Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling
- 1st Edition - October 20, 2022
- Latest edition
- Editor: Jahan B. Ghasemi
- Language: English
Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling outlines key knowledge in this area, combining critical introduct… Read more
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Description
Description
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.
Key features
Key features
- 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
Readership
Readership
Students, teachers and researchers across chemistry interested in developing their data analysis skills
Table of contents
Table of contents
1. Statistical Methods in Chemical Data Analysis
2. Multivariate Predictive Modeling and Validation
3. Multivariate Pattern Recognition by Machine Learning Methods
4. Tuning the Apparent Thermodynamic Parameters of Chemical Systems
5. The Analytical/Measurement Sources of Multivariate Errors
6. Autoencoders in Analytical Chemistry
7. Uniqueness in Resolving Multivariate Chemical Data
Appendix 1. Introduction to Python
Product details
Product details
- Edition: 1
- Latest edition
- Published: October 20, 2022
- Language: English
About the editor
About the editor
JG