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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #322
PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #322: Real Exam Question with Answer & Explanation
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Submitted by neha2k· Apr 18, 2026ML model development
Question
You lead a data science team that is working on a computationally intensive project involving running several experiments. Your team is geographically distributed and requires a platform that provides the most effective real-time collaboration and rapid experimentation. You plan to add GPUs to speed up your experimentation cycle, and you want to avoid having to manually set up the infrastructure. You want to use the Google-recommended approach. What should you do?
Options
- AConfigure a managed Dataproc cluster for large-scale data processing. Configure individual
- BUse Colab Enterprise with Cloud Storage for data management. Use a Git repository for version
- CUse Vertex AI Workbench and Cloud Storage for data management. Use a Git repository for
- DConfigure a distributed JupyterLab instance that each team member can access on a Compute
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Topics
#Vertex AI Workbench#Managed ML development#Collaboration tools#ML experimentation