A Beginners Guide and Tutorial for GANs

Via O'Reilly, supported by Google. A Simplified Tutorial.  Instructive, not the idea of a network generating content.

Beginner's guide to GANs

This tutorial will show you how to build a generative adversarial network that learns to generate handwritten digits—essentially you'll teach a neural network how to write. You can download and modify the code from this tutorial on GitHub.

Generative Adversarial Networks for Beginners
Build a neural network that learns to generate handwritten digits.

By Jon Bruner,  Adit Deshpande  

Practical Generative Adversarial Networks for Beginners

You can download and modify the code from this tutorial on GitHub ... 

According to Yann LeCun, “adversarial training is the coolest thing since sliced bread.” Sliced bread certainly never created this much excitement within the deep learning community. Generative adversarial networks—or GANs, for short—have dramatically sharpened the possibility of AI-generated content, and have drawn active research efforts since they were first described by Ian Goodfellow et al. in 2014.

GANs are neural networks that learn to create synthetic data similar to some known input data. For instance, researchers have generated convincing images from photographs of everything from bedrooms to album covers, and they display a remarkable ability to reflect higher-order semantic logic.   .... "