umap-learn
Description
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
How to Use
- Visit the GitHub repository to get the SKILL.md file
- Copy the file to your project root or .cursor/rules directory
- Restart your AI assistant or editor to apply the new skill
Tags
About umap-learn
umap-learn is an AI skill in the llm-agents category, designed to help developers and users work more effectively with AI tools. UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
This skill has earned 2,800 stars on GitHub, reflecting strong community adoption and trust. It is compatible with claude.
Key Capabilities
Why Use umap-learn
Adding umap-learn to your AI workflow can significantly enhance your productivity in llm-agents tasks. With pre-defined prompt templates and best practices, this skill helps AI assistants better understand your requirements and deliver more accurate responses.
Whether you use claude, you can easily integrate this skill into your existing development environment.
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