The book "Machine Learning in 2D Materials Science" is a comprehensive guide to the application of machine learning techniques in the field of two-dimensional materials science. The author, a renowned expert in the field, provides a detailed overview of the current state of the art in machine learning algorithms and their applications in the study of 2D materials. The book covers topics such as the use of deep learning methods for predicting the properties of 2D materials, the development of new materials using machine learning algorithms, and the integration of machine learning into existing materials science tools. The book begins by discussing the challenges of studying 2D materials and the need for new approaches to understanding their behavior. The author highlights the limitations of traditional methods and the potential of machine learning to revolutionize the field. The book then delves into the fundamentals of machine learning, providing readers with a solid foundation for understanding the concepts and techniques presented later in the book. The main part of the book is divided into three sections. The first section focuses on the application of machine learning to the prediction of material properties, such as electronic structure, mechanical properties, and optical properties.

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