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Exploring the Frontier of Graph Neural Networks: Key Concepts, Architectures, and Trends

Toronto Machine Learning Series (TMLS) via YouTube

Overview

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Discover the fundamentals of Graph Neural Networks (GNNs) in this 30-minute conference talk from the Toronto Machine Learning Series, presented by Anik Pat, Lead Machine Learning Applied Scientist at Genesys. Gain insights into how GNNs leverage relationships within data to drive innovation across various domains, from social network analysis to drug discovery. Learn about the core principles, architectures, and applications that make GNNs a powerful tool for modeling complex data structures through graph representations. Master the essential concepts needed to harness GNNs' potential in data analysis and problem-solving, whether working as a data scientist, researcher, or industry professional.

Syllabus

Exploring the Frontier of Graph Neural Networks Key Concepts, Architectures, and Trends

Taught by

Toronto Machine Learning Series (TMLS)

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