Overview

This application allows users to predict real estate prices of properties in the Greater Toronto Area. It uses a dataset of over 1500 listed properties in the region. I used Jupyter Notebooks to conduct all the machine learning processes. I used Sci-kit learn to build a linear regression model that does the prediction, and used Numpy in unison with Pandas to perform data cleaning, feature engineering, and outlier detection. I also used Matplotlib for data visualization. I incorporated a Python Flask server to create an API with the ML model, and to communicate 'POST' and 'GET' requests to the frontend, which was made using basic HTML, JavaScript, and CSS. I then deployed the whole application using the help of Nginx to an AWS EC2 instance.