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Scenario: Big Belly Foods, Inc. (BBF) operates azure video

 ·  PT1H46M27S  ·  EN

dp-100-data-scientist-assoc video for scenario: Big Belly Foods, Inc. (BBF) operates 300 convenience stores across Latin America, offering a variety of packaged

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Scenario: Big Belly Foods, Inc. (BBF) operates 300 convenience stores across Latin America, offering a variety of packaged foods, drinks, and prepared meals such as sandwiches and pizzas. The company’s IT Team is focused on optimizing hyperparameters for a machine learning model used to enhance business operations. As a member of the team, you need to terminate the hyperparameter tuning process early when the target metric is at least 35% worse than the best-performing one in the ratio. Question: Which early termination configuration policy should be applied to ensure efficient tuning and avoid excessive computation?