MARC details
| 000 -LEADER |
|---|
| fixed length control field |
01647pam a2200337 a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
CUTN |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20190906110541.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
120529s2012 enka b 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781107096394 (hbk.) : |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
1107096391 (hbk.) : |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781107422223 (pbk.) : |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
1107422221 (pbk.) : |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781316506110 |
| 041 ## - LANGUAGE CODE |
|---|
| Language |
English |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
ukblcatcopy |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.31 |
| Edition number |
23 |
| Item number |
FLA |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Flach, Peter A. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Machine learning : |
| Remainder of title |
the art and science of algorithms that make sense of data / |
| Statement of responsibility, etc |
Peter Flach. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
Cambridge : |
| Name of publisher, distributor, etc |
Cambridge University Press, |
| Date of publication, distribution, etc |
2012. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvii, 396 p. : |
| Other physical details |
col. ill. ; |
| Dimensions |
26 cm. |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Formerly CIP. |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Title |
1. The ingredients of machine learning --<br/> |
| -- |
2. Binary classification and related tasks --<br/> |
| -- |
3. Beyond binary classification --<br/> |
| -- |
4. Concept learning --<br/> |
| -- |
5. Tree models --<br/> |
| -- |
6. Rule models --<br/> |
| -- |
7. Linear models --<br/> |
| -- |
8. Distance-based models --<br/> |
| -- |
9. Probabilistic models --<br/> |
| -- |
10. Features --<br/> |
| -- |
11. Model ensembles --<br/> |
| -- |
12. Machine learning experiments -- |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
'Machine Learning' brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures, it explains the principles behind these methods in an intuitive yet precise manner and will appeal to novice and experienced readers alike. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Machine learning |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Algorithmes. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
General Books |
| 500 ## - GENERAL NOTE |
|---|
| Institution to which field applies |
Uk |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references and index. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Form subdivision |
Textbooks. |
