Introduction - If you have any usage issues, please Google them yourself
Its focus is on supervised classification with several classifiers available: SVMs (based on libsvm), k-NN, random forests, decision trees. It also performs feature selection. These classifiers can be combined in many ways to form different classification systems. It works over many datatypes, with a preference for numpy arrays.
For unsupervised learning, milk supports k-means clustering and affinity propagation.