Xml And Web Technologies For Data Sciences With R

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XML and Web Technologies for Data Sciences with R

Deborah Nolan,Duncan Temple Lang
XML and Web Technologies for Data Sciences with R Book PDF

Author : Deborah Nolan,Duncan Temple Lang
Publisher : Springer Science & Business Media
Page : 677 pages
File Size : 46,7 Mb
Release : 2013-11-29
Category : Computers
ISBN : 9781461479000

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XML and Web Technologies for Data Sciences with R by Deborah Nolan,Duncan Temple Lang Pdf

Web technologies are increasingly relevant to scientists working with data, for both accessing data and creating rich dynamic and interactive displays. The XML and JSON data formats are widely used in Web services, regular Web pages and JavaScript code, and visualization formats such as SVG and KML for Google Earth and Google Maps. In addition, scientists use HTTP and other network protocols to scrape data from Web pages, access REST and SOAP Web Services, and interact with NoSQL databases and text search applications. This book provides a practical hands-on introduction to these technologies, including high-level functions the authors have developed for data scientists. It describes strategies and approaches for extracting data from HTML, XML, and JSON formats and how to programmatically access data from the Web. Along with these general skills, the authors illustrate several applications that are relevant to data scientists, such as reading and writing spreadsheet documents both locally and via Google Docs, creating interactive and dynamic visualizations, displaying spatial-temporal displays with Google Earth, and generating code from descriptions of data structures to read and write data. These topics demonstrate the rich possibilities and opportunities to do new things with these modern technologies. The book contains many examples and case-studies that readers can use directly and adapt to their own work. The authors have focused on the integration of these technologies with the R statistical computing environment. However, the ideas and skills presented here are more general, and statisticians who use other computing environments will also find them relevant to their work. Deborah Nolan is Professor of Statistics at University of California, Berkeley. Duncan Temple Lang is Associate Professor of Statistics at University of California, Davis and has been a member of both the S and R development teams.

Data Science in R

Deborah Nolan,Duncan Temple Lang
Data Science in R Book PDF

Author : Deborah Nolan,Duncan Temple Lang
Publisher : CRC Press
Page : 767 pages
File Size : 46,9 Mb
Release : 2015-04-21
Category : Business & Economics
ISBN : 9781498759878

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Data Science in R by Deborah Nolan,Duncan Temple Lang Pdf

Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and ComputationData Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts

Learning Data Science

Sam Lau,Joseph Gonzalez,Deborah Nolan
Learning Data Science Book PDF

Author : Sam Lau,Joseph Gonzalez,Deborah Nolan
Publisher : "O'Reilly Media, Inc."
Page : 597 pages
File Size : 48,8 Mb
Release : 2023-09-15
Category : Electronic
ISBN : 9781098112974

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Learning Data Science by Sam Lau,Joseph Gonzalez,Deborah Nolan Pdf

As an aspiring data scientist, you appreciate why organizations rely on data for important decisions--whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the data science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data. Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle. It's aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the "technical/nontechnical" divide. If you have a basic knowledge of Python programming, you'll learn how to work with data using industry-standard tools like pandas. Refine a question of interest to one that can be studied with data Pursue data collection that may involve text processing, web scraping, etc. Glean valuable insights about data through data cleaning, exploration, and visualization Learn how to use modeling to describe the data Generalize findings beyond the data

Web and Network Data Science

Thomas W. Miller
Web and Network Data Science Book PDF

Author : Thomas W. Miller
Publisher : FT Press
Page : 370 pages
File Size : 53,9 Mb
Release : 2014-12-19
Category : Business & Economics
ISBN : 9780133887648

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Web and Network Data Science by Thomas W. Miller Pdf

Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.

Data Wrangling with R

Bradley C. Boehmke, Ph.D.
Data Wrangling with R Book PDF

Author : Bradley C. Boehmke, Ph.D.
Publisher : Springer
Page : 238 pages
File Size : 44,5 Mb
Release : 2016-11-17
Category : Computers
ISBN : 9783319455990

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Data Wrangling with R by Bradley C. Boehmke, Ph.D. Pdf

This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Data wrangling, which is also commonly referred to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process. Roughly 80% of data analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis, reporting), it is essential that one become fluent and efficient in data wrangling techniques. This book will guide the user through the data wrangling process via a step-by-step tutorial approach and provide a solid foundation for working with data in R. The author's goal is to teach the user how to easily wrangle data in order to spend more time on understanding the content of the data. By the end of the book, the user will have learned: How to work with different types of data such as numerics, characters, regular expressions, factors, and dates The difference between different data structures and how to create, add additional components to, and subset each data structure How to acquire and parse data from locations previously inaccessible How to develop functions and use loop control structures to reduce code redundancy How to use pipe operators to simplify code and make it more readable How to reshape the layout of data and manipulate, summarize, and join data sets

Automated Data Collection with R

Simon Munzert,Christian Rubba,Peter Meißner,Dominic Nyhuis
Automated Data Collection with R Book PDF

Author : Simon Munzert,Christian Rubba,Peter Meißner,Dominic Nyhuis
Publisher : John Wiley & Sons
Page : 474 pages
File Size : 42,5 Mb
Release : 2015-01-20
Category : Computers
ISBN : 9781118834817

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Automated Data Collection with R by Simon Munzert,Christian Rubba,Peter Meißner,Dominic Nyhuis Pdf

A hands on guide to web scraping and text mining for both beginners and experienced users of R Introduces fundamental concepts of the main architecture of the web and databases and covers HTTP, HTML, XML, JSON, SQL. Provides basic techniques to query web documents and data sets (XPath and regular expressions). An extensive set of exercises are presented to guide the reader through each technique. Explores both supervised and unsupervised techniques as well as advanced techniques such as data scraping and text management. Case studies are featured throughout along with examples for each technique presented. R code and solutions to exercises featured in the book are provided on a supporting website.

Mastering Data Analysis with R

Gergely Daroczi
Mastering Data Analysis with R Book PDF

Author : Gergely Daroczi
Publisher : Packt Publishing Ltd
Page : 397 pages
File Size : 50,9 Mb
Release : 2015-09-30
Category : Computers
ISBN : 9781783982035

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Mastering Data Analysis with R by Gergely Daroczi Pdf

Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R's advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R's range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.

Machine Learning with R

Abhijit Ghatak
Machine Learning with R Book PDF

Author : Abhijit Ghatak
Publisher : Springer
Page : 210 pages
File Size : 51,7 Mb
Release : 2017-11-23
Category : Computers
ISBN : 9789811068089

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Machine Learning with R by Abhijit Ghatak Pdf

This book helps readers understand the mathematics of machine learning, and apply them in different situations. It is divided into two basic parts, the first of which introduces readers to the theory of linear algebra, probability, and data distributions and it’s applications to machine learning. It also includes a detailed introduction to the concepts and constraints of machine learning and what is involved in designing a learning algorithm. This part helps readers understand the mathematical and statistical aspects of machine learning. In turn, the second part discusses the algorithms used in supervised and unsupervised learning. It works out each learning algorithm mathematically and encodes it in R to produce customized learning applications. In the process, it touches upon the specifics of each algorithm and the science behind its formulation. The book includes a wealth of worked-out examples along with R codes. It explains the code for each algorithm, and readers can modify the code to suit their own needs. The book will be of interest to all researchers who intend to use R for machine learning, and those who are interested in the practical aspects of implementing learning algorithms for data analysis. Further, it will be particularly useful and informative for anyone who has struggled to relate the concepts of mathematics and statistics to machine learning.

Sports Analytics and Data Science

Thomas W. Miller
Sports Analytics and Data Science Book PDF

Author : Thomas W. Miller
Publisher : FT Press
Page : 576 pages
File Size : 46,7 Mb
Release : 2015-11-18
Category : Business & Economics
ISBN : 9780133887419

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Sports Analytics and Data Science by Thomas W. Miller Pdf

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. This up-to-the-minute reference will help you master all three facets of sports analytics — and use it to win! Sports Analytics and Data Science is the most accessible and practical guide to sports analytics for everyone who cares about winning and everyone who is interested in data science. You’ll discover how successful sports analytics blends business and sports savvy, modern information technology, and sophisticated modeling techniques. You’ll master the discipline through realistic sports vignettes and intuitive data visualizations–not complex math. Every chapter focuses on one key sports analytics application. Miller guides you through assessing players and teams, predicting scores and making game-day decisions, crafting brands and marketing messages, increasing revenue and profitability, and much more. Step by step, you’ll learn how analysts transform raw data and analytical models into wins: both on the field and in any sports business.

Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 2

Suresh Chandra Satapathy,Amit Joshi
Information and Communication Technology for Intelligent Systems ICTIS 2017 Volume 2 Book PDF

Author : Suresh Chandra Satapathy,Amit Joshi
Publisher : Springer
Page : 666 pages
File Size : 42,5 Mb
Release : 2017-08-16
Category : Technology & Engineering
ISBN : 9783319636450

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Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 2 by Suresh Chandra Satapathy,Amit Joshi Pdf

This volume includes 73 papers presented at ICTIS 2017: Second International Conference on Information and Communication Technology for Intelligent Systems. The conference was held on 25th and 26th March 2017, in Ahmedabad, India and organized jointly by the Associated Chambers of Commerce and Industry of India (ASSOCHAM) Gujarat Chapter, the G R Foundation, the Association of Computer Machinery, Ahmedabad Chapter and supported by the Computer Society of India Division IV – Communication and Division V – Education and Research. The papers featured mainly focus on information and communications technology (ICT) and its applications in intelligent computing, cloud storage, data mining and software analysis. The fundamentals of various data analytics and algorithms discussed are useful to researchers in the fiel d.

The SAGE Handbook of Research Methods in Political Science and International Relations

Luigi Curini,Robert Franzese
The SAGE Handbook of Research Methods in Political Science and International Relations Book PDF

Author : Luigi Curini,Robert Franzese
Publisher : SAGE
Page : 1861 pages
File Size : 55,8 Mb
Release : 2020-04-09
Category : Political Science
ISBN : 9781526486394

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The SAGE Handbook of Research Methods in Political Science and International Relations by Luigi Curini,Robert Franzese Pdf

The SAGE Handbook of Research Methods in Political Science and International Relations offers a comprehensive overview of research processes in social science — from the ideation and design of research projects, through the construction of theoretical arguments, to conceptualization, measurement, & data collection, and quantitative & qualitative empirical analysis — exposited through 65 major new contributions from leading international methodologists. Each chapter surveys, builds upon, and extends the modern state of the art in its area. Following through its six-part organization, undergraduate and graduate students, researchers and practicing academics will be guided through the design, methods, and analysis of issues in Political Science and International Relations: Part One: Formulating Good Research Questions & Designing Good Research Projects Part Two: Methods of Theoretical Argumentation Part Three: Conceptualization & Measurement Part Four: Large-Scale Data Collection & Representation Methods Part Five: Quantitative-Empirical Methods Part Six: Qualitative & "Mixed" Methods

Computational Science – ICCS 2018

Yong Shi,Haohuan Fu,Yingjie Tian,Valeria V. Krzhizhanovskaya,Michael Harold Lees,Jack Dongarra,Peter M. A. Sloot
Computational Science ICCS 2018 Book PDF

Author : Yong Shi,Haohuan Fu,Yingjie Tian,Valeria V. Krzhizhanovskaya,Michael Harold Lees,Jack Dongarra,Peter M. A. Sloot
Publisher : Springer
Page : 730 pages
File Size : 51,8 Mb
Release : 2018-06-11
Category : Computers
ISBN : 9783319936987

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Computational Science – ICCS 2018 by Yong Shi,Haohuan Fu,Yingjie Tian,Valeria V. Krzhizhanovskaya,Michael Harold Lees,Jack Dongarra,Peter M. A. Sloot Pdf

The three-volume set LNCS 10860, 10861 + 10862 constitutes the proceedings of the 18th International Conference on Computational Science, ICCS 2018, held in Wuxi, China, in June 2018. The total of 155 full and 66 short papers presented in this book set was carefully reviewed and selected from 404 submissions. The papers were organized in topical sections named: Part I: ICCS Main Track Part II: Track of Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Track of Agent-Based Simulations, Adaptive Algorithms and Solvers; Track of Applications of Matrix Methods in Artificial Intelligence and Machine Learning; Track of Architecture, Languages, Compilation and Hardware Support for Emerging ManYcore Systems; Track of Biomedical and Bioinformatics Challenges for Computer Science; Track of Computational Finance and Business Intelligence; Track of Computational Optimization, Modelling and Simulation; Track of Data, Modeling, and Computation in IoT and Smart Systems; Track of Data-Driven Computational Sciences; Track of Mathematical-Methods-and-Algorithms for Extreme Scale; Track of Multiscale Modelling and Simulation Part III: Track of Simulations of Flow and Transport: Modeling, Algorithms and Computation; Track of Solving Problems with Uncertainties; Track of Teaching Computational Science; Poster Papers

Applied Survival Analysis Using R

Dirk F. Moore
Applied Survival Analysis Using R Book PDF

Author : Dirk F. Moore
Publisher : Springer
Page : 226 pages
File Size : 53,5 Mb
Release : 2016-05-11
Category : Medical
ISBN : 9783319312453

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Applied Survival Analysis Using R by Dirk F. Moore Pdf

Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis, as well as a basic knowledge of calculus and the R system, will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points, shedding light on the application of survival analysis in a way that is useful for graduate students, researchers, and practitioners in biostatistics.

Heart Rate Variability Analysis with the R package RHRV

Constantino Antonio García Martínez,Abraham Otero Quintana,Xosé A. Vila,María José Lado Touriño,Leandro Rodríguez-Liñares,Jesús María Rodríguez Presedo,Arturo José Méndez Penín
Heart Rate Variability Analysis with the R package RHRV Book PDF

Author : Constantino Antonio García Martínez,Abraham Otero Quintana,Xosé A. Vila,María José Lado Touriño,Leandro Rodríguez-Liñares,Jesús María Rodríguez Presedo,Arturo José Méndez Penín
Publisher : Springer
Page : 157 pages
File Size : 45,6 Mb
Release : 2017-09-18
Category : Medical
ISBN : 9783319653556

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Heart Rate Variability Analysis with the R package RHRV by Constantino Antonio García Martínez,Abraham Otero Quintana,Xosé A. Vila,María José Lado Touriño,Leandro Rodríguez-Liñares,Jesús María Rodríguez Presedo,Arturo José Méndez Penín Pdf

This book introduces readers to the basic concepts of Heart Rate Variability (HRV) and its most important analysis algorithms using a hands-on approach based on the open-source RHRV software. HRV refers to the variation over time of the intervals between consecutive heartbeats. Despite its apparent simplicity, HRV is one of the most important markers of the autonomic nervous system activity and it has been recognized as a useful predictor of several pathologies. The book discusses all the basic HRV topics, including the physiological contributions to HRV, clinical applications, HRV data acquisition, HRV data manipulation and HRV analysis using time-domain, frequency-domain, time-frequency, nonlinear and fractal techniques. Detailed examples based on real data sets are provided throughout the book to illustrate the algorithms and discuss the physiological implications of the results. Offering a comprehensive guide to analyzing beat information with RHRV, the book is intended for masters and Ph.D. students in various disciplines such as biomedical engineering, human and veterinary medicine, biology, and pharmacy, as well as researchers conducting heart rate variability analyses on both human and animal data.

Extending R

John M. Chambers
Extending R Book PDF

Author : John M. Chambers
Publisher : CRC Press
Page : 364 pages
File Size : 51,6 Mb
Release : 2017-12-19
Category : Mathematics
ISBN : 9781498775724

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Extending R by John M. Chambers Pdf

Up-to-Date Guidance from One of the Foremost Members of the R Core Team Written by John M. Chambers, the leading developer of the original S software, Extending R covers key concepts and techniques in R to support analysis and research projects. It presents the core ideas of R, provides programming guidance for projects of all scales, and introduces new, valuable techniques that extend R. The book first describes the fundamental characteristics and background of R, giving readers a foundation for the remainder of the text. It next discusses topics relevant to programming with R, including the apparatus that supports extensions. The book then extends R’s data structures through object-oriented programming, which is the key technique for coping with complexity. The book also incorporates a new structure for interfaces applicable to a variety of languages. A reflection of what R is today, this guide explains how to design and organize extensions to R by correctly using objects, functions, and interfaces. It enables current and future users to add their own contributions and packages to R. A 2017 Choice Outstanding Academic Title