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GCP Cloud Digital Leader Practice Question

A retailer's data-science team already builds image-classification models with the open-source TensorFlow framework. To shorten training time they want to move the workload to Google Cloud, avoid buying on-premises GPUs, and keep most of their TensorFlow code unchanged. Which Google Cloud option best meets these requirements?

  • Run the training jobs on Cloud TPU to leverage Google's custom ML accelerators.

  • Export the data to BigQuery ML and retrain the model by writing SQL statements.

  • Move the project to AutoML Vision so Google handles the entire training process.

  • Create a Dataproc Hadoop cluster using standard CPU virtual machines for training.

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