Online Read Ebook Advanced R Statistical
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
Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization
Ebook deutsch gratis download Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization English version
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).
R and Python machine learning and programming extensions
R and Python in SQL Server, with built-in data science modeling and machine learning algorithms for enterprise data analysis at scale.
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Learn Python and R for data science. Learn by coding and working with data in your browser. Build your portfolio with projects and become a data scientist.
18 New Must Read Books for Data Scientists on R and Python
Here is a list of books on doing machine learning / data science in R and This book introduces you to details of R programming environment such as data visualization, data manipulation, predictive modeling, but not in as much depth. probability, statistics, time series analysis, data pre-processing etc.
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.
Comprehensive Beginners Guide to Learn Data Visualization in R
It helps tremendously in doing any exploratory data analysis as well as create the common as well as advanced visualizations in R Programming. The founder of graphical methods in statistics is William Playfair. . If you like what you just read & want to continue your analytics learning, subscribe to our
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