Publication

Abstract : The automobile industry is experiencing a rapid increase in demand due to the growing population, leading to an increase in the sales of automobiles. Industry experts focus on renewing automobiles and increasing their efficiency and power while making them user-friendly and cost-effective. To assist people in purchasing cars within their budget, machine learning algorithms are utilized to predict the price of cars accurately. A machine learning model with high accuracy is integrated into a user-friendly interface, allowing people to view the precise price of the car. The user interface is designed to be user-friendly, making it easy for people to use. This paper presents various regression and classification models and their accuracies and promises to provide the price of the cars according to given inputs with a user-friendly interface. A supervised regression model is developed using multiple regression techniques trained from the car dataset provided. Data cleaning is performed to enhance the performance of these regression models by converting null values to non null values in the dataset.