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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #322

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…

The correct answer is C. Use Vertex AI Workbench and Cloud Storage for data management. Use a Git repository for. Vertex AI Workbench is the Google-recommended, fully managed environment for collaborative ML development. It supports GPU acceleration, integrates seamlessly with Cloud Storage for data, and allows version control through Git. It also eliminates the need to manually set up…

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

How the community answered

(33 responses)
  • A
    9% (3)
  • B
    12% (4)
  • C
    76% (25)
  • D
    3% (1)

Explanation

Vertex AI Workbench is the Google-recommended, fully managed environment for collaborative ML development. It supports GPU acceleration, integrates seamlessly with Cloud Storage for data, and allows version control through Git. It also eliminates the need to manually set up infrastructure, making it ideal for distributed teams needing real-time collaboration and rapid experimentation.

Topics

#Vertex AI Workbench#Managed ML development#Collaboration tools#ML experimentation

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