Foundations of Deep Reinforcement Learning: Theory and Practice in Python (Addison-Wesley Data & Analytics Series)

Price: $62.99
(as of Dec 15,2024 19:45:19 UTC – Details)

ASIN ‏ : ‎ B07ZVYZC6F
Publisher ‏ : ‎ Addison-Wesley Professional; 1st edition (November 20, 2019)
Publication date ‏ : ‎ November 20, 2019
Language ‏ : ‎ English
File size ‏ : ‎ 30740 KB
Simultaneous device usage ‏ : ‎ Up to 5 simultaneous devices, per publisher limits
Text-to-Speech ‏ : ‎ Enabled
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Not Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 416 pages

Foundations of Deep Reinforcement Learning: Theory and Practice in Python (Addison-Wesley Data & Analytics Series)

Are you interested in diving deep into the world of reinforcement learning and its applications in Python? Look no further than this comprehensive guide that covers the theoretical foundations and practical implementation of deep reinforcement learning.

Written by experts in the field, this book provides a thorough introduction to the fundamentals of reinforcement learning, including Markov decision processes, value functions, policy gradients, and more. You’ll learn how to apply deep learning techniques to reinforcement learning tasks, using popular libraries such as TensorFlow and Keras.

With real-world examples and hands-on exercises, you’ll gain a solid understanding of the principles behind deep reinforcement learning and how to implement them in Python. Whether you’re a beginner or an experienced practitioner, this book is a valuable resource for anyone looking to enhance their skills in this exciting field.

Don’t miss out on this essential guide to deep reinforcement learning – get your copy today!
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