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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions (Q186-Q191):

NEW QUESTION # 186
What is the purpose of the "Explore" phase in UiPath Communications Mining?

A. To provide each label/entity in a taxonomy with enough training examples so the model can make accurate predictions at scale.
B. To fully review and correctly tag the model version, regardless if it's "Live" or "Staging".
C. To use the bulk label functionality, a helpful tool to quickly train the model when searching for specific terms.
D. To review the clusters of similar communications from a data set that unsupervised learning automatically found.

Answer: A

Explanation:
The Explore phase is the second phase of model training in UiPath Communications Mining, which is a solution that enables the analysis of large volumes of text-based communications using natural language processing and machine learning. The Explore phase builds on the foundations of the taxonomy that was created in the Discover phase by reviewing clusters and searching for different terms and phrases. The objective of the Explore phase is to provide each of the labels or entities that are important for the use case with enough varied and consistent training examples, so that the platform has sufficient training data from which to make accurate predictions across the entire dataset. The Explore phase is the core phase of model training, and requires the most time and effort, but also leads to better model performance and accuracy1.
References: 1: Communications Mining - Explore

NEW QUESTION # 187
How do you load a taxonomy from a given non-default location text file into a variable?
Instructions: Drag the steps found on the "Left" and drop them on the "Right" in the correct order.

Answer:

Explanation:

Explanation:

to load a taxonomy from a given non-default location text file into a variable, the order of steps should be as follows:
* Create a new variable of type 'DocumentTaxonomy' called 'documentTaxonomy', then create a new string variable called 'taxonomyPath'.
* This step involves setting up the necessary variables that will be used in the process. The
'documentTaxonomy' variable will hold the deserialized taxonomy object, and 'taxonomyPath' will store the path to the taxonomy file.
* Using an Assign activity, assign the given non-default taxonomy text file path to the most recent variable created.
* Here you will assign the path of the taxonomy file to the 'taxonomyPath' variable.
* Use the Read Text File activity on the 'taxonomyPath' variable created. Next, create a new variable 'taxonomyText', then save the output of the Read Text File activity to 'taxonomyText'.
* This step is where you read the contents of the taxonomy file using the 'Read Text File' activity.
The contents are stored in the 'taxonomyText' variable.
* Inside the last Assign activity 'Value to Save' property add the following expression: "Newtonsoft.
Json.JsonConvert.DeserializeObject(Of DocumentTaxonomy)(taxonomyText)" where ' taxonomyText' is the text read from the file and 'documentTaxonomy' (the most recent variable created) is the variable you created.
* In this final step, you will deserialize the JSON content from the 'taxonomyText' into a
'DocumentTaxonomy' object using the 'JsonConvert.DeserializeObject' method and assign it to the 'documentTaxonomy' variable.
Following these steps in this order will load the taxonomy from a text file into the 'documentTaxonomy' variable in UiPath.

NEW QUESTION # 188
Under what condition can a dataset be edited in UiPath AI Center?

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

Answer: A

Explanation:
According to the UiPath documentation, a dataset is a folder of storage containing arbitrary sub-folders and files that allows machine learning models in your project to access new data points. You can edit a dataset's name, description, or content from the Datasets > [Dataset Name] page, by clicking Edit dataset. However, you can only edit a dataset if it is not currently being used in an active pipeline. A pipeline is a sequence of steps that defines how to train, test, and deploy a machine learning model. If a dataset is being used in an active pipeline, you will see a lock icon next to it, indicating that it cannot be edited. You can either wait for the pipeline to finish or stop it before editing the dataset.
References:
* AI Center - Managing Datasets
* AI Center - About Datasets
* AI Center - About Pipelines

NEW QUESTION # 189
What is the correct execution order of the Document Understanding template stages?
Instructions: Drag the stages found on the "Left" and drop them on the "Right" in the correct order.

Answer:

Explanation:

Explanation:
The correct execution order of the Document Understanding template stages is:
* Taxonomy
* Digitize
* Classify
* Extract
* Extraction Validation
* Export
Comprehensive and Detailed Explanation: The Document Understanding template stages are based on a document processing flowchart that follows these steps:
* First, you need to define the Taxonomy of the document types and fields that you want to process and extract information from. This is done using the Taxonomy Manager in UiPath Studio1.
* Next, you need to Digitize the input documents, which can be in various formats such as PDF, image, or text. This is done using the Digitize Document activity, which converts the documents into a machine-readable format and performs OCR if needed2.
* Then, you need to Classify the digitized documents into the predefined document types in your taxonomy. This is done using the Classify Document Scope activity, which can use various classifiers such as Keyword Based Classifier, Machine Learning Classifier, or Intelligent Form Extractor3.
* After that, you need to Extract the relevant information from the classified documents based on the fields in your taxonomy. This is done using the Data Extraction Scope activity, which can use various extractors such as Regex Based Extractor, Machine Learning Extractor, or Form Extractor.
* Next, you need to perform Extraction Validation to review and correct the extracted information, either manually or automatically. This is done using the Present Validation Station activity, which can use either the Validation Station or the Action Center for human-in-the-loop validation.
* Finally, you need to Export the validated information to the desired output location, such as a file, a database, or a queue. This is done using the Export Extraction Results activity, which can use various exporters such as Excel Exporter, CSV Exporter, or Queue Item Exporter.
References:
* UiPath Studio - Taxonomy Manager
* UiPath Activities - Digitize Document
* UiPath Activities - Classify Document Scope

NEW QUESTION # 190
What do entities represent in UiPath Communications Mining?

A. Structured data points.
B. Thread properties.
C. Concepts, themes, and intents.
D. Metadata properties.

Answer: A

NEW QUESTION # 191
......

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