Supervised Machine Learning with scikit-learn Cheatsheet

Supervised learning is one loop: split the data, fit a model, evaluate it honestly, and improve it with regularisation and tuning. This cheatsheet gathers the whole loop on one page, from the fit-predict verbs through ridge and lasso, the metrics that survive imbalance, cross-validation, and leak-proof pipelines, each snippet annotated line by line. Keep it open while you model, or save the image and pin it nearby.

For the full background, read the guide to supervised machine learning with scikit-learn. To practise, work through the 10 code-along examples.

Download the cheatsheet

Thanks for reading my blog, Andrei