This book introduces the fundamental principles of machine learning, beginning with the basics of data analysis and the different types of learning approaches. It explains key supervised and unsupervised learning algorithms, data preprocessing techniques, feature engineering, visualization methods, and model evaluation. The final chapters provide an introduction to deep learning concepts, including optimization, neural networks, and model validation. Written in a clear and structured manner, this book serves as an essential resource for students, researchers, and professionals seeking a practical foundation in machine learning and artificial intelligence.
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Mr. Sundaresan K and Ms. Abinaya V are Assistant Professors in the Department of Artificial Intelligence and Data Science at Karpagam Institute of Technology. Their research interests include deep learning, machine learning, algorithm analysis, database systems, and distributed computing.
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Paperback. Zustand: new. Paperback. This book introduces the fundamental principles of machine learning, beginning with the basics of data analysis and the different types of learning approaches. It explains key supervised and unsupervised learning algorithms, data preprocessing techniques, feature engineering, visualization methods, and model evaluation. The final chapters provide an introduction to deep learning concepts, including optimization, neural networks, and model validation. Written in a clear and structured manner, this book serves as an essential resource for students, researchers, and professionals seeking a practical foundation in machine learning and artificial intelligence. 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 9786209809231
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Taschenbuch. Zustand: Neu. Machine Learning Essentials: Algorithms, Data Mining, and Deep Network | Sundaresan Kalappan (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209809231 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 136194599
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book introduces the fundamental principles of machine learning, beginning with the basics of data analysis and the different types of learning approaches. It explains key supervised and unsupervised learning algorithms, data preprocessing techniques, feature engineering, visualization methods, and model evaluation. The final chapters provide an introduction to deep learning concepts, including optimization, neural networks, and model validation. Written in a clear and structured manner, this book serves as an essential resource for students, researchers, and professionals seeking a practical foundation in machine learning and artificial intelligence. 216 pp. Englisch. Bestandsnummer des Verkäufers 9786209809231
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Paperback. Zustand: new. Paperback. This book introduces the fundamental principles of machine learning, beginning with the basics of data analysis and the different types of learning approaches. It explains key supervised and unsupervised learning algorithms, data preprocessing techniques, feature engineering, visualization methods, and model evaluation. The final chapters provide an introduction to deep learning concepts, including optimization, neural networks, and model validation. Written in a clear and structured manner, this book serves as an essential resource for students, researchers, and professionals seeking a practical foundation in machine learning and artificial intelligence. 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 9786209809231
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book introduces the fundamental principles of machine learning, beginning with the basics of data analysis and the different types of learning approaches. It explains key supervised and unsupervised learning algorithms, data preprocessing techniques, feature engineering, visualization methods, and model evaluation. The final chapters provide an introduction to deep learning concepts, including optimization, neural networks, and model validation. Written in a clear and structured manner, this book serves as an essential resource for students, researchers, and professionals seeking a practical foundation in machine learning and artificial intelligence. Bestandsnummer des Verkäufers 9786209809231
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