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broom
Convert statistical analysis objects from R into tidy formattidymodels
Easily install and load the tidymodels packagesinfer
An R package for tidyverse-friendly statistical inferenceparsnip
A tidy unified interface to modelscorrr
Explore correlations in RTMwR
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 modelingtune
Tools for tidy parameter tuningtidypredict
Run predictions inside the databaseworkflows
Modeling Workflowstextrecipes
Extra recipes for Text Processingthemis
Extra recipes steps for dealing with unbalanced dataembed
Extra recipes for predictor embeddingsbutcher
Reduce the size of model objects saved to diskcensored
Parsnip wrappers for survival modelsprobably
Tools for post-processing class probability estimatesdials
Tools for creating tuning parameter valuestidyclust
A tidy unified interface to clustering modelstidyposterior
Bayesian comparisons of models using resampled statisticshardhat
Construct Modeling Packagesaml-training
The most recent version of the Applied Machine Learning notestidymodels.org-legacy
Legacy Source of tidymodels.orgworkshops
Website and materials for tidymodels workshopsworkflowsets
Create a collection of modeling workflowsusemodels
Boilerplate Code for tidymodelsmodeldb
Run models inside a database using Rmultilevelmod
Parsnip wrappers for mixed-level and hierarchical modelsspatialsample
Create and summarize spatial resampling objects πΊlearntidymodels
Learn tidymodels with interactive learnr primersbrulee
High-Level Modeling Functions with 'torch'finetune
Additional functions for model tuningbonsai
parsnip wrappers for tree-based modelsshinymodels
applicable
Quantify extrapolation of new samples given a training setmodel-implementation-principles
recommendations for creating R modeling packagesrules
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 βοΈ resources to accompany tidymodels.orgorbital
Turn Tidymodels Workflows Into Series of Equationsdesirability2
Desirability Functions for Multiparameter Optimizationmodeldatatoo
More Data Sets Useful for Modeling Examples.github
GitHub contributing guidelines for tidymodels packagestailor
Sandbox for a postprocessor object.survivalauc
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