Graph-Powered Machine Learning

Book Excerpt

Learn how graphs use context to improve machine learning workflows for better recommendation engines.


By Alessandro Negro

Published by Manning

Print Length: 142 pages

Available Formats: PDF US


Modern machine learning demands new approaches. A powerful ML workflow is more than picking the right algorithms. You also need the right tools, technology, datasets and model to brew your secret ingredient: context.

This book explores the new way of looking at machine learning – through the lens of graph technology. In particular, this excerpt takes a closer look at how graph-powered ML can be used to build hybrid, real-time recommendation engines.

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Read this book excerpt to discover and learn:

  • The role of graph technology in machine learning applications
  • How graph data science enhances content-based recommendation engines
  • How to design a context-aware and hybrid recommendation engine, with concrete examples
  • How graphs provide better context to improve your ML understanding and workflow

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