Feature Improvements In Microsoft R Server 9.1

David Smith gives us a nice roundup of feature improvements in Microsoft R Server 9.1:

Interoperability between Microsoft R Server and sparklyr. You can now use RStudio’s sparklyr package in tandem with Microsoft R Server in a single Spark session

New machine learning models in Hadoop and Spark. The new machine learning functions introduced with Version 9.0 (such as FastRank gradient-boosted trees and GPU-accelerated deep neural networks) are now available in the Hadoop and Spark contexts in addition to standalone servers and within SQL Server.

I have been looking forward to these.

Related Posts

Logistic Regression In R

Steph Locke has a presentation on performing logistic regression using R: Logistic regressions are a great tool for predicting outcomes that are categorical. They use a transformation function based on probability to perform a linear regression. This makes them easy to interpret and implement in other systems. Logistic regressions can be used to perform a classification […]

Read More

SQL Server ML Services

SQL Server R Services is now SQL Server Machine Learning Services and supports Python.  First, Nagesh Pabbisetty and Sumit Kumar talk about Python support: The addition of Python builds on the foundation laid for R Services in SQL Server 2016 and extends that mechanism to include Python support for in-database analytics and machine learning. We are […]

Read More

Leave a Reply

Your email address will not be published. Required fields are marked *

Categories

April 2017
MTWTFSS
« Mar  
 12
3456789
10111213141516
17181920212223
24252627282930