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Paperback. Condition: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.
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Reinforcement Learning: Indust
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Seller rating 5 out of 5 stars
Condition: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.
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Reinforcement Learning: Indust
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
Seller rating 5 out of 5 stars
Condition: Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.
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Paperback. Condition: new. New Copy. Customer Service Guaranteed.
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Reinforcement Learning (Paperback)
Language: English
Published by O'Reilly Media, Sebastopol, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Paperback. Condition: new. Paperback. Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This exciting development avoids constraints found in traditional machine learning (ML) algorithms. This practical book shows data science and AI professionals how to perform the reinforcement process that allows a machine to learn by itself.Author Dr. Phil Winder of Winder Research covers everything from basic building blocks to state-of-the-art practices. You'll explore the current state of RL, focusing on industrial applications, and learn numerous algorithms, frameworks, and environments. This is no cookbook-it doesn't shy away from math and expects familiarity with ML.Learn what RL is and how the algorithms help solve problems Become grounded in RL fundamentals including Markov decision processes, dynamic programming, and temporal difference learning Dive deep into value methods and policy gradient methods Apply advanced RL implementations such as meta learning, hierarchical learning, evolutionary algorithms, and imitation learning Understand cutting-edge deep RL algorithms including Rainbow, PPO, TD3, SAC, and more Get practical examples through the accompanying Git repository" Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This practical book shows data science and AI professionals how to perform the reinforcement process that allows a machine to learn by itself. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Reinforcement Learning: Industrial Applications of Intelligent Agents
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Condition: New. 1st edition NO-PA16APR2015-KAP.
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Reinforcement Learning (Paperback)
Language: English
Published by O'Reilly Media, Sebastopol, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Paperback. Condition: new. Paperback. Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This exciting development avoids constraints found in traditional machine learning (ML) algorithms. This practical book shows data science and AI professionals how to perform the reinforcement process that allows a machine to learn by itself.Author Dr. Phil Winder of Winder Research covers everything from basic building blocks to state-of-the-art practices. You'll explore the current state of RL, focusing on industrial applications, and learn numerous algorithms, frameworks, and environments. This is no cookbook-it doesn't shy away from math and expects familiarity with ML.Learn what RL is and how the algorithms help solve problems Become grounded in RL fundamentals including Markov decision processes, dynamic programming, and temporal difference learning Dive deep into value methods and policy gradient methods Apply advanced RL implementations such as meta learning, hierarchical learning, evolutionary algorithms, and imitation learning Understand cutting-edge deep RL algorithms including Rainbow, PPO, TD3, SAC, and more Get practical examples through the accompanying Git repository" Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This practical book shows data science and AI professionals how to perform the reinforcement process that allows a machine to learn by itself. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
