how is it that for 6 pixels, performing pooling reduces it to 3 pixels ??
Doubt at 12:43 in video
Hey @ishabehera, to understand this you need to know how maxpooling layer works !
Max Pooling is a convolution process where the Kernel extracts the maximum value of the area it convolves. Max Pooling simply says to the Convolutional Neural Network that we will carry forward only that information, if that is the largest information available amplitude wise.
Max-pooling on a 4 * 4 channel using 2 * 2 kernel and a stride of 2: As we are convolving with a 2 * 2 Kernel. If we observe the first 2 * 2 set on which the kernel is focusing the channel have four values 8,3,4,7. Max-Pooling picks the maximum value from that set which is “8”.
So similarily if we have a (6,6) channel, using a (2,2) filter and a stride of 2, we get a final image of shape (3,3).
I hope you are able to understand ! 
Happy Learning 