Concise Machine Learning by Jonathan Richard Shewchuk

This report contains lecture notes for UC Berkeley’s introductory class on Machine Learning. It covers many methods for classification and regression, and several methods for clustering and dimensionality reduction. It is concise because nothing is included that cannot be written or spoken in a single semester’s lectures (with whiteboard lectures and almost no slides!) and because the choice of topics is limited to a small selection of particularly useful, popular algorithms.