Efficient Learning Machines (Record no. 1436)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04435nam a22005295i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-1-4302-5990-9 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20210511122118.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 150427s2015 xxu| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781430259909 |
| -- | 978-1-4302-5990-9 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-1-4302-5990-9 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | Q334-342 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | Q334-342 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYQ |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM004000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYQ |
| Source | thema |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYQ |
| Source | thema |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.3 |
| Edition number | 23 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.3 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Awad, Mariette. |
| Relator term | author. |
| Relationship | aut |
| -- | http://id.loc.gov/vocabulary/relators/aut |
| 9 (RLIN) | 6984 |
| 245 10 - TITLE STATEMENT | |
| Title | Efficient Learning Machines |
| Medium | [electronic resource] : |
| Remainder of title | Theories, Concepts, and Applications for Engineers and System Designers / |
| Statement of responsibility, etc. | by Mariette Awad, Rahul Khanna. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2015. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Berkeley, CA : |
| Name of producer, publisher, distributor, manufacturer | Apress : |
| -- | Imprint: Apress, |
| Date of production, publication, distribution, manufacture, or copyright notice | 2015. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | XIX, 268 p. 88 illus. |
| Other physical details | online resource. |
| 336 ## - CONTENT TYPE | |
| Content type term | text |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type term | computer |
| Media type code | c |
| Source | rdamedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | online resource |
| Carrier type code | cr |
| Source | rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS | |
| File type | text file |
| Encoding format | |
| Source | rda |
| 506 0# - RESTRICTIONS ON ACCESS NOTE | |
| Terms governing access | Open Access |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Machine learning techniques provide cost-effective alternatives to traditional methods for extracting underlying relationships between information and data and for predicting future events by processing existing information to train models. Efficient Learning Machines explores the major topics of machine learning, including knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and biologically-inspired techniques. Mariette Awad and Rahul Khanna’s synthetic approach weaves together the theoretical exposition, design principles, and practical applications of efficient machine learning. Their experiential emphasis, expressed in their close analysis of sample algorithms throughout the book, aims to equip engineers, students of engineering, and system designers to design and create new and more efficient machine learning systems. Readers of Efficient Learning Machines will learn how to recognize and analyze the problems that machine learning technology can solve for them, how to implement and deploy standard solutions to sample problems, and how to design new systems and solutions. Advances in computing performance, storage, memory, unstructured information retrieval, and cloud computing have coevolved with a new generation of machine learning paradigms and big data analytics, which the authors present in the conceptual context of their traditional precursors. Awad and Khanna explore current developments in the deep learning techniques of deep neural networks, hierarchical temporal memory, and cortical algorithms. Nature suggests sophisticated learning techniques that deploy simple rules to generate highly intelligent and organized behaviors with adaptive, evolutionary, and distributed properties. The authors examine the most popular biologically-inspired algorithms, together with a sample application to distributed datacenter management. They also discuss machine learning techniques for addressing problems of multi-objective optimization in which solutions in real-world systems are constrained and evaluated based on how well they perform with respect to multiple objectives in aggregate. Two chapters on support vector machines and their extensions focus on recent improvements to the classification and regression techniques at the core of machine learning. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Artificial intelligence. |
| 9 (RLIN) | 6985 |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Artificial Intelligence. |
| Authority record control number or standard number | https://scigraph.springernature.com/ontologies/product-market-codes/I21000 |
| 9 (RLIN) | 6986 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Artificial Intelligence. |
| Authority record control number or standard number | https://scigraph.springernature.com/ontologies/product-market-codes/I21000 |
| 9 (RLIN) | 6986 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Khanna, Rahul. |
| Relator term | author. |
| Relationship | aut |
| -- | http://id.loc.gov/vocabulary/relators/aut |
| 9 (RLIN) | 6987 |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 9 (RLIN) | 141 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9781430259893 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9781430259916 |
| 773 ## - HOST ITEM ENTRY | |
| Title | Springer Nature Open Access eBook |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-1-4302-5990-9">https://doi.org/10.1007/978-1-4302-5990-9</a> |
| 912 ## - | |
| -- | ZDB-2-CWD |
| 912 ## - | |
| -- | ZDB-2-SXPC |
| 912 ## - | |
| -- | ZDB-2-SOB |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | e-Books |
| -- | Administrator Library |
No items available.