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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions (Q193-Q198):
NEW QUESTION # 193
Which OCR (Optical Character Recognition) option is recommended to be initially utilized for document processing in a project?
Answer: A
Explanation:
In UiPath's Document Understanding Framework, UiPath Document OCR is recommended as the initial OCR engine for processing documents. This OCR option is optimized for extracting text from a wide variety of document types and provides good accuracy with structured, semi-structured, and unstructured documents.
It is designed to work seamlessly within the UiPath Document Understanding process and is highly compatible with other UiPath activities and models, making it a preferred choice for starting document processing in most projects.
For more details, refer to:
* UiPath Document Understanding Framework: UiPath OCR Engines
* UiPath Document OCR: UiPath OCR Guide
NEW QUESTION # 194
What is the role of the dispatcher in the Document Understanding Process?
Answer: D
Explanation:
In the Document Understanding framework, the dispatcher is responsible for ensuring that one job is created for each input file. It works by submitting files to be processed individually, ensuring that each document or group of documents is handled as a separate transaction. This allows for more efficient processing and better tracking of each file, especially in high-volume workflows where managing each file as a separate job is critical for performance and error handling.
(Source: UiPath Documentation on Document Understanding)
NEW QUESTION # 195
When processing a document type that comes in a high variety of layouts, what is the recommended data extraction methodology?
Answer: B
Explanation:
Based on the classification of documents, there are two common types of data extraction methodologies: rule- based data extraction and model-based data extraction1. Rule-based data extraction targets structured documents, while model-based data extraction is used to process semi-structured and unstructured documents1. However, neither of these methods alone can handle the high variety of layouts that some document types may have. Therefore, a hybrid data extraction approach is recommended, which combines the strengths of both methods and allows for more flexibility and accuracy23. A hybrid data extraction approach can use one or more extractors, such as RegEx Based Extractor, Form Extractor, Intelligent Form Extractor, Machine Learning Extractor, or FlexiCapture Extractor, depending on the document type and the fields of interest3. The Data Extraction Scope activity in UiPath enables the configuration and execution of a hybrid data extraction methodology, by allowing the user to customize which fields are requested from each extractor, what is the minimum confidence threshold for a given data point extracted by each extractor, what is the taxonomy mapping, at field level, between the project taxonomy and the extractor's internal taxonomy (if any), and how to implement "fall-back" rules for data extraction2.
References: 2: Data Extraction Overview 3: Data Extraction 1: Document Processing with Improved Data Extraction
NEW QUESTION # 196
Under what condition can a project be deleted in UiPath AI Center?
Answer: A
Explanation:
A project in UiPath AI Center is an isolated group of resources (datasets, pipelines, packages, skills, and logs) that you use to build a specific ML solution. You can create, edit, or delete projects from the Projects page or the project's Dashboard page. However, you can only delete a project if it does not have any package currently deployed in a skill. A package is a versioned and deployable unit of an ML model or an OS script that can be used to create an ML skill. A skill is a consumer-ready, live deployment of a package that can be used in RPA workflows in Studio. If a project has a package deployed in a skill, you need to undeploy the skill first before deleting the project. This is to ensure that you do not accidentally delete a project that is being used by a skill12.
References: 1: AI Center - Managing Projects 2: AI Center - Managing ML Skills
NEW QUESTION # 197
What happens during the Classify stage of the Document Understanding Framework?
Answer: A
NEW QUESTION # 198
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