This is my approach on Kaggle’s House Prices challenge. Here you can find a complete step-by-step analysis on the issue as well as my Python code and conclusions.
Introduction Ask a home buyer to describe their dream house, and they probably won’t begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition’s dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence.
The goal of this project is to build a model that can help real estate agents predict the sales price for each house in Ames, Iowa. The data consist of 2,919 residential property sales in Ames, Iowa between 2006 and 2012 (1,460 in the training set).
For the full analysis go to my website page here.