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Convolutional Neural Networks
Plotting the model accuracy and the model loss, we understand that we can train in
only 10 iterations to achieve a similar accuracy of 99.1%:
Figure 8: Model accuracy after 10 iterations
Let us see some of the MNIST images in order to understand how good the number
99.1% is! For instance, there are many ways in which humans write a 9, one of
them being in Figure 9. The same goes for 3, 7, 4, and 5; number 1 in this figure
is so difficult to recognize that even a human would likely have trouble:
Figure 9: An example of MNIST handwritten chars
We can summarize all the progress made so far with our different models in the
following graph. Our simple net started with an accuracy of 90.71%, meaning that
about 9 handwritten characters out of 100 are not correctly recognized. Then, we
gained 8% with the deep learning architecture, reaching an accuracy of 99.2%, which
means that less than one handwritten character out of one hundred is incorrectly
recognized (see Figure 10):
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