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Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes)
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Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes)

Book Details

Format Hardback or Cased Book
ISBN-10 9811204446
ISBN-13 9789811204449
Publisher World Scientific Publishing Co Pte Ltd
Imprint World Scientific Publishing Co Pte Ltd
Country of Manufacture GB
Country of Publication GB
Publication Date May 12th, 2020
Print length 1000 Pages
Weight 2,050 grams
Dimensions 18.10 x 25.40 x 6.50 cms
Product Classification: Data capture & analysis
Ksh 162,000.00
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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.
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.

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