How to Train StyleGAN2-ADA with Custom Datasets using TensorFlow and Google Colab

Generative Adversarial Networks (GANs) are one of the hottest topics in computer science in recent times. They are a clever way of training a generative model (unsupervised learning) by framing the problem as a supervised learning problem. The main idea is that two different models are trained simultaneously by an adversarial process. Generative adversarial networks are based on a game theoretic scenario in which the generator network must compete against an adversary. The generator network directly produces samples.