Fanzhang Li & Li Zhang 
Lie Group Machine Learning [PDF ebook] 

Wsparcie

This book explains deep learning concepts and derives semi-supervised learning and nuclear learning frameworks based on cognition mechanism and Lie group theory. Lie group machine learning is a theoretical basis for brain intelligence, Neuromorphic learning (NL), advanced machine learning, and advanced artifi cial intelligence. The book further discusses algorithms and applications in tensor learning, spectrum estimation learning, Finsler geometry learning, Homology boundary learning, and prototype theory. With abundant case studies, this book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artifi cial intelligence, machine learning, automation, mathematics, management science, cognitive science, financial management, and data analysis. In addition, this text can be used as the basis for teaching the principles of machine learning.




Li Fanzhang


is professor at the Soochow University, China. He is director of network security engineering laboratory in Jiangsu Province and is also the director of the Soochow Institute of industrial large data. He published more than 200 papers, 7 academic monographs, and 4 textbooks.



Zhang Li


is professor at the School of Computer Science and Technology of the Soochow University. She published more than 100 papers in journals and conferences, and holds 23 patents.



Zhang Zhao


is currently an associate professor at the School of Computer Science and Technology of the Soochow University. He has authored and co-authored more than 60 technical papers.

€154.95
Metody Płatności

O autorze

Fanzhang Li, Soochow University, Suzhou, China
Kup ten ebook, a 1 kolejny otrzymasz GRATIS!
Język Angielski ● Format PDF ● Strony 533 ● ISBN 9783110499506 ● Rozmiar pliku 10.2 MB ● Wydawca De Gruyter ● Miasto Berlin/Boston ● Opublikowany 2018 ● Ydanie 1 ● Do pobrania 24 miesięcy ● Waluta EUR ● ID 6966021 ● Ochrona przed kopiowaniem Adobe DRM
Wymaga czytnika ebooków obsługującego DRM

Więcej książek elektronicznych tego samego autora (ów) / Redaktor

16 550 Ebooki w tej kategorii