Automatic feature engineering using Generative Adversarial Networks

We will explore the use of Generative Adversarial Networks for automatic feature engineering. The idea is to automatically learn a set of features from, potentially noisy, raw data that can be useful in supervised learning tasks such as in computer vision.

Python environment

pip3 install -r requirements.txt