I've recently been delving into R—mostly messing around with linear models and regularization, but also generally figuring out the language. Here are some resources that I found useful while learning.

*June 16, 2019 - 20:53:27*

Hope someone can find this useful!

### Linear models, regularization and `glmnet`

*Rose Martin (DataQuest)*

Using Linear Regression for Predictive Modeling in R*Justin Post (Statistics Dept., NC State University)*

LASSO, Ridge, and Elastic Net*J. Thompson*

Regularized Linear Models (in R)*Trevor Hastie, Junyang Qian (Stanford University)*

`glmnet`

vignette*Ricardo Carvalho*

How to use Ridge Regression and Lasso in R*Michał Oleszak (DataCamp)*

Regularization: Ridge, Lasso and Elastic Net

### Explanatory analysis and correlation plots

*Statistical Tools for High-throughput Data Analysis*

Visualize correlation matrix using correlogram*CRAN*

An Introduction to`corrplot`

Package*melike (RPubs)*

Correlation Plots Using`corrplot`

Package*Kyle Thomas*

R Exploratory Analysis with`ggpairs`

*Dr. Simon Jackson*

Visualising Residuals*The Minitab Blog*

Why You Need to Check Your Residual Plots for Regression Analysis*Adam Medcalf (Dabbling with Data)*

My favourite R package for: summarising data*Dominic Comtois (CRAN)*

Introduction to`summarytools`

*Ando Saabas (DataDive)*

Selecting good features – Part II: linear models and regularization (`python`

)*GGobi foundation for interactive and dynamic graphics*

GGally - Extension to`ggplot2`

*François Briatte*

`ggcorr`

: correlation matrixes with`ggplot2`

*Akshay Mahale (DataScience+)*

Regression Models in R: Story of`pairs`

,`ggpairs`

, and the linear regression

### RStudio, R-Markdown and notebooks

*Anaconda*

Using the R programming language in Jupyter Notebook*GitHub Issue (*`rstudio/rmarkdown#1020`

)

Display R notebooks on github*RStudio*

Creating Custom Themes for RStudio*Allen Bargi*

Color scheme (tmTheme) editor*Andrew Zieffler (DataDreaming)*

R Markdown Theme Gallery