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