Graduate Computer Science

CS G220: Machine Learning

This course provides a broad look at machine learning techniques and issues, including algorithms for: supervised learning, including back-propagation neural networks and decision tree induction; unsupervised learning; reinforcement learning; and explanation-based learning. Also covers simulated annealing and genetic algorithms, and introduces computational learning theory and other methods for analyzing and measuring the performance of learning algorithms. Coursework includes a programming term project.
Prerequisites:
CS G120 MS: AI Ph.D.: AI
Credit hours: 4
Course offerings: