Abstract

Writing code which uses SQL Server Machine Learning Services is easy enough, but that is just the beginning of the story. In this talk, we will cover the rest of the R development story for database administrators. We will look at the methods available to install and maintain R packages, learn good practices for deploying and maintaining custom SQL Server Machine Learning Services code, and learn where to find critical information when things break. These battle-tested tips will make it easier for you to integrate R and SQL Server Machine Learning Services in your existing deployment processes and get the most out of this feature.


Slides

The slides are available as a GitPitch slide deck.

The slides are licensed under Creative Commons Attribution-ShareAlike.


Demo Code

The demonstration code is available on my GitHub repository. This includes a set of SQL and R scripts.

The source code is licensed under the terms offered by the GPL. The slides are licensed under Creative Commons Attribution-ShareAlike.


Links and Further Information

This talk looks suspiciously similar to my Launching a Data Science Project talk. There's a fair amount of overlap, particularly on the process slides, but if you want a deeper dive into a more realistic project than the Bills winning football games, check out the accompanying notebook as well as links to cool projects like MariFlow and MarIO.

Reading Material

Additional Resources