This repository focuses on the development of a linear regression model to predict rental costs in Manhattan using data obtained from StreetEasy. The dataset can be accessed on Kaggle or dowloaded directly from this repository.
The model was developed with Scikit-Learn's LinearRegression. Features were selected based on correlation with rent and absence of multicollinearity. The square footage of the rental unit was the single best predictor of rent, with an R-squared value of .74:
For additional questions regarding this analysis, please contact me at fisheravonlea@gmail.com or via my LinkedIn profile.