Notes from Week 2 : Deep Unsupervised Learning, UC Berkeley

This post discusses GANs, providing an analysis of the learning paradigm with discussions on objective functions and optimization. I have included a link to a notebook GAN implementation on the MNIST fashion dataset with explanations at the end.

This post serves to introduce and explore the math powering Variational AutoEncoders. A link for the notebook implementation of the discussed concepts in TensorFlow along with explanations has been inserted at the end. I intend for this to be the first in a series of posts on generative models