Welcome to the repository for my participation in the Kaggle Home Credit Default Risk competition. This project aims to build a predictive model to evaluate the credit risk of loan applicants.
Achievement: I ranked 93rd out of 3,858 participants in the competition Kaggle Profile.
This repository contains the code and documentation for my solution. The development and experimentation were primarily conducted on Google Colab. Consequently, the code is designed to run within this environment and is not structured as a fully-fledged, production-ready machine learning pipeline.
notebooks/: Contains the Jupyter notebooks used for feature engineering, feature selection, and model training.README.md: Project overview and instructions.
Due to the large amount of data involved in this competition, a Google Colab Pro subscription might be required to lift the RAM constraints.
This project is licensed under the MIT License. See the LICENSE file for details.