Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling...

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Jahan B. Ghasemi (Faculty of Chemistry, University of Tehran, Tehran, Iran)

Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling

Jahan B. Ghasemi (Faculty of Chemistry, University of Tehran, Tehran, Iran)

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English

Elsevier - Health Sciences Division
20 October 2022

Physical chemistry; Machine learning; Pattern recognition

Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling outlines key knowledge in this area, combining critical introductory approaches with the latest advanced techniques. Beginning with an introduction of univariate and multivariate statistical analysis, the book then explores multivariate calibration and validation methods. Soft modeling in chemical data analysis, hyperspectral data analysis, and autoencoder applications in analytical chemistry are then discussed, providing useful examples of the techniques in chemistry applications.

Drawing on the knowledge of a global team of researchers, this book will be a helpful guide for chemists interested in developing their skills in multivariate data and error analysis.

Edited by: Jahan B. Ghasemi (Faculty of Chemistry University of Tehran Tehran Iran)
Imprint: Elsevier - Health Sciences Division
Country of Publication: United States
Dimensions: Height: 229mm, Width: 152mm,
Weight: 450g
ISBN: 9780323904087
ISBN 10: 0323904084
Pages: 216
Publication Date: 20 October 2022
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Dr. Jahan B Ghasemi received his PhD from Shiraz University. He was a visiting Scientist at the University of Chalmers in 2001 and Delaware University in 2006. His current research interests are focused on chemometrics and data analysis and computational drug design. He is the author of more than 200 papers and 4 chapter books in international journals and books.