A small selection of my open-source projects that can be found on my github page:
distfit is for probability density function fitting of univariate distributions of non-censored data.
findpeaks is Python package for the detection of peaks and valleys in 1 dimensional vectors and (2D) images.
bnlearn is for learning the graphical structure of Bayesian networks in Python.
hgboost is to minimize the function for xgboost, catboost or lightboost over a hyper-parameter space by using cross-validation, and evaluating the results on an independent validation set. hgboost can be applied for classification and regression tasks.
classeval is to evaluate the models performance for any kind of two-class or multi-class model.
hnet stands for graphical Hypergeometric NEtworks, which is a method where associations across variables are tested for significance by statistical inference.