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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #206
You work for a retail company. You have been asked to develop a model to predict whether a customer will purchase a product on a given day. Your team has processed the company's sales data, and create
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Submitted by helene.fr· Apr 18, 2026ML model development
Question
You work for a retail company. You have been asked to develop a model to predict whether a customer will purchase a product on a given day. Your team has processed the company's sales data, and created a table with the following rows: - Customer_id - Product_id - Date - Days_since_last_purchase (measured in days) - Average_purchase_frequency (measured in 1/days) - Purchase (binary class, if customer purchased product on the Date) You need to interpret your model's results for each individual prediction. What should you do?
Options
- ACreate a BigQuery table. Use BigQuery ML to build a boosted tree classifier. Inspect the partition
- BCreate a Vertex AI tabular dataset. Train an AutoML model to predict customer purchases.
- CCreate a BigQuery table. Use BigQuery ML to build a logistic regression classification model. Use
- DCreate a Vertex AI tabular dataset. Train an AutoML model to predict customer purchases.
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Topics
#Model Explainability#Vertex AI AutoML#Tabular Data#Prediction Interpretability