Exam Professional-Machine-Learning-Engineer Topic 5 Question 43 Discussion

Actual exam question for Google's Professional-Machine-Learning-Engineer exam
Question #: 43
Topic #: 5

You are developing an image recognition model using PyTorch based on ResNet50 architecture Your code is working fine on your local laptop on a small subsample. Your full dataset has 200k labeled images You want to quickly scale your training workload while minimizing cost. You plan to use 4 V100 GPUs What should you do?

A. Configure a Compute Engine VM with all the dependencies that launches the training Tram your model with Vertex Al using a custom tier that contains the required GPUs. B. Package your code with Setuptools and use a pre-built container. Train your model with Vertex Al using a custom tier that contains the required GPUs. C. Create a Vertex Al Workbench user-managed notebooks instance with 4 V100 GPUs, and use it to tram your model. D. Create a Google Kubernetes Engine cluster with a node pool that has 4 V100 GPUs Prepare and submit a TFJob operator to this node pool.

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