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SkillHub ClubAnalyze Data & AIData / AI

scikit-learn

This skill provides detailed guidance for using scikit-learn, covering classification, regression, clustering, and preprocessing. It includes practical code examples, algorithm selection tables, and warnings about common mistakes like data leakage. The documentation helps users build ML pipelines and evaluate models effectively.

Packaged view

This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.

Stars
15,469
Hot score
99
Updated
March 20, 2026
Overall rating
A8.8
Composite score
7.7
Best-practice grade
N/A

Install command

npx @skill-hub/cli install k-dense-ai-claude-scientific-skills-scikit-learn
machine-learningpythondata-sciencemodel-trainingml-pipelines

Repository

K-Dense-AI/claude-scientific-skills

Skill path: scientific-skills/scikit-learn

This skill provides detailed guidance for using scikit-learn, covering classification, regression, clustering, and preprocessing. It includes practical code examples, algorithm selection tables, and warnings about common mistakes like data leakage. The documentation helps users build ML pipelines and evaluate models effectively.

Open repository

Best for

Primary workflow: Analyze Data & AI.

Technical facets: Data / AI.

Target audience: AI/ML teams looking for install-ready agent workflows..

License: Unknown.

Original source

Catalog source: SkillHub Club.

Repository owner: K-Dense-AI.

This is still a mirrored public skill entry. Review the repository before installing into production workflows.

What it helps with

  • Install scikit-learn into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
  • Review https://github.com/K-Dense-AI/claude-scientific-skills before adding scikit-learn to shared team environments
  • Use scikit-learn for ai/ml workflows

Works across

Claude CodeCodex CLIGemini CLIOpenCode

Favorites: 0.

Sub-skills: 0.

Aggregator: No.