Paper Title
A Comparative Study of Machine Learning Algorithm to Predict Used Car Prices in India with EDA

Abstract
In this research, we are doing a comparative analysis of the performance of regression models that can predict the prices of a used car and utilize exploratory data analysis to develop actionable insights to increase the profit. The dataset includes the data of the sold cars, which is extracted from the car Dekho website. To solve this problem, we propose a radical solution based on machine learning of ten regression models, namely Linear Regression, Ridge Regression, Lasso Regression, Decision Trees, KNN, Light GBM, Random Forest, XGBoost, SVM and Bayesian Regressor. Tree-based models XGBoost and Random Forest achieved the best R2 score of 0.91 on test data, whereas other models were effective to some extent. Keywords - Regression, Comparative Study, Data Visualization, Ensemble Modeling, Exploratory Data Analysis, Machine Learning