Google Cloud Professional Machine Learning Engineer — Question 64

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?

Answer options

• 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.

Correct answer: B

Explanation

The correct answer is B, as running a hyperparameter tuning job on AI Platform using custom containers allows for leveraging the PyTorch model directly without the need for conversion to another framework. Options A and D involve converting the model to Keras and TensorFlow respectively, which is not necessary and can complicate the tuning process. Option C, while valid, requires additional setup with Kubeflow Pipelines and Katib, making it less efficient for this scenario.