Shiny-server on Docker for ARM (arm64) with Python Support. Has a lot of common tools used by data scientists in both R and Python pre-installed.

Quantile Regression Forests compatible with scikit-learn.

Fast SHAP value computation for interpreting tree-based models

The Tidymodels Extension for Time Series Boosting Models

Public repository for NBA EPAA analysis

Extensive and Tidy NCAA Men's College Basketball Data

Open-Sourcing Our Hiring Process for Data Scientist and Data Engineer Positions in Hockey

Instance-based uncertainty estimation for gradient-boosted regression trees

Codes for tweets from @NbaInRstats

Time Series Forecasting with LightGBM

Loose collection of unrelated yet highly useful tools, models, functions etc. for all sorts of data science needs.

Pen and paper exercises in machine learning

Distributional Gradient Boosting Machines

Feature selection library in python

Probabilistic Gradient Boosting Machines

Python package for drawing regulation playing surfaces for several sports

Project holding various data for the worldfootballR R package

A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.

A simple yet comprehensive web scraper for kenpom.com.

Multi-target Random Forest implementation that can mix both classification and regression tasks

R package for pro Halo data

Fit interpretable models. Explain blackbox machine learning.

Editing machine learning models to reflect human knowledge and values

LRBoost is a scikit-learn compatible approach to performing linear residual based stacking/boosting.

tools for computing advanced nba stats

XGBoost + Optuna