Develop a System to Predict the Price of Used Car Using ML

Shubham MukharjeeStudent, Dept. of Automobile Engineering, Dhole Patil College of Engineering, Pune, Maharashtra, IndiaMohit PatilStudent, Dept. of Automobile Engineering, Dhole Patil College of Engineering, Pune, Maharashtra, IndiaShriraj PatilStudent, Dept. of Automobile Engineering, Dhole Patil College of Engineering, Pune, Maharashtra, IndiaOmkar SonawaneStudent, Dept. of Automobile Engineering, Dhole Patil College of Engineering, Pune, Maharashtra, IndiaProf. Bhushan KaramkarProfessor, Dept. of Automobile Engineering, Dhole Patil College of Engineering, Pune, Maharashtra, India

Vol 7 No 2 (2023): Volume 7, Issue 2, February 2023 | Pages: 98-100

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 02-03-2023

doi Logo doi.org/10.47001/IRJIET/2023.702015

Abstract

The price of a vehicle is determined by the manufacturer, compiling all the taxes by the government and not everyone can afford it so the people look for some Less costly alternatives that are-used car and this helps to build a large used car market but due to the price irregularities this market is going through lots of problem so by using machine learning to develop a new model that will predict the price and help consume to buy the used car at a perfect, reasonable and trusted price. This research paper is the combination of datasets that have been collected by the Quickrcar.com and ML will be used to predict the price of a used car by creating a model using python, flask and HTML and Linear Regression and Lasso Regression will be used.

Keywords

Used Car, ML, python, flask, Lasso Regression, Linear Regression


Citation of this Article

Shubham Mukharjee, Mohit Patil, Shriraj Patil, Omkar Sonawane, Prof. Bhushan Karamkar, “Develop a System to Predict the Price of Used Car Using ML” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 2, pp 98-100, February 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.702015

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