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Newly Released UiPath UiPath-SAIAv1 Exam PDF

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Total 248 questions

UiPath Specialized AI Associate Exam (2023.10) Questions and Answers

Question 41

Which of the following extractors can be used for Data Extraction Scope activity?

Options:

A.

Intelligent Form Extractor, Machine Learning Extractor. Logic Extractor, and Regex Based Extractor.

B.

Full Extractor. Machine Learning Extractor, Intelligent Form Extractor, and Regex Based Extractor.

C.

Form Extractor Incremental Extractor Machine Learning Extractor and Intelligent Form Extractor

D.

Regex Based Extractor. Form Extractor. Intelligent Form Extractor, and Machine Learning Extractor.

Question 42

Why is having high coverage important for an automation-focused use case in UiPath Communications Mining?

Options:

A.

The higher the coverage, the lower the model's recall, resulting in greater throughput of automatable processes.

B.

High coverage ensures that the software consumes less computational resources, resulting in cost savings for the organization implementing the automation.

C.

High coverage on the model means that fewer communications will be sent for manual review and that fewer automatable processes are missed.

D.

With high coverage, you can increase the amount of data provided downstream via Streams.

Question 43

What additional information can be included in the exported data, apart from the extraction results?

Options:

A.

The number of occurrences and the extraction confidence.

B.

The page number from which the field was extracted and the exact position on the page.

C.

The extraction confidence and the digitization confidence.

D.

The position on the page.

Question 44

What happens to your document and the process of pre-labeling when you choose the "Predict" option from the "Predict" dropdown in Document Manager?

Options:

A.

It merges the results of the Generative Predict functionality and the results of the prelabeling endpoint (if configured). If the latter is not configured, it uses solely Generative Predict for all fields.

B.

It predicts fields using the Generative Prelabeling for OOTB document types and the pre-labeling endpoint for custom document types.

C.

It predicts fields using only the prelabeling endpoint model configured in the Prelabeling settings, and it does not use Generative Predict.

D.

It predicts all fields using the Generative Predict capability only, ignoring any pre-labeling endpoint that may be configured. If Generative Predict is not available, it will not predict any fields.

Page: 11 / 19
Total 248 questions