Automated Machine Learning (Record no. 581)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03899nam a22005775i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-030-05318-5 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20210511115646.0 |
| 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 | 190517s2019 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783030053185 |
| -- | 978-3-030-05318-5 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-030-05318-5 |
| Source of number or code | doi |
| 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 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.3 |
| Edition number | 23 |
| 245 10 - TITLE STATEMENT | |
| Title | Automated Machine Learning |
| Medium | [electronic resource] : |
| Remainder of title | Methods, Systems, Challenges / |
| Statement of responsibility, etc. | edited by Frank Hutter, Lars Kotthoff, Joaquin Vanschoren. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2019. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Cham : |
| Name of producer, publisher, distributor, manufacturer | Springer International Publishing : |
| -- | Imprint: Springer, |
| Date of production, publication, distribution, manufacture, or copyright notice | 2019. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | XIV, 219 p. 54 illus., 45 illus. in color. |
| 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 |
| 490 1# - SERIES STATEMENT | |
| Series statement | The Springer Series on Challenges in Machine Learning, |
| International Standard Serial Number | 2520-131X |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 1 Hyperparameter Optimization -- 2 Meta-Learning -- 3 Neural Architecture Search -- 4 Auto-WEKA -- 5 Hyperopt-Sklearn -- 6 Auto-sklearn -- 7 Towards Automatically-Tuned Deep Neural Networks -- 8 TPOT -- 9 The Automatic Statistician -- 10 AutoML Challenges. |
| 506 0# - RESTRICTIONS ON ACCESS NOTE | |
| Terms governing access | Open Access |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Artificial intelligence. |
| 9 (RLIN) | 2433 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Optical data processing. |
| 9 (RLIN) | 746 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Pattern recognition. |
| 9 (RLIN) | 2434 |
| 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) | 2435 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Image Processing and Computer Vision. |
| Authority record control number or standard number | https://scigraph.springernature.com/ontologies/product-market-codes/I22021 |
| 9 (RLIN) | 748 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Pattern Recognition. |
| Authority record control number or standard number | https://scigraph.springernature.com/ontologies/product-market-codes/I2203X |
| 9 (RLIN) | 2436 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Hutter, Frank. |
| Relator term | editor. |
| Relationship | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 9 (RLIN) | 2437 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Kotthoff, Lars. |
| Relator term | editor. |
| Relationship | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 9 (RLIN) | 2438 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Vanschoren, Joaquin. |
| Relator term | editor. |
| Authority record control number or standard number | (orcid)0000-0001-7044-9805 |
| Real World Object URI | https://orcid.org/0000-0001-7044-9805 |
| Relationship | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 9 (RLIN) | 2439 |
| 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 | 9783030053178 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9783030053192 |
| 773 ## - HOST ITEM ENTRY | |
| Title | Springer Nature Open Access eBook |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | The Springer Series on Challenges in Machine Learning, |
| International Standard Serial Number | 2520-131X |
| 9 (RLIN) | 2440 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-3-030-05318-5">https://doi.org/10.1007/978-3-030-05318-5</a> |
| 912 ## - | |
| -- | ZDB-2-SCS |
| 912 ## - | |
| -- | ZDB-2-SXCS |
| 912 ## - | |
| -- | ZDB-2-SOB |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | e-Books |
| -- | Administrator Library |
No items available.