Description: Deep learning toolkit, there are major cattle raised deep learning method matlab realize, quite wide
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DeepLearnToolbox\.travis.yml
................\CAE\caeapplygrads.m
................\...\caebbp.m
................\...\caebp.m
................\...\caedown.m
................\...\caeexamples.m
................\...\caenumgradcheck.m
................\...\caesdlm.m
................\...\caetrain.m
................\...\caeup.m
................\...\max3d.m
................\...\scaesetup.m
................\...\scaetrain.m
................\.NN\cnnapplygrads.m
................\...\cnnbp.m
................\...\cnnff.m
................\...\cnnnumgradcheck.m
................\...\cnnsetup.m
................\...\cnntest.m
................\...\cnntrain.m
................\CONTRIBUTING.md
................\DBN\dbnsetup.m
................\...\dbntrain.m
................\...\dbnunfoldtonn.m
................\...\rbmdown.m
................\...\rbmtrain.m
................\...\rbmup.m
................\LICENSE
................\NN\nnapplygrads.m
................\..\nnbp.m
................\..\nnchecknumgrad.m
................\..\nneval.m
................\..\nnff.m
................\..\nnpredict.m
................\..\nnsetup.m
................\..\nntest.m
................\..\nntrain.m
................\..\nnupdatefigures.m
................\README.md
................\README_header.md
................\REFS.md
................\SAE\saesetup.m
................\...\saetrain.m
................\create_readme.sh
................\data\mnist_uint8.mat
................\tests\runalltests.m
................\.....\test_cnn_gradients_are_numerically_correct.m
................\.....\test_example_CNN.m
................\.....\test_example_DBN.m
................\.....\test_example_NN.m
................\.....\test_example_SAE.m
................\.....\test_nn_gradients_are_numerically_correct.m
................\util\allcomb.m
................\....\expand.m
................\....\flicker.m
................\....\flipall.m
................\....\fliplrf.m
................\....\flipudf.m
................\....\im2patches.m
................\....\isOctave.m
................\....\makeLMfilters.m
................\....\normalize.m
................\....\patches2im.m
................\....\randcorr.m
................\....\randp.m
................\....\rnd.m
................\....\sigm.m
................\....\sigmrnd.m
................\....\softmax.m
................\....\tanh_opt.m
................\....\visualize.m
................\....\whiten.m
................\....\zscore.m
................\CAE
................\CNN
................\DBN
................\NN
................\SAE
................\data
................\tests
................\util
DeepLearnToolbox