7. Generative Adversarial Networks
Introduction
In this chapter, you will embark on another interesting topic within the deep learning domain: Generative Adversarial Networks (GANs). You will get introduced to GANs and their basic components, along with some of their use cases. This chapter will give you hands-on experience of creating a GAN to generate a data distribution produced by a sine function. You will also be introduced to deep convolutional GANs and will perform an exercise to generate an MNIST data distribution. By the end of this chapter, you will have tested your understanding of GANs by generating the MNIST fashion dataset.
Introduction
The power of creativity was always the exclusive domain of the human mind. This was one ...
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