Long Short Term Memory networks


Long Short Term Memory networks (LSTM) is a Artificial Neural network that is a special kind of Recurrent Neural network, capable of Machine Learning long-term dependencies.

They were introduced by Hochreiter & Schmidhuber (1997), and were refined and popularized by many people in following work.

Long Short Term Memory networkss work tremendously well on a large variety of problems, and are now widely used.

Long Short Term Memory networkss are explicitly designed to avoid the long-term dependency problem. Remembering information for long periods of time is practically their default behavior, not something they struggle to learn!

All Recurrent Neural networks have the form of a chain of repeating modules of neural network. In standard RNNs, this repeating module will have a very simple structure, such as a single tanh layer.

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