Hi. This is almost a theory question. Sorry if this forum is not an appropriate place to ask.
Are there any advantages to shuffle a dataset to train Neural Networks when a batch size is 1?
Since normal networks (no recurrence inside) don’t have abilities to take a past (or future) input data into account, I have a feeling that shuffling the dataset does not make any difference as long as the batch size is 1.
Is this correct?