TTIC 103 (CMSC 35420): Statistical Methods for Artificial Intelligence, Autumn 2009

Instructor: David McAllester, Nathan Srebro and Raquel Urtasun

TA: Jian Peng

Textbook: Pattern Recognition and Machine Learning by Chris Bishop, Springer 2006

MWF 2:30 - 3:30

Location TTI-C (6045 S. Kenwood Ave)

Course Description

Grading: The course will have roughly five homework sets, a midterm, and a final.

Description: This course gives a survey of mathematical methods in statistical modeling, inference, and learning with an emphasis on techniques widely used in speech recognition, computational linguistics, computer vision, and computational biology. This course is aimed at providing students with a core understanding of statistical AI.

Lecture Schedule

Homework

·       Problem set 1 README Code and Data

·       Problem set 2 README Data

·       Problem set 3 README

·       Problem set 4 README

·       Problem set 5

Topics and Lecture Notes:

·       Course Notes

·       Least Squares Regression, Logistic Regression, Priors and Regularizaition and Gaussian Processes

·       Gaussian Processes Sample Code Chapters