Table of Contents
0:00 Recap
0:40 A simple example (more in the practicals)
3:44 Pytorch tensor: requires_grad field
6:44 Pytorch backward function
9:05 The chain rule on our example
16:00 Linear regression
18:00 Gradient descent with numpy...
27:30 ... with pytorch tensors
31:30 Using autograd
34:35 Using a neural network (linear layer)
39:50 Using a pytorch optimizer
44:00 algorithm: how automatic differentiation works
Automatic differentiation: a simple example static notebook, code (GitHub) in colab
notebook used in the video for the linear regression. If you want to open it in colab
Bonus: JAX implementation of the linear regression notebook in colab
backprop slide (used for the practical below)
practicals in colab Coding backprop.
To check your understanding of automatic differentiation, you can do the quizzes
Last modified: September 14, 2022. Website built with Franklin.jl and the Julia programming language. 
