Blog Archives

Slides for Revolution R Enterprise: 100% R and more

October 20, 2011
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If you haven't yet taken a look at Revolution R Enterprise but wanted to know what is adds to open-source R, the slides below from yesterday's webinar will give you a quick overview: A recorded replay with audio of the me giving the presentation is also available at the link below. Revolution Analytics Webinars: Revolution R Enterprise: 100% R...

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The R-Files: Paul Teetor

October 19, 2011
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The R-Files: Paul Teetor

"The R-Files" is an occasional series from Revolution Analytics, where we profile prominent members of the R Community. Name: Paul Teetor Profession: Quantitative developer (freelance) Nationality: American Years Using R: 7 Known for: Author of R Cookbook (O’Reilly Media, 2011) An active member of the R community, Paul Teetor is a quantitative developer and statistical consultant based in the...

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Revolution Newsletter: October 2011

October 17, 2011
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The most recent edition of the Revolution Newsletter is out. The news section is below, and you can read the full October edition (with highlights from this blog and community events) online. You can subscribe to the Revolution Newsletter to get it monthly via email. Applications of R Contest: Deadline October 31. Revolution Analytics is offering $20,000 in prizes...

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Implementing K-means clustering for Hadoop in R and Java

October 14, 2011
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Implementing K-means clustering for Hadoop in R and Java

At the Bay Area R User Group meeting this week, Antonio Piccolboni gave an overview of the design goals and implementation of the RHadoop Project packages that connect Hadoop and R: rhdfs, rhbase and rmr: (The image above was captured from Antionio's slides.) The most revealing part of the talk for me was the comparison of implementing the K-means...

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Tomorrow: ACM Data Mining Camp at eBay

October 14, 2011
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If you're in the Bay Area, tomorrow would be a great day to head down to San José for the ACM Data Mining Camp. Hundreds of data scientists, data hackers and data miners will be there for a fun "unconference", with talks and practical sessions organized on the spot according to demand. Revolution Analytics is proud to be a...

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There’s a lot to like about R

October 13, 2011
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I once heard John Chambers (the inventor of the S language, and member of the R Core Group) say, "Show me a programming language no-one complains about, and I'll show you a language no-one uses". The R language has its fair share of complainants, to be sure -- and that's to be expected for a language with more than...

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Slides and replay for "Introduction to R for SAS and SPSS users"

October 12, 2011
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If you missed last week's webinar from Bob Muenchen, "Introduction to R for SAS and SPSS users", you missed a great overview of the R Project and how it compares to commercial statistical software. Bob's slides are below, and you can download the slides and replay from the Revolution Analytics website. Bob pointed out a couple of really useful...

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Top 50 Statistics blogs

October 10, 2011
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TheBestColleges.org has just published their list of the "Top 50 Statistics Blogs of 2011", and I'm pleased say that not only did our own Revolutions blog make the list, but it's in fine company with some truly excellent blogs. Several of my personal favourites made the list, including: Guardian columnist Ben Goldacre's Bad Science blog The Dataists, a blog...

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Because it’s Friday: Reviews of Random Digits

October 7, 2011
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If you dig around enough on Amazon.com, you can find some pretty odd products (like the Badonkadonk tank now sadly unavailable). Attached to these products you can often find a new form of comedy: the funny Amazon review. The products that attract such attention can be hard to fathom: this gallon of milk has more than 1,000 reviews. (Sample:...

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In case you missed it: September Roundup

October 7, 2011
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In case you missed them, here are some articles from September of particular interest to R users. The deadline to enter the "R Applications" contest with $20,000 in prizes is October 31. The RHadoop Project, a new collection of open-source R packages from Revolution Analytics, makes it possible to write map-reduce jobs in R to analyze huge data sets...

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