Concepts, Techniques, and Applications with XLMiner
Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data.
Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes:
Real-world examples to build a theoretical and practical understanding of key data mining methods
End-of-chapter exercises that help readers better understand the presented material
Data-rich case studies to illustrate various applications of data mining techniques
Completely new chapters on social network analysis and text mining
A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint® slides
Free 140-day license to use XLMiner for Education software
Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology.
Edition: 3rd Edition
ISBN: 978-1-118-72927-4
Posted on: 12/11/2016
Format: Pdf
Page Count: 552 Pages
Author: Galit Shmueli,: Peter C Bruce,
Nitin R Patel,: --------------------
