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L2M – Next Generation Data Validation and Annotation Utilizing Geometrical Space of Differentiable Labelers
The challenge to be addressed in this project is to develop a next generation of machine-learning-guided data validation and annotation tools that take account of differences in human judgment and decision-making processes.
Faculty Supervisor:
Eldan Cohen
Student:
Partner:
DMZ Ventures Inc
Discipline:
Computer science
Sector:
Professional, scientific and technical services
University:
University of Toronto
Program:
Business Strategy Internship
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