Machine Learning and Pattern Recognition Methods in Chemistry from Multivariate and Data Driven Modeling
Elsevier - Health Sciences Division (Verlag)
978-0-323-90408-7 (ISBN)
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.
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.
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
Erscheinungsdatum | 28.10.2022 |
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Verlagsort | Philadelphia |
Sprache | englisch |
Maße | 152 x 229 mm |
Gewicht | 450 g |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Naturwissenschaften ► Chemie ► Physikalische Chemie | |
ISBN-10 | 0-323-90408-4 / 0323904084 |
ISBN-13 | 978-0-323-90408-7 / 9780323904087 |
Zustand | Neuware |
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