1. Regularized_regressions.ipynb compares three different regularized regression: Lasso, Ridge, Elastic Net. It was used for the Kaggle House Prices competition. It receives an log rmse score of .12094. It is ranked top 25% (beat 75%) in April 2019.
2. Used ensemble model that combine bagging gradient boost, lasso and ridge to achieve my current best ranking.
3. Keras-Neural-Network-Regression.ipynb is my first attempt of building a neural network with Keras. This NN regression receives an log rmse score of .15725