Dear students,
The second graded exercise will take place on May 24th, during the exercise session. We will start at 10:25 and the submission deadline is 12:00. You need to bring your own laptops, with all the packages installed (you needed to install them in the first exercise session from requirements.txt). Additionally, please make sure you have PyTorch installed (the framework we used in the CNN and UNet exercises.) You can test whether you have it by trying to import it in a Jupyter Notebook with the line:
import torch
In order to get settled in, please be in the classrooms by 10:15. The student-to-room distribution will be the same as the regular exercise sessions. Please bring your IDs for verification.
You are responsible for all the lecture content after Graded Exercise 1, up to (and including) this week's lecture on Dimensionality Reduction. We released another practice graded exercise which covers similar topics to what you have covered (under "Practice Graded Exercise").
Similarly to graded exercise 1, you will be able to use all the course materials (lecture notes, programming cheat sheets and previous exercise sessions). You are not allowed to use the internet except Moodle.
Reminder: For programming help, you can use Jupyter notebook. If you type func_name?? (for example: np.sum??) then Jupyter notebook will display a description of the function, its parameters and what it returns, and in some cases, examples. Try it out beforehand and make sure this works for you, as it may be useful during the exercise! You can also download the numpy and Python documentation and use those if that is easier for you. We will provide some documentation for PyTorch functions, if necessary.
Best,
Sena
