Document Understanding
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Document Understanding User Guide
Last updated 2024年4月1日


About ML Packages

Using a Document Understanding ML Package involves these steps:

  • Collecting document samples and the requirements of the data points that need to be extracted.
  • Labeling documents using Document Manager.
  • Downloading or exporting labeled documents as a Training dataset and uploading the exported folder to AI Center Storage.
  • Running a Training Pipeline on AI Center.
  • Deploying the trained model as an ML Skill in AI Center.
  • Querying the ML Skill from an RPA workflow using the UiPath.DocumentUnderstanding.ML activity package.
    Note: Remember that using Document Understanding ML Packages requires that the machine on which AI Center is installed can access
    Important: When creating a UiPath.DocumentUnderstanding.ML.Activities Package in AI Center, the package name should not be any python reserved keyword, such as class , break, from, finally, global, None, etc. Note that this list is not exhaustive since the package name is used for class <pkg-name> and import <pkg-name> .

These are out-of-the-box Machine Learning Models to classify and extract any commonly occurring data points from semi-structured or unstructured documents, including regular fields, table columns, and classification fields, in a template-less approach.


Out-of-the-box Machine Learning Packages that are delivered by UiPath have version 0 and are already available on your tenant, meaning that there is no need to download them.

Download is available only for versions 1 or higher, that were already trained by you.

Types of ML Packages

  • About ML Packages
  • Types of ML Packages

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