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