Add Keras to SNN conversion example

Co-authored-by: Daniel Rasmussen <[email protected]>
nengo · Apr 1, 2020 · e5e7d1c · e5e7d1c
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diff --git a/CHANGES.rst b/CHANGES.rst
@@ -37,6 +37,9 @@ Release history
 - Added a new ``synapse`` argument to the Converter, which can be used to automatically
   add synaptic filters on the output of neural layers during the conversion process.
   (`#141`_)
+- Added a `new example <https://www.nengo.ai/nengo-dl/examples/keras-to-snn.html>`__
+  demonstrating how to use the NengoDL Converter to convert a Keras model to a spiking
+  Nengo network. (`#141`_)
 
 **Changed**
 

diff --git a/README.rst b/README.rst
@@ -60,8 +60,9 @@ adds a number of unique features, such as:
 - optimizing the parameters of a model through deep learning
   training methods (using the Keras API)
 - faster simulation speed, on both CPU and GPU
-- inserting networks defined using TensorFlow (such as
-  deep learning architectures) directly into a Nengo model
+- automatic conversion from Keras models to Nengo networks
+- inserting  TensorFlow code (individual functions or whole
+  network architectures) directly into a Nengo model
 
 **Documentation**
 

diff --git a/docs/examples.rst b/docs/examples.rst
@@ -33,6 +33,7 @@ These examples illustrate some different possible use cases for NengoDL:
 
     examples/tensorflow-models
     examples/spiking-mnist
+    examples/keras-to-snn
     examples/lmu
     examples/spa-retrieval
     examples/spa-memory