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End-to-end implementation and deployment of Machine Learning Car Price Prediction using python, flask, gunicorn, scikit-Learn, etc. on Heroku web application platform.

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Car Price Prediction

This repository consists of files required for end to end implementation and deployment of Machine Learning Car Price Prediction web application created with Flask and deployed on the Heroku platform.

Table Of Contents

App Link

If you want to view the deployed model, click on the following link: https://carpricepredictionv1.herokuapp.com/

A glimpse of the web app:

APP GIF

• If you encounter this webapp as shown in the picture given below, it is occuring just because free dynos for this particular month provided by the Heroku platform have been completely used. You can access the webpage on 1st of the next month.

Heroku-Error

About the App

The Car Price Prediction is a flask web application which predicts car prices based on given independent features like Car_Name, Year, Selling_Price, Present_Price, Kms_Driven, Fuel_Type, Seller_Type, Transmission, and Owner. The dataset is available at Kaggle, and it's provided by cardekho.com.

To install the required packages and libraries, run this command in the project directory after cloning the repository:

pip install -r requirements.txt

Deployement on Heroku

Signup in order to create virtual app. You can either connect your github profile or download Heroku cli to manually to deploy this project.

The next step would be to follow the instruction given in the Heroku Documentation to deploy a web app.

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End-to-end implementation and deployment of Machine Learning Car Price Prediction using python, flask, gunicorn, scikit-Learn, etc. on Heroku web application platform.

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