Individual skill
machine-learning
Use when predicting a column from rows of tabular features with classic models — scikit-learn pipelines, RandomForest, XGBoost/LightGBM, leak-free cross-validation, metrics for imbalanced classes, or a model that aced CV then collapsed in production. NOT PyTorch neural nets (that is `deep-learning`), NOT cleaning the dirty table first (that is `data-cleaning`), NOT forecasting a dated series (that is `forecasting`), NOT text/token modeling (that is `nlp`).
skills/machine-learning/SKILL.md
Source commit d9d6bb338f66cc1e23998585e580a0ea45bbcb82
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- Observed behavior
- Network or broad shell
- Last checked
- Nov 10, 2026
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- Repository stars (not skill ratings)
- 574
- Repository last updated
- Nov 9, 2026
- License
- MIT
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- agent-skills Repository topic
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- machine-learning Declared skill tag
- scikit-learn Declared skill tag
- sklearn Declared skill tag
- xgboost Declared skill tag
- lightgbm Declared skill tag
- tabular Declared skill tag
- gbdt Declared skill tag
- cross-validation Declared skill tag
- data-leakage Declared skill tag
- classification Declared skill tag
- regression Declared skill tag
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SKILL.mdcore · 16,989 bytesSKILL.mdcore · 16,989 bytesSKILL.mdcore · 16,989 bytesevals/README.mddoc · 1,258 bytesevals/cases.yamlasset · 4,809 bytesreferences/gbdt-and-tuning.mddoc · 4,594 bytesreferences/metrics-and-imbalance.mddoc · 4,465 bytesreferences/pipelines-and-cv.mddoc · 5,857 bytes
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# Machine learning — classic/tabular models, done without lying to yourself
Tabular ML is easy to *run* and easy to *fool yourself with*. The deliverable is never "the notebook
printed 0.99" — it is an **honest estimate of how the model behaves on data it has never seen**: a
`Pipeline` that fits every transform on train only, a metric that survives class imbalance, and a
`DummyClassifier` baseline it beats. A number you can't reproduce on a sacred test set you touched exactly
once isn't a result — it's a leak you haven't found yet.
## Is this the right skill? (decide first)
| Your situation | Reach for |
| --- | --- |
| Rows of features, predict a column, with trees / linear models / sklearn | **machine-learning** (this skill) |
| Images, audio, long text, sequences, or you need a neural net / PyTorch | [`deep-learning`](../deep-learning/SKILL.md) |