# Model Evaluation

> Classification, regression, LLM, and agent evaluation — metrics, LLM-as-judge, bias detection, and A/B testing.

![Status: complete](https://img.shields.io/badge/status-complete-brightgreen)

Open [`16-model-evaluation.ipynb`](./16-model-evaluation.ipynb) for learning objectives, prerequisites, and recommended reading order.

## Topics Covered

- Classification metrics: accuracy, precision, recall, AUC
- LLM evaluation: BLEU, ROUGE, BERTScore, LLM-as-judge
- Bias and fairness measurement
- Agent evaluation: tool use, task success, multi-step scoring

## Prerequisites

[09-mlops/README.md](../09-mlops/README.md) · [15-ai-agents/README.md](../15-ai-agents/README.md)

## What Comes Next

[17-debugging-troubleshooting/README.md](../17-debugging-troubleshooting/README.md)
