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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions:

1. What is the purpose of the "Explore" phase in UiPath Communications Mining?

A) To review the clusters of similar communications from a data set that unsupervised learning automatically found.
B) To fully review and correctly tag the model version, regardless if it's "Live" or "Staging".
C) To use the bulk label functionality, a helpful tool to quickly train the model when searching for specific terms.
D) To provide each label/entity in a taxonomy with enough training examples so the model can make accurate predictions at scale.

2. Which of the following extractors can be used for Data Extraction Scope activity?

A) Intelligent Form Extractor, Machine Learning Extractor. Logic Extractor, and Regex Based Extractor.
B) Regex Based Extractor. Form Extractor. Intelligent Form Extractor, and Machine Learning Extractor.
C) Full Extractor. Machine Learning Extractor, Intelligent Form Extractor, and Regex Based Extractor.
D) Form Extractor Incremental Extractor Machine Learning Extractor and Intelligent Form Extractor

3. For what type of documents is it recommended to use the RegEx Based Extractor?

A) For structured or semi-structured documents where the extraction method is based on a set of FlexiCapture definition files.
B) For structured or semi-structured documents in which layouts of different document providers vary greatly.
C) For structured or semi-structured documents in which layouts of different document providers have little to no variation.
D) For structured or semi-structured documents where for certain fields, data is always found in a strict, predictable format and context.

4. Which is the correct description of the Configure Extractors Wizard?

A) A mandatory step in the extractor configuration that allows choosing which extractors are applied to each document type and field.
B) A mandatory step in the extractor configuration that allows choosing which extractors are applied to each document type.
C) A mandatory step in the extractor configuration that allows choosing which extractors are applied to each field.
D) An optional step in the extractor configuration which allows choosing which extractors are applied to each document type.

5. What is supervised learning?

A) 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.
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 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.
D) 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).

Solutions: