The primary aim of this book is to provide students, educators, researchers, and aspiring professionals with a strong foundation in machine learning concepts, algorithms, and practical implementation techniques. It is designed to help learners understand how intelligent systems learn from data, recognise patterns, make predictions, and support decision-making in real-world applications. This book aims to:¿ Introduce the fundamentals and types of machine learning.¿ Explain core supervised, unsupervised, and reinforcement learning techniques. ¿ Develop analytical thinking for selecting suitable algorithms for different problems. ¿ Provide practical knowledge using Python and popular ML libraries. ¿ Bridge theoretical understanding with hands-on experimentation. ¿ Prepare learners for advanced studies, research, and industry applications in AI and data science.
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Dr. D. Magdalene Delighta Angeline is an associate professor at Joginpally B.R. Engineering College. Dr. I. Samuel Peter James is an associate professor at Shadan Women's College of Engineering. Dr. T. Prabakaran is a professor at Joginpally B.R. Engineering College. The authors' research areas are Data Mining and Machine Learning.
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Paperback. Zustand: new. Paperback. The primary aim of this book is to provide students, educators, researchers, and aspiring professionals with a strong foundation in machine learning concepts, algorithms, and practical implementation techniques. It is designed to help learners understand how intelligent systems learn from data, recognise patterns, make predictions, and support decision-making in real-world applications. This book aims to: - Introduce the fundamentals and types of machine learning.- Explain core supervised, unsupervised, and reinforcement learning techniques. - Develop analytical thinking for selecting suitable algorithms for different problems. - Provide practical knowledge using Python and popular ML libraries. - Bridge theoretical understanding with hands-on experimentation. - Prepare learners for advanced studies, research, and industry applications in AI and data science. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9786209928000
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The primary aim of this book is to provide students, educators, researchers, and aspiring professionals with a strong foundation in machine learning concepts, algorithms, and practical implementation techniques. It is designed to help learners understand how intelligent systems learn from data, recognise patterns, make predictions, and support decision-making in real-world applications. This book aims to:- Introduce the fundamentals and types of machine learning.- Explain core supervised, unsupervised, and reinforcement learning techniques. - Develop analytical thinking for selecting suitable algorithms for different problems. - Provide practical knowledge using Python and popular ML libraries. - Bridge theoretical understanding with hands-on experimentation. - Prepare learners for advanced studies, research, and industry applications in AI and data science. 264 pp. Englisch. Bestandsnummer des Verkäufers 9786209928000
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Taschenbuch. Zustand: Neu. Machine Learning | Concepts and Techniques | D. Magdalene Delighta Angeline (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209928000 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 135588707
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The primary aim of this book is to provide students, educators, researchers, and aspiring professionals with a strong foundation in machine learning concepts, algorithms, and practical implementation techniques. It is designed to help learners understand how intelligent systems learn from data, recognise patterns, make predictions, and support decision-making in real-world applications. This book aims to:¿ Introduce the fundamentals and types of machine learning.¿ Explain core supervised, unsupervised, and reinforcement learning techniques. ¿ Develop analytical thinking for selecting suitable algorithms for different problems. ¿ Provide practical knowledge using Python and popular ML libraries. ¿ Bridge theoretical understanding with hands-on experimentation. ¿ Prepare learners for advanced studies, research, and industry applications in AI and data science. 264 pp. Englisch. Bestandsnummer des Verkäufers 9786209928000
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Paperback. Zustand: new. Paperback. The primary aim of this book is to provide students, educators, researchers, and aspiring professionals with a strong foundation in machine learning concepts, algorithms, and practical implementation techniques. It is designed to help learners understand how intelligent systems learn from data, recognise patterns, make predictions, and support decision-making in real-world applications. This book aims to: - Introduce the fundamentals and types of machine learning.- Explain core supervised, unsupervised, and reinforcement learning techniques. - Develop analytical thinking for selecting suitable algorithms for different problems. - Provide practical knowledge using Python and popular ML libraries. - Bridge theoretical understanding with hands-on experimentation. - Prepare learners for advanced studies, research, and industry applications in AI and data science. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9786209928000
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