Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play
(By David Foster)
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| Author | David Foster |
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 deep learning
Learn about libraries such as Keras and TensorFlow
Discover how variational autoencoders work
Get practical examples of generative adversarial networks (GANs)
Understand how autoregressive generative models function
Apply generative models within a reinforcement learning setting to accomplish tasks”
