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Bank-Customer-Prediction

This data set contains information about bank customer and their churn status , indicating whether they have exited the bank or not. It is suitable for exploring and analyzing factors influencing customer churn in banking institutions and for building predictive models to identify customers at risk of churning.

Features

Exited: Indicates whether the customer has been with the bank (binary: yes/no)

RawNumber: The sequential number assigned to each row in the data set.

CustomerId: A unique identifier for each customer.

Surname: The surname of the customer.

CreditScore: The credit score of the customer.

Geography: The geographical location of the customer(e.g., country or region)

Gender: The gender of the customer.

Age: The age of the customer.

Tenure: The number of years the customer has been with the bank.

Balance: The account balance of the customer.

NumOfProducts: The number of bank products the customer has.

HasCaCard: Indicates whether the customer has a credit card (binary:yes/no)

IsActiveMember: Indicates whether the customer is an active member(binary: yes/no)

EstimatedSalary: The estimated salary of the customer

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