Google Professional Data Engineer
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You are tasked with developing a linear regression model in BigQuery ML to predict the likelihood of a customer purchasing your company's products. The model uses city names as a key predictive factor. What is the most efficient way to structure your data into columns for training and deploying the model with minimal coding effort?
A
Utilize Cloud Data Fusion to categorize each city into regions labeled numerically (1, 2, 3, etc.), then use these numbers to represent cities in the model.
B
Apply SQL in BigQuery to perform one-hot encoding on the city column, transforming each city into a separate column with binary values (0 or 1).
C
Exclude the city information from your dataset by creating a new view in BigQuery that omits the city column.
D
Implement TensorFlow to create a categorical variable with a predefined vocabulary list, then upload this vocabulary file as part of your model to BigQuery ML.