Reinforcement Learning
Language: English
Published by O'reilly Media Dez 2020, 2020
- Softcover
- New
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
AbeBooks seller since January 11, 2012
Condition: New
£ 58.50
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Add to basketItem description from seller
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.…
Seller Inventory # 9781098114831
- Title
- Reinforcement Learning
- Author
- Phil Winder
- Publisher
- O'reilly Media Dez 2020
- Publication year
- 2020
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1098114833
- ISBN 13
- 9781098114831
- Item weight
- 710 grams
- Dimensions
- 233x183x25 mm
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
"Synopsis" may belong to another edition of this title.
About the Author
For the past 5 years, Phil has taught thousands of Engineers about Data Science in his range of Data Science training courses at conferences, in public, in private and on the online Safari learning platform. In these courses Phil focuses on the practicalities of using Data Science in industry on a wide range of topics from cleaning data all the way through to deep reinforcement learning.
"About the title" may belong to another edition of this title.
BuchWeltWeit Ludwig Meier e.K.
Bergisch Gladbach, Germany
AbeBooks seller since January 11, 2012
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