R Programming An Approach To Data Analytics
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R Programming An Approach To Data Analytics
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Author : G. Sudhamathy, C. Jothi Venkateswaran
language : en
Publisher: MJP Publisher
Release Date : 2019-06-03
R Programming An Approach To Data Analytics written by G. Sudhamathy, C. Jothi Venkateswaran and has been published by MJP Publisher this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-03 with Computers categories.
Chapter 1 - Basics of R, Chapter 2 - Data Types in R , Chapter 3 - Data Preparation. Chapter 4 - Graphics using R, Chapter 5 - Statistical Analysis Using R, Chapter 6 - Data Mining Using R, Chapter 7 - Case Studies. Huge volumes of data are being generated by many sources like commercial enterprises, scientific domains and general public daily. According to a recent research, data production will be 44 times greater in 2020 than it was in 2010. Data being a vital resource for business organizations and other domains like education, health, manufacturing etc., its management and analysis is becoming increasingly important. This data, due to its volume, variety and velocity, often referred to as Big Data, also includes highly unstructured data in the form of textual documents, web pages, graphical information and social media comments. Since Big Data is characterised by massive sample sizes, high dimensionality and intrinsic heterogeneity, traditional approaches to data management, visualisation and analytics are no longer satisfactorily applicable. There is therefore an urgent need for newer tools, better frameworks and workable methodologies for such data to be appropriately categorised, logically segmented, efficiently analysed and securely managed. This requirement has resulted in an emerging new discipline of Data Science that is now gaining much attention with researchers and practitioners in the field of Data Analytics.
Big Data Analytics And Intelligent Techniques For Smart Cities
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Author : Kolla Bhanu Prakash
language : en
Publisher: CRC Press
Release Date : 2021-09-20
Big Data Analytics And Intelligent Techniques For Smart Cities written by Kolla Bhanu Prakash and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-20 with Technology & Engineering categories.
Big Data Analytics and Intelligent Techniques for Smart Cities covers fundamentals, advanced concepts, and applications of big data analytics for smart cities in a single volume. This comprehensive reference text discusses big data theory modeling and simulation for smart cities and examines case studies in a single volume. The text discusses how to develop a smart city and state-of-the-art system design, system verification, real-time control and adaptation, Internet of Things, and testbeds. It covers applications of smart cities as they relate to smart transportation/connected vehicle (CV) and intelligent transportation systems (ITS) for improved mobility, safety, and environmental protection. It will be useful as a reference text for graduate students in different areas including electrical engineering, computer science engineering, civil engineering, and electronics and communications engineering. Features: Technologies and algorithms associated with the application of big data for smart cities Discussions on big data theory modeling and simulation for smart cities Applications of smart cities as they relate to smart transportation and intelligent transportation systems (ITS) Discussions on concepts including smart education, smart culture, and smart transformation management for social and societal changes
Methodologies And Applications Of Computational Statistics For Machine Intelligence
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Author : Samanta, Debabrata
language : en
Publisher: IGI Global
Release Date : 2021-06-25
Methodologies And Applications Of Computational Statistics For Machine Intelligence written by Samanta, Debabrata and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-25 with Computers categories.
With the field of computational statistics growing rapidly, there is a need for capturing the advances and assessing their impact. Advances in simulation and graphical analysis also add to the pace of the statistical analytics field. Computational statistics play a key role in financial applications, particularly risk management and derivative pricing, biological applications including bioinformatics and computational biology, and computer network security applications that touch the lives of people. With high impacting areas such as these, it becomes important to dig deeper into the subject and explore the key areas and their progress in the recent past. Methodologies and Applications of Computational Statistics for Machine Intelligence serves as a guide to the applications of new advances in computational statistics. This text holds an accumulation of the thoughts of multiple experts together, keeping the focus on core computational statistics that apply to all domains. Covering topics including artificial intelligence, deep learning, and trend analysis, this book is an ideal resource for statisticians, computer scientists, mathematicians, lecturers, tutors, researchers, academic and corporate libraries, practitioners, professionals, students, and academicians.
Data Analytics
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Author : Juan J. Cuadrado-Gallego
language : en
Publisher: Springer Nature
Release Date : 2023-11-10
Data Analytics written by Juan J. Cuadrado-Gallego and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-10 with Computers categories.
Building upon the knowledge introduced in The Data Science Framework, this book provides a comprehensive and detailed examination of each aspect of Data Analytics, both from a theoretical and practical standpoint. The book explains representative algorithms associated with different techniques, from their theoretical foundations to their implementation and use with software tools. Designed as a textbook for a Data Analytics Fundamentals course, it is divided into seven chapters to correspond with 16 weeks of lessons, including both theoretical and practical exercises. Each chapter is dedicated to a lesson, allowing readers to dive deep into each topic with detailed explanations and examples. Readers will learn the theoretical concepts and then immediately apply them to practical exercises to reinforce their knowledge. And in the lab sessions, readers will learn the ins and outs of the R environment and data science methodology to solve exercises with the R language. With detailed solutions provided for all examples and exercises, readers can use this book to study and master data analytics on their own. Whether you're a student, professional, or simply curious about data analytics, this book is a must-have for anyone looking to expand their knowledge in this exciting field. The following chapters have contributions by: Chapter 4, "Anomaly Detection" - Juan J. Cuadrado-Gallego, Yuri Demchenko, Josefa Gómez, and Abdelhamid Tayebi Chapter 5, "Unsupervised Classification" - Juan J. Cuadrado-Gallego, Yuri Demchenko, and Abdelhamid Tayebi Chapter 6, "Supervised Classification" - Juan J. Cuadrado-Gallego, Yuri Demchenko, and Josefa Gómez
Practical Data Analytics For Innovation In Medicine
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Author : Gary D. Miner
language : en
Publisher: Academic Press
Release Date : 2023-02-08
Practical Data Analytics For Innovation In Medicine written by Gary D. Miner and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-08 with Science categories.
Practical Data Analytics for Innovation in Medicine: Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies, Second Edition discusses the needs of healthcare and medicine in the 21st century, explaining how data analytics play an important and revolutionary role. With healthcare effectiveness and economics facing growing challenges, there is a rapidly emerging movement to fortify medical treatment and administration by tapping the predictive power of big data, such as predictive analytics, which can bolster patient care, reduce costs, and deliver greater efficiencies across a wide range of operational functions. Sections bring a historical perspective, highlight the importance of using predictive analytics to help solve health crisis such as the COVID-19 pandemic, provide access to practical step-by-step tutorials and case studies online, and use exercises based on real-world examples of successful predictive and prescriptive tools and systems. The final part of the book focuses on specific technical operations related to quality, cost-effective medical and nursing care delivery and administration brought by practical predictive analytics. - Brings a historical perspective in medical care to discuss both the current status of health care delivery worldwide and the importance of using modern predictive analytics to help solve the health care crisis - Provides online tutorials on several predictive analytics systems to help readers apply their knowledge on today's medical issues and basic research - Teaches how to develop effective predictive analytic research and to create decisioning/prescriptive analytic systems to make medical decisions quicker and more accurate
Big Data Analytics Using Multiple Criteria Decision Making Models
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Author : Ramakrishnan Ramanathan
language : en
Publisher: CRC Press
Release Date : 2017-07-12
Big Data Analytics Using Multiple Criteria Decision Making Models written by Ramakrishnan Ramanathan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-12 with Computers categories.
Multiple Criteria Decision Making (MCDM) is a subfield of Operations Research, dealing with decision making problems. A decision-making problem is characterized by the need to choose one or a few among a number of alternatives. The field of MCDM assumes special importance in this era of Big Data and Business Analytics. In this volume, the focus will be on modelling-based tools for Business Analytics (BA), with exclusive focus on the sub-field of MCDM within the domain of operations research. The book will include an Introduction to Big Data and Business Analytics, and challenges and opportunities for developing MCDM models in the era of Big Data.
Applying Data Science And Learning Analytics Throughout A Learner S Lifespan
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Author : Trajkovski, Goran
language : en
Publisher: IGI Global
Release Date : 2022-05-06
Applying Data Science And Learning Analytics Throughout A Learner S Lifespan written by Trajkovski, Goran and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-06 with Education categories.
Research in the domains of learning analytics and educational data mining has prototyped an approach where methodologies from data science and machine learning are used to gain insights into the learning process by using large amounts of data. As many training and academic institutions are maturing in their data-driven decision making, useful, scalable, and interesting trends are emerging. Organizations can benefit from sharing information on those efforts. Applying Data Science and Learning Analytics Throughout a Learner’s Lifespan examines novel and emerging applications of data science and sister disciplines for gaining insights from data to inform interventions into learners’ journeys and interactions with academic institutions. Data is collected at various times and places throughout a learner’s lifecycle, and the learners and the institution should benefit from the insights and knowledge gained from this data. Covering topics such as learning analytics dashboards, text network analysis, and employment recruitment, this book is an indispensable resource for educators, computer scientists, faculty of higher education, government officials, educational administration, students of higher education, pre-service teachers, business professionals, researchers, and academicians.
Using R To Unlock The Value Of Big Data Big Data Analytics With Oracle R Enterprise And Oracle R Connector For Hadoop
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Author : Mark Hornick
language : en
Publisher: McGraw Hill Professional
Release Date : 2013-06-14
Using R To Unlock The Value Of Big Data Big Data Analytics With Oracle R Enterprise And Oracle R Connector For Hadoop written by Mark Hornick and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-14 with Computers categories.
The Oracle Press Guide to Big Data Analytics using R Cowritten by members of the Big Data team at Oracle, this Oracle Press book focuses on analyzing data with R while making it scalable using Oracle’s R technologies. Using R to Unlock the Value of Big Data provides an introduction to open source R and describes issues with traditional R and database interaction. The book then offers in-depth coverage of Oracle’s strategic R offerings: Oracle R Enterprise, Oracle R Distribution, ROracle, and Oracle R Connector for Hadoop. You can practice your new skills using the end-of-chapter exercises.
Data Analytics For Intelligent Transportation Systems
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Author : Mashrur Chowdhury
language : en
Publisher: Elsevier
Release Date : 2024-11-02
Data Analytics For Intelligent Transportation Systems written by Mashrur Chowdhury and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-02 with Computers categories.
Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. It presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies. All fundamentals/concepts presented in this book are explained in the context of ITS. Users will learn everything from the basics of different ITS data types and characteristics to how to evaluate alternative data analytics for different ITS applications. They will discover how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. Data Analytics for Intelligent Transportation Systems will prepare an educated ITS workforce and tool builders to make the vision for safe, reliable, and environmentally sustainable intelligent transportation systems a reality. It serves as a primary or supplemental textbook for upper-level undergraduate and graduate ITS courses and a valuable reference for ITS practitioners. - Utilizes real ITS examples to facilitate a quicker grasp of materials presented - Contains contributors from both leading academic and commercial domains - Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications - Includes exercise problems in each chapter to help readers apply and master the learned fundamentals, concepts, and techniques - New to the second edition: Two new chapters on Quantum Computing in Data Analytics and Society and Environment in ITS Data Analytics
Data Analytics In Cognitive Linguistics
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Author : Dennis Tay
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-05-09
Data Analytics In Cognitive Linguistics written by Dennis Tay and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-09 with Language Arts & Disciplines categories.
Contemporary data analytics involves extracting insights from data and translating them into action. With its turn towards empirical methods and convergent data sources, cognitive linguistics is a fertile context for data analytics. There are key differences between data analytics and statistical analysis as typically conceived. Though the former requires the latter, it emphasizes the role of domain-specific knowledge. Statistical analysis also tends to be associated with preconceived hypotheses and controlled data. Data analytics, on the other hand, can help explore unstructured datasets and inspire emergent questions. This volume addresses two key aspects in data analytics for cognitive linguistic work. Firstly, it elaborates the bottom-up guiding role of data analytics in the research trajectory, and how it helps to formulate and refine questions. Secondly, it shows how data analytics can suggest concrete courses of research-based action, which is crucial for cognitive linguistics to be truly applied. The papers in this volume impart various data analytic methods and report empirical studies across different areas of research and application. They aim to benefit new and experienced researchers alike.