Quick-tutorials-for-PyTorch

This is just a refresher on PyTorch before taking any deep learning project. These notebooks will be constantly updated and may overlap to some degree.

Notebooks

1. Introduction to tensors

   • Introduction to tensors
   • Basic operations
   • Broadcasting rules

2. Building Your First Neural Network

   • Basic structures
   • nn.Module, optimisers, In-built Loss functions
   • Notes on gradient calculation

3. Convolutions

   • Convolution as Linear Transformation
   • Strides and Dialations
   • Padding
   • Channels
   • ConvTranspose

4. Attention and Transformers (upcoming)