Understanding machine learning : (Record no. 89907)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 01921cam a2200241 i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 18053648 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20170107110154.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 140304s2014 nyua b 001 0 eng |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781107057135 (hardback) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 1107057132 (hardback) |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | PK-LaUMT |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 |
| Edition number | 23 |
| Item number | SHA-U |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Shalev-Shwartz, Shai |
| 245 10 - TITLE STATEMENT | |
| Title | Understanding machine learning : |
| Remainder of title | from theory to algorithms / |
| Statement of responsibility, etc | Shai Shalev-Shwartz and Shai Ben-David |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc | New York : |
| Name of publisher, distributor, etc | Cambridge University Press, |
| Date of publication, distribution, etc | 2014 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xvi, 397 pages : |
| Other physical details | illustrations ; |
| Dimensions | 26 cm |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | "Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics of the field, the book covers a wide array of central topics that have not been addressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for an advanced undergraduate or beginning graduate course, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics, and engineering"-- |
| 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 | Algorithms. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | COMPUTERS / Computer Vision & Pattern Recognition. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Ben-David, Shai. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Home library | Current library | Date acquired | Full call number | Barcode | Date last seen | Price effective from | Koha item type | Copy number |
|---|---|---|---|---|---|---|---|---|---|---|---|
| UMT Main Campus | UMT Main Campus | 2017-01-07 | 006.31 SHA-U | 104170 | 2026-03-06 | 2017-01-07 | Books | ||||
| UMT Main Campus | UMT Main Campus | 2017-01-07 | 006.31 SHA-U | 104171 | 2026-02-09 | 2017-01-07 | Books | C. 2 |