| 000 -LEADER |
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| fixed length control field |
nam a22 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20191203151558.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
191126b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780262018029 |
| 040 ## - CATALOGING SOURCE |
|---|
| Transcribing agency |
AIKTC-KRRC |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
ENG |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Edition number |
DDC23 |
| Item number |
MUR |
| Classification number |
006.31 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| 9 (RLIN) |
10681 |
| Personal name |
Murphy, Kevin P. |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Machine learning |
| Remainder of title |
: A probabilistic perspective |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
London |
| Name of publisher, distributor, etc. |
MIT Press |
| Date of publication, distribution, etc. |
2012 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxix, 1071p. |
| Other physical details |
| Binding- Hard Bound | |
| Dimensions |
23.5*20.8 cm |
| 440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| 9 (RLIN) |
10248 |
| Title |
Adaptive computation and machine learning |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
oday'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. |
| Expansion of summary note |
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. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| 9 (RLIN) |
4619 |
| Topical term or geographic name entry element |
EXTC Engineering |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Koha item type |
Text Books |
