Hands-On Graph Neural Networks using Python: Practical techniques and architectures for building powerful graph and deep learning apps with PyTorch

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Publisher ‏ : ‎ Packt Publishing – ebooks Account (May 9, 2023)
Language ‏ : ‎ English
Paperback ‏ : ‎ 365 pages
ISBN-10 ‏ : ‎ 1804617520
ISBN-13 ‏ : ‎ 978-1804617526
Item Weight ‏ : ‎ 1.36 pounds
Dimensions ‏ : ‎ 9.25 x 7.52 x 0.74 inches

Graph Neural Networks (GNNs) have gained popularity in recent years for their ability to model complex relationships and dependencies in data that can be represented as graphs. In this post, we will explore hands-on techniques and architectures for building powerful graph and deep learning applications using Python and PyTorch.

We will start by introducing the basics of graph theory and how it can be applied to machine learning tasks. Then, we will dive into the fundamentals of GNNs, including how they work, different types of GNN architectures, and how they can be implemented in PyTorch.

Throughout the post, we will walk through practical examples and code snippets to help you understand how to build and train GNN models using PyTorch. We will cover topics such as graph representation, message passing, node classification, link prediction, and more.

By the end of this post, you will have a solid understanding of how to leverage GNNs for your own projects and how to use PyTorch to implement powerful graph and deep learning applications. Stay tuned for more updates on Hands-On Graph Neural Networks using Python!
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