CS 446

CS 446 - Machine Learning

Spring 2026

TitleRubricSectionCRNTypeHoursTimesDaysLocationInstructor
Machine LearningCS446CSP68039PKG3 -  ARR Illini Center Liangyan Gui
Machine LearningCS446CSP68039PKG3 -    Liangyan Gui
Machine LearningCS446DS378279ONL3 -    Liangyan Gui
Machine LearningCS446DS462698ONL4 -    Liangyan Gui
Machine LearningCS446MC369727PKG3 -    Liangyan Gui
Machine LearningCS446MC369727PKG3 -  ARR Illini Center Liangyan Gui
Machine LearningCS446MC468040PKG4 -  ARR Illini Center Liangyan Gui
Machine LearningCS446MC468040PKG4 -    Liangyan Gui
Machine LearningCS446P378289LCD31230 - 1345 T R  1320 Digital Computer Laboratory Huan Zhang
Machine LearningCS446P439433LCD41230 - 1345 T R  1320 Digital Computer Laboratory Huan Zhang
Machine LearningCS446PU31421LCD31230 - 1345 T R  1320 Digital Computer Laboratory Huan Zhang
Machine LearningECE449P378290LCD31230 - 1345 T R  1320 Digital Computer Laboratory Huan Zhang
Machine LearningECE449P470857LCD41230 - 1345 T R  1320 Digital Computer Laboratory Huan Zhang
Machine LearningECE449PU70856LCD31230 - 1345 T R  1320 Digital Computer Laboratory Huan Zhang

Official Description

Principles and applications of machine learning. Main paradigms and techniques, including discriminative and generative methods, reinforcement learning: linear regression, logistic regression, support vector machines, deep nets, structured methods, dimensionality reduction, k-means, Gaussian mixtures, expectation maximization, Markov decision processes, and Q-learning. Application areas such as natural language and text understanding, speech recognition, computer vision, data mining, and adaptive computer systems, among others. Course Information: Same as ECE 449. 3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: CS 225; One of MATH 225, MATH 257, MATH 415, MATH 416, ASRM 406 or BIOE 210; one of CS 361, STAT 361, ECE 313, MATH 362, MATH 461, MATH 463, STAT 400 or BIOE 310.

Subject Area

  • Computational Materials