MSML 606
Algorithms and Data Structures for Machine Learning
Provides both a broad coverage of basic algorithms and data structures. Topics include sorting, searching, graph and string algorithms; greedy algorithm, branch-and-bound, dynamic programming and job scheduling; Arrays, linked lists, queues, stacks, and hash tables; Algorithm complexity, best/average/worst case analysis. Applications selected from machine learning problems.
Topics
- sorting
- searching
- graph and string algorithms
- greedy algorithm
- branch-and-bound
- dynamic programming and job scheduling
- Arrays
- linked lists
- queues
- stacks
- and hash tables
- Algorithm complexity
- best/average/worst case analysis
Topics explicitly listed in official catalogue description
Sources
- Course catalogue ↗2026-2027