Blog Archives

How R is used at Microsoft

July 15, 2016
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At the useR! conference last month, I was pleased to be able to give a couple of talks about the ways that Microsoft is using and integrating R. In my first talk, Hear, See, Move, I shared how data scientists at Microsoft are working to help the disabled: During the talk I gave some pointers to some of the...

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Introducing the free Microsoft R Client

July 11, 2016
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Over the years, we've shared several posts on using the ScaleR package to import, process, visualize and analyze large data sets with R. Until now, you needed to have access to a Microsoft R Server license to take advantage of the package. Now, you can use all of the capabilities of ScaleR free of charge with Microsoft R Client...

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In case you missed it: June 2016 roundup

July 8, 2016
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In case you missed them, here are some articles from June of particular interest to R users. A preview of the tutorials presented at the useR! 2016 conference. A "advanced beginner's" guide to R published by ComputerWorld includes guides on data wrangling, visualization, and data APIs. Microsoft R Server now runs on Apache Spark, bringing high performance to big-data...

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The history of R’s predecessor, S, from co-creator Rick Becker

July 6, 2016
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The history of R’s predecessor, S, from co-creator Rick Becker

Before there was R, there was S. R was modeled on a language developed at AT&T Bell Labs starting in 1976 by Rick Becker and John Chambers (and, later, Alan Wilks) along with Doug Dunn, Jean McRae, and Judy Schilling. At last week's useR! conference, Rick Becker gave a fascinating keynote address, Forty Years of S. His talk recounts...

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Run compiled R packages in AzureML

July 1, 2016
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Run compiled R packages in AzureML

We've shown a few times here how you can run R code on data in the cloud with Azure ML Studio, and even how to enable that code as a web service to be called from other applications. But what if you want to run code in a compiled language, like C++? Fortunately, you can take advantage of R's...

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Computerworld’s advanced beginner’s guide to R

June 29, 2016
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Computerworld’s advanced beginner’s guide to R

Many newcomers to R got their start learning the language with Computerworld's Beginner's Guide to R, a 6-part introduction to the basics of the language. Now, budding R users who want to take their skills to the next level have a new guide to help them: Computerword's Advanced Beginner's Guide to R. Written by Sharon Machlis, author of the...

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Livestreaming of useR! 2016 conference begins tomorrow, June 28

June 27, 2016
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Livestreaming of useR! 2016 conference begins tomorrow, June 28

The useR! 2016 conference, the annual gathering of R users from around the world, is already underway at Stanford University. Today is a day of interactive tutorials, and the presentation program begins tomorrow. But don't worry if you weren't able to make it to California, or if you missed out on getting a ticket for the conference. (You're not...

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Amazon X-ray data provides insight into movie characters

June 24, 2016
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Amazon X-ray data provides insight into movie characters

I'm a regular user of Amazon Video: as someone who spends a fair bit of time on planes, it's great to be able to download some of my favourite shows (hello, Orphan Black and Vikings) and catch up on episodes during the trip. Amazon Video has a useful feature, too: if you forget the name of a character, or...

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R 3.3.1 now available

June 22, 2016
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Peter Dalgaard announced yesterday on behalf of the R core team that R 3.3.1, the latest update to the R language, is now available for download from your local CRAN mirror. As of this writing, binaries of R 3.3.1 are available for Windows and Linux; the Mac version should appear very soon. This minor update, codenamed "Bug in Your...

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Updates to the ‘forecast’ package for R

June 20, 2016
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Updates to the ‘forecast’ package for R

The forecast package for R, created and maintained by Professor Rob Hyndman of Monash University, is one of the more useful R packages available available on CRAN. Statistical forecasting — the process of predicting the future value of a time series — is used in just about every realm of data analysis, whether it's trying to predict a future...

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