scikit-learn
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.
Third-Party Skill: Review the code before installing. Skills execute in your AI assistant's environment and can access your files. Learn more about security
Installation
View all platforms →skilz install davila7_claude-code-templates/scikit-learn skilz install davila7_claude-code-templates/scikit-learn --agent opencode skilz install davila7_claude-code-templates/scikit-learn --agent codex skilz install davila7_claude-code-templates/scikit-learn --agent gemini
First time? Install Skilz: pip install skilz
Works with 14 AI coding assistants
Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...
Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/davila7/claude-code-templates cp -r claude-code-templates/cli-tool/components/skills/scientific/scikit-learn ~/.claude/skills/ Need detailed installation help? Check our platform-specific guides:
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Details
- Owner
- davila7
- Repository
- claude-code-templates
- Stars
- 13,835
- Forks
- 1,200
- Type
- Technical
- Meta-Domain
- data ai
- Primary Domain
- machine learning
- Sub-Domain
- learning models model
- Skill Size
- 114.9 KB
- Files
- 9
- Quality Score
- 68.9
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Extracted using NLP analysis
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