matlab代码实现深度学习工具包我要分享

Matlab code implementation of deep learning Toolkit

deep-learning deeplearntoolbox 深度学习 深度学习-matlab already22t

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文件大小: 14.07M

代码分类: 智能算法

开发平台: matlab

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代码描述

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 complete


代码预览

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

................\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