Open source. Open possibilities.

XGBoost is an optimized distributed gradient boosting library that is efficient, flexible, and portable. It implements machine learning algorithms under the Gradient Boosting framework and provides parallel tree boosting (GBDT, GBM) to solve data science problems accurately and quickly. It runs on major distributed environments and supports multiple languages.

An open-source UFC fight prediction project: Elo ratings, a gradient-boosted ensemble and a multi-task neural network blended into one calibrated scorer, evaluated by expanding-window walk-forward over 2018-2026, with a Streamlit matchup explorer and a weekly self-updating data pipeline.