SE 132. Machine Learning for Structural Engineering (4 units)
Link to catalog page: https://catalog.ucsd.edu/courses/SE.html#se132
Description
This course aims at introducing concepts of machine learning and its applications to structural engineering. Theory behind popular machine learning algorithms will be discussed, including supervised learning, unsupervised learning, and deep learning. Topics include regression, classification, support vector machines, clustering, tree-based methods, model selections and regularizations, cross-validation and bootstrapping, neural networks, and Python programming. Prerequisites: SE 9 (or MAE 8), SE 110A (or MAE 131A), and SE 125 (or MAE 108).
Prerequisite courses
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Successor courses
No courses have SE 132 as a prerequisite.