AIML 429 (2024) - Home Page

AIML 429: Probabilistic Machine Learning.

Lectures and tutorials in T1, 2024:

  • Tuesdays and Thursdays, 10am in Murphy LT102, Kelburn
(Videos available via "Nuku" on left side-bar, but I'd prefer you show up in class)
  • Tutorials are Tuesdays from 4pm in Kirk204

Because the recordings were very poor (both sound and vision) before the room got "fixed", here are the corresponding lectures (first 3 weeks) as they were presented in 2023:

Marcus's Office Hours are Tuesdays from 3-4pm , in CO337 (i.e. just prior to Tutorial -- if it's appropriate, consider asking your question in the tut so that others can hear the answer too). In-person is best. There's also zoom by arrangement.

Useful Texts

Materials

NotesAndQueries.pdf these are the lecture notes, as a single document.
May change as the course proceeds.
PortfolioTasks.pdf these are the portfolio tasks. Datasets: Meal-Shirt-Wine.csv and prey-pet-temp.csv
Notebooks Some ipython notebooks get used as demonstrations in class.

Notes and Queries is the base material for lectures. Portfolio Tasks is the set of assignment questions that you can collate. There's also a diff.pdf version if you care about seeing the `changes` made to the starting version.

Updated assessment structure:

item # due worth
Portfolio Part 1 Friday 19th April (end of week 6) 25%
10-min in-person Q&A mutual arrangement in weeks 7-8 (22 April - 3 May) 20%
Portfolio Part 2 Friday 31st May, the last day of lectures 25%
1 hour test in the exam period (date t.b.a.) 30%

I Attachment Action Size Date Who Comment
NotesAndQueries.pdfpdf NotesAndQueries.pdf manage 14 MB 21 Mar 2024 - 11:07 Main.marcus novc
OneChapter.pdfpdf OneChapter.pdf manage 983 K 21 Mar 2024 - 17:40 Main.marcus  
PortfolioTasks.pdfpdf PortfolioTasks.pdf manage 245 K 26 Mar 2024 - 13:15 Main.marcus  
diff.pdfpdf diff.pdf manage 14 MB 26 Feb 2024 - 15:59 Main.marcus