Implemented various machine learning models such as linear regression, lasso and ridge regression, and random forests to predict prices of Pittsburgh houses based on historical housing data containing detailed property information.

Implemented various machine learning models such as linear regression, lasso and ridge regression, and random forests to predict prices of Pittsburgh houses based on historical housing data containing detailed property information.

Manipulated data from the FiveThirtyEight package in R to produce a similar graph found on the company's website. Utilized the dplyr and ggplot2 packages in R to wrangle and display the necessary data.