登录
首页 » WINDOWS » SparkMLlibDeepLearn-master

SparkMLlibDeepLearn-master

于 2020-11-26 发布 文件大小:293KB
0 162
下载积分: 1 下载次数: 2

代码说明:

  深度信念网络,非常好的代码,有具体的事例(Deep belief network, very good code, there are specific examples)

文件列表:

SparkMLlibDeepLearn-master
SparkMLlibDeepLearn-master\.cache
SparkMLlibDeepLearn-master\.classpath
SparkMLlibDeepLearn-master\.project
SparkMLlibDeepLearn-master\.settings
SparkMLlibDeepLearn-master\.settings\org.eclipse.jdt.core.prefs
SparkMLlibDeepLearn-master\LICENSE
SparkMLlibDeepLearn-master\README.md
SparkMLlibDeepLearn-master\bin
SparkMLlibDeepLearn-master\bin\CAE
SparkMLlibDeepLearn-master\bin\CAE\CAE$.class
SparkMLlibDeepLearn-master\bin\CAE\CAE.class
SparkMLlibDeepLearn-master\bin\CNN
SparkMLlibDeepLearn-master\bin\CNN\CNN$.class
SparkMLlibDeepLearn-master\bin\CNN\CNN.class
SparkMLlibDeepLearn-master\bin\DBN
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$16.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$DBNtrain$1$$anonfun$apply$mcVI$sp$1.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$DBNtrain$1.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$DBNtrain$2$$anonfun$2.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$DBNtrain$2$$anonfun$apply$mcVI$sp$2$$anonfun$apply$mcVI$sp$3.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$DBNtrain$2$$anonfun$apply$mcVI$sp$2.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$DBNtrain$2.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$InitialW$1.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$Initialb$1.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$Initialc$1.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$InitialvW$1.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$Initialvb$1.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$Initialvc$1.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$1.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$10.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$11.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$12.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$13.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$14.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$15.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$3.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$4.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$5.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$6.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$7.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$8.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4$$anonfun$9.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1$$anonfun$apply$mcVI$sp$4.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$$anonfun$RBMtrain$1.class
SparkMLlibDeepLearn-master\bin\DBN\DBN$.class
SparkMLlibDeepLearn-master\bin\DBN\DBN.class
SparkMLlibDeepLearn-master\bin\DBN\DBNConfig$.class
SparkMLlibDeepLearn-master\bin\DBN\DBNConfig.class
SparkMLlibDeepLearn-master\bin\DBN\DBNModel$$anonfun$dbnunfoldtonn$1.class
SparkMLlibDeepLearn-master\bin\DBN\DBNModel.class
SparkMLlibDeepLearn-master\bin\DBN\DBNweight$.class
SparkMLlibDeepLearn-master\bin\DBN\DBNweight.class
SparkMLlibDeepLearn-master\bin\NN
SparkMLlibDeepLearn-master\bin\NN\NNConfig$.class
SparkMLlibDeepLearn-master\bin\NN\NNConfig.class
SparkMLlibDeepLearn-master\bin\NN\NNLabel$.class
SparkMLlibDeepLearn-master\bin\NN\NNLabel.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$1.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$11$$anonfun$12.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$11.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$13.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$14$$anonfun$5.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$14.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$15$$anonfun$apply$1.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$15.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$16.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$17.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$2.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$21.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$22$$anonfun$apply$2$$anonfun$6.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$22$$anonfun$apply$2$$anonfun$7.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$22$$anonfun$apply$2.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$22$$anonfun$apply$3.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$22.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$23.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$24$$anonfun$apply$4.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$24.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$25$$anonfun$apply$5.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$25.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$26.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$27.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$28.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$3.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$ActiveP$1$$anonfun$18.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$ActiveP$1$$anonfun$19.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$ActiveP$1$$anonfun$20.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$ActiveP$1.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$InitialActiveP$1.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$InitialWeight$1.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$InitialWeightV$1.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$NNapplygrads$1.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$NNbp$1.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$NNbp$2.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$NNtrain$1$$anonfun$4.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$NNtrain$1$$anonfun$apply$mcVI$sp$1$$anonfun$10.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$NNtrain$1$$anonfun$apply$mcVI$sp$1$$anonfun$6$$anonfun$apply$2$$anonfun$2.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$NNtrain$1$$anonfun$apply$mcVI$sp$1$$anonfun$6$$anonfun$apply$2.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$NNtrain$1$$anonfun$apply$mcVI$sp$1$$anonfun$7.class
SparkMLlibDeepLearn-master\bin\NN\NeuralNet$$anonfun$NNtrain$1$$anonfun$apply$mcVI$sp$1$$anonfun$8.class

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • source
    Image Binirization with Adaptive Threshold. Very goo when used with morphology
    2011-05-24 14:55:28下载
    积分:1
  • FFT_Analysis
    mathlab code of ofdm based system
    2012-05-02 02:40:06下载
    积分:1
  • MATLAB-commands
    这是matlab的命令大全,初学者可以在多次尝试后快速进入专业状态,熟练者可以用更简洁的程序实现功能(Matlab command Daquan, beginners can quickly after several attempts to enter the professional status, the experts were more concise program functions)
    2012-12-03 08:09:03下载
    积分:1
  • wangfei
    北京理工大学王菲教授讲述的大学物理及力学和热学的内容(Beijing Institute of Technology Professor Wang Fei told a university physics and mechanical and thermal content of)
    2010-03-11 09:49:39下载
    积分:1
  • MatlabofSINS
    说明:  SINS仿真Matlab程序,对初学者还算全,应该有点用处,虽然比较简单,也省些前期编写的麻烦, 希望能花更多时间研究些专门的有用处的东西。如大家有需要还可增加一些其它内容(SINS Matlab simulation program, for beginners fairly full, should be of some use, although relatively simple, but also save the trouble of some pre-prepared, I hope to spend more time to study some specific useful things. If you need to also increase the number of other elements)
    2021-04-17 21:38:52下载
    积分:1
  • WIRELESS-COMMUNICATIONS-WITH-MATLAB
    The aim of this book is to help readers understand the concepts, techniques, and equations appearing in the field of MIMO-OFDM communication, while simulating various techniques used in MIMO-OFDM systems.
    2013-03-12 23:02:25下载
    积分:1
  • BISPECDX
    双谱对角谱,用语双谱对角谱11/2维信号的提取(Bispectrum of the angular spectrum, bispectrum terms of the angular spectrum of 11/2-dimensional signal extraction)
    2007-09-27 08:21:21下载
    积分:1
  • mbd_gui
    多通道盲卷积实现图像超分辨率重建 效果不错 (Blind convolution multiple images super-resolution)
    2010-07-30 10:43:09下载
    积分:1
  • fir
    用matlab来实现fir滤波器,包括矩形窗、汉宁窗、汉明窗、等波纹法!(Using matlab to achieve the fir filter, including the rectangular window, Hanning window, Hamming window, such as corrugated Act!)
    2008-05-12 19:48:13下载
    积分:1
  • Matlab_Image_Processing
    这是一个MATLAB图像处理程序,可以实现对图像的预处理(This is a MATLAB image-processing program, you can achieve the right image preprocessing)
    2010-01-05 09:52:19下载
    积分:1
  • 696516资源总数
  • 106432会员总数
  • 11今日下载