Items related to Machine Learning: A Practical Approach on the Statistical...
- PublisherSpringer
- Publication date2019
- ISBN 10 3030069494
- ISBN 13 9783030069490
- BindingPaperback
- LanguageEnglish
- Number of pages377
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Machine Learning : A Practical Approach on the Statistical Learning Theory
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Machine Learning : A Practical Approach on the Statistical Learning Theory
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Machine Learning: A Practical Approach on the Statistical Learning Theory
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Machine Learning: A Practical Approach on the Statistical Learning Theory
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Machine Learning: A Practical Approach on the Statistical Learning Theory
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Machine Learning : A Practical Approach on the Statistical Learning Theory
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Machine Learning : A Practical Approach on the Statistical Learning Theory
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Machine Learning
Published by
Springer International Publishing Feb 2019, 2019
ISBN 10: 3030069494
ISBN 13: 9783030069490
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents the Statistical Learning Theory in a detailed and easy to understand way, by using practical examples, algorithms and source codes. It can be used as a textbook in graduation or undergraduation courses, for self-learners, or as reference with respect to the main theoretical concepts of Machine Learning. Fundamental concepts of Linear Algebra and Optimization applied to Machine Learning are provided, as well as source codes in R, making the book as self-contained as possible.It starts with an introduction to Machine Learning concepts and algorithms such as the Perceptron, Multilayer Perceptron and the Distance-Weighted Nearest Neighbors with examples, in order to provide the necessary foundation so the reader is able to understand the Bias-Variance Dilemma, which is the central point of the Statistical Learning Theory.Afterwards, we introduce all assumptions and formalize the Statistical Learning Theory, allowing the practical study of different classification algorithms. Then, we proceed with concentration inequalities until arriving to the Generalization and the Large-Margin bounds, providing the main motivations for the Support Vector Machines. From that, we introduce all necessary optimization concepts related to the implementation of Support Vector Machines. To provide a next stage of development, the book finishes with a discussion on SVM kernels as a way and motivation to study data spaces and improve classification results. 380 pp. Englisch. Seller Inventory # 9783030069490
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Machine Learning : A Practical Approach on the Statistical Learning Theory
Published by
Springer International Publishing, Springer International Publishing, 2019
ISBN 10: 3030069494
ISBN 13: 9783030069490
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the Statistical Learning Theory in a detailed and easy to understand way, by using practical examples, algorithms and source codes. It can be used as a textbook in graduation or undergraduation courses, for self-learners, or as reference with respect to the main theoretical concepts of Machine Learning. Fundamental concepts of Linear Algebra and Optimization applied to Machine Learning are provided, as well as source codes in R, making the book as self-contained as possible.It starts with an introduction to Machine Learning concepts and algorithms such as the Perceptron, Multilayer Perceptron and the Distance-Weighted Nearest Neighbors with examples, in order to provide the necessary foundation so the reader is able to understand the Bias-Variance Dilemma, which is the central point of the Statistical Learning Theory.Afterwards, we introduce all assumptions and formalize the Statistical Learning Theory, allowing the practical study of different classification algorithms. Then, we proceed with concentration inequalities until arriving to the Generalization and the Large-Margin bounds, providing the main motivations for the Support Vector Machines. From that, we introduce all necessary optimization concepts related to the implementation of Support Vector Machines. To provide a next stage of development, the book finishes with a discussion on SVM kernels as a way and motivation to study data spaces and improve classification results. Seller Inventory # 9783030069490
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Machine Learning
Published by
Springer International Publishing, 2019
ISBN 10: 3030069494
ISBN 13: 9783030069490
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Softcover
Seller: moluna, Greven, Germany
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book includes a relevant discussion on Classification Algorithms as well as their source codes using the R Statistical LanguageIt also presents a very simple approach to understand the Statistical Learning Theory, which is considered a comple. Seller Inventory # 448670254
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