scikit-learn
Supports machine learning in Python with scikit-learn: classification, regression, clustering, dimensionality reduction, evaluation, tuning and pipelines.
- Kind
- Skill
- Works with
- Claude Code, Codex, Cursor, Gemini / Antigravity
- Languages
- Python
- Source
- Scientific Agent Skills (K-Dense) @ 5f2bc0341354
- Path
- skills/scikit-learn/SKILL.md
- License
- MIT
- Jobs
- Implementation
InstallInstall it by hand, following the source.
gh skill install K-Dense-AI/scientific-agent-skills scikit-learn
# Scikit-learn ## Overview This skill provides comprehensive guidance for machine learning tasks using scikit-learn, the industry-standard Python library for classical machine learning. Use this skill for classification, regression, clustering, dimensionality reduction, preprocessing, model evaluation, and building production-ready ML pipelines. ## Installation Targets **scikit-learn 1.9.1**, verified with Python 3.13. The release requires Python 3.11+; use its published wheels for your interpreter/platform. See the [1.9 release notes](https://scikit-learn.org/stable/whats_new/v1.9.html). The bundled scripts and regression tests are executable examples. Reference snippets using caller-provided `X`, `y`, columns, or placeholders are illustrative adaptations, not complete standalone programs. Install the PyPI package **`scikit-learn`** (not the deprecated `sklearn` package on PyPI). Import in code as `sklearn`. ```bash # Install scikit-learn using uv uv pip install "scikit-learn==1.9.1" # Optional: plotting utilities and bundled script dependencies uv pip install "scikit-learn[plots]==1.9.1" matplotlib pandas # Commonly used with uv pip install pandas numpy ``` …