Hello.
Welcome back.
And this lesson we are going to examine that convolution or neural network with a pool layer.
In this arrangement over here we see a combination of a convolution or layer an appallingly denoted
as Layer 1 and that a combination of a convolution layer and appalling layer denoted as Layer 2.
Also we see three f C's.
Over here we have FC FC FC FC stands for firmly connected layer like we mentioned earlier we use the
polling data to reduce the size of the inputs in order to speed up the computation.
A formal connected layout is a simple layer perception.
This is like the normal neural network.
Examples we saw earlier in this convolution on neural network arrangement is similar to the one we saw
earlier.
The two differences over here is the introduction of the pooling layer and the two extra fully connected
layers and the soft max function and the fully connected layer is your standard normal neural network
right.
If you have any questions regarding this just send me a message.
So that's one of the for this lesson and I shall see you in the next lesson.