Microsoft R Server 9.0 released; Now available for download

In a short span of time, Microsoft has delivered many Microsoft R Server capabilities. The latest one, MRS 9.0 rolled out yesterday on MSDN and Visual Studio Dev Essentials, marks a culmination of all the hard work of the team this year. Yes, Microsoft has released Microsoft R Server 9.0 for public use.

The release, gives access to a powerful tool, supporting wide range of operating systems and a variety of data sources. Moreover, it comes with several new capabilities. For instance, in MRS 9.0, you can combine the algorithms with pre-existing parallel external memory algorithms such as the RevoScaleR package as well as open source innovations such as CRAN R packages to deliver the best predictive analytics.

Cortana and Machine learning blog

Microsoft R Server 9.0

In today’s modern age, consumers generate and consume vast amount of data every moment.  Data-driven marketing and predictive analytics are therefore becoming more prevalent. Predictive Analytics technique makes it possible to extract useful information from these data sets and analyze them in a way to estimate future outcomes. Why the need for such a technique? Big Data, alone, is not sufficient to provide insights about customer behavior. Predictive Analytics capabilities therefore assumes importance. The technique can transform big data into a more powerful tool by combining data sets in a more meaningful way to make educated guesses, particularly, about future events.

Existing solutions fall short in delivering sufficient insights. As such Microsoft, has stepped up investments in advanced analytics solutions.

Today, we are making Microsoft R Server 9.0 immediately available for download from MSDN and Visual Studio Dev Essentials. Packed with tons of value, and built on top of the latest open source R engine, Microsoft R Server (MRS) version 9.0 includes several exciting new capabilities”, mentions Cortana and Machine learning blog.

MicrosoftML includes following algorithms:

  1. Fast linear learner, with support for L1 and L2 regularization.
  2. Logistic regression, with support for L1 and L2 regularization
  3. Fast random forest
  4. Fast boosted decision tree
  5. GPU-accelerated Deep Neural Networks (DNNs) with convolutions.
  6. Binary classification using a One-Class Support Vector Machine.

In addition to the above, Microsoft R Server 9.0 improves on operational capabilities which allows you to get your R models deployed ever more efficiently, irrespective of your data residing on ground premises or in the cloud.

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The author Hemant Saxena is a post-graduate in technology and has an immense interest in following Microsoft and other technology developments around the world. Quiet by nature, he is an avid Lacrosse player.

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