UiPath-SAIv1 Exam Dumps - UiPath Certified Professional - General Track Certification Questions and Answers

An area of machine learning concerned with artificial neural networks. These are a series of algorithms that aim to recognize relationships in a set of data through a process that mimics biological neural networks.

The theory and development of computer systems that are able to perform tasks that normally require human intelligence and decision making.

A sub-field of artificial intelligence that enables systems to learn from data. Systems learn from previous experience and information to deduce and predict future information. To do this they use algorithms that learn to perform a specific task without being explicitly programmed.

A branch of artificial intelligence that deals with analyzing, understanding, and generating human natural languages. For example, NLP enables computers to hear speech, read text, interpret the text/speech or measure the sentiment.

For use cases in which non-variable format documents need to be processed.

For structured or semi-structured documents where the extraction method is based on a set of FlexiCapture definition files.

For structured or semi-structured documents where for certain fields, data is always found in a strict, predictable format and context.

For structured or semi-structured documents in which layouts of different document providers vary greatly.

Integer

Tuple

List

Array

Variables can only be used within the main workflow, while arguments can only be used within invoked workflows.

Variables are used for input data, while arguments are used for output data.

Variables have a limited scope within a specific workflow or sequence, while arguments are used to pass data between workflows.

Variables are global and arguments are local.

Analyzing customer complaints in a B2C organization.

Analyzing employee engagement survey responses.

Analyzing customer satisfaction survey responses.

Monitoring "Quality of Service" in an operations-focused shared mailbox in a B2B organization.

Project Manager

Solution Architect

Automation Developer

Business Analyst

Name, Classification type. Input to be labeled. Attribute name. Shortcut, and Color.

Name, Input to be labeled. Attribute name, and Shortcut.

Name, Classification type, Attribute name, and Shortcut.

Name, Classification Type. Attribute name. Color, and Shortcut.

The extraction confidence and the digitization confidence.

The number of occurrences and the extraction confidence.

The position on the page.

The page number from which the field was extracted and the exact position on the page.

The trained-from-scratch general fields depend on the model version, while the ones that are pre-trained do not.

The trained-from-scratch general fields have better accuracy, while the pre-trained general fields have a longer training time.

The trained-from-scratch general fields are entirely user-trained, while the ones that are pre-trained are typically based on a set of standard or custom-defined rule

The trained-from-scratch general fields need to be normalized to be used in downstream automation, while the ones that are pre-trained can only be used in dashboards within the platform.

ApplyOcrOnPdf -> Auto

ApplyOcrOnPdf -> Auto DegreeOfParallelism -> -1 DetectCheckboxes -> True

ApplyOcrOnPdf -> No DegreeOfParallelism -> True DetectCheckboxes -> True

ApplyOcrOnPdf -> Auto DegreeOfParallelism -> Max DetectCheckboxes -> True

ApplyOcrOnPdf -> No DegreeOfParallelism -> -1 DetectCheckboxes -> False