regression model

The car market is highly dynamic, with vehicle prices influenced by various factors such as brand, model, mileage, year of manufacture, fuel type, engine capacity, and transmission system. Manually estimating the fair price of a car can be challenging for buyers, sellers, and dealerships.

This project aims to build a machine learning-based car price prediction model that accurately estimates the resale or market value of a car based on its features. The model will be trained on a dataset containing historical car sales data and their corresponding prices.