Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro by Galit Shmueli, Peter C. Bruce, Mia L. Stephens, Nitin R. Patel
Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro by Galit Shmueli, Peter C. Bruce, Mia L. Stephens, Nitin R. Patel PDF, ePub eBook D0wnl0ad
“Data Mining for Business Analytics with JMP Pro® hits the ‘sweet spot’ in terms of balancing the technical and applied aspects of data mining. The content and technical level of the book works beautifully for a variety of students ranging from undergraduates to MBAs to those in applied graduate programs.”
- Allison Jones-Farmer, Van Andel Professor of Business Analytics & Director of the Center for Analytics and Data Science, Department of Information Systems & Analytics, Farmer School of Business, Miami University
Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® presents an applied and interactive approach to data mining.
Featuring hands-on applications with JMP Pro®, a statistical package from the SAS Institute, the book uses engaging, real-world examples to build a theoretical and practical understanding of key data mining methods, especially predictive models for classification and prediction. Topics include data visualization, dimension reduction techniques, clustering, linear and logistic regression, classification and regression trees, discriminant analysis, naïve Bayes, neural networks, uplift modeling, ensemble models, and time series forecasting.
- Detailed summaries that supply an outline of key topics at the beginning of each chapter
- End-of-chapter examples and exercises that allow readers to expand their comprehension of the presented material
- Data-rich case studies to illustrate various applications of data mining techniques
- A companion website with over two dozen data sets, exercise and case study solutions, and slides for instructors
Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro® is an excellent textbook for upper-undergraduate and graduate-level courses on data mining, predictive analytics, and business analytics. The book is also a one-of-a-kind resource for data scientists, analysts, researchers, and practitioners working with analytics in the fields of management, finance, marketing, information technology, healthcare, education, and any other data-rich field.
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