label-training-data - Systematic Data Labeling for ML
Set up systematic data labeling workflows using Label Studio or similar tools
Tags
Updated: 2026-05-09Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Install Label Studio
- Configure labeling platform
- Design labeling interface
- Create label schema
- Format data
- Import unlabeled dataset
- Implement sampling strategy
- Measure inter-annotator agreement
- Track annotator performance
- Export labeled data
- Prepare training format
- Set up active learning
- Automate labeling workflow
Inputs
- Unlabeled dataset
- Label schema
- Labeling guidelines
- Pre-existing labels
- Model predictions
- Budget constraints
- Domain experts
Outputs
- Labeled dataset
- Training-ready format
- Quality metrics
- Annotation exports
- Labeling reports
Requirements
- Label Studio
- Python environment
- Docker (optional)
- PostgreSQL (optional)
- Port 8080 access
- Sufficient disk space