(Pronounced like Mark Gaggle-Eve-Ski) 🙃
🏷 Senior Lecturer in Applied Artificial Intelligencemarek🔶gagolewski🔹com
(main)m🔹gagolewski🔶deakin🔹edu🔹au
(academic)🔍
Researcher in the Science of Data (with particular emphasis on modelling of complex phenomena and developing of usable, general purpose algorithms)
|
💻
Free (Libre) and Open Source Data Analysis Software Developer
|
🎓
Data Science, Machine Learning, and Statistical Computing Tutor & Trainer
|
Hierarchical data fusion processes involving the Möbius representation of capacities
To appear in Fuzzy Sets and Systems — a new paper written together with Gleb Beliakov and Simon James; abstract below. Read more…
Package genieclust
0.9.8 Released
A maintenance release of the R language version of
genieclust
is now available on CRAN.
Read more…
Interpretable sport team rating models based on the gradient descent algorithm
Jan Lasek and I authored a paper that will soon appear in International Journal of Forecasting, where we introduce several new (and efficient) rating models for teams (football/soccer in particular) based on the gradient descent algorithm. Read more…
ARC 2021 Discovery Project
Our (Gleb Beliakov, Simon James, and yours truly) 2021 Discovery Project Beyond black-box models: Interaction in eXplainable Artificial Intelligence has been approved by the Australian Research Council. Read more…
R Package stringi
1.5.3 Released
A new, major release of my R package
stringi
brings quite a few new features and bug fixes.
Read more…
Tutorial on stringi
A comprehensive tutorial on the stringi package is now available.
stringi
Has a New Website
I have created a new home(page) for my stringi
package,
see stringi.gagolewski.com/.
Python and R package genieclust
0.9.4
A reimplementation of my robust hierarchical clustering algorithm Genie is now available on PyPI and CRAN. Now even faster and equipped with many more features, including noise point detection. See genieclust.gagolewski.com/ for more details, documentation, benchmarks, and tutorials.