The Microsoft Data Science Virtual machine (VM) is a custom Azure VM based on Windows Server 2012 with several popular tools for data science modeling/development like: * SQL Server 2016 Developer Edition * Microsoft R server Developer Edition * Anaconda Python with Juypter notebooks * Visual Studio 2015 Community edition with language and Azure tools and * ML and Deep Learning tools like xgboost, CNTK, mxnet More information on how to use the VM can be found on the [documentation page](http://aka.ms/dsvmdoc). If are wondering about things you can do with the DSVM read this [How-To Guide to the Data Science Virtual Machine](http://aka.ms/dsvmtenthings). Here is a list of key software on the Data Science Virtual Machine and comparison between the Windows and Linux editions of the product.

Microsoft R Server 9.0.1 (MRS9) developer edition, a major update to the enterprise scalable R extension from Microsoft, is now available on the VM. This version brings a lot of exciting changes including several fast ML / deep learning algorithms developed by Microsoft in a new library called Microsoft ML. There's a new architecture and interface for deploying R models and functions as web services, this follows a paradigm and interface library very similar to Azure ML operationalization. The library is called mrsdeploy. We have some R deployment samples for both notebook and R Tools for Visual Studio (RTVS) and RStudio.