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DTSTAMP:20260617T192614Z
DESCRIPTION:Click for Latest Location Information: http://edw2021.dataversi
 ty.net/sessionPop.cfm?confid=133&proposalid=12771\nData quality is one&nbsp
 ;of the most time-consuming activities within projects and data-d
 riven organizations. As many organizations embark on machine learning (ML) 
 initiatives to provide more value and gain competitive advantage, organizat
 ions need to understand the importance of good-quality data to tr
 ain the ML model, and ways to achieve this. On the other hand, how can mach
 ine learning be leveraged to minimize time spent on data quality and get be
 yond a corrective or even a preventive data quality model?\nIn this session
 , we will go over:\n\n	Data Quality for Machine Learning\n	\n
 Importance of data quality shown through ML projects gone wrong\n
 Key things to take into consideration regarding data quality for machine l
 earning projects\n	\n	\n	Machine Learning for Data Quality\n	\n
 How to implement machine learning in data quality practice\n
 Benefits and key things to look out for based on lessons learned\n
 Case study: Implementation of ML in a data quality project\n	\n
 \n\n
DTSTART:20210421T080000
SUMMARY:Data Quality for Machine Learning, and Machine Learning for Data Qu
 ality
DTEND:20210421T084959
LOCATION: See Description
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