CarAudit.com : A Streamlit Webapp

Currently we can see many cars available in the market. Every car has different features and specifications. We decide the selling price of the car based on all these features available in the car. But instead of manually checking each and every feature and then deciding the price of the car might be sometime unfair, so I have developed one webapp using Linear regression model of machine learning and deployed using streamlit python framework. By using this webapp both seller and buyer can estimate the selling price of the car based on the features available in it.

2. How it works?

Complete machine learning model has been trained into the python programming language. For development of the code I have used Pycharm IDE. I have used Linear regression model of machine learning for prediction. I have used Scikit i.e. Sklearn libraries of machine learning in python. The dataset used in this project has been taken from Kaggle. I have used stramlit for deployment of the project which is basically python framework. I have also used Google Colaboratory for data preprocessing.