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About the Webinar
The Webinar on Data Quality and Data Synthesis Using Constraints is organised by IBM on Sep 7, 2020 at 4:00 PM.
The increasing industrial usage of machine learning models raises the question of the reliability of machine learning models, which also depends on the quality of the data used for training. The current industry practice of testing with limited data is often insufficient.
We provide techniques for understanding the data, inferring data constraints and using these constraints to improve the data quality by removing anomalies, imputing missing values and also generating synthetic data required for model training and testing. We address multiple important challenges like realistic and user-controllable data generation, essentially to increase trust in machine learning models.
- Sandeep Hans is a Research Scientist at IBM Research, India. His current focus is on building dependable AI systems using bias and adversarial AI testing, and data quality for AI.
- He received his PhD from Technion(Israel), MS from IIIT-H and B.Tech. from DA-IICT.
- Prior to IBM, he was a Post-doc researcher at Virginia Tech(US) and has also worked in Research and Development department at Mindtree Consulting.
- He has published papers in top conferences and journals like Journal of ACM, PODC, DISC, PPoPP and ICDE, and has been PC member of top conferences.
How to Register?
Interested participants can register for the webinar through this link.
For more details, click the link below.