Final project for CS 221 (Spring 2018) by Jesus Cervantes, Alex Kim, and Alexandre Bucquet.

This project aims to predict house prices from the Ames Housing dataset using various machine learning techniques. For a complete report, please view our final report and poster.

Some techniques we used were used were gradient boosting, weight regularization, and k-means clustering. All mechanisms were coded from scratch using numpy and pandas, allowing us to gain a deeper intuition. For more details on our techniques and their results, please view our final report.