Long Short-Term Memory (LSTM) Networks

Long Short-Term Memory (LSTM) networks are a type of artificial neural network designed to recognize patterns in sequences of data, like text, speech, or time series. They can remember information over long periods, addressing the problem of traditional networks forgetting earlier data. LSTMs achieve this through specialized components called gates that control what information to keep, forget, or pass on. This makes them especially effective for tasks that require understanding context or order, such as language translation or speech recognition, by maintaining relevant information across steps and filtering out noise or unimportant details.