Description
This course provides an introduction to pattern recognition and statistical learning. Topics covered include: Bayesian decision theory; parameter estimation; maximum likelihood; the bias-variance trade-off; Bayesian parameter estimation; the predictive distribution; conjugate and non-informative priors; density estimation: parametric vs. kernel-based methods; mixture models; expectation-maximization; applications.
General Information
Lectures
TuTh, 12:30-1:50 PM, CENTR 113
Instructor
Nuno Vasconcelos
Name | Office Hours | |
---|---|---|
Mohammad Saberian | When? Where? | |
Mandar | When? Where? | |
Nuno Vasconcelos | When? Where? | |
Weixin Li | When? Where? |
General Resources
Nothing has been added to the General Resources section, yet. Stay tuned!