Ian H. Witten, Eibe Frank, Mark A. Hall, Christopher J. Pal
Morgan Kaufmann; 4th edition
The Fourth Edition of Data Mining: Practical Machine Learning Tools and Techniques (PDF) provides a comprehensive introduction to the fundamentals of machine learning, as well as advice on how to put these concepts, tools, and techniques to use in data mining scenarios that are based in the real world. This highly anticipated fourth edition of the most highly regarded work on data mining and machine learning teaches readers everything they need to know to get started, from preparing inputs to interpreting outputs and evaluating results, as well as the algorithmic methods that are at the core of effective data mining approaches.
Extensive revisions highlight the advancements in methodology and technology that have taken place in the industry since the publication of the last edition. These revisions include important new chapters on probabilistic approaches and on deep learning. The well-known WEKA machine learning program, which was developed at the University of Waikato, has been updated, and it is included alongside the ebook. The authors Frank, Witten, Hall, and Pal blend current methodologies with cutting-edge research practices and include today’s techniques as part of this integration.
NOTE: This product only comes with the downloadable PDF version of the ebook “Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition.” There are no access codes contained within.