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Network structure inspired by simplified models of biological neurons (brain cells). Neural networks are trained to "learn" by supervised and unsupervised techniques, and can be used to solve optimization problems, approximation problems, classify patterns, and combinations thereof.

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Training a neural network by classifying its own output

I think that similar concept is actually used in Generative Adversarial Network. The entire neural network is like this:              real image --> discriminator (neural network) generator (neural ne …
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