Home Credit Default Risk Classification

This project focuses on Credit Default Risk evaluation using machine learning techniques. The analysis includes extensive data exploration, feature engineering, and model development to predict risk of default.

Overall models used were pretty basic with simple imputations and steps taken, so the results are not production ready. More sophisticated pipelines could be utilized to get better results. Key focus was on EDA, exploring feature reduction methods and imbalance handling.