Machine Learning

Undergraduate

Fundamental machine learning techniques with emphasis on using these techniques to design and implement small practical learning systems. Topics include learning as a search, inductive bias, concept learning, computational learning, explanation-based learning and reinforcement learning. Course Format: Lectures, lab, 5 hours per week. Prerequisite(s): COSC 3P71 (minimum 60 percent). Course Notes: This course may be offered in multiple modes of delivery. The method of delivery will be listed on the academic timetable, in the applicable term.