When should I use GRU instead of LSTM?

What are the main differences between GRU and LSTM?

GRU (Gated Recurrent Unit) is simpler and has fewer parameters than LSTM (Long Short-Term Memory), making it faster to train.

In what scenarios is GRU preferred over LSTM?

GRU is often preferred when you have limited data or need faster training times, as it can perform comparably to LSTM.

Are there specific tasks where LSTM outperforms GRU?

Yes, LSTM may perform better in tasks requiring long-term dependencies due to its more complex architecture.

How do I decide which one to use for my project?

Consider your dataset size, the complexity of the task, and the computational resources available. Experimentation can also help.