Deep Learning uses neural networks with many hidden layers, i.e. those which lie between the input and output layers. It allows a large number of variables to be used as inputs with feedback, allowing the network to learn how those variables interact in different scenarios, and then to develop a weighting and bias for each, in the same way a human would, but with the advantage of being able to accurately consider many more than a person.
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