AI-900 Microsoft Azure AI Fundamentals Exam Questions and Answers – Page 6

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AI-900 Microsoft Azure Fundamentals Exam Questions and Answers
AI-900 Microsoft Azure AI Fundamentals Exam Questions and Answers

Exam Question 501

You plan to apply Text Analytics API features to a technical support ticketing system.
Match the Text Analytics API features to the appropriate natural language processing scenarios.
To answer, drag the appropriate feature from the column on the left to its scenario on the right. Each feature may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Select and Place:
API Features:

  • Entity recognition
  • Key phrase extraction
  • Language detection
  • Sentiment analysis

Answer Area:

  • Understand how upset a customer is based on the text contained in the support ticket.
  • Summarize important information from the support ticket.
  • Extract key dates from the support ticket.

Correct Answer:
Sentiment analysis: Understand how upset a customer is based on the text contained in the support ticket.
Key phrase extraction: Summarize important information from the support ticket.
Entity recognition: Extract key dates from the support ticket.
Answer Description:
API Feature 1: Sentiment analysis. Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.
API Feature 2: Broad entity extraction: Broad entity extraction: Identify important concepts in text, including key. Key phrase extraction/ Broad entity extraction: Identify important concepts in text, including key phrases and named entities such as people, places, and organizations.
API Feature 3: Entity Recognition: Named Entity Recognition: Identify and categorize entities in your text as people, places, organizations, date/time, quantities, percentages, currencies, and more. Well-known entities are also recognized and linked to more information on the web.

Exam Question 502

_____ is used to generate additional features.

A. Feature engineering
B. Feature selection
C. Model evaluation
D. Model training

Correct Answer:
A. Feature engineering

Exam Question 503

Returning a bounding box that indicates the location of a vehicle in an image is an example of _____.

A. image classification
B. object detection
C. optical character recognizer (OCR)
D. semantic segmentation

Correct Answer:
B. object detection

Exam Question 504

Match the types of AI workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all. NOTE: Each correct selection is worth one point.
Workload Types:

  • Anomaly detection
  • Computer vision
  • Machine Learning (Regression)
  • Natural language processing

Answer Area:

  • Identify handwritten letters.
  • Predict the sentiment of a social media post.
  • Identify a fraudulent credit card payment.
  • Predict next month’s toy sales.

Correct Answer:
Computer vision: Identify handwritten letters.
Natural language processing: Predict the sentiment of a social media post.
Anomaly detection: Identify a fraudulent credit card payment.
Machine Learning (Regression): Predict next month’s toy sales.