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The quickly growing field of artificial intelligence uses a number of different algorithmic theories to help computers simulate thought and learning in an effort to solve complex problems, infer information from a set of input, scale, and accomplish other tasks. Some of the more popular systems used for machine learning are based on the concept of artificial neural networks.
In the computing world, a neural network combines algorithms and inputs to simulate an understanding of something and then perform tasks related to it. As an example, a neural network for image processing could provide many examples of handwriting along with instructions of what each letter, number, and punctuation equals on the keyboard. It could then be up to the neural network to take new handwriting inputs and convert them to text.
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