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UiPath UiPath-SAIAv1 Simulation Questions | Associate UiPath-SAIAv1 Level Exam
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UiPath Specialized AI Associate Exam (2023.10) Sample Questions (Q81-Q86):
NEW QUESTION # 81
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. 20-50 document samples from each class.
- C. 50-200 document samples from each class.
- D. 10-20 document samples from each class.
Answer: B
Explanation:
According to the UiPath documentation, the recommended number of samples for the classification fields depends on the number of document types and layouts that you want to classify. The more document types and layouts you have, the more samples you need to cover the diversity of your data. However, a general guideline is to have at least 20-50 document samples from each class, as this would provide enough data for the classifiers to learn from12. A large number of samples per layout is not mandatory, as the classifiers can generalize from other layouts as well3.
References: 1: Document Classification Training Overview 2: Document Classification Training Related Activities 3: Training High Performing Models
NEW QUESTION # 82
Can a custom-built extractor be used in the Data Extraction Scope activity?
- A. Yes, by using Coded Workflows.
- B. Yes, by referencing UiPath.Documentprocessing.Contracts in the custom-built implementation.
- C. Yes, by creating a new extractor that implements Form Extractor or Regex Based Extractor in the custom-built implementation.
- D. No, only out-of-the-box extractors can be used.
Answer: B
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
UiPath allows developers to buildcustom extractorsthat can be used within theData Extraction Scope activity by implementing a specific interface. This is done by referencing theUiPath.DocumentProcessing.
Contractsassembly in the custom extractor.
* This enables plugging custom ML models or logic into the Document Understanding workflow.
* Custom extractors must implement interfaces like IExtractor or IFormExtractor.
* UiPath Documentation Reference:Create a Custom Extractor - UiPath Docs
NEW QUESTION # 83
For what type of documents is it recommended to use the RegEx Based Extractor?
- A. For structured or semi-structured documents where for certain fields, data is always found in a strict, predictable format and context.
- B. For structured or semi-structured documents where the extraction method is based on a set of FlexiCapture definition files.
- C. For structured or semi-structured documents in which layouts of different document providers have little to no variation.
- D. For structured or semi-structured documents in which layouts of different document providers vary greatly.
Answer: A
Explanation:
The RegEx Based Extractor is most effective for documents where data fields follow a strict and predictable format, such as dates, invoice numbers, or specific patterns like email addresses. This method is well-suited for extracting information from structured or semi-structured documents with consistent formats across different documents, making it highly reliable for use cases where patterns are easily identifiable and do not vary significantly.
(Source: UiPath Document Understanding documentation)
NEW QUESTION # 84
What are the characteristics of the AI Center platform?
- A. Permits the creation of ML models, their improvement and their consumption within RPA workflows in Studio.
- B. Enables the creation of ML packages and allows their consumption within RPA workflows.
- C. Allows human intervention for validating the classification results or the extraction results from different documents.
- D. Allows the deployment, management and improvement of ML models and their consumption within RPA workflows in Studio.
Answer: D
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
AI Center is designed to:
Deploy, manage, and monitor ML models
Create ML Skills that are used directly in Studio workflows
Integrate with Document Understanding for intelligent data extraction
Manage training and retraining pipelines
It is not primarily used for labeling or human validation (that's handled in DU components like the Validation Station).
UiPath Documentation Reference:
AI Center Overview
NEW QUESTION # 85
What new capability has been introduced for processing unstructured documents in the 2023.10 release?
- A. Generative capabilities for classifying various document types.
- B. Only using pre-trained extraction models.
- C. Manual classification of document types.
- D. Real-time document translation.
Answer: A
Explanation:
In the 2023.10 release of UiPath, a significant new feature is the introduction of generative capabilities for classifying various document types. This update allows for more advanced handling of unstructured data by leveraging AI to automatically generate classifications, even for document types that the model hasn't encountered before. This feature enhances the flexibility and power of Document Understanding, enabling organizations to handle a wider variety of documents without needing extensive manual setup for each new type.
(Source: UiPath 2023.10 Release Notes)
NEW QUESTION # 86
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