With 79 explanatory variables describing almost every aspect of residential homes in Ames, Iowa, this competition challenges the data science community to predict the final price of each home.
train.csv: 1460 houses with 81 attributes, including the labels (sale prices)
test.csv: 1459 houses with 80 attributes
data_description.txt: full description of each column of the csv files
Feature engineering and a solution using Kernel Ridge regression are shown in Kernel_Ridge.ipynb.
NumPyPandasscikit-learnscipyseabornmatplotlibXGBoost