Machine Learning Services

A Revolution in Advanced Analytics

We hope you enjoy this collection of resources for Machine Learning & R Services. Keep an eye on the BlueGranite Blog and Resources for additional Microsoft R and advanced analytics posts and videos.

TUTORIALS

SQL Server

SQL Server R Services

This tutorial walks through some basic development and deployment scenarios for R Services in SQL Server 2016. You will use sample order data and take R code that can be run standalone in RStudio or another R IDE, adapt it for use in SQL Server, and then consume it both in SQL Management Studio as well as from Reporting Services.

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SQL Server R Services

R Services on HD Insight

R Server on Azure HDInsight is a convenient way to utilize R in a distributed environment. In this tutorial, you will create an HDInsight cluster that includes R Server using the Azure Portal. You will then install RStudio on the R Server edge node. Finally, you will use R to manage HDFS resources, change compute contexts, and build models under each context. General familiarity with HDInsight, HDFS, and R is assumed.

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Power BI and R

Power BI and R

There are two different ways to apply R in Power BI: the R Script for loading and transforming data, and the R Visual for additional enhancement and data visualization. This tutorial walks through a basic scenario using both.

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Power-Bi-Interactive-R-Custom-Visual

POWER BI INTERACTIVE R CUSTOM VISUAL

This tutorial steps through the process of adding a sample R HTML visual, viewing it in Power BI Service, and altering the R script to quickly change the appearance of the custom visual.

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Recorded Webinar

Advanced Analytics
and Microsoft R

R statistical computing has grown from a research and prototyping tool into a key component of commercial analytics platforms. The greatest evidence of this may be in Microsoft’s acquisition and subsequent embedding of Revolution R in its key data and analytics technologies.

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WEBINAR TOPICS INCLUDE:

  • An introduction to the R platform – including a getting started guide
  • An overview of the major components of the Microsoft R ecosystem – including features of parallel processing on big data, and using R in environments like SQL Server 2016, PowerBI, and Hadoop
  • A demonstration of R in action in multiple platforms – from prototyping to production