Building a simple Generative Adversarial Network (GAN) using TensorFlow

Introduction

Generative Adversarial Networks or GANs are one of the most active areas in deep learning research and development due to their incredible ability to generate synthetic results. In this blog, we will build out the basic intuition of GANs through a concrete example. This post is broken down in following way:

• Basic idea and intuition behind workings of Generative Adversarial Networks
• Implementing a GAN-based model that generates data from a simple distribution
• Visualizing and analyzing different aspects of the GAN to better understand what’s happening behind the scenes.

The code for this blog can be found here.