title: Mining Graph Data
author: Diane J. Cook
description: "individuals with no background analyzing graph data can learn how to represent the data as graphs, extract patterns or concepts from the data, and see how researchers apply the methodologies to real datasets." (<i>Computing Reviews.com</i>, March 23, 2007)
zlib_text: ©Manning Publications Co.  To comment go to  liveBook 
  MEAP Edition 
  Manning Early Access Program 
  Graph Powered Machine Learning 
  Version 6 
  Copyright 2020 Manning Publications 
  For more information on this and other Manning titles go to 
  manning.com
  
  ©Manning Publications Co.  To comment go to  liveBook 
  welcome 
  Dear Reader, 
  Thanks for purchasing the MEAP of Graph Powered Machine Learning. Graph-based machine 
  learning is becoming a very important trend in Artificial Intelligence, transcending a lot of 
  other techniques. Google, Facebook, and E-bay – to cite some of them - have multiple 
  projects involving graphs, and more specifically graph models and graph algorithms, as 
  empowering mechanism behind the most advanced services they are providing to their end 
  users. 
  Graph-Powered Machine Learning is a practical guide to effectively using graphs in machine 
  learning applications, driving you in all the stages necessary for building complete solutions 
  where graphs play a key role.