Model evaluation metrics
Model Evaluation Metrics - Auto-activating skill for ML Training. Triggers on: model evaluation metrics, model evaluation metrics Part of the ML Training skill category.From its SKILL.md
npx -y skills add ComeOnOliver/skillshub --skill model-evaluation-metricsAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
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Model Evaluation Metrics
Purpose
This skill provides automated assistance for model evaluation metrics tasks within the ML Training domain.
When to Use
This skill activates automatically when you:
- Mention "model evaluation metrics" in your request
- Ask about model evaluation metrics patterns or best practices
- Need help with machine learning training skills covering data preparation, model training, hyperparameter tuning, and experiment tracking.
Capabilities
- Provides step-by-step guidance for model evaluation metrics
- Follows industry best practices and patterns
- Generates production-ready code and configurations
- Validates outputs against common standards
Example Triggers
- "Help me with model evaluation metrics"
- "Set up model evaluation metrics"
- "How do I implement model evaluation metrics?"
Related Skills
Part of the ML Training skill category. Tags: ml, training, pytorch, tensorflow, sklearn
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.