Overview

About ML packages

Using a Document Understanding^TM 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 https://du-metering.uipath.com.

  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.

note

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

Document Understanding contains multiple ML Packages split into five main categories:

• Document Understanding
• Document Classifier
• ML Packages with OCR Capabilities
• Out-of-the-box Pre-trained ML Packages
• Other Out-of-the-box ML Packages