Author: Omar Villa
Date: December 15 2018
The project proposal is to create a ML model to accurately predict Home Credit Defaults Risks in order to do this we will have to merge several tables and analyze the data using a feature engineering technique with Featuretools module and utilize chart tools as seaborn to present the data and use scikit-learn or keras to get predictions.
https://www.kaggle.com/c/home-credit-default-risk/data
Python 3.6.5
numpy
pandas
matplotlib
seaborn
visuals (included in as library)
IPython
sklearn
csv