| LDR | | 03272cmm uu200553Ia 4500 |
| 001 | | 000000301441 |
| 003 | | OCoLC |
| 005 | | 20230519143114 |
| 006 | | m o d |
| 007 | | cr |n| |
| 008 | | 120919s2012 maua ob 001 0 eng d |
| 020 | |
▼a 9780262305242 (electronic bk.) |
| 020 | |
▼a 0262305240 (electronic bk.) |
| 020 | |
▼z 9780262018029 (hardcover : alk. paper) |
| 020 | |
▼z 0262018020 (hardcover : alk. paper) |
| 029 | 1 |
▼a AU@
▼b 000050203647 |
| 029 | 1 |
▼a NZ1
▼b 14792486 |
| 029 | 1 |
▼a NLGGC
▼b 351162631 |
| 035 | |
▼a (OCoLC)810414751 |
| 040 | |
▼a YDXCP
▼c YDXCP
▼d OCLCO
▼d E7B
▼d N$T
▼d GZM
▼d OCLCQ
▼d OSU
▼d NLGGC
▼d COO
▼d ZCU
▼d OCLCF
▼d 248032 |
| 049 | |
▼a K4RA |
| 050 | 4 |
▼a Q325.5
▼b .M87 2012 |
| 072 | 7 |
▼a COM
▼x 005030
▼2 bisacsh |
| 072 | 7 |
▼a COM
▼x 004000
▼2 bisacsh |
| 082 | 04 |
▼a 006.3/1
▼2 23 |
| 100 | 1 |
▼a Murphy, Kevin P.,
▼d 1970- |
| 245 | 10 |
▼a Machine learning
▼h [electronic resource] :
▼b a probabilistic perspective /
▼c Kevin P. Murphy. |
| 260 | |
▼a Cambridge, Mass. :
▼b MIT Press,
▼c c2012 |
| 300 | |
▼a 1 online resource (xxix, 1067 p.) :
▼b ill. (chiefly col.) |
| 490 | 1 |
▼a Adaptive computation and machine learning series |
| 504 | |
▼a Includes bibliographical references and indexes. |
| 520 | |
▼a "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. |
| 650 | 0 |
▼a Machine learning. |
| 650 | 0 |
▼a Probabilities. |
| 650 | 7 |
▼a COMPUTERS / Enterprise Applications / Business Intelligence Tools.
▼2 bisacsh |
| 650 | 7 |
▼a COMPUTERS / Intelligence (AI) & Semantics.
▼2 bisacsh |
| 650 | 17 |
▼a Machine-learning.
▼2 gtt |
| 650 | 7 |
▼a Machine learning.
▼2 fast
▼0 (OCoLC)fst01004795 |
| 650 | 7 |
▼a Probabilities.
▼2 fast
▼0 (OCoLC)fst01077737 |
| 655 | 7 |
▼a Electronic books.
▼2 local |
| 655 | 4 |
▼a Electronic books. |
| 776 | 08 |
▼i Print version:
▼a Murphy, Kevin P., 1970-
▼t Machine learning.
▼d Cambridge, Mass. : MIT Press, c2012
▼z 0262018020
▼w (DLC) 2012004558
▼w (OCoLC)781277861 |
| 830 | 0 |
▼a Adaptive computation and machine learning. |
| 856 | 40 |
▼3 EBSCOhost
▼u http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=480968 |
| 938 | |
▼a YBP Library Services
▼b YANK
▼n 9644170 |
| 938 | |
▼a ebrary
▼b EBRY
▼n ebr10597102 |
| 938 | |
▼a EBSCOhost
▼b EBSC
▼n 480968 |
| 990 | |
▼a 관리자 |
| 994 | |
▼a 92
▼b K4R |