A hands-on, Python-based deep dive into the practical machine learning workflow with scikit-learn: exploratory data analysis, preprocessing, feature engineering, leak-free pipelines, cross-validation and metrics, linear models, trees and gradient-boosted ensembles, tuning, imbalanced data, interpretation, and deploying a saved model. Builds directly on Foundations of Artificial Intelligence.