A data science team needs a centralized and organized location to store its various model versions, track their metadata, and easily deploy them to the respective applications. What Google Cloud service should they use?
A Model Registry (specifically part of Vertex AI Model Registry) is designed precisely for managing the lifecycle of machine learning models. It provides a centralized repository for storing, versioning, tracking metadata, and facilitating the deployment of models, which is essential for MLOps. Cloud Storage is for raw data, BigQuery for data warehousing, and Vertex AI Pipelines for workflow orchestration.
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