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If Your Data Is Bad, Your Machine Learning Tools Are Useless | Harvard

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Five steps to ensure higher-quality data.

“Poor data quality is enemy number one to the widespread, profitable use of machine learning. While the caustic observation, “garbage-in, garbage-out” has plagued analytics and decision-making for generations, it carries a special warning for machine learning...

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