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Neural networks can be intuitively visualized in 3D by imagining each decision layer as a surface or plane that gradually reshapes based on the inputs and learned weights. Each neuron acts like a point on this surface, contributing to the overall shape. Initially, the surface is smooth and unrefined, but as the network trains, the neurons begin ...
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