House price prediction using deep Learning

Abstract

House price prediction is an important financial decision for individuals working in the housing market as well as potential buyers. From investment to buying a house for residence, a person investing in the housing market is interested in the potential gain. This study uses deep learning to develop a prediction model for predicting housing prices. The study is focused on the housing market in the Capital, Islamabad. The data used is the asking price from online property stores which provide a good estimate of the city housing market. The prediction model can greatly assist in prediction of future housing prices of Pakistan. The proposed approach is evaluated using the real property data and the results are encouraging and give promising directions for future work.