Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play by David Foster

English book to download Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play by David Foster


Download Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play PDF

  • Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play
  • David Foster
  • Page: 322
  • Format: pdf, ePub, mobi, fb2
  • ISBN: 9781492041948
  • Publisher: O'Reilly Media, Incorporated

Download Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play




English book to download Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play by David Foster

Generative modeling is one of the hottest topics in artificial intelligence. Recent advances in the field have shown how it’s possible to teach a machine to excel at human endeavors—such as drawing, composing music, and completing tasks—by generating an understanding of how its actions affect its environment. With this practical book, machine learning engineers and data scientists will learn how to recreate some of the most famous examples of generative deep learning models, such as variational autoencoders and generative adversarial networks (GANs). You’ll also learn how to apply the techniques to your own datasets. David Foster, cofounder of Applied Data Science, demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to the most cutting-edge algorithms in the field. Through tips and tricks, you’ll learn how to make your models learn more efficiently and become more creative. Get a fundamental overview of generative modeling Learn how to use the Keras and TensorFlow libraries for deep learning Discover how variational autoencoders (VAEs) work Get practical examples of generative adversarial networks (GANs) Understand how to build generative models that learn how to paint, write, and compose Apply generative models within a reinforcement learning setting to accomplish tasks

What Are Generative Adversarial Networks? - RSSUnify
Generative modeling is an unsupervised learning task in machine learning . are adversarial in the game theory sense, and are playing a zero-sum game. in turn teaching the generator to generate examples of that class in order to Creating Art. The ability to great new and artistic images, sketches, painting, and more. Generative Deep Learning: Teaching Machines to Paint, Write
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With this practical book, machine learning engineers and data scientists will learn how to Understand how to build generative models that learn how to paint, write, and compose Teaching Machines to Paint, Write, Compose and Play · 5. Learning Generative Adversarial Networks: Next-generation deep
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