O tej e-knjigi
'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data from proteomics, and simulated data. High-dimension low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code, and problem sets complete the package. Suitable for master's/graduate students in statistics and researchers in data-rich disciplines.
O avtorju
Inge Koch is Associate Professor of Statistics at the University of Adelaide, Australia.
Ocenite to e-knjigo
Povejte nam svoje mnenje.
Informacije o branju
Pametni telefoni in tablični računalniki
Namestite aplikacijo Knjige Google Play za Android in iPad/iPhone. Samodejno se sinhronizira z računom in kjer koli omogoča branje s povezavo ali brez nje.
Prenosni in namizni računalniki
Poslušate lahko zvočne knjige, ki ste jih kupili v Googlu Play v brskalniku računalnika.
Bralniki e-knjig in druge naprave
Če želite brati v napravah, ki imajo zaslone z e-črnilom, kot so e-bralniki Kobo, morate prenesti datoteko in jo kopirati v napravo. Podrobna navodila za prenos datotek v podprte bralnike e-knjig najdete v centru za pomoč.
