Definition of Epoch

Epoch: Epoch is a term used in data science to denote a specific point in time. It may be used, for example, to indicate the beginning of a period when data is collected or the end of a period when data is analyzed.

When is an Epoch used?

An epoch is a term often used in the context of deep learning and machine learning. It is a point in time where a section of data has been completely processed by an algorithm during training, or when a new set of weights have been applied to a neural network after the completion of one cycle through the training dataset. An epoch is usually used to measure the progress made by an algorithm while it is being trained on a dataset over multiple cycles. During each epoch, each data point in the training set will be iterated through once, meaning that each piece of data will go through one complete cycle before the next data point begins. Generally speaking, increasing the number of epochs can help improve model accuracy but too many epochs can lead to overfitting, where a model has memorized training data instead of learning from it.

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