Machine Learning for Behavioral Data

Introduces the basics of machine learning, covering supervised and unsupervised learning, linear regression, and data understanding.

Introduces the course structure and fundamental concepts of machine learning, including supervised learning and linear regression.

Covers the basics of machine learning, including supervised and unsupervised learning, linear regression, and classification.

Introduces applied machine learning concepts such as data collection, feature engineering, model selection, and performance evaluation metrics.

Discusses regression trees, ensemble methods, and their applications in predicting used car prices and stock returns.