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Añadir al carritoPaperback. Condición: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less.
Librería: World of Books (was SecondSale), Montgomery, IL, Estados Unidos de America
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Librería: World of Books (was SecondSale), Montgomery, IL, Estados Unidos de America
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 41,60
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Idioma: Inglés
Publicado por O'Reilly Media 12/1/2020, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 45,39
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Añadir al carritoPaperback or Softback. Condición: New. Reinforcement Learning: Industrial Applications of Intelligent Agents. Book.
Librería: Phatpocket Limited, Waltham Abbey, HERTS, Reino Unido
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Añadir al carritoCondición: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
EUR 47,29
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Añadir al carritoPaperback. Condición: New. 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 learn by reinforcement and enable a machine to learn by itself.Author 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, focus on industrial applications, learn numerous algorithms, and benefit from dedicated chapters on deploying RL solutions to production. This is no cookbook; doesn't shy away from math and expects familiarity with ML.Learn what RL is and how the algorithms help solve problemsBecome grounded in RL fundamentals including Markov decision processes, dynamic programming, and temporal difference learningDive deep into a range of value and policy gradient methodsApply advanced RL solutions such as meta learning, hierarchical learning, multi-agent, and imitation learningUnderstand cutting-edge deep RL algorithms including Rainbow, PPO, TD3, SAC, and moreGet practical examples through the accompanying website.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 46,73
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Librería: GoldBooks, Denver, CO, Estados Unidos de America
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Idioma: Inglés
Publicado por O'Reilly Media, Sebastopol, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 57,70
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Añadir al carritoPaperback. Condición: 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.
EUR 59,06
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Añadir al carritoPaperback. Condición: New. 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 learn by reinforcement and enable a machine to learn by itself.Author 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, focus on industrial applications, learn numerous algorithms, and benefit from dedicated chapters on deploying RL solutions to production. This is no cookbook; doesn't shy away from math and expects familiarity with ML.Learn what RL is and how the algorithms help solve problemsBecome grounded in RL fundamentals including Markov decision processes, dynamic programming, and temporal difference learningDive deep into a range of value and policy gradient methodsApply advanced RL solutions such as meta learning, hierarchical learning, multi-agent, and imitation learningUnderstand cutting-edge deep RL algorithms including Rainbow, PPO, TD3, SAC, and moreGet practical examples through the accompanying website.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 47,73
Cantidad disponible: 10 disponibles
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 44,14
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 50,76
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Idioma: Inglés
Publicado por O'Reilly Media 2020-11-30, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Librería: Chiron Media, Wallingford, Reino Unido
EUR 47,15
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Añadir al carritoCondición: New. 2020. Paperback. . . . . .
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 51,02
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Idioma: Inglés
Publicado por O'Reilly Media 2020-11-30, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Librería: Chiron Media, Wallingford, Reino Unido
EUR 56,22
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Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
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Añadir al carritoCondición: New. 2020. Paperback. . . . . . Books ship from the US and Ireland.
Idioma: Inglés
Publicado por O'Reilly Media, Inc, USA, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 55,89
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
Idioma: Inglés
Publicado por Oreilly & Associates Inc, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Librería: Revaluation Books, Exeter, Reino Unido
EUR 67,54
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Añadir al carritoPaperback. Condición: Brand New. 381 pages. 9.00x7.00x0.75 inches. In Stock.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 71,25
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Librería: Basi6 International, Irving, TX, Estados Unidos de America
EUR 92,16
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Añadir al carritoCondición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Idioma: Inglés
Publicado por O'reilly Media Dez 2020, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 67,00
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -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 learn by reinforcement and enable a machine to learn by itself.Author 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, focus on industrial applications, learn numerous algorithms, and benefit from dedicated chapters on deploying RL solutions to production. This is no cookbook; 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 a range of value and policy gradient methods- Apply advanced RL solutions such as meta learning, hierarchical learning, multi-agent, and imitation learning- Understand cutting-edge deep RL algorithms including Rainbow, PPO, TD3, SAC, and more- Get practical examples through the accompanying website Englisch.
Idioma: Inglés
Publicado por O'reilly Media Dez 2020, 2020
ISBN 10: 1098114833 ISBN 13: 9781098114831
Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Alemania
EUR 67,00
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Neuware -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 learn by reinforcement and enable a machine to learn by itself.Author 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, focus on industrial applications, learn numerous algorithms, and benefit from dedicated chapters on deploying RL solutions to production. This is no cookbook; 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 a range of value and policy gradient methods- Apply advanced RL solutions such as meta learning, hierarchical learning, multi-agent, and imitation learning- Understand cutting-edge deep RL algorithms including Rainbow, PPO, TD3, SAC, and more- Get practical examples through the accompanying website Englisch.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 88,94
Cantidad disponible: 1 disponibles
Añadir al carritoCondición: New. 1st edition NO-PA16APR2015-KAP.
EUR 44,15
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