MARC details
| 000 -LEADER |
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| fixed length control field |
03097naaaa2200421uu 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
BUT |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20230331142025.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
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| fixed length control field |
m o d |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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| fixed length control field |
cr|mn|---annan |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
20230105s2022 sz x |||||o ||||eng|| d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781638280538 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781638280521 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
oapen |
| Transcribing agency |
oapen |
| 041 0# - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
dc |
| 080 ## - UNIVERSAL DECIMAL CLASSIFICATION NUMBER |
|---|
| Universal Decimal Classification number |
004 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Suh, Changho |
| Relationship |
auth |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Convex Optimization for Machine Learning |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Name of publisher, distributor, etc. |
Now Publishers |
| Date of publication, distribution, etc. |
2022 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
1 electronic resource (379 p.) |
| 490 1# - SERIES STATEMENT |
|---|
| Series statement |
NowOpen |
| 506 0# - RESTRICTIONS ON ACCESS NOTE |
|---|
| Terms governing access |
Open Access |
| Source of term |
star |
| Standardized terminology for access restriction |
Unrestricted online access |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
This book covers an introduction to convex optimization, one of the powerful and tractable optimization problems that can be efficiently solved on a computer. The goal of the book is to<br/>help develop a sense of what convex optimization is, and how it can be used in a widening array of practical contexts with a particular emphasis on machine learning.<br/><br/>The first part of the book covers core concepts of convex sets, convex functions, and related basic definitions that serve understanding convex optimization and its corresponding models. The second part deals with one very useful theory, called duality, which enables us to: (1) gain algorithmic insights; and (2) obtain an approximate solution to non-convex optimization problems which are often difficult to solve. The last part focuses on modern applications in machine learning and deep learning.<br/><br/>A defining feature of this book is that it succinctly relates the “story” of how convex optimization plays a role, via historical examples and trending machine learning applications. Another key feature is that it includes programming implementation of a variety of machine learning algorithms inspired by optimization fundamentals, together with a brief tutorial of the used programming tools. The implementation is based on Python, CVXPY, and TensorFlow.<br/><br/>This book does not follow a traditional textbook-style organization, but is streamlined via a series of lecture notes that are intimately related, centered around coherent themes and concepts. It serves as a textbook mainly for a senior-level undergraduate course, yet is also suitable for a first-year graduate course. Readers benefit from having a good background in linear algebra, some exposure to probability, and basic familiarity with Python. |
| 540 ## - TERMS GOVERNING USE AND REPRODUCTION NOTE |
|---|
| Terms governing use and reproduction |
Creative Commons |
| Use and reproduction rights |
https://creativecommons.org/licenses/by-nc/4.0/ |
| Source of term |
cc |
| 546 ## - LANGUAGE NOTE |
|---|
| Language note |
English |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Программирование |
| 9 (RLIN) |
1403 |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Convex Optimization |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Deep Learning |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Generative Adversarial Networks (GANs) |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
TensorFlow |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Supervised Learning |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Wasserstein GAN |
| 830 ## - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| 9 (RLIN) |
4532 |
| Uniform title |
NowOpen |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Host name |
www.oapen.org |
| Uniform Resource Identifier |
<a href="https://library.oapen.org/bitstream/20.500.12657/60495/1/9781638280538.pdf">https://library.oapen.org/bitstream/20.500.12657/60495/1/9781638280538.pdf</a> |
| Access status |
0 |
| Public note |
Download |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Host name |
www.oapen.org |
| Uniform Resource Identifier |
<a href="https://directory.doabooks.org/handle/20.500.12854/95746">https://directory.doabooks.org/handle/20.500.12854/95746</a> |
| Access status |
0 |
| Public note |
Description |
| 909 ## - Составили записи |
|---|
| -- |
197 |
| -- |
Khurliman Arzieva |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Универсальная десятичная классификация |
| Koha item type |
Electronic edition |
