Nine lightning talks on R
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At Tuesday's Bay Area R User Group meetup, nine speakers gave five-minute talks on various aspects of R. Revolution Analytics' Luba Gloukhov was one of the presenters, and also provides the summary of the talks below. Links to the slides are included where available for you to check out.
Ariel Faigon: Chrestomathy with R
Ariel walked us through his quest for the perfect language, one of minimal syntax. “If you want some fluff, go pet a bunny.” Ariel compared syntax of different languages in tackling textbook problems like printing the first N squares.
Luba Gloukhov : Interactive maps with R
I presented my visual exploration of the million song (sub)-dataset, and demoed an interactive Google map with embedded YouTube video search results.
Dan Putler (in collaboration with Brett Gottdener and Richard Snow): Election Prediction with R
Dan gave us a preview of Alteryx's forthcoming Presidential Election Preference Application. Given a zip code, the R-driven application provides local area estimates of presidential preferences.
Andrew Fisher: Automatic Forecasting in R
Andy highlighted Rob Hyndman's forecast package for automatic forecasting in supply chain management. He discussed the advantages of the forecast package over the standard stat package offering and also noted additional considerations aren't addressed by forecast.
Graham Goldbeck: R and Baseball
Graham introdcuded us to Sportvision's PITCHf/x which has tracked full trajectories of 99.8% of all baseball pitches since 2008. He showed us the code behind hitter heat maps and stressed the increasing focus on data analysis within the industry.
Shivaram Venkataraman (in collaboration with Indrajit Roy): Presto: Distributed R for Big Data
Shivaram introduced us to the brain-child of HP Labs and Berkeley EECS — Presto. Presto is a distributed system that extends R for complex, big-data analytics and has been shown to be more than 20 times faster than in-memory Hadoop.
Valeriy Lazarev: R in Educational Effectiveness Research
Val walked us through non-experimental educational effectiveness studies. He showed us how R's data handling, flexibility/ease of modeling and automation options help his team identify and communicate statistically significant impacts of a new program or policy.
Aamir Salaam: Conjoint Analysis with R
Aamir gave us peak into market research statistics. He demonstrated how the conjoint package can be used to perform analysis of trade-offs, lending insight into survey respondent's preferences.
Antonio Piccolboni: R and Hadoop
Antonio introduced us to rmr 2.0. We saw how RHadoop extends apply-like functionality to terabyte sized datasets with code that's minimal yet intuitive.
Many thanks to the presenters for sharing their talks, and thanks to Luba for the write-up!
Bay Area R User's Group: “Official” BARUG October Meeting
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