Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest.
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Andrea Ahlemeyer-Stubbe, Director Strategic Analytics, DRAFTFCB München GmbH, Germany
Shirley Coleman, Principal Statistician, Industrial Statistics Research Unit, School of Maths and Statistics, Newcastle University, UK
A Practical Guide to Data Mining for Business and Industry
A Practical Guide to Data Mining for Business and Industry presents a user friendly approach to data mining methods and provides a solid foundation for their application. The methodology presented is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. This book is designed so that the reader can cross-reference a particular application or method to sectors of interest. The necessary basic knowledge of data mining methods is also presented, along with sector issues relating to data mining and its various applications.
A Practical Guide to Data Mining for Business and Industry:
Aimed at statisticians, computer scientists and economists involved in data mining as well as students studying economics, business administration and international marketing.
A Practical Guide to Data Mining for Business and Industry
A Practical Guide to Data Mining for Business and Industry presents a user friendly approach to data mining methods and provides a solid foundation for their application. The methodology presented is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. This book is designed so that the reader can cross-reference a particular application or method to sectors of interest. The necessary basic knowledge of data mining methods is also presented, along with sector issues relating to data mining and its various applications.
A Practical Guide to Data Mining for Business and Industry:
Aimed at statisticians, computer scientists and economists involved in data mining as well as students studying economics, business administration and international marketing.
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Zustand: New. * Presents data mining processes, methods and commonly used methods for descriptive and exploratory statistics using SAS and JMP. Num Pages: 324 pages, illustrations. BIC Classification: KJQ; UNF. Category: (P) Professional & Vocational. Dimension: 157 x 230 x 21. Weight in Grams: 538. . 2014. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland. Artikel-Nr. V9781119977131
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Gebunden. Zustand: New. A Practical Guide to Data Mining for Business and Industrygives practical tools on how information can be extracted from masses of data. The book is very well written, in a conversational tone that makes it enjoyable to read. The authors are excellent comm. Artikel-Nr. 477200594
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Buch. Zustand: Neu. Neuware - Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest. Artikel-Nr. 9781119977131
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