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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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Language: English
Published by O'Reilly Media 12/1/2020, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.
Paperback or Softback. Condition: New. Reinforcement Learning: Industrial Applications of Intelligent Agents. Book.
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Language: English
Published by O'Reilly Media, Sebastopol, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
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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Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Seller: Majestic Books, Hounslow, United Kingdom
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Language: English
Published by Oreilly & Associates Inc, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Seller: Revaluation Books, Exeter, United Kingdom
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Add to basketPaperback. Condition: Brand New. 381 pages. 9.00x7.00x0.75 inches. In Stock.
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Seller: Books Puddle, New York, NY, U.S.A.
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Language: English
Published by O'Reilly Media, Sebastopol, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Seller: AussieBookSeller, Truganina, VIC, Australia
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.
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Language: English
Published by Oreilly & Associates Inc, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Seller: Revaluation Books, Exeter, United Kingdom
US$ 69.50
Quantity: 2 available
Add to basketPaperback. Condition: Brand New. 381 pages. 9.00x7.00x0.75 inches. In Stock. This item is printed on demand.