AI-powered delivery ETA prediction system using Decision Trees and real-world features.
# đźšš Morocco Delivery Intelligence
An AI-powered delivery system that predicts **Estimated Time of Arrival (ETA)** and determines whether a delivery will arrive **on time or late**, using machine learning.
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## 📌 Project Overview
This application simulates a real-world delivery system in Morocco.
It allows users to:
- Select a **warehouse city** and a **delivery destination**
- Predict the **ETA (Estimated Time of Arrival)**
- Determine whether the delivery will be **On Time or Late**
- Visualize the **delivery route on an interactive map**
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## đź§ Machine Learning
The system uses:
- **Decision Tree Model** for prediction
- Classification:
- âś… On Time
- ❌ Late
- Regression for ETA prediction
### Features used:
- Distance between cities
- Vehicule type
- Traffic level
- Weather conditions
- Product weight
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## 🗺️ Features
- 📍 Interactive map with delivery route (Folium)
- ⏱ ETA calculation
- 📊 On-time vs Late prediction
- đź§ Machine Learning integration
- 🌍 Morocco cities dataset
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## 🛠️ Tech Stack
- Python
- Streamlit
- Scikit-learn
- Pandas
- Folium
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## 🚀 How to Run the App
```bash
# Clone the repository
git clone
github.com
# Navigate to the project folder
cd Morocco-Delivery-Intelligence
# Install dependencies
pip install -r requirements.txt
# Run the app
streamlit run app.py