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 run any of the materials locally on your own machine, you will need the following:

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

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", "distill", "gapminder", 
    "GGally", "gganimate", "ggiraph", "ggdendro", "ggdist", "ggforce",
    "ggplot2movies", "ggrepel", "ggridges", "ggthemes", "gifski", "glue",
    "knitr", "learnr", "naniar", "margins", "MASS", "Matrix",
    "nycflights13", "palmerpenguins", "patchwork", "rmarkdown", "rnaturalearth",
    "scales", "sf", "shinyjs", "tidyverse", "transformr", "umap",
    "xaringan"
  )
)

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

Reuse

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Any computer code (R, HTML, CSS, etc.) in slides and worksheets, including in slide and worksheet sources, is also licensed under MIT. Note that figures in slides may be pulled in from external sources and may be licensed under different terms. For such images, image credits are available in the slide notes, accessible via pressing the letter ‘p’.