oumaimabelabbas/AutoPredict

Full-stack Machine Learning system for used car price prediction in Morocco – from data scraping to model deployment via FastAPI, integrated into a web application. # AutoPredict AutoPredict is a used car price prediction project for the Moroccan market. The project covers the complete pipeline: data collection, machine learning and deep learning modeling, deployment through a REST API, and integration into a web application. ## Technologies Used **Data & ML:** Python, Pandas, Selenium, BeautifulSoup, scikit-learn, TensorFlow **Backend:** FastAPI, Node.js, Express, MongoDB **Frontend:** HTML, CSS, JavaScript **Security:** JWT authentication ## Branch Structure **master:** Web interface and deployment (Node.js + MongoDB + frontend) **ml_pipeline:** Jupyter notebooks containing all ML stages: - Data scraping and cleaning - Dataset preparation - Training and comparison of models (Linear Regression, Polynomial Regression, Decision Tree, Random Forest, SVR, ANN) - Model testing and validation ## Key Features - Data collection and CSV dataset preparation - Training and evaluation of regression models and neural networks - Model deployment via REST API using FastAPI - Full-stack web interface for accessing predictions - JWT authentication, prediction storage, and history tracking