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Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro

Unknown Author
4.9/5 (15479 ratings)
Description:Incorporating an innovative focus on data visualization and time series forecasting, "Data Mining for Business Intelligence" supplies insightful, detailed guidance on fundamental data mining techniques. The book guides readers through the use of JMP(R) (now in a newly revised student version) for developing predictive models and techniques in order to describe and find patterns in data. The authors use interesting, real-world examples to build a theoretical and practical understanding of key data mining methods. The book includes free access to the student edition of SAS Institute's JMP(R), allowing readers to work hands-on with the provided data. Throughout the book, applications of the discussed topics focus on the business problem as motivation and avoid unnecessary statistical theory. Each chapter concludes with exercises that allow readers to expand their comprehension of the presented material. Over a dozen cases that require use of the different data mining techniques are introduced, and a related Web site features over two dozen data sets, exercise solutions, PowerPoint slides, and case solutions. Modern topics include text analytics, recommender systems, social network analysis, getting data from a database into the analytics process, and scoring and employing the results of an analysis to a database.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro. To get started finding Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.
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Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro

Unknown Author
4.4/5 (1290744 ratings)
Description: Incorporating an innovative focus on data visualization and time series forecasting, "Data Mining for Business Intelligence" supplies insightful, detailed guidance on fundamental data mining techniques. The book guides readers through the use of JMP(R) (now in a newly revised student version) for developing predictive models and techniques in order to describe and find patterns in data. The authors use interesting, real-world examples to build a theoretical and practical understanding of key data mining methods. The book includes free access to the student edition of SAS Institute's JMP(R), allowing readers to work hands-on with the provided data. Throughout the book, applications of the discussed topics focus on the business problem as motivation and avoid unnecessary statistical theory. Each chapter concludes with exercises that allow readers to expand their comprehension of the presented material. Over a dozen cases that require use of the different data mining techniques are introduced, and a related Web site features over two dozen data sets, exercise solutions, PowerPoint slides, and case solutions. Modern topics include text analytics, recommender systems, social network analysis, getting data from a database into the analytics process, and scoring and employing the results of an analysis to a database.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro. To get started finding Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.
Pages
Format
PDF, EPUB & Kindle Edition
Publisher
Release
ISBN
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