闪播福利库

This course covers an introduction to supervised and unsupervised learning algorithms for engineering applications, such as visualization-based physical quantity predictions, dynamic signal classification, and prediction, data-driven control of dynamical systems, surrogate modeling, and dimensionality reduction, among others. The lectures cover the fundamental concepts and examples of developing machine learning models using Python and MATLAB. This course includes four homework assignments to practice the application of different machine learning algorithms in specific mechanical engineering problems and a project assignment that gives the students the flexibility of selecting their topics to study using designated machine learning tools. Students are not allowed to take both 惭贰贰骋听44403 and 惭贰贰骋听54403 for credits. Prerequisite: 惭贰贰骋听27003 or equivalent and Graduate student standing. (Typically offered: Fall)