Elements of Statistical Machine Learning
Introduction to the concepts and tools of data science, statistics, and machine learning used to draw inferences about large-scale and real-world data. Explore data visualization, linear and nonlinear models, regularization, classification, resampling, tree-based methods, support vector machines, and unsupervised learning. Statistics and Data Sciences 323 and 326E may not both be counted. Three lecture hours a week for one semester.
Prerequisites & course information
Introduction to the concepts and tools of data science, statistics, and machine learning used to draw inferences about large-scale and real-world data. Explore data visualization, linear and nonlinear models, regularization, classification, resampling, tree-based methods, support vector machines, and unsupervised learning. Statistics and Data Sciences 323 and 326E may not both be counted. Three lecture hours a week for one semester.
Sources
- Course catalogue ↗2026-2027