Linux Data Science Virtual Machine: new and upgraded tools

September 20, 2016

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

The Linux edition of the Data Science Virtual Machine on Microsoft Azure was recently upgraded. The Linux DSVM includes Microsoft R, Anaconda Python, Jupyter, CNTK and many other data science and machine learning tools, new or upgraded for this release. This eWeek story gives an overview of the improvements, but the highlights are:

  • Microsoft R Server (developer edition) is now included. This includes the complete R distribution from CRAN, plus additional data-analysis functions with big-data capabilities, and the DeployR framework for integrating R into applications as a web service. (The developer edition is identical to the enterprise Microsoft R Server edition, but licensed for development/test use.).
  • JupyterHub is now included, allowing multiple users to collaborate on Jupyter Notebooks (including R and/or Python code) simultaneously.
  • A new data science language, Julia, is now included. You can program in Julia from the command line or from a Jupyter notebook. 

Linux dsvm banner

The Windows edition of the Data Science VM has also been updated, and now includes SQL Server 2016 (developer edition) with R Services for in-database R processing.

Both editions of the Data Science VM are available on Microsoft Azure in a variety of configurations of RAM, cores, and disk. There are no software costs; you pay only the hourly Azure infrastructure charge to use it. For more details on the improvements to the Data Science Virtual Machine, follow the link to the blog post below.

Cortana Intelligence and Machine Learning Blog: Recent Updates to the Microsoft Data Science Virtual Machine 


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