Machine learning methods extract value from vast data sets quickly & with modest resources. They are established tools in a wide range of industrial applications including search engines DNA sequencing stock market analysis & robot locomotion & their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates & masters students with limited background in linear algebra & calculus. Comprehensive & coherent it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques they develop analytical & problem-solving skills that equip them for the real world. Numerous examples & exercises both computer based & theoretical are included in every chapter. Resources for students & instructors including a MATLAB toolbox are available online.