Zima 2026 / Fall 2026
Basic information
| 2-INF-150: Strojové učenie / Machine Learning Zima 2026 / Fall 2026 Basic information |
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Contact | Basic information | Homeworks | Exams | Handouts | Previous semesters
| Syllabus | ||
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| Supervised machine learning (linear and generalized linear regression, neural networks, classification with support vector machines, kernel methods, discrete classifiers). Machine learning theory (statistical model of machine learning, bias-variance trade-off, overfitting and underfitting, PAC learning, VC dimension estimates). Unsupervised machine learning (clustering, self-organizing maps, principal component analysis). Reinforcement learning. Ensemble learning (bagging, boosting). | ||
| Recommended literature | ||
| The lectures will be loosely inspired by the recommended literature and will cover only some chapters. Lectures will be the primary source of information for the exam. | ||
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| Grading | ||
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Grade for the semester:
Grade for the semester: A: 90+, B: 80+, C: 70+, D: 60+, E: 50+ Everything you hand in must be your own work. We may ask you for a consultation to explain details of your work. If you are unable to explain details of your work, you may be subject to disciplinary penalties outlined below. Grade for the exam:
Written exam with 100 points maximum
The final grade is the lower of semester grade and exam grade.
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| Complaints about grades | ||
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All complaints about homework grades must be submitted
in writing within two weeks of the time when the graded solutions
are available, but no later than on the business day before the exam date.
By examining your solution in more detail, the grade can be increased
or decreased. Before submitting a claim, carefully read the
relevant materials.
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| AI Usage Policy | ||
Unless otherwise specified, you are allowed to use AI in the way analogous to discussions with your classmates. You are allowed to discuss the assignments with AI, but after such discussions you must discard all notes and you should wait for several hours before writing up your own solution without using the AI. In addition, you are allowed to use AI tools for grammar correction or syntax completion. Unless specified otherwise, do not use tools that would write significant portions of your text or your code. In all cases, it is mandatory to declare AI use and describe
how you used AI. | ||
| Academic Integrity | ||
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Copying homework assignments, projects and cheating on exams is a serious violation of academic integrity. Cheating on homework assignments and projects include copying work of somebody else (i.e. classmate, internet, literature) and handing the work under your name, allowing somebody else to copy your work, or excessive collaboration. Cheating on exam includes use of unauthorized devices, as well as communication with others during the exam. The standard penalty for cheating on homework assignment is a grade of -100%. Penalty for cheating on exam is Fx with no option of retaking the exam. Serious infraction will be reported to the faculty disciplinary committee. With respect to homeworks, we encourage discussion between
students and in groups. However, the solution you hand in must be
your own and described in your own words. To avoid problems, do
not keep any notes from such discussions and wait for several hours
after the discussion before writing up your own solution. If you choose
to discuss homeworks with you classmates, it is mandatory to declare
with whom you discussed your assignments and to what detail.
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