Topics in Computer Science: Machine Learning

Catalog description

This course provides an overview of concepts, techniques, algorithms and applications in machine learning, including supervised learning (e.g.: classification and regression), unsupervised learning (e.g.: clustering and dimensionality reduction), and learning theory (e.g.: bias/variance; regularization and feature selection). Moreover, the course will include research projects that will require writing computer code, conduction experiments, and writing papers. If students take CPSC 480 for the undergraduate program, they can take CPSC 680 for additional credits. Enrollment is limited to Graduate level students.