RELIABLE UIPATH UIPATH-SAIV1 TEST TOPICS, FREE UIPATH-SAIV1 LEARNING CRAM

Reliable UiPath UiPath-SAIv1 Test Topics, Free UiPath-SAIv1 Learning Cram

Reliable UiPath UiPath-SAIv1 Test Topics, Free UiPath-SAIv1 Learning Cram

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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions (Q180-Q185):

NEW QUESTION # 180
How does UiPath Document Understanding handle structured documents with fixed formats?

  • A. It requires manual data entry, as structured documents cannot be processed automatically.
  • B. It relies on AI models for natural language processing.
  • C. It leverages predefined templates for accurate data extraction.
  • D. It uses optical character recognition (OCR) to extract text from the documents.

Answer: C


NEW QUESTION # 181
Which activity can be used to convert the default taxonomy.json file into a variable for further use?

  • A. UiPath.IntelligentOCR.Activities.TaxonomyManagement.LoadTaxonomyFile
  • B. UiPath.IntelligentOCR.Activities.TaxonomyManagement.LoadTaxonomy
  • C. UiPath.IntelligentOCR.Activities.TaxonomyManagement.LoadFileTaxonomy
  • D. UiPath.IntelligentOCR.Activities.TaxonomyManagement.LoadFile

Answer: A


NEW QUESTION # 182
Why is the Shuffle training mode important in the "Explore" phase while working with UiPath Communications Mining?

  • A. Because it creates a high precision model, focusing on labels with low precision and a low number of examples.
  • B. Because it helps create a balanced model by focusing on outlier labels with sufficient training examples but low confidence.
  • C. Because it helps create a balanced model free from labelling bias by introducing random variation into the training data.
  • D. Because it creates a new model version with shuffled labels and general fields and lets the user explore to understand the state of the model

Answer: C

Explanation:
The Shuffle training mode in the "Explore" phase of UiPath Communications Mining helps to introduce randomness into the training data. This prevents labeling bias by ensuring that the model does not overly focus on certain labels or examples, leading to a more balanced and generalized model. By shuffling the data, the model is exposed to a diverse range of examples, which enhances its ability to make accurate predictions across different labels and datasets.
(Source: UiPath Communications Mining documentation)


NEW QUESTION # 183
Which of the following functionalities does UiPath Assistant provide?

  • A. Analyzing processes to determine optimal automation solutions.
  • B. Developing automation workflows in UiPath Studio.
  • C. Running, managing, and organizing automation workflows on the user's machine.
  • D. Scheduling and monitoring robot processes in Orchestrator.

Answer: C


NEW QUESTION # 184
What is supervised learning?

  • A. Supervised learning is a machine learning paradigm in which algorithms try to solve a problem only by trial and error and using a system of rewards and punishments.
    There is no need for labeled input/output pairs to be presented. Instead, the focus is on finding a balance between exploration (of uncharted territory) and exploitation (of current knowledge).
  • B. Supervised learning is a machine learning paradigm with the goal of learning a function that maps input variables with output variables.
    In every case there is a correct answer, so the aim is to train the model until it reaches an acceptable level of performance in predicting the outcome, at which point the learning stops.
  • C. Supervised learning is a machine learning paradigm in which algorithms try to solve a problem in an uncertain, potentially complex environment only by trial and error and using a system of rewards and punishments.
    There are no correct answers, but feedback is given in the form of rewards and penalties.
  • D. Supervised learning is a machine learning paradigm that refers to algorithms that learn patterns from unlabeled data.There are only input variables, but no corresponding output variables. The goal of the algorithm is to model the underlying structure of the data, but there are no correct answers and no teachers.

Answer: B

Explanation:
Supervised learning is one of the most popular and widely used machine learning approaches. It involves providing the algorithm with labeled input/output pairs, which serve as examples of the desired behavior or outcome. The algorithm then learns a function that can generalize from these examples and make predictions for new, unseen data. Supervised learning can be used for tasks such as classification, regression, and anomaly detection. Some common supervised learning algorithms are linear regression, logistic regression, decision trees, support vector machines, and neural networks.
References:
* UiPath AI Fabric - Machine Learning Concepts
* UiPath Document Understanding - Machine Learning Models
* UiPath Communications Mining - Overview


NEW QUESTION # 185
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