Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling
Language: English
Published by Elsevier Science & Technology, Elsevier, 2022
- Softcover
- New
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
AbeBooks seller since January 11, 2012
Condition: New
£ 154.52
Quantity: 2 available
Add to basketItem description from seller
This item is printed on demand - it takes 3-4 days longer - Neuware -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. Englisch.
Seller Inventory # 9780323904087
- Title
- Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling
- Author
- Jahan B. Ghasemi
- Publisher
- Elsevier Science & Technology, Elsevier
- Publication year
- 2022
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0323904084
- ISBN 13
- 9780323904087
- Item weight
- 350 grams
- Dimensions
- 229x152x10 mm
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.
- Provides an introductory overview of statistical methods for the analysis and interpretation of chemical data
- Discusses the use of machine learning for recognizing patterns in multidimensional chemical data
- Identifies common sources of multivariate errors
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
BuchWeltWeit Ludwig Meier e.K.
Bergisch Gladbach, Germany
AbeBooks seller since January 11, 2012
Shipping rates from Germany to U.S.A.
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