This project aims to predict customer churn using machine learning techniques. Churn, in this context, refers to the phenomenon where customers stop doing business with a company. By predicting churn, companies can take proactive measures to retain customers and reduce revenue loss.
Dataset
The dataset used in this project is synthetic and generated to simulate real-world scenarios of customer behavior. It contains synthetic features representing various aspects of customer interactions and behaviors, as well as a binary target variable indicating whether a customer churned or not within a certain time period