For our machine learning project, we participated in a Kaggle competition to predict house prices with 79 explanatory variables using various regression techniques (ridge, lasso, elastic net, gradient boosting, support vector regression). Here, we outline our process of exploratory data analysis, missingness imputation, transformation, standardization, feature engineering, and finally model development.