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MATHEMATICAL FOUNDATIONS OF MACHINE LEARNING

COMPSCI/ECE 761
Course Description

Mathematical foundations of machine learning theory and algorithms. Probabilistic, algebraic, and geometric models and representations of data, mathematical analysis of state-of-the-art learning algorithms and optimization methods, and applications of machine learning. Knowledge of probability [such asMATH/​STAT  431orCOMP SCI/​E C E  561] and linear algebra [such asMATH 341orM E/​COMP SCI/​E C E  532] is required.

Prerequisites

Graduate/professional standing

Satisfies
Credits

Not Reported

Offered

Not Reported

Grade Point Average
3.45

2.94% from Historical

Completion Rate
97.5%

0.02% from Historical

A Rate
40%

-7.49% from Historical

Class Size
40

-24.53% from Historical

Cumulative Grade Distribution

Instructors (2026 Summr)

Sorted by ratings from Rate My Professors

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