Real Estate

Machine Learning carries excellent promises for real estate. There are many risks and opportunities related to analytics and machine learning in real estate. Predictive models can help with property valuation, for instance. They can forecast the future and predict the market demand depending upon the listing situation and features. But regression models can also predict house prices based on its location, age of the structure, living spaces, number of rooms, energy efficiency, and the quality of life in the area.
AI, Machine Learning & Real Estate
Artificial Intelligence trained on big data can classify images to assist in the search of comparable properties. Data Analytics can investigate past deals. Therefore, these statistical models can help property owners, real estate agents, and tenants understand parameters for matching offers. Predictive models can also forecast the expected time of closing a home in a market, taking into account factors like market cycles and season. Neural networks can also be of service in identifying credit risks before payment incidents occur on mortgages.
Real Estate Valuation

Real estate valuation

For 40% of Americans, buying a new home is the most stressful event in their life, even when they eventually find the perfect house. How can the buyer determine the ‘right’ price...