Course Number
605.746
Next Offered
Spring 2022
Primary Program
Computer Science
Location
Online
Mode of Study
Online

This course focuses on recent advances in machine learning and on developing skills for performing research to advance the state of knowledge in machine learning. The material integrates multiple ideas from basic machine learning and assumes familiarity with concepts such as inductive bias, the bias-variance trade-off, the curse of dimensionality, and no free lunch. Topics range from determining appropriate data representations and models for learning, understanding different algorithms for knowledge and model discovery, and using sound theoretical and experimental techniques in assessing learning performance. Specific approaches discussed cover nonparametric and parametric learning; supervised, unsupervised, and semi-supervised learning; graphical models; ensemble methods; and reinforcement learning. Topics will be discussed in the context of research reported in the literature within the previous two years. Students will participate in seminar discussions and will present the results of a semester-long research project of their own choosing.

Course Prerequisite(s)

EN.605.649 Introduction to Machine Learning; multivariate calculus;Students cannot receive credit for both EN.605.746 and EN.625.742

Course Offering(s)

Waitlist Only

605.746.81
01/24/2022 - 05/10/2022
Semester
Spring 2022
Mode of Study
Online
Location
Online
Cost
$4,755
Textbook
TBD