LSTM networks use gating mechanisms to control what information is stored, forgotten, and exposed over time. They were widely used for language, speech, and time-series tasks before transformer architectures became dominant in many areas. It matters because model performance depends on how data, training, validation, and evaluation are designed, not only on which algorithm is selected.
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