Exploring Reinforcement Learning Strategies - ISMAIL, SAFAD;SATHYA NARAYAN, P
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Reinforcement learning is a type of machine learning where an agent interacts with its environment, learning through trial and error to maximize rewards.The aim of this book is to serve all those to intend to learn Reinforcement Learning especially for Seventh Semester ( Honours) KTU students. From this book, you will learn the basics of Reinforcement Learning and Various Statistical Concept in an efficient manner.This book is also covering the syllabus of M-Tech ,BCA, MCA, AMIE, B.Tech of various Universities and other capable courses. This book has been divided in to five modules based on…mehr

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Produktbeschreibung
Reinforcement learning is a type of machine learning where an agent interacts with its environment, learning through trial and error to maximize rewards.The aim of this book is to serve all those to intend to learn Reinforcement Learning especially for Seventh Semester ( Honours) KTU students. From this book, you will learn the basics of Reinforcement Learning and Various Statistical Concept in an efficient manner.This book is also covering the syllabus of M-Tech ,BCA, MCA, AMIE, B.Tech of various Universities and other capable courses. This book has been divided in to five modules based on KTU syllabus, each of which contains the concerned text and examples. Each modules endswith a set of exercises and previous year KTU questions. Answer to the selected questions are given at the end of each modules. The use of very simple illustrations to explain the difficult concepts makes this book reader friendly.
Autorenporträt
Safad Ismail holds a Master's degree in Computer Science and Engineering and a Bachelor of Laws (LLB). He currently serves as an Assistant Professor in the Department of Computer Science and Engineering at Saintgits Engineering College.A prolific researcher,Ismail has published over a dozen of  academic  papers and books in reputed journals.