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KhalilAmamri/Car_Valuation_Tunisia

Domaine:

socioeconomic

Type de record:

modelsoftware
Créateur:
Kha
Hôte:
🚗 Estimate used car prices in Tunisia using a Multiple Linear Regression model trained on 60,000+ synthetic listings (23 brands, 89% accuracy). Interactive Streamlit app with real-time predictions. # 🚗 Tunisia Car Price Predictor Estimate used car prices in Tunisia using Machine Learning. Interactive Streamlit app with real-time predictions and market insights. **Live App:** carvaluationtunisia.streaml… --- ## ✨ Key Features - ✅ **High Accuracy**: R² = 89.91% | MAE = 3,876 TND - 🎯 **3-Page Interactive App**: Predict Price • Market Insights • About Model - 💰 **Real-time Predictions**: Instant price estimates - 📊 **Market Dashboard**: 4 interactive charts showing pricing trends - 📦 **60,000+ Dataset**: Synthetic but realistic car listings - 🤖 **Linear Regression Model**: scikit-learn with feature transparency --- ## 🎬 Demo Video **Watch the app in action:** --- ## 🚀 Quick Start ### Online (Easiest) Visit: carvaluationtunisia.streaml… ### Local Setup ```pwsh # Clone & setup git clone github.com cd Car_Valuation_Tunisia # Create environment python -m venv .venv ./.venv/Scripts/Activate.ps1 # Install & run pip install -r requirements.txt streamlit run app/Predict_Price.py ``` Then open localhost --- ## 📁 Project Structure ``` Car_Valuation_Tunisia/ ├── app/ │ ├── Predict_Price.py # Main page - Price prediction │ └── pages/ │ ├── 1_Market_Insights.py # Dashboard with 4 charts │ └── 2_About_Model.py # Model documentation ├── data/raw/ │ └── tunisia_cars_dataset.csv # 60,000+ listings ├── models/ │ └── linear_regression_tunisia_cars.pkl ├── notebooks/ │ └── Tunisia_Cars_Price_Prediction.ipynb ├── requirements.txt └── README.md ``` --- ## 📖 How to Use ### 1. Predict Price - Enter car details (brand, year, mileage, etc.) - Click "Predict Price" - Get instant estimate with confidence range ### 2. Market Insights - **Chart 1**: Price distribution by category - **Chart 2**: Depreciation trends (year vs price) - **Chart 3**: Market price distribution - **Chart 4**: Top features affecting price ### 3. About Model …