UIPATH-SAIAV1 ACCURATE ANSWERS, RELIABLE UIPATH-SAIAV1 EXAM QUESTIONS

UiPath-SAIAv1 Accurate Answers, Reliable UiPath-SAIAv1 Exam Questions

UiPath-SAIAv1 Accurate Answers, Reliable UiPath-SAIAv1 Exam Questions

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UiPath Specialized AI Associate Exam (2023.10) Sample Questions (Q184-Q189):

NEW QUESTION # 184
What is the main difference between an array and a list in UiPath?

  • A. An array is a fixed-size collection of elements of the same type while a list is a dynamic-sized collection of elements of different types.
  • B. An array is a fixed-size collection of elements of different types while a list is a dynamic-sized collection of elements of the same type.
  • C. An array is a dynamic-sized collection of elements of the same type while a list is a fixed-sizecollection of elements of the same type.
  • D. An array is a fixed-size collection of elements of the same type while a list is a dynamic-sized collection of elements of the same type.

Answer: D

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
* Arraysin UiPath (VB.NET) arefixed-sizeand must be initialized with a defined number of elements of thesame type.
* Lists(List<T>) aredynamicand allow you to add/remove elements at runtime, but still enforcetype safety(same type elements).
* UiPath Documentation Reference:Collections in UiPath Academy # RPA Developer Foundation # Data Manipulation


NEW QUESTION # 185
Which is a high-level view of the tabs within an AI Center project?

  • A. Dashboard. Datasets. ML Packages. ML Training. ML Evaluation, and ML Logs.
  • B. Datasets. Data Labeling. ML Packages. Pipelines, and ML Skills.
  • C. Dashboard. Datasets, Data Labeling. ML Packages. Pipelines, ML Skills, and ML Logs.
  • D. Datasets, Data Labeling. ML Packages, ML Training, ML Evaluation, ML Skills, and ML Logs.

Answer: C

Explanation:
A high-level view of the tabs within an AI Center project is as follows:
Dashboard: This tab provides an overview of the project's status, such as the number of datasets, pipelines, packages, skills, and logs, as well as the AI Units consumption and quota.
Datasets: This tab enables you to upload, view, and manage the datasets that are used for training and evaluating the ML models within the project. A dataset is a folder of storage containing arbitrary files and sub- folders1.
Data Labeling: This tab enables you to upload raw data, annotate text data in the labeling tool (for classification or entity recognition), and use the labeled data to train ML models. It is also used by the human reviewer to re-label incorrect predictions as part of the feedback process2.
ML Packages: This tab enables you to upload, view, and manage the ML packages and package versions within the project. An ML package is a group of package versions of the same package type, and a package version is a trained model that can be deployed to a skill3.
Pipelines: This tab enables you to create, view, and manage the pipelines and pipeline runs within the project. A pipeline is a description of an ML workflow, including the functions and their order of execution, and a pipeline run is an execution of a pipeline based on code provided by the user4.
ML Skills: This tab enables you to deploy, view, and manage the ML skills within the project. An ML skill is a live deployment of a package version, which can be consumed by an RPA workflow using an ML skill activity in UiPath Studio5.
ML Logs: This tab enables you to view and filter the logs related to the project, such as the events, messages, and errors that occurred during the pipeline runs, skill deployments, and skill executions6.
References:
1: About Datasets 2: About Data Labeling 3: About ML Packages 4: About Pipelines 5: About ML Skills 6: About ML Logs


NEW QUESTION # 186
What are all the types of ML (Machine Learning) models supported by Al Center?

  • A. Out-of-the-box models from UiPath technology partners and custom models.
  • B. Out-of-the-box models from UiPath and UiPath technology partners.
  • C. Out-of-the-box models from UiPath, UiPath technology partners, open-source models from the community, and custom models.
  • D. Out-of-the-box models from UiPath technology partners, and open-source models from the community.

Answer: C

Explanation:
In UiPath AI Center, the platform supports several types of machine learning (ML) models, including:
Out-of-the-box models from UiPath: Pre-built models designed for common automation tasks.
Models from UiPath technology partners: External models developed by UiPath's partners.
Open-source models: Community-contributed models that can be used and adapted for various use cases.
Custom models: Models that users build and train specifically for their projects using their datasets.
This flexibility in model support ensures that organizations can leverage a wide range of machine learning capabilities to suit different automation needs.
For more details, refer to:
UiPath AI Center Documentation: AI Center Models
Machine Learning Model Types: Types of Models in UiPath AI Center


NEW QUESTION # 187
Which of the following OCR (Optical Character Recognition) engines is not free of charge?

  • A. Tesseract.
  • B. Microsoft OCR.
  • C. Microsoft Azure OCR.
  • D. OmniPaqe.

Answer: D

Explanation:
According to the UiPath documentation, OmniPaqe is a paid OCR engine that requires a license to use. It is one of the most accurate and reliable OCR engines available, and it supports over 200languages. The other OCR engines listed are free of charge, but they may have different features, limitations, and performance levels. For example, Tesseract is an open-source OCR engine that supports over 100 languages, but it may not be as accurate as OmniPaqe. Microsoft Azure OCR and Microsoft OCR are both cloud-based OCR engines that use Microsoft's technology, but they have different capabilities and pricing models. Microsoft Azure OCR can process both printed and handwritten text, and it uses a pay-as-you-go model based on the number of transactions. Microsoft OCR can only process printed text, and it is included in the UiPath Studio license.
References:
Document Understanding - OCR Engines
Automation Pricing - Complete UiPath Enterprise Solution


NEW QUESTION # 188
In which of the following scenarios, the ML Classifier is the only recommended classifier to be used, according to best practice?

  • A. When the custom document types are not similar and file splitting is not necessary.
  • B. When the custom document types are very similar and file splitting is not necessary.
  • C. When the custom document types are very similar and file splitting is necessary.
  • D. When the custom document types are not similar and file splitting is necessary.

Answer: B

Explanation:
The ML Classifier is a document classifier that uses a machine learning model deployed as an ML Skill in AI Center to perform document classification tasks. The ML Classifier can work by default with Invoices, Purchase Orders, Receipts, and Utility Bills, or with custom document types that are trained using the Data Manager and the Machine Learning Classifier Trainer12.
According to the best practice, the ML Classifier is the only recommended classifier to be used when the custom document types are very similar and file splitting is not necessary. This is because the ML Classifier can handle complex and ambiguous cases where the document types are hard to distinguish by rules or keywords, and can also learn from feedback and improve over time. File splitting is not necessary when the documents are single-page or have a consistent number of pages per document type3.
The other options are not correct because they are scenarios where other classifiers, such as the Keyword Based Classifier or the Intelligent Keyword Classifier, can be used in combination with the ML Classifier or instead of it. These classifiers are based on rules or keywords that can identify the document types based on their content or metadata, and can also perform file splitting if the documents are multi-page or have a variable number of pages per document type3.
References: 1: Machine Learning Classifier - UiPath Activities 2: Machine Learning Classifier Trainer - UiPath Document Understanding 3: Document Classification - UiPath Document Understanding


NEW QUESTION # 189
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