GANs in Action: Deep Learning with Generative Adversarial Networks
Generative Adversarial Networks (GANs) are an incredible AI technology capable of creating images, sound, and videos that are indistinguishable from the "real thing." By pitting two neural networks against each other -- one to generate fakes and one to spot them -- GANs rapidly learn to produce photo-realistic faces and other media objects. With the potential to produce stunningly realistic animations or shocking deepfakes, GANs are a huge step forward in deep learning systems.
This book teaches you how to build and train your own Generative Adversarial Networks, one of the most important innovations in deep learning. You'll learn how to start building your own simple adversarial system as you explore the foundation of GAN architecture: the generator and discriminator networks.
| Pages : | 240 pages |
| Size : | HTML |
| File type : | |
| Downloads: | 24 |
| Created: | 2020-08-29 |
| License: | Free to read online (entire book) by the publisher. |
| Author(s): | Jakub Langr and Vladimir Bok |
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