Epoch in Machine Learning is used to indicate the count of passes in a given training dataset where the Machine Learning algorithm has done its job. Generally, when there is a huge chunk of data, it is grouped into several batches. Here, each of these batches goes through the given model, and this process is referred to as iteration. Now, if the batch size comprises the complete training dataset, then the count of iterations is the same as that of epochs.
In case there is more than one batch, d*e=i*b is the formula used, wherein ‘d’ is the dataset, ‘e’ is the number of epochs, ‘i’ is the number of iterations, and ‘b’ is the batch size.
