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Computation is the heart of an algorithm and involves arithmetic, decision-making, and repetition.
To apply this to getting dressed, you make decisions by doing some math on input quantities. Wearing a jacket might depend on the temperature. To a computer, part of getting dressed algorithm would be "if it is below 50 degrees and raining, then pick the rain jacket and a long-sleeved shirt."
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The instructions tell a computer how to transform a set of facts into useful information.
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.
The last step of an algorithm is output - expressing the answer.
To a computer, input is the information needed to make decisions.
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This was always in our minds but we didn't know whom to ask.
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QUANTAMAGAZINE
quantamagazine.org
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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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