Graph Machine Learning: Take graph data to the next level by applying machine learning techniques and algorithms

Graph Machine Learning is a comprehensive guide to building machine learning models using graph data.

With this book, you'll learn how to identify relationships between nodes in order to make better business decisions and apply graph-based machine learning methods to solve real-life problems.

You'll start by understanding the basics of graph theory and machine learning, followed by practical examples of implementing machine learning models for graph representation learning.

The book covers a wide range of supervised and unsupervised learning applications, including data processing, model training, and prediction.

By the end of this book, you will have learned essential concepts of graph theory and all the algorithms and techniques used to build successful machine learning applications.