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by Hilary Mason
Machine learning has come a long way in recent years — from a long-marginalized field so old it still has the word “machine” in the name, to the last, best hope for making sense of our massive flows of data.
The art of ‘data science’ is asking the right questions; the answers are generally trivial or impossible. This talk will focus more on questions than on answers. I’ll give a brief history of the field with a focus on the fundamental math and algorithmic tools that we use to address these kinds of problems, then walk through several descriptive and predictive scenarios.
Finally, I’ll show one example system using bit.ly data in-depth, from the backend infrastructure through the algorithms and data processing layer to show a functioning product.
Attendees should expect to hear some good stories of data gone right and data gone awry, and walk away with a few new clever tricks.
by Yehuda Katz
Ruby on Rails has shown the world that it's possible to build an open-source project that is optimized for developer happiness. In the five years since it was originally announced, Rails has gone through the typical hype cycle: enthusiastic early adopters followed by negative press attention followed by a quieter period of productivity.
What challenges did Rails face as it made its way to being a successful, well-regarded framework, and how did it overcome them? In this talk, Yehuda will talk about how the Rails team faced its challenges, and what lessons you can take away when working on your own open source project.
by Kyle Cordes
This talk will show how and WHY to use Lua (as opposed to the zillion other scripting languages) for embedded scripting inside of larger, non-Lua projects. Lua is safe, fast, simple, learning, and more popular that you might expect.
by Chris Houser
If you've done much work in any language with polymorphism, you've probably encountered the expression problem, whether you knew its name or not. Chances are even come up with a solution or two yourself. I'll define the expression problem, demonstrate some common solutions, then dig into how Clojure's multimethods and protocols each solve the problem while avoiding weaknesses of other solutions. Along the way you'll get a sense of how Clojure's approach to datatypes differs from classic object-oriented languages.
14th–15th October 2010