Boston-House-Price-Prediction

Table of Content

• Overview
• Demo
• Screenshots
• Installation
• Deployement on Heroku
• Documentation
• Bug / Feature Request
• Technologies Used
• Team

Overview

Presently, there are manual specialists who examine highlights of a real estate market and gives the expectations, however in some cases it will be correct or wrong along these lines, it makes an enormous issue for the organization, their mistake rates increments, so for this issue there is an answer by utilizing Machine Learning models to build their benefits.

We need to examine the information appropriately, understanding the highlights and afterward carrying out different models on it and choosing the best one for the task which will give us precise cost for the houses in that specific zone. It will help the land organization to acquire benefits by utilizing this House Price Prediction ML model.

Demo

Link: https://bostonhousepriceml.herokuapp.com/

Screenshots

Predictions

Installation

The Code is written in Python 3.8. If you don't have Python installed you can find it here. If you are using a lower version of Python you can upgrade using the pip package, ensuring you have the latest version of pip. 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

To deploy this app we are using Heroku Platform. You must first register on Heroku. Create your new app and give the app name and start deploying with the help of Heroku CLI command or connect your Github account. After successful connecting search your application repository and then start your deploying process. Once the app is successfully build you can visit your web app.

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

To run the app, create a procfile and shoot this command in the project directory:

web: gunicorn app:app

Documentation

The Project Documentation -

View-Documentation

Download - Project Documentation

Bug / Feature Request

If you find a bug (the website couldn't handle the query and / or gave undesired results), kindly open an issue here by including your search query and the expected result.

If you'd like to request a new function, feel free to do so by opening an issue here. Please include sample queries and their corresponding results.

Technologies Used

Team

Pratik Bambulkar