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Название: Graph Neural Networks in Action (MEAP v5)
Автор: Keita Broadwater
Издательство: Manning Publications
Год: 2022
Страниц: 257
Язык: английский
Формат: pdf, epub
Размер: 38.6 MB
A hands-on guide to powerful graph-based Deep Learning models! Learn how to build cutting-edge graph neural networks for recommendation engines, molecular modeling, and more. In Graph Neural Networks in Action you’ll create Deep Learning models that are perfect for working with interconnected graph data. Start with a comprehensive introduction to graph data’s unique properties. Then, dive straight into building real-world models, including GNNs that can generate node embeddings from a social network, recommend eCommerce products, and draw insights from social sites. This comprehensive guide contains coverage of the essential GNN libraries, including PyTorch Geometric, DeepGraph Library, and Alibaba’s GraphScope for training at scale. For Python programmers familiar with Machine Learning and the basics of Deep Learning.
Автор: Keita Broadwater
Издательство: Manning Publications
Год: 2022
Страниц: 257
Язык: английский
Формат: pdf, epub
Размер: 38.6 MB
A hands-on guide to powerful graph-based Deep Learning models! Learn how to build cutting-edge graph neural networks for recommendation engines, molecular modeling, and more. In Graph Neural Networks in Action you’ll create Deep Learning models that are perfect for working with interconnected graph data. Start with a comprehensive introduction to graph data’s unique properties. Then, dive straight into building real-world models, including GNNs that can generate node embeddings from a social network, recommend eCommerce products, and draw insights from social sites. This comprehensive guide contains coverage of the essential GNN libraries, including PyTorch Geometric, DeepGraph Library, and Alibaba’s GraphScope for training at scale. For Python programmers familiar with Machine Learning and the basics of Deep Learning.