Price-Estimation-of-Used-Cars

Estimation of price of used cars

Table of contents

• General info
• Technologies
• Setup

General info

The project is based on estimating the price of used car according to their models, engine, miles run and various other attributes like Location, Year, Kilometers_Driven, Fuel_Type, Transmission, Owner_Type, Mileage, Engine, Power and Seats.

Technologies

• Python
• Jupyter Notebook

Data

The data is present in kaggle.

Machine Learning ALgorithms used

• XGBoost
• Random Forest Regressor
• LGBM Regressor

Summary of the scores obtained after training

Framework	Prediction Score
XGBoost	89.45
Random Forest Regressor	98.35
LGBM Regressor	88.69

Results

It is observed that Random Forest Regressor performs very well on this given dataset.