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, using F#. So bring your laptop, and let's see how smart we can make our machines!
This session will be organized as an interactive workshop. Come over, and learn yourself a Machine Learning and F# for great good! No prior experience with Machine Learning required, and F# beginners are very welcome - it will be a great opportunity to see F# in action, and why it's awesome.
To get the most from the session please try and bring a laptop along with F# installed (ideally either MonoDevelop or Visual Studio Web Express/Full Edition).
Mathias Brandewinder has been writing software in C# 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 http://www.clear-lines.com/blog or find him on Twitter as @brandewinder.