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Skill · Predicting continuous valuesLive

Regression

Fit lines and curves to data and measure the error — linear, polynomial, and regularised models on real datasets.

  1. Task 1Fit a lineEasyFit the straight line that runs through your data.~11 min · 2 blanks→
  2. Task 2Score with R²EasyMeasure how much variance your model explains.~11 min · 1 blanks→
  3. Task 3Multiple featuresMediumRegress on several inputs at once.~12 min · 1 blanks→
  4. Task 4Train / test splitMediumJudge a model on data it never trained on.~13 min · 2 blanks→
  5. Task 5Polynomial fitMediumBend the line into a curve with polynomial features.~13 min · 1 blanks→
  6. Task 6Ridge & LassoHardRegularise to fight overfitting — and let Lasso prune features.~14 min · 1 blanks→
  7. Task 7Feature scalingHardPut features on the same scale before modelling.~13 min · 1 blanks→
  8. Task 8Mean absolute errorMediumMeasure error in the units you actually care about.~11 min · 1 blanks→
  9. Task 9Cross-validationHardScore across several folds, not just one lucky split.~14 min · 2 blanks→
  10. Task 10A full pipelineHardScale and model together on a real dataset, scored honestly.~16 min · 2 blanks→