Hey there,
Can someone please tell me the difference between Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)?
Hey Jimmy,
The main difference between RNNs and LSTMs is the way they handle the flow of information through the network. In an RNN, the hidden state at each time step is a simple function of the current input and the previous hidden state. This means that the RNN has a fixed-length memory, and the information flows through the network in a linear way.
On the other hand, LSTMs have a more complex structure that allows them to store and access information over longer periods of time. LSTMs have three different types of gates (input, output, and forget gates) that control the flow of information into, out of, and within the memory cell. This allows LSTMs to selectively retain or forget information, and to use the stored information in the output at a later time.
Oh! so this means LSTM and RNN are almost the same?
The only difference is that LSTM have gates that supposedly regulate a better flow of information through the unit?
Yes, That’s correct.