Plans for week 47, November 21-25

Hi all, this is sadly our last week and after our discussions on support vector machines last week (see lecture notes and videos) we are now ready to wrap up the semester by scratching the surface of unsupervised learning methods. We will focus on the standard principal component analysis (PCA) method (which allows us to revisit the correlation and covariance matrices and the SVD) and one of the simplest (and very intuitive ) clustering methods, namely what is called k-means clustering. You will find all this wonderful material, plus a summary and more by jumping into the lecture slides for week 47, see for example https://compphysics.github.io/MachineLearning/doc/pub/week47/html/week47-reveal.html.

Else, see also

  - Geron's chapter 9 on PCA

  - Hastie et al Chapter 13 (sections 13.1-13.2 are the most relevant ones)

- and excellent videos at:

  - We recommend highly the video on PCA by Brunton and Kutz at http://www.databookuw.com/page-2/page-4/, see in particular the video of section 1.5. 

  - And another good video on PCA is at https://www.youtube.com/watch?v=FgakZw6K1QQ

  - k-means clustering video at https://www.youtube.com/watch?v=4b5d3muPQmA

Look forward to see you again and best wishes with project 3. This week is also our last lab week, but we may organize an additional lab session (digital) during week 48 and possibly week 49 (digital).

Best wishes to you all,

Morten et al