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 layer.
I've 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 convolution which is the convolved image.
And so what are we going to do with this pooled 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 pooling layers with many, pooled 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 of this up, we've got an input image.
We apply a convolution layer.
And let's not forget
ReLU or rectified rectified
linear units function that we apply after the convolution layer 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 I look forward to seeing you next time.
Until then, enjoy deep learning.