Computer programmes that use deep learning go through stages analogous to how a young child learns to recognise the dog. Each algorithm in the hierarchy performs a nonlinear modification on its input before using what it has discovered to create an output that is a statistical model. Iterations continue until the outcome is reliable enough to accept. "Deep" processing refers to the quantity of processing layers that data must go through.
A computer software utilising Deep Learning algorithms can rapidly and precisely filter through millions of images to identify those that contain dogs after being presented with a training set of pictures. Unlike a young child who would need weeks or even months to understand what a dog is.
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