Car Price Project

* **Data Collection:** Scraped real-world automotive datasets from Hatla2ee and Dubizzle to build a comprehensive training corpus of used vehicle specifications (brand, mileage, transmission, fuel type).

* **Pipeline Engineering:** Engineered a robust ML pipeline with strict leakage prevention using training-split StandardScaler, Winsorizing outlier clipping, and One-Hot Encoding for categorical features.

* **Model Benchmarking & Optimization:** Benchmarked multiple regressors (Linear Regression, KNN, Decision Trees, Random Forest) and optimized performance via 5-Fold Cross-Validation with GridSearchCV for R² and RMSE evaluation.

* **Deployment:** Serialized optimal model pipeline and deployed an interactive Streamlit web application for real-time car value estimation.

* **Technologies Used:** Python, Scikit-Learn, Pandas, NumPy, Streamlit, GridSearchCV, Web Scraping.