100 Best Long Short-Term Memory Videos


Long Short-Term Memory (LSTM) is a type of recurrent neural network (RNN) that is used for modeling temporal data and making predictions based on that data. It is particularly well-suited for tasks that require the network to remember and use information from long periods of time, such as language translation or speech recognition.

The key feature of LSTM is its ability to remember and use information from previous time steps over a long period of time. It does this using a set of memory cells, which are units within the network that can store and access information from previous time steps. These memory cells are combined with input, output, and forget gates, which control the flow of information into and out of the memory cells.

LSTMs are widely used for a variety of tasks, including natural language processing, speech recognition, machine translation, and time series forecasting. They are particularly effective at tasks that require the model to remember and use information from long periods of time, and have been used to achieve state-of-the-art results on a number of benchmark datasets.


See also:

LSTM (Long Short Term Memory) & Dialog Systems 2019

[75x Dec 2020]