Phil Winder Phd (19 results)

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  • Language: English

    Published by O'Reilly Media, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: World of Books Inc, Montgomery, IL, U.S.A.World of Books Inc

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    Paperback. Condition: Good. 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.…

  • Language: English

    Published by O'Reilly Media, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices

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  • Language: English

    Published by O'Reilly Media, US, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: Rarewaves USA, HEBRON, KY, U.S.A.Rarewaves USA

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    Paperback. Condition: 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. …

  • Language: English

    Published by O'Reilly Media, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices

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  • Language: English

    Published by O'Reilly Media, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK

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  • Language: English

    Published by O'Reilly Media, Sebastopol, 2020

    1098114833 / 9781098114831

    • Softcover

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    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.…

  • Language: English

    Published by O'Reilly Media, US, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA

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    Paperback. Condition: 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. …

  • Language: English

    Published by O'Reilly Media, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK

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  • Language: English

    Published by O?Reilly Media, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrelandKennys Bookshop and Art Galleries Ltd.

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  • Language: English

    Published by O'Reilly Media 2020-11-30, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: Chiron Media, Wallingford, United KingdomChiron Media

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  • Language: English

    Published by O'Reilly Media, 2020

    1098114833 / 9781098114831

    • Softcover

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  • Language: English

    Published by O'Reilly Media, Inc, USA, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE

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  • Language: English

    Published by O'Reilly Media 2020-11-30, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: Chiron Media, Wallingford, United KingdomChiron Media

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  • Language: English

    Published by O Reilly Media, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore

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    Condition: New. 2020. Paperback. . . . . . Books ship from the US and Ireland.

  • Language: English

    Published by O'Reilly Media, US, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: Rarewaves USA United, HEBRON, KY, U.S.A.Rarewaves USA United

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    Paperback. Condition: 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. …

  • Language: English

    Published by O'Reilly Media, 2020

    1098114833 / 9781098114831

    • Softcover

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    Condition: 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 practical book shows data science and AI professionals how to perform.

  • Language: English

    Published by O'Reilly Media, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: Turor Books, Hückelhoven, GermanyTuror Books

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  • Language: English

    Published by O'Reilly Media, Sebastopol, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    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.…

  • Language: English

    Published by O'Reilly Media, US, 2020

    1098114833 / 9781098114831

    • Softcover

    Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK

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    Paperback. Condition: 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. …