Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)

ISBN-13: 9780128042915
ISBN-10: 0128042915
Edition: 4
Author: Mark A. Hall, Ian H. Witten, Eibe Frank, Christopher J. Pal
Publication date: 2016
Publisher: Morgan Kaufmann
Format: Paperback 654 pages
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Book details

ISBN-13: 9780128042915
ISBN-10: 0128042915
Edition: 4
Author: Mark A. Hall, Ian H. Witten, Eibe Frank, Christopher J. Pal
Publication date: 2016
Publisher: Morgan Kaufmann
Format: Paperback 654 pages
Category: Engineering , Computers , Database

Summary

Acknowledged authors Mark A. Hall , Ian H. Witten , Eibe Frank , Christopher J. Pal wrote Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) comprising 654 pages back in 2016. Textbook and eTextbook are published under ISBN 0128042915 and 9780128042915. Since then Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) textbook was available to sell back to BooksRun online for the top buyback price of $ 17.49 or rent at the marketplace.

Description

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.

Extensive 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.

Please visit the book companion website.

It contains

  • Powerpoint slides for Chapters 1 12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
  • Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
  • Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
  • Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
  • Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
  • Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks in an easy to use interactive interface
  • Includes open access online courses that introduce practical applications of the material in the book

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