Labonne, Maxime
Hands-On Graph Neural Networks Using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch
- ISBN 13:
- 9781804617526
- author:
- Labonne, Maxime
- format:
- Paperback
- publisher:
- Packt Publishing
- language:
- English
- Publication Year:
- 2023
- Pages:
- 354
- Dimensions:
- 23.5 x 19.1 x 1.9 centimetres (0
- Genre:
- Computers, Artificial Intelligence, Computers,
- Condition:
- New
- Availability:
- Item usually sent within 5 working days
Description
Learn to design and implement robust graph neural networks using PyTorch Geometric. This comprehensive guide covers the fundamentals of graph theory and shows you how to create datasets from tabular data, before exploring major architectures and essential concepts such as graph convolution and self-attention.
With a focus on practical techniques and applications, Hands-On Graph Neural Networks Using Python covers topics including node and graph classification, link prediction, and more. You'll learn how to build powerful traffic forecasting, recommender systems, and anomaly detection applications using PyTorch Geometric.
Purchase of the book includes a free PDF eBook, and the code is readily available online for easy adaptation to other datasets and apps. By the end of this book, you'll have gained hands-on experience with graph neural networks and be able to build a professional portfolio.
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