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UiPath Specialized AI Associate Exam (2023.10) Sample Questions (Q241-Q246):

NEW QUESTION # 241
What function in the train.py file is responsible for persisting the trained model?

A. save(self)
B. train(setf. trainmg_directory}
C. evaluate(self, evaluation_directory)
D. __init_(self)

Answer: A

Explanation:
In the context of a machine learning pipeline, specifically within the train.py file in UiPath AI models, the function responsible for persisting the trained model is typically named save(self). This function is invoked after the model has been trained, and it ensures that the model's state, weights, and configurations are saved to disk or another persistent storage medium. The saved model can then be reused for inference or further fine- tuning in future executions.
For more details, refer to:
UiPath AI Center Documentation: Training Models
Model Persistence: Saving Machine Learning Models in AI Center

NEW QUESTION # 242
What is the Machine Learning Extractor?

A. A tool that helps extract data from different document structures, and is particularly useful when the same document has multiple formats.
B. A tool using machine learning models to identify and report on data targeted for data extraction.
C. An extraction model that can be enabled and trained in Al Center. For better accuracy. 25 documents per model are recommended to train the model.
D. A specialized model that can recognize multiple languages in the same document using API calls to a Hugging Face model with over 250 languages.

Answer: A

Explanation:
The Machine Learning Extractor utilizes machine learning models to effectively extract data from documents, especially when dealing with varying structures or formats within the same document type. This capability is crucial in scenarios where documents do not follow a strict template and have variations in their layout or content organization. The extractor can be trained to understand these variations and accurately extract the needed information.
The Machine Learning Extractor is a data extraction tool that uses machine learning models to extract data from various types of documents, such as invoices, receipts, or forms. It is especially useful when the same document type has multiple layouts or formats, as it can learn and infer the values for the targeted fields, even from documents and layouts it has never seen before1.
The Machine Learning Extractor can be used with one of UiPath's public Document Understanding endpoints, which provide generic models for certain document types, or with custom trained machine learning models hosted in AI Center, which can be tailored to specific use cases. The Machine Learning Extractor can be configured and trained using the Data Extraction Scope activity in UiPath Studio2.
References:
Document Understanding - Machine Learning Extractor
UiPath Activities - Data Extraction Scope

NEW QUESTION # 243
What are the mandatory activities to be included in an automation workflow to allow a remote knowledge worker to pick up an action that validates the extracted data in the form of a Document Validation Action?

A. Document Understanding Process Activities.
B. Create Document Validation Action, Wait for Document Validation Action and Resume.
C. Present Validation Station, Wait for Document Validation Action and Resume.
D. Orchestration Process Activities.

Answer: B

Explanation:
To enable a remote knowledge worker to validate the extracted data from documents in Action Center, the automation workflow needs to include the following activities12:
Create Document Validation Action: This activity creates an action of type Document Validation in Orchestrator Action Center, and returns an action object as output. The action object contains the information needed to resume the workflow after the human validation is completed. The input properties of this activity include the action details, such as title, priority, catalog, and folder, and the document validation data, such as the document object model, the document text, the taxonomy, and the automatic extraction results.
Wait for Document Validation Action and Resume: This activity suspends the execution of the workflow until the human validation is done in Action Center, and then resumes it with the updated extraction results. The input property of this activity is the action object obtained from the Create Document Validation Action activity. The output property is the validated extraction results, which can be used for further processing or exporting.
References: 1: Create Document Validation Action 2: Wait for Document Validation Action and Resume

NEW QUESTION # 244
Which features in Generative Annotation are automatically enabled on datasets in Communication Mining technology?

A. Taxonomy Uploading
B. Preview Mode
C. Sentiment Analysis
D. Assisted Labelling

Answer: D

Explanation:
In UiPath Communication Mining, the Generative Annotation feature automatically enables Assisted Labelling on datasets. Assisted Labelling helps to accelerate the labeling process by automatically suggesting relevant labels based on the content of the communications. This feature significantly improves the efficiency of the model training process by reducing the manual effort required to label large datasets.
For more details, refer to:
UiPath Communication Mining Documentation: Generative Annotation and Assisted Labelling Labeling and Annotation in UiPath Communications Mining: UiPath AI Center Documentation

NEW QUESTION # 245
Which is the correct description of the Configure Extractors Wizard?

A. An optional step in the extractor configuration which allows choosing which extractors are applied to each document type.
B. A mandatory step in the extractor configuration that allows choosing which extractors are applied to each field.
C. A mandatory step in the extractor configuration that allows choosing which extractors are applied to each document type.
D. A mandatory step in the extractor configuration that allows choosing which extractors are applied to each document type and field.

Answer: D

Explanation:
The Configure Extractors Wizard is a tool that enables you to select and customize the extractors that are used for data extraction from documents. It is accessed via the Data Extraction Scope activity, which is a container for extractor activities. The wizard allows you to map the fields defined in your taxonomy with the fields supported by each extractor, and to set the minimum confidence level and the framework alias for each extractor. The wizard is mandatory for the extractor configuration, as it ensures that the extractors are applied correctly to each document type and field1.
References: Configure Extractors Wizard of Data Extraction Scope

NEW QUESTION # 246
......

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