Churn Prediction Model

This repository contains code and resources for building and deploying a churn prediction model based on the provided dataset.

The dataset consists of customer information from a bank, including features such as Credit Score, Geography, Gender, Age, Tenure, Balance, Number of Products, etc. The target variable, 'Exited,' indicates whether a customer has churned (1) or not (0).

The churn prediction model is built using machine learning techniques, including data preprocessing, feature engineering, model selection, and evaluation. The notebooks provide detailed explanations and code for each step in the process.

Feedback, bug reports, and contributions are welcome! Feel free to submit issues or pull requests to improve the churn prediction model and its documentation.

This project is maintained by [Mohamed Alansary]. You can contact me at [[email protected]] for any inquiries or collaborations.

This project is licensed under the MIT License.

Thank you for visiting the Churn Prediction Model repository! I hope you find it helpful in your predictive modeling endeavors.