As part of the training on data science and artificial intelligence of the Kaggle platform, we enrolled in the competition for predicting home sales prices.
In a framework of great learning, we have been improving our model positioning it in the top-10 international.
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.
With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.