Customer Churn Prediction in Telecom Sector Using Machine Learning

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Table of Contents

• About
• Project Structure
• Getting Started
  • Prerequisites
  • Installation
• Usage
  • Data Preparation
  • Model Training
  • Evaluation
• Features
• Contributing
• License
• Acknowledgments

About

This project is a machine learning model for predicting customer churn in the telecom sector. Customer churn refers to the percentage of customers who leave or stop using a service during a certain time period. In the telecom sector, reducing churn is critical for business success. This model aims to predict which customers are at risk of churning, allowing proactive retention efforts.

Project Structure

• data/: Contains dataset files and data preprocessing scripts.
• models/: Stores trained machine learning models.
• notebooks/: Jupyter notebooks for data exploration, model development, and evaluation.
• src/: Source code for the customer churn prediction model.
• requirements.txt: List of Python packages required to run the project.

Getting Started

Prerequisites

• Python 3.x
• Create a virtual environment (optional but recommended).

Installation

1. Clone this repository:

git clone https://github.com/Mr-Alite/customer-churn-prediction.git
cd customer-churn-prediction