Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Graph Neural Networks for Practical AI Systems: Designing Architectures and Training Pipelines for Scalable Graph Intelligence with GCN, GAT, GraphSAG

Graph Neural Networks for Practical AI Systems: Designing Architectures and Training Pipelines for Scalable Graph Intelligence with GCN, GAT, GraphSAG

Qinghan, Xu

Paperback

Series: Modern AI Systems Engineering with Python, Book 2

General Computers

ISBN13: 9798244713992
Publisher: Independently Published
Published: Jan 20 2026
Pages: 198
Weight: 0.80
Height: 0.42 Width: 7.44 Depth: 9.69
Language: English
Graph Neural Networks (GNNs) are transforming the way AI systems reason about complex, relational data. In domains like social networks, recommendation engines, knowledge graphs, fraud detection, and beyond, the relationships between entities are often more important than the entities themselves. Traditional deep learning approaches struggle to capture these intricate connections, leaving a gap in both performance and interpretability.

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