Materials Data Science

Discover the cutting-edge world of Materials Data Science by Stefan Sandfeld, published by Springer International Publishing AG in 2024. This comprehensive hardback edition spans an impressive 618 pages and serves as an essential resource for anyone interested in the intersection of data science and materials engineering.

This insightful text delves into critical topics such as data science, machine learning, and deep learning, tailored specifically for the materials science field. With numerous practical examples and applications, readers will gain a solid understanding of how these advanced techniques can be applied to real-world challenges. The section on unsupervised learning highlights principal component analysis and explores advanced methods like manifold learning (t-SNE and UMAP) and various clustering techniques.

Whether you are a student, researcher, or industry professional, Materials Data Science is a must-have addition to your library, equipping you with the knowledge to leverage data science in materials innovation.