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Data Mining: Practical Machine Learning Tools and Techniques Paperback – 17 November 2016

4.2 4.2 out of 5 stars 121 ratings
Edition: 4th
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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 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.
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  1. ISBN-10
    0128042915
  2. ISBN-13
    978-0128042915
  3. Edition
    4th
  4. Publisher
    Morgan Kaufmann
  5. Publication date
    17 November 2016
  6. Part of series
    The Morgan Kaufmann Series in Data Management Systems
  7. Language
    English
  8. Dimensions
    18.8 x 2.79 x 23.37 cm
  9. Print length
    654 pages
  10. See all details
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Product description

Review

"...this volume is the most accessible introduction to data mining to appear in recent years. It is worthy of a fourth edition." --Computing Reviews

Review

This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning provides practical advice and techniques

Product details

  • Publisher ‏ : ‎ Morgan Kaufmann; 4th edition (17 November 2016)
  • Language ‏ : ‎ English
  • Paperback ‏ : ‎ 654 pages
  • ISBN-10 ‏ : ‎ 0128042915
  • ISBN-13 ‏ : ‎ 978-0128042915
  • Dimensions ‏ : ‎ 18.8 x 2.79 x 23.37 cm
  • Customer Reviews:
    4.2 4.2 out of 5 stars 121 ratings

About the authors

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  1. Ian H. Witten

    Ian H. Witten

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  2. Christopher J. Pal

    Christopher J. Pal

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4.2 out of 5 stars
4.2 out of 5
121 global ratings

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Top review from Australia

Lee
1.0 out of 5 stars Unnecessarily convoluted
Reviewed in Australia on 13 April 2024
Verified Purchase
I had to get this for my data mining course however there is extremely little value and almost everything I have learnt has been through finding someone else to explain what this book fails to explain in a comprehensible way.

Definitely would not recommend if you can avoid it.
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Top reviews from other countries

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Amazon Customer
5.0 out of 5 stars Quality of book - good, content - do not recommend
Reviewed in Canada on 22 August 2020
Verified Purchase
The book was in great condition. I wish it had a hard cover though.

If you want to learn about data mininh (I had to buy this book for an advanced data mining course) I would NOT recommend this book. The content is really of poor quality. Please do NOT use this book in your classes, just waste of money for students.
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M
5.0 out of 5 stars Easy to read & follow content
Reviewed in the United Kingdom on 2 December 2020
Verified Purchase
One of the best on Data mining.
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Double-E
5.0 out of 5 stars Great text for the subject matter but i think this edition needs some editing to fix reference errors
Reviewed in the United States on 4 March 2018
Verified Purchase
This is a great textbook for the subject, but this edition has some significant typos in it. The book i received has significant errors in reference to chapters in the book. For example, the opening to part two of the book references the later chapters all incorrectly. The book seems to be legit as far as being genuine so i don't think i got a knock-off version.
2 people found this helpful
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hugo
3.0 out of 5 stars buen libro pero no tiene teoria
Reviewed in Mexico on 18 January 2018
Verified Purchase
lo compré porque pensaba que la parte de deep learning estaba bien explicada, pero es similar a las
versiones anteriores, en el sentido de que es demasiado practico, lo único realmente nuevo es el capítulo 9 de
metodos probabilisticos.
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Raja Subramanian
4.0 out of 5 stars Four Stars
Reviewed in India on 9 March 2018
Verified Purchase
The front page is featuring wrongly as geophysics.
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