Course Number(s):
Stat 161, Stat 261
Instructor(s):
School(s):
Semester:
- Spring 2014
Course Level:
- Graduate, Undergraduate
Prerequisite(s):
Stat 100B, Mathematics 33A
Course Website:
Course Description:
Introduction to pattern analysis and machine intelligence designed for advanced undergraduate and graduate students. Topics include Bayes decision theory, learning parametric distributions, non-parametric methods, regression, Adaboost, perceptrons, support vector machines, principal components analysis, nonlinear dimension reduction, independent component analysis, K-means analysis, and probability models.