Graph-Powered Machine Learning
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.
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
Fill out the form to get your excerpt of Graph-Powered Machine Learning.