HOT NEW UIPATH-SAIAV1 DUMPS BOOK PASS CERTIFY | RELIABLE UIPATH-SAIAV1 LATEST TEST ANSWERS: UIPATH SPECIALIZED AI ASSOCIATE EXAM (2023.10)

Hot New UiPath-SAIAv1 Dumps Book Pass Certify | Reliable UiPath-SAIAv1 Latest Test Answers: UiPath Specialized AI Associate Exam (2023.10)

Hot New UiPath-SAIAv1 Dumps Book Pass Certify | Reliable UiPath-SAIAv1 Latest Test Answers: UiPath Specialized AI Associate Exam (2023.10)

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UiPath Specialized AI Associate Exam (2023.10) Sample Questions (Q66-Q71):

NEW QUESTION # 66
What information does the comparison between two cohorts display on the Comparison page in UiPath Communications Mining?

  • A. Verbatim content for each label.
  • B. Entity count for each metadata.
  • C. Differences in verbatim length between Group A and Group B.
  • D. Total verbatim count and proportion for each label.

Answer: D

Explanation:
According to the UiPath documentation, UiPath Communications Mining is a tool that enables you to analyze text-based communications data, such as customer feedback, support tickets, or chat transcripts, using natural language processing (NLP) and machine learning (ML) techniques1. One of the features of UiPath Communications Mining is the Comparison page, which allows you to compare two cohorts of verbatims based on different criteria, such as date range, source, metadata, or label2. The Comparison page displays the following information for each cohort3:
Total verbatim count: The number of verbatims in the cohort.
Proportion for each label: The percentage of verbatims in the cohort that are assigned to each label. A label is a category or a topic that is relevant for the analysis, such as sentiment, intent, or issue type. Labels can be predefined or custom-defined by the user.
Statistical significance: The p-value that indicates whether the difference in proportions between the two cohorts is statistically significant or not. A p-value less than 0.05 means that the difference is unlikely to be due to chance.
The Comparison page also provides a visual representation of the proportions for each label using a bar chart, and allows the user to drill down into the verbatim content for each label by clicking on the bars3. Therefore, the correct answer is A.
References:
1: About Communications Mining 2: Communications Mining - Comparing Cohorts 3: Communications Mining - Comparison Page


NEW QUESTION # 67
Which of the following statements is correct in the context of migrating a schema from Document Manager to a Modern Project?

  • A. If you import a schema into a document type that already contains a schema, the import will fail.
  • B. If you import a schema into a document type that already contains a schema, the import will be successful and the schema will be updated with the missing field.
  • C. If you import a schema into a document type that already contains a schema, the import will be successful and the schema will be overridden.
  • D. If you import a schema into a document type that already contains a schema, the import will fail only if documents were already uploaded.

Answer: C

Explanation:
When migrating a schema from Document Manager to a Modern Project, UiPath will override any existing schema associated with the document type if you attempt to import a new schema. This behavior is confirmed in UiPath's handling of document types and schema imports, where the new schema will replace the old one, ensuring that the latest version is applied to the project. This helps maintain consistency in schema configurations during migrations, especially when schemas are updated or need to be standardized


NEW QUESTION # 68
For which version(s) from Out-of-the-Box ML Packages minor versions is the download functionality available?

  • A. Version 0 and above
  • B. Version 1 and above
  • C. Version 0 only
  • D. Version 1 only

Answer: B

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
UiPath AI Center allowsdownloading only Out-of-the-Box ML packages from version 1 and above.
* Version 0 is consideredexperimental or in preview, and the download functionality isnot availablefor those.
* This is important when users want to clone or retrain these models.
* UiPath Documentation Reference:Managing ML Packages - AI Center


NEW QUESTION # 69
What happens when multiple users try to label the same document concurrently?

  • A. The changes made by all users are saved successfully.
  • B. Concurrent labeling is not allowed.
  • C. The changes made by one user override the changes made by others.
  • D. A warning message is displayed to the other user(s) indicating unsuccessful changes.

Answer: B

Explanation:
According to the UiPath documentation, data labeling is a process that involves uploading raw data, annotating text data in the labeling tool, and using the labeled data to train ML models1. Data labeling is performed by human labelers, who can be either internal or external to the organization2. However, concurrent labeling is not supported by the UiPath Data Labeling tool, which means that only one user can label a document at a time3. If multiple users try to label the same document concurrently, they will encounter an error message that says "The document is locked by another user. Please try again later.". Therefore, the correct answer is C.
References:
1: About Data Labeling 2: Data Labeling Roles 3: Data Labeling Limitations : Data Labeling Error Messages


NEW QUESTION # 70
What is the main purpose of the Document Understanding Process template in UiPath Studio?

  • A. To create custom workflows from scratch.
  • B. To integrate with other connected automations seamlessly.
  • C. To eliminate the need for exception handling in workflows.
  • D. To offer a fully functional document processing tool that is easy to use and execute.

Answer: D

Explanation:
The main purpose of the Document Understanding Process template in UiPath Studio is to provide users with a ready-to-use document processing framework. It is designed to simplify the development of document understanding automations by offering out-of-the-box features like logging, exception handling, and retry mechanisms. This template allows developers to quickly start working on both simple demos and large-scale document processing projects without needing to build everything from scratch. It is equipped with key components such as classifiers and extractors to streamline document classification and data extraction workflows


NEW QUESTION # 71
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