Introduction to Machine Learning - Interactive Tutorials

This repository contains the learnr tutorials for the lecture "Introduction to machine learning".

Each day is treated interactively in form of a Shiny App.

Run Locally

To run a tutorial locally the only thing you have to do is to run rmarkdown::run("tutorial.Rmd") of the specific day. For instance, to run day 1 you just have to call:

rmarkdown::run("01-intro/01_tutorial.Rmd")

NOTE: It seems that the app is not correctly loaded when calling run from the terminal. Opening the tutorial.Rmd in RStudio and clicking the Run document will properly build the app.

NOTE: learnr saves the state of all tutorials in file.path(rappdirs::user_data_dir(), "R", "learnr", "tutorial", "storage"), if you are developing, delete this every time before you re-run the app for testing: Just do unlink(file.path(rappdirs::user_data_dir(), "R", "learnr", "tutorial", "storage")).

Run on shinyapps.io

Check results

Since lreanr passes the defined objects from the student directly as R environment it is possible to use any checking or testing mechanism we like. There are two packages that are very suitable for that task:

• testthat: http://testthat.r-lib.org/
• testwhat: https://datacamp.github.io/testwhat/index.html

testthat

Testing your code can be painful and tedious, but it greatly increases the quality of your code. testthat tries to make testing as fun as possible, so that you get a visceral satisfaction from writing tests.

testwhat

Verify R code submissions and auto-generate meaningful feedback messages. Originally developed for R exercises on DataCamp for so-called Submission Correctness Tests, but can also be used independently.

Using testwhat might be very useful in terms of parsing the submitted and solution code and checking multiple things like objects, functions, function definitions, and so on.