This book introduces the fundamental principles of machine learning and intelligent modeling through practical Python implementations and real-world examples. It begins by establishing the foundations of smart systems, learning paradigms, evaluation metrics, and model validation before progressing to classical supervised and unsupervised machine learning algorithms. Readers are guided through linear regression, logistic regression, k-nearest neighbors, support vector machines, decision trees, ensemble learning, clustering techniques, and principal component analysis, with an emphasis on both the underlying mathematical concepts and their practical implementation using Python. Each chapter combines theoretical background, methodology, implementation, experimental evaluation, and discussion to provide a comprehensive learning experience. Intended for undergraduate and graduate students, researchers, and practitioners, this volume serves as both an academic textbook and a practical reference for developing reliable, interpretable, and data-driven intelligent systems using modern machine learning techniques.
"synopsis" may belong to another edition of this title.
Seller: California Books, Miami, FL, U.S.A.
Condition: New. Seller Inventory # I-9786630107265
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # L2-9786630107265
Quantity: Over 20 available
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 316 pp. Englisch. Seller Inventory # 9786630107265
Quantity: 2 available
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book introduces the fundamental principles of machine learning and intelligent modeling through practical Python implementations and real-world examples. It begins by establishing the foundations of smart systems, learning paradigms, evaluation metrics, and model validation before progressing to classical supervised and unsupervised machine learning algorithms. Readers are guided through linear regression, logistic regression, k-nearest neighbors, support vector machines, decision trees, ensemble learning, clustering techniques, and principal component analysis, with an emphasis on both the underlying mathematical concepts and their practical implementation using Python. Each chapter combines theoretical background, methodology, implementation, experimental evaluation, and discussion to provide a comprehensive learning experience. Intended for undergraduate and graduate students, researchers, and practitioners, this volume serves as both an academic textbook and a practical reference for developing reliable, interpretable, and data-driven intelligent systems using modern machine learning techniques. Seller Inventory # 9786630107265
Quantity: 1 available
Seller: CitiRetail, Stevenage, United Kingdom
Paperback. Condition: new. Paperback. This book introduces the fundamental principles of machine learning and intelligent modeling through practical Python implementations and real-world examples. It begins by establishing the foundations of smart systems, learning paradigms, evaluation metrics, and model validation before progressing to classical supervised and unsupervised machine learning algorithms. Readers are guided through linear regression, logistic regression, k-nearest neighbors, support vector machines, decision trees, ensemble learning, clustering techniques, and principal component analysis, with an emphasis on both the underlying mathematical concepts and their practical implementation using Python. Each chapter combines theoretical background, methodology, implementation, experimental evaluation, and discussion to provide a comprehensive learning experience. Intended for undergraduate and graduate students, researchers, and practitioners, this volume serves as both an academic textbook and a practical reference for developing reliable, interpretable, and data-driven intelligent systems using modern machine learning techniques. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9786630107265
Quantity: 1 available
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware 316 pp. Englisch. Seller Inventory # 9786630107265
Quantity: 1 available