In this project we created a model to predict the per squarefoot housing prices from the NYC rolling sales data and the pluto dataset, taking into consideration the number of covid cases per day.
We compared the results from an LSTM time series model versus ARIMA, which one gives a more accurate prediction of per square foot prices in NYC real estate market.
The process is documented in the 'CS700B Final Report.pdf' included in this repository.