Information-theoretic methods in data science / (Record no. 84087)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02280nam a2200361 i 4500 |
| 001 - CONTROL NUMBER | |
| control field | CR9781108616799 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730160735.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 170831s2021||||enk o ||1 0|eng|d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781108616799 (ebook) |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.312 |
| 245 00 - TITLE STATEMENT | |
| Title | Information-theoretic methods in data science / |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | 1 online resource (xxi, 538 pages) : |
| 500 ## - GENERAL NOTE | |
| Remark 1 | Title from publisher's bibliographic system (viewed on 26 Mar 2021). |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | Learn about the state-of-the-art at the interface between information theory and data science with this first unified treatment of the subject. Written by leading experts in a clear, tutorial style, and using consistent notation and definitions throughout, it shows how information-theoretic methods are being used in data acquisition, data representation, data analysis, and statistics and machine learning. Coverage is broad, with chapters on signal acquisition, data compression, compressive sensing, data communication, representation learning, emerging topics in statistics, and much more. Each chapter includes a topic overview, definition of the key problems, emerging and open problems, and an extensive reference list, allowing readers to develop in-depth knowledge and understanding. Providing a thorough survey of the current research area and cutting-edge trends, this is essential reading for graduate students and researchers working in information theory, signal processing, machine learning, and statistics. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Rodrigues, Miguel R. D., |
| 700 1# - AUTHOR 2 | |
| Author 2 | Eldar, Yonina C., |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1017/9781108616799 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | Cambridge : |
| -- | Cambridge University Press, |
| -- | 2021. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Information theory. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Machine learning. |
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