深度学习训练神经网络我要分享

DeepLearnToolbox - master

深度学习 神经网络

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文件大小: 28778KB

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:

这是关于深度学习的一些很重要的代码 包括基础的深度学习 RBM等,还有用深度学习去训练神经网络等。


English Description:

This is about the depth of learning, including some very important code based on the depth of learning RBM, as well as by the depth of learning to train the neural network, etc.


代码预览

DeepLearnToolbox-master

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

.......................\....\DBN

.......................\....\...\dbnsetup.m

.......................\....\...\dbntrain.m

.......................\....\...\dbnunfoldtonn.m

.......................\....\...\rbmdown.m

.......................\....\...\rbmtrain.m

.......................\....\...\rbmup.m

.......................\....\mnist_uint8.mat

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

.......................\.....\mnist_uint8.mat

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

.......................\....\myOctaveVersion.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