Revolutions

Microsoft ML Server 9.4 now available

Microsoft Machine Learning Server, the enhanced deployment platform for R and Python applications, has been updated to version 9.4. This update includes the open source R 3.5.2 and Python 3.7.1 engines, and supports integration with Spark 2.4. Microsoft ML Server also includes specialized R packages and Python modules focused on application deployment, scalable machine learning, and integration with SQL Server.

Microsoft Machine Learning Server is used by organizations that need to use R and/or Python code in production applications. For some examples of deployments, take a look at these open-source solution templates for credit risk estimation, energy demand forecasting, fraud detection and many other applications.

Microsoft ML Server 9.4 is available now. For more details on this update, take a look at the announcement at the link below.

SQL Server Blog: Microsoft Machine Learning Server 9.4 is now available 

Watch keynote presentations from the useR!2019 conference

The keynote presentations from last week's useR!2019 conference in Toulouse are now available for everyone to view on YouTube. (The regular talks were also recorded and video should follow soon, and slides for most talks are available for download now at the conference website.) Here are links to the videos, indexed to the start of each presentation:

• Shiny's Holy Grail: Interactivity with reproducibility.  Joe Cheng, Chief Technology Officer at RStudio 
• "AI for Good" in the R and Python ecosystems. Julien Cornebise, Director of Research at Element AI
• Tools for Model-Based Clustering in R. Bettina Grün, Professor at Johannes Kepler Universität Linz
• A missing value tour in R. Julie Josse, Professor at École Polytechnique
• How Bioconductor advances science while contributing to the R language and community. Martin Morgan, Professor at Roswell Park Comprehensive Cancer Center and Bioconductor
• R for better science in less time. Julia Stewart Lowndes, Mozilla Fellow and Marine Data Scientist at NCEAS

All of the presentations are excellent, but if I had to choose one to watch first, it would be Julia Stewart Lowndes' presentation, which is an inspiring example of how R has enabled marine researchers to collaborate and learn from data (like a transponder-equipped squid!). 

The videos have been made available thanks to sponsorship by the R Consortium. If you're not familiar with the R Consortium, you can learn more in the short presentation below from Joe Rickert:

The R Consortium is funded by its member organizations, so if you'd like to see more of the above, consider asking your company to become a member.

YouTube (R Consortium): 2019 Keynotes

R 3.6.1 is now available

On July 5, the R Core Group released the source code for the latest update to R, R 3.6.1, and binaries are now available to download for Windows, Linux and Mac from your local CRAN mirror.

R 3.6.1 is a minor update to R that fixes a few bugs. As usual with a minor release, this version is backwards-compatible with R 3.6.0 and remains compatible with your installed packages. Nonetheless, an upgrade is recommended to address issues including:

• A fix for "lock errors" when attempting to re-install packages on Windows
• Efficiency improvements and other fixes when using "quasi" links with Generalized Linear Models
• Fixed axis labels for boxplots
• writeClipboard on Windows now supports Unicode, so you can copy text with special characters from R for pasting

See the release notes for the complete list.

By long tradition the code name for this release, "Action of the Toes", is likely a reference to the Peanuts comic. If you know specifically which one, let us know in the comments!

R-announce mailing list: R 3.6.1 is released

Updates on Microsoft's R Roadmap in Azure

Yesterday, Microsoft's AI Customer Engineering Team posted the first in a series of blog posts on the state and future of support for R in Azure. Check out that post for some details on the forthcoming capabilities to support R and Python-based deployments in the Azure cloud service. 

The post references this guide to the machine learning services in Azure, along with their supported languages. Services that currently support R include Azure Machine Learning Studio, SQL Server Microsoft Machine Learning Service, Microsoft Machine Learning Server, Azure Data Science Virtual Machine, Azure Databricks, and more.

The post also notes that Microsoft is committed to bring R support to Azure Machine Learning Services. (I'll have further news about that in my talk at the useR conference in Toulouse.)

Future posts in the series will cover:

• A deeper dive on R operationalization options
• Big Data architectural topologies with R
• Orchestrating mixed R and Python Machine Learning pipelines with Azure Machine Learning Services

I'll provide links to those posts on this blog when they're published as well.

Microsoft Tech Communities: Understanding your R strategy options on the Azure AI Platform