{"id":31579143,"url":"https://github.com/artemxdata/car-price-prediction","last_synced_at":"2026-05-01T12:32:27.967Z","repository":{"id":317848385,"uuid":"1069077635","full_name":"artemxdata/Car-Price-Prediction","owner":"artemxdata","description":"Car Price Prediction – Machine learning project for estimating car prices based on technical specifications and market data. 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The goal is to build and compare several regression models and achieve RMSE \u003c 2500.\n\n## Project Description\nCars can have very different prices depending on mileage, age, engine power, brand, and other parameters. This project demonstrates how ML models can be applied to predict car prices and help buyers or sellers estimate the fair market value.\n\nWorkflow:\n1. Data preprocessing – cleaning, handling categorical and numerical features, scaling \u0026 encoding with ColumnTransformer.\n2. Model training – testing multiple regressors:\n   - Linear Regression \u0026 Ridge\n   - Decision Tree \u0026 Random Forest\n   - LightGBM (gradient boosting)\n3. Hyperparameter tuning with GridSearchCV inside Pipeline (no data leakage).\n4. Model evaluation – comparing performance with RMSE metric, analyzing training and prediction time.\n\n## Tech Stack\n- Python 3.13\n- NumPy\n- Pandas\n- Matplotlib\n- Seaborn\n- Scikit-learn\n- LightGBM\n\n## Results\n- Best performing model: LightGBM\n- Achieved RMSE \u003c 2500 (target reached)\n- Compared training time vs prediction speed across models\n\n## How to Run\nClone the repo:\ngit clone https://github.com/artemxdata/Car-Price-Prediction.git\ncd car-price-prediction\n\n\n## Create and activate a virtual environment:\n- python -m venv venv\n- source venv/bin/activate # Linux/Mac\n- venv\\Scripts\\activate # Windows\n\n\n## Install dependencies:\npip install -r requirements.txt\n\n\n## Run Jupyter Notebook:\njupyter notebook \"Car Price Prediction.ipynb\"\n\n\n## Project Structure\n\n```\n├── .gitignore # Git ignore file\n├── Car Price Prediction.ipynb # Main notebook with full ML pipeline\n├── LICENSE # Project license\n├── README.md # Project description and instructions\n└── requirements.txt # Minimal dependencies\n```\n\n## Future Improvements\n- Add more feature engineering (engine volume, region, condition, etc.)\n- Try additional boosting models (XGBoost, CatBoost)\n- Deploy as a simple web app for interactive car valuation\n\n## Author\nMade for educational and practical purposes.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fartemxdata%2Fcar-price-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fartemxdata%2Fcar-price-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fartemxdata%2Fcar-price-prediction/lists"}