Java Deep Learning Cookbook

How to do it...

1. Create ImagePreProcessingScaler for image normalization:

DataNormalization scaler = new ImagePreProcessingScaler(0,1);

2. Create a neural network configuration and add default hyperparameters:

MultiLayerConfiguration.Builder builder = new NeuralNetConfiguration.Builder().weightInit(WeightInit.DISTRIBUTION) .dist(new NormalDistribution(0.0, 0.01)) .activation(Activation.RELU) .updater(new Nesterovs(new StepSchedule(ScheduleType.ITERATION, 1e-2, 0.1, 100000), 0.9)) .biasUpdater(new Nesterovs(new StepSchedule(ScheduleType.ITERATION, 2e-2, 0.1, 100000), 0.9)) .gradientNormalization(GradientNormalization.RenormalizeL2PerLayer) // normalize to prevent vanishing or exploding gradients .l2(l2RegularizationParam) .list();

3. Create ...