The Book of R  Download eBook Read PdfePubKindle
Download full pdf book The Book of R by Tilman M. Davies available in full 832 pages, and make sure to check out other latest books Computers related to The Book of R below.The Book of R
By Tilman M. Davies ISBN Code: : 1593277792
 Publisher : No Starch Press
 Pages : 832
 Category : Computers
 Reads : 679
 Book Compatibility : Pdf, ePub, Mobi, Kindle
 Pdf : thebookofr.pdf
Book Excerpt :
The Book of R is a comprehensive, beginnerfriendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of handson exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publicationquality graphics of your results Combining detailed explanations with realworld examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.
Recommended Books For Reading

The Big RBook
A Book written by Philippe J. S. De Brouwer, published by John Wiley & Sons 20200929  928 pages  part of Mathematics books.
Get eBook 
R for Data Science
A Book written by Hadley Wickham,Garrett Grolemund, published by "O'Reilly Media, Inc." 20161212  520 pages  part of Computers books.
Get eBook 
The Art of R Programming
A Book written by Norman Matloff, published by No Starch Press 20111011  400 pages  part of Computers books.
Get eBook 
Reproducible Finance with R
A Book written by Jonathan K. Regenstein, Jr., published by CRC Press 20180924  230 pages  part of Mathematics books.
Get eBook 
Statistical Analysis with R For Dummies
A Book written by Joseph Schmuller, published by John Wiley & Sons 20170303  456 pages  part of Computers books.
Get eBook 
The R Software
A Book written by Pierre Lafaye de Micheaux,Rémy Drouilhet,Benoit Liquet, published by Springer Science & Business 20140513  628 pages  part of Computers books.
Get eBook 
Introductory Statistics with R
A Book written by Peter Dalgaard, published by Springer Science & Business Media 20080627  364 pages  part of Mathematics books.
Get eBook
Read Also This Books
The R Book
By Michael J. Crawley File : Pdf, ePub, Mobi, Kindle
 Publisher : John Wiley & Sons
 Book Code : 1118448960
 Total of Pages : 1080
 Category : Mathematics
 Members : 466
 Pdf File: therbook.pdf
Book Short Summary:
Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and MetaAnalysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. Praise for the first edition: ‘...if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008) ‘The Highlevel software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book...’ (Professional Pensions, July 2007)
Learning RStudio for R Statistical Computing
By Mark P. J. Van der Loo File : Pdf, ePub, Mobi, Kindle
 Publisher : Packt Publishing Ltd
 Book Code : 1782160612
 Total of Pages : 126
 Category : Computers
 Members : 564
 Pdf File: learningrstudioforrstatisticalcomputing.pdf
Book Short Summary:
A practical tutorial covering how to leverage RStudio functionality to effectively perform R Development, analysis, and reporting with RStudio. The book is aimed at R developers and analysts who wish to do R statistical development while taking advantage of RStudio functionality to ease their development efforts. Familiarity with R is assumed. Those who want to get started with R development using RStudio will also find the book useful. Even if you already use R but want to create reproducible statistical analysis projects or extend R with selfwritten packages, this book shows how to quickly achieve this using RStudio.
Advanced R
By Hadley Wickham File : Pdf, ePub, Mobi, Kindle
 Publisher : CRC Press
 Book Code : 1498759807
 Total of Pages : 476
 Category : Mathematics
 Members : 624
 Pdf File: advancedr.pdf
Book Short Summary:
An Essential Reference for Intermediate and Advanced R Programmers Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of experience programming in R, the author illustrates the elegance, beauty, and flexibility at the heart of R. The book develops the necessary skills to produce quality code that can be used in a variety of circumstances. You will learn: The fundamentals of R, including standard data types and functions Functional programming as a useful framework for solving wide classes of problems The positives and negatives of metaprogramming How to write fast, memoryefficient code This book not only helps current R users become R programmers but also shows existing programmers what’s special about R. Intermediate R programmers can dive deeper into R and learn new strategies for solving diverse problems while programmers from other languages can learn the details of R and understand why R works the way it does.
Beginning R
By Mark Gardener File : Pdf, ePub, Mobi, Kindle
 Publisher : John Wiley & Sons
 Book Code : 1118239377
 Total of Pages : 504
 Category : Computers
 Members : 736
 Pdf File: beginningr.pdf
Book Short Summary:
Conquer the complexities of this open source statistical language R is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a userfriendly context. Both students and workers in fields that require extensive statistical analysis will find this book helpful as they learn to use R for simple summary statistics, hypothesis testing, creating graphs, regression, and much more. It covers formula notation, complex statistics, manipulating data and extracting components, and rudimentary programming. R, the open source statistical language increasingly used to handle statistics and produces publicationquality graphs, is notoriously complex This book makes R easier to understand through the use of simple statistical examples, teaching the necessary elements in the context in which R is actually used Covers getting started with R and using it for simple summary statistics, hypothesis testing, and graphs Shows how to use R for formula notation, complex statistics, manipulating data, extracting components, and regression Provides beginning programming instruction for those who want to write their own scripts Beginning R offers anyone who needs to perform statistical analysis the information necessary to use R with confidence.
Extending R
By John M. Chambers File : Pdf, ePub, Mobi, Kindle
 Publisher : CRC Press
 Book Code : 1498775721
 Total of Pages : 364
 Category : Mathematics
 Members : 597
 Pdf File: extendingr.pdf
Book Short Summary:
UptoDate 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 objectoriented 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
R for Everyone
By Jared P. Lander File : Pdf, ePub, Mobi, Kindle
 Publisher : AddisonWesley Professional
 Book Code : 0134546997
 Total of Pages : 560
 Category : Computers
 Members : 276
 Pdf File: rforeveryone.pdf
Book Short Summary:
Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for nonstatisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone, Second Edition, is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s selfcontained chapters start with the absolute basics, offering extensive handson practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this you’ll make your code reproducible with LaTeX, RMarkdown, and Shiny. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. Coverage includes Explore R, RStudio, and R packages Use R for math: variable types, vectors, calling functions, and more Exploit data structures, including data.frames, matrices, and lists Read many different types of data Create attractive, intuitive statistical graphics Write userdefined functions Control program flow with if, ifelse, and complex checks Improve program efficiency with group manipulations Combine and reshape multiple datasets Manipulate strings using R’s facilities and regular expressions Create normal, binomial, and Poisson probability distributions Build linear, generalized linear, and nonlinear models Program basic statistics: mean, standard deviation, and ttests Train machine learning models Assess the quality of models and variable selection Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods Analyze univariate and multivariate time series data Group data via Kmeans and hierarchical clustering Prepare reports, slideshows, and web pages with knitr Display interactive data with RMarkdown and htmlwidgets Implement dashboards with Shiny Build reusable R packages with devtools and Rcpp Register your product at informit.com/register for convenient access to downloads, updates, and corrections as they become available.
Geocomputation with R
By Robin Lovelace,Jakub Nowosad,Jannes Muenchow File : Pdf, ePub, Mobi, Kindle
 Publisher : CRC Press
 Book Code : 1351396900
 Total of Pages : 335
 Category : Mathematics
 Members : 843
 Pdf File: geocomputationwithr.pdf
Book Short Summary:
Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domainspecific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you uptospeed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to realworld problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do crossvalidation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle realworld problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/. Dr. Robin Lovelace is a University Academic Fellow at the University of Leeds, where he has taught R for geographic research over many years, with a focus on transport systems. Dr. Jakub Nowosad is an Assistant Professor in the Department of Geoinformation at the Adam Mickiewicz University in Poznan, where his focus is on the analysis of large datasets to understand environmental processes. Dr. Jannes Muenchow is a Postdoctoral Researcher in the GIScience Department at the University of Jena, where he develops and teaches a range of geographic methods, with a focus on ecological modeling, statistical geocomputing, and predictive mapping. All three are active developers and work on a number of R packages, including stplanr, sabre, and RQGIS.
An Introduction to Statistical Learning
By Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani File : Pdf, ePub, Mobi, Kindle
 Publisher : Springer Science & Business Media
 Book Code : 1461471389
 Total of Pages : 426
 Category : Mathematics
 Members : 662
 Pdf File: anintroductiontostatisticallearning.pdf
Book Short Summary:
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, treebased methods, support vector machines, clustering, and more. Color graphics and realworld examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors cowrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and nonstatisticians alike who wish to use cuttingedge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
Learning R
By Richard Cotton File : Pdf, ePub, Mobi, Kindle
 Publisher : "O'Reilly Media, Inc."
 Book Code : 1449357180
 Total of Pages : 400
 Category : Computers
 Members : 817
 Pdf File: learningr.pdf
Book Short Summary:
Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this handson guide, you’ll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts. The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you’ve learned, and concludes with exercises, most of which involve writing R code. Write a simple R program, and discover what the language can do Use data types such as vectors, arrays, lists, data frames, and strings Execute code conditionally or repeatedly with branches and loops Apply R addon packages, and package your own work for others Learn how to clean data you import from a variety of sources Understand data through visualization and summary statistics Use statistical models to pass quantitative judgments about data and make predictions Learn what to do when things go wrong while writing data analysis code
R Cookbook
By JD Long,Paul Teetor File : Pdf, ePub, Mobi, Kindle
 Publisher : "O'Reilly Media, Inc."
 Book Code : 1492040630
 Total of Pages : 600
 Category : Computers
 Members : 769
 Pdf File: rcookbook.pdf
Book Short Summary:
Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These taskoriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an intermediate user, this book will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform basic functions Simplify data input and output Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data
Data Visualization
By Kieran Healy File : Pdf, ePub, Mobi, Kindle
 Publisher : Princeton University Press
 Book Code : 0691185069
 Total of Pages : 296
 Category : Social Science
 Members : 505
 Pdf File: datavisualization.pdf
Book Short Summary:
An accessible primer on how to create effective graphics from data This book provides students and researchers a handson introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make highquality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data Visualization builds the reader’s expertise in ggplot2, a versatile visualization library for the R programming language. Through a series of worked examples, this accessible primer then demonstrates how to create plots piece by piece, beginning with summaries of single variables and moving on to more complex graphics. Topics include plotting continuous and categorical variables; layering information on graphics; producing effective “small multiple” plots; grouping, summarizing, and transforming data for plotting; creating maps; working with the output of statistical models; and refining plots to make them more comprehensible. Effective graphics are essential to communicating ideas and a great way to better understand data. This book provides the practical skills students and practitioners need to visualize quantitative data and get the most out of their research findings. Provides handson instruction using R and ggplot2 Shows how the “tidyverse” of data analysis tools makes working with R easier and more consistent Includes a library of data sets, code, and functions
The R Student Companion
By Brian Dennis File : Pdf, ePub, Mobi, Kindle
 Publisher : CRC Press
 Book Code : 1439875413
 Total of Pages : 360
 Category : Mathematics
 Members : 686
 Pdf File: therstudentcompanion.pdf
Book Short Summary:
R is the amazing, free, openaccess software package for scientific graphs and calculations used by scientists worldwide. The R Student Companion is a studentoriented manual describing how to use R in high school and college science and mathematics courses. Written for beginners in scientific computation, the book assumes the reader has just some
R by Example
By Jim Albert,Maria Rizzo File : Pdf, ePub, Mobi, Kindle
 Publisher : Springer Science & Business Media
 Book Code : 1461413656
 Total of Pages : 359
 Category : Mathematics
 Members : 512
 Pdf File: r.pdf
Book Short Summary:
R by Example is an examplebased introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data. The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, this book is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculusbased courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data and this book is intended to be a useful resource for learning how to implement these procedures in R.
Using the R Commander
By John Fox File : Pdf, ePub, Mobi, Kindle
 Publisher : CRC Press
 Book Code : 1498741916
 Total of Pages : 233
 Category : Mathematics
 Members : 325
 Pdf File: usingthercommander.pdf
Book Short Summary:
This book provides a general introduction to the R Commander graphical user interface (GUI) to R for readers who are unfamiliar with R. It is suitable for use as a supplementary text in a basic or intermediatelevel statistics course. It is not intended to replace a basic or other statistics text but rather to complement it, although it does promote sound statistical practice in the examples. The book should also be useful to individual casual or occasional users of R for whom the standard commandline interface is an obstacle.
Introductory R: A Beginner's Guide to Data Visualisation, Statistical Analysis and Programming in R
By Robert Knell File : Pdf, ePub, Mobi, Kindle
 Publisher : Robert Knell
 Book Code : 0957597118
 Total of Pages : 531
 Category :
 Members : 768
 Pdf File: introductoryr.pdf
Book Short Summary:
R is now the most widely used statistical software in academic science and it is rapidly expanding into other fields such as finance. R is almost limitlessly flexible and powerful, hence its appeal, but can be very difficult for the novice user. There are no easy pulldown menus, error messages are often cryptic and simple tasks like importing your data or exporting a graph can be difficult and frustrating. Introductory R is written for the novice user who knows a little about statistics but who hasn't yet got to grips with the ways of R. This new edition is completely revised and greatly expanded with new chapters on the basics of descriptive statistics and statistical testing, considerably more information on statistics and six new chapters on programming in R. Topics covered include: A walkthrough of the basics of R's command line interface Data structures including vectors, matrices and data frames R functions and how to use them Expanding your analysis and plotting capacities with addin R packages A set of simple rules to follow to make sure you import your data properly An introduction to the script editor and advice on workflow A detailed introduction to drawing publicationstandard graphs in R How to understand the help files and how to deal with some of the most common errors that you might encounter. Basic descriptive statistics The theory behind statistical testing and how to interpret the output of statistical tests Thorough coverage of the basics of data analysis in R with chapters on using chisquared tests, ttests, correlation analysis, regression, ANOVA and general linear models What the assumptions behind the analyses mean and how to test them using diagnostic plots Explanations of the summary tables produced for statistical analyses such as regression and ANOVA Writing your own functions in R Using table operations to manipulate matrices and data frames Using conditional statements and loops in R programmes. Writing longer R programmes. The techniques of statistical analysis in R are illustrated by a series of chapters where experimental and survey data are analysed. There is a strong emphasis on using real data from real scientific research, with all the problems and uncertainty that implies, rather than wellbehaved madeup data that give ideal and easy to analyse results.
A Tiny Handbook of R
By Mike Allerhand File : Pdf, ePub, Mobi, Kindle
 Publisher : Springer Science & Business Media
 Book Code : 3642179800
 Total of Pages : 83
 Category : Computers
 Members : 212
 Pdf File: atinyhandbookofr.pdf
Book Short Summary:
This Brief provides a roadmap for the R language and programming environment with signposts to further resources and documentation.
R and MATLAB
By David E. Hiebeler File : Pdf, ePub, Mobi, Kindle
 Publisher : CRC Press
 Book Code : 1466568399
 Total of Pages : 233
 Category : Mathematics
 Members : 945
 Pdf File: randmatlab.pdf
Book Short Summary:
The First Book to Explain How a User of R or MATLAB Can Benefit from the Other In today’s increasingly interdisciplinary world, R and MATLAB® users from different backgrounds must often work together and share code. R and MATLAB® is designed for users who already know R or MATLAB and now need to learn the other platform. The book makes the transition from one platform to the other as quick and painless as possible. Enables R and MATLAB Users to Easily Collaborate and Share Code The author covers essential tasks, such as working with matrices and vectors, writing functions and other programming concepts, graphics, numerical computing, and file input/output. He highlights important differences between the two platforms and explores common mistakes that are easy to make when transitioning from one platform to the other.
R for Health Data Science
By Ewen Harrison,Riinu Pius File : Pdf, ePub, Mobi, Kindle
 Publisher : CRC Press
 Book Code : 1000226107
 Total of Pages : 364
 Category : Medical
 Members : 497
 Pdf File: rforhealthdatascience.pdf
Book Short Summary:
In this age of information, the manipulation, analysis, and interpretation of data have become a fundamental part of professional life; nowhere more so than in the delivery of healthcare. From the understanding of disease and the development of new treatments, to the diagnosis and management of individual patients, the use of data and technology is now an integral part of the business of healthcare. Those working in healthcare interact daily with data, often without realising it. The conversion of this avalanche of information to useful knowledge is essential for highquality patient care. R for Health Data Science includes everything a healthcare professional needs to go from R novice to R guru. By the end of this book, you will be taking a sophisticated approach to health data science with beautiful visualisations, elegant tables, and nuanced analyses. Features Provides an introduction to the fundamentals of R for healthcare professionals Highlights the most popular statistical approaches to health data science Written to be as accessible as possible with minimal mathematics Emphasises the importance of truly understanding the underlying data through the use of plots Includes numerous examples that can be adapted for your own data Helps you create publishable documents and collaborate across teams With this book, you are in safe hands – Prof. Harrison is a clinician and Dr. Pius is a data scientist, bringing 25 years’ combined experience of using R at the coal face. This content has been taught to hundreds of individuals from a variety of backgrounds, from rank beginners to experts moving to R from other platforms.
HandsOn Machine Learning with R
By Brad Boehmke,Brandon M. Greenwell File : Pdf, ePub, Mobi, Kindle
 Publisher : CRC Press
 Book Code : 1000730190
 Total of Pages : 456
 Category : Business & Economics
 Members : 420
 Pdf File: handsonmachinelearningwithr.pdf
Book Short Summary:
Handson Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a handson approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a handson approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering, resampling, deep learning and more. · Uses a handson approach and real world data.
Proofs from THE BOOK
By Martin Aigner,Günter M. Ziegler File : Pdf, ePub, Mobi, Kindle
 Publisher : Springer Science & Business Media
 Book Code : 3662223430
 Total of Pages : 199
 Category : Mathematics
 Members : 897
 Pdf File: proofsfromthebook.pdf
Book Short Summary:
According to the great mathematician Paul Erdös, God maintains perfect mathematical proofs in The Book. This book presents the authors candidates for such "perfect proofs," those which contain brilliant ideas, clever connections, and wonderful observations, bringing new insight and surprising perspectives to problems from number theory, geometry, analysis, combinatorics, and graph theory. As a result, this book will be fun reading for anyone with an interest in mathematics.
Doing MetaAnalysis with R
By Mathias Harrer,Pim Cuijpers,Toshi A. Furukawa,David D. Ebert File : Pdf, ePub, Mobi, Kindle
 Publisher : CRC Press
 Book Code : 1000435636
 Total of Pages : 500
 Category : Mathematics
 Members : 295
 Pdf File: doingmetaanalysiswithr.pdf
Book Short Summary:
Doing MetaAnalysis with R: A HandsOn Guide serves as an accessible introduction on how metaanalyses can be conducted in R. Essential steps for metaanalysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, metaregression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network metaanalysis, multithreelevel metaanalyses, Bayesian metaanalysis approaches and SEM metaanalysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a nonexpert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of metaanalysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes stepbystep guidance through the coding required to perform metaanalyses, and a companion R package for the book
A Course in Statistics with R
By Prabhanjan N. Tattar,Suresh Ramaiah,B. G. Manjunath File : Pdf, ePub, Mobi, Kindle
 Publisher : John Wiley & Sons
 Book Code : 1119152755
 Total of Pages : 696
 Category : Computers
 Members : 305
 Pdf File: acourseinstatisticswithr.pdf
Book Short Summary:
Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject. With this dual goal in mind, the book begins with R basics and quickly covers visualization and exploratory analysis. Probability and statistical inference, inclusive of classical, nonparametric, and Bayesian schools, is developed with definitions, motivations, mathematical expression and R programs in a way which will help the reader to understand the mathematical development as well as R implementation. Linear regression models, experimental designs, multivariate analysis, and categorical data analysis are treated in a way which makes effective use of visualization techniques and the related statistical techniques underlying them through practical applications, and hence helps the reader to achieve a clear understanding of the associated statistical models. Key features: Integrates R basics with statistical concepts Provides graphical presentations inclusive of mathematical expressions Aids understanding of limit theorems of probability with and without the simulation approach Presents detailed algorithmic development of statistical models from scratch Includes practical applications with over 50 data sets
The Essential R Reference
By Mark Gardener File : Pdf, ePub, Mobi, Kindle
 Publisher : John Wiley & Sons
 Book Code : 1118391381
 Total of Pages : 576
 Category : Computers
 Members : 284
 Pdf File: theessentialrreference.pdf
Book Short Summary:
An essential library of basic commands you can copy and pasteinto R The powerful and opensource statistical programming language Ris rapidly growing in popularity, but it requires that you type incommands at the keyboard rather than use a mouse, so you have tolearn the language of R. But there is a shortcut, and that's wherethis unique book comes in. A companion book to Visualize This:The FlowingData Guide to Design, Visualization, and Statistics,this practical reference is a library of basic R commands that youcan copy and paste into R to perform many types of statisticalanalyses. Whether you're in technology, science, medicine, business, orengineering, you can quickly turn to your topic in this handy bookand find the commands you need. Comprehensive command reference for the R programming languageand a companion book to Visualize This: The FlowingData Guide toDesign, Visualization, and Statistics Combines elements of a dictionary, glossary, and thesaurus forthe R language Provides easy accessibility to the commands you need, by topic,which you can cut and paste into R as needed Covers getting, saving, examining, and manipulating data;statistical test and math; and all the things you can do withgraphs Also includes a collection of utilities that you'll finduseful Simplify the complex statistical R programming language withThe Essential R Reference. .
Basic Statistics with R
By Stephen C. Loftus File : Pdf, ePub, Mobi, Kindle
 Publisher : Academic Press
 Book Code : 0128209267
 Total of Pages : 304
 Category : Mathematics
 Members : 439
 Pdf File: basicstatisticswithr.pdf
Book Short Summary:
Basic Statistics with R: Reaching Decisions with Data provides an understanding of the processes at work in using data for results. Sections cover data collection and discuss exploratory analyses, including visual graphs, numerical summaries, and relationships between variables  basic probability, and statistical inference  including hypothesis testing and confidence intervals. All topics are taught using realdata drawn from various fields, including economics, biology, political science and sports. Using this wide variety of motivating examples allows students to directly connect and make statistics essential to their field of interest, rather than seeing it as a separate and ancillary knowledge area. In addition to introducing students to statistical topics using real data, the book provides a gentle introduction to coding, having the students use the statistical language and software R. Students learn to load data, calculate summary statistics, create graphs and do statistical inference using R with either Windows or Macintosh machines. Features realdata to give students an engaging practice to connect with their areas of interest Evolves from basic problems that can be worked by hand to the elementary use of opensource R software Offers a direct, clear approach highlighted by useful visuals and examples
R Packages
By Hadley Wickham File : Pdf, ePub, Mobi, Kindle
 Publisher : "O'Reilly Media, Inc."
 Book Code : 1491910542
 Total of Pages : 202
 Category : Computers
 Members : 206
 Pdf File: rpackages.pdf
Book Short Summary:
Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham’s package development philosophy. In the process, you’ll work with devtools, roxygen, and testthat, a set of R packages that automate common development tasks. Devtools encapsulates best practices that Hadley has learned from years of working with this programming language. Ideal for developers, data scientists, and programmers with various backgrounds, this book starts you with the basics and shows you how to improve your package writing over time. You’ll learn to focus on what you want your package to do, rather than think about package structure. Learn about the most useful components of an R package, including vignettes and unit tests Automate anything you can, taking advantage of the years of development experience embodied in devtools Get tips on good style, such as organizing functions into files Streamline your development process with devtools Learn the best way to submit your package to the Comprehensive R Archive Network (CRAN) Learn from a wellrespected member of the R community who created 30 R packages, including ggplot2, dplyr, and tidyr
Efficient R Programming
By Colin Gillespie,Robin Lovelace File : Pdf, ePub, Mobi, Kindle
 Publisher : "O'Reilly Media, Inc."
 Book Code : 1491950730
 Total of Pages : 222
 Category : Computers
 Members : 438
 Pdf File: efficientrprogramming.pdf
Book Short Summary:
There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively—until now. This handson book teaches novices and experienced R users how to write efficient R code. Drawing on years of experience teaching R courses, authors Colin Gillespie and Robin Lovelace provide practical advice on a range of topics—from optimizing the setup of RStudio to leveraging C++—that make this book a useful addition to any R user’s bookshelf. Academics, business users, and programmers from a wide range of backgrounds stand to benefit from the guidance in Efficient R Programming. Get advice for setting up an R programming environment Explore general programming concepts and R coding techniques Understand the ingredients of an efficient R workflow Learn how to efficiently read and write data in R Dive into data carpentry—the vital skill for cleaning raw data Optimize your code with profiling, standard tricks, and other methods Determine your hardware capabilities for handling R computation Maximize the benefits of collaborative R programming Accelerate your transition from R hacker to R programmer
HandsOn Programming with R
By Garrett Grolemund File : Pdf, ePub, Mobi, Kindle
 Publisher : "O'Reilly Media, Inc."
 Book Code : 1449359108
 Total of Pages : 250
 Category : Computers
 Members : 728
 Pdf File: handsonprogrammingwithr.pdf
Book Short Summary:
Learn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems. With this book, you’ll learn how to load data, assemble and disassemble data objects, navigate R’s environment system, write your own functions, and use all of R’s programming tools. RStudio Master Instructor Garrett Grolemund not only teaches you how to program, but also shows you how to get more from R than just visualizing and modeling data. You’ll gain valuable programming skills and support your work as a data scientist at the same time. Work handson with three practical data analysis projects based on casino games Store, retrieve, and change data values in your computer’s memory Write programs and simulations that outperform those written by typical R users Use R programming tools such as if else statements, for loops, and S3 classes Learn how to write lightningfast vectorized R code Take advantage of R’s package system and debugging tools Practice and apply R programming concepts as you learn them
The Rust Programming Language (Covers Rust 2018)
By Steve Klabnik,Carol Nichols File : Pdf, ePub, Mobi, Kindle
 Publisher : No Starch Press
 Book Code : 1718500459
 Total of Pages : 560
 Category : Computers
 Members : 245
 Pdf File: therustprogramminglanguage.pdf
Book Short Summary:
The official book on the Rust programming language, written by the Rust development team at the Mozilla Foundation, fully updated for Rust 2018. The Rust Programming Language is the official book on Rust: an open source systems programming language that helps you write faster, more reliable software. Rust offers control over lowlevel details (such as memory usage) in combination with highlevel ergonomics, eliminating the hassle traditionally associated with lowlevel languages. The authors of The Rust Programming Language, members of the Rust Core Team, share their knowledge and experience to show you how to take full advantage of Rust's featuresfrom installation to creating robust and scalable programs. You'll begin with basics like creating functions, choosing data types, and binding variables and then move on to more advanced concepts, such as: • Ownership and borrowing, lifetimes, and traits • Using Rust's memory safety guarantees to build fast, safe programs • Testing, error handling, and effective refactoring • Generics, smart pointers, multithreading, trait objects, and advanced pattern matching • Using Cargo, Rust's builtin package manager, to build, test, and document your code and manage dependencies • How best to use Rust's advanced compiler with compilerled programming techniques You'll find plenty of code examples throughout the book, as well as three chapters dedicated to building complete projects to test your learning: a number guessing game, a Rust implementation of a command line tool, and a multithreaded server. New to this edition: An extended section on Rust macros, an expanded chapter on modules, and appendixes on Rust development tools and editions.
Text Mining with R
By Julia Silge,David Robinson File : Pdf, ePub, Mobi, Kindle
 Publisher : "O'Reilly Media, Inc."
 Book Code : 1491981601
 Total of Pages : 194
 Category : Computers
 Members : 168
 Pdf File: textminingwithr.pdf
Book Short Summary:
Much of the data available today is unstructured and textheavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you’ll explore textmining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You’ll learn how tidytext and other tidy tools in R can make text analysis easier and more effective. The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You’ll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media. Learn how to apply the tidy text format to NLP Use sentiment analysis to mine the emotional content of text Identify a document’s most important terms with frequency measurements Explore relationships and connections between words with the ggraph and widyr packages Convert back and forth between R’s tidy and nontidy text formats Use topic modeling to classify document collections into natural groups Examine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages
Using R for Introductory Statistics
By John Verzani File : Pdf, ePub, Mobi, Kindle
 Publisher : CRC Press
 Book Code : 1466590742
 Total of Pages : 518
 Category : Mathematics
 Members : 656
 Pdf File: usingrforintroductorystatistics.pdf
Book Short Summary:
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, taskoriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computerintensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of usercontributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computerintensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.
Learning R Programming
By Kun Ren File : Pdf, ePub, Mobi, Kindle
 Publisher : Packt Publishing Ltd
 Book Code : 1785880624
 Total of Pages : 582
 Category : Computers
 Members : 240
 Pdf File: learningrprogramming.pdf
Book Short Summary:
Become an efficient data scientist with R About This Book Explore the R language from basic types and data structures to advanced topics Learn how to tackle programming problems and explore both functional and objectoriented programming techniques Learn how to address the core problems of programming in R and leverage the most popular packages for common tasks Who This Book Is For This is the perfect tutorial for anyone who is new to statistical programming and modeling. Anyone with basic programming and data processing skills can pick this book up to systematically learn the R programming language and crucial techniques. What You Will Learn Explore the basic functions in R and familiarize yourself with common data structures Work with data in R using basic functions of statistics, data mining, data visualization, root solving, and optimization Get acquainted with R's evaluation model with environments and metaprogramming techniques with symbol, call, formula, and expression Get to grips with objectoriented programming in R: including the S3, S4, RC, and R6 systems Access relational databases such as SQLite and nonrelational databases such as MongoDB and Redis Get to know high performance computing techniques such as parallel computing and Rcpp Use web scraping techniques to extract information Create RMarkdown, an interactive app with Shiny, DiagramR, interactive charts, ggvis, and more In Detail R is a highlevel functional language and one of the mustknow tools for data science and statistics. Powerful but complex, R can be challenging for beginners and those unfamiliar with its unique behaviors. Learning R Programming is the solution  an easy and practical way to learn R and develop a broad and consistent understanding of the language. Through handson examples you'll discover powerful R tools, and R best practices that will give you a deeper understanding of working with data. You'll get to grips with R's data structures and data processing techniques, as well as the most popular R packages to boost your productivity from the offset. Start with the basics of R, then dive deep into the programming techniques and paradigms to make your R code excel. Advance quickly to a deeper understanding of R's behavior as you learn common tasks including data analysis, databases, web scraping, high performance computing, and writing documents. By the end of the book, you'll be a confident R programmer adept at solving problems with the right techniques. Style and approach Developed to make learning easy and intuitive, this book comes packed with a wide variety of statistical and graphical techniques and a wealth of practical information for anyone looking to get started with this exciting and powerful language.