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## How do I calculate the partial derivative with respect to \$x\$?

I am trying to implement CNN using python Numpy. I searched so much, but all I found was for one filter with one channel for Convolution. Suppose we have an X as Image with this shape: (N_Height, N_Width, N_Channel) = (5,5,3) And Let’s say I have 16 filters with this shape: (F_Height, F_Width, N_Channel) = […]

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## How do I calculate the partial derivative with respect to \$x\$?

I am trying to implement CNN using python Numpy. I searched so much, but all I found was for one filter with one channel for Convolution. Suppose we have an X as Image with this shape: (N_Height, N_Width, N_Channel) = (5,5,3) And Let’s say I have 16 filters with this shape: (F_Height, F_Width, N_Channel) = […]

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## gradient respect to Input in CNN Backpropagation

I am trying to implement CNN using python Numpy. I searched so much, but all I found was for one filter with one channel for Convolution. Suppose we have an X as Image with this shape: (N_Height, N_Width, N_Channel) = (5,5,3) And Let’s say I have 16 filters with this shape: (F_Height, F_Width, N_Channel) = […]