ansarthescientist/xgboost_prediction

This project demonstrates how machine learning can be employed to identify potential churn risks.

Customer Churn Prediction with XGBoost

Overview

This project focuses on predicting customer churn using the XGBoost algorithm. Customer churn, or attrition, is a critical metric for businesses as it impacts revenue and long-term growth. This project demonstrates how machine learning can be employed to identify potential churn risks.

Installation

Ensure you have the following Python packages installed:

• Pandas
• NumPy
• Scikit-learn
• XGBoost

You can install these packages using pip: !pip install pandas>=0.25.1 !pip install numpy>=1.17.2 !pip install scikit-learn !pip install xgboost>=0.90

Usage

Run the Jupyter Notebook to proceed through the stages of data preprocessing, feature engineering, model training, evaluation, and prediction.