| Spring Term 2023 Machine Learning - 3062 - STAT 208 |
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Prerequisites/Notes: CMSC 150, or CMSC 205, or CMSC 210, or consent of instructor Catalog Description : An overview of techniques used to discover structural patterns and make predictions using complex datasets that are prevalent in today's world. The central machine learning tasks of classification, clustering, and regression will be explored, along with methods for training models and evaluating predictions. This course will be taught in a workshop format. Assignments will involve the use of statistical software. PREREQUISITES: CMSC 150, or CMSC 205, or CMSC 210, or consent of instructor Attributes: Cross-Listed Course, GER Quantitative Analysis, 200-399 Foundation/Gateway Crs
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