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When all the #Batches# of data samples have been propagated through a Neural Network through #Iterations# such that the necessary | |
networks weights have been updated in the training process, we can consider an #Epoch#. | |
For Example - I will take #N# Picutres of Cats and Dogs, and break them into #Batches# of #B#, so that I can pass them all using #I# | |
iterations through my Neural Network model, update the weights, and consider #E# Epoch to be achieved for training the model. Therefore, | |
#E# = #B# x #I# | |
N.B. It may often appear tempting to mix Epochs and Iterations together. But let's save ourselves from that :D |
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** THE PROJECT INVOLVES CONNECTING ELB (Application LB) with your Private Subnets and re-route traffic ** | |
WHAT IS COVERED BY THIS EXERCISE | |
_____________________________________ | |
1. AWS Networking (VPC, Subnet, Security Group, NACL) | |
2. AWS High Availability (Load Balancer) | |
WHAT IS OUR ASSUMPTION | |
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