This project provides a web-based car price prediction tool that uses machine learning to estimate car prices based on various features. The process involves finding and scraping tokens, cleaning the data, and using a predictive model to estimate car prices.
- Token Finder: Identifies and extracts necessary tokens for scraping data.
- Data Scraping: Collects car price data from relevant sources.
- Data Cleaning: Processes and cleans the scraped data to prepare it for prediction.
- Price Prediction: Uses a machine learning model to predict car prices based on cleaned data.
- Web Interface: Provides a user-friendly interface for inputting data and displaying predictions.
- Flask: For creating the web application backend.
- HTML/CSS: For designing the frontend interface.
- Python: For data scraping, cleaning, and implementing the machine learning model.
- Machine Learning: For predicting car prices based on historical data.