ai-center
2023.4
false
- Release Notes
- Before you begin
- Getting started
- Installing AI Center
- Migration and upgrade
- Projects
- Datasets
- Data Labeling
- About Data Labeling
- Managing Data Labels
- ML packages
- Out of the box packages
- Pipelines
- ML Skills
- ML Logs
- Document UnderstandingTM in AI Center
- AI Center API
- How to
- Licensing
- Basic Troubleshooting Guide
About Data Labeling
AI Center User Guide
Last updated Oct 22, 2024
About Data Labeling
The Data Labeling page, accessible from the Data Labeling menu after selecting a project, lists all data labeling sessions within a project.
Data Labeling enables you to upload raw data, annotate text data in the labelling tool (for classification or entity recognition), and use the labelled data to train ML models. It is also used by the human reviewer to re-label incorrect predictions as part of the feedback process. This feature brings the complete text model building workflow within AI Center, without the need for third-party tools and integrations.