Understanding Machine Learning (Record no. 31736)

MARC details
000 -LEADER
fixed length control field 01822nam a22002417a 4500
003 - CONTROL NUMBER IDENTIFIER
control field IN-KoAU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251127171655.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 251127b ii ||||| |||| 00| 0 eng d
020 ## - ISBN / ISSN
ISBN | আই এস বি এন 9781107512825
040 ## - CATALOGING SOURCE
Language of cataloging eng
082 ## - DDC | ডিউই
Classification number | বর্গসংখ্যা 006.31/SHA/U
100 ## - MAIN ENTRY--PERSONAL NAME | মুখ্য সংলেখ - ব্যাক্তিনাম
Personal name | ব্যাক্তিনাম Shalev-Shwartz, Shai
245 ## - TITLE STATEMENT | আখ্যা বিবরণী
Title | আখ্যা Understanding Machine Learning
Sub title | উপআখ্যা from theory to algorithms
Statement of responsibility | লেখকের দায়িত্বের বিবরণ Shai Shalev-Shwartz and, Shai Ben-David
260 ## - IMPRINT | প্রকাশনা ক্ষেত্র
Place of publication | প্রকাশ স্থান London
Name of publisher | প্রকাশকের নাম Cambridge
Date of publication | প্রকাশ কাল 2019
300 ## - PHYSICAL DESCRIPTION |
Page / Vol. No | পৃষ্ঠা / খন্ড সংখ্যা xvi, 397 p.
505 ## - CONTENTS NOTE | সূচীসংক্রান্ত টীকা
Contents note | সূচীসংক্রান্ত টীকা Machine generated contents note: 1. Introduction; Part I. Foundations: 2. A gentle start; 3. A formal learning model; 4. Learning via uniform convergence; 5. The bias-complexity tradeoff; 6. The VC-dimension; 7. Non-uniform learnability; 8. The runtime of learning; Part II. From Theory to Algorithms: 9. Linear predictors; 10. Boosting; 11. Model selection and validation; 12. Convex learning problems; 13. Regularization and stability; 14. Stochastic gradient descent; 15. Support vector machines; 16. Kernel methods; 17. Multiclass, ranking, and complex prediction problems; 18. Decision trees; 19. Nearest neighbor; 20. Neural networks; Part III. Additional Learning Models: 21. Online learning; 22. Clustering; 23. Dimensionality reduction; 24. Generative models; 25. Feature selection and generation; Part IV. Advanced Theory: 26. Rademacher complexities; 27. Covering numbers; 28. Proof of the fundamental theorem of learning theory; 29. Multiclass learnability; 30. Compression bounds; 31. PAC-Bayes; Appendix A. Technical lemmas; Appendix B. Measure concentration; Appendix C. Linear algebra.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | বিষয় শিরোনাম - মূল বিষয়
Topical term | মূল বিষয় Machine learning.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | বিষয় শিরোনাম - মূল বিষয়
Topical term | মূল বিষয় Algorithms.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | বিষয় শিরোনাম - মূল বিষয়
Topical term | মূল বিষয় COMPUTERS / Computer Vision & Pattern Recognition.
700 ## - ADDED ENTRY--PERSONAL NAME | অতিরিক্ত সংলেখ - ব্
Personal name | ব্যাক্তিনাম Ben-David, Shai
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Electronics Engg. Books
041 ## - LANGUAGE CODE
LANGUAGE CODE English
Holdings
Withdrawn status Lost status Source of classification Damaged status Not for loan Home library Current library Date acquired Total Checkouts Full call number Accession No. Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Newtown Campus, Kolkata Newtown Campus, Kolkata 27/11/2025   006.31/SHA/U 39618 27/11/2025 27/11/2025 Electronics Engg. Books
    Dewey Decimal Classification     Newtown Campus, Kolkata Newtown Campus, Kolkata 27/11/2025   006.31/SHA/U 39619 27/11/2025 27/11/2025 Electronics Engg. Books
    Dewey Decimal Classification     Newtown Campus, Kolkata Newtown Campus, Kolkata 27/11/2025   006.31/SHA/U 39620 27/11/2025 27/11/2025 Electronics Engg. Books

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