Generative Deep Learning - David Foster

kolman · 09.11.2020, 09:58

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Generative modeling is one of the hottest topics in AI. It's now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models.
Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you'll understand how to make your models learn more efficiently and become more creative.[*]Discover how variational autoencoders can change facial expressions in photos[*]Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation[*]Create...

Category:Pattern Recognition, Machine Theory, Computer Vision & Pattern Recognition

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