Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter

Long short-term memory

It is very common to observe vanishing and exploding gradients in RNNs. These are a severe bottleneck in the implementation of deep RNNs where the data is present in a form where relationships between features are more complex than linear functions. To overcome the vanishing gradient problem, the concept of long short-term memory (LSTM) was introduced by German researchers Sepp Hochreiter and Juergen Schmidhuber, in 1997. 

LSTM has proved highly useful in the fields of NLP, image caption generation, speech recognition, and other domains, where it broke previously established records after it was introduced. LSTMs store information outside the network that can be recalled at any moment, much like a secondary storage ...