Abstract:
"Since the beginning of human civilization, shelter has been one of the basic needs of humans. So, when the civilization developed through time, the need for dwellings was growing just as quickly. In today’s world, with constant increase of population all around the globe and influx of populace into large metropolises and cities, lack of bare lands to build properties and the limitations in the real estate resources, demand for properties in the housing market is one of the areas that has an ever-increasing exigency.
Every person or every family has dealt with the process of buying or selling a real estate property. It used to be quite a hassle with the modes of advertising and communications that used to exist. Even today, with the level of marketing and advertising, finding a property or finding a buyer for your property is no easy task. This research paper discusses the possibility of using Advanced Regression methods and multilayer perception concepts of Machine Learning to predict accurate selling prices to sellers who are willing to sell their properties. It also discusses the idea of providing a method for sellers to post advertisements directly and cutting out the middle men or “brokers”. Initial literature review has revealed that even though machine learning techniques have been utilized in projects similar to this, the usage of multilayer perception and advanced regression techniques have not been explored thoroughly. The goal of this research was to mend that gap and use multilayer perception techniques to predict most accurately. Also as a customer retention technique, the sellers will have the option to post the advertisements of their properties on the website and sellers could compare the prices and features and choose the most suitable property that matches their requirement.
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