Machine Learning and Data Analysis in Soft Matter Physics

Machine learning and data analysis techniques have found their place in soft matter physics, aiding in the understanding of complex molecular systems, self-assembly, and materials design. These tools facilitate the analysis of large-scale molecular simulations and experimental data, providing insights into the behavior and properties of soft materials. This book examines the application of machine learning and data analysis techniques in studying soft matter physics and its complex behavior.

Print ISBN: 9781682519974 | $165 | 2024 | Hardcover

Subject: Physics

Editor: George Ecker

About the Editor: George Eckert, a distinguished researcher with a PhD in AI, specializes in Decision Sciences and Information Systems. His expertise lies in machine learning and data analysis. In the realm of soft matter physics, these skills are instrumental. By applying machine learning algorithms to vast datasets, researchers can extract patterns and insights that might otherwise remain hidden. George's impressive track record in teaching and training individuals from multinational corporations underscores the importance of his work in this cutting-edge field.