CS 412 Machine Learning Select Term:
This is an introductory machine learning course that will aim a solid understanding of the fundamental issues in machine learning (overfitting, bias/variance), together with several state-of-art approaches such as decision trees, linear regression, k-nearest neighbor, Bayesian classifiers, neural networks, logistic regression, and classifier combination.
SU Credits : 3.000
ECTS Credit : 6.000
Prerequisite :
( Undergraduate level MATH 201 Minimum Grade of D
AND Undergraduate level MATH 203 Minimum Grade of D )
Corequisite :
CS 412R