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Neural Networks (NN) are systems inspired by the brain, consisting of input, hidden, and output layers. They learn through a process of propagation, supervised learning, and weight adjustment, with specific types like Radial Basis Function (RBF) networks and Perceptrons serving different purposes. Key terminology includes weights, thresholds, epochs, and learning rates, which are essential for understanding NN operations.

Author

mugamari mari

Language

EN