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Titlebook: Big Data Analytics: Systems, Algorithms, Applications; C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,L.M. Je Textbook 2019 Springer Nature Si

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发表于 2025-3-21 16:41:00 | 显示全部楼层 |阅读模式
期刊全称Big Data Analytics: Systems, Algorithms, Applications
影响因子2023C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,L.M. Je
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发行地址Presents the latest developments in data science algorithms, the output of which is highlighted in terms of the approaches to mining Big Data pursued by programmers, scientists, and managers.Documents
图书封面Titlebook: Big Data Analytics: Systems, Algorithms, Applications;  C.S.R. Prabhu,Aneesh Sreevallabh Chivukula,L.M. Je Textbook 2019 Springer Nature Si
影响因子This book provides a comprehensive survey of techniques, technologies and applications of Big Data and its analysis. The Big Data phenomenon is increasingly impacting all sectors of business and industry, producing an emerging new information ecosystem. On the applications front, the book offers detailed descriptions of various application areas for Big Data Analytics in the important domains of Social Semantic Web Mining, Banking and Financial Services, Capital Markets, Insurance, Advertisement, Recommendation Systems, Bio-Informatics, the IoT and Fog Computing, before delving into issues of security and privacy. .With regard to machine learning techniques, the book presents all the standard algorithms for learning – including supervised, semi-supervised and unsupervised techniques such as clustering and reinforcement learning techniques to perform collective Deep Learning. Multi-layered and nonlinear learning for Big Data are also covered. .In turn,the book highlights real-life case studies on successful implementations of Big Data Analytics at large IT companies such as Google, Facebook, LinkedIn and Microsoft. Multi-sectorial case studies on domain-based companies such as Deuts
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https://doi.org/10.1007/978-981-15-0094-7Big Data; Machine Learning; Internet of Things; Hadoop; NoSQL; Fog Computing
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On Exponentials and Logarithms,The latest disruptive trends and developments in digital age comprise social networking, mobility, analytics and cloud, popularly known as SMAC. The year 2016 saw Big Data Technologies being leveraged to power business intelligence applications. What holds in store for 2020 and beyond?
发表于 2025-3-22 20:45:28 | 显示全部楼层
Introduction to Analysis of the InfiniteThe ultimate goal of data science is to turn raw data into data products. Data analytics is the science of examining the raw data with the purpose of making correct decisions by drawing meaningful conclusions.
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On Exponentials and Logarithms,In the context of Big Data Analytics and Social Networking, Semantic Web Mining is an amalgamation of three scientific areas of research: (1) Social Networking (2) Semantic Web and (3) Big Data Analytics, including Web Mining and Data Mining.
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Introduction to Analysis of the InfiniteHaving surveyed in the last chapter how Big Data Analytics is applied in Social Semantic Web, in this chapter we shall delve into another very important application domain, IOT. We shall examine the interaction between IOT and Big Data Analytics.
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