Machine Learning for Manufacturing

Catalog description

This course includes two major parts: introduction of Machine Learning (ML) techniques and application to practical manufacturing processes. ML techniques covered include: multiple regression, support vector regression, principal component analysis, k-means clustering, Kalman filtering, neural networks, convolutional, and advanced deep learning techniques. ML applications cover a broad range of manufacturing settings, e.g., machine anomaly detection, part quality prediction and defect detection, etc. Offered as EMAE 368 and EMAE 468 .