Da: WorldofBooks, Goring-By-Sea, WS, Regno Unito
EUR 4,77
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Aggiungi al carrelloPaperback. Condizione: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Da: ThriftBooks-Atlanta, AUSTELL, GA, U.S.A.
EUR 23,82
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Aggiungi al carrelloPaperback. Condizione: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less 2.83.
Da: California Books, Miami, FL, U.S.A.
EUR 38,62
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Editore: Packt Publishing 6/28/2018, 2018
ISBN 10: 1788836529 ISBN 13: 9781788836524
Lingua: Inglese
Da: BargainBookStores, Grand Rapids, MI, U.S.A.
EUR 38,16
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Aggiungi al carrelloPaperback or Softback. Condizione: New. Hands-On Reinforcement Learning with Python: Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow 1.21. Book.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 39,49
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Da: California Books, Miami, FL, U.S.A.
EUR 47,40
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Da: Best Price, Torrance, CA, U.S.A.
EUR 30,60
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Da: Chiron Media, Wallingford, Regno Unito
EUR 35,78
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Aggiungi al carrelloPF. Condizione: New.
Editore: Packt Publishing 9/30/2020, 2020
ISBN 10: 1839210680 ISBN 13: 9781839210686
Lingua: Inglese
Da: BargainBookStores, Grand Rapids, MI, U.S.A.
EUR 47,85
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Aggiungi al carrelloPaperback or Softback. Condizione: New. Deep Reinforcement Learning with Python - Second Edition 2.83. Book.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 49,40
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EUR 43,88
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Da: Best Price, Torrance, CA, U.S.A.
EUR 38,33
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EUR 49,15
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 49,15
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EUR 55,44
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Aggiungi al carrelloKartoniert / Broschiert. Condizione: New. Deep Reinforcement Learning with Python - Second Edition will help you learn reinforcement learning algorithms, techniques and architectures - including deep reinforcement learning - from scratch. This new edition is an extensive update of the original, ref.
EUR 46,19
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Aggiungi al carrelloPF. Condizione: New.
Editore: Packt Publishing Limited, GB, 2020
ISBN 10: 1839210680 ISBN 13: 9781839210686
Lingua: Inglese
Da: Rarewaves.com UK, London, Regno Unito
EUR 69,02
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Aggiungi al carrelloPaperback. Condizione: New. An example-rich guide for beginners to start their reinforcement and deep reinforcement learning journey with state-of-the-art distinct algorithmsKey FeaturesCovers a vast spectrum of basic-to-advanced RL algorithms with mathematical explanations of each algorithmLearn how to implement algorithms with code by following examples with line-by-line explanationsExplore the latest RL methodologies such as DDPG, PPO, and the use of expert demonstrationsBook DescriptionWith significant enhancements in the quality and quantity of algorithms in recent years, this second edition of Hands-On Reinforcement Learning with Python has been revamped into an example-rich guide to learning state-of-the-art reinforcement learning (RL) and deep RL algorithms with TensorFlow 2 and the OpenAI Gym toolkit. In addition to exploring RL basics and foundational concepts such as Bellman equation, Markov decision processes, and dynamic programming algorithms, this second edition dives deep into the full spectrum of value-based, policy-based, and actor-critic RL methods. It explores state-of-the-art algorithms such as DQN, TRPO, PPO and ACKTR, DDPG, TD3, and SAC in depth, demystifying the underlying math and demonstrating implementations through simple code examples. The book has several new chapters dedicated to new RL techniques, including distributional RL, imitation learning, inverse RL, and meta RL. You will learn to leverage stable baselines, an improvement of OpenAI's baseline library, to effortlessly implement popular RL algorithms. The book concludes with an overview of promising approaches such as meta-learning and imagination augmented agents in research. By the end, you will become skilled in effectively employing RL and deep RL in your real-world projects.What you will learnUnderstand core RL concepts including the methodologies, math, and codeTrain an agent to solve Blackjack, FrozenLake, and many other problems using OpenAI GymTrain an agent to play Ms Pac-Man using a Deep Q NetworkLearn policy-based, value-based, and actor-critic methodsMaster the math behind DDPG, TD3, TRPO, PPO, and many othersExplore new avenues such as the distributional RL, meta RL, and inverse RLUse Stable Baselines to train an agent to walk and play Atari gamesWho this book is forIf you're a machine learning developer with little or no experience with neural networks interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you.Basic familiarity with linear algebra, calculus, and the Python programming language is required. Some experience with TensorFlow would be a plus.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 53,87
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Editore: Packt Publishing Limited, GB, 2020
ISBN 10: 1839210680 ISBN 13: 9781839210686
Lingua: Inglese
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 74,44
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Aggiungi al carrelloPaperback. Condizione: New. An example-rich guide for beginners to start their reinforcement and deep reinforcement learning journey with state-of-the-art distinct algorithmsKey FeaturesCovers a vast spectrum of basic-to-advanced RL algorithms with mathematical explanations of each algorithmLearn how to implement algorithms with code by following examples with line-by-line explanationsExplore the latest RL methodologies such as DDPG, PPO, and the use of expert demonstrationsBook DescriptionWith significant enhancements in the quality and quantity of algorithms in recent years, this second edition of Hands-On Reinforcement Learning with Python has been revamped into an example-rich guide to learning state-of-the-art reinforcement learning (RL) and deep RL algorithms with TensorFlow 2 and the OpenAI Gym toolkit. In addition to exploring RL basics and foundational concepts such as Bellman equation, Markov decision processes, and dynamic programming algorithms, this second edition dives deep into the full spectrum of value-based, policy-based, and actor-critic RL methods. It explores state-of-the-art algorithms such as DQN, TRPO, PPO and ACKTR, DDPG, TD3, and SAC in depth, demystifying the underlying math and demonstrating implementations through simple code examples. The book has several new chapters dedicated to new RL techniques, including distributional RL, imitation learning, inverse RL, and meta RL. You will learn to leverage stable baselines, an improvement of OpenAI's baseline library, to effortlessly implement popular RL algorithms. The book concludes with an overview of promising approaches such as meta-learning and imagination augmented agents in research. By the end, you will become skilled in effectively employing RL and deep RL in your real-world projects.What you will learnUnderstand core RL concepts including the methodologies, math, and codeTrain an agent to solve Blackjack, FrozenLake, and many other problems using OpenAI GymTrain an agent to play Ms Pac-Man using a Deep Q NetworkLearn policy-based, value-based, and actor-critic methodsMaster the math behind DDPG, TD3, TRPO, PPO, and many othersExplore new avenues such as the distributional RL, meta RL, and inverse RLUse Stable Baselines to train an agent to walk and play Atari gamesWho this book is forIf you're a machine learning developer with little or no experience with neural networks interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you.Basic familiarity with linear algebra, calculus, and the Python programming language is required. Some experience with TensorFlow would be a plus.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 33,81
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Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 73,88
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Aggiungi al carrelloPaperback. Condizione: New. New. book.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 76,27
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Aggiungi al carrelloPaperback. Condizione: New. New. book.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 42,95
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Da: HPB-Red, Dallas, TX, U.S.A.
EUR 20,32
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Aggiungi al carrellopaperback. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
ISBN 10: 7111612884 ISBN 13: 9787111612889
Da: liu xing, Nanjing, JS, Cina
EUR 92,39
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Aggiungi al carrellopaperback. Condizione: New. Paperback. Pub Date: 2019-01-01 Pages: 203 Language: Chinese Publisher: Mechanical Industry Press Reinforcement learning is an important machine learning method. and has many applications in the fields of agent and analysis and prediction. Python Intensive Learning Practice: Applying OpenAI Gym and TensorFlow to Master Reinforcement Learning and.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
EUR 44,30
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 40,15
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Aggiungi al carrelloPAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 43,20
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Aggiungi al carrelloPaperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 526.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 50,11
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Aggiungi al carrelloPAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
EUR 59,88
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.