Garbage In / Garbage Out: The Importance of Quality Data
Date Thursday, February 18, 12pm ET
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In two thought-provoking presentations, followed by audience discussion, this session will explore the most significant barrier for the implementation of incorporating machine learning in architecture: the availability of quality data.
This presentation is part of the TAP Building Connections Congress 2021: Machine Learning’s Impact on Architecture and Design.
- Explain how data quality is important in supervised learning algorithms.
- Explore the challenges of data sources, their supply chain, structure, size and other issues.
- Learn how to overcome data quality issues for effective machine learning applications in architecture.
- Discuss ways of structuring data for use in machine learning systems.