It has been over 2 months since the first satRday conference ended and I shared some quick impressions on that, where I also promised a follow-up post on my experiences as ending up being the main organizer of the event – this is what you are reading now. Although the idea was born at the EARL Boston conference last year, and I decided to take part in the project while living in Los Angeles – the conference took place in Budapest after all as logistics seemed to be easier there thanks to my closer relationship to the Hungarian R User Group.
Part 2 of the dplyr tutorial is now available! Hadley will be covering Grouped Mutate/Filter, Joins, Do, and Databases. (You can find Part 1 of the tutorial here.)
For our viewers who have just discovered the wonders of R, keep in mind that this tutorial was filmed in early July of 2014. As R packages naturally update over time (well, depending on the programmers!), please make sure to check Hadley’s Githubfor the latest changes to the dplyr package.
At this meetup, five more LA R meetup members will present short talks of what they have learned at useR! 2014. This is the 2nd round of talks about useR! since we had twice as many volunteers to speak as we could accommodate in one meetup (indeed, useR! was that awesome). The first round of talks at our September meetup is summarized here (with slides).
David Diez works on the OpenIntro team, which develops open-source textbooks, statistical software labs, and other course resources for intro-level statistics. This video above is the talk he gave at useR! 2014 entitled “Textbooks fail where Software Succeeds” in which he outlines the challenges unique to open-source textbooks, the state of OpenIntro, and how people can get involved. Below, he discusses these challenges further and offers his thoughts around their solutions.
Hadley Wickham (perhaps you’ve heard of his work) presented a 2 hour workshop on dplyr at this year’s useR! conference at UCLA. This tutorial was definitely a highlight of the week-long conference for me, and working on this tutorial video has also made me very appreciative of how versatile the dplyr package can be. It clearly is the chef’s knife of data science tools.
Joe Cheng is a software engineer. Unfortunately the term gets thrown around pretty lightly, so I’d like to make sure that I convey the appropriate amount of gravitas when I refer to him as such. Joe Cheng is a *great* Software Engineer. He has worked for some of the largest technology companies on the planet, building cutting edge tools which empowered the web browser as a full blown platform instead of a historical curiosity. Joe is one of those software engineers who saw a future with the web as a platform for modern software, then worked hard to make it a reality. When the time came to build the next generation of data science IDEs, an IDE targeting the web as a platform, RStudio called Joe.
Last week the LA R meetup featured 5 speakers each highlighting a few things they had found interesting at the useR! 2014 conference (which I had the pleasure of helping to organize this year in Los Angeles). This meetup proved to be interesting even to those of us who attended the conference (which was about half of our audience), simply because there were so many cool things to hear and enough parallel sessions at the conference that no one could possibly capture all of the action.
Heather Turner is a biostatistician and Associate Fellow at the University of Warwick, as well as a consultant. She is a former editor of the R Journal, was a local organizer for the useR! 2011 conference, and holds a wealth of information about the field of data science, the state of the technology, and the wider community.
At useR! 2014, one of the most anticipated presentations was Joe Cheng’s Shiny: R made interactive. It was but one of the of a fantastic series of talks by RStudio representatives; check out Winston Chang’s ggvis: Interactive graphics in R for another great talk. Shiny begins with your R code and ends with the customer’s view: an interactive, browser-accessible application. This enables you to place a great deal of power into your users’ hands to customize their view and provides a variety of new and innovative ways to interact with the data, such as by tuning parameters and focusing on sub-populations. Essentially, Shiny functions by allowing you to “wire up” up a reactive application, greatly speeding up the development of a data and analysis based web app.
In science consensus is irrelevant. What is relevant is reproducible results. The greatest scientists in history are great precisely because they broke with the consensus.
– Michael Crichton
Yihui Xie intended to make it easier to do his homework, but instead found himself tackling one of the greatest problems in modern science: the reproducibility of results.
Matt Dowle holds a wealth of knowledge and is worth listening to for a variety of reasons. He has worked for some of the world’s largest financial organizations, holding positions at the focal point between money and data. He has been programming in R for well over a decade. He has lived the open source mantra, by not only consuming open source software but also releasing his own community contributions to CRAN. On top of those accomplishments, he’s also quite funny and spins a heck of a good yarn.
The Interview # In the video above, Max provides some amazing insights into the why and how of caret, an R package he created. He also discusses his book on Applied Predictive Modeling which he co-authored with Kjell Johnson, including details on how he set out to write the book he wished he would have had. As a special bonus, Max also describes Quinlan’s C5.0, an alternate “forest of decision trees” algorithm, the secrets of which were hidden behind commercial licensing for years - and which has recently been ported and made available to the R ecosystem. Whether you are a beginner just getting your feet wet with R and predictive modeling, or a seasoned data scientist, this interview has something for everyone.
Hadley Wickham is famous. He’s not Kardashian famous, but walking around useR! and seeing the community’s reaction to him, there’s no question, he’s ‘R famous’. If you have the good fortune to see his talks, tutorials, or sessions in person, you owe it to yourself to do so. He projects depth and wisdom with a booming voice, which combines with a hard-won confidence brought about by years of honing his craft and developing his expertise. He takes as much time as is needed to answer questions, listens to every single bit of feedback and succeeds in making you feel that what you say indeed matters. Hadley Wickham has poise. It’s also quite obvious, if you watch him for long enough, that this fame suits him like an itchy sweater made by a loving grandparent. It brings warmth and it comes from a place of love, but it’s always a little uncomfortable regardless of how well it may fit.
Many of us here in the DataScience.LA Team were also involved in organizing the useR! 2014 conference, the annual get-together of the wonderful R community, which brought over 700 R users and developers from all over the world to Los Angeles this past July.
