Shypd.aiThe largest open index of AI toolsHands-On-Graph-Neural-Networks-Using-Python is an Open Source resource that provides practical techniques and architectures for building powerful graph and deep learning applications with PyTorch. It includes code repositories and instructions for implementing graph neural networks.
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Hands-On Graph Neural Networks Using Python, published by Packt, is a comprehensive resource for machine learning practitioners, data scientists, and students interested in graph neural networks. The book covers fundamental concepts, practical implementation using Python and PyTorch Geometric, and applications ranging from natural language processing to drug discovery. It teaches users how to classify nodes, graphs, and edges, predict graph topologies, combine heterogeneous data sources, and forecast events. The resource includes all necessary code organized into folders, along with detailed instructions for setting up the required software and hardware, including Python, PyTorch, PyTorch Geometric, and optional GPU acceleration with CUDA and cuDNN. It also provides a list of required Python libraries and offers alternative access via Google Colab.
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