Deep learning (Record no. 567171)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01973 a2200217 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783031454677 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | IIT Kanpur |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | eng |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 |
| Item number | B541d |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Bishop, Christopher M. |
| 245 ## - TITLE STATEMENT | |
| Title | Deep learning |
| Remainder of title | foundations and concepts |
| Statement of responsibility, etc | Christopher M. Bishop and Hugh Bishop |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher | Springer Nature |
| Year of publication | 2024 |
| Place of publication | Switzerland |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xx, 649p |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This book offers a comprehensive introduction to the central ideas that underpin deep learning. It is intended both for newcomers to machine learning and for those already experienced in the field. Covering key concepts relating to contemporary architectures and techniques, this essential book equips readers with a robust foundation for potential future specialization. The field of deep learning is undergoing rapid evolution, and therefore this book focusses on ideas that are likely to endure the test of time. The book is organized into numerous bite-sized chapters, each exploring a distinct topic, and the narrative follows a linear progression, with each chapter building upon content from its predecessors. This structure is well-suited to teaching a two-semester undergraduate or postgraduate machine learning course, while remaining equally relevant to those engaged in active research or in self-study. A full understanding of machine learning requires some mathematical background and so the book includes a self-contained introduction to probability theory. However, the focus of the book is on conveying a clear understanding of ideas, with emphasis on the real-world practical value of techniques rather than on abstract theory. Complex concepts are therefore presented from multiple complementary perspectives including textual descriptions, diagrams, mathematical formulae, and pseudo-code. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Deep learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Machine learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Artificial intelligence |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Bishop, Hugh |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Not for loan | Collection code | Permanent Location | Current Location | Date acquired | Source of acquisition | Cost, normal purchase price | Full call number | Accession Number | Cost, replacement price | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| In Acquisition | PK Kelkar Library, IIT Kanpur | PK Kelkar Library, IIT Kanpur | 2024-09-12 | 2 | 5938.46 | 006.31 B541d | A186478 | 7423.07 | Books |