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Data Mining Techniques, Third Edition

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Data Mining Techniques, Third Edition

Written by: Gordon S. Linoff, Michael J.A. Berry
Narrated by: Steve Menasche
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About this listen

The leading introductory book on data mining, fully updated and revised!

When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new edition - more than 50 percent new and revised - is a significant update from the previous one and reveals how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics, such as preparing data for analysis and creating the necessary infrastructure for data mining at your company.

  • Features significant updates since the previous edition and updates you on best practices for using data mining methods and techniques for solving common business problems.
  • Covers a new data mining technique in every chapter along with clear, concise explanations on how to apply each technique immediately.
  • Touches on core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, survival analysis, and more.
  • Provides best practices for performing data mining using simple tools such as Excel.

Data Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results.

PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.

©2011 Wiley Publishing, Inc., Indianapolis, Indiana (P)2018 Gildan Media
Data Science Marketing Marketing & Sales Personal Success Machine Learning Mining Business Technology Artificial Intelligence Management Programming Computer Science
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