Data Science And Its Applications

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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 : 41,9 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.

Analytics in a Big Data World

Bart Baesens
Analytics in a Big Data World Book PDF

Author : Bart Baesens
Publisher : John Wiley & Sons
Page : 256 pages
File Size : 43,9 Mb
Release : 2014-04-15
Category : Business & Economics
ISBN : 9781118892749

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Analytics in a Big Data World by Bart Baesens Pdf

The guide to targeting and leveraging business opportunities using big data & analytics By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments. The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic. Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics Offers the results of research and the author's personal experience in banking, retail, and government Contains an overview of the visionary ideas and current developments on the strategic use of analytics for business Covers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysis For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities.

Trends of Data Science and Applications

Siddharth Swarup Rautaray,Phani Pemmaraju,Hrushikesha Mohanty
Trends of Data Science and Applications Book PDF

Author : Siddharth Swarup Rautaray,Phani Pemmaraju,Hrushikesha Mohanty
Publisher : Springer Nature
Page : 341 pages
File Size : 46,5 Mb
Release : 2021-03-21
Category : Computers
ISBN : 9789813368156

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Trends of Data Science and Applications by Siddharth Swarup Rautaray,Phani Pemmaraju,Hrushikesha Mohanty Pdf

This book includes an extended version of selected papers presented at the 11th Industry Symposium 2021 held during January 7–10, 2021. The book covers contributions ranging from theoretical and foundation research, platforms, methods, applications, and tools in all areas. It provides theory and practices in the area of data science, which add a social, geographical, and temporal dimension to data science research. It also includes application-oriented papers that prepare and use data in discovery research. This book contains chapters from academia as well as practitioners on big data technologies, artificial intelligence, machine learning, deep learning, data representation and visualization, business analytics, healthcare analytics, bioinformatics, etc. This book is helpful for the students, practitioners, researchers as well as industry professional.

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 : 50,8 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.

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 : 50,8 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

Qurban A Memon,Shakeel Ahmed Khoja
Data Science Book PDF

Author : Qurban A Memon,Shakeel Ahmed Khoja
Publisher : CRC Press
Page : 325 pages
File Size : 54,8 Mb
Release : 2019-09-26
Category : Computers
ISBN : 9780429554353

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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.

Machine Learning and Data Science

Prateek Agrawal,Charu Gupta,Anand Sharma,Vishu Madaan,Nisheeth Joshi
Machine Learning and Data Science Book PDF

Author : Prateek Agrawal,Charu Gupta,Anand Sharma,Vishu Madaan,Nisheeth Joshi
Publisher : John Wiley & Sons
Page : 276 pages
File Size : 45,9 Mb
Release : 2022-07-25
Category : Computers
ISBN : 9781119776475

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Machine Learning and Data Science by Prateek Agrawal,Charu Gupta,Anand Sharma,Vishu Madaan,Nisheeth Joshi Pdf

MACHINE LEARNING AND DATA SCIENCE Written and edited by a team of experts in the field, this collection of papers reflects the most up-to-date and comprehensive current state of machine learning and data science for industry, government, and academia. Machine learning (ML) and data science (DS) are very active topics with an extensive scope, both in terms of theory and applications. They have been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. Simultaneously, their applications provide important challenges that can often be addressed only with innovative machine learning and data science algorithms. These algorithms encompass the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. They also tackle related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation.

Data Science for Undergraduates

National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Board on Science Education,Division on Engineering and Physical Sciences,Committee on Applied and Theoretical Statistics,Board on Mathematical Sciences and Analytics,Computer Science and Telecommunications Board,Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective
Data Science for Undergraduates Book PDF

Author : National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Board on Science Education,Division on Engineering and Physical Sciences,Committee on Applied and Theoretical Statistics,Board on Mathematical Sciences and Analytics,Computer Science and Telecommunications Board,Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective
Publisher : National Academies Press
Page : 139 pages
File Size : 53,9 Mb
Release : 2018-11-11
Category : Education
ISBN : 9780309475594

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Data Science for Undergraduates by National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Board on Science Education,Division on Engineering and Physical Sciences,Committee on Applied and Theoretical Statistics,Board on Mathematical Sciences and Analytics,Computer Science and Telecommunications Board,Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective Pdf

Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.

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 : 50,5 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.

Advances in Data Science: Methodologies and Applications

Gloria Phillips-Wren,Anna Esposito,Lakhmi C. Jain
Advances in Data Science Methodologies and Applications Book PDF

Author : Gloria Phillips-Wren,Anna Esposito,Lakhmi C. Jain
Publisher : Springer Nature
Page : 333 pages
File Size : 46,9 Mb
Release : 2020-08-26
Category : Technology & Engineering
ISBN : 9783030518707

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Advances in Data Science: Methodologies and Applications by Gloria Phillips-Wren,Anna Esposito,Lakhmi C. Jain Pdf

Big data and data science are transforming our world today in ways we could not have imagined at the beginning of the twenty-first century. The accompanying wave of innovation has sparked advances in healthcare, engineering, business, science, and human perception, among others. The tremendous advances in computing power and intelligent techniques have opened many opportunities for managing data and investigating data in virtually every field, and the scope of data science is expected to grow over the next decade. These future research achievements will solve old challenges and create new opportunities for growth and development. Thus, the research presented in this book is interdisciplinary and covers themes embracing emotions, artificial intelligence, robotics applications, sentiment analysis, smart city problems, assistive technologies, speech melody, and fall and abnormal behavior detection. The book is directed to the researchers, practitioners, professors and students interested in recent advances in methodologies and applications of data science. An introduction to the topic is provided, and research challenges and future research opportunities are highlighted throughout.

Computational Science and Its Applications

Anupama Chadha,Sachin Sharma,Vasudha Arora
Computational Science and Its Applications Book PDF

Author : Anupama Chadha,Sachin Sharma,Vasudha Arora
Publisher : CRC Press
Page : 215 pages
File Size : 45,9 Mb
Release : 2024-01-09
Category : Computers
ISBN : 9781000799828

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Computational Science and Its Applications by Anupama Chadha,Sachin Sharma,Vasudha Arora Pdf

This new volume explores the overlapping behavior of some aspects of computational science, focusing on the intersection of computing hardware, algorithms, mathematics, and data management components. The chapters discuss the various application areas of the computational science techniques such as artificial intelligence, machine learning, data science, quantum computing, image processing, evolutionary algorithms, process simulation, deep learning, big data analysis, etc.

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 : 40,8 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 in Engineering and Management

Zdzislaw Polkowski,Sambit Kumar Mishra,Julian Vasilev
Data Science in Engineering and Management Book PDF

Author : Zdzislaw Polkowski,Sambit Kumar Mishra,Julian Vasilev
Publisher : CRC Press
Page : 159 pages
File Size : 46,6 Mb
Release : 2021-12-31
Category : Technology & Engineering
ISBN : 9781000520842

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Data Science in Engineering and Management by Zdzislaw Polkowski,Sambit Kumar Mishra,Julian Vasilev Pdf

This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis. Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively. This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.

Data Science and Productivity Analytics

Vincent Charles,Juan Aparicio,Joe Zhu
Data Science and Productivity Analytics Book PDF

Author : Vincent Charles,Juan Aparicio,Joe Zhu
Publisher : Springer Nature
Page : 441 pages
File Size : 55,5 Mb
Release : 2020-05-23
Category : Business & Economics
ISBN : 9783030433840

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Data Science and Productivity Analytics by Vincent Charles,Juan Aparicio,Joe Zhu Pdf

This book includes a spectrum of concepts, such as performance, productivity, operations research, econometrics, and data science, for the practically and theoretically important areas of ‘productivity analysis/data envelopment analysis’ and ‘data science/big data’. Data science is defined as the collection of scientific methods, processes, and systems dedicated to extracting knowledge or insights from data and it develops on concepts from various domains, containing mathematics and statistical methods, operations research, machine learning, computer programming, pattern recognition, and data visualisation, among others. Examples of data science techniques include linear and logistic regressions, decision trees, Naïve Bayesian classifier, principal component analysis, neural networks, predictive modelling, deep learning, text analysis, survival analysis, and so on, all of which allow using the data to make more intelligent decisions. On the other hand, it is without a doubt that nowadays the amount of data is exponentially increasing, and analysing large data sets has become a key basis of competition and innovation, underpinning new waves of productivity growth. This book aims to bring a fresh look onto the various ways that data science techniques could unleash value and drive productivity from these mountains of data. Researchers working in productivity analysis/data envelopment analysis will benefit from learning about the tools available in data science/big data that can be used in their current research analyses and endeavours. The data scientists, on the other hand, will also get benefit from learning about the plethora of applications available in productivity analysis/data envelopment analysis.

Data Science

Gyanendra K. Verma,Badal Soni,Salah Bourennane,Alexandre C. B. Ramos
Data Science Book PDF

Author : Gyanendra K. Verma,Badal Soni,Salah Bourennane,Alexandre C. B. Ramos
Publisher : Springer Nature
Page : 444 pages
File Size : 41,9 Mb
Release : 2021-08-19
Category : Computers
ISBN : 9789811616815

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Data Science by Gyanendra K. Verma,Badal Soni,Salah Bourennane,Alexandre C. B. Ramos Pdf

This book targets an audience with a basic understanding of deep learning, its architectures, and its application in the multimedia domain. Background in machine learning is helpful in exploring various aspects of deep learning. Deep learning models have a major impact on multimedia research and raised the performance bar substantially in many of the standard evaluations. Moreover, new multi-modal challenges are tackled, which older systems would not have been able to handle. However, it is very difficult to comprehend, let alone guide, the process of learning in deep neural networks, there is an air of uncertainty about exactly what and how these networks learn. By the end of the book, the readers will have an understanding of different deep learning approaches, models, pre-trained models, and familiarity with the implementation of various deep learning algorithms using various frameworks and libraries.