STA 325L
Machine Learning and Data Mining
The rapid growth of digitalized data and the computer power available to analyze it has created immense opportunities for both machine learning and data mining. This course introduces machine learning and data mining methods. Topics covered include information retrieval, clustering, classification, modern regression, cross validation, boosting, and bagging. Course emphasizes selection of appropriate methods and justification of choice, use of programming for implementation of the method, and evaluation and effective communication of results in data analysis reports.
Topics
- information retrieval
- clustering
- classification
- modern regression
- cross validation
- boosting
- and bagging
Topics explicitly listed in official catalogue description
Prerequisites & course information
004368
Sources
- Course catalogue ↗2026-2027