The essence of scientific discovery has always been structure. Not surprisingly, mathematical formulae revolve around relationships between variables - information in general. If the data is not structured, what mathematical formula should be applied?
Imagine spending years learning to play a game, and then, when you play a different game, being unable to use any of your previous (gaming) experience for the new game, and having to learn everything from scratch. This could be quite depressing and make life unnecessarily difficult. Along the way, another way of using deep learning was discovered: transfer learning. Because the time it takes for a deep learning architecture to learn is very long, transfer learning uses already learned deep learning architectures, but for a slightly different task.
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