PROFESSIONAL-CLOUD-ARCHITECT · Question #357
PROFESSIONAL-CLOUD-ARCHITECT Question #357: Real Exam Question with Answer & Explanation
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Question
Your machine learning (ML) engineers use self-hosted Jupyter notebooks for tasks such as data preparation, model training, and fine-tuning. The operations team then deploys these models in various environments. You want to provide maximum flexibility for ML engineers, promote collaboration with a common toolset, and leverage Google Cloud's scalability, while following Google-recommended practices. What should you do?
Options
- AUse AutoML for machine learning and Cloud Deploy for model deployment.
- BUse Colab Enterprise for machine learning and DevOps for model deployment.
- CUse Vertex AI for machine learning and machine learning operations (MLOps) for model
- DUse TensorFlow for machine learning and Cloud Deploy for model deployment.
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