CS 446
CS 446 - Machine Learning
Fall 2025
Title | Rubric | Section | CRN | Type | Hours | Times | Days | Location | Instructor |
---|---|---|---|---|---|---|---|---|---|
Machine Learning | CS446 | B3 | 46793 | ONL | 3 | - | Liangyan Gui | ||
Machine Learning | CS446 | BG | 80991 | ONL | 4 | - | Liangyan Gui | ||
Machine Learning | CS446 | BU | 46792 | ONL | 3 | - | Liangyan Gui | ||
Machine Learning | CS446 | DS3 | 81003 | ONL | 3 | - | Liangyan Gui | ||
Machine Learning | CS446 | DS4 | 60403 | ONL | 4 | - | Liangyan Gui | ||
Machine Learning | CS446 | MC3 | 77676 | PKG | 3 | - | Liangyan Gui | ||
Machine Learning | CS446 | MC3 | 77676 | PKG | 3 | - | Liangyan Gui | ||
Machine Learning | CS446 | MC4 | 77674 | PKG | 4 | - | Liangyan Gui | ||
Machine Learning | CS446 | MC4 | 77674 | PKG | 4 | - | Liangyan Gui | ||
Machine Learning | ECE449 | B3 | 73597 | ONL | 3 | - | Liangyan Gui | ||
Machine Learning | ECE449 | BG | 77677 | ONL | 4 | - | Liangyan Gui | ||
Machine Learning | ECE449 | BU | 73595 | ONL | 3 | - | Liangyan Gui |
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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