A First Course in Random Matrix Theory
2074 Kč
Odesíláme do 3 až 5 dní
Sleva až 70% u třetiny knih
Classical statistical tools that handled real-life data have become inadequate upon the emergence of Big Data. Random matrix theory and free calculus introduced here present valuable solutions to the complex challenges posed by large datasets. Real world applications make it an essential tool for physicists, engineers, data analysts and economists.
| Autor: | Bouchaud, Jean-Philippe (Centre Commissariat ... l'Energie Atomique (CEA), Saclay); Potters, Marc |
| Nakladatel: | Cambridge University Press |
| ISBN: | 9781108488082 |
| Rok vydání: | 2020 |
| Jazyk : | Angličtina |
| Vazba: | Hardback |
| Počet stran: | 370 |
Mohlo by se vám také líbit..
-
Quantum Computing for Computer Scien...
Yanofsky, Noson S.
-
Learning Scientific Programming with ...
Hill, Christian
-
Mining of Massive Datasets
Leskovec, Jure (Stanford University, California); Rajaraman, Anand; Ullman, Jeffrey David (Stanford University, Californ
-
Machine Learning for Asset Managers
De Prado, Lopez
-
A Hands-On Introduction to Data Science
Shah, Chirag (University of Washington)
-
Bandit Algorithms
Lattimore, Tor (University of Alberta); Szepesvari, Csaba (University of Alberta)
-
Mastering Mathematical Finance
Capinski, Maciej J.; Kopp, Ekkehard
-
Integer Linear Programming in Comput...
Gusfield, Dan (University of California, Davis)
-
A/AS Level Computer Science for WJEC...
Surrall, Alistair; Hamflett, Adam
-
Modern Statistics for Modern Biology
Holmes, Susan (Stanford University, California); Huber, Wolfgang
-
Foundations of Cryptography: Volume ...
Goldreich, Oded
-
Machine Learning Refined
Watt, Jeremy (Northwestern University, Illinois); Borhani, Reza (Northwestern University, Illinois); Katsaggelos, Aggelo
-
Foundations of Data Science
Blum, Avrim; Hopcroft, John (Cornell University, New York); Kannan, Ravi
-
Modern Compiler Implementation in ML
Appel, Andrew W.
-
Model-Based Clustering and Classific...
Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan (University College Dublin); Raftery, Adrian E. (University of Wa
-
Machine Learning with Neural Networks
Mehlig, Bernhard (Goeteborgs Universitet, Sweden)
