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

Ranked Top 14% 630/4625 on Kaggle as of March 4, 2020.

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

Python Version : Python 3.7.4

• /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.

  • Final Models.zip contains models that we tried and fine tuning parameters.
  • final_model.joblib is the final tuned and fitted model to be loaded. Productionized model.

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

• /Submissions - submission files to Kaggle.