R Statistical Application Development By Example Beginner S Guide
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R Statistical Application Development By Example Beginner S Guide
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Author : Prabhanjan Narayanachar Tattar
language : en
Publisher: Packt Pub Limited
Release Date : 2013
R Statistical Application Development By Example Beginner S Guide written by Prabhanjan Narayanachar Tattar and has been published by Packt Pub Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Computers categories.
Full of screenshots and examples, this Beginner's Guide by Example will teach you practically everything you need to know about R statistical application development from scratch. You will begin learning the first concepts of statistics in R which is vital in this fast paced era and it is also a bargain as you do not need to do a preliminary course on the subject.
Mastering Data Analysis With R
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Author : Gergely Daroczi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-09-30
Mastering Data Analysis With R written by Gergely Daroczi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-30 with Computers categories.
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.
R Object Oriented Programming
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Author : Kelly Black
language : en
Publisher: Packt Publishing Ltd
Release Date : 2014-10-27
R Object Oriented Programming written by Kelly Black and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-27 with Computers categories.
This book is designed for people with some experience in basic programming practices. It is also assumed that they have some basic experience using R and are familiar using the command line in an R environment. Our primary goal is to raise a beginner to a more advanced level to make him/her more comfortable creating programs and extending R to solve common problems.
Mastering Rstudio Develop Communicate And Collaborate With R
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Author : Julian Hillebrand
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-12-04
Mastering Rstudio Develop Communicate And Collaborate With R written by Julian Hillebrand and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-04 with Computers categories.
Harness the power of RStudio to create web applications, R packages, markdown reports and pretty data visualizations About This Book Discover the multi-functional use of RStudio to support your daily work with R code Learn to create stunning, meaningful, and interactive graphs and learn to embed them into easy communicable reports using multiple R packages Develop your own R packages and Shiny web apps to share your knowledge and collaborate with others. Who This Book Is For This book is aimed at R developers and analysts who wish to do R statistical development while taking advantage of RStudio's functionality to ease their development efforts. R programming experience is assumed as well as being comfortable with R's basic structures and a number of functions. What You Will Learn Discover the RStudio IDE and details about the user interface Communicate your insights with R Markdown in static and interactive ways Learn how to use different graphic systems to visualize your data Build interactive web applications with the Shiny framework to present and share your results Understand the process of package development and assemble your own R packages Easily collaborate with other people on your projects by using Git and GitHub Manage the R environment for your organization with RStudio and Shiny server Apply your obtained knowledge about RStudio and R development to create a real-world dashboard solution In Detail RStudio helps you to manage small to large projects by giving you a multi-functional integrated development environment, combined with the power and flexibility of the R programming language, which is becoming the bridge language of data science for developers and analyst worldwide. Mastering the use of RStudio will help you to solve real-world data problems. This book begins by guiding you through the installation of RStudio and explaining the user interface step by step. From there, the next logical step is to use this knowledge to improve your data analysis workflow. We will do this by building up our toolbox to create interactive reports and graphs or even web applications with Shiny. To collaborate with others, we will explore how to use Git and GitHub with RStudio and how to build your own packages to ensure top quality results. Finally, we put it all together in an interactive dashboard written with R. Style and approach An easy-to-follow guide full of hands-on examples to master RStudio. Beginning from explaining the basics, each topic is explained with a lot of details for every feature.
A Course In Statistics With R
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Author : Prabhanjan N. Tattar
language : en
Publisher: John Wiley & Sons
Release Date : 2016-03-15
A Course In Statistics With R written by Prabhanjan N. Tattar and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-15 with Computers categories.
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
Mastering Scientific Computing With R
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Author : Paul Gerrard
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-01-31
Mastering Scientific Computing With R written by Paul Gerrard and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-31 with Computers categories.
If you want to learn how to quantitatively answer scientific questions for practical purposes using the powerful R language and the open source R tool ecosystem, this book is ideal for you. It is ideally suited for scientists who understand scientific concepts, know a little R, and want to be able to start applying R to be able to answer empirical scientific questions. Some R exposure is helpful, but not compulsory.
Learning Probabilistic Graphical Models In R
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Author : David Bellot
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-04-29
Learning Probabilistic Graphical Models In R written by David Bellot and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-29 with Computers categories.
Familiarize yourself with probabilistic graphical models through real-world problems and illustrative code examples in R About This Book Predict and use a probabilistic graphical models (PGM) as an expert system Comprehend how your computer can learn Bayesian modeling to solve real-world problems Know how to prepare data and feed the models by using the appropriate algorithms from the appropriate R package Who This Book Is For This book is for anyone who has to deal with lots of data and draw conclusions from it, especially when the data is noisy or uncertain. Data scientists, machine learning enthusiasts, engineers, and those who curious about the latest advances in machine learning will find PGM interesting. What You Will Learn Understand the concepts of PGM and which type of PGM to use for which problem Tune the model's parameters and explore new models automatically Understand the basic principles of Bayesian models, from simple to advanced Transform the old linear regression model into a powerful probabilistic model Use standard industry models but with the power of PGM Understand the advanced models used throughout today's industry See how to compute posterior distribution with exact and approximate inference algorithms In Detail Probabilistic graphical models (PGM, also known as graphical models) are a marriage between probability theory and graph theory. Generally, PGMs use a graph-based representation. Two branches of graphical representations of distributions are commonly used, namely Bayesian networks and Markov networks. R has many packages to implement graphical models. We'll start by showing you how to transform a classical statistical model into a modern PGM and then look at how to do exact inference in graphical models. Proceeding, we'll introduce you to many modern R packages that will help you to perform inference on the models. We will then run a Bayesian linear regression and you'll see the advantage of going probabilistic when you want to do prediction. Next, you'll master using R packages and implementing its techniques. Finally, you'll be presented with machine learning applications that have a direct impact in many fields. Here, we'll cover clustering and the discovery of hidden information in big data, as well as two important methods, PCA and ICA, to reduce the size of big problems. Style and approach This book gives you a detailed and step-by-step explanation of each mathematical concept, which will help you build and analyze your own machine learning models and apply them to real-world problems. The mathematics is kept simple and each formula is explained thoroughly.
Machine Learning With R
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Author : Brett Lantz
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-07-31
Machine Learning With R written by Brett Lantz and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-31 with Computers categories.
Updated and upgraded to the latest libraries and most modern thinking, Machine Learning with R, Second Edition provides you with a rigorous introduction to this essential skill of professional data science. Without shying away from technical theory, it is written to provide focused and practical knowledge to get you building algorithms and crunching your data, with minimal previous experience. With this book, you'll discover all the analytical tools you need to gain insights from complex data and learn how to choose the correct algorithm for your specific needs. Through full engagement with the sort of real-world problems data-wranglers face, you'll learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, market analysis, and clustering.
R Graph Essentials
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Author : David Alexander Lillis
language : en
Publisher: Packt Publishing Ltd
Release Date : 2014-09-22
R Graph Essentials written by David Alexander Lillis and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-22 with Computers categories.
This book is targeted at R programmers who want to learn the graphing capabilities of R. This book will presume that you have working knowledge of R.
R
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Author : Posts & Telecom Press
language : zh-CN
Publisher: Packt Publishing Ltd
Release Date : 2024-05-23
R written by Posts & Telecom Press and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-23 with Computers categories.
概率图,热门的机器学习研究方向!借助流行的R语言,掌握贝叶斯网络和马尔科夫网络! Key Features 市场上首本基于R语言的概率图图书 结合概率论与图论的知识,提供一种简单的可视化概率模型的方法 理解计算机如何通过贝叶斯模型和马尔科夫模型来解决现实世界的问题 Book Description概率图模型结合了概率论与图论的知识,提供了一种简单的可视化概率模型的方法,在人工智能、机器学习和计算机视觉等领域有着广阔的应用前景。 通过学习本书,读者可以理解概率图模型的概念,为特定的问题选取特定的概率图模型;调整模型参数,自动发现新的模型;从简单到复杂,逐步理解贝叶斯模型的基本原理;把标准的线性回归模型转换为强大的概率图模型;理解当今产业界广泛使用的高级模型;使用精确推断和近似推断算法,计算后验概率分布。 本书适合各行业的数据科学家、机器学习爱好者和工程师等人群阅读、使用。What you will learn 理解概率图模型的概念,为特定的问题选取特定的概率图模型。 调整模型参数,自动发现新的模型。 从简单到复杂,逐步理解贝叶斯模型的基本原理。 把标准的线性回归模型转换为强大的概率图模型。 理解当今产业界广泛使用的高级模型。 使用精确推断和近似推断算法,计算后验概率分布。 Who this book is for 无论你是R语言的新手,还是有经验的专业人士,都可以从本书学到概率图模型、贝叶斯网络、马尔科夫网络的分析方法。