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The go-to bible for this data scientist and many others is The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, and Jerome Friedman. Each of the authors is an expert in machine learning / prediction, and in some cases invented the techniques we turn to today to make sense of big data: ensemble learning methods, penalized regression, additive models and nonparemetric smoothing, and much much more.

This year's R/Finance conference on applied finance with R is scheduled for May 17-18 in Chicago, and promises once again to be the go-to conference for anyone using R in the finance industry. The keynote speakers have been announced, and it's a great lineup:

Melbourne's transit operator Metro Trains wanted to create a campaign to get out train safety messages to people who normally wouldn't pay attention to them. They succeeded: this adorably dark PSA (with a song in the style of — but not, as I thought, by — the awesome Of Monsters and Men) was a viral hit, generating more than 35 million views and a worldwide top-10 song on iTunes:

 

We've mentioned before how you can use R to design 3-D objects. Now, thanks to the latest version of the rgl package, you can produce real-world 3-D objects with R as well.

The rgl package has long made it possible to create virtual 3-D objects in R, and export them as animations like this:

 

'If you mindlessly apply "'data' is always plural", in the manner of a word-processor grammar checker, you'll end up with hideous infelicities like "big data are helping banks", and you'll look stupid as well as precious. So don't do that.', says Tom Chivers at The Telegraph. (via Matt Asay)

Sean Taylor, a PhD candidate in Information Systems at NYU’s Stern School of Business, describes the "Statistics Software Signal" and his observation that some software packages are correlated with bad science.

Ringing in the New Year, Peter Dalgaard announced yesterday on behalf of the entire R Core Team that the R language will graduate to Version 3 around April 1. This is only the third time that R has incremented its primary version number. Version 1.0.0 (released on February 29, 2000) was the first version deemed stable for production use. R moved to version 2.0.0 on October 4, 2004 once some major language features (the S4 object system) and platforms (MacOS) were established.

Today's the Christmas holiday in the US and many other places around the world. Wherever you may be, have a happy and safe holiday season. Best wishes go to our customers, partners and the entire R community from the team at Revolution Analytics. 


Some of the Revolution Analytics team (and significant others) photographed at our holiday party at the Chihuly Garden and Glass Museum in Seattle.