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: pytorch-tutorial-assets.s3.amazonaws.com/youtube-s…

Download individual notebooks here:

1. Tensors - 04:45 to 07:50
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2. Autograd - 08:00 to 9:50

3. A simple model - 10:00 to 14:00
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4. Datasets - 14:00 to 17:10
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5. Training loop - 17:10 to 21:00
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