What are the differences between LSTM and GRU?

What are the differences between LSTM and GRU?

LSTM (Long Short-Term Memory) and GRU (Gated Recurrent Unit) are both types of recurrent neural networks. LSTMs have a more complex architecture with three gates, while GRUs have two gates, making them simpler and often faster to train.

Which one performs better in practice?

It depends on the specific task and dataset. Generally, LSTMs can capture more complex patterns due to their architecture, but GRUs can perform comparably well with less computational cost.

Are there situations where I should prefer GRU over LSTM?

Yes, if you're working with smaller datasets or need faster training times, GRUs might be the better choice. They often achieve similar performance with fewer parameters.

Can you give me an example of a use case for each?

Sure! LSTMs are often used in tasks like language modeling and machine translation, while GRUs are commonly used in real-time applications like speech recognition.