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| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| Parent folder | |||
| CNN.tar.gz | 2017-03-24 | 960.3 kB | |
| readme.txt | 2017-03-24 | 2.9 kB | |
| CNN_Layers.txt | 2017-03-24 | 2.9 kB | |
| 001_CNN-LSTM.jpg | 2017-03-24 | 212.6 kB | |
| 002_VGG-16.jpg | 2017-03-24 | 251.1 kB | |
| 003_RNN.jpg | 2017-03-24 | 24.3 kB | |
| 004_CNN_Layers.jpg | 2017-03-24 | 476.7 kB | |
| 005_CNN_Layers_01.jpg | 2017-03-24 | 333.3 kB | |
| 006_CNN_Layers_02.jpg | 2017-03-24 | 396.7 kB | |
| 007_One_ConvolutionalLayer.jpg | 2017-03-24 | 576.3 kB | |
| 008_Adam_CrossEntropy.jpg | 2017-03-24 | 612.8 kB | |
| 009_Adam_CrossEntropy_mean.jpg | 2017-03-24 | 570.8 kB | |
| 010_GradientDescent_CrossEntropy.jpg | 2017-03-24 | 575.4 kB | |
| 011_GradientDescent_CrossEntropy_mean.jpg | 2017-03-24 | 507.6 kB | |
| 012_LearningRate_0.0001.jpg | 2017-03-24 | 566.7 kB | |
| 013_LearningRate_0.001.jpg | 2017-03-24 | 635.8 kB | |
| 014_LearningRate_0.01.jpg | 2017-03-24 | 592.8 kB | |
| Totals: 17 Items | 7.3 MB | 0 | |
@ [CNN] => 3 layers (1 "Hidden" layers + 2 "Fully_Connected" layers)
# ======================================
# [ Input_Data:{MNIST_Image} ]
# L1 => [ Convolutional_Layer_1:{conv2d} ] -> [ Max_Pooling:{max_pool} ] -> [ Activation:{relu} ]
# L2 => [ Fully_Connected_Layer_1:{xW+b} ] -> [ Activation:{relu} ]
# L3 => [ Fully_Connected_Layer_2:{xW+b} ] -> [ Classifier:{softmax} ]
# => [ Optimizer:{Adam} ]
# => [ Output_Data:{Image_Label} ]
# ======================================
@ [CNN_0] => 3 layers (1 "Hidden" layers + 2 "Fully_Connected" layers)
# ======================================
# [ Input_Data:{MNIST_Image} ]
# L1 => [ Convolutional_Layer_1:{conv2d} ] -> [ Activation:{relu} ]
# L2 => [ Fully_Connected_Layer_1:{xW+b} ] -> [ Activation:{relu} ]
# L3 => [ Fully_Connected_Layer_2:{xW+b} ] -> [ Classifier:{softmax} ]
# => [ Optimizer:{Adam} ]
# => [ Output_Data:{Image_Label} ]
# ======================================
@ [CNN_1] => 4 layers (2 "Hidden" layers + 2 "Fully_Connected" layers)
# ======================================
# [ Input_Data:{MNIST_Image} ]
# L1 => [ Convolutional_Layer_1:{conv2d} ] -> [ Max_Pooling:{max_pool} ] -> [ Activation:{relu} ]
# L2 => [ Convolutional_Layer_2:{conv2d} ] -> [ Max_Pooling:{max_pool} ] -> [ Activation:{relu} ]
# L3 => [ Fully_Connected_Layer_1:{xW+b} ] -> [ Activation:{relu} ]
# L4 => [ Fully_Connected_Layer_2:{xW+b} ] -> [ Classifier:{softmax} ]
# => [ Optimizer:{Adam} ]
# => [ Output_Data:{Image_Label} ]
# ======================================
@ [CNN_2] => 5 layers (3 "Hidden" layers + 2 "Fully_Connected" layers)
# ======================================
# [ Input_Data:{MNIST_Image} ]
# L1 => [ Convolutional_Layer_1:{conv2d} ] -> [ Max_Pooling:{max_pool} ] -> [ Activation:{relu} ]
# L2 => [ Convolutional_Layer_2:{conv2d} ] -> [ Max_Pooling:{max_pool} ] -> [ Activation:{relu} ]
# L3 => [ Convolutional_Layer_3:{conv2d} ] -> [ Activation:{relu} ]
# L4 => [ Fully_Connected_Layer_1:{xW+b} ] -> [ Activation:{relu} ]
# L5 => [ Fully_Connected_Layer_2:{xW+b} ] -> [ Classifier:{softmax} ]
# => [ Optimizer:{Adam} ]
# => [ Output_Data:{Image_Label} ]
# ======================================
@ [CNN_3] => 5 layers (3 "Hidden" layers + 2 "Fully_Connected" layers)
# ======================================
# [ Input_Data:{MNIST_Image} ]
# L1 => [ Convolutional_Layer_1:{conv2d} ] -> [ Max_Pooling:{max_pool} ] -> [ Activation:{relu} ]
# L2 => [ Convolutional_Layer_2:{conv2d} ] -> [ Max_Pooling:{max_pool} ] -> [ Activation:{relu} ]
# L3 => [ Convolutional_Layer_3:{conv2d} ] -> [ Max_Pooling:{max_pool} ] -> [ Activation:{relu} ]
# L4 => [ Fully_Connected_Layer_1:{xW+b} ] -> [ Activation:{relu} ]
# L5 => [ Fully_Connected_Layer_2:{xW+b} ] -> [ Classifier:{softmax} ]
# => [ Optimizer:{Adam} ]
# => [ Output_Data:{Image_Label} ]
# ======================================