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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions (Q160-Q165):

NEW QUESTION # 160
What is the order of steps for automatically retraining and deploying a Document Understanding ML Model in Al Center with data from Document Validation Action?
Instructions: Drag the steps found on the "Left" and drop them on the "Right" in the correct order.

Answer:

Explanation:

To automatically retrain and deploy a Document Understanding Machine Learning (ML) Model in AI Center with data from the Document Validation Action, the steps should be followed in this order:
* Send Human in the Loop data to the used Dataset.
* This step involves sending the data that has been validated and corrected by human reviewers to the dataset. This data will be used for training the ML model.
* Use the Export feature from Document Manager using Scheduled Export.
* After the data is reviewed and validated, it needs to be exported from the Document Manager.
Scheduled Export automates this process, ensuring the dataset in AI Center is regularly updated with new data.
* Run Training/Full Pipeline in AI Center using Scheduled Pipeline with Auto-Retraining enabled.
* With the updated data in the dataset, the next step is to run the training or the full pipeline. The use of Scheduled Pipeline with Auto-Retraining ensures that the ML model is automatically retrained with the latest data.
* Enable the Auto Update feature in the ML Skill.
* Finally, enabling the Auto Update feature in the ML Skill ensures that the newly trained model is automatically deployed, making the improved model available for document understanding tasks.
Following these steps in the specified order allows for a streamlined process of continuously improving the ML model based on human-validated data, ensuring better accuracy and efficiency in document understanding tasks over time.

NEW QUESTION # 161
What happens during the Classify stage of the Document Understanding Framework?

A. The documents are included in one of the taxonomy document types or skipped.
B. The target fields are extracted from the document and sent to Action Center for human validation.
C. The extracted data is exported as a dataset.
D. The OCR engine is used to extract text from the image document.

Answer: A

Explanation:
According to the UiPath documentation, the Classify stage of the Document Understanding Framework is used to automatically determine what document types are found within a digitized file. The document types are defined in the project taxonomy, which is a collection of all the labels and fields applied to the documents in a dataset. The Classify stage uses one or more classifiers, which are algorithms that assign document types to files based on their content and structure. The classifiers can be configured and executed using the Classify Document Scope activity, which also allows for document type filtering, taxonomy mapping, and minimum confidence threshold settings. The Classify stage outputs the classification information in a unified manner, irrespective of the source of classification. The documents that are classified are then sent to the next stage of the framework, which is Data Extraction. The documents that are not classified or skipped are either excluded from further processing or sent to Action Center for human validation and correction.
References:
* Document Understanding - Document Classification Overview
* Document Understanding - Introduction
* Generative Extraction & Classification using Document Understanding in Cross-Platform Projects (Public Preview)

NEW QUESTION # 162
What does a UiPath Communications Mining taxonomy include?

A. General fields and datasets.
B. Messages, labels, and general fields.
C. Labels and sources.
D. Labels and general fields.

Answer: D

NEW QUESTION # 163
What is the purpose of the generative classifier?

A. To classify documents using generative models.
B. To classify documents using AI Center out-of-the-box generative models.
C. To classify documents using a combination of generative and specialized models.
D. To classify documents using generative OCR.

Answer: A

NEW QUESTION # 164
What is the role of the Taxonomy Manager?

A. To present a document processing specific user interface for validating and correcting automatic classification outputs.
B. To select which extractors are trained for each document type and field.
C. To create and edit a Taxonomy file specific to the current automation project.
D. To select the type of ML that can be used in the project.

Answer: C

Explanation:
The Taxonomy Manager is a tool that enables you to create and edit a Taxonomy file, which is an XML file that defines the document types and fields that are relevant for your automation project1. The Taxonomy file is used by the Classify Document Scope and Data Extraction Scope activities to perform document classification and data extraction, respectively2. The Taxonomy Manager allows you to add, remove, rename, or reorder document types and fields, as well as specify the data type, format, and validation rules for each field3. The Taxonomy Manager also provides a preview of the Taxonomy file and a validation feature to check for errors or inconsistencies.
References:
1: About Taxonomy Manager 2: About Document Understanding Framework 3: Using the Taxonomy Manager : Taxonomy Manager User Interface Description

NEW QUESTION # 165
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