Extend the analytics capabilities of the R and Python open-source languages

Analyze data where it lives

Use your existing tools to apply advanced analytics to on-premises, hybrid, or cloud-based data.

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Innovate using AI

Create smarter apps with industry-leading artificial intelligence (AI) and leading machine learning capabilities.

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Build mission-critical apps faster

Move quickly from lab to production at scale with enterprise-grade security and support.

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Simplify deployment of your analytics models

Integrate analytics faster with apps written in any language and score easily across data platforms using web services and your preferred development environment.

See how to make analytics operational using Machine Learning Server

Develop and run R and Python models on your platform of choice

Run in-database analytics in Microsoft SQL Server and Teradata, and enable Windows, Linux, Hadoop or Apache Spark-based predictive analytics to maximize your open-source investments at scale.

Gain insights right from your database

Bring scalable R and Python based analytics to where your data lives—directly in your Microsoft SQL Server database, and reduce the risk, time, and cost associated with data movement.

Get started with SQL Server Machine Learning Services

Integrate with Microsoft Azure for scalable cloud-based processing

Gain even more speed and flexibility for your R data analytics. Deploy Machine Learning Server as part of your Azure subscription.

Create a Machine Learning Server virtual machine
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