Scenario: Clint Barton, now serving as an ML azure video
dp-100-data-scientist-assoc video for scenario: Clint Barton, now serving as an ML Developer at the Hydra Foundation, is tasked with deploying a trained machine
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Scenario: Clint Barton, now serving as an ML Developer at the Hydra Foundation, is tasked with deploying a trained machine learning model for real-time inferencing in production. The deployment must meet the following key requirements: High performance Scalability Security Question: Which model deployment endpoint should Clint choose to ensure optimal performance, scalability, and security in a production environment?