April 2023
Intermediate to advanced
354 pages
8h 22m
English
Content preview from Hands-On Graph Neural Networks Using Python
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Part 1: Introduction to Graph Learning
In recent years, graph representation of data has become increasingly prevalent across various domains, from social networks to molecular biology. It is crucial to have a deep understanding of Graph Neural Networks (GNNs), which are designed specifically to handle graph-structured data, to unlock the full potential of this representation.
This first part consists of two chapters and serves as a solid foundation for the rest of the book. It introduces the concepts of graph learning and GNNs and their relevance in numerous tasks and industries. It also covers the fundamental concepts of graph theory and its applications in graph learning, such as graph centrality measures. This part also highlights the unique ...
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