Professional Machine Learning Engineer

Question

You work for a hospital that wants to improve how it schedules operations. You need to create a model using the relationship between the number of scheduled surgeries and occupied beds. You want to predict, in advance, how many beds patients will need each day based on the scheduled surgeries. You have one year of hospital data arranged in 365 rows.

The data contains these variables for each day:

Number of scheduled surgeries
Number of beds occupied
Date

You want to maximize the speed of model development and testing. What should you do?

Explanation

A BigQuery ML regression model predicts a real-valued target, such as the number of occupied beds, from input features available for that day. Scheduled surgeries are the relevant predictor, and date-derived features such as day of week can capture calendar effects. BigQuery ML can create and use regression models with default settings directly from a BigQuery table, minimizing development and testing effort.

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Professional Machine Learning Engineer

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