Category: R Programming

It would be difficult for an R user not to have heard of GPU processing. In 2006, about seven years after it invented the GPU, Nvidia released the first incarnation of CUDA, the architecture that allowed scientists, engineers, and statisticians to use high-end graphics processors as pure floating-point number-crunchers. Today, Nvidia’s CUDA platform, specific for […]

The RevoscaleR functions provided by Microsoft in Machine Learning Server and MS R Client are many and varied, as are the parameters are passed to control their behavior. But while it might seem a bit overwhelming at first, it is really quite simple. Except for the fact that ETL generally reads and writes to multiple […]

Choosing a machine learning (ML) platform can be a cause of considerable stress. It’s a major commitment you will have to live with for years and an unwise decision might even affect your job prospects. Fortunately, asking yourself a few fundamental questions can simply the decision considerably. Are you primarily a Windows Shop? In recent […]

Using Microsoft olapR to Bring Analysis Services OLAP Data Into R Online Anaytical Processing (OLAP) and the R statistical language are both children of the 1990s. However, for much of the intervening time they inhabited different worlds. OLAP, and its query language MDX, lived in the world of databases and queries while R was the […]

Microsoft asserts that SQL Server is the first database with “built-in” artificial intelligence. Of course, no phrase suffers more definitions than “artificial intelligence”, so rather than quibble about AI, we’ll just take a look at the technologies that support Microsoft’s claim. Moving Machine Learning to the Server-Side Great excitement followed the introduction of the integration […]