CLOUD-DIGITAL-LEADER · Question #400
An organization wants to build custom machine learning models. They require a managed platform that provides services to gather data, build models, and then deploy and monitor those models. Which serv
The correct answer is D. Vertex AI. Vertex AI is Google Cloud's unified, managed ML platform covering the full lifecycle from data gathering through model deployment and monitoring.
Question
An organization wants to build custom machine learning models. They require a managed platform that provides services to gather data, build models, and then deploy and monitor those models. Which service should they use?
Options
- ADocument AI
- BNatural Language API
- CKubernetes Engine
- DVertex AI
How the community answered
(32 responses)- A3% (1)
- B3% (1)
- D94% (30)
Why each option
Vertex AI is Google Cloud's unified, managed ML platform covering the full lifecycle from data gathering through model deployment and monitoring.
Document AI is a specialized service for processing and extracting information from documents, not a general-purpose custom ML development platform.
Natural Language API is a pre-trained API for text analysis tasks such as sentiment and entity detection, not a platform for training and deploying custom models.
Kubernetes Engine is a container orchestration platform for deploying and managing containerized workloads, not an ML development or model management platform.
Vertex AI is a fully managed end-to-end platform that supports data gathering, custom model training, deployment, and monitoring within a single unified environment. It removes the need for organizations to maintain their own ML infrastructure while supporting custom model development. No other listed service covers all stages of the ML lifecycle in one managed platform.
Concept tested: Vertex AI as managed end-to-end ML platform
Source: https://cloud.google.com/vertex-ai/docs/start/introduction-unified-platform
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