Course: COMP 542. Machine Learning (3)
Prerequisites: COMP 380/L or equivalent; MATH 262 or equivalent; MATH 340 or MATH 341 or equivalent. Recommended Preparatory: Knowledge of Python programming. A study of the concepts, theories, techniques, and applications of machine learning. Students will get exposure to a broad range of machine learning methods and hands on practice on real data. Topics may include feature selection, feature transformation, dimensionality reduction, concept-based learning, distance-based learning, Bayesian classification and networks, regression analysis, kernel methods, support vector machines, decision trees, explainable AI, basic neural networks, and machine learning on the cloud.