Machine Learning Applications in Mechanical Engineering

3 units

This course explores the fundamentals of machine learning and deep learning, and their engineering applications. Key topics include classification, regression, dimensionality reduction, optimization methods, and uncertainty quantification. Advanced concepts such as physics-informed neural networks and operators, graph neural networks, normalizing flows, and neural differential equations will also be covered. Applications of these methods will be discussed, including reduced-order models for computational fluid dynamics simulations, automated segmentation and object detection in image data, and constitutive relations modeling of materials.