Explanation:
Vertex AI provides a comprehensive suite of services that includes Training Pipelines (MLOps), Data Management (Datasets), custom and Auto ML models management, deployment, and monitoring. This makes it a versatile choice for managing all aspects of machine learning projects, especially in a scenario requiring compliance, scalability, and cost efficiency. Options A, B, and C are partial answers and do not fully meet the project's requirements. For more details, visit Google Cloud Vertex AI and Vertex AI Custom Code Training.
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As a Financial Institution migrating to Google Cloud, you're tasked with leveraging Vertex AI for your ML models developed with PyTorch, TensorFlow, and BigQueryML. The project involves collaboration with international partners, requiring a solution that supports scalability, compliance with financial regulations, and cost efficiency. Vertex AI is being considered for its managed suite of services. Given these requirements, what comprehensive capabilities does Vertex AI offer to best meet the project's needs? (Choose two options)
A
Deployment environments only, without support for MLOps
B
Training Pipelines and Datasets for data sources, excluding models management
C
Training environments and MLOps, without inference environments
D
Training Pipelines, Datasets, Models Management and inference environments (endpoints)
E
All of the above