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Data Mining: Practical Machine Learning Tools and Techniques (3rd Edition)

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Download Data Mining: Practical Machine Learning Tools and Techniques (3rd Edition) written by Ian H. Witten, Eibe Frank, Mark A. Hall in PDF format. This book is under the category Computers and bearing the isbn/isbn13 number 123748569/9780123748560. You may reffer the table below for additional details of the book. We do NOT provide access codes, we provide eBooks ONLY. Instant access will be granted as soon as you complete the payment.

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Specifications

book-author

Ian H. Witten, Eibe Frank, Mark A. Hall

publisher

Morgan Kaufmann; 3rd edition

file-type

PDF

pages

664 pages

language

English

isbn10

123748569

isbn13

9780123748560


Book Description

This book, Data Mining: Practical Machine Learning Tools and Techniques, Third Edition (PDF), gives readers a solid foundation in the concepts of machine learning as well as advice on how to practically apply machine learning tools and techniques in data mining scenarios that take place in the real world. You will learn everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the core of successful data mining from this eagerly awaited third edition of the most acclaimed work on data mining and machine learning. This edition has been highly anticipated and is now available.

Comprehensive revisions made to the book “Data Mining: Practical Machine Learning Tools and Techniques.” The third edition reviews the various technological advancements and adaptations that have been made in the industry since the publication of the previous edition. This includes new information on Data Transformations, Ensemble Learning, Massive Data Sets, and Multi-instance Learning, as well as a new version of the well-known Weka machine learning software that was developed by the authors. Methods that are cutting edge in terms of modern research are covered by Witten, Frank, and Hall. These authors cover both time-tested practices that are still used today as well as those that are at the forefront of this field.

Those who work in information systems, including practitioners, programmers, developers, consultants, information technology managers, data analysts, specification writers, data modelers, database research and development professionals, data mining professionals, and data warehouse engineers, are the target audience for this ebook. The textbook will also be useful for teachers and students in advanced undergraduate and graduate-level data mining and machine learning classes who wish to incorporate data mining into their existing knowledge base and expertise in the field of data management. These groups will find the book particularly useful.

 

Reviews

 

“This is without a doubt one of my most sought-after data mining ebooks in my collection.” — Tom Breur, Principal at XLNT Consulting, located in Tilburg, the Netherlands, The Netherlands

This e-book, Data Mining: Practical Machine Learning Tools and Techniques, is an excellent candidate for inclusion in a technical data mining class. It is among the very best examples of its kind. — Herb Edelstein, Principal at Two Crows Consulting and a Data Mining Consultant at Two Crows

“The writers present enough theory to permit practical application,” and “this ebook's focus on practical application is what distinguishes it from the vast majority of other works on this subject, if not all of them.” — Dorian Pyle, Director of Modeling at Numetrics and an author with a significant international reputation

P.S. You can also get the fourth edition, which is the most recent version. Contact us for details

NOTE: This product only includes the downloadable PDF version of the ebook titled “Data Mining: Practical Machine Learning Tools and Techniques, Third Edition.” There are no access codes contained within.

book-author

Ian H. Witten, Eibe Frank, Mark A. Hall

publisher

Morgan Kaufmann; 3rd edition

file-type

PDF

pages

664 pages

language

English

isbn10

123748569

isbn13

9780123748560

Reviews

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