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Titlebook: Data Centric Artificial Intelligence: A Beginner’s Guide; Parikshit N. Mahalle,Gitanjali R. Shinde,Namrata N Book 2023 The Editor(s) (if a

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書目名稱Data Centric Artificial Intelligence: A Beginner’s Guide
編輯Parikshit N. Mahalle,Gitanjali R. Shinde,Namrata N
視頻videohttp://file.papertrans.cn/263/262747/262747.mp4
概述Discusses basics of model centric AI and data centric AI, its relevance and need.Provides in-depth understanding of various challenges of data centric AI applications.Elaborates on problem solving and
叢書名稱Data-Intensive Research
圖書封面Titlebook: Data Centric Artificial Intelligence: A Beginner’s Guide;  Parikshit N. Mahalle,Gitanjali R. Shinde,Namrata N Book 2023 The Editor(s) (if a
描述.This book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It presents comparative studies of model-centric and data-centric AI. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI. It serves as a reference guide for researchers and practitioners in academia and industry..
出版日期Book 2023
關(guān)鍵詞Model-Centric AI; Data-Centric Principles for AI Engineering; Data-Centric AI in healthcare; Health Inf
版次1
doihttps://doi.org/10.1007/978-981-99-6353-9
isbn_softcover978-981-99-6355-3
isbn_ebook978-981-99-6353-9Series ISSN 2731-555X Series E-ISSN 2731-5568
issn_series 2731-555X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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Data-Centric AI,ing, processing, and analyzing large amounts of data to extract insights, identify patterns, and make predictions. Data-centric AI is often used in machine learning, where algorithms are trained on large datasets to learn how to perform specific tasks.
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Book 2023s. It presents comparative studies of model-centric and data-centric AI. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI. It serves as a reference guide for researchers and practitioners in academia and industry..
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Mitigation and Adaptation Measuresing, processing, and analyzing large amounts of data to extract insights, identify patterns, and make predictions. Data-centric AI is often used in machine learning, where algorithms are trained on large datasets to learn how to perform specific tasks.
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https://doi.org/10.1007/978-981-99-6353-9Model-Centric AI; Data-Centric Principles for AI Engineering; Data-Centric AI in healthcare; Health Inf
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