In this chapter, we have seen how the GAN model truly displays the power of CNN. We learned how to train our own generative model and saw a practical example of GAN that can generate photos from paintings and turn horses into zebras.

We understood how GAN differs from other discriminative models and learned why generative models are preferred.

In the next chapter, we will learn about deep learning software comparison from scratch.