Topics covered: Unsupervised learning, k-means clustering, distance metric, cluster merging, centroid, k-mean error, hold out set, k value significance, features of k-means clustering, merits and disadvantages of types of clustering.
Attribution: The Open Education Consortium
http://www.ocwconsortium.org/courses/view/95d7beec68c50467dd03ef3c3e6f32a9/
Course Home http://videolectures.net/mit600SCs2011_guttag_rec08/
