What are memory models in neural networks?

What are memory models in neural networks?

Memory models in neural networks refer to architectures that can store and retrieve information over time, enhancing learning.

How do these models differ from traditional neural networks?

Unlike traditional models, memory models can maintain state and context, allowing them to handle sequences and temporal data better.

Can you give examples of memory models?

Sure! Examples include Long Short-Term Memory (LSTM) networks and Gated Recurrent Units (GRUs), both designed for sequence prediction.

What are the applications of these memory models?

They are widely used in natural language processing, speech recognition, and time series forecasting, among other fields.