Free UiPath Certified Professional Specialized AI Professional v1.0 Exam UiPath-SAIv1 Exam Practice Test

What is the difference between OCR (Optical Character Recognition) and IntelligentOCR?

• OCR (Optical Character Recognition) is a method that reads text from images, recognizing each character and its position, while IntelligentOCR is an enhanced version of it that can also work with noisier input data.
• IntelligentOCR is simply a rebranding of the OCR (Optical Character Recognition), both of them being methods that read text from images, recognizing each character and its position.
• OCR (Optical Character Recognition) is a UiPath Studio activity package that contains IntelligentOCR as an activity used to read text from images, recognizing each character and its position. OCR is widely used in Document Understanding processes.
• IntelligentOCR is a UiPath Studio activity package that contains all the activities needed to enable information extraction, while OCR (Optical Character Recognition) is a method that reads text from images, recognizing each character and its position.

How can you build custom models supported by AI Center?

• Using the Al Center IDE (Integrated Development Environment).
• Using the Al Center model builder.
• Using a Python IDE (Integrated Development Environment) or an AutoML platform.
• Using a C/C++ IDE (Integrated Development Environment), then upload the code to Al Center IDE.

Which of the following OCR (Optical Character Recognition) engines is not free of charge?

• Tesseract.
• Microsoft Azure OCR.
• OmniPaqe.
• Microsoft OCR.

Which UiPath Communications Mining model performance factor assesses the proportion of the entire dataset that has informative label predictions?

• Average label performance.
• Coverage.
• Balance.
• Underperforming labels.

A Document Understanding Process is in production. According to best practices, what are thelocations recommended for exporting the result files?

• Network Attached Storage and Orchestrator Bucket.
• Locally, Temp Folder, Network Attached Storage, and Orchestrator Bucket.
• Orchestrator Bucket and Queue Item.
• On a VM, Orchestrator Bucket, and Network Attached Storage.

For an analytics use case, what are the recommended minimum model performance requirements in UiPath Communications Mining?

• Model Ratings of "Good" or better and individual performance factors rated as "Good" or better.
• Model Ratings of "Good" and individual performance factors rated as "Excellent".
• Model Ratings of "Excellent" and individual performance factors rated as "Good" or better.
• Model Ratings of "Excellent" and individual performance factors rated as "Excellent".

What is one of the purposes of the Config file in the UiPath Document Understanding Template?

• It contains the configuration settings for the UiPath Robot and Orchestrator integration.
• It stores the API keys and authentication credentials for accessing external services.
• It specifies the output file path and format for the processed documents.
• It defines the input document types and formats supported by the template.

Which is the correct description of the Configure Extractors Wizard?

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

Which of the following statements is true regarding reviewing and applying entities in UiPath Communications Mining?

• A single entity value can be split across multiple paragraphs.
• If the entity value is correctly predicted, but the entity type is wrong, it cannot be changed.
• All of the entities within a paragraph should be reviewed.
• All of the entities in a communication must be reviewed.

What is the Machine Learning Extractor?

• A specialized model that can recognize multiple languages in the same document using API calls to a Hugging Face model with over 250 languages.
• 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.
• A tool using machine learning models to identify and report on data targeted for data extraction.
• A tool that helps extract data from different document structures, and is particularly useful when the same document has multiple formats.