MARC details
| 000 -LEADER |
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| fixed length control field |
01992nmm a2200265Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20240522134847.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
220920s9999||||xx |||||||||||||| ||und|| |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781107298019 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
IITJ |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.31 |
| Item number |
Sh93U |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Shalev-Shwartz, Shai |
| Relator term |
Author |
| Language of a work |
English |
| 9 (RLIN) |
1866 |
| 245 #0 - TITLE STATEMENT |
|---|
| Title |
Understanding Machine Learning |
| Remainder of title |
: From Theory to Algorithms |
| Statement of responsibility, etc. |
/ by Shai Shalev-Shwartz and Shai Ben-David. |
| Medium |
[Electronic Resource] |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Cambridge |
| Name of publisher, distributor, etc. |
: Cambridge University Press, |
| Date of publication, distribution, etc. |
2014 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvi, 397p. |
| 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 a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics unaddressed 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 advanced undergraduates or beginning graduates, 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 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Computer Science |
| 9 (RLIN) |
926 |
|
|---|
| Topical term or geographic name entry element |
Machine Learning |
| 9 (RLIN) |
15726 |
|
|---|
| Topical term or geographic name entry element |
Pattern Recognition |
| 9 (RLIN) |
15727 |
| 658 ## - INDEX TERM--CURRICULUM OBJECTIVE |
|---|
| Main curriculum objective |
Machine Learning I |
|
|---|
| Curriculum code |
CSL7XX0 |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ben-David, Shai. |
| Relationship information |
[Author] |
| 9 (RLIN) |
1868 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
<a href="https://doi.org/10.1017/CBO9781107298019">https://doi.org/10.1017/CBO9781107298019</a> |
| Electronic format type |
PDF |
| Link text |
Click to Access the Online Book |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
e-Book |
| Source of classification or shelving scheme |
Dewey Decimal Classification |
