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==Reasons for Data-centric AI== | ==Reasons for Data-centric AI== | ||
*Data quality issues are | *Data quality issues alone are estimated to cost the United States $3 Trillion annually. | ||
*Automated methods | *Automated methods, systematic engineering principles and automated methods are required to ensure that ML models are trained using clean data. | ||
*Recent research | *Recent research has shown that simple methods that adapt to changing data can produce more accurate models than complex modeling strategies. |
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