From the tutorial description at OSCON 2011:
Mahout is an open source machine learning library from Apache. At the present stage of development, it is evolving with a focus on collaborative filtering/recommendation engines, clustering, and classification.
There is no user interface, or a pre-packaged distributable server or installer. It is, at best, a framework of tools intend to be used and adapted by developers. The algorithms in this “suite” can be used in applications ranging from recommendation engines for movie websites to designing early warning systems in credit risk engines supporting the cards industry out there.
This tutorial aims at helping you set up Mahout to run on a Hadoop setup. The instructor will walk you through the basic idea behind each of the algorithms. Having done that, we’ll take a look at how it can be run on some of the large-sized datasets and how it can be used to solve real world problems.
If your site or smartphone app or viral facebook app collects data which you really want to use a lot more productively, this session is for you!
Not the only resource on Mahout you will want but an excellent place to start.