Scaling Graph Learning for the Enterprise - Menshawy, Ahmed; Mohamed, Sameh; Masoud, Maraim Rizk
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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.

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Produktbeschreibung
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.
Autorenporträt
Ahmed Menshawy is the Vice President of AI Engineering at Mastercard's Cyber and Intelligence. In this role, he leads the AI Engineering team, driving the development and operationalization of AI products and addressing the broad range of challenges and technical debts surrounding ML pipelines. Ahmed also leads a team dedicated to creating a number of AI accelerators and capabilities, including Serving engines and Feature stores, aimed at enhancing various aspects of AI engineering. Ahmed is the coauthor of Deep Learning with TensorFlow and the author of Deep Learning by Example, focusing on advanced topics in deep learning.