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Generative Adversarial Networks Cookbook

Josh Kalin

The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on.

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Generative Adversarial Networks Cookbook

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Generative Adversarial Networks Cookbook: Over 100 recipes to build generative models using Python, TensorFlow, and Keras

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Length: 261 pages

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