Anbieter: World of Books (was SecondSale), Montgomery, IL, USA
Zustand: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.
Sprache: Englisch
Verlag: The MIT Press (edition Illustrated), 2012
ISBN 10: 0262018020 ISBN 13: 9780262018029
Anbieter: BooksRun, Philadelphia, PA, USA
Hardcover. Zustand: Very Good. Illustrated. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
Anbieter: World of Books (was SecondSale), Montgomery, IL, USA
Zustand: Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.
Anbieter: Anybook.com, Lincoln, Vereinigtes Königreich
EUR 60,41
Anzahl: 1 verfügbar
In den WarenkorbZustand: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,2050grams, ISBN:9780262018029.
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Anbieter: WorldofBooks, Goring-By-Sea, WS, Vereinigtes Königreich
EUR 92,59
Anzahl: 1 verfügbar
In den WarenkorbPaperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Anbieter: medimops, Berlin, Deutschland
Zustand: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.
EUR 99,19
Anzahl: 1 verfügbar
In den WarenkorbHRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
EUR 109,02
Anzahl: 3 verfügbar
In den WarenkorbZustand: New. pp. 1104 465 Illus. (300 Col.).
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 110,89
Anzahl: 1 verfügbar
In den WarenkorbZustand: New. In.
EUR 84,95
Anzahl: 1 verfügbar
In den WarenkorbZustand: NEW.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 120,84
Anzahl: 3 verfügbar
In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 1104 pages. 9.10x8.10x1.70 inches. In Stock.
Zustand: New. Kevin P. Murphy is a Senior Staff Research Scientist at Google Research.A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.Today s Web-enabled deluge of electronic data calls fo.
Hardcover. Zustand: Sehr gut. Gebraucht - Sehr gut Sg - leichte Beschädigungen, Verschmutzungen, ungelesenes Mängelexemplar, gestempelt - A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package PMTK (probabilistic modeling toolkit) that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
Zustand: New. 2012. 1st Edition. Hardcover. Series: Adaptive Computation and Machine Learning Series. Num Pages: 1104 pages, 300 color illus., 165 b&w illus. BIC Classification: UYQM. Category: (G) General (US: Trade). Dimension: 241 x 213 x 44. Weight in Grams: 1958. . . . . . Books ship from the US and Ireland.
Buch. Zustand: Neu. Neuware - A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package PMTK (probabilistic modeling toolkit) that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
Buch. Zustand: Neu. Machine Learning | A Probabilistic Perspective | Kevin P. Murphy | Buch | Machine Learning | Einband - fest (Hardcover) | Englisch | 2016 | MIT Press Ltd | EAN 9780262018029 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Anbieter: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, Deutschland
Zustand: gut. 2012. Machine Learning - A Probabilistic Perspective In englischer Sprache. pages.