ABSTRACT
This chapter is dedicated to Generative Adversarial Networks (GAN). The first section covers the basic details about a generative model and GANs. Generative models are part of a statistical classification approach. This model has been widely used in prediction of a next sentence or a word in a sequence, where the probability of the adjacent word/s matters a lot. Next, it covers the different types of GAN, which include Deep Convolution GANs, stack GAN, cycle GAN, and so forth. Then it covers the application areas of GAN. This includes speech modification, image modification, photo to emoji, and so forth. Toward the end, the implementation part is touched upon. Finally, the chapter summarizes the key points and has a quiz.
