Data Mining: Practical Machine Learning Tools and Techniques / Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher J. Pal
Material type: TextLanguage: English Publication details: United States : Morgan Kaufmann, 2017Edition: 4th EditionDescription: xxxii, 621 p. ; 28 cmISBN: 9780128042915Subject(s): Data mining | Khai thác dữ liệuDDC classification: 006.312 Online resources: Click here to access online Summary: Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.rnrnExtensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.Item type | Current library | Call number | Status | Date due | Barcode | Item holds |
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Sách tham khảo |
Thư viện Trường Quốc tế - Cơ sở Trịnh Văn Bô
Thư viện Trường Quốc tế - Đại học Quốc gia Hà Nội |
006.312 WRI 2017 | Available | TVB.1/00246 | ||
Giáo trình |
Thư viện Trường Quốc tế - Cơ sở Trịnh Văn Bô
Thư viện Trường Quốc tế - Đại học Quốc gia Hà Nội |
006.312 WRI 2017 | Available | TVB.1/00248 |
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.rnrnExtensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
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