'Keras Tuner' <https://keras-team.github.io/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.
Version: | 0.1.0.1 |
Imports: | reticulate, tensorflow, rstudioapi, plotly, data.table, RJSONIO, rjson, tidyjson, dplyr |
Suggests: | knitr, rmarkdown, covr, stats, testthat, keras, tfdatasets, purrr |
Published: | 2020-03-20 |
Author: | Turgut Abdullayev [aut, cre], Google Inc. [cph] |
Maintainer: | Turgut Abdullayev <turqut.a.314 at gmail.com> |
BugReports: | https://github.com/henry090/kerastuneR/issues |
License: | Apache License 2.0 |
URL: | https://github.com/henry090/kerastuneR |
NeedsCompilation: | no |
SystemRequirements: | TensorFlow >= 2.0 (https://www.tensorflow.org/) |
Materials: | README |
CRAN checks: | kerastuneR results |
Reference manual: | kerastuneR.pdf |
Vignettes: |
Bayesian Optimization HyperModel subclass R interface to Keras Tuner MNIST hypertuning |
Package source: | kerastuneR_0.1.0.1.tar.gz |
Windows binaries: | r-prerelease: kerastuneR_0.1.0.1.zip, r-release: kerastuneR_0.1.0.1.zip, r-oldrel: kerastuneR_0.1.0.1.zip |
macOS binaries: | r-prerelease: kerastuneR_0.1.0.1.tgz, r-release: kerastuneR_0.1.0.1.tgz, r-oldrel: not available |
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