A neural networks API. It can run on top of Tensorflow, CNTK or Theano. This library allows you to prototype easy and fast, supports both convolutional networks and recurrent networks and runs seamlessly on CPU and GPU.
|Developed by||François Chollet|
|Latest stable version||Keras 2|
|Used by||Amazon, DataBricks, Google|
In 2017, Google's TensorFlow team decided to support Keras in TensorFlow's core library. Chollet explained that Keras was conceived to be an interface rather than an end-to-end machine-learning framework. It presents a higher-level, more intuitive set of abstractions that make it easy to configure neural networks regardless of the backend scientific computing library. Microsoft has been working to add a CNTK backend to Keras as well and the functionality is currently in beta release with CNTK v2.0
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