Car Price Prediction Using Machine Learning Algorithms

Abstract

Abstract: Machine learning(ML) is an area of a AI that has been a key component of digitization solutions that have attracted much recognition in the digital arena. ML is used everywhere from automating and do heavy tasks to offering intelligent insights in every industry to benefit from it. The current world already using the devices that are suitable these problems. For example, a wearable fitness tracker like Smart Band or a smart home assistant like Alexa, Google Home. However, there are many more examples of machine learning in use. In this project the task is to find out price of a used car. The cars dataset taken from Kaggle, where dataset contains used car details (variables), Our task is to finds out which variables are significant in predicting the price of a used car and how well these variables are important in predicting the price of a car. For this task we were using machine learning algorithms are linear regression, ridge regression, lasso regression, K-Nearest Neighbors (KNN) regressor, random forest regressor, bagging regressor, Adaboost regressor, and XGBoost.