中文说明:深度学习工具包,内有各大牛提出深度学习方法的matlab实现,挺全的
English Description:
Deep learning toolkit, which has the matlab implementation of deep learning method proposed by each big bull, is quite completeMatlab code implementation of deep learning Toolkit
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中文说明:深度学习工具包,内有各大牛提出深度学习方法的matlab实现,挺全的
English Description:
Deep learning toolkit, which has the matlab implementation of deep learning method proposed by each big bull, is quite completeDeepLearnToolbox
................\.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
................\CNN
................\...\cnnapplygrads.m
................\...\cnnbp.m
................\...\cnnff.m
................\...\cnnnumgradcheck.m
................\...\cnnsetup.m
................\...\cnntest.m
................\...\cnntrain.m
................\CONTRIBUTING.md
................\create_readme.sh
................\data
................\....\mnist_uint8.mat
................\DBN
................\...\dbnsetup.m
................\...\dbntrain.m
................\...\dbnunfoldtonn.m
................\...\rbmdown.m
................\...\rbmtrain.m
................\...\rbmup.m
................\htm" target=_blank>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
................\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