MARC details
| 000 -LEADER |
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| fixed length control field |
03049nam a22003017i 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20250812152508.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
250728s2024 flua fr 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780367425500 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
EG-GaU |
| Transcribing agency |
EG-GaU |
| Modifying agency |
EG-GaU |
| Description conventions |
rda |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Edition number |
23 |
| Classification number |
519.6 |
| Item number |
W.J.I |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Wheeler, Jeffrey Paul, |
| Relator term |
author. |
| 9 (RLIN) |
62387 |
| 245 13 - TITLE STATEMENT |
|---|
| Title |
An introduction to optimization with applications in machine learning and data analytics / |
| Statement of responsibility, etc. |
Jeffrey Paul Wheeler. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Boca Raton, FL : |
| Name of producer, publisher, distributor, manufacturer |
CRC Press, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2024. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
448 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
24 cm. |
| 336 ## - CONTENT TYPE |
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| Source |
rdacontent |
| Content type term |
text |
| Content type code |
txt |
| 337 ## - MEDIA TYPE |
|---|
| Source |
rdamedia |
| Media type term |
unmediated |
| Media type code |
n |
| 338 ## - CARRIER TYPE |
|---|
| Source |
rdacarrier |
| Carrier type term |
volume |
| Carrier type code |
nc |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references and index. |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
I. Preliminary Matters -- 1. Preamble -- 2. The Language of Optimization -- 3. Computational Complexity -- 4. Algebra Review -- 5. Matrix Factorization -- II. Linear Programming -- 6. Linear Programming -- 7. Sensitivity Analysis -- 8. Integer Linear Programming -- III. Nonlinear (Geometric) Programming -- 9. Calculus Review -- 10. A Calculus Approach to Nonlinear Programming -- 11. Constrained Nonlinear Programming: Lagrange Multipliers and the KKT Conditions -- 12. Optimization Involving Quadratic Forms -- 13. Iterative Methods -- 14. Derivative-Free Methods -- 15. Search Algorithms -- IV. Convexity and the Fundamental Theorem of Linear Programming -- 16. Important Sets for Optimization -- 17. The Fundamental Theorem of Linear Programming -- 18. Convex Functions -- 19. Convex Optimization (Jourdain Lamperski) -- V. Combinatorial Optimization -- 20. An Introduction to Combinatorics -- 21. An Introduction to Graph Theory -- 22. Network Flows -- 23. Minimum-Weight Spanning Trees and Shortest Paths -- 24. Network Modeling and the Transshipment Problem -- 25. The Traveling Salesperson Problem -- VI. Optimization for Data Analytics and Machine Learning -- 26. Probability -- 27. Regression Analysis via Least Squares (John McKay and Suren Jayasuria) -- 28. Forecasting (Joseph “Nico” Gabriel) -- 29. Introduction to Machine Learning (Suren Jayasuria and John McKay) -- Appendices: A. Techniques of Proof -- B. Useful Tools from Analysis and Topology -- Bibliography -- Index -- Notation. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
This textbook offers a practical and balanced approach to optimization, blending theory and applications across multiple disciplines such as machine learning, economics, and engineering. It includes comprehensive coverage of linear and nonlinear programming, combinatorics, convex analysis, and modern machine learning techniques. The book integrates hands-on computing via Excel, Python, MATLAB, and other tools, making it accessible for a broad audience of students and professionals. |
| 650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Mathematical optimization. |
| 9 (RLIN) |
1638 |
| 650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Machine learning. |
| 9 (RLIN) |
15543 |
| 650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data analytics. |
| 9 (RLIN) |
60497 |
| 650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Operations research. |
| 9 (RLIN) |
25111 |
| 650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Engineering mathematics. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |