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 at https:
//www.cs.waikato.ac.nz/ ml/weka/book.html.
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.
