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 is better for time series prediction?

It depends on the specific dataset and problem. LSTMs can capture long-term dependencies better, while GRUs are often more efficient and can perform just as well on many tasks.

Are there situations where GRU outperforms LSTM?

Yes, in cases with limited data or when computational resources are constrained, GRUs can outperform LSTMs due to their simpler structure.

Can you give me an example of when to use each?

Use LSTM for tasks requiring long-term memory, like language modeling. Use GRU for tasks with less complexity, like short-term sequence predictions.