115,95 €*
Versandkostenfrei per Post / DHL
Lieferzeit 1-2 Wochen
Tongyi Zhang, born in October 1949 in Zhengzhou, China, is Expert in the interdisciplinary area of materials science and engineering and solid mechanics. He received his Ph.D. in 1985 in materials physics from the University of Science and Technology Beijing, China. He was Research Fellow of the Alexander von Humboldt Foundation, 1986-1988, Germany; Postdoctoral Fellow, 1988-1990, University of Rochester; and Associate Research Scientist, 1990-1993, Yale University. From 1993 to 2015, he worked at the Hong Kong University of Science and Technology, as Lecturer, Associate Professor, Professor, Chair Professor, and Fang Professor of Engineering.
He is the founding dean of Materials Genome Institute, Shanghai University, and the founding director of the Materials Genome Engineering division in the Chinese Materials Research Society (CMRS). Currently he is doing his best to promote Materials Genome Engineering and Materials/Mechanics Informatics, especially, materials AI labs, materials AI computations, and materials large multimodal model. He is the Vice President of the International Congress on Fracture, the Honorary President of the Chinese Society for Corrosion and Protection, and was the Vice President of the Far East and Oceanic Fracture Society. He is the founding Editor-in-Chief of Journal of Materials Informatics and was the Editor-in-Chief of Science China Technological Sciences 2018-2022. He became Fellow of International Congress on Fracture in 2013, Fellow of the Hong Kong Academy of Engineering Sciences in 2012, Member of Chinese Academy of Sciences in 2011, Senior Research Fellow of Croucher Foundation, Hong Kong, in 2003, Fellow of ASM International, USA, in 2001. He received the awards including the 2018 Prize for Scientific and Technological Progress from the HLHL Foundation, the Second Prizes of 2007 and 1987 State Natural Science Award, China, and the 1988 National Award for Young Scientists, China.Introduction.- Linear Regression.- Linear Classification.- Support Vector Machine.- Decision Tree and K-Nearest-Neighbors (KNN).- Ensemble Learning.- Bayesian Theorem and Expectation-Maximization (EM) Algorithm.- Symbolic Regression.- Neural Networks.- Hidden Markov Chains.- Data Preprocessing and Feature Selection.- Interpretative SHAP Value and Partial Dependence Plot.
| Erscheinungsjahr: | 2025 |
|---|---|
| Fachbereich: | Allgemeines |
| Genre: | Importe, Technik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Buch |
| Inhalt: |
xvi
479 S. 11 s/w Illustr. 126 farbige Illustr. 479 p. 137 illus. 126 illus. in color. |
| ISBN-13: | 9789819979912 |
| ISBN-10: | 9819979919 |
| Sprache: | Englisch |
| Einband: | Gebunden |
| Autor: | Zhang, Tongyi |
| Hersteller: |
Springer Singapore
Springer Nature Singapore |
| Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
| Maße: | 241 x 160 x 33 mm |
| Von/Mit: | Tongyi Zhang |
| Erscheinungsdatum: | 28.02.2025 |
| Gewicht: | 0,902 kg |
Tongyi Zhang, born in October 1949 in Zhengzhou, China, is Expert in the interdisciplinary area of materials science and engineering and solid mechanics. He received his Ph.D. in 1985 in materials physics from the University of Science and Technology Beijing, China. He was Research Fellow of the Alexander von Humboldt Foundation, 1986-1988, Germany; Postdoctoral Fellow, 1988-1990, University of Rochester; and Associate Research Scientist, 1990-1993, Yale University. From 1993 to 2015, he worked at the Hong Kong University of Science and Technology, as Lecturer, Associate Professor, Professor, Chair Professor, and Fang Professor of Engineering.
He is the founding dean of Materials Genome Institute, Shanghai University, and the founding director of the Materials Genome Engineering division in the Chinese Materials Research Society (CMRS). Currently he is doing his best to promote Materials Genome Engineering and Materials/Mechanics Informatics, especially, materials AI labs, materials AI computations, and materials large multimodal model. He is the Vice President of the International Congress on Fracture, the Honorary President of the Chinese Society for Corrosion and Protection, and was the Vice President of the Far East and Oceanic Fracture Society. He is the founding Editor-in-Chief of Journal of Materials Informatics and was the Editor-in-Chief of Science China Technological Sciences 2018-2022. He became Fellow of International Congress on Fracture in 2013, Fellow of the Hong Kong Academy of Engineering Sciences in 2012, Member of Chinese Academy of Sciences in 2011, Senior Research Fellow of Croucher Foundation, Hong Kong, in 2003, Fellow of ASM International, USA, in 2001. He received the awards including the 2018 Prize for Scientific and Technological Progress from the HLHL Foundation, the Second Prizes of 2007 and 1987 State Natural Science Award, China, and the 1988 National Award for Young Scientists, China.Introduction.- Linear Regression.- Linear Classification.- Support Vector Machine.- Decision Tree and K-Nearest-Neighbors (KNN).- Ensemble Learning.- Bayesian Theorem and Expectation-Maximization (EM) Algorithm.- Symbolic Regression.- Neural Networks.- Hidden Markov Chains.- Data Preprocessing and Feature Selection.- Interpretative SHAP Value and Partial Dependence Plot.
| Erscheinungsjahr: | 2025 |
|---|---|
| Fachbereich: | Allgemeines |
| Genre: | Importe, Technik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Buch |
| Inhalt: |
xvi
479 S. 11 s/w Illustr. 126 farbige Illustr. 479 p. 137 illus. 126 illus. in color. |
| ISBN-13: | 9789819979912 |
| ISBN-10: | 9819979919 |
| Sprache: | Englisch |
| Einband: | Gebunden |
| Autor: | Zhang, Tongyi |
| Hersteller: |
Springer Singapore
Springer Nature Singapore |
| Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
| Maße: | 241 x 160 x 33 mm |
| Von/Mit: | Tongyi Zhang |
| Erscheinungsdatum: | 28.02.2025 |
| Gewicht: | 0,902 kg |
Ähnliche Produkte
Lieferzeit 1-2 Wochen
Lieferzeit 2-4 Werktage
Lieferzeit 1-2 Wochen
Lieferzeit 1-2 Wochen
Lieferzeit 1-2 Werktage
Lieferzeit 1-2 Wochen
Lieferzeit 1-2 Wochen
Lieferzeit 1-2 Wochen
Lieferzeit 2-4 Werktage