Machine learning for engineers : (Record no. 13361)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02219cam a22002538i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 10604 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | IN-BhIIT |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20231229154844.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220303s2022 enk b 001 0 eng |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783030703905 |
| 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 | MCC/M |
| 100 1# - MAIN ENTRY--AUTHOR NAME | |
| Personal name | McClarren, Ryan G. |
| Relator term | Author. |
| 245 10 - TITLE STATEMENT | |
| Title | Machine learning for engineers : |
| Sub Title | using data to solve problems for physical systems / |
| Statement of responsibility, etc | by Ryan G. McClarren. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication | Switzerland : |
| Name of publisher | Springer, |
| Year of publication | 2021. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xii, 247 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 | " All engineers and applied scientists will need to harness the power of machine learning to solve the highly complex and data intensive problems now emerging. This text teaches state-of-the-art machine learning technologies to students and practicing engineers from the traditionally “analog” disciplines—mechanical, aerospace, chemical, nuclear, and civil. Dr. McClarren examines these technologies from an engineering perspective and illustrates their specific value to engineers by presenting concrete examples based on physical systems. The book proceeds from basic learning models to deep neural networks, gradually increasing readers’ ability to apply modern machine learning techniques to their current work and to prepare them for future, as yet unknown, problems. Rather than taking a black box approach, the author teaches a broad range of techniques while conveying the kinds of problems best addressed by each. Examples and case studies in controls, dynamics, heat transfer, and other engineering applications are implemented in Python and the libraries scikit-learn and tensorflow, demonstrating how readers can apply the most up-to-date methods to their own problems. The book equally benefits undergraduate engineering students who wish to acquire the skills required by future employers and practicing engineers who wish to expand and update their problem-solving toolkit. " |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Engineering |
| General subdivision | Data processing. |
| Topical Term | Machine learning. |
| Topical Term | Technology & engineering |
| General subdivision | Signals & Signal Processing. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Technical Reference Book |
| Koha issues (borrowed), all copies | 1 |
| Withdrawn status | Lost status | Damaged status | Not for loan | Collection code | Home library | Current library | Date acquired | Source of acquisition | Cost, normal purchase price | Full call number | Accession Number | Cost, replacement price | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Not withdrawn | Not Lost | not damaged | SMMME | Central Library, IIT Bhubaneswar | Central Library, IIT Bhubaneswar | 22/09/2023 | 22 | 3588.10 | 006.31 MCC/M | 10604 | 4915.20 | 22/09/2023 | Technical Reference Book |