Data Mining: Concepts and Techniques, 3rd Edition
Concepts and Techniques
By Jiawei Han, Micheline Kamber, Jian Pei
Publisher: Elsevier / Morgan Kaufmann
Final Release Date: June 2011
Pages: 744

Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets.
After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining.
This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.

    Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects. * Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields. Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

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5.0

Comprehensive, Clear Guide to ML

By Will J

from Milwaukee, WI

About Me Analyst, Marketer, Student

Verified Reviewer

Pros

  • Comprehensive
  • Helpful examples
  • Well-written

Cons

  • No Programming

Best Uses

  • Analyst
  • Expert
  • Intermediate
  • Student

Comments about oreilly Data Mining: Concepts and Techniques, 3rd Edition:

I'm a graduate student in Predictive Analytics (and full-time Business Analyst) and this book has been my go to reference for half a dozen classes. O'Reilly doesn't have the Table of Contents on this catalog page but the book covers:
-Data PreProcessing
-Data Warehousing
-Association Rules (Market Basket Analysis)
-Classification (Naive Bayes, Decision Trees, k-Nearest Neighbors)
-Neural Networks (Bayesian Belief Networks, Backprop)
-Support Vector Machines
-Clustering (K-Means, Hierarchical, Fuzzy)
-Outlier Detection

Who should read this book:
-People who want to understand how data mining algorithms work.
-People who need one reference that covers a lot of material.
-People who are familiar with some machine learning concepts (not required).

People who shouldn't read this book:
-Managers looking to skim the basics of data mining
-Programmers looking to build their own ML libraries.
-Statisticians wanting to learn software (R, SAS, Julia) to do data mining.

If you just want a high level overview look at Linoff and Berry's "Data Mining Techniques" book.

O'Reilly has Programming Collective Intelligence and Machine Learning for Hackers (better yet, Machine Learning with R) for those programmers / statisticians needing code.

This book is in my top three practical data mining references. I'm so glad O'Reilly had this product available right as I started my masters program!

(1 of 2 customers found this review helpful)

 
3.0

Unreadable equations in ebook format

By L.W.

from Poland

About Me Developer

Verified Reviewer

Pros

  • Accurate
  • Concise
  • Easy to understand
  • Well-written

Cons

  • Ebook Format Quality

Best Uses

  • Novice
  • Student

Comments about oreilly Data Mining: Concepts and Techniques, 3rd Edition:

I have just bought the book, and the equations do not scale with the text, are too small and unreadable in the epub format (probably images were used for the equations). I would recommend ordering a printed copy of the book. The ebook formats might work if you have a high resolution ebook reader, and can to view the PDF which is OK.

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