Explores supervised learning in financial econometrics, covering linear regression, model fitting, potential problems, basis functions, subset selection, cross-validation, regularization, and random forests.
Covers the basics of Ordinary Least Squares (OLS) in econometrics, including variable relationships, coefficient determination, and model interpretation.
Covers linear models, including regression, derivatives, gradients, hyperplanes, and classification transition, with a focus on minimizing risk and evaluation metrics.
Covers ANOVA method, focusing on partitioning total sum of squares into treatment and error components, mean square calculations, Fisher statistic, and F-distribution.
Introduces the basics of electromagnetism, covering derivatives, vector calculus, scalar and vector products, and their applications in physics and engineering.