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Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization by Matt Wiley, Joshua F. Wiley

• Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization
• Matt Wiley, Joshua F. Wiley
• Page: 638
• Format: pdf, ePub, mobi, fb2
• ISBN: 9781484228715
• Publisher: Apress

Download Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization

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Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples using R to achieve results, and concludes with a case study. Written by Matt and Joshua F. Wiley, Advanced R Statistical Programming and Data Models shows you how to conduct data analysis using the popular R language. You’ll delve into the preconditions or hypothesis for various statistical tests and techniques and work through concrete examples using R for a variety of these next-level analytics. This is a must-have guide and reference on using and programming with the R language. What You’ll Learn Conduct advanced analyses in R including: generalized linear models, generalized additive models, mixed effects models, machine learning, and parallel processing Carry out regression modeling using R data visualization, linear and advanced regression, additive models, survival / time to event analysis Handle machine learning using R including parallel processing, dimension reduction, and feature selection and classification Address missing data using multiple imputation in R Work on factor analysis, generalized linear mixed models, and modeling intraindividual variability Who This Book Is For Working professionals, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to use R to perform more advanced analytics. Particularly, researchers and data analysts in the social sciences may benefit from these techniques. Additionally, analysts who need parallel processing to speed up analytics are given proven code to reduce time to result(s).

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R is an open-source statistical programming language. Includes FAQs, learning modules, sample code and data analysis examples. Online courses covering a variety of topics (e.g. machine learning, visuals, etc.) in R. Linear Regression Using R: An Introduction to Data Modeling Advanced Books. R Programming Courses in Singapore - R Statistics, R Machine
R Programming Courses in Singapore - R Statistics, R Machine Learning, R R is a popular programming language for data analytics, statistical analysis and This course will go through some advanced data analysis concepts techniques such as data extraction, data pre processing, data visualization, data modeling and  Advanced R Statistical Programming and Data Models - Springer
All errors and omissions excepted. M. Wiley, J.F. Wiley. Advanced R Statistical Programming and Data Models. Analysis, Machine Learning, and Visualization. Top 7 Online Data Science Courses for 2019 - Learn Data Science
Included is a learning guide and syllabus to help you learn data science this year . R Programming; Getting and Cleaning Data; Exploratory Data Analysis Statistical Inference; Regression Models; Practical Machine Learning . way to advanced data manipulation features, visualization, and machine learning libraries. Advanced R Statistical Programming and Data Models - Springer
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R is an open source programming language and software R's greatest asset is its wide variety of packages for statistical and graphical modeling. tools for advanced fields like data science, artificial intelligence, machine learning etc. Each has its own analysis, visualization, machine learning and data  Hands-on Machine Learning with R - Bradley Boehmke
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R is a programming language which can be as useful as you want it to for multiple purposes such as statistical analysis, data visualization, Once, you are done splitting the data into training and test sets, You . data.table- provides fast reading of large files; rpart and caret- for machine learning models. New York Open Statistical Programming Meetup (New York, NY
Meet with other users of the open-source programming language R. only on R Learning Path: From beginner to expert in R in 7 steps - KDnuggets
Learning R can be tricky, especially if you have no programming experience or are with point-and-click statistical software versus a real programming language. the latest changes in the language that might appeal to more advanced R users. 5.1 Importing Data; 5.2 Data Manipulation; 5.3 Data Visualization; 5.4 The  What is a good book on learning R with examples? - Quora
One book I enjoyed reading is the combination of machine learning and R. 7- if you want some general data analysis / processing / mining R book try : on R programming, statistics and visualization. by Alket Cecaj on Algorithms and Data Fusion R for Everyone: Advanced Analytics and Graphics by Jared P. Lander. STHDA - Home
STHDA is a web site for statistical data analysis and data visualization using R software. It provides many R programming tutorials easy to follow.

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