Deep learning uses neural networks loosely modeled on those of the human brain. In simple terms, these systems “learn” when their networks are “trained” on large amounts of data. In the case of AlexNet, the training data consisted of images. Each red, green, or blue pixel is given a value, and the resulting array of numbers is fed into the network as an input. Within the network, “neurons” link to other neurons by a series of weighted connections, each of which roughly corresponds to the strength of the relationship between inputs. Each layer in the neural network feeds its input down to the
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