Business Problem :
This project is to create an algorithm that predicts used car price based on the Car dataset.This dataset contains information about used cars listed on different websites. The data can be used for a lot of purposes such as price prediction to exemplify the use of linear regression in Machine Learning. i need to predict the Selling price is my target feature and all other features are independant variable. Selling price is my y-hat.
The columns in the given dataset is as follows:
- Car_Name
- Year
- Selling_Price
- Present_Price
- Kms_Driven
- Fuel_Type
- Seller_Type
- Transmission
- Owner
Click Link : Car Price Prediction.
Conclusion :
I did my EDA and trained my dataset using linear regression and random forest regresser. The r2 score for linear regression was 0.91 and for random forest regressor was 0.96 therefotre i chose the random forest with 0.96 accuracy