customer-churn

Customer churn prediction with Python using synthetic datasets. Includes data generation, feature engineering, and training with Logistic Regression, Random Forest, and Gradient Boosting. Improved pipeline applies hyperparameter tuning and threshold optimization to boost recall. Outputs metrics, reports, and charts.

Customer Churn Prediction (End-to-End ML Pipeline)

Analyze your customer database with ease

Cloud-native MLOps platform for customer churn prediction using FastAPI, MLflow, Docker, Kubernetes, and GitHub Actions.

This is a Machine Learning + Flask Web App that predicts whether a customer is likely to churn and suggests a discount policy based on churn probability.

Machine learning project for customer churn prediction using Python, Scikit-learn, and interactive business analytics.

AI-Powered Telecom Customer Churn Prediction Dashboard using Random Forest and Streamlit

E-commerce customer churn prediction with CatBoost. 98.1% ROC-AUC, 60.6% cost reduction. Interactive Streamlit dashboard with business impact analysis.

customer churn prediction system with Django REST, MongoDB, and ML (87% accuracy)

Customer _Churn_Prediction using Machine Learning

Predict customer churn using machine learning models with the Telco Customer Churn dataset. Includes EDA, feature engineering, and Random Forest classification.

A machine learning pipeline to predict customer churn and improve retention

Customer Churn Analysis using Python, SQL , Excel and Power BI with interactive dashboard and business insights.

Production-style machine learning platform for telecom customer churn prediction with modular pipelines, MLflow tracking, FastAPI inference, and Docker deployment.

🎯 Predict customer churn with 96%+ accuracy using Random Forest ML. Beautiful visualizations, production-ready code, and real business impact. Save revenue before customers leave! 🚀

A Machine Learning-Based Decision Support System for Predicting Customer Attrition and Quantifying Revenue Risk in Subscription Businesses

🚀 ChurnNova — An AI-powered customer churn prediction app built with Streamlit, Random Forest & Plotly. Supports single & bulk predictions with risk segmentation and model insights.

End-to-end Machine Learning project to predict and analyze customer churn using scikit-learn and Pandas.

🛒 Machine Learning model to predict customer churn in e-commerce using RFM analysis and LightGBM. Achieved 77% ROC-AUC with 75% recall. Features SHAP interpretability, 24 engineered features from 540K+ transactions. Includes full EDA, model comparison, and business recommendations.

An end-to-end Customer Churn Prediction project built using Machine Learning, FastAPI, and Streamlit. The model predicts whether a telecom customer is likely to churn based on factors such as tenure, contract type, internet service, payment method, monthly charges, and total charges. The project includes model training, backend API integration, and