Machine learning fundamentals : (Record no. 13845)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02245cam a22002538i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 10867 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | IN-BhIIT |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240626174319.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 210805s2021 enk b 001 0 eng |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781108940023 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | IN-BhIIT |
| 041 ## - LANGUAGE CODE | |
| Language code of text | eng |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 |
| Book number | JIA/M |
| 100 1# - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Jiang, Hui |
| Relator term | Author. |
| 245 10 - TITLE STATEMENT | |
| Title | Machine learning fundamentals : |
| Sub Title | a concise introduction / |
| Statement of responsibility, etc | by Hui Jiang. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | New Delhi : |
| Name of publisher | Cambridge University Press, |
| Year of publication | 2021. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xv, 380 p. : |
| Other physical details(ill.) | ill. ; |
| Dimensions(size) | 24 cm. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc | Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | "This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely "from scratch" based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts. Hui Jiang is Professor of Electrical Engineering and Computer Science at York University, where he has been since 2002. His main research interests include machine learning, particularly deep learning, and its applications to speech and audio processing, natural language processing, and computer vision. Over the past 30 years, he has worked on a wide range of research problems from these areas and published hundreds of technical articles and papers in the mainstream journals and top-tier conferences. His works have won the prestigious IEEE Best Paper Award and the ACL Outstanding Paper honor"-- |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Machine learning. |
| Topical Term | Artificial Intelligence. |
| Topical Term | Computer Vision and Pattern Recognition. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Technical Reference Book |
| Withdrawn status | Lost status | Damaged status | Not for loan | Collection code | Home library | Current library | Date acquired | Source of acquisition | Cost, normal purchase price | Accession Number | Cost, replacement price | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Not withdrawn | Not Lost | not damaged | SES | Central Library, IIT Bhubaneswar | Central Library, IIT Bhubaneswar | 08/02/2024 | 47 | 3087.13 | 10867 | 4228.94 | 08/02/2024 | Technical Reference Book |