文件名称:DeepLearningTutorials
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [Linux] [SHELL] [源码]
- 上传时间：
- 2014-06-07
- 文件大小：
- 5.94mb
- 下载次数：
- 0次
- 提 供 者：
- ec***
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
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介绍说明－－下载内容均来自于网络，请自行研究使用
deeplearning.net官网上的deep learning的教程，可以跟着网站上的内容一步一步的进行学习，达到快速入门的效果，是用python实现的-Deeplearning.net website deep learning tutorial, you can follow the content of the website step by step to learn, to achieve the effect of quick start, is made of python implementation
(系统自动生成,下载前可以参看下载内容)
下载文件列表
DeepLearningTutorials\code\cA.py
.....................\....\convolutional_mlp.py
.....................\....\dA.py
.....................\....\DBN.py
.....................\....\hmc\hmc.py
.....................\....\...\test_hmc.py
.....................\....\...\__init__.py
.....................\....\logistic_cg.py
.....................\....\logistic_sgd.py
.....................\....\mlp.py
.....................\....\rbm.py
.....................\....\rnnrbm.py
.....................\....\SdA.py
.....................\....\test.py
.....................\....\utils.py
.....................\data\download.sh
.....................\....\training_colorpatches_16x16_demo.mat
.....................\.oc\.templates\layout.html
.....................\...\conf.py
.....................\...\contents.txt
.....................\...\dA.txt
.....................\...\DBN.txt
.....................\...\deep.txt
.....................\...\gettingstarted.txt
.....................\...\hmc.txt
.....................\...\images\3wolfmoon.jpg
.....................\...\......\3wolfmoon_output.png
.....................\...\......\bm.png
.....................\...\......\cnn_explained.png
.....................\...\......\conv_1D_nn.png
.....................\...\......\DBN3.png
.....................\...\......\filters_at_epoch_14.png
.....................\...\......\filters_corruption_0.png
.....................\...\......\filters_corruption_30.png
.....................\...\......\markov_chain.png
.....................\...\......\mlp.png
.....................\...\......\mnist_0.png
.....................\...\......\mnist_1.png
.....................\...\......\mnist_2.png
.....................\...\......\mnist_3.png
.....................\...\......\mnist_4.png
.....................\...\......\mnist_5.png
.....................\...\......\mylenet.png
.....................\...\......\rbm.png
.....................\...\......\rnnrbm.png
.....................\...\......\rnnrbm.svg
.....................\...\......\sample1.png
.....................\...\......\sample2.png
.....................\...\......\samples.png
.....................\...\......\sparse_1D_nn.png
.....................\...\intro.txt
.....................\...\lenet.txt
.....................\...\LICENSE.txt
.....................\...\logreg.txt
.....................\...\Makefile
.....................\...\mlp.txt
.....................\...\rbm.txt
.....................\...\references.txt
.....................\...\rnnrbm.txt
.....................\...\scripts\docgen.py
.....................\...\SdA.txt
.....................\...\utilities.txt
.....................\issues_closed\2_RBM_cost_fn.txt
.....................\.......open\1_SdA_performance.txt
.....................\...........\3_RBM_scan_GPU.txt
.....................\...........\4_RBM_scan.txt
.....................\...........\5_results.txt
.....................\...........\6_benchmarking_pybrain.txt
.....................\misc\do_nightly_build
.....................\code\hmc
.....................\doc\.templates
.....................\...\images
.....................\...\scripts
.....................\code
.....................\data
.....................\doc
.....................\issues_closed
.....................\issues_open
.....................\misc
DeepLearningTutorials