Scaling Graph Learning for the Enterprise by Ahmed Menshawy (.ePUB)

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File Size: 10 MB

Scaling Graph Learning for the Enterprise: Production-Ready Graph Learning and Inference by Ahmed Menshawy, Sameh Mohamed, Maraim Rizk Masoud
Requirements: .ePUB reader, 10 MB
Overview: Tackle the core challenges related to enterprise-ready graph representation and learning. With this hands-on guide, applied data scientists, Machine Learning engineers, and practitioners will learn how to build an E2E graph learning pipeline. You’ll explore core challenges at each pipeline stage, from data acquisition and representation to real-time inference and feedback loop retraining. Drawing on their experience building scalable and production-ready graph learning pipelines, the authors take you through the process of building robust graph learning systems in a world of dynamic and evolving graphs. The primary audience for this book includes data scientists and Machine Learning engineers who want to go beyond training a one-off graph model and successfully productize their Data Science projects. You should be comfortable with basic Machine Learning concepts and familiar with at least one Machine Learning framework (e.g., PyTorch, TensorFlow, Keras).
Genre: Non-Fiction > Tech & Devices

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