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This is arguably the most mind-blowing application in the book. CycleGAN performs unpaired image-to-image translation, turning a photo of a horse into a zebra, or a summer landscape into a winter one, without needing a dataset of matching pairs. gans in action pdf github
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Generative Adversarial Networks (GANs) represent one of the most significant breakthroughs in modern artificial intelligence. By pitting two neural networks against each other—a Generator and a Discriminator—GANs can synthesize hyper-realistic images, music, text, and synthetic data. Can’t copy the link right now