Written for undergraduate and graduate students, A First Course in Machine Learning covers the core mathematical and statistical techniques needed to understand some of the most popular machine learning algorithms. The algorithms presented span the main problem areas within machine learning: classification, clustering, and projection. Topics include linear modeling, making predictions, vector/matrix notation, and nonlinear response from a linear model.

The book includes many examples featuring MATLAB code available online.