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Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes)
- Publication Year :
- 2019
-
Abstract
- This compendium provides a comprehensive collection of the emergent applications of big data, machine learning, and artificial intelligence technologies to present day physical sciences ranging from materials theory and imaging to predictive synthesis and automated research. This area of research is among the most rapidly developing in the last several years in areas spanning materials science, chemistry, and condensed matter physics.Written by world renowned researchers, the compilation of two authoritative volumes provides a distinct summary of the modern advances in instrument — driven data generation and analytics, establishing the links between the big data and predictive theories, and outlining the emerging field of data and physics-driven predictive and autonomous systems.
- Subjects :
- Photoemission
Synchrotron radiation
Powders
Diffraction
Cyberinfrastructure
Identification
Differential equations, Nonlinear
Machine learning
Big data
Physical sciences--Data processing
Visual analytics
Artificial intelligence
Mathematics
Materials--Analysis
Simulation methods
Matter--Constitution
Materials
Communication in science
Computer network resources
Application software--Development
Computer software--Development
Molecular structure
Tomography
Subjects
Details
- Language :
- English
- ISBNs :
- 9789811204449 and 9789811204531
- Volume :
- 00001
- Database :
- eBook Index
- Journal :
- Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes)
- Publication Type :
- eBook
- Accession number :
- 2600949