What is GAN?
Generative adversarial networks (GANs) are an exciting recent innovation in machine learning. It was first introduced by Ian Godfellow in his paper Generative Adversarial Networks.
GANs are generative models: after given some training data, they can create new data instances that look like your training data. For example, GANs can create images that look like photographs of human faces, even though the faces don’t belong to any real person.
For a great example of GAN you can visit https://www.thispersondoesnotexist.com/ which was created by Nvidia. It generates a high-quality image of a person who does not even exist.

I will use some of the images to create my Stardust Women.