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

• 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

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Ebooks download for free for mobile Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play (English Edition)

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

Generative Deep Learning: Teaching Machines to Paint, Write
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Amazon配送商品ならGenerative Deep Learning: Teaching Machines to Paint, Write, Compose and Playが通常配送無料。更にAmazonならポイント還元本が多数。 How to Generate Music using a LSTM Neural Network in Keras
A recurrent neural network is a class of artificial neural networks that make use of It allows us to teach the fundamentals of music theory, generate music then followed by a rest period where no note is played for a short while. .. we use the write function in the Music21 toolkit to write the stream to a file.

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