Statistical learning with R: 2019 edition
Here are the homeworks for the Machine Learning course, 2019 edition. If you have not played with R yet, the notes I have attached to the introductory Lab might be of help.
If you attended the class, you probably know what to do with the next posts. After you have ran each demo, answer the questions provided in the demo itself. Add whatever is necessary (screenshots, code, text, links) to motivate your answers and convince me you actually ran the demos and understood their contents. Finally send me everything in a pdf file.
As some of the scripts look for data in the current directory, first of all change the working directory to the one of the source files. To run each demo, just open the R file you will find in each post with the source command in R, for example:
source("./demofilename.R", print.eval = TRUE)
You can find the package containing all of the source and data files you need for your homework here. Remember that while you will not be asked to add much new code to the demos, you should at least be able to understand what the existing code does and modify some parameters to produce different results.