Delivery Time Prediction App

A web application built with Streamlit that predicts food delivery time based on several features. The app also provides interactive visualizations to help understand the impact of each feature on the final prediction.

---

Features

• Real-time Prediction: Get an estimated delivery time in hours and minutes based on your inputs.
• Interactive UI: Use sliders and number inputs to set feature values.
• Feature Impact Analysis: Interactive charts show how changes in one feature affect delivery time while others are held constant.
• Modular Codebase: Clean separation between user interface, model handling, and plotting logic.

---

Technologies Used

• Python: Core programming language.
• Streamlit: For building the interactive web app.
• Scikit-learn: For using the Random Forest Regressor model.
• Pandas: For data manipulation and DataFrame creation.
• NumPy: For numerical operations.
• Joblib: For loading the pre-trained .pkl model.
• Altair: For declarative and interactive visualizations.

---