Understanding Machine Learning: From Theory to Algorithms/ (Record no. 198794)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01594 a2200193 4500 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781107512825 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | CUS |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Shalev-Shwartz, Shai |
| 245 ## - TITLE STATEMENT | |
| Title | Understanding Machine Learning: From Theory to Algorithms/ |
| Statement of responsibility, etc. | Shai Shalev-Shwartz, Shai Ben-David |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher, distributor, etc. | Cambridge University Press, |
| Place of publication, distribution, etc. | New Delhi: |
| Date of publication, distribution, etc. | 2014 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xvi, 397 p. : |
| Other physical details | ill. ; |
| Dimensions | 26 cm. |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Introduction --<br/>Part I. Foundations --<br/>2 A gentle start --<br/>3 A formal learning model --<br/>4 Learning via uniform convergence --<br/>5 The bias-complexity tradeoff --<br/>6 The VC-dimension --<br/>7 Nonuniform learnability --<br/>8 The runtime of learning --<br/>Part II. From Theory to Algorithms --<br/>9 Linear predictors --<br/>10 Boosting --<br/>11 Model selection and validation --<br/>12 Convex learning problems --<br/>13 Regularization and stability --<br/>14 Stochastic gradient descent --<br/>15 Support vector machines --<br/>16 Kernel methods --<br/>17 Multiclass, ranking, and complex prediction problems --<br/>18 Decision trees --<br/>19 Nearest neighbor --<br/>20 Neural networks --<br/><br/>Part III. Additional Learning Models --<br/>21 Online learning --<br/>22 Clustering --<br/>23Dimensionality reduction --<br/>24 Generative models --<br/>25 Feature selection and generation --<br/><br/>Part IV. Advanced Theory --<br/>26 Rademacher complexities --<br/>27 Covering numbers --<br/>28 Proof of the fundamental theorem of learning theory --<br/>29 Multiclass learnability --<br/>30 Compression bounds --<br/>31 PAC-Bayes. |
| 650 ## - SUBJECT | |
| Keyword | Machine Learning |
| 650 ## - SUBJECT | |
| Keyword | Algorithms |
| 650 ## - SUBJECT | |
| Keyword | Computers |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Ben-David, Shai |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | General Books |
| Withdrawn status | Lost status | Damaged status | Not for loan | Home library | Current library | Date acquired | Source of acquisition | Cost, normal purchase price | Full call number | Accession number | Date last seen | Date last checked out | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Central Library, Sikkim University | Central Library, Sikkim University | 05/10/2020 | 62 | 796.00 | 006.31 SHA/U | 49449 | 14/07/2023 | 21/06/2023 | General Books |