- R Studio — AGPLv3-licensed IDE for R. It brings your R console, source code, plots, help, history, and workspace browser into one cohesive package. We’ve added some neat productivity features like a searchable endless command history, function/symbol completion, data import dialog with preview, one-click Sweave compile, and more. Source on github. Built as a web-app on Google AppEngine, from Joe Cheng who did Windows Live Writer at Microsoft. (via DeWitt Clinton)
- Adventures in Participatory Audience — Nina Simon helped thirteen students produce three projects to encourage participation in museum audiences: Xavier, Stringing Connections, and Dirty Laundry. My favourite was Dirty Laundry, where people shared secrets connected to works of art. Nina’s description of what she learned has some nuggets: friendly faces welcoming people in gets better response than a card with instructions, and I am still flummoxed as to what would make someone admit to an affair or bad parenting in a sterile art gallery, or the devastating one that read, “I avoid the important, difficult conversations with those I love the most.” Audience participation in the real world has lessons on what works for those who would build social software.
- Why Generic Machine Learning Fails — Returns for increasing data size come from two sources: (1) the importance of tails and (2) the cost of model innovation. When tails are important, or when model innovation is difficult relative to cost of data capture, then more data is the answer. […] Machine learning is not undifferentiated heavy lifting, it’s not commoditizable like EC2, and closer to design than coding. The Netflix prize is a good example: the last 10% reduction in RMSE wasn’t due to more powerful generic algorithms, but rather due to some very clever thinking about the structure of the problem; observations like “people who rate a whole slew of movies at one time tend to be rating movies they saw a long time ago” from BellKor.
- Anatomy of a Crushing — Maciej Ceglowski describes how pinboard.in survived the flood of Delicious émigrées. It took several rounds of rewrites to get the simple tag cloud script right, and this made me very skittish about touching any other parts of the code over the next few days, even when the fixes were easy and obvious. The part of my brain that knew what to do no longer seemed to be connected directly to my hands.
Four short links: 9 March 2011
R IDE, Audience Participation, Machine Learning, Surviving Success
tags: devops, machine learning, museums, open source, pinboard, R, scale, social software, user generated content