Keras is a high-level neural networks API, developed with a focus on enabling fast experimentation. Keras has the following key features:
Maintainer: Tomasz Kalinowski tomasz@posit.co [contributor, copyright holder]
Authors:
JJ Allaire [copyright holder]
François Chollet [copyright holder]
Other contributors:
Daniel Falbel daniel@rstudio.com [contributor, copyright holder]
RStudio [contributor, copyright holder, funder]
Google [contributor, copyright holder, funder]
Yuan Tang terrytangyuan@gmail.com (ORCID) [contributor, copyright holder]
Wouter Van Der Bijl [contributor, copyright holder]
Martin Studer [contributor, copyright holder]
Sigrid Keydana [contributor]
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.
Is capable of running on top of multiple back-ends including TensorFlow, CNTK, or Theano.
See the package website at https://tensorflow.rstudio.com for complete documentation.
Useful links: