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R Interface to Keras
Customer Churn Shiny Application
An R package for tidyverse-friendly statistical inference
Construct Modeling Packages
Additional functions for model tuning
Extra recipes for predictor embeddings
Wrappers for discriminant analysis and naive Bayes models for use with the parsnip package
Tools for creating tuning parameter values
Explore correlations in R
R interface to Google Cloud Machine Learning Engine
Parsnip wrappers for survival models
Reduce the size of model objects saved to disk
Prepare objects for serialization with a consistent interface
High-Level Modeling Functions with ’torch'
Convert statistical analysis objects from R into tidy format
parsnip wrappers for tree-based models
Quantify extrapolation of new samples given a training set
The most recent version of the Applied Machine Learning notes
Repository for the RStudio AI Blog (formerly: TensorFlow for R Blog)
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