Machine Learning (3cr)

Objective

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

Content

Basics of machine learning:
Minimization by gradient descent
Linear regression
Logistic regression
Neural networks

Qualifications

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

Assessment criteria, satisfactory (1)

The student knows and understands the basic concepts and methods of mathematics of machine learning to the extent that he/she is able to solve problems given in the course material independently but utilizing the material directly.

Assessment criteria, good (3)

The student is familiar with the concepts and methods of machine learning, and is able to apply them to different types of problems given in the course material and also outside of it. The student is able to combine the accumulated knowledge and skills with previous experiences in the subject.

Assessment criteria, excellent (5)

The student is able to describe the concepts and methods of machine learning flawlessly, and he/she is able to apply them to a variety of different problems that can be out of scope of the course material. The student has demonstrated creativity and innovation, and is able to find new meanings when applying what they have learned

Materials

Lecture material and demonstrations