Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks are model architectures suited for time series data. They can capture temporal dependencies and patterns over time. LSTMs are a variant that addresses the vanishing gradient problem in standard RNNs.
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