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A practical guide to data mining for business and industry /

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Xehetasun bibliografikoak
Egile Nagusiak:	Ahlemeyer-Stubbe, Andrea (Egilea), Coleman, Shirley (Egilea)
Formatua:	Baliabide elektronikoa eBook
Hizkuntza:	ingelesa
Argitaratua:	Chichester, England : Wiley, 2014.
Gaiak:	Data mining. Marketing > Data processing. Management > Mathematical models. Electronic books.
Sarrera elektronikoa:	An electronic book accessible through the World Wide Web; click to view
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!

Antzeko izenburuak

Data mining techniques for marketing, sales, and customer relationship management /
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Data mining techniques for marketing, sales, and customer relationship management /
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Commercial data mining : processing, analysis and modeling for predictive analytics projects /
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Data mining in finance advances in relational and hybrid methods /
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Data mining for business analytics : concepts, techniques, and applications in Microsoft Office Excel with XLMiner /
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Data mining in biomedicine using ontologies
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Predictive analytics and data mining : concepts and practice with rapidminer /
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Data analysis and data mining an introduction /
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Making sense of data I : a practical guide to exploratory data analysis and data mining /
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Data mining for the social sciences : an introduction /
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Spectral feature selection for data mining /
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Statistical data analytics : foundations for data mining, informatics, and knowledge discovery /
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Data mining practical machine learning tools and techniques /
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Practical data science cookbook : 89 hands-on recipes to help you complete real-world data science projects in R and Python /
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Fundamentals of big data : network analysis for research and industry /
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Data mining and management
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Data mining and predictive analysis intelligence gathering and crime analysis /
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Big data marketing : engage your customers more effectively and drive value /
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Marketing research with SAS enterprise guide
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Marketing automation for dummies /
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Practical text mining and statistical analysis for non-structured text data applications
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