In this chapter, you will learn the basics about implementing and training Generative Adversarial Network (GAN) models for image synthesis. You will learn to implement a Generator and Discriminator a GAN. You will then learn to implement your loss function and use it to train your GAN framework. You will also learn to visualize the samples from your first GAN. We will focus on the well-known CIFAR-10 dataset with 60,000 32 by 32 colour images in 10 classes.
The following topics will be covered in this chapter:
- Imports
- Implementing the Generator and the Discriminator
- Auxiliary functions
- Training your GAN
