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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. It focuses on methods, algorithms, and design patterns related to graphs. Based on my personal experience on building complex machine learning applications, this book suggests many recipes in which graphs are the main ingredient to prepare a tasty product to your customers. Across the lifecycle of a machine learning project such approaches can be useful under several aspects: managing data sources more efficiently, implement better algorithms, storing the prediction model so that they can be accessed faster, and visualizing the results in a more effective way for further analysis.

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