Description:
Predicting customer churn using data analysis, feature engineering, and machine learning techniques to help businesses retain at-risk customers and improve loyalty.
INTRODUCTION
In this notebook, we will explore how to predict customer churn using various data analysis and machine learning techniques. Churn prediction is crucial for businesses aiming to retain loyal customers who are at risk of leaving. By identifying these customers early, we can implement targeted strategies to improve customer satisfaction and loyalty, ultimately reducing churn rates and enhancing business performance. This project will involve data preprocessing, feature engineering, model training, and evaluation to develop an effective churn prediction model.