May 2019
Intermediate to advanced
272 pages
7h 19m
English
Content preview from Hands-On Generative Adversarial Networks with Keras
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Summary
In this chapter, we learned about the Progressive Growing of GANs architecture and how to implement it. We learned how to increase variation by using minibatch standard deviation, along with how to normalize the generator and discriminator for training stability.
In the next chapter, we will learn about the generation of discrete sequences using GANs.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.