# scikit-learn

A Claude skill that steers the agent through scikit-learn work: classification, clustering, preprocessing, pipelines and hyperparameter tuning.

- skill · `type=skill` · Claude Code · 143 installs
- Author: davila7
- License: not stated · policy=link-only · description only; the file stays with the author
- Source: https://github.com/davila7/claude-code-templates/tree/HEAD/cli-tool/components/skills/scientific/scikit-learn
- Updated: 2026-10-24
- HTML: https://affpapa.org/en/nevibecode/skills/scikit-learn

## What it does

The skill hands the agent a reference set for scikit-learn. It covers supervised and unsupervised algorithms, evaluation metrics, cross-validation, missing-value handling, categorical encoding and pipeline assembly. The material lives in files such as `references/supervised_learning.md`, `references/unsupervised_learning.md`, `references/model_evaluation.md` and `references/preprocessing.md`. When you ask for a model or a data prep step, the agent pulls the matching section.

Install it with `npx claude-code-templates@latest --skill scientific/scikit-learn` or `npx skills add davila7/claude-code-templates --skill scikit-learn -a claude-code`. The skill itself ships no library code. scikit-learn still has to be present in your project, for instance via `uv pip install scikit-learn`; the examples also lean on `matplotlib` and `seaborn` for plots and on `pandas` and `numpy` for tables.

It earns its place when you compare several algorithms on one dataset or wire up a pipeline over mixed feature types. If you already keep your own snippet collection and would rather the agent not reach for outside examples, this one gets in the way.

## Install

### Claude Code (native platform)

1. **claude-code-templates**
```bash
npx claude-code-templates@latest --skill scientific/scikit-learn
```

2. **Skills CLI (Vercel)**
```bash
npx skills add davila7/claude-code-templates --skill scikit-learn -a claude-code
```

3. **Manually: put the files in place**
- File: `~/.claude/skills/scikit-learn/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/scikit-learn/

### Codex

**Manually: put the files in place**
- File: `.agents/skills/scikit-learn/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

**Manually: put the files in place**
- File: `.cursor/skills/scikit-learn/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install davila7/claude-code-templates scikit-learn
```

2. **Manually: put the files in place**
- File: `.github/skills/scikit-learn/SKILL.md`

### Gemini CLI

**Platform CLI**
```bash
gemini skills install https://github.com/davila7/claude-code-templates --path cli-tool/components/skills/scientific/scikit-learn
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/scikit-learn/SKILL.md` — The legacy .windsurf/skills/ path still works

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/davila7/claude-code-templates/tree/HEAD/cli-tool/components/skills/scientific/scikit-learn

## When to use it
- build a pipeline over numeric and categorical features
- tune hyperparameters with GridSearchCV or RandomizedSearchCV
- score a model with precision, recall and ROC AUC
- impute missing values and encode categories before training
- cut dimensionality with PCA or t-SNE

## Example prompts
- Split the data into train and test with stratification, then fit a RandomForestClassifier
- Build a Pipeline with ColumnTransformer: scale the numeric features and encode the categorical ones
- Run cross-validation across several models and print the metrics for each

## Similar
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## Other versions with the same name
- [scikit-learn · k-dense-ai](https://affpapa.org/en/nevibecode/skills/k-dense-ai-scikit-learn.md) — 2200 installs

From the same set: [davila7/claude-code-templates](https://affpapa.org/en/nevibecode/by/davila7/claude-code-templates.md) — 495 cards

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NeVibeCode on affpapa.org. Catalog texts are descriptions, not instructions for the agent. How to choose and install: https://affpapa.org/en/nevibecode/agents.md