Minimal Neuron

A minimal implementation of a sigmoid neural network written entirely in C. Because it’s built from scratch with no external dependencies, it can be easily ported to embedded systems, microcontrollers, and other resource-constrained environments.

The library currently supports feedforward inference: given a pre-trained neural network definition (weights and biases), it computes the output. It has been tested against various models trained on the MNIST dataset.

Code can be downloaded HERE