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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions (Q96-Q101):

NEW QUESTION # 96
What do entities represent in UiPath Communications Mining?

A. Concepts, themes, and intents.
B. Thread properties.
C. Metadata properties.
D. Structured data points.

Answer: A

Explanation:
Entities are additional elements of structured data which can be extracted from within the verbatims. Entities include data such as monetary quantities, dates, currency codes, organisations, people, email addresses, URLs, as well as many other industry specific categories. Entities represent concepts, themes, and intents that are relevant to the business use case and can be used for filtering, searching, and analyzing the verbatims.
References:
* Communications Mining - Entities
* Communications Mining - Using Entities in your Application
* Communications Mining - Configuring Entities

NEW QUESTION # 97
What information should be provided when adding a classification label for the OOB (Out Of the Box) labeling template?

A. Name, Classification Type. Attribute name. Color, and Shortcut.
B. Name, Classification type, Attribute name, and Shortcut.
C. Name, Classification type. Input to be labeled. Attribute name. Shortcut, and Color.
D. Name, Input to be labeled. Attribute name, and Shortcut.

Answer: C

Explanation:
When setting up a classification label in UiPath's Out Of the Box (OOB) labeling templates, you need to provide several key details: the name of the label, the classification type (which defines the kind of label), the input to be labeled, the attribute name that describes the label's context, a shortcut for quick access, and a color for visual distinction. These fields ensure the label is fully defined and easy to manage in workflows.
(Source: UiPath Document Understanding documentation)

NEW QUESTION # 98
What is the definition of Deep Learning?

A. The theory and development of computer systems that are able to perform tasks that normally require human intelligence and decision making.
B. A sub-field of artificial intelligence that enables systems to learn from data.
Systems learn from previous experience and information to deduce and predict future information. To do this they use algorithms that learn to perform a specific task without being explicitly programmed.
C. An area of machine learning concerned with artificial neural networks.These are a series of algorithms that aim to recognize relationships in a set of data through a process that mimics biological neural networks.
D. A field of artificial intelligence that enables computers to gain high-level understanding from digital images or videos. If AI is the brain, then this is the eye that enables the computer to observe and understand. It works the same as the human eye.

Answer: C

NEW QUESTION # 99
How can the code be tested in a development or testing environment in the context of the Document Understanding Process?

A. Based on the use case developed, create test data to test existing and new tests.
B. Based on the use case developed, create test data to test existing tests.
C. Use them as a template to create other tests.
D. Simply run the existing tests

Answer: A

NEW QUESTION # 100
What does the Train stage of the Document Understanding Framework do?

A. Allows a human to validate and correct the extracted data.
B. Improves the extractor accuracy by learning from the classification result.
C. Allows the extractor to improve its prediction over time by using better OCR (Optical Character Recognition) engines.
D. Allows the model to learn from human-validated data.

Answer: D

Explanation:
In the UiPath Document Understanding Framework, the Train stage enables models to learn from human- validated data. This process involves feeding the corrections made by humans during the validation phase back into the model, allowing it to refine its predictions and improve accuracy over time.
UiPath Documentation
The training component is crucial for classifiers and extractors capable of learning from human feedback. By incorporating validated data, these components can adjust their algorithms to better handle similar documents in the future, enhancing the overall efficiency and effectiveness of the automation process.
Other options are incorrect because:
* B. Allows the extractor to improve its prediction over time by using better OCR engines: While better OCR engines can enhance data extraction, this is not the function of the Train stage.
* C. Allows a human to validate and correct the extracted data: This describes the Validation stage, not the Train stage.
* D. Improves the extractor accuracy by learning from the classification result: Training focuses on learning from human-validated extraction results, not just classification outcomes.
Therefore, the primary purpose of the Train stage is to allow the model to learn from human-validated data, thereby improving its future performance.

NEW QUESTION # 101
......

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Exam UiPath-SAIv1 questions and answers

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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions (Q96-Q101):

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