Introduction to Machine Learning

Catalog description

An introduction to machine learning (ML), with an emphasis on programming ML applications and using modern ML libraries. Basic discrete mathematics, statistics, and linear algebra. An overview of various supervised learning classifiers. Unsupervised learning via clustering. Reinforcement learning with model-based and model-free approaches. Safety and ethical concerns of machine learning. 45 hours lecture, 27 hours laboratory. Transfer: CSU. Prerequisite: CS 1 with a minimum grade of C.