Lesson 1077 of 2116
Eval Dataset Management: From Ad Hoc to Disciplined
Eval datasets are the foundation of AI quality. Managing them like any other data asset (versioning, governance, evolution) matters.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2eval datasets
- 3data management
- 4quality foundation
Concept cluster
Terms to connect while reading
Section 1
The premise
Eval datasets are quality infrastructure; managing them disciplinedly drives long-term AI quality.
What AI does well here
- Version control eval datasets like code
- Govern who can add, modify, or remove eval cases
- Evolve datasets as use cases change (don't ossify)
- Track dataset coverage of production input distribution
What AI cannot do
- Substitute disciplined management for actually building good eval cases
- Maintain datasets without dedicated ownership
- Eliminate the maintenance burden
Key terms in this lesson
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