Customer Churn Prediction with Machine Learning | Python, XGBoost, SHAP & Streamlit Dashboard скачать в хорошем качестве

Customer Churn Prediction with Machine Learning | Python, XGBoost, SHAP & Streamlit Dashboard

🔮 Predicting which customers will leave BEFORE they do! In this project, I built a complete machine learning pipeline to predict customer churn and calculate Customer Lifetime Value (CLV) using the IBM Telco dataset. 📊 What's Covered: • Data cleaning & feature engineering (8 new features) • Training 3 ML models: Logistic Regression, Random Forest, XGBoost • Model interpretability with SHAP values • Interactive Streamlit dashboard for real-time predictions • Business insights: Why high-value customers churn at 43%! 🛠️ Tech Stack: Python | Pandas | Scikit-learn | XGBoost | SHAP | Streamlit | Matplotlib 📈 Results: • 84% AUC-ROC score • 80% Recall (catching churners before they leave) • Actionable business recommendations 💼 Perfect for: Data Science portfolios, ML beginners, business analytics enthusiasts 🔗 GitHub: [https://github.com/NnatuanyaFrankOguguo/pr...] #MachineLearning #DataScience #Python #ChurnPrediction #XGBoost #SHAP #Streamlit #Portfolio #CustomerAnalytics