![]() Each neuron is connected to several neurons in the next layer. The zoomed-out view of deep neural networksĭeep learning algorithms use different configurations of deep neural networks, architectures that most books and articles describe as a rough imitation of biological brains (the analogy surely doesn’t help simplify the concept, does it?).Ī deep neural network is composed of several layers of artificial neurons stacked on top of each other. In this post, I will (try to) show you how deep learning works by building it piece by piece. Yet, at heart, any deep learning model is just a combination of simple mathematical components. The remarkable feats of deep learning make it seem magical and out of reach. Clarke: “Any sufficiently advanced technology is indistinguishable from magic.” In the past years, deep learning has proven to be capable of creating realistic images of non-existing people, recognize faces and voice commands, synthesize voice that sounds almost natural, and ( pretend to) understand natural language. Today, deep learning might seem like a manifestation of the saying by British science fiction writer Arthur C. This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. ![]()
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