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By Mike Bowles

Ensemble methods are the backbone of machine learning techniques. However, it can be a daunting subject for someone approaching it for the first time, so we asked Mike Bowles, machine learning expert and serial entrepreneur to provide some context.

The fine folks behind the Big Data Journal have just published a new e-book Big Data: Harnessing the Power of Big Data Through Education and Data-Driven Decision Making. (Note: Adobe Flash is required to view the e-book.) In the eBook, you'll find the following technical papers on the topics of Big Data, Data Science, and R:

Europe's borders are changing again. This is big news, but you might be surprised to find out just how malleable the borders in Europe have been over the past 1000 years, as this timelapse map shows:

 

Most people know R as a statistics/analytics language for analysis of quantitative data, and don't think of it as a tool for processing raw text. But R actually has some quite powerful facilities for processing character data. And as Gaston Sanchez learned, text manipulation is an important part of a modern data scientist's repertoire:

If you're still working on your March Madness brackets or fantasy teams, Rodrigo Zamith has updated his NCAA Data Visualizer with the latest teams, players and results. Just choose the two teams you want to compare and the metric to compare them on, and this R-based app will show you the results instantly.

If you're a student and you'd like to improve R by developing a new R package for 3 months over the summer — and get paid $5000 by Google in the process — why not apply for an R project in the Google Summer of Code?

by James Paul Peruvankal, Senior Program Manager at Revolution Analytics

CARE International is a humanitarian organization that is leading the charge to fight poverty around the world, with a focus on empowering women and girls. On March 28 in Atlanta, CARE is teaming up with Booz Allen Hamilton, Emory University's Rollins School of Public Health and Revolution Analytics to bring data scientists together to use R to explore some of CARE's data troves and — hopefully! — make discoveries that will further CARE's mission.