Graph Neural Networks in Action (Manning) |
Monday, 02 June 2025 | |||
This book shows how to to build graph neural networks for recommendation engines and molecular modeling. TKeita Broadwater and Namid Stillman show how to both design and train models, and how to develop them into practical applications, with graph neural networks for node prediction, link prediction, and graph classification. The book includes coverage of the essential GNN libraries, including PyTorch Geometric, DeepGraph Library, and Alibaba’s GraphScope for training at scale. <ASIN:1617299057 > Author: Keita Broadwater and Namid Stillman Topics include:
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