A BigQuery ML linear regressor model is trained hourly using Cloud Scheduler and Vertex AI Pipelines, with new data added every minute. The preprocessing includes quantile bucketization and MinMax scaling. The goal is to minimize storage and computational overhead.
The suggested answer is B. Using the TRANSFORM clause within the CREATE MODEL statement allows for efficient, inline calculation of necessary statistics, reducing external storage and processing needs.
You developed a BigQuery ML linear regressor model by using a training dataset stored in a BigQuery table. New data is added to the table every minute. You are using Cloud Scheduler and Vertex AI Pipelines to automate hourly model training, and use the model for direct inference. The feature preprocessing logic includes quantile bucketization and MinMax scaling on data received in the last hour. You want to minimize storage and computational overhead. What should you do?
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