CS 07656 - Machine Learning II

Credits: 3

This course examines the mathematics and theory behind of some Machine Learning approaches, fundamental issues in machine learning, basic learning theory, and recent topics in machine learning. Topics may include Learning problem, Linear Models (Perceptron, Linear Regression, Logistic Regression), Support Machine Learning, Neural Network, Deep Learning, Ensemble method, Theory of Generalization (VC-dimension, Bias and Variance), Regularization, Validation, Dimension Reduction (Principal Component Analysis), and other recent topics in machine learning. This course builds on the materials covered in CS 07556: Machine Learning I.

Prerequisite Courses: CS 07556 with a minimum grade of D-
Course Attributes: GCAT, GRAD