Food Delivery Time Prediction Using Machine Learning | ML Project with Streamlit & SHAP

Predicting Food Delivery Time using Machine Learning.

In this project, we built an advanced machine learning model to accurately predict food delivery ETA using real-world delivery data. The system uses feature engineering, ensemble learning, SHAP explainability, and a Streamlit web application for real-time predictions.

Technologies Used: Python, XGBoost, LightGBM, CatBoost, SHAP, Streamlit
Features: Distance calculation, traffic & weather analysis, ensemble stacking, confidence interval prediction
Goal: Improve delivery efficiency and customer satisfaction

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