Grant Ingersoll: Apache Mahout catching on in Academia

It’s back to school time and for those with academic interests in machine learning, it’s great to see Apache Mahout is catching on in academic circles, in addition to commercial circles.  The interest is no doubt due to its open code, active community and focus on real world machine learning techniques.  The first class based on Mahout that I am aware of was Mahout committer Isabel Drost’s class at TU Berlin.  Of course, with all due respect to Isabel, she is a bit biased towards Mahout; so I was pleasantly surprised when Dr. David Grossman (See his excellent Information Retrieval: Algorithms and Heuristics (The Information Retrieval Series)(2nd Edition) book, for starters) from the Illinois Institute of Technology contacted me last spring about putting together a class on Mahout for the fall at IIT.  Well, that class has finally come to fruition as CS 422: Data Mining Course Homepage and it looks to have nice coverage of the things near and dear to Mahout: clustering, classification, pattern mining and recommenders along with the requisite theoretical underpinnings.

I’ve also heard from a few other Professors who are working on adding Mahout to their coursework and would love to hear from more.  So, if you are teaching a class on machine learning and interested in Mahout for teaching purposes, either let me know (gsingers@apache.org) or drop a line to the Mahout community mailing list: user@mahout.apache.org.