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Graph Neural Networks in Action is a great guide about how to build cutting-edge graph neural networks and powerful deep learning models for recommendation engines, molecular modeling, and more. Ideal for Python programmers, you will dive into graph neural networks perfect for node prediction, link prediction, and graph classification.

Produktbeschreibung
Graph Neural Networks in Action is a great guide about how to build cutting-edge graph neural networks and powerful deep learning models for recommendation engines, molecular modeling, and more. Ideal for Python programmers, you will dive into graph neural networks perfect for node prediction, link prediction, and graph classification.
Autorenporträt
Keita Broadwater, PhD, MBA is a machine learning engineer with over ten years executing data science, analytics, and machine learning applications and projects. He is Chief of Machine Learning at candidates.ai, a firm which uses AI to enhance executive search. Dr. Broadwater has delivered DS and ML projects for all types of organisations, from small startups to Fortune 500 companies, and has developed and advised on graph-related projects in the industries of insurance, HR and recruiting, and supply chain.