On the Suitability of Long Short-Term Memory Networks for Time Series Forecasting
Last Updated on August 5, 2019
Long Short-Term Memory (LSTM) is a type of recurrent neural network that can learn the order dependence between items in a sequence.
LSTMs have the promise of being able to learn the context required to make predictions in time series forecasting problems, rather than having this context pre-specified and fixed.
Given the promise, there is some doubt as to whether LSTMs are appropriate for time series forecasting.
In this post, we will look at the application of LSTMs to time series forecasting by some of the leading developers of the technique.
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On the Suitability of Long Short-Term Memory Networks for Time Series Forecasting
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LSTM for Time Series Forecasting
We will take a closer look at a paper that seeks to explore the suitability of
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