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https://github.com/rstudio/keras3

R Interface to Keras
https://github.com/rstudio/keras3

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R Interface to Keras

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# R interface to Keras

![](https://s3.amazonaws.com/keras.io/img/keras-logo-2018-large-1200.png)

[![R-CMD-check](https://github.com/rstudio/keras3/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/rstudio/keras3/actions/workflows/R-CMD-check.yaml)
[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/keras3)](https://cran.r-project.org/package=keras3)
[![license](https://img.shields.io/github/license/mashape/apistatus.svg?maxAge=2592000)](https://github.com/keras-team/keras/blob/master/LICENSE)

[Keras](https://keras.io/) is a high-level neural networks API developed with a focus on enabling fast experimentation. *Being able to go from idea to result with the least possible delay is key to doing good research.* Keras has the following key features:

- Allows the same code to run on CPU or on GPU, seamlessly.

- User-friendly API which makes it easy to quickly prototype deep learning models.

- Built-in support for convolutional networks (for computer vision), recurrent networks (for sequence processing), and any combination of both.

- Supports arbitrary network architectures: multi-input or multi-output models, layer sharing, model sharing, etc. This means that Keras is appropriate for building essentially any deep learning model, from a memory network to a neural Turing machine.

See the package website at for complete documentation.