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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.
This book brings all of the elements of data mining together in a
single volume, saving the reader the time and expense of making
multiple purchases. It consolidates both introductory and advanced
topics, thereby covering the gamut of data mining and machine
learning tactics ? from data integration and pre-processing, to
fundamental algorithms, to optimization techniques and web mining
methodology.
The proposed book expertly combines the finest data mining material
from the Morgan Kaufmann portfolio. Individual chapters are derived
from a select group of MK books authored by the best and brightest
in the field. These chapters are combined into one comprehensive
volume in a way that allows it to be used as a reference work for
those interested in new and developing aspects of data mining.
This book represents a quick and efficient way to unite valuable
content from leading data mining experts, thereby creating a
definitive, one-stop-shopping opportunity for customers to receive
the information they would otherwise need to round up from separate
sources.
* Chapters contributed by various recognized experts in the field
let the reader remain up to date and fully informed from multiple
viewpoints.
* Presents multiple methods of analysis and algorithmic
problem-solving techniques, enhancing the reader's technical
expertise and ability to implement practical solutions.
* Coverage of both theory and practice brings all of the elements
of data mining together in a single volume, saving the reader the
time and expense of making multiple purchases.
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