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Titlebook: Metalearning; Applications to Auto Pavel Brazdil,Jan N. van Rijn,Joaquin Vanschoren Book‘‘‘‘‘‘‘‘ 2022Latest edition The Editor(s) (if appli

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發(fā)表于 2025-3-21 18:29:59 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Metalearning
副標(biāo)題Applications to Auto
編輯Pavel Brazdil,Jan N. van Rijn,Joaquin Vanschoren
視頻videohttp://file.papertrans.cn/632/631509/631509.mp4
概述Provide a comprehensive and systematic overview of metalearning.Blends theory and practice, presenting state-of-the-art methodologies.An update edition on the successful first edition https://link.spr
叢書名稱Cognitive Technologies
圖書封面Titlebook: Metalearning; Applications to Auto Pavel Brazdil,Jan N. van Rijn,Joaquin Vanschoren Book‘‘‘‘‘‘‘‘ 2022Latest edition The Editor(s) (if appli
描述.This open access book offers a comprehensive and thorough introduction to almost all aspects of metalearning and automated machine learning (AutoML), covering the basic concepts and architecture, evaluation, datasets, hyperparameter optimization, ensembles and workflows, and also how this knowledge can be used to select, combine, compose, adapt and configure both algorithms and models to yield faster and better solutions to data mining and data science problems. It can thus help developers to develop systems that can improve themselves through experience..As one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, AutoML is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary i
出版日期Book‘‘‘‘‘‘‘‘ 2022Latest edition
關(guān)鍵詞Metalearning; Automating Machine Learning (AutoML); Machine Learning; Artificial Intelligence; algorithm
版次2
doihttps://doi.org/10.1007/978-3-030-67024-5
isbn_softcover978-3-030-67026-9
isbn_ebook978-3-030-67024-5Series ISSN 1611-2482 Series E-ISSN 2197-6635
issn_series 1611-2482
copyrightThe Editor(s) (if applicable) and The Author(s) 2022
The information of publication is updating

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發(fā)表于 2025-3-21 20:57:09 | 只看該作者
Metalearning978-3-030-67024-5Series ISSN 1611-2482 Series E-ISSN 2197-6635
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發(fā)表于 2025-3-22 02:44:45 | 只看該作者
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發(fā)表于 2025-3-22 08:23:58 | 只看該作者
Pavel Brazdil,Jan N. van Rijn,Joaquin VanschorenProvide a comprehensive and systematic overview of metalearning.Blends theory and practice, presenting state-of-the-art methodologies.An update edition on the successful first edition https://link.spr
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發(fā)表于 2025-3-22 12:01:01 | 只看該作者
Cognitive Technologieshttp://image.papertrans.cn/m/image/631509.jpg
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發(fā)表于 2025-3-22 15:57:54 | 只看該作者
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發(fā)表于 2025-3-22 20:24:25 | 只看該作者
tverbreitetes und viel gelesenes Medium. Fast alle gro?en Unternehmen geben eine innerbetriebliche Publikation heraus, die vier- zehnt?gig, monatlich oder viertelj?hrlich kostenlos an die Belegschaft und Pensio- n?re verteilt wird und von Ver?nderungen im Konzern, den aktuellen Bilanzzah- len, von F
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發(fā)表于 2025-3-23 02:05:41 | 只看該作者
Pavel Brazdil,Jan N. van Rijn,Carlos Soares,Joaquin Vanschorentverbreitetes und viel gelesenes Medium. Fast alle gro?en Unternehmen geben eine innerbetriebliche Publikation heraus, die vier- zehnt?gig, monatlich oder viertelj?hrlich kostenlos an die Belegschaft und Pensio- n?re verteilt wird und von Ver?nderungen im Konzern, den aktuellen Bilanzzah- len, von F
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發(fā)表于 2025-3-23 06:51:22 | 只看該作者
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