What are recurrent layers in neural networks?

Can you explain what recurrent layers are in neural networks?

Sure! Recurrent layers are a type of neural network layer designed to handle sequential data by maintaining a memory of previous inputs.

How do they differ from regular layers?

Unlike regular layers, recurrent layers have connections that loop back on themselves, allowing them to retain information over time.

What are some common applications of recurrent layers?

They are commonly used in tasks like language modeling, speech recognition, and time series prediction.

Can you give an example of a recurrent layer?

An example is the Long Short-Term Memory (LSTM) layer, which is designed to remember information for long periods.