Automated Machine Learning

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...

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Formatua: Online
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Argitaratua: Springer Nature 2021
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collection Directory of Open Access Books
description 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.
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institution Directory of Open Access Books
language eng
publishDate 2021
publishDateRange 2021
publishDateSort 2021
publisher Springer Nature
publisherStr Springer Nature
record_format ojs
spelling doab-20.500.12854ir-313792025-07-30T10:22:13Z Automated Machine Learning Hutter, Frank Kotthoff, Lars Vanschoren, Joaquin Computer science Artificial intelligence Optical data processing Pattern recognition thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition thema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processing thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition thema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processing 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. 2021-02-10T13:50:03Z 2021-02-10T13:50:03Z 2020-03-18 13:36:15 2020-04-01T09:00:04Z 2019 book 1007149 OCN: 1105039769 http://library.oapen.org/handle/20.500.12657/23012 https://directory.doabooks.org/handle/20.500.12854/31379 eng The Springer Series on Challenges in Machine Learning open access image/jpeg image/jpeg image/jpeg n/a n/a n/a https://library.oapen.org/bitstream/20.500.12657/23012/1/1007149.pdf https://library.oapen.org/bitstream/20.500.12657/23012/1/1007149.pdf https://library.oapen.org/bitstream/20.500.12657/23012/1/1007149.pdf Springer Nature 10.1007/978-3-030-05318-5 10.1007/978-3-030-05318-5 9fa3421d-f917-4153-b9ab-fc337c396b5a 219 Cham open access
spellingShingle Computer science
Artificial intelligence
Optical data processing
Pattern recognition
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processing
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processing
Automated Machine Learning
title Automated Machine Learning
title_full Automated Machine Learning
title_fullStr Automated Machine Learning
title_full_unstemmed Automated Machine Learning
title_short Automated Machine Learning
title_sort automated machine learning
topic Computer science
Artificial intelligence
Optical data processing
Pattern recognition
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processing
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processing
topic_facet Computer science
Artificial intelligence
Optical data processing
Pattern recognition
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processing
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQP Pattern recognition
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processing
url 1007149