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UiPath Specialized AI Associate Exam (2023.10) Sample Questions (Q113-Q118):

NEW QUESTION # 113
What is the correct order of recommended steps when introducing new labels into a mature taxonomy?
Instructions: Drag the steps found on the "Left" and drop them on the "Right" in the correct order.

Answer:

Explanation:

Explanation:
A screenshot of a computer AI-generated content may be incorrect.

Create the new label by assigning it at least once. This is the initial step to introduce a new category or classification within your data taxonomy.
Search for instances in the reviewed data where the new label should have been assigned, and apply the label accordingly. This step is crucial for maintaining consistency across your data set.
Use 'Missed Label' to find all additional missing examples in the reviewed data. This action helps in identifying and rectifying any instances that may have been overlooked during the initial review.
Check validation to ensure the label is performing as expected, and follow recommended actions if further training is required. Validation is key to assess the accuracy and performance of the new label within the system.

NEW QUESTION # 114
Which UiPath Communications Mining label category is often mapped to a service catalogue?

A. Root causes / Exceptions.
B. Process / Request types.
C. Products / Systems.
D. Customer experiences.

Answer: B

Explanation:
In UiPath's Communications Mining, the label category "Process / Request types" is often mapped to a service catalog. This label category is used to identify different types of processes or service requests that are common in customer communications. It enables automation processes to classify incoming communications into distinct service categories, which are typically mapped to entries in a service catalog. This allows organizations to handle customer inquiries more effectively by routing them to the correct department or service line based on the classification provided by this label category.
For example, if a communication relates to a request for support or a service inquiry, it would be classified under "Process / Request types," allowing it to be mapped directly to an appropriate service in the service catalog.
For more details, refer to:
UiPath Communications Mining Documentation: Label Categories
Communications Mining Process Categories: UiPath AI Communications Mining

NEW QUESTION # 115
What is the primary advantage of the One Click Extraction feature in UiPath's Document Understanding interface?

A. It allows training document extractors without manually creating Datasets, Pipelines, and ML Skills in AI Center.
B. It allows training document extractors without manually creating Datasets and Pipelines, but you need to manually deploy the ML Skills in AI Center.
C. It provides a simplified way to manually create Datasets, Pipelines, and Datasets for document extraction.
D. It automates the creation of document extractors by automatically creating Datasets, Pipelines, and ML Skills but requires manual creation of Pipelines.

Answer: A

Explanation:
Reference: UiPath One Click Extraction

NEW QUESTION # 116
For what type of documents is it recommended to use the Form Extractor?

A. For structured or semi-structured documents where the extraction method is based on a set of FlexiCapture definition files.
B. For use cases in which non-variable format documents need to be processed.
C. For structured or semi-structured documents in which layouts of different document providers vary greatly.
D. For structured or semi-structured documents where for certain fields, data is always found in a strict, predictable format and context.

Answer: B

Explanation:
The Form Extractor in UiPath is best suited for documents that have a fixed or non-variable format. This means that documents where the layout remains consistent and predictable, such as standardized forms or invoices, are ideal for this extraction method. The Form Extractor usespredefined templates that map data fields based on their positions, making it highly effective for extracting data from documents with little to no variation in layout. It is not well-suited for documents with significant layout variability, which would require a more flexible extraction approach, such as a machine learning extractor.
(Source: UiPath Document Understanding documentation)

NEW QUESTION # 117
What are the out-of-the-box model types available in AI Center?

A. Pre-trained, custom training, and reviewed.
B. Custom training, fine-tunable, and reviewed.
C. Pre-trained, custom training, and fine-tunable.
D. Pre-trained, fine-tunable, and reviewed.

Answer: C

Explanation:
According to the UiPath documentation, AI Center provides three types of out-of-the-box model types that can be used for different purposes and scenarios1:
Pre-trained: These are models that are already trained on a large and diverse dataset and can be used as-is for inference or prediction. They do not require any additional data or training from the user. Examples of pre- trained models are Language Detection, Sentiment Analysis, and Question Answering.
Custom training: These are models that allow the user to train them on their own data using the AI Center UI or API. They require the user to upload a dataset, configure the training parameters, and monitor the training progress and results. Examples of custom training models are Image Classification, Text Classification, and Named Entity Recognition.
Fine-tunable: These are models that are pre-trained on a general dataset but can be further trained or fine- tuned on a specific dataset provided by the user. They offer the best of both worlds: the benefit of using a pre- trained model and the flexibility of customizing it to the user's needs. Examples of fine-tunable models are Object Detection, Text Summarization, and Language Translation.
References:
1: Out-of-the-Box Packages

NEW QUESTION # 118
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