Ames House Price Prediction

Goal of first machine learning model project

• Data exploration
• Feature selection and engineering
• Predict house price using various methods, including Random Forest, Gradient Boosting, Light GBM, XGBM, a stacked meta learner, and a weighted-average meta learner.

Repo organization

• code: Jupyter notebooks
• data: all files are downloaded from Kaggle
• output: saved output