Car Price Prediction

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.

Features

• 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.

Technologies Used

• 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.