AI engineering glossary · ML fundamentals
What is Data-centric AI?
Data-centric AI: An approach that focuses on improving the quality, coverage and consistency of the data, rather than mainly tweaking model architecture. It holds that better labels and data often bring larger gains than model changes.
Data-centric AI: an example
Fixing 300 inconsistent labels in a defect dataset raises accuracy more than trying three new architectures.
Related terms
More ML fundamentals terms
- Dataset
- Decision threshold
- Discriminative model
- Distribution shift
- Double descent
- Early stopping
- Empirical risk minimisation
- Feature
Where you learn it
Data-centric AI is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.