LSTM (Long Short-Term Memory)

Long Short-Term Memory (LSTM) is a type of neural network designed to remember information for long periods. Unlike standard networks that struggle with retaining data over time, LSTMs use special structures called "gates" to control what information to keep or forget. This allows them to effectively learn patterns in sequences, making them useful for tasks like language translation and speech recognition. By managing memory better, LSTMs can understand context and sequence, enabling more accurate predictions and insights in various applications involving time-based data.