100% PASS 2025 UIPATH ACCURATE UIPATH-SAIV1 RELIABLE TEST VOUCHER

100% Pass 2025 UiPath Accurate UiPath-SAIv1 Reliable Test Voucher

100% Pass 2025 UiPath Accurate UiPath-SAIv1 Reliable Test Voucher

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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions (Q53-Q58):

NEW QUESTION # 53
How long does the typical Machine Learning model deployment process take in UiPath AI Center?

  • A. Between 10 and 15 minutes.
  • B. Between 5 and 10 minutes.
  • C. Less than 5 minutes.
  • D. More than 15 minutes.

Answer: A

Explanation:
The typical machine learning model deployment process in UiPath AI Center usually takes between 10-15 minutes1. This process involves wrapping the model in UiPath's serving framework and deploying it within a namespace on AI Fabric's Kubernetes cluster that is only accessible by your tenant1. Please note that the actual time may vary depending on the complexity of the model and other factors.
AI Center - Managing ML Skills (uipath.com)


NEW QUESTION # 54
What are the out-of-the-box packages types available in Al Center?

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

Answer: B

Explanation:
UiPath AI Center offers three primary package types: pre-trained, custom training, and fine-tunable models.
These are essential for various use cases, from leveraging existing models to training custom ones based on specific data


NEW QUESTION # 55
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 # 56
What actions can be performed on a pipeline which is in the running state?

  • A. Kill.
  • B. Remove and restart.
  • C. Kill, remove, and restart.
  • D. Remove and kill.

Answer: A

Explanation:
When a pipeline is in the running state in UiPath AI Center, the only action that can be performed is to Kill it.
This terminates the process immediately, stopping any further processing. Actions like removing or restarting the pipeline can only be performed after the pipeline has stopped.(Source: UiPath Pipeline documentation


NEW QUESTION # 57
What is the Machine Learning Extractor?

  • A. A specialized model that can recognize multiple languages in the same document using API calls to a Hugging Face model with over 250 languages.
  • B. An extraction model that can be enabled and trained in Al Center. For better accuracy. 25 documents per model are recommended to train the model.
  • C. A tool using machine learning models to identify and report on data targeted for data extraction.
  • D. A tool that helps extract data from different document structures, and is particularly useful when the same document has multiple formats.

Answer: D


NEW QUESTION # 58
......

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