Original PDF Ebook – Data Mining for Business Analytics: Concepts, Techniques, and Applications in R1st Edition – 9781118879368

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Author (s): Galit Shmueli
Publisher: Wiley-Blackwell Print
ISBN: 9781118879368 1118879368
Edition: 1st
Copyright: 2017

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Original PDF Ebook – Data Mining for Business Analytics: Concepts, Techniques, and Applications in R1st Edition – 9781118879368

Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustration_x000D_
Readers will learn how to implement a variety of popular data mining algorithms in R (a free and open-source software) to tackle business problems and opportunities._x000D_
This is the fifth version of this successful text, and the first using R. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes:_x000D_
• Two new co-authors, Inbal Yahav and Casey Lichtendahl, who bring both expertise teaching business analytics courses using R, and data mining consulting experience in business and government_x000D_
• Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students_x000D_
• More than a dozen case studies demonstrating applications for the data mining techniques described_x000D_
• End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented_x000D_
• A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions_x000D_
Data Mining for Business Analytics: Concepts, Techniques, and Applications in R is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.

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