Feed-forward networks are a type of artificial neural network where connections between the nodes do not form cycles. In these networks, information moves in one direction—from input nodes, through hidden nodes, and finally to output nodes—allowing for the processing of data in a linear manner. This architecture is foundational for many deep learning models, including those used in complex tasks like natural language processing and image recognition.
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