Pass the UiPath UiPath Certified Professional - Developer Track UiPath-SAIv1 Questions and answers with CertsForce

 Adding missed labels helps improve the label precision and recall in UiPath Communications Mining. Precision is the percentage of correctly labeled verbatims out of all the verbatims that have the label applied, while recall is the percentage of correctly labeled verbatims out of all the verbatims that should have the label applied. By adding missed labels, you are increasing the recall of the label, as you are reducing the number of false negatives (verbatims that should have the label but do not). This also improves the precision of the label, as you are reducing the noise in the data and making the label more informative and consistent. Adding missed labels is one of the recommended actions that the platform suggests to improve the model rating and performance of the labels.

References: Communications Mining - Training using ‘Check label’ and ‘Missed label’, Communications Mining - Model Rating

In the UiPath 2023.10 release, a key improvement introduced was the ability to record and store failed queue transactions for debugging purposes. This feature helps users by capturing the failure details and making them accessible directly in Orchestrator. The recording of failed transactions is enabled at the process level, within the Video section of the Job recording settings. It is intended to facilitate easier troubleshooting of failed automations by providing insights into the moments leading to the failure, which can be reviewed later for debugging

The Images folder in the exported dataset from UiPath's Document Manager contains each page of the documents in the dataset saved as images. This ensures that the visual layout of the documents is preserved, which is especially important when working with scanned documents or files that need to retain their original format for processing or validation purposes​

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

In UiPath Document Understanding Cloud APIs, the Generative Classifier is used to classify documents by leveraging a generative AI model. To classify a document as either an "Invoice" or a "Receipt," a POST request must be sent to the /api/framework/projects/{projectId}/classifiers/generative_classifier/classification endpoint. The body of this request should contain prompts specifying the classification types (in this case, "Invoice" and "Receipt") along with their corresponding descriptions. This allows the model to correctly classify incoming documents based on these predefined prompts.

For further reading, refer to:

UiPath Document Understanding API Documentation: Cloud API for Classification

Generative Classifier APIs: UiPath Classification APIs

Tone analysis is better suited for monitoring situations like "Quality of Service" in shared mailboxes, where the focus is on evaluating emotional tone in communications that may not always have clear-cut positive or negative sentiments. This contrasts with label sentiment analysis, which is better for datasets with explicit feedback (e.g., customer satisfaction surveys). In operations-focused environments, tone analysis provides more nuanced insights into service quality​

When migrating a schema from Document Manager to a Modern Project, UiPath will override any existing schema associated with the document type if you attempt to import a new schema. This behavior is confirmed in UiPath's handling of document types and schema imports, where the new schema will replace the old one, ensuring that the latest version is applied to the project. This helps maintain consistency in schema configurations during migrations, especially when schemas are updated or need to be standardized

According to the UiPath documentation portal1, the Automation Suite installer is a single package that enables the deployment of the full UiPath Automation Platform in the environment of choice, whether on-premises or in the cloud. The Automation Suite installer contains all the components and dependencies required for the installation, such as the infrastructure, the orchestrator, the AI Center, the Action Center, the Insights, the Test Suite, and the Document Understanding. The Automation Suite installer also supports multi-node deployment with automatic scaling and built-in high availability, as well as easy monitoring, configuration, and upgrade options1. Therefore, option C is the correct answer, as it describes the features and benefits of the Automation Suite installer. Option A is incorrect, as it refers to the UiPath Automation Cloud, which is a different offering that does not require an installer. Option B is incorrect, as it describes a manual installation process that is not enabled by the Automation Suite installer. Option D is incorrect, as it confuses the Automation Suite installer with the installUiPathAS.sh script, which is a separate file that is used to launch the installer wizard2.

References: 1 Automation Suite - Overview 2 Automation Suite - Downloading the installation packages