Long Short-Term Memory (LSTM)
Long Short-Term Memory (LSTM) is a specialized type of Recurrent Neural Network (RNN) architecture designed to learn long-term dependencies in sequential data. LSTM networks utilize memory cells and gating mechanisms to address the vanishing gradient problem, making them essential for tasks such as language modeling, speech recognition, and time series forecasting.