Machine Learning
Debugging
Fix ML problems faster with a structured checklist.
Overfitting vs Underfitting
- Overfit: train high, test low → simplify model, regularize, get more data.
- Underfit: both low → better features, better model, less regularization.
Sanity Checks
- Shuffle labels: performance should drop near baseline.
- Train on tiny subset: model should overfit it (if not, bug in pipeline).
- Verify preprocessing is not fitted on test.