- User guide
- API reference
- Coming from Nengo to NengoDL
- Coming from TensorFlow to NengoDL
- Integrating a Keras model into a Nengo network
- Optimizing a spiking neural network
- Converting a Keras model to a spiking neural network
- Legendre Memory Units in NengoDL
- Optimizing a cognitive model
- Optimizing a cognitive model with temporal dynamics
- Additional resources
- Project information
This documentation is for a development version. Click here for the latest stable release (v3.4.0).
These examples can be found in the
<nengo-dl> is the location of the NengoDL package). The examples
are IPython/Jupyter notebooks; if you would like to run them yourself, refer to
Alternatively, you can use
to run the examples online. Note that when running on Colab you will need to add the
!pip install nengo-dl[docs] at the top of each notebook, in order to install
the necessary requirements.
We recommend starting with the two introductory tutorials. One is designed for Nengo users who want to learn about NengoDL, and the other for TensorFlow users. If you are not familiar with Nengo or TensorFlow, we would recommend beginning with the standard Nengo documentation, and then come back here!
These examples illustrate some different possible use cases for NengoDL: