A data analysis of the U.S. housing market using Zillow Research and Consumer Price Index (CPI) to compare housing costs and cost of living across multiple U.S. cities.

To address the impact of rising house prices on the economy, we built a machine learning model resistant to market trends. We experimented with Random Forest and Linear Regression models, employing sophisticated imputation methods like median state price replacement, KNN imputation, and forward/backward filling to minimize errors.

Using Zillow datasets to investigate the current state of the housing market to make data-driven decisions on single-family property investments

Simple house price forecasting sample written in Scala using Zillow historical data.