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scikit-learn

The classic toolkit for tabular machine learning.

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This course has 3 lessons. Start with the first one and use the next / previous links at the bottom of each lesson — the sidebar keeps the whole course in order.

Lessons

  1. Estimators and fit/predictThe uniform API behind every scikit-learn model: fit, predict, transform, and the data shapes the library silently expects.
  2. Pipelines and preprocessingCompose preprocessing and a model into one object, keep the test set clean, and handle numeric and categorical columns in a single ColumnTransformer.
  3. Model selection and metricsNested cross-validation, grid and randomised search, and picking a metric that reflects the cost of being wrong rather than the one that flatters the model.

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Last refreshed 2026-09-17.