Sprache: Englisch
Verlag: Cambridge University Press, 2008
ISBN 10: 0521717701 ISBN 13: 9780521717700
Anbieter: Better World Books Ltd, Dunfermline, Vereinigtes Königreich
Erstausgabe
EUR 7,17
Anzahl: 1 verfügbar
In den WarenkorbZustand: Very Good. 1st Edition. Ships from the UK. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects.
Sprache: Englisch
Verlag: Cambridge University Press, 2009
ISBN 10: 0521717701 ISBN 13: 9780521717700
Anbieter: Anybook.com, Lincoln, Vereinigtes Königreich
EUR 36,29
Anzahl: 1 verfügbar
In den WarenkorbZustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. Clean from markings. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780521717700.
Sprache: Englisch
Verlag: Cambridge University Press, 2012
ISBN 10: 0521717701 ISBN 13: 9780521717700
Anbieter: Buchpark, Trebbin, Deutschland
Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 416 | Sprache: Englisch | Produktart: Bücher | Known for his hype-free approach to neural networks, Brian Ripley here provides an excellent text on the statistics of pattern classifiers and the application of neural techniques.Ripley's text will be rightly popular with newcomers to the area for its ability to present the mathematics of statistical pattern recognition and neural networks in an accessible format and engaging style.
Sprache: Englisch
Verlag: Cambridge University Press, 2008
ISBN 10: 0521717701 ISBN 13: 9780521717700
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This 1996 book is a reliable account of the statistical framework for pattern recognition and machine learning. With unparalleled coverage and a wealth of case-studies this book gives valuable insight into both the theory and the enormously diverse applications (which can be found in remote sensing, astrophysics, engineering and medicine, for example). So that readers can develop their skills and understanding, many of the real data sets used in the book are available from the author's website: stats.ox.ac.uk/~ripley/PRbook/. For the same reason, many examples are included to illustrate real problems in pattern recognition. Unifying principles are highlighted, and the author gives an overview of the state of the subject, making the book valuable to experienced researchers in statistics, machine learning/artificial intelligence and engineering. The clear writing style means that the book is also a superb introduction for non-specialists.