Accesibility Adjustments

Choose the right accessibility profile for you
OFF ON
Highlight Links Highlights all the links on the site!
OFF ON
Pause Animations Animations will be paused on the site!
OFF ON
Dyslexia Font Dyslexia Font will be applied on the site!
OFF ON
Hide Images All images will be hidden on the site!
Choose the right accessibility profile for you
Adjust Font Sizing
Default
High Saturation
High Contrast
Light Contrast
Dark Contrast
Adjust Letter Spacing
Default
Adjust Line Height
Default
Speak Mode
Align Center
Align Left
Align Right

OSNOVI MAŠINSKOG UČENJA I VJEŠTAČKE INTELIGENCIJE


Semester: 1
ECTS: 5
Status: Obavezan
Lessons: 3+1+1
Double: Ne
ECTS catalogue
Learning outcomes:

After passing this exam, the student will be able to: Formulate a problem model they want to solve using machine learning techniques; Understand machine learning algorithms, their capabilities, and limitations in solving specific problems; Apply appropriate mathematical tools, algorithms, and machine learning techniques to real data and problem-solving, and adapt and modify them as needed; Describe and interpret the results of applying machine learning techniques; Understand the mathematical and theoretical concepts underlying machine learning algorithms; Model and simulate data and experiments necessary for the analysis, verification, and comparison of existing as well as modified or newly developed machine learning techniques.

Teaching staff

Name Lectures Exercises Laboratory
DANILO PLANINIĆ1x1
18B
1x1
18B
VESNA POPOVIĆ-BUGARIN3x1
18B
//