Data Science From Research To Application

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Data Science: From Research to Application

Mahdi Bohlouli,Bahram Sadeghi Bigham,Zahra Narimani,Mahdi Vasighi,Ebrahim Ansari
Data Science From Research to Application Book PDF

Author : Mahdi Bohlouli,Bahram Sadeghi Bigham,Zahra Narimani,Mahdi Vasighi,Ebrahim Ansari
Publisher : Springer Nature
Page : 350 pages
File Size : 49,6 Mb
Release : 2020-01-28
Category : Technology & Engineering
ISBN : 9783030373092

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Data Science: From Research to Application by Mahdi Bohlouli,Bahram Sadeghi Bigham,Zahra Narimani,Mahdi Vasighi,Ebrahim Ansari Pdf

This book presents outstanding theoretical and practical findings in data science and associated interdisciplinary areas. Its main goal is to explore how data science research can revolutionize society and industries in a positive way, drawing on pure research to do so. The topics covered range from pure data science to fake news detection, as well as Internet of Things in the context of Industry 4.0. Data science is a rapidly growing field and, as a profession, incorporates a wide variety of areas, from statistics, mathematics and machine learning, to applied big data analytics. According to Forbes magazine, “Data Science” was listed as LinkedIn’s fastest-growing job in 2017. This book presents selected papers from the International Conference on Contemporary Issues in Data Science (CiDaS 2019), a professional data science event that provided a real workshop (not “listen-shop”) where scientists and scholars had the chance to share ideas, form new collaborations, and brainstorm on major challenges; and where industry experts could catch up on emerging solutions to help solve their concrete data science problems. Given its scope, the book will benefit not only data scientists and scientists from other domains, but also industry experts, policymakers and politicians.

Data Science and Social Research

N. Carlo Lauro,Enrica Amaturo,Maria Gabriella Grassia,Biagio Aragona,Marina Marino
Data Science and Social Research Book PDF

Author : N. Carlo Lauro,Enrica Amaturo,Maria Gabriella Grassia,Biagio Aragona,Marina Marino
Publisher : Springer
Page : 300 pages
File Size : 42,6 Mb
Release : 2017-11-17
Category : Social Science
ISBN : 9783319554778

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Data Science and Social Research by N. Carlo Lauro,Enrica Amaturo,Maria Gabriella Grassia,Biagio Aragona,Marina Marino Pdf

This edited volume lays the groundwork for Social Data Science, addressing epistemological issues, methods, technologies, software and applications of data science in the social sciences. It presents data science techniques for the collection, analysis and use of both online and offline new (big) data in social research and related applications. Among others, the individual contributions cover topics like social media, learning analytics, clustering, statistical literacy, recurrence analysis and network analysis. Data science is a multidisciplinary approach based mainly on the methods of statistics and computer science, and its aim is to develop appropriate methodologies for forecasting and decision-making in response to an increasingly complex reality often characterized by large amounts of data (big data) of various types (numeric, ordinal and nominal variables, symbolic data, texts, images, data streams, multi-way data, social networks etc.) and from diverse sources. This book presents selected papers from the international conference on Data Science & Social Research, held in Naples, Italy in February 2016, and will appeal to researchers in the social sciences working in academia as well as in statistical institutes and offices.

Data Science and Its Applications

Aakanksha Sharaff,G R Sinha
Data Science and Its Applications Book PDF

Author : Aakanksha Sharaff,G R Sinha
Publisher : CRC Press
Page : 443 pages
File Size : 51,7 Mb
Release : 2021-08-18
Category : Computers
ISBN : 9781000414004

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Data Science and Its Applications by Aakanksha Sharaff,G R Sinha Pdf

The term "data" being mostly used, experimented, analyzed, and researched, "Data Science and its Applications" finds relevance in all domains of research studies including science, engineering, technology, management, mathematics, and many more in wide range of applications such as sentiment analysis, social medial analytics, signal processing, gene analysis, market analysis, healthcare, bioinformatics etc. The book on Data Science and its applications discusses about data science overview, scientific methods, data processing, extraction of meaningful information from data, and insight for developing the concept from different domains, highlighting mathematical and statistical models, operations research, computer programming, machine learning, data visualization, pattern recognition and others. The book also highlights data science implementation and evaluation of performance in several emerging applications such as information retrieval, cognitive science, healthcare, and computer vision. The data analysis covers the role of data science depicting different types of data such as text, image, biomedical signal etc. useful for a wide range of real time applications. The salient features of the book are: Overview, Challenges and Opportunities in Data Science and Real Time Applications Addressing Big Data Issues Useful Machine Learning Methods Disease Detection and Healthcare Applications utilizing Data Science Concepts and Deep Learning Applications in Stock Market, Education, Behavior Analysis, Image Captioning, Gene Analysis and Scene Text Analysis Data Optimization Due to multidisciplinary applications of data science concepts, the book is intended for wide range of readers that include Data Scientists, Big Data Analysists, Research Scholars engaged in Data Science and Machine Learning applications.

Research in Data Science

Ellen Gasparovic
Research in Data Science Book PDF

Author : Ellen Gasparovic
Publisher : Unknown
Page : 302 pages
File Size : 41,5 Mb
Release : 2019
Category : Computer science
ISBN : 3030115674

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Research in Data Science by Ellen Gasparovic Pdf

This edited volume on data science features a variety of research ranging from theoretical to applied and computational topics. Aiming to establish the important connection between mathematics and data science, this book addresses cutting edge problems in predictive modeling, multi-scale representation and feature selection, statistical and topological learning, and related areas. Contributions study topics such as the hubness phenomenon in high-dimensional spaces, the use of a heuristic framework for testing the multi-manifold hypothesis for high-dimensional data, the investigation of interdisciplinary approaches to multi-dimensional obstructive sleep apnea patient data, and the inference of a dyadic measure and its simplicial geometry from binary feature data. Based on the first Women in Data Science and Mathematics (WiSDM) Research Collaboration Workshop that took place in 2017 at the Institute for Compuational and Experimental Research in Mathematics (ICERM) in Providence, Rhode Island, this volume features submissions from several of the working groups as well as contributions from the wider community. The volume is suitable for researchers in data science in industry and academia.

Data Science and Social Research II

Paolo Mariani,Mariangela Zenga
Data Science and Social Research II Book PDF

Author : Paolo Mariani,Mariangela Zenga
Publisher : Springer Nature
Page : 391 pages
File Size : 50,9 Mb
Release : 2020-11-25
Category : Social Science
ISBN : 9783030512224

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Data Science and Social Research II by Paolo Mariani,Mariangela Zenga Pdf

The peer-reviewed contributions gathered in this book address methods, software and applications of statistics and data science in the social sciences. The data revolution in social science research has not only produced new business models, but has also provided policymakers with better decision-making support tools. In this volume, statisticians, computer scientists and experts on social research discuss the opportunities and challenges of the social data revolution in order to pave the way for addressing new research problems. The respective contributions focus on complex social systems and current methodological advances in extracting social knowledge from large data sets, as well as modern social research on human behavior and society using large data sets. Moreover, they analyze integrated systems designed to take advantage of new social data sources, and discuss quality-related issues. The papers were originally presented at the 2nd International Conference on Data Science and Social Research, held in Milan, Italy, on February 4-5, 2019.

Data Science

Anonim
Data Science Book PDF

Author : Anonim
Publisher : Unknown
Page : 350 pages
File Size : 53,7 Mb
Release : 2020
Category : Big data
ISBN : 303037310X

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Data Science by Anonim Pdf

This book presents outstanding theoretical and practical findings in data science and associated interdisciplinary areas. Its main goal is to explore how data science research can revolutionize society and industries in a positive way, drawing on pure research to do so. The topics covered range from pure data science to fake news detection, as well as Internet of Things in the context of Industry 4.0. Data science is a rapidly growing field and, as a profession, incorporates a wide variety of areas, from statistics, mathematics and machine learning, to applied big data analytics. According to Forbes magazine, "Data Science" was listed as LinkedIn's fastest-growing job in 2017. This book presents selected papers from the International Conference on Contemporary Issues in Data Science (CiDaS 2019), a professional data science event that provided a real workshop (not "listen-shop") where scientists and scholars had the chance to share ideas, form new collaborations, and brainstorm on major challenges; and where industry experts could catch up on emerging solutions to help solve their concrete data science problems. Given its scope, the book will benefit not only data scientists and scientists from other domains, but also industry experts, policymakers and politicians.

Data Science Applied to Sustainability Analysis

Jennifer Dunn,Prasanna Balaprakash
Data Science Applied to Sustainability Analysis Book PDF

Author : Jennifer Dunn,Prasanna Balaprakash
Publisher : Elsevier
Page : 312 pages
File Size : 45,9 Mb
Release : 2021-05-11
Category : Science
ISBN : 9780128179772

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Data Science Applied to Sustainability Analysis by Jennifer Dunn,Prasanna Balaprakash Pdf

Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery Includes considerations sustainability analysts must evaluate when applying big data Features case studies illustrating the application of data science in sustainability analyses

Data Science Concepts and Techniques with Applications

Usman Qamar,Muhammad Summair Raza
Data Science Concepts and Techniques with Applications Book PDF

Author : Usman Qamar,Muhammad Summair Raza
Publisher : Springer Nature
Page : 492 pages
File Size : 41,9 Mb
Release : 2023-04-02
Category : Computers
ISBN : 9783031174421

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Data Science Concepts and Techniques with Applications by Usman Qamar,Muhammad Summair Raza Pdf

This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. The chapters of this book are organized into three parts: The first part (chapters 1 to 3) is a general introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics, followed by presentation of a wide range of applications and widely used techniques in data science. The second part, which has been updated and considerably extended compared to the first edition, is devoted to various techniques and tools applied in data science. Its chapters 4 to 10 detail data pre-processing, classification, clustering, text mining, deep learning, frequent pattern mining, and regression analysis. Eventually, the third part (chapters 11 and 12) present a brief introduction to Python and R, the two main data science programming languages, and shows in a completely new chapter practical data science in the WEKA (Waikato Environment for Knowledge Analysis), an open-source tool for performing different machine learning and data mining tasks. An appendix explaining the basic mathematical concepts of data science completes the book. This textbook is suitable for advanced undergraduate and graduate students as well as for industrial practitioners who carry out research in data science. They both will not only benefit from the comprehensive presentation of important topics, but also from the many application examples and the comprehensive list of further readings, which point to additional publications providing more in-depth research results or provide sources for a more detailed description of related topics. "This book delivers a systematic, carefully thoughtful material on Data Science." from the Foreword by Witold Pedrycz, U Alberta, Canada.

Data Science in Practice

Alan Said,Vicenç Torra
Data Science in Practice Book PDF

Author : Alan Said,Vicenç Torra
Publisher : Springer
Page : 195 pages
File Size : 42,5 Mb
Release : 2018-09-19
Category : Technology & Engineering
ISBN : 9783319975566

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Data Science in Practice by Alan Said,Vicenç Torra Pdf

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.

Data Science

Qurban A Memon,Shakeel Ahmed Khoja
Data Science Book PDF

Author : Qurban A Memon,Shakeel Ahmed Khoja
Publisher : CRC Press
Page : 403 pages
File Size : 52,7 Mb
Release : 2019-09-26
Category : Computers
ISBN : 9780429558825

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Data Science by Qurban A Memon,Shakeel Ahmed Khoja Pdf

The aim of this book is to provide an internationally respected collection of scientific research methods, technologies and applications in the area of data science. This book can prove useful to the researchers, professors, research students and practitioners as it reports novel research work on challenging topics in the area surrounding data science. In this book, some of the chapters are written in tutorial style concerning machine learning algorithms, data analysis, information design, infographics, relevant applications, etc. The book is structured as follows: • Part I: Data Science: Theory, Concepts, and Algorithms This part comprises five chapters on data Science theory, concepts, techniques and algorithms. • Part II: Data Design and Analysis This part comprises five chapters on data design and analysis. • Part III: Applications and New Trends in Data Science This part comprises four chapters on applications and new trends in data science.

Data Science

Pallavi Vijay Chavan,Parikshit N Mahalle,Ramchandra Mangrulkar,Idongesit Williams
Data Science Book PDF

Author : Pallavi Vijay Chavan,Parikshit N Mahalle,Ramchandra Mangrulkar,Idongesit Williams
Publisher : CRC Press
Page : 322 pages
File Size : 52,5 Mb
Release : 2022-08-15
Category : Computers
ISBN : 9781000613421

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Data Science by Pallavi Vijay Chavan,Parikshit N Mahalle,Ramchandra Mangrulkar,Idongesit Williams Pdf

This book covers the topic of data science in a comprehensive manner and synthesizes both fundamental and advanced topics of a research area that has now reached its maturity. The book starts with the basic concepts of data science. It highlights the types of data and their use and importance, followed by a discussion on a wide range of applications of data science and widely used techniques in data science. Key Features • Provides an internationally respected collection of scientific research methods, technologies and applications in the area of data science. • Presents predictive outcomes by applying data science techniques to real-life applications. • Provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. • Gives the reader a variety of intelligent applications that can be designed using data science and its allied fields. The book is aimed primarily at advanced undergraduates and graduates studying machine learning and data science. Researchers and professionals will also find this book useful.

Applied Data Science in Tourism

Roman Egger
Applied Data Science in Tourism Book PDF

Author : Roman Egger
Publisher : Springer Nature
Page : 647 pages
File Size : 49,6 Mb
Release : 2022-01-31
Category : Business & Economics
ISBN : 9783030883898

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Applied Data Science in Tourism by Roman Egger Pdf

Access to large data sets has led to a paradigm shift in the tourism research landscape. Big data is enabling a new form of knowledge gain, while at the same time shaking the epistemological foundations and requiring new methods and analysis approaches. It allows for interdisciplinary cooperation between computer sciences and social and economic sciences, and complements the traditional research approaches. This book provides a broad basis for the practical application of data science approaches such as machine learning, text mining, social network analysis, and many more, which are essential for interdisciplinary tourism research. Each method is presented in principle, viewed analytically, and its advantages and disadvantages are weighed up and typical fields of application are presented. The correct methodical application is presented with a "how-to" approach, together with code examples, allowing a wider reader base including researchers, practitioners, and students entering the field. The book is a very well-structured introduction to data science – not only in tourism – and its methodological foundations, accompanied by well-chosen practical cases. It underlines an important insight: data are only representations of reality, you need methodological skills and domain background to derive knowledge from them - Hannes Werthner, Vienna University of Technology Roman Egger has accomplished a difficult but necessary task: make clear how data science can practically support and foster travel and tourism research and applications. The book offers a well-taught collection of chapters giving a comprehensive and deep account of AI and data science for tourism - Francesco Ricci, Free University of Bozen-Bolzano This well-structured and easy-to-read book provides a comprehensive overview of data science in tourism. It contributes largely to the methodological repository beyond traditional methods. - Rob Law, University of Macau

Data Science

Pallavi Vijay Chavan,Parikshit N. Mahalle,Ramchandra Mangrulkar,Idongesit Williams
Data Science Book PDF

Author : Pallavi Vijay Chavan,Parikshit N. Mahalle,Ramchandra Mangrulkar,Idongesit Williams
Publisher : Chapman & Hall/CRC
Page : 0 pages
File Size : 55,6 Mb
Release : 2022-07
Category : Computers
ISBN : 1003283241

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Data Science by Pallavi Vijay Chavan,Parikshit N. Mahalle,Ramchandra Mangrulkar,Idongesit Williams Pdf

"The proposed book covers the topic of data science in a very comprehensive manner and synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The book starts from the basic concepts of data science; it highlights the types of data, its use and its importance, followed by discussion on a wide range of applications of data science and widely used techniques in data science. Key features: provides an internationally respected collection of scientific research methods, technologies and applications in the area of data science, presents predictive outcomes by applying data science techniques on real life applications, provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods, and gives the reader variety of intelligent applications that can be designed using data science and its allied fields. The book is aimed primarily at advanced undergraduates and graduates studying machine learning and data science. Researchers and professionals will also find this book useful"--

Data Science Thinking

Longbing Cao
Data Science Thinking Book PDF

Author : Longbing Cao
Publisher : Springer
Page : 390 pages
File Size : 49,6 Mb
Release : 2018-08-17
Category : Computers
ISBN : 9783319950921

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Data Science Thinking by Longbing Cao Pdf

This book explores answers to the fundamental questions driving the research, innovation and practices of the latest revolution in scientific, technological and economic development: how does data science transform existing science, technology, industry, economy, profession and education? How does one remain competitive in the data science field? What is responsible for shaping the mindset and skillset of data scientists? Data Science Thinking paints a comprehensive picture of data science as a new scientific paradigm from the scientific evolution perspective, as data science thinking from the scientific-thinking perspective, as a trans-disciplinary science from the disciplinary perspective, and as a new profession and economy from the business perspective.

Applied Data Science

Martin Braschler,Thilo Stadelmann,Kurt Stockinger
Applied Data Science Book PDF

Author : Martin Braschler,Thilo Stadelmann,Kurt Stockinger
Publisher : Springer
Page : 465 pages
File Size : 43,7 Mb
Release : 2019-06-13
Category : Computers
ISBN : 9783030118211

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Applied Data Science by Martin Braschler,Thilo Stadelmann,Kurt Stockinger Pdf

This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors – some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science: first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors’ combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry.