Data Mining

Data Mining

Practical Machine Learning Tools and Techniques

by Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher J. Pal

654 pages· 2016· ISBN 9780128043578
About
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 http://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. 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

Discuss Data Mining with other readers

Join or start a book club for Data Mining on Readfeed. Live chat, shared reading progress, and AI discussion questions — free to get started.

Frequently asked questions

How do I join a book club for Data Mining?

Sign up free on Readfeed, then browse public clubs or start your own club with Data Mining as the current read. Invite friends with a share link and discuss together with live chat and AI discussion questions.

Can I discuss Data Mining with other readers online?

Yes. Readfeed book clubs let you chat live, share progress, and join discussions about Data Mining with readers worldwide — whether your club is virtual, in-person, or hybrid.

Is Readfeed free?

Yes. Creating an account and joining book clubs is free. Sign up to find readers who love the same books and start discussing today.