California-housing-price-prediction 🏠🏘✔

Table of Contents

• Demo
• Overview
• About the dataset
• Installation
• Deployement on Heroku
• Directory Tree
• Technologies used

Demo

Link: https://housingpricepred-api.herokuapp.com/

Overview

This is a Flask web app which predicts the median value of house.

About the dataset

This dataset was derived from the 1990 U.S. census, using one row per census block group. A block group is the smallest geographical unit for which the U.S Census Bureau publishes sample data (a block group typically has a population of 600 to 3,000 people).

Installation

The Code is written in Python 3.6.10. 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

Login or signup in order to create virtual app. You can either connect your github profile or download ctl to manually deploy this project.

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

Directory Tree

├── static 
│   ├── css
|   |   ├── cssfile.css
|   |   ├── h3.jpg
├── template
│   ├── index.html
├── Procfile
├── README.md
├── app.py
├── Housing_Price_EDA.ipynb
├── Housing_Model.ipynb
├── model.pkl
├── housing.csv
├── requirements.txt

Technologies Used