Temporal convolutional network (TCN) “outperform canonical recurrent networks such as LSTMs across a diverse range of tasks and datasets, while demonstrating longer effective memory”. Note 4: Related to this topic, is the fact that we know little of how our human brain learns and remembers sequences.
Read moreIs LSTM good for prediction?
LSTMs are widely used for sequence prediction problems and have proven to be extremely effective . The reason they work so well is that LSTM can store past important information and forget the information that is not.
Read moreIs LSTM good for prediction?
LSTMs are widely used for sequence prediction problems and have proven to be extremely effective . The reason they work so well is that LSTM can store past important information and forget the information that is not.
Read moreCan LSTM be used for time series prediction?
LSTM are useful for making predictions, classification and processing sequential data . We use many kinds of LSTM for different purposes or for different specific types of time series forecasting.
Read moreIs time series used for forecasting?
What is time series forecasting? Time series forecasting is the process of analyzing time series data using statistics and modeling to make predictions and inform strategic decision-making .
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