NCP-ADS

Data Preparation

hard

Question 1 of 34

In a model-serving readiness check, several options sound plausible and only one matches the documented guidance. Which recommendation best addresses augment limited data scenario?

ASkip benchmarking and assume the fastest option is obvious before measuring.

BTreat data preparation, model training, deployment, and monitoring as the same stage.

CChoose synthetic augmentation when the dataset needs additional examples before later modeling stages.

DSkip dataset acquisition because preparation starts only after perfectly curated data already exists.

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