Housing Sector Trends Prediction Using Machine Learning

I worked on a project that uses machine learning to predict trends in the housing market. I wanted to know how well machines can analyze complex data to help real estate professionals make better decisions. This project focuses on different parts of the real estate market, including how to value properties, set prices, invest in real estate, and make policy decisions. 

I used advanced technology to analyze data from sources like Zillow, Realtor, and the National Association of Realtors (NAR). I aim to create three models that can predict market changes, and then I compare these models to see which is the most accurate. 

I also worked with DataQuotient (my sponsor company), which helped me access better tools and knowledge to improve my research. My project will help real estate professionals make better decisions by providing them with information about market trends and pricing. 

My research will be helpful in the real world and help people make better decisions, especially as the world changes after COVID-19.