FNN, or Feedforward Neural Network, is a type of artificial neural network where connections between nodes do not form cycles. In this architecture, data moves in one direction—from input nodes, through hidden nodes (if any), and finally to output nodes. FNNs are foundational in machine learning and can be used in various applications, including classification and regression tasks.
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