Hello and welcome back to the course on deep learning I hope you're tracking along with these intuition
tutorials just fine and that you had a chance to play around with everything we've learned so far and
today we're talking about flattening and the good news is that this is a very simple step and this tutorial
is going to be very quick and then we'll be able to move on to the next interesting things.
All right so we so far we've got the pulled Lehre pulled feature map and that is after we apply the
convolution operation to our image and then we apply pooling to the result of the collision which the
involved image.
And so what are we going to do if this puled feature map.
Well we're going to take it and we're going to flatten it into a column.
So basically just take the numbers row by row and put them into this one long column.
And the reason for that is because we want to later input this into an artificial neural network for
further processing.
So this is what it looks like when you have many pooling layers or you have the pulling levers with
many puled feature maps and then you flatten them so you put them into this one long column sequentially
one after the other and you get one huge vector of inputs for an artificial neural network.
And so to sum all this up we've got an input image.
We apply a convolutional there and let's not forget the reals or rectified rectified linear units function
that we apply after the revolution there as well.
And then we apply pooling and then we flatten everything into a long vector which will be our input
layer for an artificial neural network and exactly how that works we'll find out in the next tutorial.
Hope you enjoyed today's session and looked forward to you next time.
Until then enjoy deep learning.