Intro to Python again after a long time using a Kaggle Dataset to predict House Prices in Iowa. I took part in "10 Days of Code" event where people from all programming levels come together and code for ten consecutive days.

My main goal was not to go into a very detailed data cleaning and preprocessing, (that probably would improve the accuracy of my predictions) but to built various linear and ensemble models, compare them and select the best of them based on it's out of sample performance.

There are a lot of things that could be improved, but given the nature of the "10 Days of code event" I decided to emphasize on the modeling part of the process.