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Google Professional Machine Learning Engineer

Google Professional Machine Learning Engineer

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You are using BigQuery ML to train a linear regression model on a table that receives new data every minute. The model is retrained hourly using Cloud Scheduler and Vertex AI Pipelines. Feature preprocessing involves quantile bucketization and MinMax scaling on the last hour of data. To minimize storage and computational overhead, what is your recommended approach?

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