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文件名称:stanford-deep-learning-matlab-code
介绍说明－－下载内容来自于网络，使用问题请自行百度
stanford大学deep learning在线课程课后练习代码，我自己写的，可以参考一下。-Excercise of deep learning online course from http://deeplearning.stanford.edu/wiki. It is written by myself, aiming to help other students who is confused in the course.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
cnnConvolve.m
cnnExercise.m
sparseAutoencoderLinearCost.m
softmaxExercise.m
checkStackedAECost.m
softmaxCost.m
softmaxPredict.m
sparseAutoencoderCost.m
stlExercise.m
feedForwardAutoencoder.m
loadMNISTImages.m
pca_gen.m
pca_2d.m
trainMNIST.m
train.m
sparseAutoencoderCost - 副本.m
computeNumericalGradient.m
sampleIMAGES.m
linearDecoderExercise.m
displayColorNetwork.m
stackedAEExercise.m
softmaxTrain.m
stackedAEPredict.m
stackedAECost.m
params2stack.m
stack2params.m
display_network.m
sampleIMAGESRAW.m
loadMNISTLabels.m
checkNumericalGradient.m
initializeParameters.m
cnnPool.m
cnnExercise.m
sparseAutoencoderLinearCost.m
softmaxExercise.m
checkStackedAECost.m
softmaxCost.m
softmaxPredict.m
sparseAutoencoderCost.m
stlExercise.m
feedForwardAutoencoder.m
loadMNISTImages.m
pca_gen.m
pca_2d.m
trainMNIST.m
train.m
sparseAutoencoderCost - 副本.m
computeNumericalGradient.m
sampleIMAGES.m
linearDecoderExercise.m
displayColorNetwork.m
stackedAEExercise.m
softmaxTrain.m
stackedAEPredict.m
stackedAECost.m
params2stack.m
stack2params.m
display_network.m
sampleIMAGESRAW.m
loadMNISTLabels.m
checkNumericalGradient.m
initializeParameters.m
cnnPool.m
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