May 2019
Intermediate to advanced
272 pages
7h 19m
English
Content preview from Hands-On Generative Adversarial Networks with Keras
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Implementations
We learned to implement several models in different domains. In the image domain, we implemented pix2pix, pix2pixHD, and Progressive Growing of GANs; in the text domain, we implemented natural language generation with GANs; and in the audio domain, we implemented sound enhancement GANs.
Combining the image and text domains, we implemented text-to-image synthesis. Finally, we also looked into identifying GAN samples.
We have done a lot but there still is a lot that is left to do. GANs are an ongoing field of research and there are many questions that still need to be answered! So, let's look at them.
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.