Predicting the Price of used Cars using Machine Learning
V Viswanatha, A C Ramachandra, Bidare Divakarachari Parameshachari, H V Vachan, Sourav S Shetty · 2023
A significant element of digitizing solutions that have gained widespread awareness in the digital sphere is Machine Learning (ML), a field of artificial intelligence. Every sector uses ML to its advantage, from automating laborious activities to providing insightful analysis. The modern world already employs the tools necessary to solve these issues. For instance, a smart home companion like Alexa or Google Home or a wearable fitness device like Smart Band. There are, however, a lot more applications for machine learning. The purpose of this model is to calculate the value of a used car. Our objective is to establish which factors influence the cost of a used car and how those factors influence the cost of a car. The dataset for vehicles was obtained from the Kaggle database. The Linear Regression approach is utilized to calculate the automobile costs in this case. The goal of this research is to create models utilizing the vehicle dataset and the aforementioned machine learning approaches. The purpose of this study is to show how well the Linear Regression model handles regression problems. This research has been attempted to forecast the price of a used automobile and develop a statistical model based on the data. The obtained results of MAE, MSE and R2 as score of the Linear Regression Model are 1.259 , 3.493 and 0.829 respectively.