What's new in Machine Learning Server

Applies to: Machine Learning Server                       (Find R Server 9.x What's New)

Machine Learning Server 9.2.1 expands upon Microsoft R Server 9.1 with new Python libraries for integrating machine learning and data science into analytical solutions in the enterprise. Language-specific development is available when you add Python or R support (or both) during setup.

Python development

In Machine Learning Server, Python support is through libraries that can be used in script executing locally, or remotely in either Spark over Hadoop Distributed File System (HDFS) or in a SQL Server compute context.

Python libraries include revoscalepy, microsoftml, and azureml-model-management-sdk. Modules are built on Anaconda 4.2 over Python 3.5. You can run any 3.5-compatible library on a Python interpreter included in Machine Learning Server.

Together, the libraries provide full-spectrum data mining: data transformation and manipulation, analysis and visualization, model management. Machine learning algorithms, as well as pre-trained models provided by Microsoft, are now in Python.


Remote execution is not available for Python scripts. For information about to do this in R, see Remote execution in R.

R development

  • R function libraries are built on Microsoft R Open (MRO), Microsoft's distribution of open source R 3.4.1.

  • R realtime model scoring is now also supported on Linux.

  • The last several releases of R Server added substantial capability for R developers. To review recent additions to R functionality, see feature announcements for previous versions.


Previous versions

Visit Feature announcements in R Server version 9.1 and earlier, for descriptions of features added in recent past releases.

See Also

Welcome to Machine Learning Server

Install Machine Learning Server on Windows

Install Machine Learning Server on Linux

Install Machine Learning Server on Hadoop

Configure Machine Learning Server to operationalize your analytics