Edistyneet koneoppimisen menetelmät (5 op)

Arviointiasteikko

H-5

Sisällön jaksotus

- Natural language processing machine learning models
- Advanced specialized machine learning algorithms
- Machine learning model optimization tools
- Error metrics and ML model performance evaluation
- Use of suitable tools (e.g., a high-level ML application programming interface, like scikit-learn and TensorFlow) for building solutions

Tavoitteet

- 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

Aika ja paikka

Lapland University of Applied Sciences, Rantavitikka Campus, 13.1.2025 - 15.5.2025.

Opetusmenetelmät

Lectures, workshops, examples, exercises and self-supervised work.

Tenttien ajankohdat ja uusintamahdollisuudet

The course will be graded based on personal work and exercises.

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.

Esitietovaatimukset

Introduction to Machine Learning Methods