%% example from Matlab help for training neural network on PC
digitDatasetPath = fullfile(matlabroot,'toolbox','nnet', ...
    'nndemos','nndatasets','DigitDataset');
imds = imageDatastore(digitDatasetPath, ...
    'IncludeSubfolders',true, ...
    'LabelSource','foldernames');

figure
numImages = 10000;
perm = randperm(numImages,20);
for i = 1:20
    subplot(4,5,i);
    imshow(imds.Files{perm(i)});
    drawnow;
end


numTrainingFiles = 750;
[imdsTrain,imdsTest] = splitEachLabel(imds,numTrainingFiles,'randomize');



layers = [...
    imageInputLayer([28 28 1])
    convolution2dLayer(5,20)
    reluLayer
    maxPooling2dLayer(2,'Stride',2)
    fullyConnectedLayer(10)
    softmaxLayer
    classificationLayer];



options = trainingOptions('sgdm', ...
    'MaxEpochs',10,...
    'InitialLearnRate',0.5e-3,...
    'LearnRateSchedule','piecewise',...
    'LearnRateDropFactor',0.1,...
    'LearnRateDropPeriod',4);
[net,info] = trainNetwork(imdsTrain,layers,options);