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You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or planning anything new, in software or out of it (a talk, a business, a renovation).
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hyperparameter-tuner
hyperparameter-tunerManage hyperparameter tuner operations. Auto-activating skill for ML Training. Triggers on: hyperparameter tuner, hyperparameter tuner Part of the ML Training skill category. Use when working with hyperparameter tuner functionality. Trigger with phrases like "hyperparameter tuner", "hyperparameter tuner", "hyperparameter".
Independent GitHub snapshot · Automated classification · Original documentation governs
Documentation de la Skill
GitHubname: hyperparameter-tuner description: 'Manage hyperparameter tuner operations. Auto-activating skill for ML Training.
Triggers on: hyperparameter tuner, hyperparameter tuner
Part of the ML Training skill category. Use when working with hyperparameter tuner functionality. Trigger with phrases like "hyperparameter tuner", "hyperparameter tuner", "hyperparameter".
' allowed-tools: Read, Write, Edit, Bash(python:), Bash(pip:) version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:
- ai
- machine-learning compatibility: Designed for Claude Code
Hyperparameter Tuner
Overview
This skill provides automated assistance for hyperparameter tuner tasks within the ML Training domain.
When to Use
This skill activates automatically when you:
- Mention "hyperparameter tuner" in your request
- Ask about hyperparameter tuner patterns or best practices
- Need help with machine learning training skills covering data preparation, model training, hyperparameter tuning, and experiment tracking.
Instructions
- Provides step-by-step guidance for hyperparameter tuner
- Follows industry best practices and patterns
- Generates production-ready code and configurations
- Validates outputs against common standards
Examples
Example: Basic Usage Request: "Help me with hyperparameter tuner" Result: Provides step-by-step guidance and generates appropriate configurations
Prerequisites
- Relevant development environment configured
- Access to necessary tools and services
- Basic understanding of ml training concepts
Output
- Generated configurations and code
- Best practice recommendations
- Validation results
Error Handling
| Error | Cause | Solution |
|---|---|---|
| Configuration invalid | Missing required fields | Check documentation for required parameters |
| Tool not found | Dependency not installed | Install required tools per prerequisites |
| Permission denied | Insufficient access | Verify credentials and permissions |
Resources
- Official documentation for related tools
- Best practices guides
- Community examples and tutorials
Related Skills
Part of the ML Training skill category. Tags: ml, training, pytorch, tensorflow, sklearn