Machine Learning is the art of writing programs that get better at performing a task as they gain experience, without being explicitly programmed to do so. Feed your program more data, and it will get smarter at handling new situations.
Some machine learning algorithms use fairly advanced math, but simple approaches can be surprisingly effective. In this session, we'll take a classic Machine Learning challenge from Kaggle.com, automatically recognizing hand-written digits (http://www.kaggle.com/c/digit-recognizer), and build a classifier, from scratch. So bring your laptop, your language of choice, and let's see how smart we can make our machines!
This session is meant to be interactive - we'll code, and compare solutions. This is also a perfect opportunity to team up with someone, and experiment with a language you are curious about (like my personal favorite, F# :)). Come over, and learn yourself a Machine Learning for great good! No prior experience with Machine Learning required, just bring your laptop and your brain.
Host Information: Mathias Brandewinder has been writing software in C# and F# for nearly 10 years, and loving every minute of it, except maybe for a few release days. He is an F# MVP, enjoys arguing about code and how to make it better, and gets very excited when discussing TDD or F#. His other professional interests are applied math and probability. If you want to know more about him, you can check out his blog at www.clear-lines.com/blog or find him on Twitter as @brandewinder.