This section will describe the inner components of a single LSTM cell, primarily, the three different gates present inside the cell. A number of such cells stacked together form an LSTM network:
- LSTMs also have a chain-like structure like RNNs. Standard RNNs are basically modules of repeating units like a simple function (for example, tanh).
- LSTMs have the capability to retain information for long periods of time as compared to RNNs owing to the presence of memory in each unit. This allows them to learn important information during the early stages in a sequence of inputs and also gives it the ability to have a significant impact on the decisions made by the model at the end of each time step.
- By being able to store information ...