# Scikit Learn

> Scikit-learn machine learning library. Use for classical ML.

- **Type:** Skill
- **Install:** `agentstack add skill-g1joshi-agent-skills-scikit-learn`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [G1Joshi](https://agentstack.voostack.com/s/g1joshi)
- **Installs:** 0
- **Category:** [Developer Tools](https://agentstack.voostack.com/c/developer-tools)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [G1Joshi](https://github.com/G1Joshi)
- **Source:** https://github.com/G1Joshi/Agent-Skills/tree/main/skills/ai-ml/scikit-learn
- **Website:** https://skills.sh/g1joshi/agent-skills

## Install

```sh
agentstack add skill-g1joshi-agent-skills-scikit-learn
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Scikit-learn

Scikit-learn is the gold standard for "Classical ML" (Regression, SVM, Random Forest). v1.6 (2025) adds **Array API** support (running on GPUs via PyTorch/CuPy).

## When to Use

- **Tabular Data**: Random Forests / Gradient Boosting.
- **Preprocessing**: `StandardScaler`, `LabelEncoder`.
- **Small Data**: When Deep Learning is overkill.

## Core Concepts

### Estimators

Everything implements `.fit(X, y)` and `.predict(X)`.

### Pipelines

Chaining preprocessing and modeling: `Pipeline([('scaler', StandardScaler()), ('svc', SVC())])`.

### Array API

Passing PyTorch tensors directly to Scikit-learn without converting to NumPy (keeping data on GPU).

## Best Practices (2025)

**Do**:

- **Use Pipelines**: Prevent data leakage during cross-validation.
- **Use `HistGradientBoostingClassifier`**: It is much faster than standard extraction implementation (inspired by LightGBM).

**Don't**:

- **Don't use for Images/Audio**: Use PyTorch/DL for unstructured data.

## References

- [Scikit-learn Documentation](https://scikit-learn.org/)

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [G1Joshi](https://github.com/G1Joshi)
- **Source:** [G1Joshi/Agent-Skills](https://github.com/G1Joshi/Agent-Skills)
- **License:** MIT
- **Homepage:** https://skills.sh/g1joshi/agent-skills

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-g1joshi-agent-skills-scikit-learn
- Seller: https://agentstack.voostack.com/s/g1joshi
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.