cppNet is small and easy to use library for neural networks. It is based on Eigen, C++ template library for linear algebra.

The library supports:

• Fully connected layers
• Convolution layers
• Max pooling layers
• Dropout
• SGD - stochastic gradient decent
• Loading and storing trained network
• Live graphs (Python)

Here are the steps to install cppNet.

1. First thing you need are the repository files, get them by typing git clone https://github.com/soCzech/cppNet.git into terminal.
2. Run the download.sh script. It downloads MNIST dataset (used in the example files) and Eigen library which is needed for the vector operations.
3. You are ready to rock. You can try it by typing make [all] and running fc or cn demo (see example usage in docs.pdf).

To find out how to build your own network, see test/*test.cpp files and documentation in docs directory. For technical details, see the source files.