Study Guide

Objective

Student understands the principles of machine learning and neural networks methods. The student can apply the machine learning methods in applications of automation technology.

Content

- Introduction to artificial intelligence and machine learning
- Linear regression
- Logistic regression
- Neural networks
- Clustering
- Main component analysis
- Machine learning applications in industrial automation and technology
- Machine learning in machine vision systems

Materials

to be announced

Teaching methods

lectures and exercises

Student workload

135 h

Evaluation scale

1-5

Assessment criteria, satisfactory (1)

Student knows the concept of machine learning. Student can apply basic machine learning methods.

Assessment criteria, good (3)

Student understands the principles of machine learning and neural networks methods. Student can apply various machine learning methods.

Assessment criteria, excellent (5)

Student understands the principles of machine learning and neural networks methods. Student can choose the best machine learning method for the application and can apply it.

Assessment methods and criteria

execises

Qualifications

- Linear algebra and matrix calculation
- Basics of programming