Explores polynomial curve fitting, kernel functions, and regularization techniques, emphasizing the importance of model complexity and overfitting.
Explores supervised learning in financial econometrics, covering linear regression, model fitting, potential problems, basis functions, subset selection, cross-validation, regularization, and random forests.
Introduces machine learning basics, including data collection, model evaluation, and feature normalization.
Explores the implementation of Connect Four game functionalities and testing methods.
Covers sampling, cross-validation, quantifying performance, optimal model determination, overfitting detection, and classification sensitivity.
