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: Download individual notebooks here: 1. Tensors - 04:45 to 07:50 +-+PyTorch+ 2. Autograd - 08:00 to 9:50 3. A simple model - 10:00 to 14:00 +-+A+Simple+PyTorch+ 4. Datasets - 14:00 to 17:10 +-+Dataset+and+ 5. Training loop - 17:10 to 21:00 +-+A+Simple+PyTorch+Training+