Data mining and machine learning : fundamental concepts and algorithms / Mohammed J. Zaki, Wagner Meira, Jr.
Material type:
TextPublication details: New York : Cambridge University Press, 2020. Description: xii, 766 pages : illustrations ; 25 cmISBN: 9781108473989Subject(s): Data miningOther classification: QA76.9 ZAK 2020 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.
| Item type | Current library | Call number | Status | Notes | Date due | Barcode |
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General Collection
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Universiti Teknologi Brunei Library - at level 2 | QA76.9 ZAK 2020 c. 1 (Browse shelf(Opens below)) | Available | Reg. no. 033889_UTB | 834284 |
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.
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