Customer Churn Prediction using Artificial Neural Networks (ANN)

app link: https://customer-churn-project-akashvarma26.streamlit.app
This repository contains a project aimed at predicting customer churn using Artificial Neural Networks (ANN) built with TensorFlow and deployed using Streamlit.

Project Overview

Customer churn prediction helps businesses identify customers who are likely to leave (churn) and enables them to take necessary actions to retain these customers. This project involves building and training an ANN model to classify whether a customer is likely to churn or not based on their profile and interaction data.

The project includes:

• Data preprocessing
• Model building using TensorFlow
• Model evaluation and performance metrics
• Deployment of the model using Streamlit for easy interaction with the model

Conclusion

This project demonstrates how to build a predictive model for customer churn using ANN in TensorFlow and deploy it with Streamlit. By predicting churn, businesses can proactively identify at-risk customers and take steps to retain them, improving customer satisfaction and reducing churn rates.