Elements of Machine Learning

Catalog description

Fundamental concepts of supervised machine learning, with sample algorithms and applications. Focuses on how to think about machine learning problems and solutions, rather than on a systematic coverage of techniques. Serves as an introduction to the methods of machine learning. Prerequisite: Computer Science 201. Recommended Prerequisites: Mathematics 221, 218, or 216 or equivalent; Mathematics 212 or equivalent; and Mathematics 230, Statistical Science 230 or equivalent.