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maksim lapan deep reinforcement learning hands-on 2nd edition pdf PDF
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"Deep Reinforcement Learning Hands-On" by Maksim Lapan is a practical guide that delves into the methodologies and applications of deep reinforcement learning (DRL). This second edition has been thoroughly updated to reflect the latest advancements in the field. Lapan emphasizes a hands-on approach, targeting both newcomers and experienced practitioners who seek to enhance their understanding of DRL through real-world projects and coding examples.
The book's bibliographic information includes an ISBN of 978-1838985354. It was published by Packt Publishing in 2021. Maksim Lapan is not only the author but also a prominent figure in the fields of reinforcement learning and artificial intelligence, contributing extensive knowledge and practical insights through his works and research.
Readers will find that the text is structured to build foundational concepts in reinforcement learning before moving into complex architectures and applications. The content covers essential topics such as policy gradients, actor-critic methods, and deep Q-learning. Each chapter includes practical implementations using the Python programming language and popular libraries like PyTorch, providing readers with hands-on experience in developing their own DRL agents.
This book is a valuable resource for those interested in leveraging advanced machine learning techniques for real-world problems. With its practical exercises and up-to-date information, "Deep Reinforcement Learning Hands-On" serves as a comprehensive guide that empowers readers to effectively understand and apply deep reinforcement learning principles in various applications throughout technology and research.
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