We just ended the founding meeting of a Machine Learning Study Group here in Copenhagen. We're planning to meet approximately once a month to discuss machine learning algorithms. In between meetings there's a Facebook group where we hang out and discuss our current pet machine learning problems and a Google Docs repository of machine learning resource (still to come).
Here's how we're going to run the group: The goal is to get smarter about machine learning. We're narrowing down on a couple of stacks we care about. Big data using databases - we're going to have a look at Madlib for Postgresql. Or something based on Map/Reduce. Some of us occasionally work in Processing using OpenCV - which is neat, because it's also a good choice on the iPhone/in XCode/Openframeworks.
Some of us are probably going to be looking at Microsoft Solver Foundation in C# at some point. Some of us might be looking at implementing algorithms for one of these environments if no one else has.
We'll be building out our knowledge on configuring and setting up these stacks. The idea is for everyone to work on a pet problem with a machine learning element. We'll share our ideas on how to proceed, share how to approach the stack of software.
The typical approach to a machine learning problems involves
Just to give a little landscape: The founder members are primarily interested in the following spaces of problems: Image analysis - with a little time series analysis of sensor data thrown in for interactive fun - and "big data", running machine learning algorithms on web scala data.
If you're into this problem space, and this style of working - project driven, collaborative and conversational - feel free to join. If there's simply something you'd like to be able to do with a computer, feel free to join as well - maybe one of the more technical hangers on will take an interest in your idea and start working on it.