For those who might be wondering, the programming language was created by Ross Ihaka and Robert Gentleman in 1993. Furthermore, note that most of the R libraries are written using R, but for others, C ...

This story contains interviews with David Smith, chief community officer at Revolution Analytics; Casey Herron, data scientist at Revolution Analytics; Tess Nesbitt, director of analytics at DataSong; ...

The R programming language is quickly gaining popular ground against the traditional statistics packages such as SPSS, SAS and MATLAB, at least according to one data statistician who teaches the ...

But data science is a specific field, so while Python is emerging as the most popular language in the world, R still has its place and has advantages for those doing data analysis. Hoping to settle ...

I 'm a big fan of Python for data analysis, but even I get curious about what else is available. R has long been the go-to ...

The functions .C and .Call. provide a standard interface to compiled code that has been linked into R. These functions are explored in the following presentation.

Programming has become essential for looking at large datasets, and the R language is particularly useful for statistical analysis. With the R Programming Language Compiler app, you can now test and ...

A few years ago, I was the CTO and cofounder of a startup in the medical practice management software space. One of the problems we were trying to solve was how medical office visit schedules can ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

Java can handle large workloads, and even if it hits limitations, peripheral JVM languages such as Scala and Kotlin can pick up the slack. But in the world of data science, Java isn't always the go-to ...