Kaggle-House-Pricing-Competition

• Gerardo Antonio Lopez Ruiz

Overview

This repo is my code for the Kaggle competition "House Prices: Advanced Regression Techniques". It is also my final project for the course: Applied Machine Learning for Finance Modelling, Columbia University, Spring 2019. In it, I manage to get to the top 8 percent.

Repository containing code of submissions regarding the Kaggle competition and paper explaining course of action and results of the project.

Dataset can be found here: https://www.kaggle.com/c/house-prices-advanced-regression-techniques/data

Important dependencies

• lightgbm
• xgboost
• mlxtend
• scipy
• sklearn
• Tested to work for Python 3.6

Contents

• Submission.ipynb: Main code for the Kaggle competition.
• Visualizations.ipynb: Nice visualizations for better understanding the data
• funcs.py: Functions for visualization
• Final Paper - AMLF.docx: Final paper for the course, explaining course of action and results of the project.

Instructions on Running

Download the entire zip folder of our repo and run the Submission.ipynb jupyter notebook file.