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

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


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ISBN: 9781492041948 | 322 pages | 9 Mb

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

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Exciting news - our new book, 'Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play' is now available on early release! Foster David. Generative Deep Learning: Teaching Machines to
Foster David. Generative Deep Learning: Teaching Machines to Paint, Write, Compose and Play. Файл формата pdf; размером 10,45 МБ. Generative Deep Learning - Browns Books for Students
Generative Deep Learning : Teaching Machines to Paint, Write, Compose and Play Generative modeling is one of the hottest topics in artificial intelligence. What Are GANs? | Manning
Generative Adversarial Networks and their Potential Teaching Computers Creativity. One of the most exciting chapters in machine learning began in one of recognition[1] and defeating the world's top human player in a game of Go. set—for example, if we want a GAN to paint like Leonardo da Vinci,  David Foster: Books - Amazon.co.uk
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Simplify next-generation deep learning by implementing powerful generative Generative Adversarial Networks Cookbook and millions of other books are .. and learning new techniques in robotics and machine learning (like writing . Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play. Strengthening Deep Neural Networks: Making AI Less Susceptible
As Deep Neural Networks (DNNs) become increasingly common in Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play. Deep generative neural networks for novelty generation - Theses.fr
8.2 Machine learning and novelty generation: the innovation engine, in situations where the task is hard to write down formally and thus an explicit al- to a painting, or play music by mimicking sounds of acoustic instruments. The because the decoder is constrained to compose the stroke features in such a way. Coming Soon - Intelligence & Semantics / AI & Machine Learning
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Notes on Artificial Intelligence, Machine Learning and Deep AI composers/ artists, hand writing recognition, Email marketing . They learn first by copying human players and then play one They are Convolutional Neural Networks, Recurrent Neural Networks and Generative Adversarial Networks. Computer Vision & Pattern Recognition: Books - Amazon.com
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Название: Generative Deep Learning: Teaching Machines to Paint, Write, Compose and Play Автор: David FosterИздательство: O'Reilly