RealTime2
Introduction
Recently, housing prices in Toronto have been growing with volatility. Prices jumped by 30% in the 2021 calendar year, and over 25% just between July 2021 and January 2022. With such unpredictability in the market, brokerages and realtors have resorted to giving “hunch” price estimates, while clients are worrying about overpaying for their dream home. Machine learning offers a promising alternative for housing price estimates - one which is data-driven, accurate, and constantly up-to-date.
This is the premise of our project, RealTime, which was awarded the Best Project Award by UTMIST in the 2021-2022 year. This year, we are looking to achieve a MAPE of ~7.5% by making improvements to our database and network architecture, which will bring us on par with leading companies in the industry and recent publications.
We are looking for 2-3 developers with experience in python, and an understanding of machine learning concepts primarily dealing with supervised learning to join us. Email sepehr.hosseini@mail.utoronto.ca if you’re interested!
