Customer Churn Prediction using Logistic Regression

This project was completed as part of the Codveda Data Analytics Internship.

Project Objective

The objective of this project was to build a machine learning classification model to predict customer churn.

Tasks Performed

• Loaded and preprocessed churn dataset
• Converted categorical values into numerical format
• Split dataset into training and testing sets
• Built Logistic Regression classification model
• Predicted customer churn
• Evaluated model using:
  • Accuracy Score
  • Confusion Matrix

Tools Used

• Python
• Pandas
• Matplotlib
• Scikit-learn

Dataset

Customer Churn Dataset

Output

Successfully built and evaluated a customer churn prediction model using Logistic Regression.