train a convolution neural network in matlab

main.m
imds = imageDatastore('path/to/image/folder', ...
    'IncludeSubfolders',true, 'LabelSource','foldernames');
110 chars
3 lines

main.m
layers = [
    imageInputLayer([32 32 3])
    convolution2dLayer(5,20)
    reluLayer
    maxPooling2dLayer(2,'Stride',2)
    fullyConnectedLayer(10)
    softmaxLayer
    classificationLayer];
192 chars
9 lines

main.m
opts = trainingOptions('sgdm', ...
    'MaxEpochs',20, ...
    'InitialLearnRate',0.01, ...
    'LearnRateSchedule','piecewise', ...
    'LearnRateDropFactor',0.1, ...
    'LearnRateDropPeriod',5, ...
    'MiniBatchSize',100, ...
    'ValidationData',imdsValidation, ...
    'ValidationFrequency',30, ...
    'Plots','training-progress');
339 chars
11 lines

main.m
net = trainNetwork(imds,layers,opts);
38 chars
2 lines

main.m
im = imread('image.jpg');
label = classify(net,im);
52 chars
3 lines