Convolutional Neural Network (CNN) with maxpooling
By : Jesús Pérez
Date : March 29 2020, 07:55 AM
it fixes the issue I've implemented a simple CNN program with Python that can machine learn on the MNIST data set. I've implemented 3 layers: , [updated] For forward propagation for max pooling use : code :
#forward
activationPrevious = np.copy(activation)
skimage.measure.block_reduce(activation, block_size=(1, 1, 2, 2), func=np.max)
maxs = activations.repeat(2, axis=2).repeat(2, axis=3)
mask = np.equal(activationPrevious, maxs).astype(int)
#backward
delta = delta.repeat(2, axis=2).repeat(2, axis=3)
delta = np.multiply(delta, mask)

Can I view convolutional neural network as fully connected neural network
By : Mani
Date : March 29 2020, 07:55 AM
I hope this helps you . In short, yes. You can see CNN as (among other possible interpretations): neural net with convolutional operation and gradients computed directly for it (typical approach) code :
X1
X2 h1 = X1v11+X2v21+X3v31
X3 h2 = X1v12+X2v22+X3v32
/patch 1  shared fully connected net\
Input splittingpatch 2  shared fully connected netmerging
. .
. .
\patch K  shared fully connected net/

How to run a convolutional neural network on new data
By : Keepup
Date : March 29 2020, 07:55 AM
To fix the issue you can do You can not use mnist_classifier.evaluate without a y paramater, because you have nothing to evaluate. Instead, use y = mnist_classifier.predict(x=x) to get results, and have a look at them yourself to know if they are correct or not.

Convolutional Neural Network Loss
By : Repelsteeltje
Date : March 29 2020, 07:55 AM
should help you out No. Tensorflow loss functions typically accept tensors as input and also outputs a tensor. So np.array() wouldn't work. In case of CNNs, you'd generally come across loss functions like crossentropy, softmax corssentropy, sigmoid crossentropy etc. These are already inbuilt in tf.losses module. So you can use them directly. The loss function that you're trying to apply looks like a Meansquared loss. This is built in tf.losses as well. tf.losses.mean_squared_error.

Groups in Convolutional Neural Network / CNN
By : user2522597
Date : March 29 2020, 07:55 AM
hop of those help? Perhaps you're looking up an older version of the docs. 1.0.1 documentation for nn.Conv2d expands on this.

