n*m
to 1*nm
1-D Array fig, ax = plt.subplots(nrows=2,ncols=2,sharex='all',sharey='all')
ax = ax.flatten()
for i in range(4):
img = image[i].reshape(28, 28)
ax[i].imshow(img, cmap='Greys', interpolation='nearest')
# ax[i] is available
flatten()
fig, ax = plt.subplots(nrows=2,ncols=2,sharex='all',sharey='all')
for i in range(4):
img = image[i].reshape(28, 28)
ax[0, 0].imshow(img, cmap='Greys', interpolation='nearest')
ax[0, 1].imshow(img, cmap='Greys', interpolation='nearest')
ax[1, 0].imshow(img, cmap='Greys', interpolation='nearest')
ax[1, 1].imshow(img, cmap='Greys', interpolation='nearest')
# ax[i] is unavailable
Flatten
, converting matrice to vectors.Fully Connected Layers
.CNN
-> Pooling
-> CNN
-> Pooling
...-> Flatten
-> Fully Connected Layers
-> Softmax
-> Probabilities
<<: [Matplotlib] - Introduction to Charts and Plots
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