broom
Convert statistical analysis objects from R into tidy formattidymodels
Easily install and load the tidymodels packagesinfer
An R package for tidyverse-friendly statistical inferencecorrr
Explore correlations in Rparsnip
A tidy unified interface to modelsTMwR
Code and content for "Tidy Modeling with R"recipes
Pipeable steps for feature engineering and data preprocessing to prepare for modelingyardstick
Tidy methods for measuring model performancersample
Classes and functions to create and summarize resampling objectsstacks
An R package for tidy stacked ensemble modelingtidypredict
Run predictions inside the databasetune
Tools for tidy parameter tuningworkflows
Modeling Workflowstextrecipes
Extra recipes for Text Processingembed
Extra recipes for predictor embeddingsthemis
Extra recipes steps for dealing with unbalanced databutcher
Reduce the size of model objects saved to diskcensored
Parsnip wrappers for survival modelsdials
Tools for creating tuning parameter valuesprobably
Tools for post-processing class probability estimatestidyclust
A tidy unified interface to clustering modelstidyposterior
Bayesian comparisons of models using resampled statisticstidymodels.org-legacy
Legacy Source of tidymodels.orgaml-training
The most recent version of the Applied Machine Learning noteshardhat
Construct Modeling Packagesworkflowsets
Create a collection of modeling workflowsusemodels
Boilerplate Code for tidymodelsmodeldb
Run models inside a database using Rworkshops
Website and materials for tidymodels workshopsmultilevelmod
Parsnip wrappers for mixed-level and hierarchical modelsspatialsample
Create and summarize spatial resampling objects 🗺learntidymodels
Learn tidymodels with interactive learnr primersbrulee
High-Level Modeling Functions with 'torch'finetune
Additional functions for model tuningshinymodels
applicable
Quantify extrapolation of new samples given a training setmodel-implementation-principles
recommendations for creating R modeling packagesbonsai
parsnip wrappers for tree-based modelsrules
parsnip extension for rule-based modelsplanning
Documents to plan and discuss future developmentdiscrim
Wrappers for discriminant analysis and naive Bayes models for use with the parsnip packagebaguette
parsnip Model Functions for Baggingmodeldata
Data Sets Used by tidymodels Packagespoissonreg
parsnip wrappers for Poisson regressionagua
Create and evaluate models using 'tidymodels' and 'h2o'extratests
Integration and other testing for tidymodelstidymodels.org
Source of tidymodels.orgplsmod
Model Wrappers for Projection Methodscloudstart
RStudio Cloud ☁️ resources to accompany tidymodels.orgdesirability2
Desirability Functions for Multiparameter Optimizationmodeldatatoo
More Data Sets Useful for Modeling Examples.github
GitHub contributing guidelines for tidymodels packagesmodelenv
Provide Tools to Register Models for use in Tidymodelssurvivalauc
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