evaluating-machine-learning-models
This skill allows Claude to evaluate machine learning models using a comprehensive suite of metrics. It should be used when the user requests model performance analysis, validation, or testing. Claude can use this skill to assess model accuracy, precision, recall, F1-score, and other relevant metrics. Trigger this skill when the user mentions "evaluate model", "model performance", "testing metrics", "validation results", or requests a comprehensive "model evaluation".
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Installation for Agentic Skill
View all platforms →skilz install jeremylongshore/claude-code-plugins-nixtla/evaluating-machine-learning-models skilz install jeremylongshore/claude-code-plugins-nixtla/evaluating-machine-learning-models --agent opencode skilz install jeremylongshore/claude-code-plugins-nixtla/evaluating-machine-learning-models --agent codex skilz install jeremylongshore/claude-code-plugins-nixtla/evaluating-machine-learning-models --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/jeremylongshore/claude-code-plugins-nixtla cp -r claude-code-plugins-nixtla/archive/backups-20251108/skill-structure-cleanup-20251108-073936/plugins/ai-ml/model-evaluation-suite/skills/model-evaluation-suite ~/.claude/skills/ Need detailed installation help? Check our platform-specific guides:
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Agentic Skill Details
- Owner
- jeremylongshore (GitHub)
- Repository
- claude-code-plugins-nixtla
- Type
- Technical
- Meta-Domain
- data ai
- Primary Domain
- machine learning
- Market Score
- 17.1
Browse Category
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