Graph Neural Networks in Python

Build creative and powerful applications using graph data and become an expert in graph neural networks!

Just ten years after their emergence, graph neural networks have become one of the most interesting architectures in deep learning. Tech companies are trying to apply them everywhere: in drug development, food recommendation systems, video and romantic partner searches, and for detecting fake news. This book presents the basics of graph theory for data science and machine learning, as well as practical tasks that are solved using graph neural networks.

As you read, you will discover a whole range of previously unknown applications of machine learning and create a professional portfolio.

Students, data science specialists, and experts in machine and deep learning will find clear and illustrated explanations in the book with code and notebooks to quickly get started. Basic knowledge of Python and linear algebra will be helpful for studying the material.