Machine learning : a probabilistic perspective / Kevin P Murphy
By: Murphy, Kevin P
Material type:
TextPublisher: Cambridge, Mass. : MIT Press, c2012Description: xxvii, 1071 p.: ills., pic., chat.; 23 cmISBN: 9780262018029Subject(s): Computer -- Enterprise Applications -- Business Intelligence ToolsDDC classification: 006.31 Summary: "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"--Back cover.
| Item type | Current location | Home library | Collection | Call number | Vol info | Copy number | Status | Date due | Barcode | Item holds | ||||||||||||
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Southeast University Central Library
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Southeast University Central Library
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Non-fiction | 006.31 M978m (Browse shelf) | 2012 | C- 1 | Available | 019376 | ||||||||||||||
| Books |
Southeast University Central Library
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Southeast University Central Library
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Non-fiction | 006.31 M978m (Browse shelf) | 2012 | C- 2 | Available | 019377 | ||||||||||||||
| Books |
Southeast University Central Library
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Southeast University Central Library
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Non-fiction | 006.31 M978m (Browse shelf) | 2012 | C- 3 | In transit from Southeast University Central Library to Computer Science & Engineering Seminar Library since 01/07/2018 | 019378 | ||||||||||||||
| Books |
Southeast University Central Library
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|
Southeast University Central Library
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Non-fiction | 006.31 M978m (Browse shelf) | 2012 | C- 4 | Available | 019379 | ||||||||||||||
| Books |
Southeast University Central Library
Library service hours:
|
Southeast University Central Library
Library service hours:
|
Non-fiction | 006.31 M978m (Browse shelf) | 2012 | C- 5 | Available | 019380 |
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| 006.3 W783a Artificial intelligence / | 006.31 A457i Introduction to machine learning / | 006.31 M692m Machine learning / | 006.31 M978m Machine learning : a probabilistic perspective / | 006.31 M978m Machine learning : a probabilistic perspective / | 006.31 M978m Machine learning : a probabilistic perspective / | 006.31 M978m Machine learning : a probabilistic perspective / |
include index and bibliography.
"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"--Back cover.
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