Przemyslaw Biecek
Author of 37 CRAN packages
Przemyslaw Biecek has completed over 37 packages! The dedication here is off the charts—clearly a coding superstar! 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