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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions (Q196-Q201):
NEW QUESTION # 196
What is the relationship between AI Center and UiPath Document Understanding?
- A. AI Center is the infrastructure on top of which UiPath Document Understanding digitization runs.
- B. Document Understanding is the infrastructure on which AI Center machine learning models run.
- C. AI Center is the infrastructure on top of which UiPath Document Understanding machine learning models run.
- D. Document Understanding is the infrastructure on which AI Center digitization runs.
Answer: C
NEW QUESTION # 197
What does the Label Trends table in UiPath Communications Mining show?
- A. How the top 10 labels for a given time period perform compared to the previous period and their change in rank.
- B. How the top 10 labels and entities for a given time period perform compared to the previous period and their change in rank.
- C. How the top 10 senders for a given time period perform compared to the previous period and their change in rank.
- D. How the top 10 entities for a given time period perform compared to the previous period and their change in rank.
Answer: A
Explanation:
The Label Trends table in UiPath Communications Mining shows the trend of the top 10 highest volume labels over the selected time period, as well as their percentage change and rank change compared to the previous period1. The table allows users to quickly identify which labels are increasing or decreasing in volume, and by how much, over time. The table also shows the net sentiment score for each label, which is calculated as the difference between the positive and negative sentiment probabilities for each verbatim2. The table can be filtered by data type, source, date range, and label category. Users can also sort the table by label name, volume, percentage change, rank change, or net sentiment1.
References: 1: Trends 2: Sentiment Analysis
NEW QUESTION # 198
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. 10-20 document samples from each class.
- C. 20-50 document samples from each class.
- D. 50-200 document samples from each class.
Answer: C
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 # 199
What is the benefit of making an ML Skill public?
- A. It allows access from outside of the UiPath environment.
- B. It provides additional security measures for the ML Skill.
- C. It allows access from inside of the UiPath environment.
- D. It enables automatic updates and enhancements to the ML Skill without user intervention.
Answer: A
Explanation:
Making an ML Skill public in UiPath enables it to be accessed externally from the UiPath ecosystem. This can be beneficial if the ML Skill needs to be utilized in external applications, systems, or services beyond UiPath's automation environment. Public access expands the usability of the skill, allowing integration with other systems while maintaining security through managed endpoints.
NEW QUESTION # 200
What is the role of the Taxonomy Manager?
- A. To create and edit a Taxonomy file specific to the current automation project.
- B. To select the type of ML that can be used in the project.
- C. To select which extractors are trained for each document type and field.
- D. To present a document processing specific user interface for validating and correcting automatic classification outputs.
Answer: A
Explanation:
The Taxonomy Manager is a tool that enables you to create and edit a Taxonomy file, which is an XML file that defines the document types and fields that are relevant for your automation project1. The Taxonomy file is used by the Classify Document Scope and Data Extraction Scope activities to perform document classification and data extraction, respectively2. The Taxonomy Manager allows you to add, remove, rename, or reorder document types and fields, as well as specify the data type, format, and validation rules for each field3. The Taxonomy Manager also provides a preview of the Taxonomy file and a validation feature to check for errors or inconsistencies.
References:
1: About Taxonomy Manager 2: About Document Understanding Framework 3: Using the Taxonomy Manager : Taxonomy Manager User Interface Description
NEW QUESTION # 201
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