DATA MINING FOR BUSINESS ANALYTICS : Concepts, Techniques and Applications in Python /
"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 t...
| Main Authors: | , , , |
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| Format: | |
| Language: | eng |
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Hoboken, NJ : John Wiley & Sons, Inc.,
2020
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| Subjects: |
| _version_ | 1796761372606857216 |
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| author | Shmueli, Galit, 1971-, author Bruce, Peter C., 1953-, author Gedeck, Peter, author Patel, Nitin R. (Nitin Ratilal), author |
| author_facet | Shmueli, Galit, 1971-, author Bruce, Peter C., 1953-, author Gedeck, Peter, author Patel, Nitin R. (Nitin Ratilal), author |
| author_sort | Shmueli, Galit, 1971-, author |
| collection | OCEAN |
| description | "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". |
| first_indexed | 2024-03-05T16:25:15Z |
| format | |
| id | KOHA-OAI-TEST:557951 |
| institution | Universiti Teknologi Malaysia - OCEAN |
| language | eng |
| last_indexed | 2024-03-05T16:25:15Z |
| publishDate | 2020 |
| publisher | Hoboken, NJ : John Wiley & Sons, Inc., |
| record_format | dspace |
| spelling | KOHA-OAI-TEST:5579512020-12-19T17:21:06ZDATA MINING FOR BUSINESS ANALYTICS : Concepts, Techniques and Applications in Python / Shmueli, Galit, 1971-, author Bruce, Peter C., 1953-, author Gedeck, Peter, author Patel, Nitin R. (Nitin Ratilal), author Hoboken, NJ : John Wiley & Sons, Inc.,2020eng "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".Includes bibliographical references and index. "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".PSZJBLBusiness mathematics Business xData processingData miningPython (Computer program language)URN:ISBN:9781119549840 |
| spellingShingle | Business mathematics Business xData processing Data mining Python (Computer program language) Shmueli, Galit, 1971-, author Bruce, Peter C., 1953-, author Gedeck, Peter, author Patel, Nitin R. (Nitin Ratilal), author DATA MINING FOR BUSINESS ANALYTICS : Concepts, Techniques and Applications in Python / |
| title | DATA MINING FOR BUSINESS ANALYTICS : Concepts, Techniques and Applications in Python / |
| title_full | DATA MINING FOR BUSINESS ANALYTICS : Concepts, Techniques and Applications in Python / |
| title_fullStr | DATA MINING FOR BUSINESS ANALYTICS : Concepts, Techniques and Applications in Python / |
| title_full_unstemmed | DATA MINING FOR BUSINESS ANALYTICS : Concepts, Techniques and Applications in Python / |
| title_short | DATA MINING FOR BUSINESS ANALYTICS : Concepts, Techniques and Applications in Python / |
| title_sort | data mining for business analytics concepts techniques and applications in python |
| topic | Business mathematics Business xData processing Data mining Python (Computer program language) |
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