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Model Evaluation Metrics

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'Build model evaluation metrics operations. Auto-activating skill for ML Training. Triggers on: model evaluation metrics, model evaluation metrics Part of the ML Training skill category. Use when working with model evaluation metrics functionality. Trigger with phrases like \"model evaluation metrics\", \"model metrics\", \"model\". '

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  • Added September 12, 2026
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Scanned September 12, 2026

npx -y skills add thedixitjain/the-mega-skill-library --skill model-evaluation-metrics --agent claude-code

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SKILL.md
---
name: model-evaluation-metrics
description: "'Build model evaluation metrics operations. Auto-activating skill for ML Training. Triggers on: model evaluation metrics, model evaluation metrics Part of the ML Training skill category. Use when working with model evaluation metrics functionality. Trigger with phrases like \"model evaluation metrics\", \"model metrics\", \"model\". '"
allowed-tools: "Read, Write, Edit, Bash(python:*), Bash(pip:*)"
category: data-science-and-ml
source_repo: jeremylongshore/claude-code-plugins-plus-skills
source_path: "skills/07-ml-training/model-evaluation-metrics/SKILL.md"
source_url: https://github.com/jeremylongshore/claude-code-plugins-plus-skills/blob/HEAD/skills/07-ml-training/model-evaluation-metrics/SKILL.md
---

# Model Evaluation Metrics

## Overview

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.

## Instructions

1. Provides step-by-step guidance for model evaluation metrics
2. Follows industry best practices and patterns
3. Generates production-ready code and configurations
4. Validates outputs against common standards

## Examples

**Example: Basic Usage**
Request: "Help me with model evaluation metrics"
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

---

**Source:** [`jeremylongshore/claude-code-plugins-plus-skills`](https://github.com/jeremylongshore/claude-code-plugins-plus-skills) → `skills/07-ml-training/model-evaluation-metrics/SKILL.md`

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