justmarkham/scikit-learn-videos

Covers 10 structured tutorials progressing from ML fundamentals through cross-validation, grid search, and classification metrics to production-ready pipelines with categorical feature encoding. Notebooks integrate pandas for data loading, seaborn for visualization, and scikit-learn's estimator API—demonstrating the complete supervised learning workflow from train/test splitting to ROC curve analysis. Updated for Python 3.9+ and scikit-learn 0.23+, with bonus material covering text vectorization and model comparison techniques.

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