Kernel Methods and Machine Learning
7
%
2329 Kč 2 493 Kč
Sleva až 70% u třetiny knih
Containing numerous algorithms and major theorems, this step-by-step guide covers the fundamentals of kernel-based learning theory. Including over two hundred problems and real-world examples, it is an essential resource for graduate students and professionals in computer science, electrical and biomedical engineering. Solutions to problems are provided online for instructors.
Autor: | Kung, S. Y. (Princeton University, New Jersey) |
Nakladatel: | Cambridge University Press |
ISBN: | 9781107024960 |
Rok vydání: | CZE |
Jazyk : | Čeština |
Vazba: | CZE |
Počet stran: | CZE |
Mohlo by se vám také líbit..
-
Mathematics for Machine Learning
Deisenroth, Marc Peter (University College London); Faisal, A. Aldo (Imperial College London); Ong, Cheng Soon
-
Mining of Massive Datasets
Leskovec, Jure (Stanford University, California); Rajaraman, Anand; Ullman, Jeffrey David (Stanford University, Californ
-
Quantum Computing for Computer Scien...
Yanofsky, Noson S.
-
Machine Learning for Asset Managers
De Prado, Lopez
-
Learning Scientific Programming with ...
Hill, Christian
-
Industry Unbound
Waldman, Ari Ezra (Northeastern University, Boston)
-
Thinking Functionally with Haskell
Richard Bird
-
Applied Stochastic Differential Equat...
Sarkka, Simo (Aalto University, Finland); Solin, Arno (Aalto University, Finland)
-
Machine Learning with Neural Networks
Mehlig, Bernhard (Goeteborgs Universitet, Sweden)
-
Integer Linear Programming in Comput...
Gusfield, Dan (University of California, Davis)
-
Language, Cognition, and Computation...
-
Introduction to Applied Linear Algebra
Boyd, Stephen P.
-
Wireless Communications and Networkin...
Saad, Walid (Virginia Polytechnic Institute and State University); Bennis, Mehdi (University of Oulu, Finland); Mozaffar
-
How to Prove It
-
How to Write Good Programs
Stevens, Perdita
-
A/AS Level Computer Science for WJEC...
Surrall, Alistair; Hamflett, Adam