kerastuneR: Interface to 'Keras Tuner'

'Keras Tuner' <> is a hypertuning framework made for humans. It aims at making the life of AI practitioners, hypertuner algorithm creators and model designers as simple as possible by providing them with a clean and easy to use API for hypertuning. 'Keras Tuner' makes moving from a base model to a hypertuned one quick and easy by only requiring you to change a few lines of code.

Imports: reticulate, tensorflow, rstudioapi, plotly, data.table, RJSONIO, rjson, tidyjson, dplyr, echarts4r, crayon, keras, magick
Suggests: knitr, tfdatasets, testthat, purrr, rmarkdown
Published: 2020-10-04
Author: Turgut Abdullayev [aut, cre], Google Inc. [cph]
Maintainer: Turgut Abdullayev <turqut.a.314 at>
License: Apache License 2.0
NeedsCompilation: no
SystemRequirements: TensorFlow >= 2.0 (
Materials: README
CRAN checks: kerastuneR results


Reference manual: kerastuneR.pdf
Vignettes: Bayesian Optimization
HyperModel subclass
Introduction to kerastuneR
MNIST hypertuning
KerasTuner best practices
Package source: kerastuneR_0.1.0.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): kerastuneR_0.1.0.3.tgz, r-release (x86_64): kerastuneR_0.1.0.3.tgz, r-oldrel: kerastuneR_0.1.0.3.tgz
Old sources: kerastuneR archive


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