Temporal Convolutional Networks (TCNs):

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TCNs are an alternative to RNNs for sequence modeling, leveraging dilated convolutions to capture long-term dependencies more efficiently.
Example: Using Keras to build a TCN model for predicting weather patterns based on historical climate data, where seasonal and yearly cycles require capturing long-term dependencies.

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