Chapter 2: Graph Machine Learning
Machine learning is a subset of artificial intelligence that aims to provide systems with the ability to learn and improve from data. It has achieved impressive results in many different applications, especially where it is difficult or unfeasible to explicitly define rules to solve a specific task. For instance, we can train algorithms to recognize spam emails, translate sentences into other languages, recognize objects in an image, and so on.
In recent years, there has been an increasing interest in applying machine learning to graph-structured data. Here, the primary objective is to automatically learn suitable representations to make predictions, discover new patterns, and understand complex dynamics in a better manner with respect to "traditional" machine learning approaches.
This chapter will first review some of the basic machine learning concepts. Then, an introduction to graph machine learning will be provided, with a particular...
