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
关注次数: 564
下载次数: 2
文件大小: 14.07M
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