Want to understand why machine learning models fail — and how to fix them? This hands-on session dives into practical ML debugging using visualization-driven techniques.
Learn how to diagnose hidden model failure patterns, interpret learning curves and confusion matrices, analyze ROC performance, and investigate error patterns before changing model architecture. You’ll build a stronger, more systematic approach to developing reliable ML systems.
Led by Sheida Majouni, PhD Candidate in Computer Science at Dalhousie University and AI/ML Lead at DeepSense.
March 26, 2026
6:00–8:00 PM
Room 143
FREE
Register here! https://bit.ly/shiftkey-events
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