Explores supervised learning in financial econometrics, covering linear regression, model fitting, potential problems, basis functions, subset selection, cross-validation, regularization, and random forests.
Introduces Scientific Machine Learning, emphasizing its application in various scientific fields and the connection between machine learning and physics.