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Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python by Thomas W. Miller

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D. Code and Utilities

Doing marketing data science with R means looking for task views posted with the Comprehensive R Archive Network (CRAN). We go to RForge and GitHub. We read package vignettes and papers in The R Journal and the Journal of Statistical Software. At the time of this writing, the R programming environment consists of more than 5,000 packages, many of them focused on modeling methods. Useful general references for learning R include Fox and Weisberg (2011), Matloff (2011) and Wickham (2015). Chambers and Hastie (1992) and Venables and Ripley (2002), although written with S/SPlus in mind, remain critical references in the statistical programming community.

Doing marketing data science with Python means gathering programs and documentation ...

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