Introduction to Machine Learning in R

Monday 9 December 2024, 1:00 pm - 5:00 pm (AEDT), Online

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Information for the workshop

During the workshop we will provide access to virtual machines will all packages and software preinstalled. These will only during the workshop.

For after the workshop

If you like to continue after the workshop, you’ll need to setup the following software and libraries into your own computer.

Download R and R Studio

  1. Go to the CRAN website and follow the instructions to download and install R.
  2. Download and install RStudio.

Installing additional packages

Open RStudio and install the following packages.

## To install needed CRAN packages:
install.packages("tidyverse")
install.packages("GGally")
install.packages("caret")
install.packages("gmodels")
install.packages("rpart")
install.packages("rpart.plot")
install.packages("dendextend")
install.packages("randomForest")
install.packages("mlr3")
install.packages("devtools")
install.packages("klaR")
install.packages("kernlab")
install.packages("ggbiplot")

## To install needed Bioconductor packages:
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install()
BiocManager::install(c("limma", "edgeR"))

In case you encounter issues with ggbiplot, please have a look at this GitHub issue.

Load them to make sure they were successfully installed.

# Load packages
library(ggbiplot)

library(tidyverse) # working with data frames, plotting
library(GGally)
library(caret)
library(gmodels)
library(rpart)
library(rpart.plot)
library(randomForest)

library(dendextend)
library(mlr3)


library(edgeR)      # cpm, etc -- RNA-Seq normalization
library(limma)      # lmFit, etc -- fitting many models