Exercise sessions

During the course, 10 exercise sessions are offered. For most topics, there is both a pen-and-paper session (pp) and a computer session (c). Each session is offered at two different time slots in the schedule. We hope that the students will be evenly distributed among the sessions, but you can choose which session to attend. There are two exercise sessions in parallel, split between two teaching assistants: one on campus and one on zoom. Use the course zoom link to reach the zoom sessions.

During each exercise session, the teacher will present a summary of the material covering the specific topic, after which you are expected to work on the problems on your own. We recommend attempting to solve the problems beforehand, and taking the opportunity to ask questions and discuss the problems with the teacher and your fellow students during the exercise sessions. A few of the problems are listed as recommended, but we encourage you to read and reflect upon all problems (even if you do not solve them).

Use this document Links to an external site. to queue for help during the zoom exercise sessions.

 

# Topic Material Recommended problems Additional problems
 1. Linear Regression (pp)

Session1.pdf Links to an external site.

1, 2, 3 4, 5
2. Linear Regression (c)

Notebook Links to an external site.

Solutions Links to an external site.

Open in colab Links to an external site.

1, 2, 3, 4 5
3. Logistic Regression, LDA, QDA, kNN (pp)

Session3.pdf Links to an external site.

Session3 - Recap + solutions Download Session3 - Recap + solutions

1, 2, 3, 5 4, 6, 7
4. Logistic Regression, LDA, QDA, kNN (c)

Notebook Links to an external site.

Solutions Links to an external site. 

Open in colab Links to an external site.

Ex. 4.1 from the live coding session

1, 2, 3, 4 5
5. Bias and variance, model selection, cross validation (pp)

Session5.pdf Links to an external site.

Session5 - Recap + solutions

1, 2, 3, 4 5, 6
6. Bias and variance, model selection, cross validation (c)

Notebook Links to an external site.

Solutions Links to an external site.

Open in colab Links to an external site.

1, 2, 3 4
7. Tree-based methods (pp) Session7.pdf Links to an external site.

1, 2, 3, 4
8. Tree-based methods (c)

Notebook Links to an external site.

Solutions Links to an external site.

Open in colab Links to an external site.

Extra material on bootstrapping

1, 2 3
9. Boosting (c)

Notebook Links to an external site.

Solutions Links to an external site.

Open in colab Links to an external site.

1, 2, 3 4, 5
10. Neural Networks (pp)

Session10.pdf Links to an external site.

Detailed solutions to 2 & 4 Download Detailed solutions to 2 & 4

Session10 Recap + Solutions

1, 2, 3, 4

pp = pen and paper, c = computer