keras3: R Interface to 'Keras'

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:	0.2.0
Depends:	R (≥ 4.0)
Imports:	generics (≥ 0.0.1), reticulate (≥ 1.35.0.9000), tensorflow (≥ 2.15.0.9000), tfruns (≥ 1.5.2), magrittr, zeallot, fastmap, glue, cli, rlang
Suggests:	ggplot2, testthat (≥ 2.1.0), knitr, rmarkdown, callr, tfdatasets, withr, png, jsonlite, purrr, rstudioapi, R6, jpeg
Published:	2024-04-18
Author:	Tomasz Kalinowski [aut, cph, cre], Daniel Falbel [ctb, cph], JJ Allaire [aut, cph], François Chollet [aut, cph], Posit Software, PBC [cph, fnd], Google [cph, fnd], Yuan Tang [ctb, cph], Wouter Van Der Bijl [ctb, cph], Martin Studer [ctb, cph], Sigrid Keydana [ctb]
Maintainer:	Tomasz Kalinowski <tomasz at posit.co>
BugReports:	https://github.com/rstudio/keras/issues
License:	MIT + file LICENSE
URL:	https://keras.posit.co/, https://github.com/rstudio/keras
NeedsCompilation:	no
Materials:	NEWS
CRAN checks:	keras3 results

Documentation:

Reference manual:

keras3.pdf

Vignettes:

Customizing what happens in 'fit()' with TensorFlow Multi-GPU distributed training with TensorFlow Distributed training with Keras 3 The Functional API Getting Started with Keras Introduction to Keras for engineers Introduction to Keras for Researchers Making new layers and models via subclassing The Sequential model Save, serialize, and export models Training & evaluation with the built-in methods Transfer learning & fine-tuning Understanding masking & padding Writing a training loop from scratch in TensorFlow Writing your own callbacks

Downloads:

Package source:	keras3_0.2.0.tar.gz
Windows binaries:	r-devel: keras3_0.2.0.zip, r-release: keras3_0.2.0.zip, r-oldrel: keras3_0.2.0.zip
macOS binaries:	r-release (arm64): keras3_0.2.0.tgz, r-oldrel (arm64): keras3_0.2.0.tgz, r-release (x86_64): keras3_0.2.0.tgz, r-oldrel (x86_64): keras3_0.2.0.tgz
Old sources:	keras3 archive

Reverse dependencies:

Reverse suggests:

kerastuneR, tensorflow

Linking:

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