bayesAB
Github: https://github.com/FrankPortman/bayesAB/
Website: https://frankportman.github.io/bayesAB/
bayesAB is an R package which provides a suite of functions to conduct and interpret the results of an A/B test in a Bayesian way. The package is meant to be used at all steps of the process - from choosing a prior, to interpreting final results, and then calculating lifts based on certain thresholds. bayesAB currently supports 8 common probability distributions. Currently used for inference at: Uber, Netflix, Microsoft, Blizzard, and others.
stannis
Github: https://github.com/FrankPortman/stannis/
The one true Game AI library. stannis allows you to build up both game logic and AI for one, two, … player games with an emphasis on composability. stannis also exposes benchmarking for both speed and AI performance for evolving your games and AI.
genX
Github: https://github.com/FrankPortman/genX/
Better, or at least different, generators for Python. genX is effectively a generator/iterable DSL for Python and places an emphasis on ergonomics and readability. We expose push, pull, and DAG primitives in order to specify the outputs you care about rather than dealing with loops and intermediate collections explicitly. If all you care about is getting the data, genX can be used exclusively with in-memory lists while still enjoying the code quality benefits of a stream DSL.