Hiển thị biểu ghi dạng vắn tắt

dc.contributor.authorShmueli, Galit
dc.contributor.authorBruce, Peter C.
dc.contributor.authorGedeck, Peter
dc.contributor.authorPatel, Nitin R.
dc.date.issued2020
dc.identifier.isbn97811195498 40
dc.identifier.urihttps://thuvienso.hoasen.edu.vn/handle/123456789/11705
dc.description.abstract"This book supplies insightful, detailed guidance on fundamental data mining techniques. The book guides readers through the use of Python software 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, with a focus on analytics rather than programming. The book includes discussions of Python subroutines, 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. Topics covered include time series, text mining, and dimension reduction. 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" Provided by publisher.
dc.format705 p. : ill.
dc.language.isoen
dc.publisherJohn Wiley & Sons, Inc.
dc.subjectBusiness
dc.subjectBusiness mathematics
dc.subjectData mining
dc.subjectData processing
dc.subjectComputer programs
dc.subjectPython (Computer program language)
dc.titleData mining for business analytics : concepts, techniques and applications in Python
dc.typeBook


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Hiển thị biểu ghi dạng vắn tắt