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It can sometimes be too complicated to spell out a decision-making process. Machine learning tries to "learn" based on a set of past decision-making examples.
Machine learning is used for things like recommendations, predictions, and looking up information.
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Computation is the heart of an algorithm and involves arithmetic, decision-making, and repetition.
The instructions tell a computer how to transform a set of facts into useful information.
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This was always in our minds but we didn't know whom to ask.
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Are we keeping a close eye on machine learning and it's ability to replicate what we teach it?
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