A prediction model on Real Estate Housing and rental price

This is an academic project that is required to accurately analyze the United States real estate housing dataset to identify patterns/trends and build a prediction model to forecast housing rental prices or home purchases based on the location, economic and social impact by leveraging machine learning, AI and statistical analysis to train the model and produce a reliable predictive accuracy of above 88%.

The objective of this project is to build a predictive model that will forecast housing prices based on specific influential factors. With this insight, people looking for accommodation can easily make better decisions.