Description

Long Short-Term Memory (LSTM) is a type of recurrent neural network architecture designed to address the vanishing gradient problem that traditional RNNs face when learning long-term dependencies. LSTMs use a gating mechanism to selectively remember or forget information, allowing them to capture and utilize information over long sequences. This makes them particularly effective for tasks involving sequential data, such as time series analysis or natural language processing.

Examples

• 😃 Sentiment analysis
• 🌐 Machine translation
• 🗣️ Speech recognition

Applications