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Machine Learning

A Probabilistic Perspective

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.
Portrait
Kevin P. Murphy is a Research Scientist at Google. Previously, he was Associate Professor of Computer Science and Statistics at the University of British Columbia.
Zitat
"This comprehensive book should be of great interest to learners and practitioners in the field of machine learning." -- British Computer Society
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Produktdetails


Einband gebundene Ausgabe
Seitenzahl 1104
Erscheinungsdatum 18.09.2012
Sprache Englisch
ISBN 978-0-262-01802-9
Reihe Adaptive Computation and Machine Learning Series
Verlag MIT Press Ltd
Maße (L/B/H) 241/213/44 mm
Gewicht 1984
Buch (gebundene Ausgabe, Englisch)
Fr. 89.90
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