This project has been deployed using railway. You can access it through : https://fordpredictor.up.railway.app
Fordpredictor is a web application that uses linear regression to predict the prices of used Ford cars. It is developed as a final project for a college course that aims to demonstrate the capability of machine learning in solving real-world problems. The app allows users to input various parameters such as the model, year, mileage, and additional features of the car, and returns an estimated price for the vehicle. The dashboard for the application is sourced from Kaggle and provides a user-friendly interface for viewing the predictions and inputting data. The app is built using Flask, a Python web framework, and utilizes pre-trained linear regression models. It is a useful tool for people who are planning to buy or sell a used Ford car as it provides an estimated value of the car based on the input parameters.
This project is intended for educational and demonstration purposes only. It is available on Github for anyone who is interested in learning about machine learning and web development using Flask and Python.