Advances In Data Science Methodologies And Applications

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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 : 47,6 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.

Advances in Data Science

Anonim
Advances in Data Science Book PDF

Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 45,5 Mb
Release : 2021
Category : Data mining
ISBN : 303051871X

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Advances in Data Science by Anonim 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.

Data Science for Healthcare

Sergio Consoli,Diego Reforgiato Recupero,Milan Petković
Data Science for Healthcare Book PDF

Author : Sergio Consoli,Diego Reforgiato Recupero,Milan Petković
Publisher : Springer
Page : 367 pages
File Size : 53,9 Mb
Release : 2019-02-23
Category : Computers
ISBN : 9783030052492

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Data Science for Healthcare by Sergio Consoli,Diego Reforgiato Recupero,Milan Petković Pdf

This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.

Data Science for Economics and Finance

Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana
Data Science for Economics and Finance Book PDF

Author : Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana
Publisher : Springer Nature
Page : 357 pages
File Size : 51,7 Mb
Release : 2021
Category : Application software
ISBN : 9783030668914

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Data Science for Economics and Finance by Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana Pdf

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

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 : 47,9 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"--

Advances in Data Science and Analytics

M. Niranjanamurthy,Hemant Kumar Gianey,Amir H. Gandomi
Advances in Data Science and Analytics Book PDF

Author : M. Niranjanamurthy,Hemant Kumar Gianey,Amir H. Gandomi
Publisher : John Wiley & Sons
Page : 356 pages
File Size : 41,6 Mb
Release : 2022-11-01
Category : Computers
ISBN : 9781119792802

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Advances in Data Science and Analytics by M. Niranjanamurthy,Hemant Kumar Gianey,Amir H. Gandomi Pdf

ADVANCES in DATA SCIENCE and ANALYTICS Presenting the concepts and advances of data science and analytics, this volume, written and edited by a global team of experts, also goes into the practical applications that can be utilized across multiple disciplines and industries, for both the engineer and the student, focusing on machining learning, big data, business intelligence, and analytics. Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, deep learning, and big data. Data analytics software is a more focused version of this and can even be considered part of the larger process. Analytics is devoted to realizing actionable insights that can be applied immediately based on existing queries. For the purposes of this volume, data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. While a data scientist is expected to forecast the future based on past patterns, data analysts extract meaningful insights from various data sources. Although data mining and other related areas have been around for a few decades, data science and analytics are still quickly evolving, and the processes and technologies change, almost on a day-to-day basis. This volume provides an overview of some of the most important advances in these areas today, including practical coverage of the daily applications. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in these areas, this is a must-have for any library.

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 : 44,7 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 and Computing Technology

Suman Ghosal,Amitava Choudhury,Vikram Kumar Saxena,Arindam Biswas,Prasenjit Chatterjee
Advances in Data Science and Computing Technology Book PDF

Author : Suman Ghosal,Amitava Choudhury,Vikram Kumar Saxena,Arindam Biswas,Prasenjit Chatterjee
Publisher : CRC Press
Page : 449 pages
File Size : 53,8 Mb
Release : 2022-11-24
Category : Computers
ISBN : 9781000564860

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Advances in Data Science and Computing Technology by Suman Ghosal,Amitava Choudhury,Vikram Kumar Saxena,Arindam Biswas,Prasenjit Chatterjee Pdf

This volume helps to address the genuine 21st century need for advances in data science and computing technology. It provides an abundance of new research and studies on progressive and innovative technologies, including artificial intelligence, communication systems, cyber security applications, data analytics, Internet of Things (IoT), machine learning, power systems, VLSI, embedded systems, and much more. The book presents a variety of interesting and important aspects of data science and computing technologies and methodologies in a wide range of applications, including deep learning, DNA cryptography, classy fuzzy MPPT controller, driving assistance, and safety systems. Novel algorithms and their applications for solving cutting-edge computational and data science problems are included also for an interdisciplinary research perspective. The book addresses recent applications of deep learning and ANN paradigms, the role and impact of big data in the e-commerce and retail sectors, algorithms for load balancing in cloud computing, advances in embedded system based applications, optimization techniques using a MATLAB platform, and techniques for improving information and network security. Advances in Data Science and Computing Technology: Methodology and Applications provides a wealth of valuable information and food for thought on many important issues for data scientists and researchers, industry professionals, and faculty and students in the data and computing sciences.

Principles and Methods for Data Science

Anonim
Principles and Methods for Data Science Book PDF

Author : Anonim
Publisher : Elsevier
Page : 498 pages
File Size : 53,9 Mb
Release : 2020-05-28
Category : Mathematics
ISBN : 9780444642127

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Principles and Methods for Data Science by Anonim Pdf

Principles and Methods for Data Science, Volume 43 in the Handbook of Statistics series, highlights new advances in the field, with this updated volume presenting interesting and timely topics, including Competing risks, aims and methods, Data analysis and mining of microbial community dynamics, Support Vector Machines, a robust prediction method with applications in bioinformatics, Bayesian Model Selection for Data with High Dimension, High dimensional statistical inference: theoretical development to data analytics, Big data challenges in genomics, Analysis of microarray gene expression data using information theory and stochastic algorithm, Hybrid Models, Markov Chain Monte Carlo Methods: Theory and Practice, and more. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Statistics series Updated release includes the latest information on Principles and Methods for Data Science

Data-Driven Science and Engineering

Steven L. Brunton,J. Nathan Kutz
Data Driven Science and Engineering Book PDF

Author : Steven L. Brunton,J. Nathan Kutz
Publisher : Cambridge University Press
Page : 615 pages
File Size : 42,9 Mb
Release : 2022-05-05
Category : Computers
ISBN : 9781009098489

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Data-Driven Science and Engineering by Steven L. Brunton,J. Nathan Kutz Pdf

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Advances in Statistical Methodologies and Their Application to Real Problems

Tsukasa Hokimoto
Advances in Statistical Methodologies and Their Application to Real Problems Book PDF

Author : Tsukasa Hokimoto
Publisher : BoD – Books on Demand
Page : 327 pages
File Size : 49,5 Mb
Release : 2017-04-26
Category : Mathematics
ISBN : 9789535131014

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Advances in Statistical Methodologies and Their Application to Real Problems by Tsukasa Hokimoto Pdf

In recent years, statistical techniques and methods for data analysis have advanced significantly in a wide range of research areas. These developments enable researchers to analyze increasingly large datasets with more flexibility and also more accurately estimate and evaluate the phenomena they study. We recognize the value of recent advances in data analysis techniques in many different research fields. However, we also note that awareness of these different statistical and probabilistic approaches may vary, owing to differences in the datasets typical of different research fields. This book provides a cross-disciplinary forum for exploring the variety of new data analysis techniques emerging from different fields.

Big and Complex Data Analysis

S. Ejaz Ahmed
Big and Complex Data Analysis Book PDF

Author : S. Ejaz Ahmed
Publisher : Springer
Page : 386 pages
File Size : 42,8 Mb
Release : 2017-03-21
Category : Mathematics
ISBN : 9783319415734

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Big and Complex Data Analysis by S. Ejaz Ahmed Pdf

This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Its peer-reviewed contributions showcase recent advances in variable selection, estimation and prediction strategies for a host of useful models, as well as essential new developments in the field. The continued and rapid advancement of modern technology now allows scientists to collect data of increasingly unprecedented size and complexity. Examples include epigenomic data, genomic data, proteomic data, high-resolution image data, high-frequency financial data, functional and longitudinal data, and network data. Simultaneous variable selection and estimation is one of the key statistical problems involved in analyzing such big and complex data. The purpose of this book is to stimulate research and foster interaction between researchers in the area of high-dimensional data analysis. More concretely, its goals are to: 1) highlight and expand the breadth of existing methods in big data and high-dimensional data analysis and their potential for the advancement of both the mathematical and statistical sciences; 2) identify important directions for future research in the theory of regularization methods, in algorithmic development, and in methodologies for different application areas; and 3) facilitate collaboration between theoretical and subject-specific researchers.

Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence

Trivedi, Shrawan Kumar,Dey, Shubhamoy,Kumar, Anil,Panda, Tapan Kumar
Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence Book PDF

Author : Trivedi, Shrawan Kumar,Dey, Shubhamoy,Kumar, Anil,Panda, Tapan Kumar
Publisher : IGI Global
Page : 438 pages
File Size : 48,9 Mb
Release : 2017-02-14
Category : Computers
ISBN : 9781522520320

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Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence by Trivedi, Shrawan Kumar,Dey, Shubhamoy,Kumar, Anil,Panda, Tapan Kumar Pdf

The development of business intelligence has enhanced the visualization of data to inform and facilitate business management and strategizing. By implementing effective data-driven techniques, this allows for advance reporting tools to cater to company-specific issues and challenges. The Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence is a key resource on the latest advancements in business applications and the use of mining software solutions to achieve optimal decision-making and risk management results. Highlighting innovative studies on data warehousing, business activity monitoring, and text mining, this publication is an ideal reference source for research scholars, management faculty, and practitioners.

Handbook on Artificial Intelligence-Empowered Applied Software Engineering

Maria Virvou,George A. Tsihrintzis,Nikolaos G. Bourbakis,Lakhmi C. Jain
Handbook on Artificial Intelligence Empowered Applied Software Engineering Book PDF

Author : Maria Virvou,George A. Tsihrintzis,Nikolaos G. Bourbakis,Lakhmi C. Jain
Publisher : Springer Nature
Page : 342 pages
File Size : 55,9 Mb
Release : 2022-09-03
Category : Technology & Engineering
ISBN : 9783031082023

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Handbook on Artificial Intelligence-Empowered Applied Software Engineering by Maria Virvou,George A. Tsihrintzis,Nikolaos G. Bourbakis,Lakhmi C. Jain Pdf

This book provides a structured overview of artificial intelligence-empowered applied software engineering. Evolving technological advancements in big data, smartphone and mobile software applications, the Internet of Things and a vast range of application areas in all sorts of human activities and professions lead current research towards the efficient incorporation of artificial intelligence enhancements into software and the empowerment of software with artificial intelligence. This book at hand, devoted to Novel Methodologies to Engineering Smart Software Systems Novel Methodologies to Engineering Smart Software Systems, constitutes the first volume of a two-volume Handbook on Artificial Intelligence-empowered Applied Software Engineering. Topics include very significant advances in (i) Artificial Intelligence-Assisted Software Development and (ii) Software Engineering Tools to develop Artificial Intelligence Applications, as well as a detailed Survey of Recent Relevant Literature. Professors, researchers, scientists, engineers and students in artificial intelligence, software engineering and computer science-related disciplines are expected to benefit from it, along with interested readers from other disciplines.

Data Science in Theory and Practice

Maria Cristina Mariani,Osei Kofi Tweneboah,Maria Pia Beccar-Varela
Data Science in Theory and Practice Book PDF

Author : Maria Cristina Mariani,Osei Kofi Tweneboah,Maria Pia Beccar-Varela
Publisher : John Wiley & Sons
Page : 404 pages
File Size : 54,9 Mb
Release : 2021-10-12
Category : Mathematics
ISBN : 9781119674689

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Data Science in Theory and Practice by Maria Cristina Mariani,Osei Kofi Tweneboah,Maria Pia Beccar-Varela Pdf

DATA SCIENCE IN THEORY AND PRACTICE EXPLORE THE FOUNDATIONS OF DATA SCIENCE WITH THIS INSIGHTFUL NEW RESOURCE Data Science in Theory and Practice delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. The book offers readers a multitude of topics all relevant to the analysis of complex data sets. Along with a robust exploration of the theory underpinning data science, it contains numerous applications to specific and practical problems. The book also provides examples of code algorithms in R and Python and provides pseudo-algorithms to port the code to any other language. Ideal for students and practitioners without a strong background in data science, readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets Perfect for advanced undergraduate and graduate students in Data Science, Business Analytics, and Statistics programs, Data Science in Theory and Practice will also earn a place in the libraries of practicing data scientists, data and business analysts, and statisticians in the private sector, government, and academia.