Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

Batcher	Runs an epoch for a single set of already-loaded data
ConvolutionalMaker	Use to create a convolutional layer
FullyConnectedMaker	Use to create a fully-connected layer
GenericLoader	Use to load data from file, given the path to the images file
InputLayerMaker	Use to create an InputLayer, which can be added to a NeuralNet
Layer	A single layer within the neural net
NetdefToNet	Add layers to a NeuralNet object, based on a netdef-string
NetLearner	Runs multiple learning epochs using Batcher objects
NetLearnerOnDemand	Learns multiple epochs, for data that wont fit in memory
NeuralNet	NeuralNet: main container class for network layers
NormalizationLayerMaker	Use to add a NormalizationLayer to a NeuralNet
OnDemandBatcher	Learns an entire epoch of training, for data that wont fit in memory
PoolingMaker	Use to create a Max-Pooling layer
RandomPatchesMaker	Use to create a RandomPatches Layer
RandomTranslationsMaker	Use to create a RandomTranslations Layer
WeightsPersister	Use to read/write weights from a NeuralNet