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Generative Deep Learning Teaching Machines To Paint Write Compose And Play David Foster

  • SKU: BELL-49851050
Generative Deep Learning Teaching Machines To Paint Write Compose And Play David Foster
$ 31.00 $ 45.00 (-31%)

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Generative Deep Learning Teaching Machines To Paint Write Compose And Play David Foster instant download after payment.

Publisher: "O'Reilly Media, Inc."
File Extension: MOBI
File size: 38.67 MB
Author: David Foster
ISBN: 9781492041917, 58ee1c26-5199-4150-b162-2b8bf02fd08d, 9781492041917, 58EE1C26-5199-4150-B162-2B8BF02FD08D
Language: English
Year: 2019

Product desciption

Generative Deep Learning Teaching Machines To Paint Write Compose And Play David Foster by David Foster 9781492041917, 58ee1c26-5199-4150-b162-2b8bf02fd08d, 9781492041917, 58EE1C26-5199-4150-B162-2B8BF02FD08D instant download after payment.

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 photosBuild practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generationCreate recurrent generative models for text generation and learn how to improve the models using attentionUnderstand how generative models can help agents to accomplish tasks within a reinforcement learning settingExplore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN

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