What does LSTM stand for?

LSTM Stands for Long Short-Term Memory

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LSTM Stands for Long Short-Term Memory

Long Short-Term Memory (LSTM) is a type of recurrent neural network (RNN) architecture designed to model sequential data and capture long-term dependencies.

Unlike traditional RNNs, which struggle with learning long-range dependencies due to the vanishing gradient problem, LSTMs are specifically designed to retain important information over extended sequences of data, making them highly effective for tasks that require memory over time.

Key Components of LSTM:

1. Cell State:
   The cell state is the “memory” component of the LSTM. It allows the network to store information over long time periods, enabling it to remember previous inputs and maintain context over time. The cell state is modified by gates that decide which information to keep or discard as new data comes in.
2. Gates:
   LSTMs have three key gates that control the flow of information through the network:

• Input Gate: Decides which information from the current…