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This is an implementation of a machine learning library in C++11

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Nunn implements an artificial intelligent framework written in modern C++11, which supports artificial networks able to learn by example and other machine learning algorithms.

The project includes demo applications, which are an excellent prototype problem for neural networks learning:
- mnist_test application lets you evaluate multiple net configurations on MNIST
- ocr_test provides a GUI to write digits that can recognize by using MNIST trained nets
- TicTacToe game
- Xor-function implementation
- And-perceptron sample
- Hopfield test

Binaries for Windows have been built by using Microsoft Visual C++ 2015, so you may need to install Visual C++ Redistributable Packages.
To do this, search for "Visual C++ Redistributable Packages for Visual Studio 2015" or use the link

nunn Web Site


  • Free open source neural network library
  • Implements perceptron, MLP, RMLP and Hopfield NNs
  • Implement Q-Learning algorithm
  • Supports fully connected networks
  • Back-propagation with MSE and Cross Entropy cost functions support
  • Easy to use and understand
  • Versatile
  • Easy to save and load entire ANNs
  • Includes non-trivial samples for Windows and Linux
  • Samples include MNIST OCR Demo and TicTacToe
  • Multi-platform, multi-architecture
  • Exports neural network diagrams that you can draw using Graphviz dot


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Intended Audience


User Interface

Win32 (MS Windows), Console/Terminal, Command-line

Programming Language




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