AI
Evaluation (Eval)
Systematic assessment of AI model performance against defined criteria and test cases.
Why it matters
- Ensures AI systems meet quality standards
- Catches regressions before production
- Enables data-driven improvements
When to use
- Before deploying AI features
- When comparing model versions
- For ongoing quality monitoring
Common mistakes
- Evaluating on insufficient test cases
- Using metrics that do not match user needs
- Not automating evaluation in CI/CD
Related terms
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