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You are viewing ARCHIVED CONTENT released online between 1 April 2010 and 24 August 2018 or content that has been selectively archived and is no longer active. Content in this archive is NOT UPDATED, and links may not function.Extract from article by Bernard Marr
Deep learning is a topic that is making big waves at the moment. It is basically a branch of machine learning (another hot topic) that uses algorithms to e.g. recognize objects and understand human speech. Scientists have used deep learning algorithms with multiple processing layers (hence “deep”) to make better models from large quantities of unlabeled data (such as photos with no description, voice recordings or videos on YouTube).
It’s one kind of supervised machine learning, in which a computer is provided a training set of examples to learn a function, where each example is a pair of an input and an output from the function.
Very simply: if we give the computer a picture of a cat and a picture of a ball, and show it which one is the cat, we can then ask it to decide if subsequent pictures are cats. The computer compares the image to its training set and makes an answer. Today’s algorithms can also do this unsupervised; that is, they don’t need every decision to be pre-programmed.
Read the complete article at A Short History Of Deep Learning — Everyone Should Read