Provides a consistent interface to the 'Keras' Deep Learning Library directly from within R. 'Keras' provides specifications for describing dense neural networks, convolution neural networks (CNN) and recurrent neural networks (RNN) running on top of either 'TensorFlow' or 'Theano'. Type conversions between Python and R are automatically handled correctly, even when the default choices would otherwise lead to errors. Includes complete R documentation and many working examples.
Version: | 0.8.1 |
Depends: | R (≥ 2.10) |
Imports: | reticulate (≥ 0.7) |
Suggests: | knitr, rmarkdown, testthat, covr |
Published: | 2022-08-17 |
Author: | Taylor Arnold [aut, cre], Andrie de Vries [aut] |
Maintainer: | Taylor Arnold <tarnold2 at richmond.edu> |
BugReports: | https://github.com/statsmaths/kerasR/issues |
License: | LGPL-2 |
URL: | https://github.com/statsmaths/kerasR |
NeedsCompilation: | no |
SystemRequirements: | Python (>= 2.7); keras <https://keras.io/> (>= 2.0.1) |
Materials: | NEWS |
CRAN checks: | kerasR results |
Reference manual: | kerasR.pdf |
Vignettes: |
R Interface to the Keras Deep Learning Library |
Package source: | kerasR_0.8.1.tar.gz |
Windows binaries: | r-devel: kerasR_0.8.1.zip, r-release: kerasR_0.8.1.zip, r-oldrel: kerasR_0.8.1.zip |
macOS binaries: | r-release (arm64): kerasR_0.8.1.tgz, r-oldrel (arm64): kerasR_0.8.1.tgz, r-release (x86_64): kerasR_0.8.1.tgz, r-oldrel (x86_64): kerasR_0.8.1.tgz |
Old sources: | kerasR archive |
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