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DeepLearnToolbox-master

于 2020-10-22 发布
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下载积分: 1 下载次数: 1

代码说明:

说明:  这是关于深度学习工具箱的材料,特别适合初学者,可以帮助你们快速学习深度学习(This is the material for a deep learning toolbox, especially for beginners, to help you learn deep learning quickly)

文件列表:

DeepLearnToolbox-master, 0 , 2020-02-23
DeepLearnToolbox-master\.travis.yml, 249 , 2015-12-01
DeepLearnToolbox-master\CAE, 0 , 2020-02-23
DeepLearnToolbox-master\CAE\caeapplygrads.m, 1219 , 2015-12-01
DeepLearnToolbox-master\CAE\caebbp.m, 917 , 2015-12-01
DeepLearnToolbox-master\CAE\caebp.m, 1011 , 2015-12-01
DeepLearnToolbox-master\CAE\caedown.m, 259 , 2015-12-01
DeepLearnToolbox-master\CAE\caeexamples.m, 754 , 2015-12-01
DeepLearnToolbox-master\CAE\caenumgradcheck.m, 3618 , 2015-12-01
DeepLearnToolbox-master\CAE\caesdlm.m, 845 , 2015-12-01
DeepLearnToolbox-master\CAE\caetrain.m, 1148 , 2015-12-01
DeepLearnToolbox-master\CAE\caeup.m, 489 , 2015-12-01
DeepLearnToolbox-master\CAE\max3d.m, 173 , 2015-12-01
DeepLearnToolbox-master\CAE\scaesetup.m, 1937 , 2015-12-01
DeepLearnToolbox-master\CAE\scaetrain.m, 270 , 2015-12-01
DeepLearnToolbox-master\CNN, 0 , 2020-03-01
DeepLearnToolbox-master\CNN\cnnapplygrads.m, 575 , 2015-12-01
DeepLearnToolbox-master\CNN\cnnbp.m, 4958 , 2020-03-01
DeepLearnToolbox-master\CNN\cnnff.m, 5465 , 2020-02-29
DeepLearnToolbox-master\CNN\cnnnumgradcheck.m, 3430 , 2015-12-01
DeepLearnToolbox-master\CNN\cnnsetup.m, 9173 , 2020-02-27
DeepLearnToolbox-master\CNN\cnntest.m, 193 , 2015-12-01
DeepLearnToolbox-master\CNN\cnntrain.m, 3065 , 2020-02-27
DeepLearnToolbox-master\CONTRIBUTING.md, 544 , 2015-12-01
DeepLearnToolbox-master\create_readme.sh, 744 , 2015-12-01
DeepLearnToolbox-master\data, 0 , 2020-02-23
DeepLearnToolbox-master\data\mnist_uint8.mat, 14735220 , 2015-12-01
DeepLearnToolbox-master\DBN, 0 , 2020-02-23
DeepLearnToolbox-master\DBN\dbnsetup.m, 557 , 2015-12-01
DeepLearnToolbox-master\DBN\dbntrain.m, 232 , 2015-12-01
DeepLearnToolbox-master\DBN\dbnunfoldtonn.m, 425 , 2015-12-01
DeepLearnToolbox-master\DBN\rbmdown.m, 90 , 2015-12-01
DeepLearnToolbox-master\DBN\rbmtrain.m, 1401 , 2015-12-01
DeepLearnToolbox-master\DBN\rbmup.m, 89 , 2015-12-01
DeepLearnToolbox-master\LICENSE, 1313 , 2015-12-01
DeepLearnToolbox-master\NN, 0 , 2020-02-23
DeepLearnToolbox-master\NN\nnapplygrads.m, 628 , 2015-12-01
DeepLearnToolbox-master\NN\nnbp.m, 1638 , 2015-12-01
DeepLearnToolbox-master\NN\nnchecknumgrad.m, 704 , 2015-12-01
DeepLearnToolbox-master\NN\nneval.m, 811 , 2015-12-01
DeepLearnToolbox-master\NN\nnff.m, 1849 , 2015-12-01
DeepLearnToolbox-master\NN\nnpredict.m, 192 , 2015-12-01
DeepLearnToolbox-master\NN\nnsetup.m, 1844 , 2015-12-01
DeepLearnToolbox-master\NN\nntest.m, 184 , 2015-12-01
DeepLearnToolbox-master\NN\nntrain.m, 2414 , 2015-12-01
DeepLearnToolbox-master\NN\nnupdatefigures.m, 1858 , 2015-12-01
DeepLearnToolbox-master\README.md, 8861 , 2015-12-01
DeepLearnToolbox-master\README_header.md, 2244 , 2015-12-01
DeepLearnToolbox-master\REFS.md, 950 , 2015-12-01
DeepLearnToolbox-master\SAE, 0 , 2020-02-23
DeepLearnToolbox-master\SAE\saesetup.m, 132 , 2015-12-01
DeepLearnToolbox-master\SAE\saetrain.m, 308 , 2015-12-01
DeepLearnToolbox-master\tests, 0 , 2020-02-27
DeepLearnToolbox-master\tests\runalltests.m, 277 , 2020-08-16
DeepLearnToolbox-master\tests\test_cnn_gradients_are_numerically_correct.m, 552 , 2015-12-01
DeepLearnToolbox-master\tests\test_example_CNN.m, 1977 , 2020-02-27
DeepLearnToolbox-master\tests\test_example_DBN.m, 1031 , 2015-12-01
DeepLearnToolbox-master\tests\test_example_NN.m, 3247 , 2015-12-01
DeepLearnToolbox-master\tests\test_example_SAE.m, 934 , 2015-12-01
DeepLearnToolbox-master\tests\test_nn_gradients_are_numerically_correct.m, 749 , 2015-12-01
DeepLearnToolbox-master\util, 0 , 2020-02-23
DeepLearnToolbox-master\util\allcomb.m, 2618 , 2015-12-01
DeepLearnToolbox-master\util\expand.m, 1958 , 2015-12-01
DeepLearnToolbox-master\util\flicker.m, 208 , 2015-12-01
DeepLearnToolbox-master\util\flipall.m, 80 , 2015-12-01
DeepLearnToolbox-master\util\fliplrf.m, 543 , 2015-12-01
DeepLearnToolbox-master\util\flipudf.m, 576 , 2015-12-01
DeepLearnToolbox-master\util\im2patches.m, 313 , 2015-12-01
DeepLearnToolbox-master\util\isOctave.m, 108 , 2015-12-01
DeepLearnToolbox-master\util\makeLMfilters.m, 1895 , 2015-12-01
DeepLearnToolbox-master\util\myOctaveVersion.m, 169 , 2015-12-01
DeepLearnToolbox-master\util\normalize.m, 97 , 2015-12-01
DeepLearnToolbox-master\util\patches2im.m, 242 , 2015-12-01
DeepLearnToolbox-master\util\randcorr.m, 283 , 2015-12-01
DeepLearnToolbox-master\util\randp.m, 2083 , 2015-12-01
DeepLearnToolbox-master\util\rnd.m, 49 , 2015-12-01
DeepLearnToolbox-master\util\sigm.m, 48 , 2015-12-01
DeepLearnToolbox-master\util\sigmrnd.m, 126 , 2015-12-01
DeepLearnToolbox-master\util\softmax.m, 256 , 2015-12-01
DeepLearnToolbox-master\util\tanh_opt.m, 54 , 2015-12-01
DeepLearnToolbox-master\util\visualize.m, 1072 , 2015-12-01
DeepLearnToolbox-master\util\whiten.m, 183 , 2015-12-01
DeepLearnToolbox-master\util\zscore.m, 137 , 2015-12-01

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  • 一个好的通迅录
    一个好的通迅录程序-a good communications process.
    2023-08-23 14:40:04下载
    积分:1
  • 1)用户界面模块负责响应用户的键盘鼠标输入设置服务器的各个参数,显示服务器的工作状态以及错误提示,为用户提供标准的Windows界面。 2)帐户管理模块负责设置...
    1)用户界面模块负责响应用户的键盘鼠标输入设置服务器的各个参数,显示服务器的工作状态以及错误提示,为用户提供标准的Windows界面。 2)帐户管理模块负责设置用户的访问权限,用户登陆后的根目录,并提供对用户透明的虚拟目录服务。同时还为别的模块提供查询文件(夹)的权限,查找本地文件是否存在等服务, 3)连接监听与FTP命令处理模块负责监听客户端的连接,并负责关闭阻塞的连接,释放每个连接占用的资源。此模块为FTP协议的核心,它具体负责FTP命令的解析与实现。 4)客户数据传输模块负责具体的与客户端的数据传输,包括文件的上传,下载,传输文件目录列表等。-1) user interface module for the user response to keyboard and mouse input settings server parameters, display server status and the error messages to users with standard Windows interface. 2) module responsible for the account management of user access rights, user landing after the root directory, and provide transparent to users of virtual directory services. Also for the other modules provide access to files (folders), the authority that you document the existence of local services, 3) connect with the FTP eavesdropping order processing module is responsible for monitoring client connectivity, and is responsible for the closure of the connecting block, the release of each link the resource. This FTP protocol
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    积分:1
  • 对话音的全双工传输
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    积分:1
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    积分:1
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    积分:1
  • ceshi
    实现本地程序从远程服务器下载文件。保存到本地。同时,具备断点续传的功能。可以在下载一部分的情况下,再次下载从断点处继续下载。(Implement a local program to download files a remote server. Saved locally. At the same time, with the functions of HTTP. You can download a part in the case, once again download continue downloading the breakpoint.)
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  • 1101
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    2014-02-16 18:46:29下载
    积分:1
  • HTTP下载序。类似IE中的下载界面
    HTTP下载程序。类似IE中的下载界面-HTTP downloading procedure. In similar IE downloading contact surface
    2023-03-13 22:10:03下载
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