ML model to predict customer churn for a telecom company

Developed a machine learning model to predict customer churn for a telecommunications company. Used Python and popular machine learning libraries like scikit-learn and XGBoost to preprocess data, train and validate the model. Achieved an accuracy of 87% on the test dataset. Implemented the model in a web application using Flask and deployed it on Heroku for real-time predictions."

This project involves building a machine learning model for predicting customer churn for a telecommunications company. It uses Python and popular machine learning libraries to preprocess data, train and validate the model. The project achieved a high level of accuracy, which indicates that the model is effective in predicting customer churn. The model was then implemented in a web application using Flask and deployed on Heroku for real-time predictions.