Analyzing Customer Churn with Python

Introduction

Customer churn is a critical metric for any subscription-based business. In this post, I explore how to predict churn using a telecom dataset.

The Data

We used a dataset containing 7000 customer records…

Methodology

1. Data Cleaning: Handling missing values.
2. EDA: Visualizing distributions.
3. Modeling: Comparing Logistic Regression vs Random Forest.

Results

Random Forest achieved an accuracy of 85%…