1.4 AI/Machine Learning 400-007 Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   Which workload characteristic is most suitable for auto-scaling in an AI/ML environment?

   • AVariable inference demand that peaks during business hours
   • BA small model that runs on a single GPU
   • CA steady, predictable training job that runs for weeks
   • DA batch job that runs once a month
   Reveal Solution Discussion Select an answer first
2. 2foundation · easy

   Which AI/ML phase typically generates the most intensive network traffic?

   • AModel deployment
   • BModel evaluation
   • CData ingestion
   • DModel inference
   Reveal Solution Discussion Select an answer first
4. 3foundation · easy

   What is the primary purpose of assurance mechanisms such as monitoring and logging in AI/ML operations?

   • ATo automate the retraining of models without human intervention
   • BTo reduce the computational cost of training models
   • CTo eliminate the need for data validation
   • DTo ensure the AI/ML system operates reliably and produces trustworthy outcomes
   Reveal Solution Discussion Select an answer first
5. 4foundation · easy

   What does ROI measure in the context of an AI/ML deployment?

   • AThe financial return generated relative to the cost of the AI/ML investment
   • BThe speed at which the model can make predictions
   • CThe accuracy of the machine learning model
   • DThe amount of data processed by the system
   Reveal Solution Discussion Select an answer first
6. 5foundation · easy

   What is a common storage requirement for AI/ML training workloads?

   • ALow-latency storage optimized for small random reads
   • BStorage with built-in data deduplication to save space
   • CHigh-throughput storage capable of handling large datasets
   • DStorage that supports only a single writer to ensure consistency
   Reveal Solution Discussion Select an answer first