Microsoft Azure

Microsoft Azure AI Fundamentals

AI-900
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The AI-900 exam tests your foundational knowledge of AI concepts and Azure AI services.

147 questions 0 views Free
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Questions 141–147 of 147

Q141

You are configuring a recommendation system. What type of model should you prioritize?

  • A Collaborative filtering
  • B Linear regression
  • C Support vector machines
  • D Ensemble learning
Explanation Collaborative filtering is ideal for recommendations.
Q142

Which Azure service is primarily used for building conversational agents?

  • A Azure Bot Services
  • B Azure DevOps
  • C Azure Functions
  • D Azure Cognitive Analytics
Explanation Azure Bot Services is designed for creating conversational agents, while the others serve different functions.
Q143

A company wants to improve its model's accuracy through historical data analysis. Which Azure service should they use?

  • A Azure Machine Learning
  • B Azure Monitor
  • C Azure Data Lake
  • D Azure Logic Apps
Explanation Azure Machine Learning facilitates model training and evaluation, while the others do not focus on ML accuracy.
Q144

What happens when you apply a lower threshold to an anomaly detection model?

  • A Fewer anomalies are detected
  • B More anomalies are detected
  • C No change in detection
  • D Model performance decreases
Explanation Lowering the threshold increases sensitivity, leading to more detected anomalies, while other options incorrectly assume the opposite or no effect.
Q145

Which Azure service is primarily used for implementing conversational AI?

  • A Azure Bot Service
  • B Azure Functions
  • C Azure Logic Apps
  • D Azure DevOps
Explanation Azure Bot Service is designed for conversational AI, while others serve different purposes.
Q146

A company needs to process large amounts of real-time data from IoT devices. Which Azure service should they use?

  • A Azure Event Hubs
  • B Azure Data Lake
  • C Azure Blob Storage
  • D Azure SQL Database
Explanation Azure Event Hubs is designed for real-time streaming data, while other options focus on storage or batch processing.
Q147

You are configuring a machine learning model in Azure. What happens if you choose the 'Auto ML' option?

  • A Model parameters require manual tuning
  • B Automated feature engineering occurs
  • C It only supports regression tasks
  • D Training is limited to small datasets
Explanation 'Auto ML' includes automated feature engineering to optimize model performance, while A, C, and D are incorrect constraints.