Blog Archives

In case you missed it: October 2014 Roundup

November 12, 2014
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In case you missed them, here are some articles from October of particular interest to R users. R hits a new milestone with 6,000 CRAN packages, and R 3.1.2 released. Revolution Analytics announces Revolution R Open, a supported and enhanced downstream distribution of R. (Learn more at the webinar on Wednesday November 12.) Some benchmarks on the performance improvements...

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Benchmarking Revolution R Open on Linux

November 10, 2014
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Benchmarking Revolution R Open on Linux

We recently shared some benchmarks for Revolution R Open on the Windows platform, which showed significant improvements compared to R downloaded from CRAN. Those performance gains mainly come from multi-threading: Revolution R Open is linked to the Intel Math Kernel Library, which uses all available cores (rather than just one core) to compute matrix and vector operations in parallel....

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Learn about Revolution R Open in live webinar, November 12

November 7, 2014
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On Wednesday next week, I'll be presenting a live webinar to introduce Revolution R Open and several other open source projects from Revolution Analytics. In the webinar I'll describe: The enhancements included in Revolution R Open The Reproducible R Toolkit and the checkpoint package How to call R from other applications with DeployR Open How to run R in...

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Running R in the Azure ML cloud

November 3, 2014
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The key to making data science successful is making sure you can deploy the machine learning code that data scientists create into applications that rely on the results of the analysis. Microsoft has tackled this problem with Azure ML: machine learning in the cloud. This short video neatly summarizes the process of deploying R code to the cloud in...

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R 3.1.2 released with over 6,000 CRAN packages available

October 31, 2014
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The latest update to the world's most popular statistical data analysis software is now available. R 3.1.2 (codename: "Pumpkin Helmet") makes a number of minor improvements and bug fixes to the R language engine. You can see the complete list of changes here, which include improvements for the log-Normal distribution function, improved axis controls for histograms, a fix to...

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Integrate R into applications with DeployR Open

October 29, 2014
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Integrate R into applications with DeployR Open

If you ever find you need to embed the results of R functions — data, charts, or even a single calculation — into other applications, then you might want to take a look at DeployR Open. DeployR Open is an open-source server-based framework for R, that makes it easy to call out to the server to run R code...

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Create Fashion Fingerprints with R

October 27, 2014
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Create Fashion Fingerprints with R

How do you summarize fashion? For New York Fashion Week, the New York Times used the idea of "Fashion Fingerprints", distilling a designer's collections into small fragments highlighting the palette. Here's what Marc Jacobs' current collection looks like: Click through for an interactive version where you can explore each design, and scroll down to the bottom where you can...

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Rocker: Docker containers for R

October 24, 2014
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If you haven't heard the buzz about Docker but you often need to spin up Linux-based VM's for testing, simulations, etc. then you should check it out. In short, Docker rocks: we use it for testing our Linux-based distros of Revolution R Open. If you want to use R and Docker together, Dirk Eddelbuettel and Carl Boettiger have made...

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Explore R package connections at MRAN

October 20, 2014
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Explore R package connections at MRAN

Many R scripts depend on CRAN packages, and most CRAN packages in turn depend on other CRAN packages. If you install an R package, you'll also be installing its dependencies to make it work, and possibly other packages as well to enable its full functionality. My colleague Andrie posted some R code to map package dependencies a couple of...

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Statistics doesn’t have to be so hard: simulate!

October 17, 2014
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My second-favourite keynote from yesterday's Strata Hadoop World conference was this one, from Pinterest's John Rauser. To many people (especially in the Big Data world), Statistics is a series of complex equations, but a just a little intuition goes a long way to really understanding data. John illustrates this wonderfully using an example of data collected to determine whether...

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