👉 Preemphasis, also known as prior knowledge or prior knowledge, refers to a method of training in which information from previous epochs is used to inform the current model's predictions. This technique allows for better generalization and reduces overfitting. In machine learning, it can be applied by preprocessing data such that each piece of input is "preprocessed" into a form where it can be fed into the network without needing to know what came before. For example, in image recognition tasks, one might use
