Items related to Machine Learning
- PublisherSpringer
- Publication date2022
- ISBN 10 9811519692
- ISBN 13 9789811519697
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages472
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Machine Learning
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Machine Learning
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Machine Learning
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Machine Learning
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Springer-Nature New York Inc, 2022
ISBN 10: 9811519692
ISBN 13: 9789811519697
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Paperback
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Machine Learning
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Machine Learning
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Springer Nature Singapore Aug 2022, 2022
ISBN 10: 9811519692
ISBN 13: 9789811519697
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Taschenbuch
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Machine Learning, a vital and core area of artificial intelligence (AI), is propelling the AI field ever further and making it one of the most compelling areas of computer science research. This textbook offers a comprehensive and unbiased introduction to almost all aspects of machine learning, from the fundamentals to advanced topics. It consists of 16 chapters divided into three parts: Part 1 (Chapters 1-3) introduces the fundamentals of machine learning, including terminology, basic principles, evaluation, and linear models; Part 2 (Chapters 4-10) presents classic and commonly used machine learning methods, such as decision trees, neural networks, support vector machines, Bayesian classifiers, ensemble methods, clustering, dimension reduction and metric learning; Part 3 (Chapters 11-16) introduces some advanced topics, covering feature selection and sparse learning, computational learning theory, semi-supervised learning, probabilistic graphical models, rule learning, and reinforcement learning. Each chapter includes exercises and further reading, so that readers can explore areas of interest. The book can be used as an undergraduate or postgraduate textbook for computer science, computer engineering, electrical engineering, data science, and related majors. It is also a useful reference resource for researchers and practitioners of machine learning. 472 pp. Englisch. Seller Inventory # 9789811519697
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Machine Learning
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paperback. Condition: New. 1st ed. 2021. Special order direct from the distributor. Seller Inventory # ING9789811519697
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Machine Learning
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Machine Learning
Published by
Springer Nature Singapore, Springer Nature Singapore, 2022
ISBN 10: 9811519692
ISBN 13: 9789811519697
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Taschenbuch
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Machine Learning, a vital and core area of artificial intelligence (AI), is propelling the AI field ever further and making it one of the most compelling areas of computer science research. This textbook offers a comprehensive and unbiased introduction to almost all aspects of machine learning, from the fundamentals to advanced topics. It consists of 16 chapters divided into three parts: Part 1 (Chapters 1-3) introduces the fundamentals of machine learning, including terminology, basic principles, evaluation, and linear models; Part 2 (Chapters 4-10) presents classic and commonly used machine learning methods, such as decision trees, neural networks, support vector machines, Bayesian classifiers, ensemble methods, clustering, dimension reduction and metric learning; Part 3 (Chapters 11-16) introduces some advanced topics, covering feature selection and sparse learning, computational learning theory, semi-supervised learning, probabilistic graphical models, rule learning, and reinforcement learning. Each chapter includes exercises and further reading, so that readers can explore areas of interest. The book can be used as an undergraduate or postgraduate textbook for computer science, computer engineering, electrical engineering, data science, and related majors. It is also a useful reference resource for researchers and practitioners of machine learning. Seller Inventory # 9789811519697
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Machine Learning
ISBN 10: 9811519692
ISBN 13: 9789811519697
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Machine Learning, a vital and core area of artificial intelligence (AI), is propelling the AI field ever further and making it one of the most compelling areas of computer science research. This textbook offers a comprehensive and unbiased introduction t. Seller Inventory # 668477826
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