General information

The Bachelor lecture Introduction to Machine Learning is one of the compulsory modules for students of ET and NES

Lecture and exercise dates and materials

Lectures and exercises are organized in separate Moodle rooms, where the semester-accompanying materials and dates are announced.
Registration takes place via LSF

Lecture content

Fundamentals of machine learning
Regression and classification
Basic concepts of statistics and probability
Supervised learning

• Naive Bayes
• Linear Discriminant
• Instance-based learning methods
• Linear and polynomial regression
• Neural networks
• Deep Learning

Ensemble methods
Implementation of machine learning methods with the help of Matlab
Case studies from technical applications