000 | 01463nam a22001817a 4500 | ||
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999 |
_c1263 _d1263 |
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005 | 20211125135047.0 | ||
008 | 211125b ||||| |||| 00| 0 eng d | ||
020 | _a9781108473989 | ||
082 |
_a006.312 _bZAK |
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100 | _aZaki, Mohammed J | ||
245 |
_aData mining and machine learning : _b fundamental concepts and algorithms _cMohammed J Zaki; Wagner Meira |
||
250 | _a2ND | ||
260 |
_a NY : _bCambridge University Press, 2020. _c©2020 |
||
300 | _a766 pages | ||
505 |
_t Part one: Data analysis foundations _tPart two: Frequent pattern mining - _tPart three: Clustering _tPart four: Classification _tPart five: Regression |
||
520 | _aThe 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 | ||
942 |
_2ddc _cBK |