UMAP Optimization Skill
CommunitySpeed up UMAP embeddings for large datasets.
AuthorWesley1600
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Large-scale UMAP embeddings can be slow to train and evaluate. This skill provides optimization strategies to accelerate UMAP-based pipelines while preserving embedding quality.
Core Features & Use Cases
- Computational Efficiency: Cluster caching and mixed-precision strategies to reduce compute time.
- Scalability Enhancements: FAISS integration for large datasets and efficient kNN search.
- Stability & Practicality: Auto-alignment calibration and gradient clipping to improve numerical stability.
Quick Start
Apply optimization steps to your umap_analogy_engine workflow, starting with enabling cluster caching and mixed-precision settings, then consider FAISS for very large N.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: UMAP Optimization Skill Download link: https://github.com/Wesley1600/ClaudeCodeFrameWork/archive/main.zip#umap-optimization-skill Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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