TY  - BOOK
AU  - Krishnan,N.M.Anoop
AU  - Kodamana,Hariprasad
AU  - Bhattoo,Ravinder
ED  - SpringerLink (Online service)
TI  - Machine Learning for Materials Discovery: Numerical Recipes and Practical Applications 
T2  - Machine Intelligence for Materials Science,
SN  - 9783031446221
AV  - TA404.23 
PY  - 2024///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Materials science
KW  - Data processing
KW  - Machine learning
KW  - System theory
KW  - Mathematical physics
KW  - Ceramic materials
KW  - Computational Materials Science
KW  - Machine Learning
KW  - Complex Systems
KW  - Theoretical, Mathematical and Computational Physics
KW  - Ceramics
N1  - Part I: Introduction -- Part II: Basics of Machine Learning Methods -- Introduction to Data-Based Modeling -- Model Development -- Introduction to Machine Learning -- Quick Dive into Probabilistic Methods -- Optimization -- Part III: Application in Glass Science -- Property Prediction -- Glass Discovery -- Understanding Glass Physics -- Atomistic Modeling -- Future Directions
N2  - Focusing on the fundamentals of machine learning, this book covers broad areas of data-driven modeling, ranging from simple regression to advanced machine learning and optimization methods for applications in materials modeling and discovery. The book explains complex mathematical concepts in a lucid manner to ensure that readers from different materials domains are able to use these techniques successfully. A unique feature of this book is its hands-on aspect—each method presented herein is accompanied by a code that implements the method in open-source platforms such as Python. This book is thus aimed at graduate students, researchers, and engineers to enable the use of data-driven methods for understanding and accelerating the discovery of novel materials
UR  - https://doi.org/10.1007/978-3-031-44622-1
ER  -