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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions (Q103-Q108):

NEW QUESTION # 103
What does the darker shading of a label prediction represent in Explore in UiPath Communications Mining?

A. An incorrect prediction.
B. A lower confidence score.
C. A higher confidence score.
D. Multiple label predictions.

Answer: C

Explanation:
In UiPath Communications Mining, the shading of label predictions in the Explore section indicates confidence levels. Darker shading represents a higher confidence score, meaning the model is more certain of the prediction made for that particular label

NEW QUESTION # 104
Which OCR (Optical Character Recognition) option is recommended to be initially utilized for document processing in a project?

A. UiPath Document OCR.
B. Tesseract OCR.
C. UiPath CJK (for Chinese. Japanese. Korean).
D. OmniPage.

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 # 105
Which role consumes ML Skills within customized workflows in Studio using the ML Skill activity from the UiPath.MLServices.Activities package?

A. Administrator.
B. Data Scientist.
C. RPA Developer.

Answer: C

Explanation:
D Process Controller

NEW QUESTION # 106
How many types of synchronization mechanisms exist in the Document Understanding Process to prevent multiple robots to write in a file at the same time?2

A. 0
B. 1
C. 2
D. 3

Answer: C

Explanation:
The Document Understanding Process uses two types of synchronization mechanisms to prevent multiple robots from writing in a file at the same time: file locks and queues. File locks are used to ensure that only one robot can access a file at a time, while queues are used to store the information extracted from the documents and to avoid data loss or duplication. The process uses the following activities to implement these mechanisms:
* File Lock Scope: This activity creates a lock on a file or folder and executes a set of activities within it.
The lock is released when the scope ends or when an exception occurs. This activity ensures that only one robot can read or write a file or folder at a time, and prevents other robots from accessing it until the lock is released.
* Add Queue Item: This activity adds an item to a queue in Orchestrator, along with some relevant information, such as a reference, a priority, or a deadline. The item can be a JSON object, a string, or any serializable .NET type. This activity ensures that the information extracted from the documents is stored in a queue and can be retrieved by another robot or process later.
* Get Queue Items: This activity retrieves a collection of items from a queue in Orchestrator, based on some filters, such as status, reference, or creation time. The items can be processed by the robot or passed to another activity, such as Update Queue Item or Delete Queue Item. This activity ensures that the information stored in the queue can be accessed and manipulated by the robot or process.
References: Document Understanding Process: Studio Template, File Lock Scope, Add Queue Item, [Get Queue Items]

NEW QUESTION # 107
How is the Taxonomy component used in the Document Understanding Template?

A. To assign predefined document categories based on content similarity, simplifying classification tasks for easier document organization.
B. To define the document types and the pieces of information targeted for data extraction (fields) for each document type.
C. To convert scanned documents into machine-readable formats, utilizing taxonomy rules to enhance digitized content accuracy.
D. To automatically extract structured data fields from documents, leveraging taxonomy mappings for precise data extraction.

Answer: B

NEW QUESTION # 108
......

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