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Sinopsis
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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Machine Learning (Paperback)
Publicado por
LAP Lambert Academic Publishing, 2026
ISBN 10: 6209928005
ISBN 13: 9786209928000
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Paperback
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: 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. Nº de ref. del artículo: 9786209928000
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Machine Learning
Publicado por
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6209928005
ISBN 13: 9786209928000
Nuevo
PAP
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9786209928000
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Machine Learning
Publicado por
LAP Lambert Academic Publishing, 2026
ISBN 10: 6209928005
ISBN 13: 9786209928000
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Tapa blanda
Librería: California Books, Miami, FL, Estados Unidos de America
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Machine Learning
Publicado por
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6209928005
ISBN 13: 9786209928000
Nuevo
PAP
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9786209928000
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Machine Learning
Publicado por
LAP LAMBERT Academic Publishing Mai 2026, 2026
ISBN 10: 6209928005
ISBN 13: 9786209928000
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9786209928000
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Machine Learning | Concepts and Techniques
Publicado por
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6209928005
ISBN 13: 9786209928000
Nuevo
Taschenbuch
Librería: preigu, Osnabrück, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 135588707
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Machine Learning
Publicado por
LAP LAMBERT Academic Publishing Mai 2026, 2026
ISBN 10: 6209928005
ISBN 13: 9786209928000
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9786209928000
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Machine Learning : Concepts and Techniques
Publicado por
LAP LAMBERT Academic Publishing, 2026
ISBN 10: 6209928005
ISBN 13: 9786209928000
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9786209928000
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Machine Learning (Paperback)
Publicado por
LAP Lambert Academic Publishing, 2026
ISBN 10: 6209928005
ISBN 13: 9786209928000
Nuevo
Paperback
Librería: CitiRetail, Stevenage, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: 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. Nº de ref. del artículo: 9786209928000
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