Description
This course provides an introduction to popular machine learning algorithms and their underlying mathematical concepts. Using Python as the primary programming language, students will explore real-world datasets, uncover patterns, and build predictive models with a variety of machine learning techniques. Key topics include linear and logistic regression, decision trees, k-nearest neighbors, and neural networks, equipping students with the foundational skills to tackle data-driven challenges. Prerequisite: CSC 130, MAT 141, and MAT 211. (MAT 231 and MAT 341 recommended.)