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Sessional Lecturer, INF2205H - Designing Sustainable & Resilient Machine Learning Systems with MLOps
the everchanging nature of data that is conveyed by the adage “model drifts as data shifts”. Students will use frameworks and techniques for architectural modeling, analysis, and design to understand and apply
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levels. The ideal candidate will possess a strong background in the design, synthesis, modeling, fabrication, multi-technique analysis, and testing of photocatalyst and photoreactor architectures
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