Discover how Machine Learning augments data quality and matching in entity resolution.
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In this AI Whitepaper we cover a real-world application of how Machine Learning can be used to improve consistency in entity resolution and reduce manual intervention by up to 45%. We highlight how tools in the Ä¢¹½¶ÌÊÓÆµ Self-Service Data Quality platform can be used for key data preparation tasks including cleansing, feature engineering and dataset labelling for input into ML models.
Discover:
- An Overview of AI and Machine Learning
- Data Quality as a Foundation for Machine Learning
- Machine Learning in Entity Resolution
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A bit about the author
is Head of Software Development and Machine Learning at Ä¢¹½¶ÌÊÓÆµ with over 15 years’ research and industrial experience.
Prior to joining Ä¢¹½¶ÌÊÓÆµ, Fiona lectured in Computing Science at Ulster University teaching Data Analytics and undertaking research on applied artificial intelligence and data integration. She was a Research Fellow at Queen’s University Belfast and a Senior Software Developer at PathXL. Fiona received a BSc (Hons.) degree in Computing Science and a PhD on Artificial Intelligence in Bioinformatics from Ulster University.