Schedule

How to get the PDF version of slides

In order to print the PDF, please append “?print-pdf” after the slide URL. For example, the URL to the week 0 lecture slide is “https://emitanaka.org/iml/lectures/lecture-00.html”. You can access the PDF print ready version as “https://emitanaka.org/iml/lectures/lecture-00.html?print-pdf” then print with Google Chrome as PDF (press control/command P).

How to keep a local copy of the HTML slides

All materials to build the slides can be found in the repo here. You can download this repo by clicking here, then unzip and open HTML lecture slide under the “lectures” folder. If you are curious about how the slide was made, check out the .qmd files.


Week Slides Topic Readings
0 Unit Information
1 Overview Chapter 2
2 A:
B: 		Regression: (A) non-parametric and (B) variable selection Chapter 6.1 and 7.1-7.4
3 A:
B: 		Resampling (A) and Regularisation (B) Chapter 5 and Chapter 6.2
4 A:
B: 		Logistic regression (A) and Discriminant analysis (B) Chapter 4.1-4.4
5 Decision trees Chapter 8.1
6 Tree ensemble methods Chapter 8.2
Midsemester Break (1 week)
7 \(k\)-nearest neighbours Chapter 3.5
8 Dimension reduction Chapter 12.2
9 Clustering Chapter 12.4
10 Support vector machines Chapter 9
11 Neural network I Chapter 10
12 A:
B: 		Neural network II Chapter 10

Acknowledgement

Thanks to Di and Ruben for their past teaching materials.

Resources