32K views · 235 reactions | The Universal Approximation Theorem states that a feedforward neural network with a single hidden layer, using a non-linear activation function, can approximate any continuous function on a compact, given enough neurons. | Visual Math+ | Facebook
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32K views · 235 reactions | The Universal Approximation Theorem states that a feedforward neural network with a single hidden layer, using a non-linear activation function,
Visual Math . . The Universal Approximation Theorem states that a feedforward neural network with a single hidden layer, using a non-linear activation function, can approximate any continuous function on a compact, given enough neurons.
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