# Machine Learning & Optimiztn

## CSCI-4140

The first portion of this course introduces the optimization background necessary to understand the algorithms that dominate the landscape of machine learning. The second portion introduces effective architectures used in modern machine learning. Students revisit classical models and learn state-of-the-art models, always in service of gaining algorithmic insight that is broadly useful beyond specific models.

4 credits
Cross-listed with:
CSCI-6960 Topics in CSCI
Prereqs:
CSCI-2300 Introduction To Algorithms
and
one of:
CSCI-2210 Math Fndtns Of Machine Lrning MATH-4100 Linear Algebra

# Past Term Data
Offered
Not Offered
Offered as Cross-Listing Only
No Term Data
Simple View
Detailed View

| Spring | Summer | Fall
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| (Session 1) | (Session 2) |

2026

Machine Learning & Optimiztn (4c)

- Alex Algernon Theodore Gittens

Seats Taken: 27/32

2025 |  |  |

2024

Machine Learning & Optimiztn (4c)

- Alex Algernon Theodore Gittens

Seats Taken: 15/40

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