Deep Learning with Keras

Towards a deep learning approach

While playing with handwritten digit recognition, we came to the conclusion that the closer we get to the accuracy of 99%, the more difficult it is to improve. If we want to have more improvements, we definitely need a new idea. What are we missing? Think about it.

The fundamental intuition is that, so far, we lost all the information related to the local spatiality of the images. In particular, this piece of code transforms the bitmap, representing each written digit into a flat vector where the spatial locality is gone:

#X_train is 60000 rows of 28x28 values --> reshaped in 60000 x 784X_train = X_train.reshape(60000, 784)X_test = X_test.reshape(10000, 784)

However, this is not how our brain works. Remember ...