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52:24
YouTube
Alexander Jung
Gradient Based Learning
This lecture shows how to use the concept of gradients to update or improve the weights of an artificial neural network. The main idea is to use the gradient of the training error (viewed as a function of weights) to construct a local approximation that is then optimized (locally).
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