document-understanding
2022.10
false
- Overview
- Document Understanding Process
- Quickstart Tutorials
- Framework Components
- ML Packages
- Pipelines
- Document Manager
- OCR Services
- Document Understanding deployed in Automation Suite
- Install and use
- First run experience
- Deploy UiPathDocumentOCR
- Deploy an out-of-the-box ML package
- Offline Bundles 2022.10.0
- Offline Bundles 2022.10.2
- Offline Bundles 2022.10.4
- Offline Bundles 2022.10.6
- Offline Bundles 2022.10.8
- Offline bundles 2022.10.9
- Offline Bundles 2022.10.10
- Offline bundles 2022.10.11
- Offline bundles 2022.10.12
- Offline bundles 2022.10.13
- Offline bundles 2022.10.14
- Offline bundles 2022.10.14+patch1
- Use Document Manager
- Use the Framework
- Document Understanding deployed in AI Center standalone
- Deep Learning
- Training High Performing Models
- Licensing
- References
- UiPath.Abbyy.Activities
- UiPath.AbbyyEmbedded.Activities
- UiPath.DocumentUnderstanding.ML.Activities
- UiPath.DocumentUnderstanding.OCR.LocalServer.Activities
- UiPath.IntelligentOCR.Activities
- UiPath.OCR.Activities
- UiPath.OCR.Contracts
- UiPath.DocumentProcessing.Contracts
- UiPath.OmniPage.Activities
- UiPath.PDF.Activities
Document Understanding User Guide
Last updated Mar 5, 2025
- What Can a Data Extraction ML Model Do?
- Training and Evaluation Datasets
- Data Extraction Components
- Build a High Performing ML Model
- 1. Choose an OCR Engine
- 2. Create a Training Dataset
- 3. Create an Evaluation Dataset
- 4. Define Fields
- 5. Configure the Fields
- 6. Label the Training Dataset
- 7. Label the Evaluation Dataset
- 8. Train and Evaluate the Model
- 9. Define and Implement Business Rules
- 10. (Optional) Choose a Confidence Threshold
- 11. Training Using Data From Validation Station
- 12. The Auto-Fine-tuning Loop (Preview)
- 13. Deploy Your Automation
