I found an awesome tutorial page explaining how to recognize the music interval by ear. The best thing on the page is the table discussing the feeling of each interval.
Today I just found an interesting website BigML, and it seems to offer a playground for people, especially ML researchers, to experiment standard machine learning techniques on your data set or even on your business.
The main website is here:
You can try the BigML for free in development mode, but I think 1 MB for training data set is pretty restrictive though.
MapReduce is a framework to efficiently process a task that can be parallelized using cluster or grid. A good introduction can be found in the link below.
In a sense, MapReduce framework is very similar to message-passing algorithm in graphical models where the Map and Reduce are comparable to building (tree) structure and marginalization of the messages respectively. So, I think MapReduce can make an inference plausible for large-scale graphical models.