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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions:

1. Given the following scenario:
* You have a trained version of the Document Understanding Model with 1000 pages called v22.10.0.1.
* You have an evaluation dataset of 100 pages that gave a score of 0.72 for v22.10.0.1.
* The business team labeled 800 pages and they ask for an increment of the Model that would contain all
1000+800 pages.
What is the first recommended pipeline run configuration to create the new version?

A) Pipeline type: Evaluate
Package Major Version: 23.10.4.0 Package Minor Version: 0 Input Dataset: 1000+800 pages Evaluation Dataset: 100 pages
B) Pipeline type: Full Package Major Version: 23.10.4.0 Package Minor Version: 0 Input Dataset:
1000+800 pages Evaluation Dataset: 100 pages
C) Pipeline type: Full
Package Major Version: 23.10.4.0 Package Minor Version: 1 Input Dataset: 800 pages Evaluation Dataset: 100 pages
D) Pipeline type: Training Package Major Version: 23.10.4.0 Package Minor Version: 1 Input Dataset:
1000+800 Evaluation Dataset: N/A

2. Which of the following is a characteristic of a poorly-performing model in UiPath Communications Mining?

A) The model makes correct predictions across the majority of the dataset.
B) 2% of the dataset has been reviewed by a model trainer.
C) Many of the labels in the taxonomy have amber or red performance warnings.
D) All of the labels in the dataset have at least 25 training examples.

3. What can be done in the Reports section of the dataset navigation bar in UiPath Communication Mining?

A) Access detailed, queryable charts, statistics, and customizable dashboards.
B) Train models using unsupervised learning.
C) View, save, and modify dataset model versions.
D) Monitor model performance and receive recommendations.

4. What can the Custom Named Entity Recognition out-of-the-box model be used for?

A) Extract and classify text in emails, letters, web pages, research papers, and call transcripts.
B) Understand sentiment in product reviews, customer surveys, social media posts, and emails.
C) Classify text in resumes, emails, web pages, and other formats.
D) Relate customer questions to FAQ documents and automatically pull responses from these documents.

5. In which of the following scenarios, the ML Classifier is the only recommended classifier to be used, according to best practice?

A) When the custom document types are not similar and file splitting is necessary.
B) When the custom document types are very similar and file splitting is not necessary.
C) When the custom document types are not similar and file splitting is not necessary.
D) When the custom document types are very similar and file splitting is necessary.

Solutions: