A company wants to build an ML model by using Amazon SageMaker. The company needs to share and manage variables for model development across multiple teams. Which SageMaker feature meets these requirements?
Amazon SageMaker Feature Store ensures all teams have access to a centralized store of features, improving consistency and collaboration in ML workflows.
Amazon SageMaker Feature Store is designed to store, manage, and share features (variables) for machine learning models across teams. It provides a centralized repository to track and manage features, ensuring consistency in feature usage across various models and teams. This is ideal when you need to collaborate on feature development and reuse them in multiple ML models.
A: Amazon SageMaker Feature Store
Explanation:
Amazon SageMaker Feature Store is a purpose-built repository for storing, sharing, and managing features (variables) used in machine learning models. It allows teams to collaborate effectively by providing a centralized location for storing and accessing features across multiple ML workflows, ensuring consistency and reusability.
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