Irizarry, Rafael A., <br/><br/>
Introduction to data science :  data analysis and prediction algorithms with R / 
Rafael A. Irizarry. 
 - xxx, 713 pages :  illustrations ;  26 cm 
<br/><br/>Installing R and RStudio -- Getting started with R and RStudio -- R Basics -- Programming basics -- The tidyverse -- Importing data -- Introduction to data visualization -- ggplot2 -- Visualizing data distributions -- Data visualization in practice -- Data visualization principles -- Robust summaries -- Introduction to statistics with R -- Probability -- Random variables -- Statistical inference -- Statistical models -- Regression -- Linear models -- Association is not causation -- Introduction to data wrangling -- Reshaping data -- Joining tables -- Web scraping -- String processing -- Parsing dates and times -- Text mining -- Introduction to machine learning -- Smoothing -- Cross validation -- The caret package -- Examples of algorithms -- Machine learning in practice -- Large datasets -- Clustering -- Introduction to productivty tools -- Accessing the terminal and installing Git -- Organizing with Unix -- Git and GitHub -- Reproducible projects with RStudio and R markdown. 
<br/><br/> 'The book begins by going over the basics of R and the tidyverse. You learn R throughout the book, but in the first part we go over the building blocks needed to keep learning during the rest of the book'-- 
<br/><br/><label>ISBN: </label>9780367357986  RM419.19 (PTSL) 
<br/><br/><label>Subjects--Topical Terms: </label><br/>R (Computer program language)<br/>Information visualization.<br/>Data mining.<br/>Statistics--Data processing.<br/>Probabilities--Data processing.<br/>Computer algorithms.<br/>Quantitative research.