/Churn-model-for-customers-of-bank

In this project, a predictive churn model is developed for a bank data using machine learning techniques. 10000 observations were used to build and validate the model that has 10 features. The target feature is a binary class with Positive (1) label being the customer has exited from the bank and Negative (0) being the customer stays.

Primary LanguageJupyter Notebook

Churn-model-for-customers-of-bank

In this project, a predictive churn model is developed for a bank data using machine learning techniques. 10000 observations were used to build and validate the model that has 10 features. The target feature is a binary class with Positive (1) label being the customer has exited from the bank and Negative (0) being the customer stays.