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– Find patterns and relationships in massive amounts of
data too complicated for humans to analyze

– “Learn” patterns by searching for relationships, building models, and correcting over and over again

– Humans “train” network by feeding it data inputs for which outputs are known, to help neural network learn solution by example

– Used in medicine, science, and business for problems in pattern classification, prediction, financial analysis, and control and optimization