Key takeways on Variational Autoencoders and Variational Inference; includes a detailed notebook, and helpful resources if you would like to learn more.

Introduction to Backpropagation and hands on examples to demonstrate the effects of backpropagation in a neural network.

My notes on the MIT 18.06 Linear Algebra lectures by Gilbert Strang

Introduction to Gaussian processes and a simple code implementation.