{"product_id":"graph-machine-learning-mastery-philip-oscar-9798261760221","title":"Graph Machine Learning Mastery: A Complete Guide to Graph Neural Networks, Graph Transformers, Temporal GNNs, and LLM-Powered Graph AI with PyTorch Ge","description":"\u003cb\u003eGraph Machine Learning Mastery\u003c\/b\u003e\u003cbr\u003e\u003cb\u003e\u003ci\u003eA Complete Guide to Graph Neural Networks, Graph Transformers, Temporal GNNs, and LLM-Powered Graph AI with PyTorch Geometric \u0026amp; DGL\u003c\/i\u003e\u003c\/b\u003e\u003cp\u003eGraph-structured data powers today's most advanced AI systems-from recommendation engines and fraud detection to drug discovery, cybersecurity, and large-scale knowledge graphs. \u003cb\u003eGraph Machine Learning Mastery\u003c\/b\u003e is the definitive, end-to-end guide for engineers, researchers, and data scientists who want to \u003cb\u003edesign, train, scale, and deploy production-ready graph AI systems\u003c\/b\u003e using state-of-the-art techniques.\u003c\/p\u003e\u003cp\u003eThis book goes far beyond theory. You'll master \u003cb\u003eGraph Neural Networks (GNNs)\u003c\/b\u003e, \u003cb\u003eGraph Transformers\u003c\/b\u003e, \u003cb\u003eTemporal \u0026amp; Dynamic Graph Models\u003c\/b\u003e, and \u003cb\u003eLLM-augmented Graph AI\u003c\/b\u003e, all with hands-on implementations using industry-standard frameworks like and .\u003c\/p\u003e\u003cbr\u003e\u003cb\u003eWhat You'll Learn\u003c\/b\u003e\u003cul\u003e\n\u003cli\u003eBuild powerful \u003cb\u003eGNN architectures\u003c\/b\u003e: GCN, GAT, GraphSAGE, GIN, heterogeneous and large-scale GNNs\u003c\/li\u003e\n\u003cli\u003eTransition from GNNs to \u003cb\u003eGraph Transformers\u003c\/b\u003e with positional encodings and attention mechanisms\u003c\/li\u003e\n\u003cli\u003eModel \u003cb\u003etemporal and dynamic graphs\u003c\/b\u003e using TGN, TGAT, DySAT, and continuous-time message passing\u003c\/li\u003e\n\u003cli\u003eDesign \u003cb\u003eLLM + GNN hybrid systems\u003c\/b\u003e for reasoning, knowledge graphs, and GraphRAG pipelines\u003c\/li\u003e\n\u003cli\u003eApply graph ML to \u003cb\u003ereal-world domains\u003c\/b\u003e: fraud detection, recommender systems, molecular graphs, finance, telecom, and cybersecurity\u003c\/li\u003e\n\u003cli\u003eTrain, optimize, monitor, and deploy graph models in \u003cb\u003eproduction environments\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eIntegrate GNNs with \u003cb\u003egraph databases\u003c\/b\u003e, MLOps pipelines, and scalable inference system.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003e\u003cb\u003eHands-On, End-to-End Projects\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003eYou'll implement complete production-grade projects including: \u003cul\u003e\n\u003cli\u003eNode classification, graph classification, and link prediction\u003c\/li\u003e\n\u003cli\u003eTemporal graph forecasting\u003c\/li\u003e\n\u003cli\u003eMolecular property prediction with OGB benchmarks\u003c\/li\u003e\n\u003cli\u003eGraph-augmented LLM systems for intelligent reasoning and recommendation.\u003c\/li\u003e\n\u003c\/ul\u003eEach project walks you through \u003cb\u003edata preprocessing, model architecture, training, evaluation, deployment, and monitoring\u003c\/b\u003e-so you don't just learn concepts, you \u003cb\u003ebuild real systems.\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003e\u003cul\u003e\n\u003cli\u003eData scientists and ML engineers expanding into \u003cb\u003egraph-based AI\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eAI researchers exploring \u003cb\u003enext-generation GNN and Transformer architectures\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eBackend and platform engineers deploying \u003cb\u003egraph intelligence at scale\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eProfessionals working with \u003cb\u003eknowledge graphs, recommendation systems, and complex networks\u003c\/b\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003eA working knowledge of Python and basic machine learning is recommended. \u003cp\u003e\u003c\/p\u003e\u003cb\u003eWhy This Book Stands Out\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003eUnlike fragmented tutorials or outdated references, \u003cb\u003eGraph Machine Learning Mastery\u003c\/b\u003e delivers a modern, unified, and production-focused roadmap-from classical graph learning to cutting-edge \u003cb\u003eLLM-powered Graph A\u003c\/b\u003eI. With deep technical insight, real-world case studies, and extensive appendices packed with APIs, cheat sheets, troubleshooting guides, and learning paths, this book is designed to become your long-term reference and career accelerator. \u003cp\u003e\u003c\/p\u003eIf you're serious about mastering \u003cb\u003eGraph Machine Learning, Graph Transformers, Temporal GNNs, and LLM-driven AI systems, \u003c\/b\u003e this is the book you've been waiting for.\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Philip Oscar\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9798261760221\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Independently Published\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 12\/17\/2025\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 266\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 1.37lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 11.00h x 8.50w x 0.56d","brand":"Philip Oscar","offers":[{"title":"Paperback","offer_id":48447192695039,"sku":"9798261760221","price":25.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_addc93e4-fcd1-44bc-a0e7-9ae0ef708e7a.jpg?v=1777229462","url":"https:\/\/www.whiterainbookhouse.com\/products\/graph-machine-learning-mastery-philip-oscar-9798261760221","provider":"WR Book House","version":"1.0","type":"link"}