes reading the PyTorch [`torchvision.datasets` documentation](https://pytorch.org/vision/stable/datasets.html).\n",
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" * What are some datasets that stand out to you?\n",
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" * How could you try building a model on these?\n",

docs/04_pytorch_custom_datasets.ipynb

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"\n",
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"Training a model on this *artificially* altered dataset hopefully results in a model that is capable of better *generalization* (the patterns it learns are more robust to future unseen examples).\n",
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"\n",
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"You can see many different examples of data augmentation performed on images using `torchvision.transforms` in PyTorch's [Illustration of Transforms example](https://pytorch.org/vision/stable/auto_examples/plot_transforms.html#illustration-of-transforms).\n",
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"You can see many different examples of data augmentation performed on images using `torchvision.transforms` in PyTorch's [Illustration of Transforms example](https://pytorch.org/vision/main/auto_examples/transforms/plot_transforms_illustrations.html).\n",
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"But let's try one out ourselves.\n",
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"\n",
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"* To practice your knowledge of PyTorch `Dataset`'s and `DataLoader`'s through PyTorch [datasets and dataloaders tutorial notebook](https://pytorch.org/tutorials/beginner/basics/data_tutorial.html).\n",
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"* Spend 10-minutes reading the [PyTorch `torchvision.transforms` documentation](https://pytorch.org/vision/stable/transforms.html).\n",
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" * You can see demos of transforms in action in the [illustrations of transforms tutorial](https://pytorch.org/vision/stable/auto_examples/plot_transforms.html#illustration-of-transforms). \n",
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" * You can see demos of transforms in action in the [illustrations of transforms tutorial](https://pytorch.org/vision/main/auto_examples/transforms/plot_transforms_illustrations.html). \n",
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"* Spend 10-minutes reading the PyTorch [`torchvision.datasets` documentation](https://pytorch.org/vision/stable/datasets.html).\n",
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" * What are some datasets that stand out to you?\n",
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" * How could you try building a model on these?\n",

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