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GCP Cloud Digital Leader Practice Question

An e-commerce retailer keeps millions of historical transaction records in BigQuery. The marketing team wants to quickly build a model that predicts whether a customer will make another purchase, and they have very limited machine-learning expertise. To avoid moving data out of BigQuery, which Google Cloud approach will deliver the needed insights with the least development effort and fastest time-to-value?

  • Create an AutoML Vision model to perform image classification on the transaction tables.

  • Export the data to Vertex AI and code a custom TensorFlow model that trains on Cloud TPUs.

  • Use BigQuery ML to train a classification model directly within BigQuery using SQL.

  • Call the pre-trained Natural Language API to classify the transaction data.

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