Workshop 2

In this workshop we are going to explore the nomad data (cities) using unsupervised ML techniques. We used the data in a research project some years ago and you can check out a conference presentation below:

Things to do!

You will find the data for today’s session here: https://sds-aau.github.io/SDS-master/M1/data/cities.csv Use the template from the Penguin analysis with UML and build a notebook that covers following steps:

• Stratup
  • Load up and explore the data (a bit)
  • Clean up if you thing you neeed to
  • Select the nummerical variables to be used for UML
  • Preprocess the data for UML
• Dimensionality reduction
  • Use PCA for dimensionality reduction
  • Explore variable loading
  • Plot 1. vs 2. component
  • If you want, use another algorithm for the same steps and compare results
• Clustering
  • Perform a clustering on the reduced data
  • Plot the clusters into the above visualization
  • Explore the results (clusters vs components / clusters vs aggregated variables of interest)

Schedule for the workshop

In class Notebooks

• R team :::: HERE ::::
• Py team (coming…I know I’m late)

Videos