Knowledge-based Mathematical Systems
Objectives: Modern machine learning techniques are proving to be extremely valuable for the analysis of data in computational biology problems. This course provides an introduction to many concepts, techniques, and algorithms in machine learning such as classification and linear regression and ending up with more recent topics such as support vector machines. The students will learn the fundamental concepts and modern machine learning methods as well as a more formal understanding. The underlying theme in the course is statistical inference as it provides the foundation for most of the methods covered. The students apply the knowledge on examples from biological data and techniques considering real biological examples.
Module 1. Introduction
Module 2. Unsupervised and Reinforced Learning
Module 3. Supervised and Reinforced Learning
Module 4. Kernel methods in system identification
Previous Courses: Otto-von-Guericke-Universität Magdeburg (Winter 2016)
Next Course: Otto-von-Guericke-Universität Magdeburg (Winter 2017)