GANS are a machine learning framework that uses two competing neural networks in order to estimate densities. It was introduced in 2014 by Goodfellow et al. and received much attention ever since.
Given a training set, the technique tries to create new data that looks as similar as possible to the training data. This course aims to give an introduction to this framework, give the mathematical intuition behind the idea and show some basic applications.