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Google Professional Machine Learning Engineer

280 Questions120 Minutes70% Passing Score▣ Updated: Sep 2026

Question 70 of 280

Single answer
You lead a data science team at a large international corporation. Most of the models your team trains are largescale models using high-level TensorFlow APIs on AI Platform with GPUs. Your team usually takes a few weeks or months to iterate on a new version of a model. You were recently asked to review your team’s spending. How should you reduce your Google Cloud compute costs without impacting the model’s performance?
AUse AI Platform to run distributed training jobs with checkpoints.
BUse AI Platform to run distributed training jobs without checkpoints.
CMigrate to training with Kuberflow on Google Kubernetes Engine, and use preemptible VMs with checkpoints.
DMigrate to training with Kuberflow on Google Kubernetes Engine, and use preemptible VMs without checkpoints.
Correct Answer: C

Migrate to training with Kuberflow on Google Kubernetes Engine, and use preemptible VMs with checkpoints.

Explanation

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