GRU (Gated Recurrent Unit)

A type of recurrent neural network that is similar to LSTM but with a simpler architecture.

Description

Gated Recurrent Unit (GRU) is a type of recurrent neural network architecture that is similar to Long Short-Term Memory (LSTM) but with a simpler design. GRUs use update and reset gates to solve the vanishing gradient problem of traditional RNNs. This allows them to effectively capture long-term dependencies in sequential data. GRUs are often computationally more efficient than LSTMs while achieving comparable performance on many tasks.

Examples

📊 Time series prediction
🗣️ Speech recognition
📝 Text classification

Applications

🎵 Music generation

🌐 Machine translation

📈 Stock price prediction

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