- Gerardo Antonio Lopez Ruiz
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
- lightgbm
- xgboost
- mlxtend
- scipy
- sklearn
- Tested to work for Python 3.6
- 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.
Download the entire zip folder of our repo and run the Submission.ipynb
jupyter notebook file.