Question: code python customer_id credit_score country gender age tenure balance products_number credit_card active_member estimated_salary churn Step 2: Feature Extraction and Selection Select relevant features that may

code python customer_id credit_score country gender age tenure balance products_number credit_card active_member estimated_salary churn Step 2: Feature Extraction and Selection Select relevant features that may be predictive of the target variable (churn). . Retain features such as credit_score, age, tenure, balance, products_number, credit_card, active_member, and estimated_salary as they can have predictive power regarding churn

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