Question 66

Your data science team is training a PyTorch model for image classification based on a pre-trained RestNet model. You need to perform hyperparameter tuning to optimize for several parameters. What should you do?

A. Convert the model to a Keras model, and run a Keras Tuner job.
B. Run a hyperparameter tuning job on AI Platform using custom containers.
C. Create a Kuberflow Pipelines instance, and run a hyperparameter tuning job on Katib.
D. Convert the model to a TensorFlow model, and run a hyperparameter tuning job on AI Platform.

References

https://www.kubeflow.org/docs/components/katib/overview/

https://cloud.google.com/blog/topics/developers-practitioners/pytorch-google-cloud-how-deploy-pytorch-models-vertex-ai

https://cloud.google.com/blog/topics/developers-practitioners/pytorch-google-cloud-how-train-and-tune-pytorch-models-vertex-a i

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Question 66