Machine Learning for Design, Analysis and Prediction.

Catalog description

Rigorous exploration of the theoretical foundations and applications of machine learning. Predictive modeling, sequential design, optimization, and probabilistic inference in industrial engineering. Key concepts including Lasso and Ridge regression, basis expansions, support vector machines, Gaussian processes, Bayesian optimization, data reduction, imputation, augmentation methods, matrix factorization, and generative models.