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