r nnet tutorial

The compilation process takes nnet and computationrequest as inputs and outputs nnetcomputation. The computationrequest contains a representation of the output index of the request, the available input index.Create a calculation diagramMore about Computationgraphcomputationgraph maps cindexes to cindex_ids and maps cindex_ids to cindexes.The computationgraph class is defined as follows: struct Computationgraph {The mapping of c

here Description: http://deeplearning.net/software/theano/library/tensor/nnet/conv.html# theano.tensor.nnet.conv.conv2d #激活函数用tanh #你还可以在model. Add (Activation (' tanh ') with dropout tips: model.add (Dropout (0.5 ) Model.add (convolution2d (4, 5, 5, border_mode= ' valid ', input_shape= (1,28,28))) Model.add (Activation (' Tanh ')) # The second convolution layer, 8 convolution cores, each volume kernel size 3*3. 4 represents the number of feature gra

'); h1 = NNETFW (net_rbm1,x);%RBM training Gets the network parameters of the second hidden layer, The input is the output of the first hidden layer rbm2 = RBM ([400,200]), rbm2 = Checkrbmtrain (@rbmtrain1, rbm2,h1,50,0.1), net_rbm2 = Rbm2nnet (rbm2, ' up '); H2 = NNETFW (NET_RBM2,H1);%RBM training Gets the network parameters of the third hidden layer, the output of the second hidden layer RBM3 = RBM ([200,100]); rbm3 = Checkrbmtrain (@rbmtrain1, RBM3,H2, 50,0.1); net_rbm3 = Rbm2nnet (rbm3, ' u

Platform: Windows 7 32-bitDatabase: SQL Server 2008Python 2.7 pymssql modulesModule installation instructions for database and Python omittedThe following test code is posted: Simple connection Database Testing1 Import 2 4 conn = Pymssql.connect (host="localhost", user=" SA ", password=" ********", database="master" "UTF8", login_timeout = 5) 5A test run may appear:conn = Pymssql.connect (host= "localhost", user= "sa", password= "sa", database= "Master", CharSet = "UTF8", Login_timeout = 5