Google Professional Machine Learning Engineer
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Ultimate access to all questions.
You are building an MLOps platform to automate your company's ML experiments and model retraining. You need to organize the artifacts for dozens of pipelines. How should you store the pipelines' artifacts?
A
Store parameters in Cloud SQL, and store the models’ source code and binaries in GitHub.
B
Store parameters in Cloud SQL, store the models’ source code in GitHub, and store the models’ binaries in Cloud Storage.
C
Store parameters in Vertex ML Metadata, store the models’ source code in GitHub, and store the models’ binaries in Cloud Storage.
D
Store parameters in Vertex ML Metadata and store the models’ source code and binaries in GitHub.