Machine learning methodsLaajuus (5 cr)

Objective

You are familiar with various machine learning methods.
You understand what supervised learning means.
You understand what unsupervised learning means.
You understand the principles of linear regression.
You understand how logistic regression is used in classification.
You can communicate using machine learning terminology.
You are familiar with the basics of neural networks.
You understand the principles of decision trees and random forests.

Content

What are the different methods of machine learning?
How are machine learning models implemented through programming?
How is the appropriate machine learning method chosen for a specific application?
How are different libraries for machine learning used in programming?

Qualifications

Skills in machine learning mathematics, programming, and data analysis are required.

Accomplishment methods

a. use professional vocabulary systematically.
b. look for information in the key information sources of the field.
c. identify interrelated tasks.
d. work together with customers/clients, users and target groups.
e. use the key models, methods, software and techniques of the professional field.
f. work as team members in a goal-oriented way.
g. justify their actions according to the ethical principles of the professional field.