Very exciting news for R Data Scientists yesterday as RStudio announced that the Keras package is now available on CRAN. The package provides an R interface to Keras, a high-level neural networks API developed with a focus on enabling fast experimentation. 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.
To view the announcement post, click here
To view the dedicated RStudio page for Keras, including how to install and a example of how to build a Convolutional Neural Network for Image Recognition (using the famous MNIST dataset), click here
