cars_price_prediction

Objective

In this project I'm trying to analyse and visualize the used car prices from the dataset availabe at Kaggle in order to predict the most probable car prices with the use of basic linear regression models: Linear Regression, Ridge Regression, Lasso Regression and ElasticNet Regression.

Vehicle dataset from cardekho : https://www.kaggle.com/nehalbirla/vehicle-dataset-from-cardekho

Dataset Description

This dataset contains information about used cars listed on www.cardekho.com. We are going to use for finding predictions of price with the use of regression models.

Size of the dataset : 301 records * 9 features

The datasets consist of several features include:

1. Car_Name : This column should be filled with the name of the car.

2. Year : This column should be filled with the year in which the car was bought.

3. Selling_Price : This column should be filled with the price the owner wants to sell the car at.

4. Present_Price : This is the current ex-showroom price of the car.

5. Kms_Driven : This is the distance completed by the car in km.

6. Fuel_Type : Fuel type of the car i.e Diesel,Petrol,CNG

7. Seller_Type : Defines whether the seller is a dealer or an individual.

8. Transmission : Defines whether the car is manual or automatic.

9. Owner : Defines the number of owners the car has previously had.