DSC 385

Data Exploration, Visualization, and Foundations of Unsupervised Learning

This is the home page for DSC 385, Data Exploration, Visualization, and Foundations of Unsupervised Learning.

Computing requirements

To complete assignments in this class, you will need the following:

A recent version of R, download from here.
A recent version of RStudio, download from here, OR a recent version of Positron, download from here.
The following R packages:
broom, cluster, colorspace, cowplot, gapminder, GGally, gganimate, ggiraph, ggdendro, ggdist, ggforce, ggplot2movies, ggrepel, ggridges, ggthemes, gifski, glue, knitr, learnr, naniar, margins, MASS, Matrix, nycflights13, palmerpenguins, patchwork, quarto, rmarkdown, rnaturalearth, rnaturalearthhires, Rtsne, scales, sf, sp, tidyverse, transformr, umap

You can install all required R packages at once by running the following code in the R command line:

# first run this command:
install.packages(
  c(
    "broom", "cluster", "colorspace", "cowplot", "gapminder", 
    "GGally", "gganimate", "ggiraph", "ggdendro", "ggdist", "ggforce",
    "ggplot2movies", "ggrepel", "ggridges", "ggthemes", "gifski", "glue",
    "knitr", "learnr", "naniar", "margins", "MASS", "Matrix",
    "nycflights13", "palmerpenguins", "patchwork", "quarto", "rmarkdown",
    "rnaturalearth", "Rtsne", "scales", "sf", "sp", "tidyverse",
    "transformr", "umap"
  )
)

# then run this command:
install.packages(
  "rnaturalearthhires", repos = "https://packages.ropensci.org", type = "source"
)