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Bigquery Ml Create Model Linear Regression

Section: Execute SQL to create, train, and evaluate models using BigQuery ML

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A data analyst at a retail company wants to build a machine learning model directly in BigQuery to predict the continuous numerical dollar amount (total_spend) that each customer will spend over the next quarter.

The training data resides in a BigQuery table named ecommerce.customer_features and contains columns for age, country, previous_purchases, and total_spend.

Which SQL statement correctly creates and trains this model?

CREATE OR REPLACE MODEL ecommerce.spend_model OPTIONS(model_type='logistic_reg', input_label_cols=['total_spend']) AS SELECT age, country, previous_purchases, total_spend FROM ecommerce.customer_features;

CREATE OR REPLACE MODEL ecommerce.spend_model OPTIONS(model_type='linear_reg', input_label_cols=['total_spend']) AS SELECT age, country, previous_purchases, total_spend FROM ecommerce.customer_features;

TRAIN MODEL ecommerce.spend_model SET TARGET = 'total_spend' USING 'linear_reg' AS SELECT age, country, previous_purchases, total_spend FROM ecommerce.customer_features;

CREATE OR REPLACE MODEL ecommerce.spend_model OPTIONS(model_type='kmeans', num_clusters=4) AS SELECT age, country, previous_purchases, total_spend FROM ecommerce.customer_features;

Associate Data Practitioner

Bigquery Ml Create Model Linear Regression

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