Kaggle Competition House Prices: Advanced Regression Techniques (link: https://www.kaggle.com/c/house-prices-advanced-regression-techniques)

Using machine learning techniques to predict house prices based on various house features.

• /EDA - data processing, imputation and feature engineering

• /Model - for modeling with ridge, lasso, elastic net, gradient boosting, catBoost, XGBoost, LightGBM, and stacked regressor models. Model visualization is also included in this folder.

• /Data - contains raw and processed data for this project.

• /Submissions - submission files to Kaggle.