[ctb, cph],
Daniel Falbel [ctb, cph],
Wouter Van Der Bijl [ctb, cph],
Martin Studer [ctb, cph],
Sigrid Keydana [ctb]Interface to 'Keras' <https://keras.io>, a high-level neural networks 'API'. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both 'CPU' and 'GPU' devices.
| Version: | 2.2.4 |
| Depends: | R (≥ 3.2) |
| Imports: | generics (≥ 0.0.1), reticulate (≥ 1.10), tensorflow (≥ 1.10), tfruns (≥ 1.0), magrittr, zeallot, methods, R6 |
| Suggests: | ggplot2, testthat, knitr, rmarkdown |
| Published: | 2018-11-22 |
| Author: | JJ Allaire [aut, cre],
François Chollet [aut, cph],
RStudio [ctb, cph, fnd],
Google [ctb, cph, fnd],
Yuan Tang [ctb, cph],
Daniel Falbel [ctb, cph],
Wouter Van Der Bijl [ctb, cph],
Martin Studer [ctb, cph],
Sigrid Keydana [ctb] |
| Maintainer: | JJ Allaire <jj at rstudio.com> |
| BugReports: | https://github.com/rstudio/keras/issues |
| License: | MIT + file LICENSE |
| URL: | https://keras.rstudio.com |
| NeedsCompilation: | no |
| SystemRequirements: | Keras >= 2.0 (https://keras.io) |
| Materials: | NEWS |
| In views: | HighPerformanceComputing, ModelDeployment |
| CRAN checks: | keras results |
| Reference manual: | keras.pdf |
| Vignettes: |
About Keras Layers About Keras Models Using Pre-Trained Models Keras Backend Writing Custom Keras Layers Writing Custom Keras Models Writing Custom Keras Wrappers Keras with eager execution Frequently Asked Questions Guide to the Functional API Getting Started with Keras Guide to Keras Basics Guide to the Sequential Model Training Callbacks Training Visualization Tutorial: Basic Classification Tutorial: Basic Regression Tutorial: Text Classification Tutorial: Overfitting and Underfitting Tutorial: Save and Restore Models Why Use Keras? |
| Package source: | keras_2.2.4.tar.gz |
| Windows binaries: | r-devel: keras_2.2.4.zip, r-release: keras_2.2.4.zip, r-oldrel: keras_2.2.0.zip |
| OS X binaries: | r-release: keras_2.2.4.tgz, r-oldrel: keras_2.2.4.tgz |
| Old sources: | keras archive |
| Reverse depends: | kerasformula |
| Reverse imports: | embed, ruta |
| Reverse suggests: | bamlss, cloudml, dimRed, lime, mlflow, OSTSC, parsnip, pdp, reinforcelearn, tensorflow, tfdatasets, vip |
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