UiPath-SAIAv1 Exam Dumps - UiPath Specialized AI Associate Exam (2023.10)

In UiPath Communications Mining, pinning a model ensures that the predictions shown in the Explore tab are generated from that specific model version. This feature allows users to control which version of the model is actively making predictions, particularly during evaluation or comparison stages. By pinning a model, the user ensures that the UI reflects the predictions from the selected version, helping maintain consistency when analyzing results or making changes.

For more details, refer to:

UiPath Communications Mining: Model Management and Pinning

UiPath AI Center Documentation: Managing Model Versions

The Present Classification Station activity is used for classification validation in attended mode. It allows the user to review and correct the classification results of documents using the Classification Station interface. The other options are not suitable for attended mode, as they are either used for creating Action Center tasks (A and C) or for training classifiers (B).

 According to the UiPath documentation, the Classify stage of the Document Understanding Framework is used to automatically determine what document types are found within a digitized file. The document types are defined in the project taxonomy, which is a collection of all the labels and fields applied to the documents in a dataset. The Classify stage uses one or more classifiers, which are algorithms that assign document types to files based on their content and structure. The classifiers can be configured and executed using the Classify Document Scope activity, which also allows for document type filtering, taxonomy mapping, and minimum confidence threshold settings. The Classify stage outputs the classification information in a unified manner, irrespective of the source of classification. The documents that are classified are then sent to the next stage of the framework, which is Data Extraction. The documents that are not classified or skipped are either excluded from further processing or sent to Action Center for human validation and correction.

In UiPath AI Center, versioning of ML packages is an integral part of managing the lifecycle of machine learning models. Each ML package has a major and minor version to track changes. When an ML package is initially uploaded, it is assigned a major version (e.g., 1.0). If a package is retrained via pipelines, it increments the minor version (e.g., from 1.0 to 1.1). This mechanism helps differentiate between user-uploaded packages and those that have been retrained. Only packages that undergo retraining through pipelines modify their minor version, not the major version. Thus, answer D is correct.

(Source: docs.uipath.com on ML Package Management).

Here is the correct order to configure the Extractor Wizard in UiPath Document Understanding:

Step 1: Add a Data Extraction Scope activity to the workflow.Step 2: Place one or more extractors.Step 3: Click on the Configure Extractors button.Step 4: Select the checkboxes next to each field for the extractor type that should be activated.Step 5: Get capabilities (if needed).Step 6: Click on the Save button.

This sequence ensures that the Extractor Wizard is correctly configured to work with the Document Understanding workflow.