stanford-deep-learning-matlab-code
代码说明：
说明： Stanford 大学的深度学习源代码，可用于模式识别和预测，比较稳定。(Stanford University's deep learning source code can be used for pattern recognition and prediction, and is relatively stable.)
文件列表：
cnnConvolve.m, 3702 , 2013-04-12
cnnExercise.m, 9289 , 2013-04-12
sparseAutoencoderLinearCost.m, 4261 , 2013-04-11
softmaxExercise.m, 4796 , 2013-04-10
checkStackedAECost.m, 1745 , 2013-04-10
softmaxCost.m, 1281 , 2013-04-10
softmaxPredict.m, 849 , 2013-04-10
sparseAutoencoderCost.m, 3865 , 2013-04-09
stlExercise.m, 5514 , 2013-04-07
feedForwardAutoencoder.m, 1304 , 2013-04-07
loadMNISTImages.m, 835 , 2013-04-03
pca_gen.m, 6377 , 2013-04-03
pca_2d.m, 3426 , 2013-04-01
trainMNIST.m, 1830 , 2013-03-11
train.m, 5796 , 2013-03-11
sparseAutoencoderCost - 副本.m, 4104 , 2013-03-11
computeNumericalGradient.m, 1115 , 2013-03-11
sampleIMAGES.m, 2120 , 2013-03-10
linearDecoderExercise.m, 5346 , 2011-07-16
displayColorNetwork.m, 1233 , 2011-05-22
stackedAEExercise.m, 7412 , 2011-05-13
softmaxTrain.m, 1891 , 2011-05-10
stackedAEPredict.m, 1296 , 2011-05-09
stackedAECost.m, 3100 , 2011-05-09
params2stack.m, 1174 , 2011-05-09
stack2params.m, 1653 , 2011-05-09
display_network.m, 2647 , 2011-04-29
sampleIMAGESRAW.m, 696 , 2011-04-29
loadMNISTLabels.m, 516 , 2011-04-25
checkNumericalGradient.m, 1982 , 2011-01-05
initializeParameters.m, 622 , 2011-01-05
cnnPool.m, 1641 , 2013-04-12
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