| name | model-evaluation-metrics |
| description | Model Evaluation Metrics - Auto-activating skill for ML Training. Triggers on: model evaluation metrics, model evaluation metrics Part of the ML Training skill category. |
| allowed-tools | Read, Write, Edit, Bash(python:*), Bash(pip:*) |
| version | 1.0.0 |
| license | MIT |
| author | Jeremy Longshore <jeremy@intentsolutions.io> |
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