This accessible book introduces the fundamental principles of machine learning. Organized into forty-three concise chapters, the book helps students develop intuition through simple examples that illustrate the often complex behaviors of machine learning models. Models and algorithms are discussed mathematically and concepts beyond linear algebra and multivariable calculus are introduced along the way. A First Course in Machine Learning teaches the mathematics needed to understand machine learning and to prepare for more advanced study, contains a carefully curated and ordered set of topics so students progressively gain the knowledge needed to understand the subject, and does not rely on any particular computer language but includes programming exercises so the reader can experiment with the algorithms.
