From 1e14d4e66879e1e98752a1f9ea38b98bd786a995 Mon Sep 17 00:00:00 2001
From: Vincent Templier <47155758+vtemplier@users.noreply.github.com>
Date: Wed, 18 May 2022 14:20:18 +0200
Subject: [PATCH] Add N2D2

---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index c19f6d3..e5d4c6e 100644
--- a/README.md
+++ b/README.md
@@ -221,6 +221,7 @@ Further resources:
 * [MLDB](https://mldb.ai) - The Machine Learning Database is a database designed for machine learning. Send it commands over a RESTful API to store data, explore it using SQL, then train machine learning models and expose them as APIs.
 * [mlpack](https://www.mlpack.org/) - A scalable C++ machine learning library.
 * [MXNet](https://github.com/apache/incubator-mxnet) - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Go, Javascript and more.
+* [N2D2](https://github.com/CEA-LIST/N2D2) - CEA-List's CAD framework for designing and simulating Deep Neural Network, and building full DNN-based applications on embedded platforms
 * [ParaMonte](https://github.com/cdslaborg/paramonte) - A general-purpose library with C/C++ interface for Bayesian data analysis and visualization via serial/parallel Monte Carlo and MCMC simulations. Documentation can be found [here](https://www.cdslab.org/paramonte/).
 * [proNet-core](https://github.com/cnclabs/proNet-core) - A general-purpose network embedding framework: pair-wise representations optimization Network Edit.
 * [PyCaret](https://github.com/pycaret/pycaret) - An open-source, low-code machine learning library in Python that automates machine learning workflows.