Car Price Prediction using Linear Regression

This project demonstrates the use of linear regression to predict car prices based on features such as mileage, age, brand, and more. The goal was to create a model that helps sellers and buyers make informed decisions about the fair market value of used cars.

Key Features of the Project

Data preprocessing, including handling missing values and feature scaling.
Training and evaluation of a linear regression model.
Visualization of results for better interpretability.
Deployment-ready scripts for production use.

Project Screenshots

Training Linear Regression Model Screenshot

The screenshots above illustrate the step-by-step implementation of the project, including data preprocessing, training, evaluation metrics, and results visualization. These steps showcase the accuracy and interpretability of the model.