Edistyneet koneoppimisen menetelmätLaajuus (5 op)

Osaamistavoitteet

- Knowledge and skills to understand beyond-basic contemporary machine learning (ML) models and methods, and to choose and apply them in a principled and sound way
- Abilities for understanding connections to, and dependencies between, model/method properties and timely topics (e.g., ethics, sustainability, explainability).
- Abilities to solve a computational problem via machine learning without using a high-level ML application programming interface

Sisältö

- Theory and practice of the beyond-basic contemporary machine learning (ML) models and methods
- Use of suitable tools (e.g., an ML application programming interface enabling both high and low level expression) for building solutions

Esitietovaatimukset

Introduction to Machine Learning Methods

Arviointikriteerit, tyydyttävä (1)

Grade 1: The student knows the theory on the considered ML models and methods. The student is able to solve beyond-basic contemporary ML problems, using the considered tools.

Arviointikriteerit, hyvä (3)

Grade 3: The student understand the theory on the considered ML models and methods. The student is able to solve a variety of beyond-basic contemporary ML problems, using the considered tools, suitably.

Arviointikriteerit, kiitettävä (5)

Grade 5: The student understand the theory on the considered ML models and methods. The student is able to solve a variety of beyond-basic contemporary ML problems, using the considered tools, most suitably.