What this book covers

Chapter 1, Deep Learning Basics and Environment Setup, contains essential knowledge for building and training deep learning models, including GANs. In this chapter, you will also learn how to set up your deep learning Python and Keras environments for the upcoming projects. Finally, you will learn about the importance of using GPUs in deep learning and how to choose the platform that best suits you.

Chapter 2, Introduction to Generative Models, covers the basics of generative models, including GANs, variational autoencoders, autoregressive models and reversible flow models. You will learn about state-of-the-art applications that use GANs. You will learn the building blocks of GANs, along with their strengths and limitations. ...

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