Matt Willis has a two-parter on R Tools for Visual Studio. First, an introduction:
Once all the prerequisites have been installed it is time to move onto the fun stuff! Open up Visual Studio 2015 and add an R Project: File > Add > New Project and select R. You will be presented with the screen below, name the project AutomobileRegression and select OK.
Microsoft have done a fantastic job realising that the settings and toolbar required in R is very different to those required when using Visual Studio, so they have split them out and made it very easy to switch between the two. To switch to the settings designed for using R go to R Tools > Data Science Settings you’ll be presented with two pop ups select Yes on both to proceed. This will now allow you to use all those nifty shortcuts you have learnt to use in RStudio. Anytime you want to go back to the original settings you can do so by going to Tools > Import/Export Settings.
Whilst in R you can implement very complex Machine Learning algorithms, for anyone new to Machine Learning I personally believe Azure Machine Learning is a more suitable tool for being introduced to the concepts.
Please refer to this blog where I have described how to create the Azure Machine Learning web service I will be using in the next section of this blog. You can either use your own web service or follow my other blog, which has been especially written to allow you to follow along with this blog.
Coming back to RTVS we want to execute the web service we have created.
RTVS has grown on me. It’s still not R Studio and may never be, but they’ve come a long way in a few months.