Blog Archives

Microsoft R Open 3.3.2 now available

November 30, 2016
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Microsoft R Open 3.3.2, Microsoft's enhanced distribution of open source R, is now available for download for Windows, Mac, and Linux. This update upgrades the R language engine to version 3.3.2, adds new bundled packages and updates others, and upgrades the Intel Math Kernel Libraries. The updated R 3.3.2 engine includes some performance improvements (particularly in calculation of eigenvalues),...

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Free online course: Analyzing big data with Microsoft R Server

November 29, 2016
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If you're already familiar with R, but struggling with out-of-memory or performance problems when attempting to analyze large data sets, you might want to check out this new EdX course, Analyzing Big Data with Microsoft R Server, presented by my colleague Seth Mottaghinejad. In the course, you'll learn how to build models using the RevoScaleR package, and deploy those...

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A heat map of Divvy bike riders in Chicago

November 28, 2016
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A heat map of Divvy bike riders in Chicago

Chicago's a great city for a bike-sharing service. It's pretty flat, and there are lots of wide roads with cycle lanes. I love Divvy and use it all the time. Not so much in the winter though: it gets very cold here. Nonetheless, this heat map of Divvy riders, created in R by Austin Wehrwein, reveals a hardcore set...

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Happy Thanksgiving! (2016)

November 24, 2016
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Happy Thanksgiving! (2016)

It's Thanksgiving day here in the US, so we're taking the rest of the week off to reflect on what we're thankful for. And even if you're not in the US, today is a great day to send thanks to the R Core Group for providing their dedication, time, and expertise to make the R Project what it is...

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Tutorial: Build a live rental prediction service with SQL Server R Services

November 23, 2016
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Tutorial: Build a live rental prediction service with SQL Server R Services

A great way to learn is by doing, so if you've been thinking about how to enable R-based computations within SQL Server, a new tutorial will take you through all the steps of building an intelligent application. In a few simple steps, you'll set up all the necessary software and code to build a live service that predicts demand...

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The 5 most popular R packages

November 18, 2016
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The good folks at DataCamp track activity related to R packages on the RDocumentation.org Trends page. As of this writing, it tracks statistics on 11,768 packages (distributed across CRAN, BioConductor and Github) comprising over 1.7 million R functions in total. On that page, you can find current rankings on the most downloaded R packages, the most prolific package contributors,...

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Notable New and Updated R packages (to October 2016)

November 17, 2016
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As we prepare for the upcoming release of Microsoft R Open, I've been preparing the list of new and updated packages for the spotlights page. This involves scanning the CRANberries feed (with gracious thanks to Dirk Eddelbuettel) for newly-released packages and significant updates to existing ones. This is a lot of data to process. For context, in October 2016...

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How to call Cognitive Services APIs with R

November 16, 2016
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Microsoft Cognitive Services is a set of cloud-based machine-intelligence APIs that you can use to extract structured data from complex sources (unstructured text, images, video and audio), and add "AI" type features to applications. A good example is the "Seeing AI" glasses in the video below: the image descriptions, emotion inference, and text recognition are all driven by Cognitive...

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In case you missed it: October 2016 roundup

November 15, 2016
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In case you missed them, here are some articles from October of particular interest to R users. A brief summary of the R 3.3.2 release. "Data Science with SQL Server 2016", a free E-book featuring several in-depth R examples, is now available for download. The ReporterRs package makes it easy to insert R output, tables and graphics into Word...

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A computer vision challenge: finding boats in the Mona Lisa

November 11, 2016
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A computer vision challenge: finding boats in the Mona Lisa

About a decade or so photomosaics were all the rage: a near-recreation of a famous image by using many smaller images as elements. Here, for example, is the Mona Lisa, created using the Metapixel program by overlaying 32x32 images of vehicles and animals. An image like this presents an interesting computer vision challenge: can you use deep learning techniques...

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