In Azure ML Studio, you use a browser-based “workbench” tool to flow data through pre-built data munging, machine learning and predictive modeling modules. These pre-built components perform computations in the Azure cloud and cover just about everything you'd want to do with data, including data transformation tools (add/remove columns, split data), variable selection, statistical and machine learning functions (classification, clustering, regression), and even text analytics. For everything else, you can use a language module that allows you to pass the data stream through any R or Python script, which gives you pretty much unlimited flexibility in how you handle the data. (If you're new to ML Studio, these videos will help you get started, including how to sign up for a free trial account.)
ML studio now gives you even more flexibility, with new language engines supported in the language modules. Within the Execute Python Script module, you can now choose to use Python 2.7.11 or Python 3.5, both of which run within the Acaconda 4.0 distribution. And within the Execute R Script module, you can now choose Microsoft R Open 3.2.2 as your R engine, in addition to the existing CRAN R 3.1.0 engine. Microsoft R Open 3.2.2 not only gives you a newer R language engine, it also gives you access to a wealth of new R packages for use within ML Studio. Over 400 packages are pre-installed for use with the R Script module, and you can install and use any other R package (including CRAN packages and your own R packages) via the Script Bundle input port.
The new Execute R Script and Execure Python Script modules are available in Azure ML Studio now. For more information on the new features, follow the link below.
Cortana Intelligence and Machine Learning Blog: Azure ML Now Supports Multiple R & Python Versions, Including Microsoft R Open & Python 3