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Titlebook: Data Analytics and Machine Learning; Navigating the Big D Pushpa Singh,Asha Rani Mishra,Payal Garg Book 2024 The Editor(s) (if applicable)

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發(fā)表于 2025-3-21 17:53:06 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Data Analytics and Machine Learning
副標(biāo)題Navigating the Big D
編輯Pushpa Singh,Asha Rani Mishra,Payal Garg
視頻videohttp://file.papertrans.cn/263/262687/262687.mp4
概述Highlights the current state of data analytics, big data, and machine learning techniques to treat data in real time.Addresses the ethical and privacy concerns associated with data analytics, big data
叢書名稱Studies in Big Data
圖書封面Titlebook: Data Analytics and Machine Learning; Navigating the Big D Pushpa Singh,Asha Rani Mishra,Payal Garg Book 2024 The Editor(s) (if applicable)
描述.This book presents an in-depth analysis of successful data-driven initiatives, highlighting how organizations have leveraged data to drive decision-making processes, optimize operations, and achieve remarkable outcomes. Through case studies, readers gain valuable insights and learn practical strategies for implementing data analytics, big data, and machine learning solutions in their own organizations. The book discusses the transformative power of data analytics and big data in various industries and sectors and how machine learning applications have revolutionized exploration by enabling advanced data analysis techniques for mapping, geospatial analysis, and environmental monitoring, enhancing our understanding of the world and its dynamic processes. This book explores how big data explosion, the power of analytics and machine learning revolution can bring new prospects and opportunities in the dynamic and data-rich landscape. It highlights the future research directions in data analytics, big data, and machine learning that explores the emerging trends, challenges, and opportunities in these fields by covering interdisciplinary approaches such as handling and analyzing real-tim
出版日期Book 2024
關(guān)鍵詞Predictive Analytics; Stream data model; Real-time analytics; Time series analysis; Natural Language Pro
版次1
doihttps://doi.org/10.1007/978-981-97-0448-4
isbn_softcover978-981-97-0450-7
isbn_ebook978-981-97-0448-4Series ISSN 2197-6503 Series E-ISSN 2197-6511
issn_series 2197-6503
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

書目名稱Data Analytics and Machine Learning影響因子(影響力)




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發(fā)表于 2025-3-21 23:53:54 | 只看該作者
978-981-97-0450-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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發(fā)表于 2025-3-22 03:27:54 | 只看該作者
Data Analytics and Machine Learning978-981-97-0448-4Series ISSN 2197-6503 Series E-ISSN 2197-6511
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發(fā)表于 2025-3-22 08:12:29 | 只看該作者
Pushpa Singh,Asha Rani Mishra,Payal GargHighlights the current state of data analytics, big data, and machine learning techniques to treat data in real time.Addresses the ethical and privacy concerns associated with data analytics, big data
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Civil Society and Public Policy in Turkeyytics systems is ranged over in this chapter. The chapter also delves into detailing open-source tools such as Power BI and Tableau used in developing data analytics systems. Traditional analysis is different from big data analysis in terms of volume and data processed varieties. To meet the require
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Citizens and Democracy in Europedata into actionable insights. Key themes include the selection of an appropriate machine learning model tailored to specific problems, mastering the art of feature engineering to refine raw data into informative features aligned with chosen algorithms, and the iterative process of model training an
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Contextual Theories of Political Supportusly generated at a bang-up velocity. Because of integral dynamical features of big data, it is hard to apply existing working models directly on big data streams. The solution of this limitation is data streaming. A modern-day data streaming architecture allows taking up, operating and analyzing hi
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