This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches, which rely on optimization techniques, as well as Bayesian inference, which is based on a hierarchy of probabilistic models. The book presents the major machine learning methods as they have been developed in different disciplines, such as statistics, statistical and adaptive signal processing and computer science. Focusing on the physical reasoning behind the mathematics, all the various methods and techniques are explained in depth, supported by examples and problems, giving an invaluable resource to the student and researcher for understanding and applying machine learning concepts. The book builds carefully from the basic classical methods to the most recent trends, with chapters written to be as self-contained as possible, making the text suitable for different courses: pattern recognition, statistical/adaptive signal processing, statistical/Bayesian learning, as well as short courses on sparse modeling, deep learning, and probabilistic graphical models.
Produktkennzeichnungen
ISBN-10
0128015225
ISBN-13
9780128015223
eBay Product ID (ePID)
211362974
Produkt Hauptmerkmale
Produktart
Lehrbuch
Sprache
Englisch
Anzahl der Seiten
Xxi Seiten
Verlag
Elsevier Ltd, Oxford
Publikationsname
Machine Learning
Autor
Sergios Theodoridis
Format
Gebundene Ausgabe
Erscheinungsjahr
2015
Zusätzliche Produkteigenschaften
Hörbuch
No
Item Length
24cm
Item Height
6cm
Item Width
19cm
Item Weight
2kg
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