tuning-hyperparameters
This skill enables Claude to optimize machine learning model hyperparameters using grid search, random search, or Bayesian optimization. It is used when the user requests hyperparameter tuning, model optimization, or improvement of model performance. The skill analyzes the current context, generates code for the specified search strategy, handles data validation and errors, and provides performance metrics. Trigger terms include "tune hyperparameters," "optimize model," "grid search," "random search," and "Bayesian optimization."
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Installation for Agentic Skill
View all platforms →skilz install jeremylongshore/claude-code-plugins-nixtla/tuning-hyperparameters skilz install jeremylongshore/claude-code-plugins-nixtla/tuning-hyperparameters --agent opencode skilz install jeremylongshore/claude-code-plugins-nixtla/tuning-hyperparameters --agent codex skilz install jeremylongshore/claude-code-plugins-nixtla/tuning-hyperparameters --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/skills-migration-20251108-070147/plugins/ai-ml/hyperparameter-tuner/skills/hyperparameter-tuner ~/.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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