Opinto-opas

Tavoitteet

Students will be competent in using the mathematical methods described in the course contents to solve practical mathematical problems.

Sisältö

Minimization by gradient descent
Linear regression
Logistic regression
Neural networks

Oppimateriaalit

ilmoitetaan opintojakson alussa

Opetusmenetelmät

luentoja ja laskuharjoituksia

Opiskelijan ajankäyttö ja kuormitus

81h

Lisätietoja opiskelijoille

Tunneilla 80% läsnäolovaatimus

Arviointiasteikko

1-5

Arviointikriteerit, tyydyttävä (1)

satisfactory (1-2): The student knows and understands to a satisfactory extent the basic concepts and methods discussed in the course, and is able to apply them to usual problems.

Arviointikriteerit, hyvä (3)

good (3-4): The student is familiar with the concepts and methods discussed in the course, and is able to apply them to different types of problems. The student is able to combine the accumulated knowledge and skills with previous experiences in the subject.

Arviointikriteerit, kiitettävä (5)

excellent (5): The student is familiar with the concepts and methods discussed in the course, and is able to apply them to a variety of different problems. The student has demonstrated creativity and innovation, and is able to find new meanings when applying what they have learned

Arviointimenetelmät ja arvioinnin perusteet

harjoitustyöt

Esitietovaatimukset

Algebra and geometry, Vectors and matrices, Differential and integral calculus, Automation technology mathematics