Exercise sessions
The material include a relatively rich set of problems. We list a few of them as recommended, but we encourage you to read and reflect upon all problems (even if you do not solve them).
# Topic Material Recommended problems Additional problems
L1
Probabilistic modelling (pp)
Session1.pdf
Download Session1.pdf 1.1, 1.3, 1.4, 1.9
1.2, 1.10
L2
Bayesian linear regression (pp)
Session2.pdf
Download Session2.pdf 2.7, 2.8, 2.9, 2.1, 2.3
L3
Bayesian linear regression (c)
Session 3.ipynb
Links to an external site.
Session 3 (Google Colab)
Links to an external site.
Session 3 (Binder)
Links to an external site.
Session 3.html
Links to an external site.
Session3.pdf
Download Session3.pdf
Session3-code.zip
Download Session3-code.zip
3.1, 3.2
3.3
L4
Bayesian networks (pp)
Session4.pdf
Download Session4.pdf 4.1, 4.4, 4.5, 4.7, 4.8
4.2, 4.3, 4.6, 4.9
L5
Monte Carlo methods (pp/c)
Session5.pdf
Download Session5.pdf 5.1, 5.2, 5.4, 5.5 5.3, 5.6
L6
Message passing (pp)
Session6.pdf
Download Session6.pdf 6.2, 6.3
L7
Message passing (pp/c)
Session7.pdf
Download Session7.pdf
kf-example-data.csv
Download kf-example-data.csv
7.1., 7.2
7.3
L8 Gaussian processes (c) (only 1RT003)
Session8.ipynb
Download Session8.ipynb
Session 8 (Colab)
Links to an external site.
Session 8 (Solutions)
Links to an external site.
Session 8 (Binder)
Links to an external site.
8.1, 8.2, 8.3 8.4
L9 Gaussian processes (c) (only 1RT003)
Session9.ipynb
Download Session9.ipynb
Session 9 (Colab)
Links to an external site.
Session 9 (Solutions)
Links to an external site.
Session 9 (binder)
Links to an external site.
9.1, 9.2
9.3, 9.4
L10 Variational inference (pp/c) (only 1RT003) Session10.pdf
Download Session10.pdf
L11
Unsupervised learning (c)
Session11.ipynb
Links to an external site.
Session11 (Google Colab)
Links to an external site.
Session 11 (Binder)
Links to an external site.
Session11.html
Links to an external site.
11.1, 11.3
11.2
Exercise session 8, 9, and 10 only covers material related to the course content 1RT003. Note that in the schedule the lectures are numbered according to the table above, also for 1RT705.
pp = pen and paper, c = computer