Przemyslaw Biecek
Author of 37 CRAN packages
Przemyslaw Biecek has worked on 37 packages, which is nothing short of amazing. Who needs sleep when you've got code to write? Przemyslaw Biecek worked with over 60 collaborators. That's a huge group of developers—almost like a coding festival!
37 Packages
- BetaBitMini Games from Adventures of Beta and Bit
- DALEXmoDel Agnostic Language for Exploration and eXplanation
- DALEXtraExtension for 'DALEX' Package
- EIXExplain Interactions in 'XGBoost'
- PBImiscA Set of Datasets Used in My Classes or in the Book 'Modele Liniowe i Mieszane w R, Wraz z Przykladami w Analizie Danych'
- PogromcyDanychDataCrunchers (PogromcyDanych) is the Massive Online Open Course that Brings R and Statistics to the People
- PrzewodnikDatasets and Functions Used in the Book 'Przewodnik po Pakiecie R'
- PvSTATEMReading, Quality Control and Preprocessing of MBA (Multiplex Bead Assay) Data
- SmarterPolandTools for Accessing Various Datasets Developed by the Foundation SmarterPoland.pl
- archivist.githubTools for Archiving, Managing and Sharing R Objects via GitHub
- archivistTools for Storing, Restoring and Searching for R Objects
- arenarArena for the Exploration and Comparison of any ML Models
- auditorModel Audit - Verification, Validation, and Error Analysis
- bgmmGaussian Mixture Modeling Algorithms and the Belief-Based Mixture Modeling
- breakDownModel Agnostic Explainers for Individual Predictions
- ceterisParibusCeteris Paribus Profiles
- corrgrapherExplore Correlations Between Variables in a Machine Learning Model
- coxphSGDStochastic Gradient Descent log-Likelihood Estimation in Cox Proportional Hazards Model
- ddstData Driven Smooth Tests
- drifterConcept Drift and Concept Shift Detection for Predictive Models
- eurostatTools for Eurostat Open Data
- hstatsInteraction Statistics
- iBreakDownModel Agnostic Instance Level Variable Attributions
- ingredientsEffects and Importances of Model Ingredients
- intsvyInternational Assessment Data Manager
- kernelshapKernel SHAP
- localModelLIME-Based Explanations with Interpretable Inputs Based on Ceteris Paribus Profiles
- modelStudioInteractive Studio for Explanatory Model Analysis
- rSAFESurrogate-Assisted Feature Extraction
- randomForestExplainerExplaining and Visualizing Random Forests in Terms of Variable Importance
- sejmRPAn Information About Deputies and Votings in Polish Diet from Seventh to Eighth Term of Office
- shapperWrapper of Python Library 'shap'
- survexExplainable Machine Learning in Survival Analysis
- survminerDrawing Survival Curves using 'ggplot2'
- treeshapCompute SHAP Values for Your Tree-Based Models Using the 'TreeSHAP' Algorithm
- triplotExplaining Correlated Features in Machine Learning Models
- vivoVariable Importance via Oscillations
Team
- Witold Chodor
- Katarzyna Fak
- Tomasz Zoltak
- Foundation SmarterPoland.pl
- Szymon Maksymiuk
- Hubert Baniecki
- Anna Kozak
- Ewelina Karbowiak
- Jakub Grzywaczewski
- Nuno Sepulveda
- Tymoteusz Kwiecinski
- Mateusz Nizwantowski
- Marcin Kosinski
- Piotr Piątyszek
- Michal Burdukiewicz
- Alicja Gosiewska
- Tomasz Mikołajczyk
- Ewa Szczurek
- Aleksandra Grudziaz
- Pawel Morgen
- Teresa Ledwina
- Paul Rougieux
- Leo Lahti
- Markus Kainu
- Pyry Kantanen
- Daniel Antal
- Oliver Reiter
- Enrico Spinielli
- Francois Briatte
- Reto Stauffer
- Janne Huovari
- Diego Hernangomez
- Joona Lehtomaki
- Anna Vasylytsya
- Michael Mayer
- Adam Izdebski
- Dariusz Komosinski
- Daniel Caro
- David Watson
- Krystian Igras
- Harel Lustiger
- Mateusz Staniak
- Willy Tadema
- Piotr Piatyszek
- Anna Gierlak
- Yue Jiang
- Aleksandra Paluszynska
- Piotr Smuda
- Tomasz Mikolajczyk
- Lorenz A. Kapsner
- Mikołaj Spytek
- Mateusz Krzyziński
- Sophie Langbein
- Alboukadel Kassambara
- Scheipl Fabian
- Mateusz Krzyzinski
- Konrad Komisarczyk
- Pawel Kozminski
- Mikolaj Spytek
- Katarzyna Pekala