Multipurpose modular deep learning neural network with OpenGl visualization.

Watch the neural net learn. Synaptic weight visualization with OpenGL allows the user to watch
the neural net train.

GLFW 3, OPENGL, GLEW.

Usage: deepnet /[mode] /[# data] /[size] /[neurons.brain] /[visualize]

mode: /[t/a] either a 't' to specify training mode or 'a' to analyze.
/# data: number of data for training or analysis.
size: the length of the largest data (including solution flag and length header if training).
neurons.brain: file to dump neurons to after training or load neurons for analysis.
visualize: [0 to # data] opengl visualization of training (slower). 0 to disable.

Make targets: spec, line, and tri are available.

spec - Screen clear after each render. Just shows current synapse values.
line - OpenGL lines.
tri - OpenGL triangles.

Primative coordinate system: ( x: synapse0, y: synapse1, z: synapse2 )

Each colored trail is one layer0 -> layer1 synaptic weight.

Each dot is one layer0 -> layer1 synaptic weight.

Connect multiple synaptic weights with lines.

Connect multiple synaptic weights with triangles.