Open source. Open possibilities.

mlr3summary is an R package that provides concise, informative summaries of machine learning models built on the mlr3 ecosystem, inspired by classical generalized linear model summary outputs.

Apache Spark is a unified analytics engine designed for large-scale data processing, offering high-level APIs and an optimized engine for general computation graphs.

theme61 is an R package for creating graphs that follow the e61 Institute style. It provides functions to make aesthetic graphs and offers easy access to the Institute's colour palette, with documentation available on its package website.

Microsoft's free 12-week, 26-lesson curriculum for learning classic machine learning with Scikit-learn. Includes quizzes, hands-on projects, assignments, Python and R lessons, and multi-language translations.

CatBoost is Yandex's open-source gradient boosting library for classification, regression and ranking, with native categorical feature support, CPU/GPU training, distributed training via Apache Spark, and APIs for Python, R, Java and C++.

LightGBM is a fast, distributed, and high-performance gradient boosting framework based on decision tree algorithms, optimized for efficiency and large-scale data.

A personal repository of articles and experiments covering statistics, machine learning, economics, and mathematics, focusing on clear, practical explanations of complex topics.