LSTM

 

Long short-term memory (LSTM) network is an improved version of recurrent neural network (RNN) where the system excels at sequence prediction tasks and capture long-term dependencies.  LSTM was first published in a technical paper by Sepp Hochreiter and Jürgen Schmidhuber.

Let's ask GPT-4 to explain LSTM at a basic level.

Here's the intermediate explanation of LSTM from GPT-4. 

LSTM network is effective at capturing long-range dependencies and retaining essential information over longer sequences.  However, LSTM network architecture is still a sequential model where the sentences are processed word by word.  In the next post we will explore an improved network model that revolutionized sequential data processing.