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Titlebook: Data Science in Practice; Alan Said,Vicenç Torra Book 2019 Springer Nature Switzerland AG 2019 Data Science applications.Big Data.Intellig

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发表于 2025-3-21 19:25:02 | 显示全部楼层 |阅读模式
书目名称Data Science in Practice
编辑Alan Said,Vicenç Torra
视频video
概述Presents the latest research on Data Science in Practice.Especially focuses on the applications of Data Science and Big Data.Written by respected experts in the field
丛书名称Studies in Big Data
图书封面Titlebook: Data Science in Practice;  Alan Said,Vicenç Torra Book 2019 Springer Nature Switzerland AG 2019 Data Science applications.Big Data.Intellig
描述This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. We have grown accustomed to seeing these terms mentioned time and time again in the mainstream media. However, our understanding of what they actually mean often remains limited. This book provides a general overview of the terms and approaches used broadly in data science, and provides detailed information on the underlying theories, models, and application scenarios. Divided into three main parts, it addresses what data science is; how and where it is used; and how it can be implemented using modern open source software. The book offers an essential guide to modern data science for all students, practitioners, developers and managers seeking a deeper understanding of how various aspects of data science work, and of how they can be employed to gain a competitive advantage.
出版日期Book 2019
关键词Data Science applications; Big Data; Intelligent Systems; Computational Intelligence; Applied Data Scien
版次1
doihttps://doi.org/10.1007/978-3-319-97556-6
isbn_softcover978-3-030-07374-9
isbn_ebook978-3-319-97556-6Series ISSN 2197-6503 Series E-ISSN 2197-6511
issn_series 2197-6503
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Complex Data Analysishat can be used to extract information and, thus, analyze these three types of data. In particular, we discuss topic modeling using a hierarchical statistical model as a way to extract relevant topics from texts, image analysis using convolutional neural networks, and measures and visual methods to summarize information from graphs.
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Data Science: An Introduction,elevant tools that can be used in data science ranging from optimization to software. We also discuss the relevance of building models from data. The chapter ends with a detailed review of the structure of the book.
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Cengiz Kahraman,Cafer Erhan Bozdağhat can be used to extract information and, thus, analyze these three types of data. In particular, we discuss topic modeling using a hierarchical statistical model as a way to extract relevant topics from texts, image analysis using convolutional neural networks, and measures and visual methods to summarize information from graphs.
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Book 2019d how it can be implemented using modern open source software. The book offers an essential guide to modern data science for all students, practitioners, developers and managers seeking a deeper understanding of how various aspects of data science work, and of how they can be employed to gain a competitive advantage.
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Business Intelligenceloratory, inferential, and predictive. This is followed by a discussion on metric design, data dictionaries, and key performance indicators. We end by reviewing the role of business intelligence teams and some of the current trends in business intelligence.
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