Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) - Softcover
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Synopsis
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...
About the Authors
Ian H. Witten is a professor of computer science at the University of Waikato in New Zealand. He directs the New Zealand Digital Library research project. His research interests include information retrieval, machine learning, text compression, and programming by demonstration. He received an MA in Mathematics from Cambridge University, England; an MSc in Computer Science from the University of Calgary, Canada; and a PhD in Electrical Engineering from...
From the Back Cover
Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying the 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 will teach you everything you need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to...
"About this title" may belong to another edition of this title.
- PublisherMorgan Kaufmann
- Publication date2016
- ISBN 10 0128042915
- ISBN 13 9780128042915
- BindingPaperback
- LanguageEnglish
- Edition number4
- Number of pages654
- Rating
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Data Mining: Practical Machine Learning Tools and Techniques, 4th
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ISBN 10: 0128042915
ISBN 13: 9780128042915
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Data Mining: Practical Machine Learning Tools and Techniques, 4th edition
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