Long Short Term Memory Tutorial
Long Short Term Memory Tutorial offers a collection of rated resources and pieces of information about using this innovative deep learning technique in order to work with big data. The Long Short Term Memory (LSTM) recurrent neural network is particularly well working for temporal sequences and long-term dependencies in the data. For more general information about this technique we refer to our article on Long Short Term Memory.
[Blog] Christopher Olah
An interesting introduction to LSTM networks can be found in this blog here. It describes LSTMs quite well including good figures despite the fact that the language is rather ‘casual’ and here and there it would be beneficial to add more application examples in context. Nevertheless the article is quite well written and numerous comments have been added in its discussions.
[Paper] Acoustic Modeling and Speech Recognition
Another interesting resource in order to understand LSTM is the paper entitled ‘Long Short-Term Memory Recurrent Neural Network Architectures for Large Scale Acoustic Modeling’ that can be downloaded here. Compared to other general introductions this paper has the interesting application area of large scale acoustic modeling for speech recognition.
[Tutorial PDF] Lisa Lab Deep Learning Tutorial
There is a relative good general deep learning tutorial from the Lisa Lab of the University of Montreal available here. There is a good and easy to follow simple example for binary classification of movie reviews in order to predict whether it is positive or negative but the length of this LSTM tutorial can be extended and is a little bit short.
Long Short Term Memory Tutorial Details
There is a wide variety of video material but we recommend to look at the following material: