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Hands-On Graph Neural Networks Using Python

Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch

Hands-On Graph Neural Networks Using Python is a comprehensive guide to building and training graph neural networks for a variety of real-world applications. With clear explanations and plenty of hands-on examples, this book is a valuable resource for anyone looking to learn about and apply graph neural networks to their own projects. Les mer

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Hands-On Graph Neural Networks Using Python is a comprehensive guide to building and training graph neural networks for a variety of real-world applications. With clear explanations and plenty of hands-on examples, this book is a valuable resource for anyone looking to learn about and apply graph neural networks to their own projects.

Detaljer

Forlag
Packt Publishing Limited
Språk
Engelsk
ISBN
9781804610701
Utgivelsesår
2023

Om forfatteren

Maxime Labonne is currently a senior applied researcher at Airbus. He received a M.Sc. degree in computer science from INSA CVL, and a Ph.D. in machine learning and cyber security from the Polytechnic Institute of Paris. During his career, he worked on computer networks and the problem of representation learning, which led him to explore graph neural networks. He applied this knowledge to various industrial projects, including intrusion detection, satellite communications, quantum networks, and AI-powered aircrafts. He is now an active graph neural network evangelist through Twitter and his personal blog.

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