I know concept of Epochs, batch size and iteration.
Total_data = 6400
Batch_size = 64
Iteration = 100
In this, basically we are taking in 64 data points to computer memory and calculate and at each iteration we get weight updated. so after 100 iterations, we will fulfill one epoch.
My question is, after one epoch, we are using again the same 6400 data. How is it different from the first epoch in terms of learning? does the model select different 64 data point than first epoch in second epoch and try to learn? how does it internally really work?
I wish I can get some clear answers.
Thank you people in advance.