Graph Neural Networks with PyTorch For Beginners : A Practical Guide to Graph Learning, GNN Architectures, Training, and Real-World Applications

Lingua: inglese

Editore: Amazon Digital Services LLC - Kdp Sep 2026, 2026

9798171189686

Serie: Libro 3 di 3 - PyTorch Programming Series

Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

Brossura

Condizione: Nuovo

EUR 35,95

EUR 35,00 spedizione 
Spedito da Germania a U.S.A.

Quantità: 2 disponibili

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Descrizione dell’articolo da parte del venditore

Neuware - Graph Neural Networks with PyTorch For Beginners introduces the concepts and practical techniques needed to understand and build Graph Neural Networks using PyTorch-based tools and workflows.Traditional neural networks work naturally with images, sequences, and other structured data, but many real-world problems involve relationships between entities. Social networks, recommendation systems, knowledge graphs, molecular structures, fraud networks, and transportation systems can all be represented as graphs. Graph Neural Networks provide a powerful approach for learning from both the features of individual entities and the relationships connecting them.This book introduces graph concepts before progressively exploring graph representations, message passing, graph convolution, node classification, link prediction, graph classification, graph attention, graph datasets, training workflows, and practical GNN applications.What You Will Learn- Understand graphs, nodes, edges, features, and graph representations- Learn the foundations of Graph Neural Networks- Understand message-passing neural networks- Build GNN models with PyTorch-based tooling- Work with graph datasets and graph structures- Perform node classification and link prediction- Build graph-level classification models- Explore graph convolution and attention mechanisms- Train, evaluate, and improve GNN models- Handle common challenges in graph machine learning- Apply GNNs to practical machine learning problems- Develop a foundation for more advanced graph learning and GraphRAG systemsDesigned for readers who already have some familiarity with Python and basic machine learning concepts, this book provides an accessible path into graph-based deep learning while maintaining a strong emphasis on practical implementation.By the end of the book, readers will understand how Graph Neural Networks work, how to implement them, and how to approach real-world problems where relationships and connectivity are as important as the data attached to individual entities. …

Codice articolo 9798171189686

Titolo
Graph Neural Networks with PyTorch For Beginners : A Practical Guide to Graph Learning, GNN Architectures, Training, and Real-World Applications
Autore
Alvin Marsh
Editore
Amazon Digital Services LLC - Kdp Sep 2026
Anno di pubblicazione
2026
Condizione
Neu
Rilegatura
Taschenbuch
Lingua
inglese
ISBN 13
9798171189686
Peso dell'articolo
354 grammi
Dimensioni
254x178x11 mm
Serie
Libro 3 di 3: PyTorch Programming Series

AHA-BUCH GmbH

Einbeck, Germania

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

Tariffe di spedizione da Germania a U.S.A.

ArticoloDa 7 a 10 giorni lavorativiDa 5 a 7 giorni lavorativi
Primo articoloEUR 35,00EUR 45,00
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