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Activation Functions Explained: Why Neural Networks Need ReLU #Shorts
Stack a hundred layers of a neural network with no activation function, and here's the shocking part: it collapses into a single straight line. All that depth, wasted. The fix is one tiny bend - the activation function. Here's why: a plain layer just does multiply and add - a linear operation - and stacking linear on top of linear still gives ...
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