Data mining and machine learning : fundamental concepts and algorithms / Mohammed J. Zaki, Wagner Meira, Jr.
By: Zaki, Mohammed J [author.].
Contributor(s): Meira, Wagner [author.].
Material type:
BookPublisher: Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2020Description: 1 online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9781108564175.Uniform titles: Data mining and analysis Subject(s): Data miningAdditional physical formats: Print version:: Data mining and machine learningDDC classification: 006.312 Summary: "The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts.New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning"-- Provided by publisher.
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Central Library | 006.312 ZMD (Browse shelf) | Available | 4548 | |
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Central Library | 006.312 ZMD (Browse shelf) | Available | 4547 | |
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Female Library | 006.312 ZMD (Browse shelf) | Available | 4546 | |
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Female Library | 006.312 ZMD (Browse shelf) | Available | 4545 |
Revised edition of: Data mining and analysis. 2014.
Includes bibliographical references and index.
"The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts.New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning"-- Provided by publisher.
Description based on print version record and CIP data provided by publisher; resource not viewed.
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