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
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 Xamarin Studio, MonoDevelop or Visual Studio); you can find detailed instructions for OSX, Linux and Windows on fsharp.org. And if you've never used F# before and want a head-start, check the great online intro tutorials on TryFSharp.org. +++++++++++++++++++++
Mathias Brandewinder has been developing software for about 10 years, and loving every minute of it, except maybe for a few release days. His language of choice was C#, until he discovered F# and fell in love with it. He enjoys arguing about code and how to make it better, and gets very excited when discussing TDD or functional programming. His other professional interests include machine learning and applied math. Mathias is a Microsoft F# MVP and the founder of Clear Lines Consulting. He is based in San Francisco, blogs at www.clear-lines.com/blog, and can be found on Twitter as @brandewinder.