CAI4510C — Machine Intelligence
The course will cover advanced modeling techniques, including ensemble learning, extended linear models and kernel methods (PCA, support vector machines), probabilistic graphical models, Bayesian networks, mixture and latent variable models, biologically inspired computing (neural networks), feature selection and feature engineering techniques, Markov models, and temporal modeling to find patterns over time.
Prerequisites: CAI 3822C, COP 3350