Multi-layer perceptron a.k.a Neural Network library.

A basic neural network framework from scratch in C++ without any 3rd-party dependencies.

The goal is to create a model powerful enough to solve the handwritten digit classification problem with reasonable training time and test accuracy.

Progress:

• Neural network with configurable architecture
• Gradient descent using backpropagation
• Gradient descent with momentum
• Hardware acceleration (SIMD, multi-threading)
• Dataset processing (one-hot encoding/decoding, shuffling, batching, ...)
• Data and model serialization
• Metrics for model evaluation
• Output layer softmax activation
• Categorical cross-entropy loss function
• Better weight initialization
• Adam optimizer

Copy the mlp.h header file to your working directory.

Look at the examples and the source code if you want to learn more.

You will need a C++ compiler that supports C++11.

./build.sh

To build with g++:

CXX=g++ ./build.sh

This project is licensed under the MIT License.