Data mining and machine learning : fundamental concepts and algorithms Mohammed J Zaki; Wagner Meira
Material type: TextPublication details: NY : Cambridge University Press, 2020. ©2020Edition: 2NDDescription: 766 pagesISBN:- 9781108473989
- 006.312 ZAK
Item type | Current library | Collection | Call number | Status | Date due | Barcode |
---|---|---|---|---|---|---|
Books | IIITDM Kurnool General Stacks | Non-fiction | 006.312 ZAK (Browse shelf(Opens below)) | Checked out | 29.12.2025 | 0003793 |
Reference | IIITDM Kurnool Reference | Reference | 006.312 ZAK (Browse shelf(Opens below)) | Not For Loan | 0003794 |
Part one: Data analysis foundations Part two: Frequent pattern mining - Part three: Clustering Part four: Classification Part five: Regression
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
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