An Efficient System for the Prediction of House Prices using a Neural Network Algorithm

The process of projecting house prices involves making estimations regarding how house prices will vary in the future. This is an essential aspect of the process. The price of a home is determined by a variety of different aspects, some of which include the location of the property, the overall land area, and the population of the surrounding area. In order to estimate the range of possible costs associated with purchasing a house, the Deep Learning methodology is used. In addition to this, alternative approaches are used for estimating, such as linear regression, key-value network analysis, and random forest. In the final stage of this process, the results obtained from the models utilised are evaluated and contrasted.