Two weeks ago we attended the useR! conference hosted on the UCLA campus. I landed in Los Angeles at 8:30 P.M on Sunday June 29, and met up with Amy — another math hacker at 0xdata. After a harrowing cab ride we arrived on the UCLA campus at Sunset Village where we would be lodging for the next 3 evenings. Having just got the h2o R package accepted by the CRAN gods, we were definitely a little more than giddy to be at useR!

Day 0 of the conference eased in with tutorials from various different R projects and packages — I sat in on the dplyr tutorial by Hadley Wickham, which turned out to be an engaging hands-on workshop in which my neighbor and I got to solve small problems designed to get us to learn about the dplyr package. As one of the R developers at 0xdata, there is a lot that I cannot wait to add h2o support for.

For the rest of Day 0, Amy and I set up our booth and connected up with Max, 0xdata’s Customer Engagement Manager. A few weeks prior to the conference, Max and Sri (CEO) hosted a meetup in Los Angeles demoing H2O, so there were a lot of folks that recognized us already on the tutorial day. It was great to catch up with them and hear about their experiences with H2O so far. We handed out the few cards and data sheets we had on hand while setting up for the official start of the conference on Tuesday.
On Tuesday, Wednesday, and Thursday morning there was quite a bit of booth traffic from every end of the spectrum — industry: folks in pharma, consultants, fast food, government; academia: professors, students, and professional researchers. Everyone had rich and diverse interests, but one common problem: how the hell do I make R work with large data sets? It was great to describe the ways in which R interfaces to Java as a back end — in the same way that R has done for years with Fortran and C++. Demonstrating how to parse and perform a logistic regression  on 116M rows of data in less time than it took to talk about what was happening was a highlight for all that swarmed around the booth. There was lots of great feedback and feature requests too, many of which are on our road map: Time Series, Mixed Effects Models, plyr, and dplyr.
John Chambers graced us by visits to our booth and calling out our freshly admitted h2o CRAN package during his keynote — that definitely set off lots more interest than the Max, Amy, Sri, and I were prepared to handle! We stayed at the booth well into the evening on Tuesday discussing h2o and installing it on laptops for people that weren’t able to come by earlier for it being so crowded.
All in all, this was a great experience, and we ended up talking to nearly everyone at the conference. On Thursday afternoon we packed up the booth and shipped everything we couldn’t fit into our bags back to the office. Amy and I caught a flight back up to San Francisco on July 3rd, and spent the next few days celebrating the 4th and cheering our favorite Futbol teams!