Allae20/Car-Price-Prediction

A Machine Learning project for predicting used car prices in Morocco using Random Forest. It includes web scraping, data preprocessing, model training, model evaluation, feature importance analysis, and an interactive Streamlit web application. # Car Price Prediction in Morocco A Machine Learning project for predicting used car prices in Morocco using a Random Forest regression model. The project covers the entire machine learning pipeline, including web scraping, data preprocessing, exploratory data analysis, model training, evaluation, and deployment through an interactive Streamlit application. --- ## Features - Web scraping of used car listings - Data cleaning and preprocessing - Exploratory Data Analysis (EDA) - Random Forest regression model - Interactive price prediction - Similar car recommendation - Data visualization and insights --- ## Technologies - Python - Pandas - NumPy - Scikit-learn - Streamlit - Selenium - BeautifulSoup - Matplotlib - Joblib --- ## Project Structure ```text Car-Price-Prediction/ │ ├── app_v2.py ├── analytics.py ├── prediction.py ├── feature_importance.py ├── similar.py ├── data/ ├── models/ ├── notebooks/ ├── assets/ ├── requirements.txt └── README.md ``` --- ## Installation Clone the repository: ```bash git clone github.com ``` Go to the project folder: ```bash cd Car-Price-Prediction ``` Install the required libraries: ```bash pip install -r requirements.txt ``` Run the application: ```bash streamlit run app_v2.py ``` --- ## Application Preview ### Price Prediction ### Data Analysis ### Dashboard Analytics ### Correlation Matrix ### Similar Cars Recommendation --- ## Future Improvements - Increase the dataset size - Improve prediction accuracy - Deploy the application online - Add more advanced visualizations --- ## Author **Allae Elbaze** Master's Student in Computer Science and Artificial Intelligence Ibn Tofail University – Morocco