This book, with the subtitle "Concepts, Techniques, and Applications in R" presents an applied approach to data mining concepts and methods, using R software for illustration. It shows how to implement a variety of popular data mining algorithms in R  to tackle business problems and opportunities.

This is the fifth version of this book, 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

Authors: Gareth M. James, Galit Shmuel, Peter C. Bruce, Inbal Yahav, Nitin R. Patel, and Kenneth C. Lichtendahl, Jr
Publisher: Wiley
Date: Sept 2017
Pages: 576
ISBN: 978-1118879368
Print: 1118879368
Kindle: B075MSG9F6
Audience: Data scientists
Level: Intermediate
Category: Data Science

• Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students
• More than a dozen case studies demonstrating applications for the data mining techniques described
• End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented
• A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions.

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