Interface to 'TensorFlow' Estimators

Interface to 'TensorFlow' Estimators <>, a high-level API that provides implementations of many different model types including linear models and deep neural networks.

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The tfestimators package is an R interface to TensorFlow Estimators, a high-level API that provides:

  • Implementations of many different model types including linear models and deep neural networks. More models are coming soon such as state saving recurrent neural networks, dynamic recurrent neural networks, support vector machines, random forest, KMeans clustering, etc.

  • A flexible framework for defining arbitrary new model types as custom estimators.

  • Standalone deployment of models (no R runtime required) in a wide variety of environments.

  • An Experiment API that provides distributed training and hyperparameter tuning for both canned and custom estimators.

For documentation on using tfestimators, see the package website at


tfestimators 1.9.1

  • Fixes for rlang 0.3 compatibility (#156, #159).

tfestimators 1.9.0

  • Add input checking to exported functions (#150).

  • input_fn.list() no longer performs type coercion on numpy arrays.

  • Added boosted_trees_regressors() and boosted_trees_classifier() (#146).

Reference manual

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1.9.2 by Tomasz Kalinowski, a month ago

Report a bug at

Browse source code at

Authors: JJ Allaire [aut] , Yuan Tang [aut] , Kevin Ushey [aut] , Kevin Kuo [aut] , Tomasz Kalinowski [cre] , Daniel Falbel [ctb, cph] , RStudio [cph, fnd] , Google Inc. [cph]

Documentation:   PDF Manual  

Task views: High-Performance and Parallel Computing with R, Model Deployment with R

Apache License 2.0 license

Imports forge, magrittr, progress, reticulate, rlang, tensorflow, tfruns, tidyselect, utils, purrr, tibble, tidyr

Suggests ggplot2, modelr, testthat, rmarkdown, knitr

System requirements: TensorFlow (

Suggested by tfdatasets, tfhub.

See at CRAN