Hands-On Deep Learning Algorithms with Python

How do they learn though?

So far, we just studied the role of the generator and discriminator, but how do they learn exactly? How does the generator learn to generate new realistic images and how does the discriminator learn to discriminate between images correctly?

We know that the goal of the generator is to generate an image in such a way as to fool the discriminator into believing that the generated image is from a real distribution.

In the first iteration, the generator generates a noisy image. When we feed this image to the discriminator, discriminator can easily detect that the image is from a generator distribution. The generator takes this as a loss and tries to improve itself, as its goal is to fool the discriminator. That is, if ...