Introduction to PyTorch

In the first video of this series, we give a broad overview of the parts of the PyTorch toolchain, including: Tensors, automatic gradient computation, model building basics, data loading abstractions, model training, and deployment for inference. This video is meant as a survey, with each topic being covered in more depth in subsequent videos.

Download all notebooks here: https://pytorch-tutorial-assets.s3.amazonaws.com/youtube-series/video1.zip

Download individual notebooks here:

1. Tensors – 04:45 to 07:50
https://pytorch-tutorial-assets.s3.amazonaws.com/youtube-series/video1/1+-+PyTorch+Tensors.ipynb

2. Autograd – 08:00 to 9:50

3. A simple model – 10:00 to 14:00
https://pytorch-tutorial-assets.s3.amazonaws.com/youtube-series/video1/2+-+A+Simple+PyTorch+model.ipynb

4. Datasets – 14:00 to 17:10
https://pytorch-tutorial-assets.s3.amazonaws.com/youtube-series/video1/3+-+Dataset+and+DataLoader.ipynb

5. Training loop – 17:10 to 21:00
https://pytorch-tutorial-assets.s3.amazonaws.com/youtube-series/video1/4+-+A+Simple+PyTorch+Training+Loop.ipynb

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