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).
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.
|Regression: (A) non-parametric and (B) variable selection||Chapter 6.1 and 7.1-7.4|
|Resampling (A) and Regularisation (B)||Chapter 5 and Chapter 6.2|
|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|
|10||Support vector machines||Chapter 9|
|11||Neural network I||Chapter 10|
|Neural network II||Chapter 10|
Thanks to Di and Ruben for their past teaching materials.