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Grokking Deep Reinforcement Learning by Miguel Morales

Description: Written for developers with some understanding of deep learning algorithms. Experience with reinforcement learning is not required.   Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field.   We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment.   • Foundational reinforcement learning concepts and methods • The most popular deep reinforcement learning agents solving high-dimensional environments • Cutting-edge agents that emulate human-like behavior and techniques for artificial general intelligence   Deep reinforcement learning is a form of machine learning in which AI agents learn optimal behavior on their own from raw sensory input. The system perceives the environment, interprets the results of its past decisions and uses this information to optimize its behavior for maximum long-term return.

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Location: East Hanover, New Jersey

End Time: 2024-12-02T10:58:41.000Z

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EAN: 9781617295454

UPC: 9781617295454

ISBN: 9781617295454

MPN: N/A

Book Title: Grokking Deep Reinforcement Learning by Miguel Mor

Number of Pages: 465 Pages

Language: English

Publication Name: Grokking Deep Reinforcement Learning

Publisher: Manning Publications Co. LLC

Item Height: 1 in

Publication Year: 2020

Subject: Programming / Algorithms, Intelligence (Ai) & Semantics

Type: Textbook

Item Weight: 28.9 Oz

Author: Miguel Morales

Subject Area: Computers

Item Length: 9.2 in

Item Width: 7.4 in

Format: Trade Paperback

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