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You work for an ecommerce company that has a BigQuery dataset that contains customer purchase history, demographics, and website interactions. You need to build a machine learning (ML) model to predict which customers are most likely to make a purchase in the next month. You have limited engineering resources and need to minimize the ML expertise required for the solution. What should you do?
Correct Answer: A
Using BigQuery ML is the best solution in this case because: Ease of use: BigQuery ML allows users to build machine learning models using SQL, which requires minimal ML expertise. Integrated platform: Since the data already exists in BigQuery, there's no need to move it to another service, saving time and engineering resources. Logistic regression: This is an appropriate model for binary classification tasks like predicting the likelihood of a customer making a purchase in the next month.
