UiPath UiPath-SAIv1 Exam With Confidence Using Practice Dumps

In UiPath AI Center, the platform supports several types of machine learning (ML) models, including:

Out-of-the-box models from UiPath: Pre-built models designed for common automation tasks.

Models from UiPath technology partners: External models developed by UiPath’s partners.

Open-source models: Community-contributed models that can be used and adapted for various use cases.

Custom models: Models that users build and train specifically for their projects using their datasets.

This flexibility in model support ensures that organizations can leverage a wide range of machine learning capabilities to suit different automation needs.

For more details, refer to:

UiPath AI Center Documentation: AI Center Models

Machine Learning Model Types: Types of Models in UiPath AI Center

The DocumentUnderstanding ML package is a generic, retrainable model designed to handle various document types that are not covered by out-of-the-box models. It allows for the extraction of data from structured and semi-structured documents by building a model from scratch through training. This package is highly flexible and can be tailored to fit different document formats, making it ideal when specific document types are not pre-configured in UiPath’s out-of-the-box offerings.(Source: UiPath Documentation on ML Packages

 According to the UiPath documentation, the RegEx Extractor is a data extraction method that uses regular expressions to define and capture data from documents1. The RegEx Extractor does not consume any page units, which are the units of measurement for the consumption of Document Understanding services2. Therefore, the page unit cost per extracted page for the RegEx Extractor is 0.

References:

1: RegEx Extractor 2: Document Understanding - Metering & Charging Logic