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You are tasked with developing a linear regression model using BigQuery ML with the goal of predicting the likelihood that a customer will purchase your company's products. One of the key predictive features in your model is the city name of the customer. For successful training and deployment of this model, your data should be structured in a columnar format. Your objective is to prepare the data with minimal coding effort while maintaining the integrity of the predictive variables. What approach should you take?
A
Create a new view with BigQuery that does not include a column with city information.
B
Use SQL in BigQuery to transform the state column using a one-hot encoding method, and make each city a column with binary values.
C
Use TensorFlow to create a categorical variable with a vocabulary list. Create the vocabulary file and upload that as part of your model to BigQuery ML.
D
Use Cloud Data Fusion to assign each city to a region that is labeled as 1, 2, 3, 4, or 5, and then use that number to represent the city in the model.