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Deep Reinforcement Learning Fundamentals (36 results)
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Deep Reinforcement Learning for Multi-Agent Systems: From Fundamentals to Advanced Cooperative Algorithms
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Paperback or Softback. Condition: New. Python AI Programming: Navigating fundamentals of ML, deep learning, NLP, and reinforcement learning in practice. Book.
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Deep Reinforcement Learning for Multi-Agent Systems: From Fundamentals to Advanced Cooperative Algorithms
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Learn Unity ML-Agents - Fundamentals of Unity Machine Learning: Incorporate new powerful ML algorithms such as Deep Reinforcement Learning for games
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Learn Unity ML-Agents - Fundamentals of Unity Machine Learning: Incorporate new powerful ML algorithms such as Deep Reinforcement Learning for games
Language: English
Published by Packt Publishing 2018-06-30, 2018
ISBN 10: 1789138132 ISBN 13: 9781789138139
£ 28.95
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Python AI Programming: Navigating fundamentals of ML, deep learning, NLP, and reinforcement learning in practice
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Python AI Programming: Navigating fundamentals of ML, deep learning, NLP, and reinforcement learning in practice
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Python AI Programming: Navigating fundamentals of ML, deep learning, NLP, and reinforcement learning in practice
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Taschenbuch. Condition: Neu. Deep Reinforcement Learning | Fundamentals, Research and Applications | Hao Dong (u. a.) | Taschenbuch | xxvii | Englisch | 2021 | Springer | EAN 9789811540974 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Condition: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. It has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine, and famously contributed to the success of AlphaGo. Furthermore, it opens up numerous new applications in domains such as healthcare, robotics, smart grids and finance.Divided into three main parts, this book provides a comprehensive and self-contained introduction to DRL. The first part introduces the foundations of deep learning, reinforcement learning (RL) and widely used deep RL methods and discusses their implementation. The second part covers selected DRL research topics, which are useful for those wanting to specialize in DRL research. To help readers gain a deep understanding of DRL and quickly apply the techniques in practice, the third part presents mass applications, such as the intelligent transportation system and learning to run, with detailedexplanations.The book is intended for computer science students, both undergraduate and postgraduate, who would like to learn DRL from scratch, practice its implementation, and explore the research topics. It also appeals to engineers and practitioners who do not have strong machine learning background, but want to quickly understand how DRL works and use the techniques in their applications.
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Deep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. It has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine, and famously contributed to the success of AlphaGo. Furthermore, it opens up numerous new applications in domains such as healthcare, robotics, smart grids and finance.Divided into three main parts, this book provides a comprehensive and self-contained introduction to DRL. The first part introduces the foundations of deep learning, reinforcement learning (RL) and widely used deep RL methods and discusses their implementation. The second part covers selected DRL research topics, which are useful for those wanting to specialize in DRL research. To help readers gain a deep understanding of DRL and quickly apply the techniques in practice, the third part presents mass applications, such as the intelligent transportation system and learning to run, with detailedexplanations.The book is intended for computer science students, both undergraduate and postgraduate, who would like to learn DRL from scratch, practice its implementation, and explore the research topics. It also appeals to engineers and practitioners who do not have strong machine learning background, but want to quickly understand how DRL works and use the techniques in their applications.
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Hardcover. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Deep Reinforcement Learning: Fundamentals. Research and Application (produced by the blog post)(Chinese Edition)
Language: Chinese
Published by Electronic Industry Press, 2021
ISBN 10: 7121411881 ISBN 13: 9787121411885
paperback. Condition: New. Paperback. Pub Date: 2021-06-01 Pages: 520 Language: Chinese Publisher: Electronic Industry Press Deep reinforcement learning combines the advantages of deep learning and reinforcement learning algorithms to solve complex decision-making tasks.?Thanks to the successful cases of DeepMind AlphaGo and OpenAI Five. deep reinforcement learning has received a lot of attention. and related technologies are widely used in different fields.?The book is divided into three parts. covering the entire con.
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Learn Unity ML-Agents - Fundamentals of Unity Machine Learning: Incorporate new powerful ML algorithms such as Deep Reinforcement Learning for games
Language: English
Published by Packt Publishing Limited, 2018
ISBN 10: 1789138132 ISBN 13: 9781789138139
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
£ 36.61
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Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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Taschenbuch. Condition: Neu. Python AI Programming | Navigating fundamentals of ML, deep learning, NLP, and reinforcement learning in practice | Patrick J | Taschenbuch | Englisch | 2024 | GitforGits | EAN 9788119177639 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book aspires young graduates and programmers to become AI engineers and enter the world of artificial intelligence by combining powerful Python programming with artificial intelligence. Beginning with the fundamentals of Python programming, the book gradually progresses to machine learning, where readers learn to implement Python in developing predictive models.The book provides a clear and accessible explanation of machine learning, incorporating practical examples and exercises that strengthen understanding. We go deep into deep learning, another vital component of AI. Readers gain a thorough understanding of how Python's frameworks and libraries can be used to create sophisticated neural networks and algorithms, which are required for tasks such as image and speech recognition. Natural Language Processing is also covered in the book, with fundamental concepts and techniques for interpreting and generating human-like language covered.The book's focus on computer vision and reinforcement learning is distinctive, presenting these cutting-edge AI fields in an approachable manner. Readers will learn how to use Python's intuitive programming paradigm to create systems that interpret visual data and make intelligent decisions based on environmental interactions. The book focuses on ethical AI development and responsible programming, emphasizing the importance of developing AI that is fair, transparent, and accountable.Each chapter is designed to improve learning by including practical examples, case studies, and exercises that provide hands-on experience. This book is an excellent starting point for anyone interested in becoming an AI engineer, providing the necessary foundational knowledge and skills to delve into the fascinating world of artificial intelligence.Key LearningsExplore Python basics and AI integration for real-world application and career advancement.Experience the power of Python in AI with practical machine learning techniques.Practice Python's deep learning tools for innovative AI solution development.Dive into NLP with Python to revolutionize data interpretation and communication strategies.Simple yet practical understanding of reinforcement learning for strategic AI decision making.Uncover ethical AI development and frameworks, and concepts of responsible and trustworthy AI.Harness Python's capabilities for creating AI applications with a focus on fairness and bias.Table of ContentIntroduction to Artificial IntelligencePython for AIData as Fuel for AIMachine Learning FoundationEssentials of Deep LearningNLP and Computer VisionHands-on Reinforcement LearningEthics to AI.
