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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 endeavours 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.
Build practical Gan examples from scratch, including cyclegan for style transfer and musegan for music generation
Create recurrent generative models for text generation and learn how to improve the models using attention
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|Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play||Paperback||English|
|Generative Deep Learning||Paperback||English|
|Reading with God: Lectio Divina||Paperback||English|
|Reading Style||Time To Finish The Book|
|2019-08-23 22:02:56 +0530|
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