Model-Based Clustering and Classification for Data Science
2492 Kč
Odesíláme do 5 až 7 dní
Sleva až 70% u třetiny knih
This accessible but rigorous introduction is written for advanced undergraduates and beginning graduate students in data science, as well as researchers and practitioners. It shows how a statistical framework yields sound estimation, testing and prediction methods, using extensive data examples and providing R code for many methods.
Autor: | Bouveyron, Charles; Celeux, Gilles; Murphy, T. Brendan (University College Dublin); Raftery, Adrian E. (University of Wa |
Nakladatel: | Cambridge University Press |
ISBN: | 9781108494205 |
Rok vydání: | CZE |
Jazyk : | Čeština |
Vazba: | CZE |
Počet stran: | CZE |
Mohlo by se vám také líbit..
-
Mining of Massive Datasets
Leskovec, Jure (Stanford University, California); Rajaraman, Anand; Ullman, Jeffrey David (Stanford University, Californ
-
Machine Learning with Neural Networks
Mehlig, Bernhard (Goeteborgs Universitet, Sweden)
-
Quantum Computing for Computer Scien...
Yanofsky, Noson S.
-
Data Mining and Machine Learning
Zaki, Mohammed J.
-
How to Write Good Programs
Stevens, Perdita
-
Purely Functional Data Structures
Okasaki, Chris (Columbia University, New York)
-
Foundations of Data Science
Blum, Avrim; Hopcroft, John (Cornell University, New York); Kannan, Ravi
-
Cambridge International AS & A L...
Piper, Tony
-
Learning Scientific Programming with ...
Hill, Christian
-
Cambridge Series in Statistical and ...
Wainwright, Martin
-
Industry Unbound
Waldman, Ari Ezra (Northeastern University, Boston)
-
A Hands-On Introduction to Data Science
Shah, Chirag (University of Washington)
-
A Level Comp 2 Computer Science OCR
Surrall, Alistair; Hamflett, Adam
-
The Discrete Mathematical Charms of P...
Applegate, David L.; Bixby, Robert E.; Chvatal, Vasek; Cook, William J.
-
Bandit Algorithms
Lattimore, Tor (University of Alberta); Szepesvari, Csaba (University of Alberta)
-
Game Theory Basics
Von Stengel, Rudiger