Are you ready to solve problems that traditional AI can't? Discover the power of Graph Neural Networks.
This essential reading is for machine learning practitioners, data engineers, and students aiming to master Graph AI and its diverse applications. Equip yourself with the skills to build intelligent systems that understand relationships, predict complex behaviors, and generate novel insights from interconnected data.
Key features include:
End-to-End Project Workflow: From graph modeling to GNN deployment and monitoring.
Key Architectures Explained: Deep dive into GCN, GraphSAGE, GAT, and heterogeneous GNNs.
Scalability Solutions: Tackle massive graphs with practical sampling and distributed training techniques.
Real-World Impact: Explore mini case studies across cybersecurity, social network analysis, and smart cities.
Ethical Deployment: Best practices for fairness, robustness, and privacy in GNNs.
Hands-on with PyTorch Geometric and DGL.
"Graph Neural Networks in Practice" provides the practical knowledge to build impactful AI Systems on graph data.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Da: California Books, Miami, FL, U.S.A.
Condizione: New. Print on Demand. Codice articolo I-9798291732144
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Da: Rarewaves.com USA, London, LONDO, Regno Unito
Paperback. Condizione: New. Codice articolo LU-9798291732144
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Da: CitiRetail, Stevenage, Regno Unito
Paperback. Condizione: new. Paperback. Are you ready to solve problems that traditional AI can't? Discover the power of Graph Neural Networks.This essential reading is for machine learning practitioners, data engineers, and students aiming to master Graph AI and its diverse applications. Equip yourself with the skills to build intelligent systems that understand relationships, predict complex behaviors, and generate novel insights from interconnected data.Key features include: End-to-End Project Workflow: From graph modeling to GNN deployment and monitoring.Key Architectures Explained: Deep dive into GCN, GraphSAGE, GAT, and heterogeneous GNNs.Scalability Solutions: Tackle massive graphs with practical sampling and distributed training techniques.Real-World Impact: Explore mini case studies across cybersecurity, social network analysis, and smart cities.Ethical Deployment: Best practices for fairness, robustness, and privacy in GNNs.Hands-on with PyTorch Geometric and DGL."Graph Neural Networks in Practice" provides the practical knowledge to build impactful AI Systems on graph data. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798291732144
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Da: Rarewaves.com UK, London, Regno Unito
Paperback. Condizione: New. Codice articolo LU-9798291732144
Quantità: Più di 20 disponibili