MTH 4330
Introduction to Machine Learni · 4 credits · Spring 2027
Requirements
Prerequisite: Three courses, one from each of the following groups (or departmental permission): 1) MTH 3300 or CIS 2300; 2) MTH 2600, 2610, 2630, 3006, or 3010); and 3) MTH 3210 or MTH 4100)Prerequisite: MTH 3300; and either MTH 3120 or MTH 4120
About this course
This course provides an introduction to Machine Learning, where students will learn both theory and application of this subject. Students will get exposure to a broad range of machine learning methods and hands-on practice with real data. Topics include linear and logistic regression, support vector machines, decision trees, dimensionality reduction, unsupervised learning, and neural networks.
Seat status as of Oct 2, 10:36 AM ET. Seats can change between refreshes.
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