|Winter Term 2023 Machine Learning - 1091 - CMSC 208
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.
Attributes: Quantitative Analy GER (01cr), BM Natural Science (01cr), Foundation/Gateway Course