LSTM
Long Short-Term Memory is a specialized recurrent neural network architecture designed to mitigate the vanishing gradient problem in long sequences.
Think of It Like This
Like a diary with a smart index that automatically decides which old entries to remember and which obsolete ones to forget.
LSTMs utilize complex internal gating mechanisms—forget, input, and output gates—to regulate the flow of information over time. This allows them to capture long-range dependencies in sequence data like text, speech, or time series. While powerful, they have largely been superseded by transformers for natural language tasks.