This is a regression project completed on the Ames Housing Dataset discussed here at: https://ww2.amstat.org/publications/jse/v19n3/decock.pdf
This project attempts to predict sale prices of homes in Ames, Iowa. In this notebook, I run some exploratory data analysis and then clean the dataset, preparing it for predictive modeling. I then engineered better features out of the data and created several regression models. Finally, I created an ensemble model and submitted it to the Kaggle Competition at:
https://www.kaggle.com/c/house-prices-advanced-regression-techniques
The Root Mean Squared Error Score that I got is: 0.12300 which is pretty accurate (0.11 would get you into the top 10).
Click on the HousingRegression.ipynb file to take a look at my analysis.
Optionally, you can open the notebook file in Jupyter Notebook on your device to run the code yourself.