Exam Details

  • Exam Code
    :A00-405
  • Exam Name
    :SAS Viya 3.5 Natural Language Processing and Computer Vision
  • Certification
    :SAS Institute Certifications
  • Vendor
    :SAS Institute
  • Total Questions
    :60 Q&As
  • Last Updated
    :Mar 29, 2025

SAS Institute SAS Institute Certifications A00-405 Questions & Answers

  • Question 21:

    Refer to the Exhibit tabs.

    The Aviation Safely Reporting System document collection contains safety reports related to aviation A term map is created fortIhe term "incursion" The term "taxiway" is directly connected to the term "incursion" Which statement is consistent with the exhibit?

    A. The document collection contains 1,888 documents, and the terms "taxiway" and "incursion" appear together in 80 documents

    B. The document collection contains 1,888 documents, and the term "taxiway" appears in 80 documents

    C. The term "incursion" appears in 1,888 documents and the term "taxrway" appears in 80 of those 1.888 documents

    D. The term "taxiway" appears in 1 888 documents, and the term "incursion" appears in 80 of those 1.888 documents

  • Question 22:

    How many channels does a BGR image contain?

    Enter your numeric answer in the space above

    A. 3

  • Question 23:

    Which is the correct syntax for using a previously defined LITI concept rule, `'Date_of_Diagnosis'' in a category rule?

    A. (_tmac, " [Date_Of_Diagnosis} ")

    B. (AND, "{Date_Of_Diagnosis)"} ")

    C. (AND, "[Data_Off_Diagnosis]'} ")

    D. (_tmac, "{Date_Of_Diagnosis} ")

  • Question 24:

    Refer to the exhibit.

    What is the false negative rate for the category that has the 2nd worst average measure1?

    A. Between 1 and 2 B. Less than 1

    C. Between 2 and 3

    D. Greater than 5

  • Question 25:

    Which statement describes a situation in which a bi-directional recurrent neural network is a better option than a unidirectional network?

    A. The data at any given point in time depends on both the previous and subsequent elements of the sequence

    B. The data at any given point in time depends only on the previous elements of the sequence

    C. The data at any given point in time is independent of both the previous and subsequent elements of the sequence

    D. The data at any given point in time depends only on the subsequent elements of the sequence

  • Question 26:

    Which statements are TRUE about importing SAS Contextual Analysis projects into SAS Visual Text Analytics when creating a new project? (Choose two)

    A. All custom concept and some predefined concept settings are imported

    B. All machine generated topics and sentiment scores are imported

    C. All custom categories are imported

    D. All sentiment classification and probability scores are imported

  • Question 27:

    The following text siring "Wonder, Wondering, Wonderful, Wonderment, Wonders" is tested using the Category Rule

    (OR, "wonder0">

    Which terms are highlighted in the text string?

    A. Wonders

    B. Wonder Wondering, Wonders

    C. Wonder Wonders

    D. Wonder Wondering

    E. Wonderful, Wonderment, Wonders

  • Question 28:

    Assume you are using an addLayer call with dcopout=o. 5 to add a pooling layer into a CNN model What is the outcome of the addLayer call?

    A. The values from halt of the output neurons of the pooling layer ate randomly set to zero

    B. The output feature map size is increased 2 times on width and height.

    C. The values from half of the input neurons to the pooling layer are randomly set to zero

    D. The output feature map size is reduced by half on width and height

  • Question 29:

    Refer to the exhibit.

    Which statement is TRUE?

    A. Five documents contain 'basketball' or 'baseball'

    B. Three documents contain both 'basketball' and "baseball'

    C. The word 'baseball' occurs three times in five document

    D. Five documents contain 'baseball'

  • Question 30:

    What computation is performed when applying a neural network with Batch Normalization to test data?

    A. μ and o^2 are estimated using an exponentially weighted average across tram and test sets

    B. Normalizations are applied using parameters learned during testing

    C. Normalizations are applied using parameters learned during training

    D. μ and o^2 are estimated using an exponentially weighted average across test set

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