Machine learning
a probabilistic perspective
By Kevin P. Murphy and Kevin P. Murphy
"Machine learning" is published by MIT Press in 2012 - Cambridge, MA, it has 1104 pages and the language of the book is English.
“Machine learning” Metadata:
- Title: Machine learning
- Authors: Kevin P. MurphyKevin P. Murphy
- Language: English
- Number of Pages: 1104
- Publisher: MIT Press
- Publish Date: 2012
- Publish Location: Cambridge, MA
“Machine learning” Subjects and Themes:
- Subjects: ➤ Probabilities - Machine learning - Probability - Apprentissage automatique - Probabilités - COMPUTERS - Enterprise Applications - Business Intelligence Tools - Intelligence (AI) & Semantics - Machine-learning - Q325.5 .m87 2012 - 006.3/1
Edition Specifications:
- Pagination: p. cm.
Edition Identifiers:
- The Open Library ID: OL25259559M - OL16571885W
- Online Computer Library Center (OCLC) ID: 810414751 - 781277861
- Library of Congress Control Number (LCCN): 2012004558
- ISBN-13: 9780262018029
- All ISBNs: 9780262018029
AI-generated Review of “Machine learning”:
"Machine learning" Description:
The Open Library:
"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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