As mentioned during the introductory sessions, there will be no scheduled classes or lectures for this course. Instead, you are welcome to attend office hours if you have any questions or need assistance. Office hours are held on Wednesdays, 11-12, in room D-334.

For general course information, please refer to the introductory slides provided at the beginning of the course. The grading breakdown is detailed on slide 50. Note that there will be no in-class quizzes. Instead, homework assignments will constitute a total of 20 points, but any points exceeding 10 will not be counted toward your final grade.

You can track all course activities, including lab assignments and homework deadlines, through the course calendar. To access the English version of the course information, please switch to the "EN" sheet in the Excel document.

The course calendar also lists the lecture topics, which you can study using the materials in the "Lecture" folder. For each lecture, there is a corresponding exercise available in the "Exercise" folder to reinforce your understanding. Additionally, exams from previous years can be found in the "Exam" folder for your reference.

While the video lectures are delivered in Croatian, you can use YouTube's auto-translated captions feature, which works reasonably well for English. If this is helpful for you, the links to the video lectures are available here.

The introductory lecture for Machine Learning 1 begins on Monday, September 30, with classes at 16:00 in A211.

All four lab assignments are published in the course repository. The deadlines for each lab assignment are listed at the top of each notebook.

Also, activities for laboratory exercises are open on Moodle. You can find the entire schedule and deadlines for all activities in the course calendar (EN sheet).