Back to Glossary
Data Annotation
Data / Training / Evaluation
Labeling raw data for training AI models.
Data annotation is the process of labeling raw data such as text, images, or audio with meaningful tags so that supervised learning models can be trained effectively.
- Examples: Image bounding boxes, text sentiment labels, speech transcriptions.
- Importance: Annotation quality directly affects model accuracy.