Where this guide comes from
Inspired by the topic of baniascodes' reel about machine-learning model rankings. Its publicly readable caption names linear regression, XGBoost, CatBoost, and PCA. The video could not be played during preparation, so this guide does not reconstruct or endorse its exact rankings. Logistic regression, decision trees, random forests, and evaluation are supporting lessons added here.
All text, diagrams, datasets, and code in this workshop are original. Datasets are synthetic; displayed metrics are calculated in your browser, not benchmark results. The boosting and categorical-encoding labs are simplified mechanisms, not runs of the XGBoost or CatBoost libraries. Sources were checked on 14 October 2026.
The visual direction uses a white instrument-board layout: blue circles for observations, a crimson model line, amber dashed residuals, and outlined validation points. Colors always have shape or text companions. A night view is also available.
Source repository