Q1easy
Why is containerization (Docker) important for Model Deployment?
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9 Questions TotalUnder 10 MCQs (Noindex)
Model Deployment & MLOps Basics MCQs
Topic-wise practice questions for Artificial Intelligence & Machine Learning. Test your knowledge, check solutions on demand, and pace your preparation.
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Practice in Timed ModeQ2easy
What is an "Artifact" in the context of an ML pipeline?
Q3easy
Which activity is typically performed during the MLOps pipeline?
Q4easy
What is the difference between Batch Inference and Real-time (Online) Inference?
Q5medium
An MLOps engineer is worried that a model's prediction accuracy is dropping in production. Which process should they implement?
Q6easy
What is the main benefit of Version Controlling a Machine Learning Model (e.g., using MLflow or DVC)?
Q7easy
Why is MLOps necessary in professional AI projects?
Q8medium
A production model was trained on data from 2020. In 2026, the predictions become significantly less accurate because customer behavior has changed. What is this called?
Q9easy
What does "Inference" mean in an MLOps pipeline?