Keras 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.

• Is capable of running on top of multiple back-ends including TensorFlow, CNTK, or Theano.

See the package website at https://keras.rstudio.com for complete documentation.