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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions (Q158-Q163):

NEW QUESTION # 158
Which of the following statements is true regarding reviewing and applying entities in UiPath Communications Mining?

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

Answer: D

Explanation:
According to the UiPath Communications Mining documentation, reviewing and applying entities is a crucial step for improving the accuracy and performance of the entity extraction models. When reviewing entities, users should check all of the predicted entities within a paragraph, as well as any missing or incorrect ones.
Users can accept, reject, edit, or create entities using the platform's interface or keyboard shortcuts. Users can also change the entity type if the value is correct but the type is wrong. Reviewing and applying entities helps the platform learn from the user feedback and refine its predictions over time. It also helps users assess the automation potential and benefit of the communications data.
References:
* Communications Mining - Reviewing and applying entities
* Communications Mining - Improving entity performance

NEW QUESTION # 159
Why is the Shuffle training mode important in the "Explore" phase while working with UiPath Communications Mining?

A. Because it helps create a balanced model by focusing on outlier labels with sufficient training examples but low confidence.
B. Because it creates a high precision model, focusing on labels with low precision and a low number of examples.
C. Because it creates a new model version with shuffled labels and general fields and lets the user explore to understand the state of the model
D. Because it helps create a balanced model free from labelling bias by introducing random variation into the training data.

Answer: D

Explanation:
The Shuffle training mode in the "Explore" phase of UiPath Communications Mining helps to introduce randomness into the training data. This prevents labeling bias by ensuring that the model does not overly focus on certain labels or examples, leading to a more balanced and generalized model. By shuffling the data, the model is exposed to a diverse range of examples, which enhances its ability to make accurate predictions across different labels and datasets.
(Source: UiPath Communications Mining documentation)

NEW QUESTION # 160
Under what condition can a dataset be edited in UiPath AI Center?

A. If it is not being used in any active pipeline.
B. If it is not linked to any data labeling session.
C. There are no restrictions in editing a dataset.
D. If it has not been modified within the last 24 hours.

Answer: A

NEW QUESTION # 161
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. Many of the labels in the taxonomy have amber or red performance warnings.
C. All of the labels in the dataset have at least 25 training examples.
D. 2% of the dataset has been reviewed by a model trainer.

Answer: B

NEW QUESTION # 162
When creating a training dataset, what is the recommended number of samples for the Classification fields?

A. 5-10 document samples from each class.
B. 50-200 document samples from each class.
C. 20-50 document samples from each class.
D. 10-20 document samples from each class.

Answer: C

NEW QUESTION # 163
......

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